examples/panthera-intro.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data science intro with panthera\n",
    "## Clojure + Pandas + Numpy = 💖\n",
    "\n",
    "I'll show how it is possible to get the most out of the [Pandas](https://pandas.pydata.org/) & the Clojure ecosystem at the same time.\n",
    "\n",
    "This intro is based on this [Kaggle notebook](https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners) you can follow along with that if you come from the Python world.\n",
    "\n",
    "## Env setup\n",
    "\n",
    "The easiest way to go is the provided [Docker image](https://cloud.docker.com/u/alanmarazzi/repository/docker/alanmarazzi/panthera), but if you want to setup your machine just follow along.\n",
    "\n",
    "### System install\n",
    "\n",
    "If you want to install everything at the system level you should do something equivalent to what we do below:\n",
    "\n",
    "```bash\n",
    "sudo apt-get update\n",
    "sudo apt-get install libpython3.6-dev\n",
    "pip3 install numpy pandas\n",
    "```\n",
    "\n",
    "### conda\n",
    "\n",
    "To work within a conda environment just create a new one with:\n",
    "\n",
    "```bash\n",
    "conda create -n panthera python=3.6 numpy pandas\n",
    "conda activate panthera\n",
    "```\n",
    "Than start your REPL from the activated conda environment. This is the best way to install requirements for panthera because in the process you get MKL as well with Numpy.\n",
    "\n",
    "### Here\n",
    "\n",
    "Let's just add panthera to our classpath and we're good to go!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       ":ok"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(require '[clojupyter.misc.helper :as helper])\n",
    "(helper/add-dependencies '[panthera \"0.1-alpha.11\"])\n",
    ":ok"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now require panthera main API namespace and define a little helper to better inspect data-frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(require '[panthera.panthera :as pt])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/show"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(require '[clojupyter.display :as display])\n",
    "(require '[libpython-clj.python :as py])\n",
    "\n",
    "(defn show\n",
    "  [obj]\n",
    "  (display/html\n",
    "    (py/call-attr obj \"to_html\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nil"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(helper/add-dependencies '[metasoarous/oz \"1.5.4\"])\n",
    "(require '[oz.notebook.clojupyter :as oz])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A brief primer\n",
    "\n",
    "We will work with Pokemons! Datasets are available [here](https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners/data).\n",
    "\n",
    "We can read data into panthera from various formats, one of the most used is `read-csv`. Most panthera functions accept either a data-frame and/or a series as a first argument, one or more required arguments and then a map of options.\n",
    "\n",
    "To see which options are available you can check docs or even original [Pandas docs](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html#pandas.read_csv), just remember that if you pass keywords they'll be converted to Python automatically (for example `:index-col` becomes `index_col`), while if you pass strings you have to use its original name.\n",
    "\n",
    "Below as an example we `read-csv` our file, but we want to get only the first 10 rows, so we pass a map to the function like `{:nrows 10}`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Charmeleon</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>80</td>\n",
       "      <td>65</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Charizard</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Flying</td>\n",
       "      <td>78</td>\n",
       "      <td>84</td>\n",
       "      <td>78</td>\n",
       "      <td>109</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Mega Charizard X</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Dragon</td>\n",
       "      <td>78</td>\n",
       "      <td>130</td>\n",
       "      <td>111</td>\n",
       "      <td>130</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Mega Charizard Y</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Flying</td>\n",
       "      <td>78</td>\n",
       "      <td>104</td>\n",
       "      <td>78</td>\n",
       "      <td>159</td>\n",
       "      <td>115</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Squirtle</td>\n",
       "      <td>Water</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "      <td>65</td>\n",
       "      <td>50</td>\n",
       "      <td>64</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/read-csv \"../resources/pokemon.csv\" {:nrows 10}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The cool thing is that we can chain operations, the threading first macro is our friend!\n",
    "\n",
    "Below we read the whole csv, get the correlation matrix and then show it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>#</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.097712</td>\n",
       "      <td>0.102664</td>\n",
       "      <td>0.094691</td>\n",
       "      <td>0.089199</td>\n",
       "      <td>0.085596</td>\n",
       "      <td>0.012181</td>\n",
       "      <td>0.983428</td>\n",
       "      <td>0.154336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HP</th>\n",
       "      <td>0.097712</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.422386</td>\n",
       "      <td>0.239622</td>\n",
       "      <td>0.362380</td>\n",
       "      <td>0.378718</td>\n",
       "      <td>0.175952</td>\n",
       "      <td>0.058683</td>\n",
       "      <td>0.273620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Attack</th>\n",
       "      <td>0.102664</td>\n",
       "      <td>0.422386</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.438687</td>\n",
       "      <td>0.396362</td>\n",
       "      <td>0.263990</td>\n",
       "      <td>0.381240</td>\n",
       "      <td>0.051451</td>\n",
       "      <td>0.345408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Defense</th>\n",
       "      <td>0.094691</td>\n",
       "      <td>0.239622</td>\n",
       "      <td>0.438687</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.223549</td>\n",
       "      <td>0.510747</td>\n",
       "      <td>0.015227</td>\n",
       "      <td>0.042419</td>\n",
       "      <td>0.246377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sp. Atk</th>\n",
       "      <td>0.089199</td>\n",
       "      <td>0.362380</td>\n",
       "      <td>0.396362</td>\n",
       "      <td>0.223549</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.506121</td>\n",
       "      <td>0.473018</td>\n",
       "      <td>0.036437</td>\n",
       "      <td>0.448907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sp. Def</th>\n",
       "      <td>0.085596</td>\n",
       "      <td>0.378718</td>\n",
       "      <td>0.263990</td>\n",
       "      <td>0.510747</td>\n",
       "      <td>0.506121</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.259133</td>\n",
       "      <td>0.028486</td>\n",
       "      <td>0.363937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Speed</th>\n",
       "      <td>0.012181</td>\n",
       "      <td>0.175952</td>\n",
       "      <td>0.381240</td>\n",
       "      <td>0.015227</td>\n",
       "      <td>0.473018</td>\n",
       "      <td>0.259133</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.023121</td>\n",
       "      <td>0.326715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Generation</th>\n",
       "      <td>0.983428</td>\n",
       "      <td>0.058683</td>\n",
       "      <td>0.051451</td>\n",
       "      <td>0.042419</td>\n",
       "      <td>0.036437</td>\n",
       "      <td>0.028486</td>\n",
       "      <td>-0.023121</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.079794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Legendary</th>\n",
       "      <td>0.154336</td>\n",
       "      <td>0.273620</td>\n",
       "      <td>0.345408</td>\n",
       "      <td>0.246377</td>\n",
       "      <td>0.448907</td>\n",
       "      <td>0.363937</td>\n",
       "      <td>0.326715</td>\n",
       "      <td>0.079794</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> (pt/read-csv \"../resources/pokemon.csv\")\n",
    "    pt/corr\n",
