facebook_post_consumptions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "159f01d0-75d1-40a9-be31-34d49781ea5c",
   "metadata": {},
   "source": [
    "## **1. Load Libraries and Helper Function**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3e17e003-ca8a-4158-895e-51d8d5eaa017",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Processing and Visualization Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Statistics libraries\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3ffd9ea3-f048-4efb-a04a-4890c3de9a59",
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_outliers(var_name, data):\n",
    "    \"\"\"Function to find outliers in the dataset\n",
    "    \n",
    "    Params\n",
    "    ------\n",
    "    var_name : str\n",
    "        Name of the variable that should be analyzed\n",
    "    data : pd.DataFrame\n",
    "        Pandas dataframe for the variable\n",
    "\n",
    "    Return\n",
    "    ------\n",
    "    outliers : pd.DataFrame\n",
    "        outliers data in pandas DataFrame\n",
    "    \"\"\"\n",
    "\n",
    "    q1 = data[var_name].quantile(0.25)\n",
    "    q3 = data[var_name].quantile(0.75)\n",
    "    iqr = q3 - q1\n",
    "\n",
    "    lower_iqr = data[var_name] < q1 - 1.5*iqr\n",
    "    upper_iqr = data[var_name] > q3 + 1.5*iqr\n",
    "\n",
    "    outliers = data[lower_iqr | upper_iqr]\n",
    "    \n",
    "    return outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8ceb98a7-ca72-4933-b58a-a33f00802f7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def numerical_univariate(var_name, data) -> None:\n",
    "    \"\"\"Procedure for Building kdeplot and boxplot \n",
    "    along with other statistics information\n",
    "\n",
    "    Params\n",
    "    ------\n",
    "    var_name : str\n",
    "        Name of the variable that should be analyzed\n",
    "    data : pd.DataFrame\n",
    "        Pandas dataframe for the variable\n",
    "    \"\"\"\n",
    "\n",
    "    # Create Matplotlib sub-plot and figures\n",
    "    fig, axs = plt.subplots(ncols=2, figsize=(10, 4))\n",
    "\n",
    "    # Draw KDE plot with seaborn on the first axis\n",
    "    sns.kdeplot(x=var_name, data=data, ax=axs[0])\n",
    "\n",
    "    # Draw axvline for kde plot\n",
    "    axs[0].axvline(x=data[var_name].mean(),\n",
    "                   color=\"red\",\n",
    "                   ls=\"--\",\n",
    "                   label=f\"mean: {round(data[var_name].mean(), 3)}\")\n",
    "\n",
    "    # Draw Boxplot with seaborn on the second axis\n",
    "    sns.boxplot(x=var_name, data=data, ax=axs[1])\n",
    "    \n",
    "    # Get legend\n",
    "    axs[0].legend(loc=\"upper right\")\n",
    "\n",
    "    # Name each chart on the axis\n",
    "    axs[0].set_title(f\"KDE Plot for {var_name}\")\n",
    "    axs[1].set_title(f\"Box Plot for {var_name}\")\n",
    "\n",
    "    # Draw all graphs\n",
    "    plt.show()\n",
    "\n",
    "    # Defining Outliers\n",
    "    outliers = find_outliers(var_name, data)\n",
    "    n_outliers = len(outliers)\n",
    "    pct_outliers = round((n_outliers/len(data[var_name]))*100, 3)\n",
    "\n",
    "    # Final Output\n",
    "    print(f\"-------Statistics of {var_name}-------\\n\"\n",
    "          f\"Median   : {data[var_name].median()}\\n\"\n",
    "          f\"Max      : {data[var_name].max()}\\n\"\n",
    "          f\"Min      : {data[var_name].min()}\\n\"\n",
    "          f\"q1       : {data[var_name].quantile(0.25)}\\n\"\n",
    "          f\"q3       : {data[var_name].quantile(0.75)}\\n\"\n",
    "          f\"outliers : {n_outliers} ({pct_outliers}%)\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c0bcc66b-7073-4674-87f2-29f076c15a9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def numerical_bivariate(input_var, target_var, data) -> None:\n",
    "    \"\"\"This procedure is to find visualize the respond variable\n",
    "    with the independent variables.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    input_var : str\n",
    "        The name of the feature\n",
    "\n",
    "    target_var : str\n",
    "        The name of the target variable\n",
    "\n",
    "    data : pd.DataFrame\n",
    "        The dataset\n",
    "    \"\"\"\n",
    "    \n",
    "    # Setup matplotlib subplot and axes\n",
    "    fig, axs = plt.subplots(ncols=2, figsize=(13, 5))\n",
    "\n",
    "    # Visualize kdeplot for the first axis\n",
    "    sns.kdeplot(x=input_var, \n",
    "                y=target_var,\n",
    "                cmap=\"Blues\",\n",
    "                cbar=True,\n",
    "                shade=True,\n",
    "                data=data, \n",
    "                ax=axs[0])\n",
    "\n",
    "    # Visualize scatterplot for the second axis\n",
    "    sns.scatterplot(x=input_var, \n",
    "                    y=target_var, \n",
    "                    data=data, \n",
    "                    ax=axs[1])\n",
    "\n",
    "    # Modify graph name\n",
    "    axs[0].set_title(f\"{input_var} Kde Plot\", fontsize=14)\n",
    "    axs[1].set_title(f\"{input_var} Scatterplot\", fontsize=14)\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6fb7aa76-7eeb-4b2c-9e9e-ef72da1c5788",
   "metadata": {},
   "outputs": [],
   "source": [
    "def categorical_univariate(var_name, data) -> None:\n",
    "    \"\"\"This is a procedure to generate univariate analysis\n",
    "    for categorical variable\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    var_name : str\n",
    "        The name of the categorical feature\n",
    "    \n",
    "    data : pd.DataFrame\n",
    "        The dataset\n",
    "    \"\"\"\n",
    "\n",
    "    # Draw matplotlib figure\n",
    "    fig, ax = plt.subplots(figsize=(7, 5))\n",
    "    \n",
    "    # Visualize seaborn countplot\n",
    "    sns.countplot(x=var_name, data=data, ax=ax)\n",
    "\n",
    "    # Add number of count on each label\n",
    "    ax.bar_label(container=ax.containers[0])\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c1accf54-470c-4d88-994b-9e77bbc8f632",
   "metadata": {},
   "outputs": [],
   "source": [
    "def categorical_bivariate(input_var, target_var, data):\n",
    "    \"\"\"This is a procedure to generate univariate analysis\n",
    "    for categorical variable\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    input_var : str\n",
    "        The name of the categorical feature\n",
    "\n",
    "    target_var : str\n",
    "        The name of the target variable\n",
    "\n",
    "    data : pd.DataFrame\n",
    "        The dataset\n",
    "    \"\"\"\n",
    "\n",
    "    # Draw matplotib figure and axes\n",
    "    fig, ax = plt.subplots(ncols=2, figsize=(13, 5))\n",
    "\n",
    "    # Draw target_var boxplot per input_var\n",
    "    sns.boxplot(x=input_var, \n",
    "                y=target_var, \n",
    "                data=data, \n",
    "                ax=ax[0])\n",
    "\n",
    "    # Draw KDE of target var per input var\n",
    "    sns.kdeplot(x=target_var,\n",
    "                hue=input_var,\n",
    "                data=data)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "    # Defining Outliers\n",
    "    for i in data[input_var].unique().tolist():\n",
    "        filter_data = data[data[input_var] == i]\n",
    "\n",
    "        outliers = find_outliers(var_name=target_var, data=filter_data)\n",
    "        n_outliers = len(outliers)\n",
    "        pct_outliers = round((n_outliers/len(filter_data[target_var]))*100, 3)\n",
    "\n",
    "        # Final Output\n",
    "        print(f\"----Statistics of {target_var} when {input_var} is {i}----\\n\"\n",
    "              f\"Median   : {filter_data[target_var].median()}\\n\"\n",
    "              f\"Max      : {filter_data[target_var].max()}\\n\"\n",
    "              f\"Min      : {filter_data[target_var].min()}\\n\"\n",
    "              f\"q1       : {filter_data[target_var].quantile(0.25)}\\n\"\n",
    "              f\"q3       : {filter_data[target_var].quantile(0.75)}\\n\"\n",
    "              f\"outliers : {n_outliers} ({pct_outliers}%)\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d2cec8d4-08ee-413d-a554-6749fd3f8996",
   "metadata": {},
   "outputs": [],
   "source": [
    "def regression_result(model_fit):\n",
    "    \"\"\"Getting the fitted linear regression model\n",
    "\n",
    "    Params\n",
    "    ------\n",
    "    model_fit : statsmodels.formula.api.ols.fit\n",
    "        the fitted linear regression model results\n",
    "\n",
    "    Return\n",
