Sampling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "453de22a",
   "metadata": {},
   "source": [
    "# Simple Random Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "91216cef",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "40c31cf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SNo</th>\n",
       "      <th>Date</th>\n",
       "      <th>StartupName</th>\n",
       "      <th>IndustryVertical</th>\n",
       "      <th>SubVertical</th>\n",
       "      <th>CityLocation</th>\n",
       "      <th>InvestorsName</th>\n",
       "      <th>InvestmentType</th>\n",
       "      <th>AmountInUSD</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>01/08/2017</td>\n",
       "      <td>TouchKin</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Predictive Care Platform</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Kae Capital</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>1,300,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Ethinos</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Digital Marketing Agency</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Triton Investment Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Leverage Edu</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Online platform for Higher Education Services</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Zepo</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>DIY Ecommerce platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Click2Clinic</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>healthcare service aggregator</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Narottam Thudi, Shireesh Palle</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>850,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SNo        Date   StartupName   IndustryVertical  \\\n",
       "0    0  01/08/2017      TouchKin         Technology   \n",
       "1    1  02/08/2017       Ethinos         Technology   \n",
       "2    2  02/08/2017  Leverage Edu  Consumer Internet   \n",
       "3    3  02/08/2017          Zepo  Consumer Internet   \n",
       "4    4  02/08/2017  Click2Clinic  Consumer Internet   \n",
       "\n",
       "                                     SubVertical CityLocation  \\\n",
       "0                       Predictive Care Platform    Bangalore   \n",
       "1                       Digital Marketing Agency       Mumbai   \n",
       "2  Online platform for Higher Education Services    New Delhi   \n",
       "3                         DIY Ecommerce platform       Mumbai   \n",
       "4                  healthcare service aggregator    Hyderabad   \n",
       "\n",
       "                                       InvestorsName  InvestmentType  \\\n",
       "0                                        Kae Capital  Private Equity   \n",
       "1                         Triton Investment Advisors  Private Equity   \n",
       "2  Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...    Seed Funding   \n",
       "3  Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...    Seed Funding   \n",
       "4                     Narottam Thudi, Shireesh Palle    Seed Funding   \n",
       "\n",
       "  AmountInUSD Remarks  \n",
       "0   1,300,000     NaN  \n",
       "1         NaN     NaN  \n",
       "2         NaN     NaN  \n",
       "3     500,000     NaN  \n",
       "4     850,000     NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv(\"Dataset/startup_funding.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a05a7813",
   "metadata": {},
   "outputs": [],
   "source": [
    "amount=data['AmountInUSD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "540abc2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1,300,000\n",
       "1          NaN\n",
       "2          NaN\n",
       "3      500,000\n",
       "4      850,000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amount.head()\n",
    "#We have NaN values and in string form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2fd24a0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1,300,000\n",
       "3      500,000\n",
       "4      850,000\n",
       "5    1,000,000\n",
       "6    2,600,000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping NaN values\n",
    "amount.dropna(inplace=True)\n",
    "amount.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5d3b8da8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1300000\n",
       "3     500000\n",
       "4     850000\n",
       "5    1000000\n",
       "6    2600000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#replacing commas in string\n",
    "a1=amount.str.replace(',','')\n",
    "a1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "86a2a580",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1300000'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#now this is of str type data\n",
    "a1[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8be5520b",
   "metadata": {},
   "outputs": [],
   "source": [
    "a2=pd.to_numeric(a1)\n",
    "#converting string to numerical value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "35cbb315",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1300000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a2[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f6ce6631",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a2[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8a757d9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12031073.099016393\n",
      "16000\n",
      "1400000000\n"
     ]
    }
   ],
   "source": [
    "#population avg,min and max values:\n",
    "pop_avg=a2.mean()\n",
    "pop_min=a2.min()\n",
    "pop_max=a2.max()\n",
    "print(pop_avg)\n",
    "print(pop_min)\n",
    "print(pop_max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "54db9fe6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1319    10000000\n",