    "    show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we'll be using `pokemon.csv` a lot, let's give it a name, `defonce` is great here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/pokemon"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defonce pokemon (pt/read-csv \"../resources/pokemon.csv\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see how plotting goes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/heatmap"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn heatmap \n",
    "  [data x y z]\n",
    "  {:data {:values data}\n",
    "   :width 500\n",
    "   :height 500\n",
    "   :encoding {:x {:field x\n",
    "                  :type \"nominal\"}\n",
    "              :y {:field y\n",
    "                  :type \"nominal\"}}\n",
    "   :layer [{:mark \"rect\"\n",
    "            :encoding {:color {:field z\n",
    "                               :type \"quantitative\"}}}\n",
    "           {:mark \"text\"\n",
    "            :encoding {:text \n",
    "                       {:field z\n",
    "                        :type \"quantitative\"\n",
    "                        :format \".2f\"}\n",
    "                       :color {:value \"white\"}}}]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div>\n",
       "  <div id='uuid-657a1268-3b10-4e2f-9c7d-61c244ec87ce'></div>\n",
       "  <script>\n",
       "  requirejs.config({\n",
       "    baseUrl: 'https://cdn.jsdelivr.net/npm/',\n",
       "    paths: {\n",
       "      'vega-embed':  'vega-embed@3?noext',\n",
       "      'vega-lib': 'vega-lib?noext',\n",
       "      'vega-lite': 'vega-lite@2?noext',\n",
       "      'vega': 'vega@3?noext'\n",
       "    }\n",
       "  });\n",
       "  require(['vega-embed'], function(vegaEmbed) {\n",
       "    let spec = {\"data\":{\"values\":[{\"index\":\"#\",\"variable\":\"#\",\"value\":1.0},{\"index\":\"HP\",\"variable\":\"#\",\"value\":0.0977123279793967},{\"index\":\"Attack\",\"variable\":\"#\",\"value\":0.10266440267663766},{\"index\":\"Defense\",\"variable\":\"#\",\"value\":0.0946906724168048},{\"index\":\"Sp. Atk\",\"variable\":\"#\",\"value\":0.0891993186423977},{\"index\":\"Sp. Def\",\"variable\":\"#\",\"value\":0.0855955930256973},{\"index\":\"Speed\",\"variable\":\"#\",\"value\":0.012180693402176939},{\"index\":\"Generation\",\"variable\":\"#\",\"value\":0.9834279016098693},{\"index\":\"Legendary\",\"variable\":\"#\",\"value\":0.15433554481371412},{\"index\":\"#\",\"variable\":\"HP\",\"value\":0.0977123279793967},{\"index\":\"HP\",\"variable\":\"HP\",\"value\":1.0},{\"index\":\"Attack\",\"variable\":\"HP\",\"value\":0.4223860287762238},{\"index\":\"Defense\",\"variable\":\"HP\",\"value\":0.2396223188467262},{\"index\":\"Sp. Atk\",\"variable\":\"HP\",\"value\":0.36237985740715783},{\"index\":\"Sp. Def\",\"variable\":\"HP\",\"value\":0.378718068612564},{\"index\":\"Speed\",\"variable\":\"HP\",\"value\":0.17595206187898574},{\"index\":\"Generation\",\"variable\":\"HP\",\"value\":0.058682508040739954},{\"index\":\"Legendary\",\"variable\":\"HP\",\"value\":0.27361955771295066},{\"index\":\"#\",\"variable\":\"Attack\",\"value\":0.10266440267663766},{\"index\":\"HP\",\"variable\":\"Attack\",\"value\":0.4223860287762238},{\"index\":\"Attack\",\"variable\":\"Attack\",\"value\":1.0},{\"index\":\"Defense\",\"variable\":\"Attack\",\"value\":0.4386870551184902},{\"index\":\"Sp. Atk\",\"variable\":\"Attack\",\"value\":0.39636175534923296},{\"index\":\"Sp. Def\",\"variable\":\"Attack\",\"value\":0.263989551101088},{\"index\":\"Speed\",\"variable\":\"Attack\",\"value\":0.3812397392410901},{\"index\":\"Generation\",\"variable\":\"Attack\",\"value\":0.05145133670846967},{\"index\":\"Legendary\",\"variable\":\"Attack\",\"value\":0.3454079755555302},{\"index\":\"#\",\"variable\":\"Defense\",\"value\":0.0946906724168048},{\"index\":\"HP\",\"variable\":\"Defense\",\"value\":0.2396223188467262},{\"index\":\"Attack\",\"variable\":\"Defense\",\"value\":0.4386870551184902},{\"index\":\"Defense\",\"variable\":\"Defense\",\"value\":1.0},{\"index\":\"Sp. Atk\",\"variable\":\"Defense\",\"value\":0.2235486094724222},{\"index\":\"Sp. Def\",\"variable\":\"Defense\",\"value\":0.5107465890885579},{\"index\":\"Speed\",\"variable\":\"Defense\",\"value\":0.01522659808859747},{\"index\":\"Generation\",\"variable\":\"Defense\",\"value\":0.04241856657677686},{\"index\":\"Legendary\",\"variable\":\"Defense\",\"value\":0.24637680045403393},{\"index\":\"#\",\"variable\":\"Sp. Atk\",\"value\":0.0891993186423977},{\"index\":\"HP\",\"variable\":\"Sp. Atk\",\"value\":0.36237985740715783},{\"index\":\"Attack\",\"variable\":\"Sp. Atk\",\"value\":0.39636175534923296},{\"index\":\"Defense\",\"variable\":\"Sp. Atk\",\"value\":0.2235486094724222},{\"index\":\"Sp. Atk\",\"variable\":\"Sp. Atk\",\"value\":1.0},{\"index\":\"Sp. Def\",\"variable\":\"Sp. Atk\",\"value\":0.5061214206155483},{\"index\":\"Speed\",\"variable\":\"Sp. Atk\",\"value\":0.4730178836686994},{\"index\":\"Generation\",\"variable\":\"Sp. Atk\",\"value\":0.03643682864867449},{\"index\":\"Legendary\",\"variable\":\"Sp. Atk\",\"value\":0.44890725643865526},{\"index\":\"#\",\"variable\":\"Sp. Def\",\"value\":0.0855955930256973},{\"index\":\"HP\",\"variable\":\"Sp. Def\",\"value\":0.378718068612564},{\"index\":\"Attack\",\"variable\":\"Sp. Def\",\"value\":0.263989551101088},{\"index\":\"Defense\",\"variable\":\"Sp. Def\",\"value\":0.5107465890885579},{\"index\":\"Sp. Atk\",\"variable\":\"Sp. Def\",\"value\":0.5061214206155483},{\"index\":\"Sp. Def\",\"variable\":\"Sp. Def\",\"value\":1.0},{\"index\":\"Speed\",\"variable\":\"Sp. Def\",\"value\":0.2591331139168082},{\"index\":\"Generation\",\"variable\":\"Sp. Def\",\"value\":0.028485991779451006},{\"index\":\"Legendary\",\"variable\":\"Sp. Def\",\"value\":0.3639371167456877},{\"index\":\"#\",\"variable\":\"Speed\",\"value\":0.012180693402176939},{\"index\":\"HP\",\"variable\":\"Speed\",\"value\":0.17595206187898574},{\"index\":\"Attack\",\"variable\":\"Speed\",\"value\":0.3812397392410901},{\"index\":\"Defense\",\"variable\":\"Speed\",\"value\":0.01522659808859747},{\"index\":\"Sp. Atk\",\"variable\":\"Speed\",\"value\":0.4730178836686994},{\"index\":\"Sp. Def\",\"variable\":\"Speed\",\"value\":0.2591331139168082},{\"index\":\"Speed\",\"variable\":\"Speed\",\"value\":1.0},{\"index\":\"Generation\",\"variable\":\"Speed\",\"value\":-0.023121060425896966},{\"index\":\"Legendary\",\"variable\":\"Speed\",\"value\":0.3267152948309066},{\"index\":\"#\",\"variable\":\"Generation\",\"value\":0.9834279016098693},{\"index\":\"HP\",\"variable\":\"Generation\",\"value\":0.058682508040739954},{\"index\":\"Attack\",\"variable\":\"Generation\",\"value\":0.05145133670846967},{\"index\":\"Defense\",\"variable\":\"Generation\",\"value\":0.04241856657677686},{\"index\":\"Sp. Atk\",\"variable\":\"Generation\",\"value\":0.03643682864867449},{\"index\":\"Sp. Def\",\"variable\":\"Generation\",\"value\":0.028485991779451006},{\"index\":\"Speed\",\"variable\":\"Generation\",\"value\":-0.023121060425896966},{\"index\":\"Generation\",\"variable\":\"Generation\",\"value\":1.0},{\"index\":\"Legendary\",\"variable\":\"Generation\",\"value\":0.07979359239925084},{\"index\":\"#\",\"variable\":\"Legendary\",\"value\":0.15433554481371412},{\"index\":\"HP\",\"variable\":\"Legendary\",\"value\":0.27361955771295066},{\"index\":\"Attack\",\"variable\":\"Legendary\",\"value\":0.3454079755555302},{\"index\":\"Defense\",\"variable\":\"Legendary\",\"value\":0.24637680045403393},{\"index\":\"Sp. Atk\",\"variable\":\"Legendary\",\"value\":0.44890725643865526},{\"index\":\"Sp. Def\",\"variable\":\"Legendary\",\"value\":0.3639371167456877},{\"index\":\"Speed\",\"variable\":\"Legendary\",\"value\":0.3267152948309066},{\"index\":\"Generation\",\"variable\":\"Legendary\",\"value\":0.07979359239925084},{\"index\":\"Legendary\",\"variable\":\"Legendary\",\"value\":1.0}]},\"width\":500,\"height\":500,\"encoding\":{\"x\":{\"field\":\"index\",\"type\":\"nominal\"},\"y\":{\"field\":\"variable\",\"type\":\"nominal\"}},\"layer\":[{\"mark\":\"rect\",\"encoding\":{\"color\":{\"field\":\"value\",\"type\":\"quantitative\"}}},{\"mark\":\"text\",\"encoding\":{\"text\":{\"field\":\"value\",\"type\":\"quantitative\",\"format\":\".2f\"},\"color\":{\"value\":\"white\"}}}]};\n",
       "    vegaEmbed('#uuid-657a1268-3b10-4e2f-9c7d-61c244ec87ce', spec, {defaultStyle:true}).catch(console.warn);\n",
       "    }, function(err) {\n",
       "    console.log('Failed to load');\n",
       "  });\n",
       "  </script>\n",