    "    ------\n",
    "    df : pd.DataFrame\n",
    "        Pandas dataframe conists of regression coefficient and\n",
    "        standard_error\n",
    "    \"\"\"\n",
    "\n",
    "    coef = model_fit.params\n",
    "    std_error = model_fit.bse\n",
    "\n",
    "    df = pd.DataFrame(data=np.transpose([coef, std_error]),\n",
    "                      index=coef.index,\n",
    "                      columns=[\"coef\", \"std_error\"])\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a5e87de-54fd-4a53-88be-f22f9da16895",
   "metadata": {},
   "outputs": [],
   "source": [
    "def multiple_regression_line(target_var,\n",
    "                             predictors,\n",
    "                             data,\n",
    "                             model_fit) -> None:\n",
    "    \"\"\"This procedure to plot multiple regression line\n",
    "\n",
    "    So, far the predictors can only accept numerical and binary predictors.\n",
    "    Also, only 2 predictors are accepted to be processed.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    target_var : str\n",
    "        The name of the target variable\n",
    "\n",
    "    model_fit : statsmodels.formula.api.ols.fit\n",
    "        the fitted linear regression model results\n",
    "\n",
    "    predictors : list\n",
    "        The list of predictors\n",
    "\n",
    "    data : pd.DataFrame\n",
    "        The dataset\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    fitted_values : list\n",
    "        list of valus that was been fitted with regression equation\n",
    "    \"\"\"\n",
    "\n",
    "    # Setup visualization parameter\n",
    "    color = {0: \"b\", 1: \"g\"}\n",
    "    markers = {0: \"x\", 1: \".\"}\n",
    "    linestyles = {0: \"--\", 1: \"-\"}\n",
    "\n",
    "    # Setup the data\n",
    "    df = data.copy()\n",
    "\n",
    "    # Get the regression model data\n",
    "    results = regression_result(model_fit=model_fit)\n",
    "\n",
    "    # Generate Linear Regression Equation\n",
    "    # 1. Load the numerical data\n",
    "    x_domain = np.linspace(np.min(df[predictors[0]]), \n",
    "                       np.max(df[predictors[0]]),\n",
    "                       len(data))\n",
    "\n",
    "    # Use the fitted model coefficient for each\n",
    "    b0 = results.loc[\"Intercept\"][\"coef\"]\n",
    "    b1 = results.loc[predictors[0]][\"coef\"]\n",
    "    b2 = results.loc[predictors[1]][\"coef\"]\n",
    "\n",
    "    # Generate Multivaraite Regression Equation\n",
    "    fitted_values = [b0 + b1*x_domain + b2*i for i in range(2)]\n",
    "\n",
    "    fig, axs = plt.subplots(ncols=3, figsize=(20, 7))\n",
    "\n",
    "    for i in range(len(axs)):\n",
    "        if i == 2:\n",
    "            # Drawing Regrssion line in a single plot\n",
    "            for j in range(2):\n",
    "                axs[i].scatter(df[df[predictors[1]]==j][predictors[0]], \n",
    "                               df[data[predictors[1]]==j][target_var], \n",
    "                               color = color[j], \n",
    "                               marker = markers[j])\n",
    "                axs[i].plot(x_domain, fitted_values[0], \n",
    "                            c = color[j], \n",
    "                            label = f\"Fitted line (paid={j})\", \n",
    "                            linestyle = linestyles[j])\n",
    "\n",
    "                # Modifying plot informaition\n",
    "                axs[i].legend(loc=\"upper left\")\n",
    "                axs[i].set_ylabel(f\"{target_var}\")\n",
    "                axs[i].set_xlabel(f\"{predictors[0]}\")\n",
    "                axs[i].set_title(\"Regression line for paid 1 and 0\")\n",
    "        else:\n",
    "            # Drawing regression line for each paid variable\n",
    "            axs[i].scatter(df[df[predictors[1]] == i][predictors[0]],\n",
    "                           df[df[predictors[1]] == i][target_var],\n",
    "                           marker=markers[i],\n",
    "                           color=color[i])\n",
    "\n",
    "            axs[i].plot(x_domain, \n",
    "                        fitted_values[i], \n",
    "                        label=f\"fitted line (paid={i})\", \n",
    "                        linestyle=linestyles[i],\n",
    "                        c=color[i])\n",
    "\n",
    "        # Modify Axes 0\n",
    "        axs[i].legend(loc=\"upper left\")\n",
    "        axs[i].set_ylabel(f\"{target_var}\")\n",
    "        axs[i].set_xlabel(f\"{predictors[0]}\")\n",
    "        axs[i].set_title(f\"Regression Line with Paid is {i}\",\n",
    "                         fontsize=15)\n",
    "    \n",
    "    plt.suptitle(\"Data and Fitted Regression Line with Interaction\",\n",
    "                 fontsize=15)\n",
    "    plt.show()\n",
    "\n",
    "    return fitted_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d4794464-5007-4e24-ad0e-a47197ffddc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def multi_regression_interaction(target_var,\n",
    "                                 predictors,\n",
    "                                 data,\n",
    "                                 model_fit) -> None:\n",
    "    \"\"\"This is a procedure to draw linear regression with interaction\n",
    "\n",
    "    The procedures only accepts 2 variables.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    target_var : str\n",
    "        The name of the target variable\n",
    "\n",
    "    model_fit : statsmodels.formula.api.ols.fit\n",
    "        the fitted linear regression model results\n",
    "\n",
    "    predictors : list\n",
    "        The list of predictors\n",
    "\n",
    "    data : pd.DataFrame \n",
    "        The dataset\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    fitted_values : list\n",
    "        list of valus that was been fitted with regression equation\n",
    "    \"\"\"\n",
    "\n",
    "    # Setup visualization parameter\n",
    "    color = {0: \"b\", 1: \"g\"}\n",
    "    markers = {0: \"x\", 1: \".\"}\n",
    "    linestyles = {0: \"--\", 1: \"-\"}\n",
    "\n",
    "    # Copy data\n",
    "    df = data.copy()\n",
    "    \n",
    "    # Setup Regression Coefficient\n",
    "    b0 = results.loc[\"Intercept\"][\"coef\"]\n",
    "    b1 = results.loc[predictors[0]][\"coef\"]\n",
    "    b2 = results.loc[predictors[1]][\"coef\"]\n",
    "    b3 = results.loc[predictors[2]][\"coef\"]\n",
    "\n",
    "    # Load the numerical data\n",
    "    x_domain = np.linspace(np.min(df[predictors[0]]), \n",
    "                           np.max(df[predictors[0]]), \n",
    "                           len(data))\n",
    "    \n",
    "    fitted_values = [b0+b1*x_domain+b2*i+b3*i*x_domain for i in range(2)]\n",
    "\n",
    "\n",
    "    # Plotting the graph\n",
    "    fig, ax = plt.subplots(figsize=(9, 6))\n",
    "\n",
    "    for i in range(2):\n",
    "        ax.scatter(df[df[predictors[1]] == i][predictors[0]],\n",
    "                    df[df[predictors[1]] == i][response],\n",
    "                    marker=markers[i],\n",
    "                    color=color[i])\n",
    "\n",
    "    # plot two fitter line\n",
    "    for i in range(2):\n",
    "        ax.plot(x_domain, \n",
    "                fitted_values[i], \n",
    "                label=f\"fitted line (paid={i})\", \n",
    "                linestyle=linestyles[i], \n",
    "                c=color[i])\n",
    "\n",
    "    # Add legends and labels\n",
    "    plt.legend()\n",
    "    plt.ylabel(f\"{response}\")\n",
    "    plt.xlabel(f\"{predictors[0]}\")\n",
    "    plt.title(\"Data and fitted regression line\", fontsize=14)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "    return fitted_values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cbe3cfb7-59e8-4311-9fa5-16ca26a89a9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def residual_plot(fit_model) -> None:\n",
    "    \"\"\"Drawing the residual plot\n",
    "\n",
    "    Params\n",
    "    ------\n",
    "    fit_model : statsmodels.formula.api.ols.fit\n",
    "        The fitted regression model from statsmodel ols module\n",
    "    name : str\n",
    "        The name of the model \n",
    "    \"\"\"\n",
    "\n",
    "    # Get the residual values\n",
    "    fitted_values = fit_model.fittedvalues\n",
    "    residual = fit_model.resid\n",
    "    \n",
    "    # Plotting matplotlib subplit\n",
    "    fig, ax = plt.subplots(figsize=(9, 5))\n",
    "    \n",
