non_to_vol.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "This notebook answers the following question:  \n",
    "\n",
    "- What is the probability of a non-volunteer becoming a volunteer ?\n",
    "\n",
    "\n",
    "by Fred Etter - December, 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import modules\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from sklearn import linear_model\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn import preprocessing\n",
    "import sklearn\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "from datetime import datetime\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn import metrics\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in the data\n",
    "df = pd.read_csv('file1_12_3.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>ContactId</th>\n",
       "      <th>Year</th>\n",
       "      <th>PledgeTotal</th>\n",
       "      <th>VolType</th>\n",
       "      <th>VolunteerActivityCnt</th>\n",
       "      <th>BirthYear</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>874ddbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>52.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>9a4ddbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>80.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>5e4edbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>10000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>c150dbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>120.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0b53dbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>500.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1947.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              ContactId  Year  PledgeTotal VolType  \\\n",
       "0  874ddbce-11cd-e111-941f-00259073dc22  2007        52.00     NaN   \n",
       "1  9a4ddbce-11cd-e111-941f-00259073dc22  2007        80.00     NaN   \n",
       "2  5e4edbce-11cd-e111-941f-00259073dc22  2007     10000.00     NaN   \n",
       "3  c150dbce-11cd-e111-941f-00259073dc22  2007       120.00     NaN   \n",
       "4  0b53dbce-11cd-e111-941f-00259073dc22  2007       500.16     NaN   \n",
       "\n",
       "   VolunteerActivityCnt  BirthYear  Gender  \n",
       "0                   NaN     1977.0  female  \n",
       "1                   NaN     1968.0  female  \n",
       "2                   NaN     1958.0    male  \n",
       "3                   NaN        NaN    male  \n",
       "4                   NaN     1947.0  female  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show the first 5 lines of the data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(385722, 7)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show the number of rows and columns of the original data\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop Council, Committe, Board members\n",
    "df = df.drop(df[df.VolType == 'Council, Committe or Board'].index).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>ContactId</th>\n",
       "      <th>Year</th>\n",
       "      <th>PledgeTotal</th>\n",
       "      <th>VolType</th>\n",
       "      <th>VolunteerActivityCnt</th>\n",
       "      <th>BirthYear</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>233549</td>\n",
       "      <td>d846b1d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2013</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135350</td>\n",
       "      <td>beda8c60-3a92-e211-a0e0-4040184c1c1a</td>\n",
       "      <td>2012</td>\n",
       "      <td>130.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>212221</td>\n",
       "      <td>e5c799cf-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2010</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>249809</td>\n",
       "      <td>63ba55d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2015</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>71833</td>\n",
       "      <td>be757cf1-7591-e611-97d4-26d4160798d6</td>\n",
       "      <td>2016</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54621</td>\n",
       "      <td>4ace55d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2014</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>231015</td>\n",
       "      <td>e64cb1d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2012</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>367801</td>\n",
       "      <td>44bf55d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2018</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>122641</td>\n",
       "      <td>11be55d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313215</td>\n",
       "      <td>684ae8cf-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year  PledgeTotal VolType  \\\n",
       "233549  d846b1d1-11cd-e111-941f-00259073dc22  2013        104.0       0   \n",
       "135350  beda8c60-3a92-e211-a0e0-4040184c1c1a  2012        130.0       0   \n",
       "212221  e5c799cf-11cd-e111-941f-00259073dc22  2010         24.0       0   \n",
       "249809  63ba55d0-11cd-e111-941f-00259073dc22  2015         52.0       0   \n",
       "71833   be757cf1-7591-e611-97d4-26d4160798d6  2016         25.0       0   \n",
       "54621   4ace55d0-11cd-e111-941f-00259073dc22  2014         52.0       0   \n",
       "231015  e64cb1d1-11cd-e111-941f-00259073dc22  2012         26.0       0   \n",
       "367801  44bf55d0-11cd-e111-941f-00259073dc22  2018       1040.0       0   \n",
       "122641  11be55d0-11cd-e111-941f-00259073dc22  2011         24.0       0   \n",
       "313215  684ae8cf-11cd-e111-941f-00259073dc22  2011       1001.0       0   \n",
       "\n",
       "        VolunteerActivityCnt  BirthYear  Gender  \n",
       "233549                   0.0        0.0  female  \n",
       "135350                   0.0        0.0  female  \n",
       "212221                   0.0        0.0  female  \n",
       "249809                   0.0     1979.0  female  \n",
       "71833                    0.0        0.0    male  \n",
       "54621                    0.0        0.0  female  \n",
       "231015                   0.0        0.0  female  \n",
       "367801                   0.0        0.0  female  \n",
       "122641                   0.0        0.0  female  \n",
       "313215                   0.0     1972.0    male  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_non_only = df.drop(df[df.VolType == 'Standard'].index).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a series that captures the earliest year that a non-volunteer donated\n",
    "a = df_non_only.groupby('ContactId')['Year'].transform('min')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a new column and populate it:\n",
    "df_non_only['min_year'] = a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>ContactId</th>\n",
       "      <th>Year</th>\n",
       "      <th>PledgeTotal</th>\n",
       "      <th>VolType</th>\n",
       "      <th>VolunteerActivityCnt</th>\n",
       "      <th>BirthYear</th>\n",
       "      <th>Gender</th>\n",
       "      <th>min_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>200842</td>\n",