       "</div>\n",
       "  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    pt/corr\n",
    "    pt/reset-index\n",
    "    (pt/melt {:id-vars :index})\n",
    "    pt/->clj\n",
    "    (heatmap :index :variable :value)\n",
    "    oz/view!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What we did is plotting the heatmap of the correlation matrix shown above. Don't worry too much to all the steps we took, we'll be seeing all of them one by one later on!\n",
    "\n",
    "What if we already read our data but we want to see only some rows? We have the `head` function for that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/head pokemon))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Charmeleon</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>80</td>\n",
       "      <td>65</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Charizard</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Flying</td>\n",
       "      <td>78</td>\n",
       "      <td>84</td>\n",
       "      <td>78</td>\n",
       "      <td>109</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Mega Charizard X</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Dragon</td>\n",
       "      <td>78</td>\n",
       "      <td>130</td>\n",
       "      <td>111</td>\n",
       "      <td>130</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Mega Charizard Y</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Flying</td>\n",
       "      <td>78</td>\n",
       "      <td>104</td>\n",
       "      <td>78</td>\n",
       "      <td>159</td>\n",
       "      <td>115</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Squirtle</td>\n",
       "      <td>Water</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "      <td>65</td>\n",
       "      <td>50</td>\n",
       "      <td>64</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/head pokemon 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another nice thing we can do is to get columns names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['#', 'Name', 'Type 1', 'Type 2', 'HP', 'Attack', 'Defense', 'Sp. Atk',\n",
       "       'Sp. Def', 'Speed', 'Generation', 'Legendary'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/names pokemon)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now when you see an output as the above one, that means that the data we have is still in Python. That's ok if you keep working within panthera, but what if you want to do something with column names using Clojure?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"#\" \"Name\" \"Type 1\" \"Type 2\" \"HP\" \"Attack\" \"Defense\" \"Sp. Atk\" \"Sp. Def\" \"Speed\" \"Generation\" \"Legendary\"]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(vec (pt/names pokemon))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's it! Just call `vec`and now you have a nice Clojure vector that you can deal with.\n",
    "\n",
    "> N.B.: with many Python objects you can directly treat them as similar Clojure collections. For instance in this case we can do something like below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#\n",
      "Name\n",
      "Type 1\n",
      "Type 2\n",
      "HP\n",
      "Attack\n",
      "Defense\n",
      "Sp. Atk\n",
      "Sp. Def\n",
      "Speed\n",
      "Generation\n",
      "Legendary\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "nil"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(doseq [a (pt/names pokemon)] (println a))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Some plotting\n",
    "\n",
    "Plotting is nice to learn how to munge data: you get a fast visual feedback and usually results are nice to look at!\n",
    "\n",
    "Let's plot `Speed` and `Defense`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/line-plot"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn line-plot\n",
    "  [data x y & [color]]\n",
    "  (let [spec {:data {:values data}\n",
    "              :mark \"line\"\n",
    "              :width 600\n",
    "              :height 300\n",
    "              :encoding {:x {:field x\n",
    "                             :type \"quantitative\"}\n",
    "                         :y {:field y\n",
    "                             :type \"quantitative\"}\n",
    "                         :color {}}}]\n",
    "    (if color\n",
    "      (assoc-in spec [:encoding :color] {:field color\n",
    "                                         :type \"nominal\"})\n",
    "      (assoc-in spec [:encoding :color] {:value \"blue\"}))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div>\n",
       "  <div id='uuid-a08e6c7d-b6af-47ad-9206-8ef7fb14f9ed'></div>\n",
       "  <script>\n",
       "  requirejs.config({\n",
       "    baseUrl: 'https://cdn.jsdelivr.net/npm/',\n",
       "    paths: {\n",
       "      'vega-embed':  'vega-embed@3?noext',\n",
       "      'vega-lib': 'vega-lib?noext',\n",
       "      'vega-lite': 'vega-lite@2?noext',\n",
       "      'vega': 'vega@3?noext'\n",
       "    }\n",
       "  });\n",
       "  require(['vega-embed'], function(vegaEmbed) {\n",
       "    let spec = 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       "    vegaEmbed('#uuid-a08e6c7d-b6af-47ad-9206-8ef7fb14f9ed', spec, {defaultStyle:true}).catch(console.warn);\n",
       "    }, function(err) {\n",
       "    console.log('Failed to load');\n",
       "  });\n",
       "  </script>\n",
       "</div>\n",
       "  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols :# :Speed :Defense)\n",
    "    (pt/melt {:id-vars :#})\n",
    "    pt/->clj\n",
    "    (line-plot :# :value :variable)\n",
    "    oz/view!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the operation above:\n",
    "\n",
    "- `subset-cols`: we use this to, well, subset columns. We can choose N columns by label, we will get a 'new' data-frame with only the selected columns\n",
    "- `melt`: this transforms the data-frame from wide to long format (for more info about it see [further below](#reshape)\n",
    "- `->clj`: this turns data-frames and serieses to a Clojure vector of maps\n",
    "\n",
    "`subset-cols` is pretty straightforward:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Speed</th>\n",
       "      <th>Attack</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols :Speed :Attack) pt/head show)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Speed</th>\n",
       "      <th>Attack</th>\n",
       "      <th>HP</th>\n",
       "      <th>#</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>60</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>80</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65</td>\n",
       "      <td>52</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols :Speed :Attack :HP :#) pt/head show)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   #  Attack\n",
       "0  1      49\n",
       "1  2      62\n",
       "2  3      82\n",
       "3  4     100\n",
       "4  5      52"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols :# :Attack) pt/head)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`->clj` tries to understand what's the better way to transform panthera data structures to Clojure ones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{:speed 45} {:speed 60} {:speed 80} {:speed 80} {:speed 65}]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols :Speed) pt/head pt/->clj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{:speed 45, :hp 45} {:speed 60, :hp 60} {:speed 80, :hp 80} {:speed 80, :hp 80} {:speed 65, :hp 39}]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols :Speed :HP) pt/head pt/->clj)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we want to see what happens when we plot `Attack` vs `Defense`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/scatter"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn scatter\n",
    "  [data x y & [color]]\n",
    "  (let [spec {:data {:values data}\n",
    "              :mark \"point\"\n",
    "              :width 600\n",
    "              :height 300\n",
    "              :encoding {:x {:field x\n",
    "                             :type \"quantitative\"}\n",
    "                         :y {:field y\n",
    "                             :type \"quantitative\"}\n",
    "                         :color {}}}]\n",
    "    (if color\n",
    "      (assoc-in spec [:encoding :color] {:field color\n",
    "                                         :type \"nominal\"})\n",