    "    # Plotting scatter plot on the axes 1\n",
    "    ax.scatter(x=fitted_values, \n",
    "                   y=residual, \n",
    "                   marker=\".\", \n",
    "                   c=\"k\")\n",
    "\n",
    "    # Plot the axhline at 0\n",
    "    ax.axhline([0])\n",
    "    \n",
    "    # Modify the graph\n",
    "    ax.set_title(\"Residual vs Predicted Values\", fontsize=14)\n",
    "    ax.set_xlabel(\"Predicted values\")\n",
    "    ax.set_ylabel(\"Residual\")\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad52379a-cd7d-4fb7-a48e-3261367fa9ec",
   "metadata": {},
   "source": [
    "## **2. Project Objectives**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "909feda6-bdd7-465b-8da2-e8fb2abde8ea",
   "metadata": {},
   "source": [
    "In this study we would like to understand the impact of the number of likes of a brand page’s and whether their posts use Facebook Ads to promote their post to gain more user to consume their posts.\n",
    "\n",
    "With that in mind, this study would have the following objectives:\n",
    "1. Testing the assumption whether a high number of likes on the brands’ page would impact users to consume posts.\n",
    "2. Testing the assumption whether using Facebook Ads (paying Facebook) would generate more user consumption of a post.\n",
    "3. Investigating the relationship between the total likes of the total likes of a brand page and whether their post is using Facebook Ads or not.\n",
    "4. Building a regression model to predict post consumptions based on the company’s page total likes and whether the post is using Facebook Ads.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6def2ddd-1597-4601-8319-c2f6ef427f42",
   "metadata": {},
   "source": [
    "## **3. Load Data & Basic Checking**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a3b6eaaf-b91f-4de4-b10d-67cdee0af394",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you look at the raw data, the CSV delimiter (separator) is ';'\n",
    "# By defualt the delimiter for CSV in pandas are commas, hence we need to change it\n",
    "\n",
    "facebook_df = pd.read_csv(\"dataset_Facebook.csv\", delimiter=\";\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f704355f-c589-454c-a724-3dcd0cdbbe2d",
   "metadata": {},
   "outputs": [
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       "    .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>Page total likes</th>\n",
       "      <th>Type</th>\n",
       "      <th>Category</th>\n",
       "      <th>Post Month</th>\n",
       "      <th>Post Weekday</th>\n",
       "      <th>Post Hour</th>\n",
       "      <th>Paid</th>\n",
       "      <th>Lifetime Post Total Reach</th>\n",
       "      <th>Lifetime Post Total Impressions</th>\n",
       "      <th>Lifetime Engaged Users</th>\n",
       "      <th>Lifetime Post Consumers</th>\n",
       "      <th>Lifetime Post Consumptions</th>\n",
       "      <th>Lifetime Post Impressions by people who have liked your Page</th>\n",
       "      <th>Lifetime Post reach by people who like your Page</th>\n",
       "      <th>Lifetime People who have liked your Page and engaged with your post</th>\n",
       "      <th>comment</th>\n",
       "      <th>like</th>\n",
       "      <th>share</th>\n",
       "      <th>Total Interactions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>139441</td>\n",
       "      <td>Photo</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2752</td>\n",
       "      <td>5091</td>\n",
       "      <td>178</td>\n",
       "      <td>109</td>\n",
       "      <td>159</td>\n",
       "      <td>3078</td>\n",
       "      <td>1640</td>\n",
       "      <td>119</td>\n",
       "      <td>4</td>\n",
       "      <td>79.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>139441</td>\n",
       "      <td>Status</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10460</td>\n",
       "      <td>19057</td>\n",
       "      <td>1457</td>\n",
       "      <td>1361</td>\n",
       "      <td>1674</td>\n",
       "      <td>11710</td>\n",
       "      <td>6112</td>\n",
       "      <td>1108</td>\n",
       "      <td>5</td>\n",
       "      <td>130.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>139441</td>\n",
       "      <td>Photo</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2413</td>\n",
       "      <td>4373</td>\n",
       "      <td>177</td>\n",
       "      <td>113</td>\n",
       "      <td>154</td>\n",
       "      <td>2812</td>\n",
       "      <td>1503</td>\n",
       "      <td>132</td>\n",
       "      <td>0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>139441</td>\n",
       "      <td>Photo</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50128</td>\n",
       "      <td>87991</td>\n",
       "      <td>2211</td>\n",
       "      <td>790</td>\n",
       "      <td>1119</td>\n",
       "      <td>61027</td>\n",
       "      <td>32048</td>\n",
       "      <td>1386</td>\n",
       "      <td>58</td>\n",
       "      <td>1572.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>139441</td>\n",
       "      <td>Photo</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7244</td>\n",
       "      <td>13594</td>\n",
       "      <td>671</td>\n",
       "      <td>410</td>\n",
       "      <td>580</td>\n",
       "      <td>6228</td>\n",
       "      <td>3200</td>\n",
       "      <td>396</td>\n",
       "      <td>19</td>\n",
       "      <td>325.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>393</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Page total likes    Type  Category  Post Month  Post Weekday  Post Hour   \n",
       "0            139441   Photo         2          12             4          3  \\\n",
       "1            139441  Status         2          12             3         10   \n",
       "2            139441   Photo         3          12             3          3   \n",
       "3            139441   Photo         2          12             2         10   \n",
       "4            139441   Photo         2          12             2          3   \n",
       "\n",
       "   Paid  Lifetime Post Total Reach  Lifetime Post Total Impressions   \n",
       "0   0.0                       2752                             5091  \\\n",
       "1   0.0                      10460                            19057   \n",
       "2   0.0                       2413                             4373   \n",
       "3   1.0                      50128                            87991   \n",
       "4   0.0                       7244                            13594   \n",
       "\n",
       "   Lifetime Engaged Users  Lifetime Post Consumers   \n",
       "0                     178                      109  \\\n",
       "1                    1457                     1361   \n",
       "2                     177                      113   \n",
       "3                    2211                      790   \n",
       "4                     671                      410   \n",
       "\n",
       "   Lifetime Post Consumptions   \n",
       "0                         159  \\\n",
       "1                        1674   \n",
       "2                         154   \n",
       "3                        1119   \n",
       "4                         580   \n",
       "\n",
       "   Lifetime Post Impressions by people who have liked your Page   \n",
       "0                                               3078             \\\n",
       "1                                              11710              \n",
       "2                                               2812              \n",
       "3                                              61027              \n",
       "4                                               6228              \n",
       "\n",
       "   Lifetime Post reach by people who like your Page   \n",
       "0                                              1640  \\\n",
       "1                                              6112   \n",
       "2                                              1503   \n",
       "3                                             32048   \n",
       "4                                              3200   \n",
       "\n",
       "   Lifetime People who have liked your Page and engaged with your post   \n",
       "0                                                119                    \\\n",
       "1                                               1108                     \n",
       "2                                                132                     \n",