       "Name: AmountInUSD, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population=a2\n",
    "sample_size=100\n",
    "population.sample()\n",
    "#by .sample() we can randomly select some record(by default it gives one record)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0b8fb11d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1833      250000\n",
       "2345       16000\n",
       "2279    40000000\n",
       "1050       89000\n",
       "1466     3000000\n",
       "1587     3000000\n",
       "1539      200000\n",
       "1376      520000\n",
       "1548      500000\n",
       "2360    56000000\n",
       "Name: AmountInUSD, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population.sample(10)\n",
    "#sample function selects random samples withpot replacement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4b7d8513",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample=population.sample(sample_size,random_state=1)\n",
    "#random state argument ensures that random selected sample remains same "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "31802f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100,)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9d44a190",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12031073.099016393   24592930.0\n",
      "16000   18000\n",
      "1400000000   1400000000\n"
     ]
    }
   ],
   "source": [
    "sample_avg=sample.mean()\n",
    "sample_min=sample.min()\n",
    "sample_max=sample.max()\n",
    "print(pop_avg,\" \",sample_avg)\n",
    "print(pop_min,\" \",sample_min)\n",
    "print(pop_max,\" \",sample_max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8ca07a72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SNo</th>\n",
       "      <th>Date</th>\n",
       "      <th>StartupName</th>\n",
       "      <th>IndustryVertical</th>\n",
       "      <th>SubVertical</th>\n",
       "      <th>CityLocation</th>\n",
       "      <th>InvestorsName</th>\n",
       "      <th>InvestmentType</th>\n",
       "      <th>AmountInUSD</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>01/08/2017</td>\n",
       "      <td>TouchKin</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Predictive Care Platform</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Kae Capital</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>1,300,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Ethinos</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Digital Marketing Agency</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Triton Investment Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Leverage Edu</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Online platform for Higher Education Services</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Zepo</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>DIY Ecommerce platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Click2Clinic</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>healthcare service aggregator</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Narottam Thudi, Shireesh Palle</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>850,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SNo        Date   StartupName   IndustryVertical  \\\n",
       "0    0  01/08/2017      TouchKin         Technology   \n",
       "1    1  02/08/2017       Ethinos         Technology   \n",
       "2    2  02/08/2017  Leverage Edu  Consumer Internet   \n",
       "3    3  02/08/2017          Zepo  Consumer Internet   \n",
       "4    4  02/08/2017  Click2Clinic  Consumer Internet   \n",
       "\n",
       "                                     SubVertical CityLocation  \\\n",
       "0                       Predictive Care Platform    Bangalore   \n",
       "1                       Digital Marketing Agency       Mumbai   \n",
       "2  Online platform for Higher Education Services    New Delhi   \n",
       "3                         DIY Ecommerce platform       Mumbai   \n",
       "4                  healthcare service aggregator    Hyderabad   \n",
       "\n",
       "                                       InvestorsName  InvestmentType  \\\n",
       "0                                        Kae Capital  Private Equity   \n",
       "1                         Triton Investment Advisors  Private Equity   \n",
       "2  Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...    Seed Funding   \n",
       "3  Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...    Seed Funding   \n",
       "4                     Narottam Thudi, Shireesh Palle    Seed Funding   \n",
       "\n",
       "  AmountInUSD Remarks  \n",
       "0   1,300,000     NaN  \n",
       "1         NaN     NaN  \n",
       "2         NaN     NaN  \n",
       "3     500,000     NaN  \n",
       "4     850,000     NaN  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Average amount of funding for Banglore or New Delhi(Without Replacement)\n",
    "data=pd.read_csv(\"Dataset/startup_funding.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fdd7df7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "627"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BA_ND = data[(data[\"CityLocation\"] == \"Bangalore\") | (data[\"CityLocation\"] == \"New Delhilen\")]\n",
    "len(BA_ND)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "14922678",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1,300,000\n",
       "5     1,000,000\n",
       "8     8,500,000\n",
       "11          NaN\n",
       "13    1,000,000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#working upon population\n",
    "amount=BA_ND['AmountInUSD']\n",
    "amount.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8e0fba44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1,300,000\n",
       "5      1,000,000\n",
       "8      8,500,000\n",
       "13     1,000,000\n",
       "19    18,500,000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amount_copy = amount.copy()\n",