    "      (assoc-in spec [:encoding :color] {:value \"dodgerblue\"}))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div>\n",
       "  <div id='uuid-91109735-b5ac-4859-a321-c1679d62e8aa'></div>\n",
       "  <script>\n",
       "  requirejs.config({\n",
       "    baseUrl: 'https://cdn.jsdelivr.net/npm/',\n",
       "    paths: {\n",
       "      'vega-embed':  'vega-embed@3?noext',\n",
       "      'vega-lib': 'vega-lib?noext',\n",
       "      'vega-lite': 'vega-lite@2?noext',\n",
       "      'vega': 'vega@3?noext'\n",
       "    }\n",
       "  });\n",
       "  require(['vega-embed'], function(vegaEmbed) {\n",
       "    let spec = 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       "    vegaEmbed('#uuid-91109735-b5ac-4859-a321-c1679d62e8aa', spec, {defaultStyle:true}).catch(console.warn);\n",
       "    }, function(err) {\n",
       "    console.log('Failed to load');\n",
       "  });\n",
       "  </script>\n",
       "</div>\n",
       "  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols :Attack :Defense)\n",
    "    pt/->clj\n",
    "    (scatter :attack :defense)\n",
    "    oz/view!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now the `Speed` histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/hist"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn hist\n",
    "  [data x & [color]]\n",
    "  (let [spec {:data {:values data}\n",
    "              :mark \"bar\"\n",
    "              :width 600\n",
    "              :height 300\n",
    "              :encoding {:x {:field x\n",
    "                             :bin {:maxbins 50}\n",
    "                             :type \"quantitative\"}\n",
    "                         :y {:aggregate \"count\"\n",
    "                             :type \"quantitative\"}\n",
    "                         :color {}}}]\n",
    "    (if color\n",
    "      (assoc-in spec [:encoding :color] {:field color\n",
    "                                         :type \"nominal\"})\n",
    "      (assoc-in spec [:encoding :color] {:value \"dodgerblue\"}))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div>\n",
       "  <div id='uuid-194cf687-e251-424e-87fe-07ca21f4276f'></div>\n",
       "  <script>\n",
       "  requirejs.config({\n",
       "    baseUrl: 'https://cdn.jsdelivr.net/npm/',\n",
       "    paths: {\n",
       "      'vega-embed':  'vega-embed@3?noext',\n",
       "      'vega-lib': 'vega-lib?noext',\n",
       "      'vega-lite': 'vega-lite@2?noext',\n",
       "      'vega': 'vega@3?noext'\n",
       "    }\n",
       "  });\n",
       "  require(['vega-embed'], function(vegaEmbed) {\n",
       "    let spec = {\"data\":{\"values\":[{\"speed\":45},{\"speed\":60},{\"speed\":80},{\"speed\":80},{\"speed\":65},{\"speed\":80},{\"speed\":100},{\"speed\":100},{\"speed\":100},{\"speed\":43},{\"speed\":58},{\"speed\":78},{\"speed\":78},{\"speed\":45},{\"speed\":30},{\"speed\":70},{\"speed\":50},{\"speed\":35},{\"speed\":75},{\"speed\":145},{\"speed\":56},{\"speed\":71},{\"speed\":101},{\"speed\":121},{\"speed\":72},{\"speed\":97},{\"speed\":70},{\"speed\":100},{\"speed\":55},{\"speed\":80},{\"speed\":90},{\"speed\":110},{\"speed\":40},{\"speed\":65},{\"speed\":41},{\"speed\":56},{\"speed\":76},{\"speed\":50},{\"speed\":65},{\"speed\":85},{\"speed\":35},{\"speed\":60},{\"speed\":65},{\"speed\":100},{\"speed\":20},{\"speed\":45},{\"speed\":55},{\"speed\":90},{\"speed\":30},{\"speed\":40},{\"speed\":50},{\"speed\":25},{\"speed\":30},{\"speed\":45},{\"speed\":90},{\"speed\":95},{\"speed\":120},{\"speed\":90},{\"speed\":115},{\"speed\":55},{\"speed\":85},{\"speed\":70},{\"speed\":95},{\"speed\":60},{\"speed\":95},{\"speed\":90},{\"speed\":90},{\"speed\":70},{\"speed\":90},{\"speed\":105},{\"speed\":120},{\"speed\":150},{\"speed\":35},{\"speed\":45},{\"speed\":55},{\"speed\":40},{\"speed\":55},{\"speed\":70},{\"speed\":70},{\"speed\":100},{\"speed\":20},{\"speed\":35},{\"speed\":45},{\"speed\":90},{\"speed\":105},{\"speed\":15},{\"speed\":30},{\"speed\":30},{\"speed\":45},{\"speed\":70},{\"speed\":60},{\"speed\":75},{\"speed\":100},{\"speed\":45},{\"speed\":70},{\"speed\":25},{\"speed\":50},{\"speed\":40},{\"speed\":70},{\"speed\":80},{\"speed\":95},{\"speed\":110},{\"speed\":130},{\"speed\":70},{\"speed\":42},{\"speed\":67},{\"speed\":50},{\"speed\":75},{\"speed\":100},{\"speed\":140},{\"speed\":40},{\"speed\":55},{\"speed\":35},{\"speed\":45},{\"speed\":87},{\"speed\":76},{\"speed\":30},{\"speed\":35},{\"speed\":60},{\"speed\":25},{\"speed\":40},{\"speed\":50},{\"speed\":60},{\"speed\":90},{\"speed\":100},{\"speed\":60},{\"speed\":85},{\"speed\":63},{\"speed\":68},{\"speed\":85},{\"speed\":115},{\"speed\":90},{\"speed\":105},{\"speed\":95},{\"speed\":105},{\"speed\":93},{\"speed\":85},{\"speed\":105},{\"speed\":110},{\"speed\":80},{\"speed\":81},{\"speed\":81},{\"speed\":60},{\"speed\":48},{\"speed\":55},{\"speed\":65},{\"speed\":130},{\"speed\":65},{\"speed\":40},{\"speed\":35},{\"speed\":55},{\"speed\":55},{\"speed\":80},{\"speed\":130},{\"speed\":150},{\"speed\":30},{\"speed\":85},{\"speed\":100},{\"speed\":90},{\"speed\":50},{\"speed\":70},{\"speed\":80},{\"speed\":130},{\"speed\":130},{\"speed\":140},{\"speed\":100},{\"speed\":45},{\"speed\":60},{\"speed\":80},{\"speed\":65},{\"speed\":80},{\"speed\":100},{\"speed\":43},{\"speed\":58},{\"speed\":78},{\"speed\":20},{\"speed\":90},{\"speed\":50},{\"speed\":70},{\"speed\":55},{\"speed\":85},{\"speed\":30},{\"speed\":40},{\"speed\":130},{\"speed\":67},{\"speed\":67},{\"speed\":60},{\"speed\":15},{\"speed\":15},{\"speed\":20},{\"speed\":40},{\"speed\":70},{\"speed\":95},{\"speed\":35},{\"speed\":45},{\"speed\":55},{\"speed\":45},{\"speed\":50},{\"speed\":40},{\"speed\":50},{\"speed\":30},{\"speed\":70},{\"speed\":50},{\"speed\":80},{\"speed\":110},{\"speed\":85},{\"speed\":30},{\"speed\":30},{\"speed\":95},{\"speed\":15},{\"speed\":35},{\"speed\":110},{\"speed\":65},{\"speed\":91},{\"speed\":30},{\"speed\":85},{\"speed\":48},{\"speed\":33},{\"speed\":85},{\"speed\":15},{\"speed\":40},{\"speed\":45},{\"speed\":85},{\"speed\":30},{\"speed\":30},{\"speed\":30},{\"speed\":45},{\"speed\":85},{\"speed\":65},{\"speed\":75},{\"speed\":5},{\"speed\":85},{\"speed\":75},{\"speed\":115},{\"speed\":40},{\"speed\":55},{\"speed\":20},{\"speed\":30},{\"speed\":50},{\"speed\":50},{\"speed\":35},{\"speed\":65},{\"speed\":45},{\"speed\":75},{\"speed\":70},{\"speed\":70},{\"speed\":65},{\"speed\":95},{\"speed\":115},{\"speed\":85},{\"speed\":40},{\"speed\":50},{\"speed\":60},{\"speed\":85},{\"speed\":75},{\"speed\":35},{\"speed\":70},{\"speed\":65},{\"speed\":95},{\"speed\":83},{\"speed\":100},{\"speed\":55},{\"speed\":115},{\"speed\":100},{\"speed\":85},{\"speed\":41},{\"speed\":51},{\"speed\":61},{\"speed\":71},{\"speed\":110},{\"speed\":90},{\"speed\":100},{\"speed\":70},{\"speed\":95},{\"speed\":120},{\"speed\":145},{\"speed\":45},{\"speed\":55},{\"speed\":80},{\"speed\":100},{\"speed\":40},{\"speed\":50},{\"speed\":60},{\"speed\":70},{\"speed\":35},{\"speed\":70},{\"speed\":60},{\"speed\":100},{\"speed\":20},{\"speed\":15},{\"speed\":65},{\"speed\":15},{\"speed\":65},{\"speed\":30},{\"speed\":50},{\"speed\":70},{\"speed\":30},{\"speed\":60},{\"speed\":80},{\"speed\":85},{\"speed\":125},{\"speed\":85},{\"speed\":65},{\"speed\":40},{\"speed\":50},{\"speed\":80},{\"speed\":100},{\"speed\":65},{\"speed\":60},{\"speed\":35},{\"speed\":70},{\"speed\":30},{\"speed\":90},{\"speed\":100},{\"speed\":40},{\"speed\":160},{\"speed\":40},{\"speed\":28},{\"speed\":48},{\"speed\":68},{\"speed\":25},{\"speed\":50},{\"speed\":20},{\"speed\":30},{\"speed\":50},{\"speed\":70},{\"speed\":50},{\"speed\":20},{\"speed\":50},{\"speed\":50},{\"speed\":30},{\"speed\":40},{\"speed\":50},{\"speed\":50},{\"speed\":60},{\"speed\":80},{\"speed\":100},{\"speed\":65},{\"speed\":105},{\"speed\":135},{\"speed\":95},{\"speed\":95},{\"speed\":85},{\"speed\":85},{\"speed\":65},{\"speed\":40},{\"speed\":55},{\"speed\":65},{\"speed\":95},{\"speed\":105},{\"speed\":60},{\"speed\":60},{\"speed\":35},{\"speed\":40},{\"speed\":20},{\"speed\":20},{\"speed\":60},{\"speed\":80},{\"speed\":60},{\"speed\":10},{\"speed\":70},{\"speed\":100},{\"speed\":35},{\"speed\":55},{\"speed\":50},{\"speed\":80},{\"speed\":80},{\"speed\":90},{\"speed\":65},{\"speed\":70},{\"speed\":70},{\"speed\":60},{\"speed\":60},{\"speed\":35},{\"speed\":55},{\"speed\":55},{\"speed\":75},{\"speed\":23},{\"speed\":43},{\"speed\":75},{\"speed\":45},{\"speed\":80},{\"speed\":81},{\"speed\":70},{\"speed\":40},{\"speed\":45},{\"speed\":65},{\"speed\":75},{\"speed\