       "3                                               1386                     \n",
       "4                                                396                     \n",
       "\n",
       "   comment    like  share  Total Interactions  \n",
       "0        4    79.0   17.0                 100  \n",
       "1        5   130.0   29.0                 164  \n",
       "2        0    66.0   14.0                  80  \n",
       "3       58  1572.0  147.0                1777  \n",
       "4       19   325.0   49.0                 393  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get a glimpse of the data\n",
    "facebook_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bab7a60a-469c-45c4-9d54-cd504f8d736d",
   "metadata": {},
   "source": [
    "**NOTES** If we look at the column name of the data, there are spaces between words. This might cause us some problems in the future, hence the column name would be renamed later "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3181a91d-f978-47c9-9ed5-e8966fef801b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(500, 19)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the dataset shape\n",
    "facebook_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0354fc45-6d64-4b90-a3b8-5395de617934",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 500 entries, 0 to 499\n",
      "Data columns (total 19 columns):\n",
      " #   Column                                                               Non-Null Count  Dtype  \n",
      "---  ------                                                               --------------  -----  \n",
      " 0   Page total likes                                                     500 non-null    int64  \n",
      " 1   Type                                                                 500 non-null    object \n",
      " 2   Category                                                             500 non-null    int64  \n",
      " 3   Post Month                                                           500 non-null    int64  \n",
      " 4   Post Weekday                                                         500 non-null    int64  \n",
      " 5   Post Hour                                                            500 non-null    int64  \n",
      " 6   Paid                                                                 499 non-null    float64\n",
      " 7   Lifetime Post Total Reach                                            500 non-null    int64  \n",
      " 8   Lifetime Post Total Impressions                                      500 non-null    int64  \n",
      " 9   Lifetime Engaged Users                                               500 non-null    int64  \n",
      " 10  Lifetime Post Consumers                                              500 non-null    int64  \n",
      " 11  Lifetime Post Consumptions                                           500 non-null    int64  \n",
      " 12  Lifetime Post Impressions by people who have liked your Page         500 non-null    int64  \n",
      " 13  Lifetime Post reach by people who like your Page                     500 non-null    int64  \n",
      " 14  Lifetime People who have liked your Page and engaged with your post  500 non-null    int64  \n",
      " 15  comment                                                              500 non-null    int64  \n",
      " 16  like                                                                 499 non-null    float64\n",
      " 17  share                                                                496 non-null    float64\n",
      " 18  Total Interactions                                                   500 non-null    int64  \n",
      "dtypes: float64(3), int64(15), object(1)\n",
      "memory usage: 74.3+ KB\n"
     ]
    }
   ],
   "source": [
    "facebook_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c68a0cc-f224-4d40-aada-c90c48a42c48",
   "metadata": {},
   "source": [
    "**Variable of Interest**\n",
    "Not all the variables above would be use because the project objectives. Here are the variable that would be examined throughout this notebook:\n",
    "- **Independent Variables**\n",
    "    - *Page total likes:* Total number of people who have liked the company's Facebook page \n",
    "    - *Paid:* Whether the company paid Facebook to promote their post (using Facebook Ads)\n",
    "- **Response Variable**\n",
    "    - *Lifetime Post Consumption:* The number of clicks anywhere in the post"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd7d571c-089f-4633-8008-238740992a60",
   "metadata": {},
   "source": [
    "## **4. Data Preparation**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bb6c532-707f-42d6-a0cf-9cab57b21374",
   "metadata": {},
   "source": [
    "### **4.1 Changing Column Name**\n",
    "As mentioned above the name of each column contains space, hence we would like to remove the space and replace it with underscore. Also the variable name would be changed to lower case for coding purposes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "79dca486-16a7-406c-b24b-191e784f4cd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Page total likes': 'page_total_likes',\n",
       " 'Type': 'type',\n",
       " 'Category': 'category',\n",
       " 'Post Month': 'post_month',\n",
       " 'Post Weekday': 'post_weekday',\n",
       " 'Post Hour': 'post_hour',\n",
       " 'Paid': 'paid',\n",
       " 'Lifetime Post Total Reach': 'lifetime_post_total_reach',\n",
       " 'Lifetime Post Total Impressions': 'lifetime_post_total_impressions',\n",
       " 'Lifetime Engaged Users': 'lifetime_engaged_users',\n",
       " 'Lifetime Post Consumers': 'lifetime_post_consumers',\n",
       " 'Lifetime Post Consumptions': 'lifetime_post_consumptions',\n",
       " 'Lifetime Post Impressions by people who have liked your Page': 'lifetime_post_impressions_by_people_who_have_liked_your_page',\n",
       " 'Lifetime Post reach by people who like your Page': 'lifetime_post_reach_by_people_who_like_your_page',\n",
       " 'Lifetime People who have liked your Page and engaged with your post': 'lifetime_people_who_have_liked_your_page_and_engaged_with_your_post',\n",
       " 'comment': 'comment',\n",
       " 'like': 'like',\n",
       " 'share': 'share',\n",
       " 'Total Interactions': 'total_interactions'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the current columns name\n",
    "current_columns = [ col for col in facebook_df.columns.tolist() ]\n",
    "\n",
    "# Prepare the new columns name\n",
    "new_columns = []\n",
    "for col in current_columns:\n",
    "    # split the column name by space and join with underscore \n",
    "    # and lowercasing it\n",
    "    col_name = \"_\".join(col.split(\" \")).lower()\n",
    "\n",
    "    # Append the new column name to the new columns\n",
    "    new_columns.append(col_name)\n",
    "\n",
    "# Mapped the current column name and the new column name into dictionary\n",
    "columns_map = dict(zip(current_columns, new_columns))\n",
    "columns_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0f072777-f4d5-4d64-81ae-f221890f42df",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename the column\n",
    "facebook_df.rename(columns_map, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aaf10fcf-43fa-4b00-acbc-61864bbf7b66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 500 entries, 0 to 499\n",
      "Data columns (total 19 columns):\n",
      " #   Column                                                               Non-Null Count  Dtype  \n",
      "---  ------                                                               --------------  -----  \n",
      " 0   page_total_likes                                                     500 non-null    int64  \n",
      " 1   type                                                                 500 non-null    object \n",
      " 2   category                                                             500 non-null    int64  \n",
      " 3   post_month                                                           500 non-null    int64  \n",
      " 4   post_weekday                                                         500 non-null    int64  \n",
      " 5   post_hour                                                            500 non-null    int64  \n",
      " 6   paid                                                                 499 non-null    float64\n",
      " 7   lifetime_post_total_reach                                            500 non-null    int64  \n",