    "amount_copy.dropna(inplace=True)\n",
    "amount_copy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e879de74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1300000'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a1=amount_copy.str.replace(',','')\n",
    "a1.head()\n",
    "a1[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "27a86470",
   "metadata": {},
   "outputs": [],
   "source": [
    "a2=pd.to_numeric(a1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6c264587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "405"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(a2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "127363f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20700676.809876543\n"
     ]
    }
   ],
   "source": [
    "#population:\n",
    "pop_mean=a2.mean()\n",
    "print(pop_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "85f13d81",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_size=50\n",
    "sample=a2.sample(sample_size,random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9baca6b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9405570.0\n"
     ]
    }
   ],
   "source": [
    "#sample:\n",
    "sample_mean=sample.mean()\n",
    "print(sample_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2d9d0e62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11295106.809876543"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sampling_error=pop_mean-sample_mean\n",
    "sampling_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "631089ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SNo</th>\n",
       "      <th>Date</th>\n",
       "      <th>StartupName</th>\n",
       "      <th>IndustryVertical</th>\n",
       "      <th>SubVertical</th>\n",
       "      <th>CityLocation</th>\n",
       "      <th>InvestorsName</th>\n",
       "      <th>InvestmentType</th>\n",
       "      <th>AmountInUSD</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>01/08/2017</td>\n",
       "      <td>TouchKin</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Predictive Care Platform</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Kae Capital</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>1,300,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Ethinos</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Digital Marketing Agency</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Triton Investment Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Leverage Edu</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Online platform for Higher Education Services</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Zepo</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>DIY Ecommerce platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Click2Clinic</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>healthcare service aggregator</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Narottam Thudi, Shireesh Palle</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>850,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SNo        Date   StartupName   IndustryVertical  \\\n",
       "0    0  01/08/2017      TouchKin         Technology   \n",
       "1    1  02/08/2017       Ethinos         Technology   \n",
       "2    2  02/08/2017  Leverage Edu  Consumer Internet   \n",
       "3    3  02/08/2017          Zepo  Consumer Internet   \n",
       "4    4  02/08/2017  Click2Clinic  Consumer Internet   \n",
       "\n",
       "                                     SubVertical CityLocation  \\\n",
       "0                       Predictive Care Platform    Bangalore   \n",
       "1                       Digital Marketing Agency       Mumbai   \n",
       "2  Online platform for Higher Education Services    New Delhi   \n",
       "3                         DIY Ecommerce platform       Mumbai   \n",
       "4                  healthcare service aggregator    Hyderabad   \n",
       "\n",
       "                                       InvestorsName  InvestmentType  \\\n",
       "0                                        Kae Capital  Private Equity   \n",
       "1                         Triton Investment Advisors  Private Equity   \n",
       "2  Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...    Seed Funding   \n",
       "3  Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...    Seed Funding   \n",
       "4                     Narottam Thudi, Shireesh Palle    Seed Funding   \n",
       "\n",
       "  AmountInUSD Remarks  \n",
       "0   1,300,000     NaN  \n",
       "1         NaN     NaN  \n",
       "2         NaN     NaN  \n",
       "3     500,000     NaN  \n",
       "4     850,000     NaN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Average amount of funding for Banglore or New Delhi(Replacement)\n",
    "data=pd.read_csv(\"Dataset/startup_funding.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "70e56a02",
   "metadata": {},
   "outputs": [],
   "source": [
    "reqdata=data[(data[\"CityLocation\"]==\"Bangalore\") | (data[\"CityLocation\"]==\"New Delhi\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f9fd9fc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "amount=reqdata['AmountInUSD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "395085e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1,300,000\n",
       "5      1,000,000\n",
       "8      8,500,000\n",
       "13     1,000,000\n",
       "19    18,500,000\n",
       "Name: AmountInUSD, dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amount_copy = amount.copy()\n",
    "amount_copy.dropna(inplace=True)\n",
    "amount_copy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f9d9d256",
   "metadata": {},
   "outputs": [],
   "source": [
    "amount_copy = amount_copy.str.replace(',', '')  \n",
    "# Remove commas from the string\n",