":25},{\"speed\":25},{\"speed\":51},{\"speed\":65},{\"speed\":75},{\"speed\":115},{\"speed\":23},{\"speed\":50},{\"speed\":80},{\"speed\":100},{\"speed\":25},{\"speed\":45},{\"speed\":65},{\"speed\":32},{\"speed\":52},{\"speed\":52},{\"speed\":55},{\"speed\":97},{\"speed\":50},{\"speed\":50},{\"speed\":100},{\"speed\":120},{\"speed\":30},{\"speed\":50},{\"speed\":70},{\"speed\":110},{\"speed\":50},{\"speed\":50},{\"speed\":50},{\"speed\":110},{\"speed\":110},{\"speed\":110},{\"speed\":110},{\"speed\":90},{\"speed\":90},{\"speed\":90},{\"speed\":90},{\"speed\":95},{\"speed\":115},{\"speed\":100},{\"speed\":150},{\"speed\":150},{\"speed\":90},{\"speed\":180},{\"speed\":31},{\"speed\":36},{\"speed\":56},{\"speed\":61},{\"speed\":81},{\"speed\":108},{\"speed\":40},{\"speed\":50},{\"speed\":60},{\"speed\":60},{\"speed\":80},{\"speed\":100},{\"speed\":31},{\"speed\":71},{\"speed\":25},{\"speed\":65},{\"speed\":45},{\"speed\":60},{\"speed\":70},{\"speed\":55},{\"speed\":90},{\"speed\":58},{\"speed\":58},{\"speed\":30},{\"speed\":30},{\"speed\":36},{\"speed\":36},{\"speed\":36},{\"speed\":36},{\"speed\":66},{\"speed\":70},{\"speed\":40},{\"speed\":95},{\"speed\":85},{\"speed\":115},{\"speed\":35},{\"speed\":85},{\"speed\":34},{\"speed\":39},{\"speed\":115},{\"speed\":70},{\"speed\":80},{\"speed\":85},{\"speed\":105},{\"speed\":135},{\"speed\":105},{\"speed\":71},{\"speed\":85},{\"speed\":112},{\"speed\":45},{\"speed\":74},{\"speed\":84},{\"speed\":23},{\"speed\":33},{\"speed\":10},{\"speed\":60},{\"speed\":30},{\"speed\":91},{\"speed\":35},{\"speed\":42},{\"speed\":82},{\"speed\":102},{\"speed\":92},{\"speed\":5},{\"speed\":60},{\"speed\":90},{\"speed\":112},{\"speed\":32},{\"speed\":47},{\"speed\":65},{\"speed\":95},{\"speed\":50},{\"speed\":85},{\"speed\":46},{\"speed\":66},{\"speed\":91},{\"speed\":50},{\"speed\":40},{\"speed\":60},{\"speed\":30},{\"speed\":125},{\"speed\":60},{\"speed\":50},{\"speed\":40},{\"speed\":50},{\"speed\":95},{\"speed\":83},{\"speed\":80},{\"speed\":95},{\"speed\":95},{\"speed\":65},{\"speed\":95},{\"speed\":80},{\"speed\":90},{\"speed\":80},{\"speed\":110},{\"speed\":40},{\"speed\":45},{\"speed\":110},{\"speed\":91},{\"speed\":86},{\"speed\":86},{\"speed\":86},{\"speed\":86},{\"speed\":86},{\"speed\":95},{\"speed\":80},{\"speed\":115},{\"speed\":90},{\"speed\":100},{\"speed\":77},{\"speed\":100},{\"speed\":90},{\"speed\":90},{\"speed\":85},{\"speed\":80},{\"speed\":100},{\"speed\":125},{\"speed\":100},{\"speed\":127},{\"speed\":120},{\"speed\":100},{\"speed\":63},{\"speed\":83},{\"speed\":113},{\"speed\":45},{\"speed\":55},{\"speed\":65},{\"speed\":45},{\"speed\":60},{\"speed\":70},{\"speed\":42},{\"speed\":77},{\"speed\":55},{\"speed\":60},{\"speed\":80},{\"speed\":66},{\"speed\":106},{\"speed\":64},{\"speed\":101},{\"speed\":64},{\"speed\":101},{\"speed\":64},{\"speed\":101},{\"speed\":24},{\"speed\":29},{\"speed\":43},{\"speed\":65},{\"speed\":93},{\"speed\":76},{\"speed\":116},{\"speed\":15},{\"speed\":20},{\"speed\":25},{\"speed\":72},{\"speed\":114},{\"speed\":68},{\"speed\":88},{\"speed\":50},{\"speed\":50},{\"speed\":35},{\"speed\":40},{\"speed\":45},{\"speed\":64},{\"speed\":69},{\"speed\":74},{\"speed\":45},{\"speed\":85},{\"speed\":42},{\"speed\":42},{\"speed\":92},{\"speed\":57},{\"speed\":47},{\"speed\":112},{\"speed\":66},{\"speed\":116},{\"speed\":30},{\"speed\":90},{\"speed\":98},{\"speed\":65},{\"speed\":74},{\"speed\":92},{\"speed\":50},{\"speed\":95},{\"speed\":55},{\"speed\":60},{\"speed\":55},{\"speed\":45},{\"speed\":48},{\"speed\":58},{\"speed\":97},{\"speed\":30},{\"speed\":30},{\"speed\":22},{\"speed\":32},{\"speed\":70},{\"speed\":110},{\"speed\":65},{\"speed\":75},{\"speed\":65},{\"speed\":105},{\"speed\":75},{\"speed\":115},{\"speed\":45},{\"speed\":55},{\"speed\":65},{\"speed\":20},{\"speed\":30},{\"speed\":30},{\"speed\":55},{\"speed\":98},{\"speed\":44},{\"speed\":59},{\"speed\":79},{\"speed\":75},{\"speed\":95},{\"speed\":103},{\"speed\":60},{\"speed\":20},{\"speed\":15},{\"speed\":30},{\"speed\":40},{\"speed\":60},{\"speed\":65},{\"speed\":65},{\"speed\":108},{\"speed\":10},{\"speed\":20},{\"speed\":30},{\"speed\":50},{\"speed\":90},{\"speed\":60},{\"speed\":40},{\"speed\":50},{\"speed\":30},{\"speed\":40},{\"speed\":20},{\"speed\":55},{\"speed\":80},{\"speed\":57},{\"speed\":67},{\"speed\":97},{\"speed\":40},{\"speed\":50},{\"speed\":105},{\"speed\":25},{\"speed\":145},{\"speed\":32},{\"speed\":65},{\"speed\":105},{\"speed\":48},{\"speed\":35},{\"speed\":55},{\"speed\":60},{\"speed\":70},{\"speed\":55},{\"speed\":60},{\"speed\":80},{\"speed\":60},{\"speed\":80},{\"speed\":65},{\"speed\":109},{\"speed\":38},{\"speed\":58},{\"speed\":98},{\"speed\":60},{\"speed\":100},{\"speed\":108},{\"speed\":108},{\"speed\":108},{\"speed\":111},{\"speed\":121},{\"speed\":111},{\"speed\":101},{\"speed\":90},{\"speed\":90},{\"speed\":101},{\"speed\":91},{\"speed\":95},{\"speed\":95},{\"speed\":95},{\"speed\":108},{\"speed\":108},{\"speed\":90},{\"speed\":128},{\"speed\":99},{\"speed\":38},{\"speed\":57},{\"speed\":64},{\"speed\":60},{\"speed\":73},{\"speed\":104},{\"speed\":71},{\"speed\":97},{\"speed\":122},{\"speed\":57},{\"speed\":78},{\"speed\":62},{\"speed\":84},{\"speed\":126},{\"speed\":35},{\"speed\":29},{\"speed\":89},{\"speed\":72},{\"speed\":106},{\"speed\":42},{\"speed\":52},{\"speed\":75},{\"speed\":52},{\"speed\":68},{\"speed\":43},{\"speed\":58},{\"speed\":102},{\"speed\":68},{\"speed\":104},{\"speed\":104},{\"speed\":28},{\"speed\":35},{\"speed\":60},{\"speed\":60},{\"speed\":23},{\"speed\":29},{\"speed\":49},{\"speed\":72},{\"speed\":45},{\"speed\":73},{\"speed\":50},{\"speed\":68},{\"speed\":30},{\"speed\":44},{\"speed\":44},{\"speed\":59},{\"speed\":70},{\"speed\":109},{\"speed\":48},{\"speed\":71},{\"speed\":46},{\"speed\":58},{\"speed\":60},{\"speed\":118},{\"speed\":101},{\"speed\":50},{\"speed\":40},{\"speed\":60},{\"speed\":80},{\"speed\":75},{\"speed\":38},{\"speed\":56},{\"speed\":51},{\"speed\":56},{\"speed\":46},{\"speed\":41},{\"speed\":84},{\"speed\":99},{\"speed\":69},{\"speed\":54},{\"speed\":28},{\"speed\":28},{\"speed\":55},{\"speed\":123},{\"speed\":99},{\"speed\":99},{\"speed\":95},{\"speed\":50},{\"speed\":110},{\"speed\":70},{\"speed\":80},{\"speed\":70}]},\"mark\":\"bar\",\"width\":600,\"height\":300,\"encoding\":{\"x\":{\"field\":\"speed\",\"bin\":{\"maxbins\":50},\"type\":\"quantitative\"},\"y\":{\"aggregate\":\"count\",\"type\":\"quantitative\"},\"color\":{\"value\":\"dodgerblue\"}}};\n",
       "    vegaEmbed('#uuid-194cf687-e251-424e-87fe-07ca21f4276f', spec, {defaultStyle:true}).catch(console.warn);\n",
       "    }, function(err) {\n",
       "    console.log('Failed to load');\n",
       "  });\n",
       "  </script>\n",
       "</div>\n",
       "  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols :Speed)\n",
    "    pt/->clj\n",
    "    (hist :speed)\n",
    "    oz/view!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data-frames basics\n",
    "\n",
    "### Creation\n",
    "\n",
    "How to create data-frames? Above we read a csv, but what if we already have some data in the runtime we want to deal with? Nothing easier than this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/data-frame [{:a 1 :b 2} {:a 3 :b 4}]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we don't care about column names, or we'd prefer to add them to an already generated data-frame?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/data-frame (to-array-2d [[1 2] [3 4]])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Columns of data-frames are just serieses:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       ":series"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols \"Defense\") pt/pytype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/series [1 2 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The column name is the name of the series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "Name: my-series, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/series [1 2 3] {:name :my-series})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filtering\n",
    "\n",
    "One of the most straightforward ways to filter data-frames is with booleans. We have `filter-rows` that takes either booleans or a function that generates booleans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>225</td>\n",
       "      <td>Mega Steelix</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Ground</td>\n",
       "      <td>75</td>\n",
       "      <td>125</td>\n",