      " 8   lifetime_post_total_impressions                                      500 non-null    int64  \n",
      " 9   lifetime_engaged_users                                               500 non-null    int64  \n",
      " 10  lifetime_post_consumers                                              500 non-null    int64  \n",
      " 11  lifetime_post_consumptions                                           500 non-null    int64  \n",
      " 12  lifetime_post_impressions_by_people_who_have_liked_your_page         500 non-null    int64  \n",
      " 13  lifetime_post_reach_by_people_who_like_your_page                     500 non-null    int64  \n",
      " 14  lifetime_people_who_have_liked_your_page_and_engaged_with_your_post  500 non-null    int64  \n",
      " 15  comment                                                              500 non-null    int64  \n",
      " 16  like                                                                 499 non-null    float64\n",
      " 17  share                                                                496 non-null    float64\n",
      " 18  total_interactions                                                   500 non-null    int64  \n",
      "dtypes: float64(3), int64(15), object(1)\n",
      "memory usage: 74.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# Verify the column\n",
    "facebook_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48435039-4e10-4347-ae79-df4b33be965b",
   "metadata": {},
   "source": [
    "### **4.2 Handling Missing Value**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0422ac5a-e95a-4e8d-8c22-44fc5211517e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "page_total_likes                                                       0.0\n",
       "type                                                                   0.0\n",
       "category                                                               0.0\n",
       "post_month                                                             0.0\n",
       "post_weekday                                                           0.0\n",
       "post_hour                                                              0.0\n",
       "paid                                                                   0.2\n",
       "lifetime_post_total_reach                                              0.0\n",
       "lifetime_post_total_impressions                                        0.0\n",
       "lifetime_engaged_users                                                 0.0\n",
       "lifetime_post_consumers                                                0.0\n",
       "lifetime_post_consumptions                                             0.0\n",
       "lifetime_post_impressions_by_people_who_have_liked_your_page           0.0\n",
       "lifetime_post_reach_by_people_who_like_your_page                       0.0\n",
       "lifetime_people_who_have_liked_your_page_and_engaged_with_your_post    0.0\n",
       "comment                                                                0.0\n",
       "like                                                                   0.2\n",
       "share                                                                  0.8\n",
       "total_interactions                                                     0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking missing value\n",
    "(facebook_df.isnull().sum()/facebook_df.shape[0])*100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31ed6a30-9124-4c69-bc7b-59013949c459",
   "metadata": {},
   "source": [
    "Total missing values doesn't significant towards the entire dataset. Dropping these values would not likely cause bias in when modeling the regression."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8b74af95-f61a-4964-8b0e-75b15be04ba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping Missing Value\n",
    "facebook_df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "98beea2d-903e-4c54-9f8f-b4ac3d42fc78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "page_total_likes                                                       0.0\n",
       "type                                                                   0.0\n",
       "category                                                               0.0\n",
       "post_month                                                             0.0\n",
       "post_weekday                                                           0.0\n",
       "post_hour                                                              0.0\n",
       "paid                                                                   0.0\n",
       "lifetime_post_total_reach                                              0.0\n",
       "lifetime_post_total_impressions                                        0.0\n",
       "lifetime_engaged_users                                                 0.0\n",
       "lifetime_post_consumers                                                0.0\n",
       "lifetime_post_consumptions                                             0.0\n",
       "lifetime_post_impressions_by_people_who_have_liked_your_page           0.0\n",
       "lifetime_post_reach_by_people_who_like_your_page                       0.0\n",
       "lifetime_people_who_have_liked_your_page_and_engaged_with_your_post    0.0\n",
       "comment                                                                0.0\n",
       "like                                                                   0.0\n",
       "share                                                                  0.0\n",
       "total_interactions                                                     0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Re-checking the missing value\n",
    "(facebook_df.isnull().sum()/facebook_df.shape[0])*100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67fdf46a-7b5d-41eb-9970-98e78550ddc0",
   "metadata": {},
   "source": [
    "**Note** There is no longer missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "702288f7-b856-4f93-9767-679f367cc5ea",
   "metadata": {},
   "source": [
    "### **4.2 Checking Duplicates**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "252b66e4-a6dd-4245-9f96-48cde0f9cb6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "facebook_df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "eb08cfb1-ec3f-4717-b198-1a1904dd0bfc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>page_total_likes</th>\n",
       "      <th>type</th>\n",
       "      <th>category</th>\n",
       "      <th>post_month</th>\n",
       "      <th>post_weekday</th>\n",
       "      <th>post_hour</th>\n",
       "      <th>paid</th>\n",
       "      <th>lifetime_post_total_reach</th>\n",
       "      <th>lifetime_post_total_impressions</th>\n",
       "      <th>lifetime_engaged_users</th>\n",
       "      <th>lifetime_post_consumers</th>\n",
       "      <th>lifetime_post_consumptions</th>\n",
       "      <th>lifetime_post_impressions_by_people_who_have_liked_your_page</th>\n",
       "      <th>lifetime_post_reach_by_people_who_like_your_page</th>\n",
       "      <th>lifetime_people_who_have_liked_your_page_and_engaged_with_your_post</th>\n",
       "      <th>comment</th>\n",
       "      <th>like</th>\n",
       "      <th>share</th>\n",
       "      <th>total_interactions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [page_total_likes, type, category, post_month, post_weekday, post_hour, paid, lifetime_post_total_reach, lifetime_post_total_impressions, lifetime_engaged_users, lifetime_post_consumers, lifetime_post_consumptions, lifetime_post_impressions_by_people_who_have_liked_your_page, lifetime_post_reach_by_people_who_like_your_page, lifetime_people_who_have_liked_your_page_and_engaged_with_your_post, comment, like, share, total_interactions]\n",
       "Index: []"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "facebook_df[facebook_df.duplicated()]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1080d464-525d-45d7-aafa-14ed371f17d9",
   "metadata": {},
   "source": [
    "**Note** There is no duplicate in the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "521945ac-c101-49bd-b193-d9a56d1ee91a",
   "metadata": {},
   "source": [
    "## **5. Exploratory Data Analysis**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baa0c4b0-a84e-4566-8b4e-7e04609da75e",
   "metadata": {},
   "source": [
    "### **5.1 Page Total Likes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cf8f629c-bd3e-4d7f-a0fb-f1076970c89a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Statistics of page_total_likes-------\n",