    "amount_copy = pd.to_numeric(amount_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "67db0a4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18045415.896272287\n"
     ]
    }
   ],
   "source": [
    "#population:\n",
    "pop_mean=amount_copy.mean()\n",
    "print(pop_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "eb5ec4c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "21243700.0\n"
     ]
    }
   ],
   "source": [
    "#sample:\n",
    "sample_size=50\n",
    "sample=amount_copy.sample(sample_size,replace=True)\n",
    "sample_mean=sample.mean()\n",
    "print(sample_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "90b25308",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-3198284.103727713\n"
     ]
    }
   ],
   "source": [
    "sampling_error=pop_mean-sample_mean\n",
    "print(sampling_error)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "145eb038",
   "metadata": {},
   "source": [
    "## Stratified Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "851d0eb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SNo</th>\n",
       "      <th>Date</th>\n",
       "      <th>StartupName</th>\n",
       "      <th>IndustryVertical</th>\n",
       "      <th>SubVertical</th>\n",
       "      <th>CityLocation</th>\n",
       "      <th>InvestorsName</th>\n",
       "      <th>InvestmentType</th>\n",
       "      <th>AmountInUSD</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>01/08/2017</td>\n",
       "      <td>TouchKin</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Predictive Care Platform</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Kae Capital</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>1,300,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Ethinos</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Digital Marketing Agency</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Triton Investment Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Leverage Edu</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Online platform for Higher Education Services</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Zepo</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>DIY Ecommerce platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Click2Clinic</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>healthcare service aggregator</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Narottam Thudi, Shireesh Palle</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>850,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>01/07/2017</td>\n",
       "      <td>Billion Loans</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Peer to Peer Lending platform</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Reliance Corporate Advisory Services Ltd</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>1,000,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>03/07/2017</td>\n",
       "      <td>Ecolibriumenergy</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Energy management solutions provider</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Infuse Ventures, JLL</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>2,600,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>04/07/2017</td>\n",
       "      <td>Droom</td>\n",
       "      <td>eCommerce</td>\n",
       "      <td>Online marketplace for automobiles</td>\n",
       "      <td>Gurgaon</td>\n",
       "      <td>Asset Management (Asia) Ltd, Digital Garage Inc</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>20,000,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>05/07/2017</td>\n",
       "      <td>Jumbotail</td>\n",
       "      <td>eCommerce</td>\n",
       "      <td>online marketplace for food and grocery</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Kalaari Capital, Nexus India Capital Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>8,500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>05/07/2017</td>\n",
       "      <td>Moglix</td>\n",
       "      <td>eCommerce</td>\n",
       "      <td>B2B marketplace for Industrial products</td>\n",
       "      <td>Noida</td>\n",
       "      <td>International Finance Corporation, Rocketship,...</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>12,000,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SNo        Date       StartupName   IndustryVertical  \\\n",
       "0    0  01/08/2017          TouchKin         Technology   \n",
       "1    1  02/08/2017           Ethinos         Technology   \n",
       "2    2  02/08/2017      Leverage Edu  Consumer Internet   \n",
       "3    3  02/08/2017              Zepo  Consumer Internet   \n",
       "4    4  02/08/2017      Click2Clinic  Consumer Internet   \n",
       "5    5  01/07/2017     Billion Loans  Consumer Internet   \n",
       "6    6  03/07/2017  Ecolibriumenergy         Technology   \n",
       "7    7  04/07/2017             Droom          eCommerce   \n",
       "8    8  05/07/2017         Jumbotail          eCommerce   \n",
       "9    9  05/07/2017            Moglix          eCommerce   \n",
       "\n",
       "                                     SubVertical CityLocation  \\\n",
       "0                       Predictive Care Platform    Bangalore   \n",
       "1                       Digital Marketing Agency       Mumbai   \n",
       "2  Online platform for Higher Education Services    New Delhi   \n",
       "3                         DIY Ecommerce platform       Mumbai   \n",
       "4                  healthcare service aggregator    Hyderabad   \n",
       "5                  Peer to Peer Lending platform    Bangalore   \n",
       "6           Energy management solutions provider    Ahmedabad   \n",
       "7             Online marketplace for automobiles      Gurgaon   \n",
       "8        online marketplace for food and grocery    Bangalore   \n",
       "9        B2B marketplace for Industrial products        Noida   \n",
       "\n",