       "      <td>230</td>\n",
       "      <td>55</td>\n",
       "      <td>95</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>231</td>\n",
       "      <td>Shuckle</td>\n",
       "      <td>Bug</td>\n",
       "      <td>Rock</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>230</td>\n",
       "      <td>10</td>\n",
       "      <td>230</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>333</th>\n",
       "      <td>334</td>\n",
       "      <td>Mega Aggron</td>\n",
       "      <td>Steel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70</td>\n",
       "      <td>140</td>\n",
       "      <td>230</td>\n",
       "      <td>60</td>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/filter-rows #(-> % (pt/subset-cols \"Defense\") (pt/gt 200)))\n",
    "    show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`gt` is exactly what you think it is: `>`. Check the [Basic concepts](https://github.com/alanmarazzi/panthera/blob/master/examples/basic-concepts.ipynb) notebook to better understand how math works in panthera.\n",
    "\n",
    "Now we'll have to introduce Numpy in the equation. Let's say we want to filter the data-frame based on 2 conditions at the same time, we can do that using `npy`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nil"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(require '[panthera.numpy :refer [npy]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/my-filter"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn my-filter\n",
    "  [col1 col2]\n",
    "  (npy :logical-and \n",
    "       {:args [(-> pokemon\n",
    "                   (pt/subset-cols col1)\n",
    "                   (pt/gt 200))\n",
    "               (-> pokemon\n",
    "                   (pt/subset-cols col2)\n",
    "                   (pt/gt 100))]}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>225</td>\n",
       "      <td>Mega Steelix</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Ground</td>\n",
       "      <td>75</td>\n",
       "      <td>125</td>\n",
       "      <td>230</td>\n",
       "      <td>55</td>\n",
       "      <td>95</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>333</th>\n",
       "      <td>334</td>\n",
       "      <td>Mega Aggron</td>\n",
       "      <td>Steel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70</td>\n",
       "      <td>140</td>\n",
       "      <td>230</td>\n",
       "      <td>60</td>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/filter-rows (my-filter :Defense :Attack))\n",
    "    show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`panthera.numpy` works a little differently than regular panthera, usually you need only `npy` to have access to all of numpy functions.\n",
    "\n",
    "For instance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3.891820\n",
       "1    4.143135\n",
       "2    4.418841\n",
       "3    4.812184\n",
       "4    3.761200\n",
       "Name: Defense, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols :Defense)\n",
    "    ((npy :log))\n",
    "    pt/head)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we just calculated the `log` of the whole `Defense` column! Remember that `npy` operations are vectorized, so usually it is faster to use them (or equivalent panthera ones) than Clojure ones (unless you're doing more complicated operations, then Clojure would *probably* be faster).\n",
    "\n",
    "Now let's try to do some more complicated things:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27311/400"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(/ (pt/sum (pt/subset-cols pokemon :Speed)) \n",
    "   (pt/n-rows pokemon))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we see how we can combine operations on serieses, but of course that's a `mean`, and we have a function for that!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/col-mean"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn col-mean\n",
    "  [col]\n",
    "  (pt/mean (pt/subset-cols pokemon col)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we would like to add a new column that says `high` when the value is above the mean, and `low` for the opposite.\n",
    "\n",
    "`npy` is really helpful here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['low' 'low' 'high' 'high' 'low']"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(npy :where {:args [(pt/gt (pt/head (pt/subset-cols pokemon :Speed)) (col-mean :Speed))\n",
    "                    \"high\"\n",
    "                    \"low\"]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But this is pretty ugly and we can't chain it with other functions. It is pretty easy to wrap it into a chainable function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/where"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn where\n",
    "  [& args]\n",
    "  (npy :where {:args args}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['low' 'low' 'high' 'high' 'low']"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols :Speed)\n",
    "    pt/head\n",
    "    (pt/gt (col-mean :Speed))\n",
    "    (where \"high\" \"low\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That seems to work! Let's add a new column to our data-frame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>speed_level</th>\n",
       "      <th>Speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>low</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>low</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>high</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>high</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>low</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>high</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>high</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>high</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>high</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>low</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(def speed-level\n",
    "  (-> pokemon\n",
    "    (pt/subset-cols :Speed)\n",
    "    (pt/gt (col-mean :Speed))\n",
    "    (where \"high\" \"low\")))\n",
    "\n",
    "(-> pokemon\n",
    "    (pt/assign {:speed-level speed-level})\n",
    "    (pt/subset-cols :speed_level :Speed)\n",
    "    (pt/head 10)\n",
    "    show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course we didn't actually add `speed_level` to `pokemon`, we created a new data-frame. Everything here is as immutable as possible, let's check if this is really the case:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"#\" \"Name\" \"Type 1\" \"Type 2\" \"HP\" \"Attack\" \"Defense\" \"Sp. Atk\" \"Sp. Def\" \"Speed\" \"Generation\" \"Legendary\"]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(vec (pt/names pokemon))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspecting data\n",
    "\n",
    "Other than `head` we have `tail`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>796</td>\n",
       "      <td>Diancie</td>\n",
       "      <td>Rock</td>\n",
       "      <td>Fairy</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>150</td>\n",
       "      <td>100</td>\n",
       "      <td>150</td>\n",
       "      <td>50</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>797</td>\n",
       "      <td>Mega Diancie</td>\n",
       "      <td>Rock</td>\n",
       "      <td>Fairy</td>\n",
       "      <td>50</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>110</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>798</td>\n",
       "      <td>Hoopa Confined</td>\n",
       "      <td>Psychic</td>\n",
       "      <td>Ghost</td>\n",
       "      <td>80</td>\n",
       "      <td>110</td>\n",
       "      <td>60</td>\n",
       "      <td>150</td>\n",
       "      <td>130</td>\n",
       "      <td>70</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>799</td>\n",
       "      <td>Hoopa Unbound</td>\n",
       "      <td>Psychic</td>\n",
       "      <td>Dark</td>\n",
       "      <td>80</td>\n",
       "      <td>160</td>\n",
       "      <td>60</td>\n",
       "      <td>170</td>\n",
       "      <td>130</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>800</td>\n",
       "      <td>Volcanion</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Water</td>\n",
       "      <td>80</td>\n",
       "      <td>110</td>\n",
       "      <td>120</td>\n",