      "Median   : 129600.0\n",
      "Max      : 139441\n",
      "Min      : 81370\n",
      "q1       : 112324.0\n",
      "q3       : 136393.0\n",
      "outliers : 0 (0.0%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Univariate Analysis\n",
    "numerical_univariate(var_name=\"page_total_likes\",\n",
    "                     data=facebook_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "034ec031-f21b-4f9b-8f23-28c6d5ecebb0",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- The distribution is skewed positively (to the right)\n",
    "- There are no outliers in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c9386255-9e8d-409a-9aea-3910751a03fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_36248/3867806122.py:21: FutureWarning: \n",
      "\n",
      "`shade` is now deprecated in favor of `fill`; setting `fill=True`.\n",
      "This will become an error in seaborn v0.14.0; please update your code.\n",
      "\n",
      "  sns.kdeplot(x=input_var,\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bivariate Analysis\n",
    "numerical_bivariate(input_var=\"page_total_likes\",\n",
    "                    target_var=\"lifetime_post_consumptions\",\n",
    "                    data=facebook_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4459f905-3601-40bd-b644-0e5d4e777526",
   "metadata": {},
   "source": [
    "**Summary**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d150d69f-385e-4299-8710-84a0c043ef35",
   "metadata": {},
   "source": [
    "### **5.2 Paid**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "faa979ba-7ee1-4565-99b3-84d8f47b1541",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# univariate analysis\n",
    "categorical_univariate(var_name=\"paid\",\n",
    "                       data=facebook_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f945ce51-02b6-44ac-a328-3f6e47ab28bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----Statistics of lifetime_post_consumptions when paid is 0.0----\n",
      "Median   : 837.0\n",
      "Max      : 14974\n",
      "Min      : 19\n",
      "q1       : 486.75\n",
      "q3       : 1425.5\n",
      "outliers : 33 (9.27%)\n",
      "\n",
      "----Statistics of lifetime_post_consumptions when paid is 1.0----\n",
      "Median   : 874.0\n",
      "Max      : 19779\n",
      "Min      : 9\n",
      "q1       : 597.5\n",
      "q3       : 1676.0\n",
      "outliers : 13 (9.353%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Bivariate Analysis\n",
    "categorical_bivariate(input_var=\"paid\",\n",
    "                      target_var=\"lifetime_post_consumptions\",\n",
    "                      data=facebook_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0434f4bc-6fd7-476a-89c3-200447777e7e",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- The distribution of lifetime post consumptions for both paid or not are skewed negatively. \n",
    "- There are outliers for each lifetime post consumptions when paid variable is 0 or 1. The outliers are from the lifetime_post_consumptions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4754664a-4c9e-4906-91e0-d351c9f60378",
   "metadata": {},
   "source": [
    "### **5.3 Lifetime Post Consumptions**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9ee10423-69ba-4494-8116-3bdc673addd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Statistics of lifetime_post_consumptions-------\n",
      "Median   : 861.0\n",
      "Max      : 19779\n",
      "Min      : 9\n",
      "q1       : 512.5\n",
      "q3       : 1479.0\n",
      "outliers : 48 (9.697%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "numerical_univariate(var_name=\"lifetime_post_consumptions\",\n",
    "                     data=facebook_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "737ee0e7-e2f9-4fb6-9417-67dccba0766a",
   "metadata": {},
   "source": [
    "**Notes** \n",
    "- The outliers are still under 10% of our total data. Dropping all of the outliers would be harsh. Instead we would like to drop only 5% of the outliers, which means dropping around 50% of the outliers data.\n",
    "- To select which outliers to drop we would investigate the distribution of the outlier data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b6aaab9e-1c6c-40fb-88a1-9ca85967eccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get outliers data\n",
    "outliers = find_outliers(var_name=\"lifetime_post_consumptions\",\n",
    "                         data=facebook_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "cea1ac6e-c04d-4bfd-a25c-a0d1b6b24728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Statistics of lifetime_post_consumptions-------\n",
      "Median   : 4573.0\n",
      "Max      : 19779\n",
      "Min      : 2969\n",
      "q1       : 3394.0\n",
      "q3       : 7458.75\n",
      "outliers : 3 (6.25%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Find the distributions of the outliers\n",
    "numerical_univariate(var_name=\"lifetime_post_consumptions\",\n",
    "                     data=outliers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ecf18bd-6abd-4121-acc5-73ee3c88d94e",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- The outliers are also have outliers.\n",
    "- The outliers distribution is skewed to the right\n",
    "- From this distribution we would like to drop the outliers that have a value more than its median of the outliers data. Which means we dropped 50% of the total current outliers data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c7de00e-9f31-4f86-b699-d794b30fa1b4",
   "metadata": {},
   "source": [
    "#### **5.3.1 Dropping Outliers**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d4289132-55e5-4025-b5d3-d53a67a696a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the the median\n",
    "med = outliers[\"lifetime_post_consumptions\"].median()\n",
    "\n",
    "# Get the dropped outliers data\n",
    "dropped_outliers = outliers[outliers[\"lifetime_post_consumptions\"] > med]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "53aeb275-a991-4674-8462-214525552ffd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping outliers on the whole data\n",
    "facebook_df.drop(dropped_outliers.index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "13625d9e-e1f0-4ca6-ad3f-dbcc1f8ab051",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Statistics of lifetime_post_consumptions-------\n",
      "Median   : 832.0\n",
      "Max      : 4550\n",
      "Min      : 9\n",
      "q1       : 499.0\n",
      "q3       : 1384.0\n",
      "outliers : 35 (7.431%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Verify the data distribution\n",
    "numerical_univariate(var_name=\"lifetime_post_consumptions\",\n",
    "                     data=facebook_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b692c02-fdb1-41fd-befa-b06514bf54fd",
   "metadata": {},
   "source": [
    "**Notes** Despite having removing the outliers we keep getting outliers, this is normal because the skewedness of our data is too steep, hence there would be more outliers coming until the mean is moving to the center."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd7cdfb8-de22-4c67-a0e8-a7c36a5954c0",
   "metadata": {},
   "source": [
    "### **5.3 Correlation Analysis**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e1cbf271-62ee-48a4-abbf-848faa7637e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get correlation heatmap for the independent variables and the response only\n",
    "selected_var = [\"page_total_likes\",\n",
    "                \"paid\",\n",
    "                \"lifetime_post_consumptions\"]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7, 7))\n",
    "\n",
    "sns.heatmap(facebook_df[selected_var].corr(), annot=True, fmt=\".2F\")\n",
    "plt.title(\"Correlation Between Independent and Response Variables\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82628c68-a1ca-41cd-8903-88f71712489e",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- The correlation between independent variables and the target is weak\n",
    "- Also there is no sign of multicollinearity in between out independent variables."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8db8a55-cbc1-4e2b-91e0-cc0b0003729f",
   "metadata": {},
   "source": [
    "## **6. Hypothesis Testing**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7168538-e79d-4a7b-8426-864c8f4bb73b",
   "metadata": {},
   "source": [
    "### **6.1 Hypothesis Testing: Page Total Likes**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eea99c8-7d66-4780-b139-88e84fc5f379",