       "                                       InvestorsName  InvestmentType  \\\n",
       "0                                        Kae Capital  Private Equity   \n",
       "1                         Triton Investment Advisors  Private Equity   \n",
       "2  Kashyap Deorah, Anand Sankeshwar, Deepak Jain,...    Seed Funding   \n",
       "3  Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...    Seed Funding   \n",
       "4                     Narottam Thudi, Shireesh Palle    Seed Funding   \n",
       "5           Reliance Corporate Advisory Services Ltd    Seed Funding   \n",
       "6                               Infuse Ventures, JLL  Private Equity   \n",
       "7    Asset Management (Asia) Ltd, Digital Garage Inc  Private Equity   \n",
       "8      Kalaari Capital, Nexus India Capital Advisors  Private Equity   \n",
       "9  International Finance Corporation, Rocketship,...  Private Equity   \n",
       "\n",
       "  AmountInUSD Remarks  \n",
       "0   1,300,000     NaN  \n",
       "1         NaN     NaN  \n",
       "2         NaN     NaN  \n",
       "3     500,000     NaN  \n",
       "4     850,000     NaN  \n",
       "5   1,000,000     NaN  \n",
       "6   2,600,000     NaN  \n",
       "7  20,000,000     NaN  \n",
       "8   8,500,000     NaN  \n",
       "9  12,000,000     NaN  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv(\"Dataset/startup_funding.csv\")\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "5c516a99",
   "metadata": {},
   "outputs": [],
   "source": [
    "Bangalore=data[\"CityLocation\"] == \"Bangalore\"\n",
    "NCR = ((data[\"CityLocation\"] == \"New Delhi\") | (data[\"CityLocation\"] == \"Gurgaon\") | (data[\"CityLocation\"] == \"Noida\"))\n",
    "Mumbai=data[\"CityLocation\"] == \"Mumbai\"\n",
    "Pune=data[\"CityLocation\"] == \"Pune\"\n",
    "Hydreabad=data[\"CityLocation\"] == \"Hydreabad\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5a66b2dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_a=data[Bangalore]  #Strata A\n",
    "group_b=data[NCR]        #Strata B\n",
    "group_c=data[Mumbai]     #Strata C\n",
    "group_d=data[Pune]       #Strata D\n",
    "group_e=data[Hydreabad]  #Strata E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e834d906",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SNo</th>\n",
       "      <th>Date</th>\n",
       "      <th>StartupName</th>\n",
       "      <th>IndustryVertical</th>\n",
       "      <th>SubVertical</th>\n",
       "      <th>CityLocation</th>\n",
       "      <th>InvestorsName</th>\n",
       "      <th>InvestmentType</th>\n",
       "      <th>AmountInUSD</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Ethinos</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Digital Marketing Agency</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Triton Investment Advisors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>02/08/2017</td>\n",
       "      <td>Zepo</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>DIY Ecommerce platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>500,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>05/07/2017</td>\n",
       "      <td>Timesaverz</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Hyperlocal home services provider</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>BCCL</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>1,000,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>11/07/2017</td>\n",
       "      <td>Flickstree</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>Video Content Discovery Platform</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Venture Catalysts, Sourav Ganguly, Ankit Adity...</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>464,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45</td>\n",
       "      <td>28/07/2017</td>\n",
       "      <td>Jhakaas</td>\n",
       "      <td>Consumer Internet</td>\n",
       "      <td>App-based Aggregator of Offline Businesses</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Amen Dhyllon</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2169</th>\n",
       "      <td>2169</td>\n",
       "      <td>18/04/2015</td>\n",
       "      <td>Doormint</td>\n",
       "      <td>On-Demand Handyman Services</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Powai Lake Ventures</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2179</th>\n",
       "      <td>2179</td>\n",
       "      <td>23/04/2015</td>\n",
       "      <td>Craftstvilla</td>\n",
       "      <td>Ethnic Product eCommerce</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Sequoia Capital, Nexus venture Partners, Light...</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>18,000,000</td>\n",
       "      <td>Series B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2185</th>\n",
       "      <td>2185</td>\n",
       "      <td>24/04/2015</td>\n",
       "      <td>Coverfox</td>\n",
       "      <td>Online Insurance Aggregator</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Accel US, Accel India, SAIF Partners.</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>12,000,000</td>\n",
       "      <td>Series B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2187</th>\n",
       "      <td>2187</td>\n",
       "      <td>27/04/2015</td>\n",
       "      <td>Grab</td>\n",
       "      <td>Food Logistics &amp; Delivery</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Oliphans Capital, Haresh Chawla</td>\n",
       "      <td>Seed Funding</td>\n",
       "      <td>1,000,000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2193</th>\n",
       "      <td>2193</td>\n",
       "      <td>28/04/2015</td>\n",
       "      <td>Naaptol.com</td>\n",
       "      <td>Tele-Shopping / eCommerce</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Mitsui &amp; Co &amp; existing investors</td>\n",
       "      <td>Private Equity</td>\n",