       "      <td>130</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/tail pokemon))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can always check what's the shape of the data structure we're interested in. `shape` returns rows and columns count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(800, 12)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/shape pokemon)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want just one of the two you can either use one of `n-rows` or `n-cols`, or get the required value by index:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/n-rows pokemon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((pt/shape pokemon) 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory data analysis\n",
    "\n",
    "Now we can move to something a little more interesting: some data analysis.\n",
    "\n",
    "One of the first things we might want to do is to look at some frequencies. `value-counts` is our friend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Water       112\n",
       "Normal       98\n",
       "Grass        70\n",
       "Bug          69\n",
       "Psychic      57\n",
       "Fire         52\n",
       "Rock         44\n",
       "Electric     44\n",
       "Ground       32\n",
       "Ghost        32\n",
       "Dragon       32\n",
       "Dark         31\n",
       "Poison       28\n",
       "Fighting     27\n",
       "Steel        27\n",
       "Ice          24\n",
       "Fairy        17\n",
       "Flying        4\n",
       "Name: Type 1, dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols \"Type 1\")\n",
    "    (pt/value-counts {:dropna false}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see we get counts by group automatically and this can come in handy!\n",
    "\n",
    "There's also a nice way to see many stats at once for all the numeric columns: `describe`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>800.0000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>400.5000</td>\n",
       "      <td>69.258750</td>\n",
       "      <td>79.001250</td>\n",
       "      <td>73.842500</td>\n",
       "      <td>72.820000</td>\n",
       "      <td>71.902500</td>\n",
       "      <td>68.277500</td>\n",
       "      <td>3.32375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>231.0844</td>\n",
       "      <td>25.534669</td>\n",
       "      <td>32.457366</td>\n",
       "      <td>31.183501</td>\n",
       "      <td>32.722294</td>\n",
       "      <td>27.828916</td>\n",
       "      <td>29.060474</td>\n",
       "      <td>1.66129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>200.7500</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>49.750000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>2.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>400.5000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>3.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>600.2500</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>5.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>800.0000</td>\n",
       "      <td>255.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>194.000000</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>6.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show (pt/describe pokemon))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you need some of these stats only for some columns, chances are that there's a function for that!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[69.25875 25.53466903233207 1 255]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> (pt/subset-cols pokemon :HP)\n",
    "    ((juxt pt/mean pt/std pt/minimum pt/maximum)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='reshape'></a>\n",
    "## Reshaping data\n",
    "\n",
    "Some of the most common operations with rectangular data is to reshape them how we most please to make other operations easier.\n",
    "\n",
    "The R people perfectly know what I mean when I talk about [tidy data](https://www.jstatsoft.org/article/view/v059i10/v59i10.pdf), if you have no idea about this check the link, but the main point is that while most are used to work with double entry matrices (like the one above built with `describe`), it is much easier to work with *long data*: one row per observation and one column per variable.\n",
    "\n",
    "In panthera there's `melt` as a workhorse for this process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon pt/head show)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Attack</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Attack</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Attack</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Attack</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Charmander</td>\n",
       "      <td>Attack</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Defense</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Defense</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Defense</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Defense</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Charmander</td>\n",
       "      <td>Defense</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon pt/head (pt/melt {:id-vars \"Name\" :value-vars [\"Attack\" \"Defense\"]}) show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we told panthera that we wanted to `melt` our data-frame and that we would like to have the column `Name` act as the main id, while we're interested in the value of `Attack` and `Defense`.\n",
    "\n",
    "This makes much easier to group values by some variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "          value\n",
       "variable       \n",
       "Attack     69.0\n",
       "Defense    72.2"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon \n",
    "    pt/head \n",
    "    (pt/melt {:id-vars \"Name\" :value-vars [\"Attack\" \"Defense\"]}) \n",
    "    (pt/groupby :variable)\n",
    "    pt/mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you've ever used Excel you already know about `pivot`, which is the opposite of `melt`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>variable</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bulbasaur</th>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charmander</th>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ivysaur</th>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mega Venusaur</th>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Venusaur</th>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon \n",
    "    pt/head \n",
    "    (pt/melt {:id-vars \"Name\" :value-vars [\"Attack\" \"Defense\"]}) \n",
    "    (pt/pivot {:index \"Name\" :columns \"variable\" :values \"value\"})\n",
    "    show)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we have more than one data-frame? We can combine them however we want!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>796</td>\n",
       "      <td>Diancie</td>\n",
       "      <td>Rock</td>\n",
       "      <td>Fairy</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>150</td>\n",
       "      <td>100</td>\n",
       "      <td>150</td>\n",
       "      <td>50</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>797</td>\n",
       "      <td>Mega Diancie</td>\n",
       "      <td>Rock</td>\n",
       "      <td>Fairy</td>\n",
       "      <td>50</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>110</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>798</td>\n",
       "      <td>Hoopa Confined</td>\n",
       "      <td>Psychic</td>\n",
       "      <td>Ghost</td>\n",
       "      <td>80</td>\n",
       "      <td>110</td>\n",
       "      <td>60</td>\n",
       "      <td>150</td>\n",
       "      <td>130</td>\n",
       "      <td>70</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>799</td>\n",
       "      <td>Hoopa Unbound</td>\n",
       "      <td>Psychic</td>\n",
       "      <td>Dark</td>\n",
       "      <td>80</td>\n",
       "      <td>160</td>\n",
       "      <td>60</td>\n",
       "      <td>170</td>\n",
       "      <td>130</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>800</td>\n",
       "      <td>Volcanion</td>\n",
       "      <td>Fire</td>\n",
       "      <td>Water</td>\n",
       "      <td>80</td>\n",
       "      <td>110</td>\n",
       "      <td>120</td>\n",
       "      <td>130</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show \n",
    "  (pt/concatenate\n",
    "    [(pt/head pokemon)\n",
    "     (pt/tail pokemon)]\n",
    "    {:axis 0\n",