   "metadata": {},
   "source": [
    "Based on the correlation analysis, we've found that the relationship between page total likes and the lifetime post consumptions is negative, which means the less page total likes, the lifetime post consumptions is also less. From this information we could derive a hypothesis as follows:\n",
    "\n",
    "> The average lifetime post consumption with page total likes less than its average would be lower than the average lifetime post consumption with page total likes higher that its average\n",
    "\n",
    "with the average total page likes is 123173.269, we could create the following notation:\n",
    "\n",
    "- $\\mu_A$: The average lifetime post consumption with page total likes less than 123173\n",
    "- $\\mu_B$: The average lifetime post consumption with page total likes greater than 123173\n",
    "\n",
    "Hence, we could develop the following null hypothesis\n",
    "$$H_0:\\mu_A \\le \\mu_B$$\n",
    "$$H_A:\\mu_A > \\mu_B$$\n",
    "\n",
    "From this we could define the test statistics:\n",
    "- the significance or ($\\alpha$) is 0.05\n",
    "- The statistic test that would be used is **right-tail** t-test statistics test because we don't know the standard deviation of the population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "148efbbd-5cdf-4ba8-bd8f-29198bba7440",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the alpha\n",
    "alpha = 0.05\n",
    "\n",
    "# Define the average of page total likes\n",
    "avg_page_total = facebook_df[\"page_total_likes\"].mean()\n",
    "\n",
    "# filter to group whether page total likes is less or greater than its average\n",
    "filter_a = facebook_df[\"page_total_likes\"] > avg_page_total\n",
    "filter_b = facebook_df[\"page_total_likes\"] < avg_page_total\n",
    "\n",
    "mu_a = facebook_df[filter_a][\"lifetime_post_consumptions\"]\n",
    "mu_b = facebook_df[filter_b][\"lifetime_post_consumptions\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb59d9fa-490d-4819-b505-6d37b11a71ae",
   "metadata": {},
   "source": [
    "before we run the test we need to check the variance between mu_a and mu_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d1b30c5c-0528-41b5-afa0-69fea9634795",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance mu_a:  682585.1869462798\n",
      "Variance mu_b:  684348.3827156507\n"
     ]
    }
   ],
   "source": [
    "print(\"Variance mu_a: \", np.var(mu_a))\n",
    "print(\"Variance mu_b: \", np.var(mu_b))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0db4433d-28f4-4667-af07-b2edb6b0491a",
   "metadata": {},
   "source": [
    "**Notes** Tha variance is almost the same, hence we would use the standard two sample t-test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "88187f8d-6fc4-4f1c-b4cc-5165c8ff6b49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t_stat:  -4.261240481718212\n",
      "p-value:  0.9999877085843641\n",
      "Failed to reject the Null Hyptohesis\n",
      "\n",
      "p-value is 0.9999877085843641 and alpha is 0.05\n"
     ]
    }
   ],
   "source": [
    "# Running the t-test statistics\n",
    "t_stat, p_value = ttest_ind(a=mu_a,\n",
    "                            b=mu_b,\n",
    "                            equal_var=True,\n",
    "                            random_state=123,\n",
    "                            alternative=\"greater\")\n",
    "\n",
    "print(\"t_stat: \", t_stat)\n",
    "print(\"p-value: \", p_value) \n",
    "\n",
    "if p_value > alpha:\n",
    "    print(\"Failed to reject the Null Hyptohesis\\n\")\n",
    "else:\n",
    "    print(\"Reject the Null Hypothesis\\n\")\n",
    "\n",
    "print(f\"p-value is {p_value} and alpha is {alpha}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "138e94d6-9607-43b7-9dd8-977038961b65",
   "metadata": {},
   "source": [
    "As we can see that p_value is greater than alpha which means we failed to reject the Null Hypothesis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c51621d-d679-49e4-a03d-66acca98bf25",
   "metadata": {},
   "source": [
    "### **6.2 Hypothesis Testing: Paid variable and the lifetime post consumptions**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38b40ef6-5f71-455e-86f9-449b658e8ae7",
   "metadata": {},
   "source": [
    "When the company paid Facebook (using Facebook ads) to promote their posts the lifetime post consumption should be greater than the lifetime post consumption without facebook ads because by using Facebook Ads, companies can have more people see the posts which can lead to consumers clicking like, share, comment, etc.\n",
    "\n",
    "With that in mind, we could have the following hypothesis\n",
    "\n",
    "> the lifetime post consumption should be grater than the the lifetime post consumption without facebook ads because by using Facebook Ads\n",
    "\n",
    "From the assumption we could create the following notation:\n",
    "\n",
    "- $\\mu_A$: The average lifetime post consumption with that paid Facebook\n",
    "- $\\mu_B$: The average lifetime post consumption without paying Facebook\n",
    "\n",
    "Hence, we could develop the following null hypothesis\n",
    "$$H_0:\\mu_A \\ge \\mu_B$$\n",
    "$$H_A:\\mu_A < \\mu_B$$\n",
    "\n",
    "From this we could define the test statistics:\n",
    "- the significance or ($\\alpha$) is 0.05\n",
    "- The statistic test that would be used is **left-tail** t-test statistics test because we don't know the standard deviation of the population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ad837c31-3b7a-4946-989e-4c795c729b3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define alpha\n",
    "alpha = 0.05\n",
    "\n",
    "# define filter\n",
    "# filter to group whether page total likes is less or greater than its average\n",
    "filter_a = facebook_df[\"paid\"] == 1\n",
    "filter_b = facebook_df[\"paid\"] == 0\n",
    "\n",
    "mu_a = facebook_df[filter_a][\"lifetime_post_consumptions\"]\n",
    "mu_b = facebook_df[filter_b][\"lifetime_post_consumptions\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd6d47ce-2599-4705-b47d-07953023ba25",
   "metadata": {},
   "source": [
    "before we run the test we need to check the variance between mu_a and mu_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5275687c-b420-49f1-b873-d6113f37caa2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance mu_a:  568730.4110717773\n",
      "Variance mu_b:  762234.6071789816\n"
     ]
    }
   ],
   "source": [
    "print(\"Variance mu_a: \", np.var(mu_a))\n",
    "print(\"Variance mu_b: \", np.var(mu_b))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbd1d8f1-cb02-4e0f-abc8-5e545fda4141",
   "metadata": {},
   "source": [
    "The variance is not equal, hence we would use the Welch's t-test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b87e3338-cb06-4bf5-89f0-157d2a9f2395",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t_stat:  0.1810100023739521\n",
      "p-value:  0.571781040150655\n",
      "Failed to reject the Null Hyptohesis\n",
      "\n",
      "p-value is 0.571781040150655 and alpha is 0.05\n"
     ]
    }
   ],
   "source": [
    "# Running the t-test statistics\n",
    "t_stat, p_value = ttest_ind(a=mu_a,\n",
    "                            b=mu_b,\n",
    "                            equal_var=True,\n",
    "                            random_state=123,\n",
    "                            alternative=\"less\")\n",
    "\n",
    "print(\"t_stat: \", t_stat)\n",
    "print(\"p-value: \", p_value) \n",
    "\n",
    "if p_value > alpha:\n",
    "    print(\"Failed to reject the Null Hyptohesis\\n\")\n",
    "else:\n",
    "    print(\"Reject the Null Hypothesis\\n\")\n",
    "\n",
    "print(f\"p-value is {p_value} and alpha is {alpha}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58eb4493-90a2-4ccb-a9d2-548bd87dae0e",
   "metadata": {},
   "source": [
    "As we can see that p_value is greater than alpha which means we failed to reject the Null Hypothesis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "258b8319-2b08-44dc-ae8a-b62147945cc7",
   "metadata": {},
   "source": [
    "## **7. Modelling with Linear Regression**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "1f0c6303-76aa-4cfe-ba51-b9236599f2d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "fb_model = ols(\"lifetime_post_consumptions ~ page_total_likes + paid\",\n",
    "               data=facebook_df)\n",