       "      <td>21,500,000</td>\n",
       "      <td>Series C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>446 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       SNo        Date   StartupName             IndustryVertical  \\\n",
       "1        1  02/08/2017       Ethinos                   Technology   \n",
       "3        3  02/08/2017          Zepo            Consumer Internet   \n",
       "10      10  05/07/2017    Timesaverz            Consumer Internet   \n",
       "17      17  11/07/2017    Flickstree            Consumer Internet   \n",
       "45      45  28/07/2017       Jhakaas            Consumer Internet   \n",
       "...    ...         ...           ...                          ...   \n",
       "2169  2169  18/04/2015      Doormint  On-Demand Handyman Services   \n",
       "2179  2179  23/04/2015  Craftstvilla     Ethnic Product eCommerce   \n",
       "2185  2185  24/04/2015      Coverfox  Online Insurance Aggregator   \n",
       "2187  2187  27/04/2015          Grab    Food Logistics & Delivery   \n",
       "2193  2193  28/04/2015   Naaptol.com    Tele-Shopping / eCommerce   \n",
       "\n",
       "                                     SubVertical CityLocation  \\\n",
       "1                       Digital Marketing Agency       Mumbai   \n",
       "3                         DIY Ecommerce platform       Mumbai   \n",
       "10             Hyperlocal home services provider       Mumbai   \n",
       "17              Video Content Discovery Platform       Mumbai   \n",
       "45    App-based Aggregator of Offline Businesses       Mumbai   \n",
       "...                                          ...          ...   \n",
       "2169                                         NaN       Mumbai   \n",
       "2179                                         NaN       Mumbai   \n",
       "2185                                         NaN       Mumbai   \n",
       "2187                                         NaN       Mumbai   \n",
       "2193                                         NaN       Mumbai   \n",
       "\n",
       "                                          InvestorsName  InvestmentType  \\\n",
       "1                            Triton Investment Advisors  Private Equity   \n",
       "3     Kunal Shah, LetsVenture, Anupam Mittal, Hetal ...    Seed Funding   \n",
       "10                                                 BCCL  Private Equity   \n",
       "17    Venture Catalysts, Sourav Ganguly, Ankit Adity...    Seed Funding   \n",
       "45                                         Amen Dhyllon    Seed Funding   \n",
       "...                                                 ...             ...   \n",
       "2169                                Powai Lake Ventures    Seed Funding   \n",
       "2179  Sequoia Capital, Nexus venture Partners, Light...  Private Equity   \n",
       "2185              Accel US, Accel India, SAIF Partners.  Private Equity   \n",
       "2187                    Oliphans Capital, Haresh Chawla    Seed Funding   \n",
       "2193                   Mitsui & Co & existing investors  Private Equity   \n",
       "\n",
       "     AmountInUSD   Remarks  \n",
       "1            NaN       NaN  \n",
       "3        500,000       NaN  \n",
       "10     1,000,000       NaN  \n",
       "17       464,000       NaN  \n",
       "45           NaN       NaN  \n",
       "...          ...       ...  \n",
       "2169         NaN       NaN  \n",
       "2179  18,000,000  Series B  \n",
       "2185  12,000,000  Series B  \n",
       "2187   1,000,000       NaN  \n",
       "2193  21,500,000  Series C  \n",
       "\n",
       "[446 rows x 10 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "686c704c",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=group_a.copy()\n",
    "b=group_b.copy()\n",
    "c=group_c.copy()\n",
    "d=group_d.copy()\n",
    "e=group_e.copy()\n",
    "a.dropna(inplace=True)\n",
    "b.dropna(inplace=True)\n",
    "c.dropna(inplace=True)\n",
    "d.dropna(inplace=True)\n",
    "e.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3885ec36",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'DataFrame' object has no attribute 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[41], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m a1\u001b[38;5;241m=\u001b[39m\u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstr\u001b[49m\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m      2\u001b[0m b1\u001b[38;5;241m=\u001b[39mb\u001b[38;5;241m.\u001b[39mstr\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m      3\u001b[0m c1\u001b[38;5;241m=\u001b[39mc\u001b[38;5;241m.\u001b[39mstr\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[1;32m~\\New folder\\lib\\site-packages\\pandas\\core\\generic.py:5575\u001b[0m, in \u001b[0;36mNDFrame.__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5568\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[0;32m   5569\u001b[0m     name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_internal_names_set\n\u001b[0;32m   5570\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_metadata\n\u001b[0;32m   5571\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_accessors\n\u001b[0;32m   5572\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_info_axis\u001b[38;5;241m.\u001b[39m_can_hold_identifiers_and_holds_name(name)\n\u001b[0;32m   5573\u001b[0m ):\n\u001b[0;32m   5574\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[1;32m-> 5575\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__getattribute__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'str'"
     ]
    }
   ],
   "source": [
    "a1=a.str.replace(',','')\n",
    "b1=b.str.replace(',','')\n",
    "c1=c.str.replace(',','')\n",
    "d1=d.str.replace(',','')\n",
    "e1=e.str.replace(',','')"
   ]
  }
 ],
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    "name": "ipython",
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