    "     :ignore-index true}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just a second to discuss some options:\n",
    "\n",
    "- `:axis`: most of panthera operations can be applied either by rows or columns, we decide which with this keyword where 0 = rows and 1 = columns\n",
    "- `:ignore-index`: panthera works by index, to better understand what kind of indexes there are and most of their quirks check [Basic concepts](https://nbviewer.jupyter.org/github/alanmarazzi/panthera/blob/master/examples/basic-concepts.ipynb#Indexing-and-subsetting)\n",
    "\n",
    "To better understand `:axis` let's make another example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(show\n",
    "  (pt/concatenate\n",
    "    (repeat 2 (pt/head pokemon))\n",
    "    {:axis 1}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Types, types everywhere\n",
    "\n",
    "There are many dedicated types, but no worries, there are nice ways to deal with them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#              int64\n",
       "Name          object\n",
       "Type 1        object\n",
       "Type 2        object\n",
       "HP             int64\n",
       "Attack         int64\n",
       "Defense        int64\n",
       "Sp. Atk        int64\n",
       "Sp. Def        int64\n",
       "Speed          int64\n",
       "Generation     int64\n",
       "Legendary       bool\n",
       "dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pt/dtype pokemon)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I guess there isn't much to say about `:int64` and `:bool`, but surely `:object` looks more interesting. When panthera (numpy included) finds either strings or something it doesn't know how to deal with it goes to the less tight type possible which is an `:object`.\n",
    "\n",
    "`:object`s are usually bloated, if we want to save some overhead and it makes sense to deal with categorical values we can convert them to `:category`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Grass\n",
       "1    Grass\n",
       "2    Grass\n",
       "3    Grass\n",
       "4     Fire\n",
       "Name: Type 1, dtype: category\n",
       "Categories (18, object): [Bug, Dark, Dragon, Electric, ..., Psychic, Rock, Steel, Water]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols \"Type 1\")\n",
    "    (pt/astype :category)\n",
    "    pt/head)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    45.0\n",
       "1    60.0\n",
       "2    80.0\n",
       "3    80.0\n",
       "4    65.0\n",
       "Name: Speed, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols \"Speed\")\n",
    "    (pt/astype :float)\n",
    "    pt/head)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dealing with missing data\n",
    "\n",
    "One of the most painful operations for data scientists and engineers is dealing with the unknown: `NaN` (or `nil`, `Null`, etc).\n",
    "\n",
    "panthera tries to make this as painless as possible:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NaN         386\n",
       "Flying       97\n",
       "Ground       35\n",
       "Poison       34\n",
       "Psychic      33\n",
       "Fighting     26\n",
       "Grass        25\n",
       "Fairy        23\n",
       "Steel        22\n",
       "Dark         20\n",
       "Dragon       18\n",
       "Ice          14\n",
       "Ghost        14\n",
       "Water        14\n",
       "Rock         14\n",
       "Fire         12\n",
       "Electric      6\n",
       "Normal        4\n",
       "Bug           3\n",
       "Name: Type 2, dtype: int64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols \"Type 2\")\n",
    "    (pt/value-counts {:dropna false}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could check for `NaN` in other ways has well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[true false]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon (pt/subset-cols \"Type 2\") ((juxt pt/hasnans? (comp pt/all? pt/not-na?))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One of the ways to deal with missing data is to just drop rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Flying      97\n",
       "Ground      35\n",
       "Poison      34\n",
       "Psychic     33\n",
       "Fighting    26\n",
       "Grass       25\n",
       "Fairy       23\n",
       "Steel       22\n",
       "Dark        20\n",
       "Dragon      18\n",
       "Ice         14\n",
       "Rock        14\n",
       "Water       14\n",
       "Ghost       14\n",
       "Fire        12\n",
       "Electric     6\n",
       "Normal       4\n",
       "Bug          3\n",
       "Name: Type 2, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/dropna {:subset [\"Type 2\"]})\n",
    "    (pt/subset-cols \"Type 2\")\n",
    "    (pt/value-counts {:dropna false}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But let's say we want to replace missing observations with a flag or value of some kind, we can do that easily with `fill-na`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Poison\n",
       "1    Poison\n",
       "2    Poison\n",
       "3    Poison\n",
       "4     empty\n",
       "5     empty\n",
       "6    Flying\n",
       "7    Dragon\n",
       "8    Flying\n",
       "9     empty\n",
       "Name: Type 2, dtype: object"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    (pt/subset-cols \"Type 2\")\n",
    "    (pt/fill-na :empty)\n",
    "    (pt/head 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time and dates\n",
    "\n",
    "Programmers hate time, that's a fact. Panthera tries to make this experience as painless as possible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['1992-01-10', '1992-02-10', '1992-03-10', '1993-03-15',\n",
       "               '1993-03-16'],\n",
       "              dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(def times\n",
    "  [\"1992-01-10\",\"1992-02-10\",\"1992-03-10\",\"1993-03-15\",\"1993-03-16\"])\n",
    "\n",
    "(pt/->datetime times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1992-01-10</th>\n",
       "      <td>1</td>\n",
       "      <td>Bulbasaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992-02-10</th>\n",
       "      <td>2</td>\n",
       "      <td>Ivysaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992-03-10</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-03-15</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-03-16</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    pt/head\n",
    "    (pt/set-index (pt/->datetime times))\n",
    "    show)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#                      5\n",
       "Name          Charmander\n",
       "Type 1              Fire\n",
       "Type 2               NaN\n",
       "HP                    39\n",
       "Attack                52\n",
       "Defense               43\n",
       "Sp. Atk               60\n",
       "Sp. Def               50\n",
       "Speed                 65\n",
       "Generation             1\n",
       "Legendary          False\n",
       "Name: 1993-03-16 00:00:00, dtype: object"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    pt/head\n",
    "    (pt/set-index (pt/->datetime times))\n",
    "    (pt/select-rows \"1993-03-16\" :loc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>Name</th>\n",
       "      <th>Type 1</th>\n",
       "      <th>Type 2</th>\n",
       "      <th>HP</th>\n",
       "      <th>Attack</th>\n",
       "      <th>Defense</th>\n",
       "      <th>Sp. Atk</th>\n",
       "      <th>Sp. Def</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Generation</th>\n",
       "      <th>Legendary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1992-03-10</th>\n",
       "      <td>3</td>\n",
       "      <td>Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-03-15</th>\n",
       "      <td>4</td>\n",
       "      <td>Mega Venusaur</td>\n",
       "      <td>Grass</td>\n",
       "      <td>Poison</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>122</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-03-16</th>\n",
       "      <td>5</td>\n",
       "      <td>Charmander</td>\n",
       "      <td>Fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> pokemon\n",
    "    pt/head\n",
    "    (pt/set-index (pt/->datetime times))\n",
    "    (pt/select-rows (pt/slice \"1992-03-10\" \"1993-03-16\") :loc)\n",
    "    show)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "mimetype": "text/x-clojure",
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