    "fb_model_fit = fb_model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "432bb44a-384d-47a4-bdd9-23d2ba89710b",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 2000x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup data\n",
    "predictors = [\"page_total_likes\", \"paid\"]\n",
    "target_var = \"lifetime_post_consumptions\"\n",
    "\n",
    "fit_values = multiple_regression_line(target_var=target_var,\n",
    "                                      predictors=predictors,\n",
    "                                      data=facebook_df,\n",
    "                                      model_fit=fb_model_fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42785129-1b59-4096-8659-aaab22527dcd",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- There is no substantial difference between slope at paid 0 and paid 1, hence we could interpret the coefficient directly. But we could directly interpret this regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "34b61641-e438-4ace-a68c-59d2dacb8b34",
   "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>coef</th>\n",
       "      <th>std_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Intercept</th>\n",
       "      <td>2662.255340</td>\n",
       "      <td>288.994238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_total_likes</th>\n",
       "      <td>-0.013023</td>\n",
       "      <td>0.002320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>paid</th>\n",
       "      <td>20.280763</td>\n",
       "      <td>84.730478</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         coef   std_error\n",
       "Intercept         2662.255340  288.994238\n",
       "page_total_likes    -0.013023    0.002320\n",
       "paid                20.280763   84.730478"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_result(fb_model_fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e055c103-ecc6-4178-8de9-977c38fb09bb",
   "metadata": {},
   "source": [
    "**Coefficient Interpretation**\n",
    "$$\\text{lifetime_post_consumptions} = 2457.41 - 0.012\\text{page_total_likes} - 13\\text{paid}$$\n",
    "\n",
    "- The model predicts lifetime post consumptions that don't pay Facebook and has 0 page total likes is 2457.41\n",
    "- The coefficient of paid: If we compare the lifetime post consumptions that have the same page total_likes but differs whether the company's paid facebook or not, the expected difference of the lifetime post consumptions is 13\n",
    "- The coefficient of the page total likes: If we compare the lifetime post consumptions that paid facebook but differs 1 point in the paid total likes, the expected difference of lifetime post consumption is 0.012"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53decbe2-2180-4c59-a49e-aba12e76bd35",
   "metadata": {},
   "source": [
    "**Conclusion**\n",
    "- From this interpretation we could see that page total likes are contributing so little to the lifetime post consumption, although it would reduce its average. \n",
    "- On the other hand, whether the company is using Facebook or not the average of lifetime post consumption would reduce\n",
    "-  the company might want to increase their total page likes because if it won’t increase their lifetime post consumption might also reduce from time to time.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85fcea54-9e64-4b79-80f6-21407c322182",
   "metadata": {},
   "source": [
    "### **7.1 Regression With Interaction**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "03f6f471-5bbb-4020-a94d-2c0e81e6b506",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_int = ols(\"lifetime_post_consumptions ~ page_total_likes + paid + paid:page_total_likes\",\n",
    "                data=facebook_df)\n",
    "model_int_fit = model_int.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c0c63c8c-120f-447e-83f9-96e10d8a9d8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictors = [\"page_total_likes\", \"paid\", \"paid:page_total_likes\"]\n",
    "response = \"lifetime_post_consumptions\"\n",
    "results = regression_result(model_fit=model_int_fit)\n",
    "\n",
    "fit_value = multi_regression_interaction(target_var=response,\n",
    "                                         predictors=predictors,\n",
    "                                         data=facebook_df,\n",
    "                                         model_fit=model_int_fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d098d7d0-46b1-4c6f-adb3-e18cbc14dc60",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "There is a slight difference in slope, which we can't see when we are not using interaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d26517e1-f7c0-434e-9f68-332c3ea8cb2e",
   "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>coef</th>\n",
       "      <th>std_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Intercept</th>\n",
       "      <td>2583.036763</td>\n",
       "      <td>331.758848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_total_likes</th>\n",
       "      <td>-0.012380</td>\n",
       "      <td>0.002671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>paid</th>\n",
       "      <td>345.244567</td>\n",
       "      <td>672.012869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>paid:page_total_likes</th>\n",
       "      <td>-0.002634</td>\n",
       "      <td>0.005404</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              coef   std_error\n",
       "Intercept              2583.036763  331.758848\n",
       "page_total_likes         -0.012380    0.002671\n",
       "paid                    345.244567  672.012869\n",
       "paid:page_total_likes    -0.002634    0.005404"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_result(model_int_fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04f25ed6",
   "metadata": {},
   "source": [
    "$$\\text{lifetime_post_consumptions} = 2342.98 - 0.011\\text{page_total_likes} + 464.12\\text{paid} - 0.004\\text{paid*page_total_likes}$$\n",
    "\n",
    "**Interpretation**\n",
    "$$\\text{paid}=0, \\text{lifetime_post_consumptions} = 2342.98 + 0.011\\text{paid}$$\n",
    "- The estimated difference between lifetime_post_consumptions that is not paid Facebook but differ 1 point in page_total_likes is 0.011\n",
    "\n",
    "$$\\text{paid}=1, \\text{lifetime_post_consumptions} = 2807.1 + 0.015\\text{paid}$$\n",
    "- The estimated difference between lifetime_post_consumptions that is using paid Facebook but differ 1 point in page_total_likes is 0.015\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a25f167b-0bd3-4fb4-96a3-541ae5752eb5",
   "metadata": {},
   "source": [
    "**Conclusion**\n",
    "there is no significant difference whether the company pays Facebook or not to promote their campaign towards the post consumption"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65a5da6f-4281-46ef-8eeb-447a4ac35d1a",
   "metadata": {},
   "source": [
    "### **7.2 Evaluation**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "497f416a-fd2a-47ac-ab69-3ce28c0190d4",
   "metadata": {},
   "source": [
    "### **7.2.1 Evaluating Model without Interaction**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "61a9ef52-7916-43ce-8be6-27bf346c95ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residual_plot(fb_model_fit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "267cb772-dcbb-451b-918d-76dc65edf4e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06313643873428232"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fb_model_fit.rsquared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c22d9cef-2901-4393-9924-71c56b71c687",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residual_plot(model_int_fit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3fb1c29c-0f32-4a20-b5ea-97142c98723b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06361289646753976"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_int_fit.rsquared"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "504fc695-1a60-4043-a224-12c4e4d755e4",
   "metadata": {},
   "source": [
    "**Summary**\n",
    "- For both models (interaction and no interaction) The residual plot shows that the data is centered around the 0 line within 1 standard deviation. Although there is some data that is outside.\n",
    "- The R squared for the model without interaction and with interaction are around 0.063, showing that the model is pretty accurate\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fbmetric-venv",
   "language": "python",
   "name": "fbmetric-venv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}