       "      <td>4bb362d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2008</td>\n",
       "      <td>156.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32553</td>\n",
       "      <td>97c462d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>48.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>110120</td>\n",
       "      <td>04d555d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2009</td>\n",
       "      <td>115.68</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>140898</td>\n",
       "      <td>bf956034-a12b-e311-a76b-4040184c1c1a</td>\n",
       "      <td>2013</td>\n",
       "      <td>25.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316420</td>\n",
       "      <td>7c3edbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2012</td>\n",
       "      <td>52.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15173</td>\n",
       "      <td>52ce55d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2009</td>\n",
       "      <td>78.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>192893</td>\n",
       "      <td>1f6bb7d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>52.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>364870</td>\n",
       "      <td>5d64a383-82a7-e711-84bd-005056975e92</td>\n",
       "      <td>2017</td>\n",
       "      <td>15.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>359115</td>\n",
       "      <td>380fce10-7891-e611-97d4-26d4160798d6</td>\n",
       "      <td>2016</td>\n",
       "      <td>130.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13957</td>\n",
       "      <td>21b855d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2009</td>\n",
       "      <td>214.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year  PledgeTotal  VolType  \\\n",
       "200842  4bb362d1-11cd-e111-941f-00259073dc22  2008       156.00        0   \n",
       "32553   97c462d1-11cd-e111-941f-00259073dc22  2011        48.00        0   \n",
       "110120  04d555d0-11cd-e111-941f-00259073dc22  2009       115.68        0   \n",
       "140898  bf956034-a12b-e311-a76b-4040184c1c1a  2013        25.00        0   \n",
       "316420  7c3edbce-11cd-e111-941f-00259073dc22  2012        52.00        0   \n",
       "15173   52ce55d0-11cd-e111-941f-00259073dc22  2009        78.00        0   \n",
       "192893  1f6bb7d0-11cd-e111-941f-00259073dc22  2007        52.00        0   \n",
       "364870  5d64a383-82a7-e711-84bd-005056975e92  2017        15.00        0   \n",
       "359115  380fce10-7891-e611-97d4-26d4160798d6  2016       130.00        0   \n",
       "13957   21b855d0-11cd-e111-941f-00259073dc22  2009       214.24        0   \n",
       "\n",
       "        VolunteerActivityCnt  BirthYear  Gender  min_year  \n",
       "200842                   0.0        0.0  female      2008  \n",
       "32553                    0.0     1965.0  female      2009  \n",
       "110120                   0.0     1952.0  female      2007  \n",
       "140898                   0.0        0.0    male      2013  \n",
       "316420                   0.0        0.0  female      2007  \n",
       "15173                    0.0        0.0    male      2007  \n",
       "192893                   0.0        0.0    male      2007  \n",
       "364870                   0.0        0.0    male      2017  \n",
       "359115                   0.0        0.0  female      2016  \n",
       "13957                    0.0     1946.0  female      2007  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display a random sample of 10 rows of the dataframe\n",
    "df_non_only.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop rows where Year = min_year\n",
    "df_non_only = df_non_only.drop(df_non_only[df_non_only.Year != df_non_only.min_year].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>ContactId</th>\n",
       "      <th>Year</th>\n",
       "      <th>PledgeTotal</th>\n",
       "      <th>VolType</th>\n",
       "      <th>VolunteerActivityCnt</th>\n",
       "      <th>BirthYear</th>\n",
       "      <th>Gender</th>\n",
       "      <th>min_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>140180</td>\n",
       "      <td>4222e471-b113-4d5c-92b4-15f07f6219ff</td>\n",
       "      <td>2013</td>\n",
       "      <td>240.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>162122</td>\n",
       "      <td>56e203b8-d09a-e511-908e-26d4160798d6</td>\n",
       "      <td>2015</td>\n",
       "      <td>25.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>292756</td>\n",
       "      <td>8a9103d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2008</td>\n",
       "      <td>30.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37458</td>\n",
       "      <td>063c15d2-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35367</td>\n",
       "      <td>250ec1f7-1ef9-e111-9497-001f290a401c</td>\n",
       "      <td>2012</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>235984</td>\n",
       "      <td>f8696ebf-5bc1-419a-a246-6ef25bea814a</td>\n",
       "      <td>2013</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>287171</td>\n",
       "      <td>48e674ce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2008</td>\n",
       "      <td>180.36</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>306586</td>\n",
       "      <td>823de8cf-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2010</td>\n",
       "      <td>52.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>345241</td>\n",
       "      <td>fb5bdbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315231</td>\n",
       "      <td>263215d2-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>104.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year  PledgeTotal  VolType  \\\n",
       "140180  4222e471-b113-4d5c-92b4-15f07f6219ff  2013       240.00        0   \n",
       "162122  56e203b8-d09a-e511-908e-26d4160798d6  2015        25.00        0   \n",
       "292756  8a9103d1-11cd-e111-941f-00259073dc22  2008        30.00        0   \n",
       "37458   063c15d2-11cd-e111-941f-00259073dc22  2011         5.00        0   \n",
       "35367   250ec1f7-1ef9-e111-9497-001f290a401c  2012        50.00        0   \n",
       "235984  f8696ebf-5bc1-419a-a246-6ef25bea814a  2013        24.00        0   \n",
       "287171  48e674ce-11cd-e111-941f-00259073dc22  2008       180.36        0   \n",
       "306586  823de8cf-11cd-e111-941f-00259073dc22  2010        52.00        0   \n",
       "345241  fb5bdbce-11cd-e111-941f-00259073dc22  2016         0.00        0   \n",
       "315231  263215d2-11cd-e111-941f-00259073dc22  2011       104.00        0   \n",
       "\n",
       "        VolunteerActivityCnt  BirthYear  Gender  min_year  \n",
       "140180                   0.0        0.0    male      2013  \n",
       "162122                   0.0        0.0  female      2015  \n",
       "292756                   0.0     1956.0  female      2008  \n",
       "37458                    0.0        0.0    male      2011  \n",
       "35367                    0.0        0.0    male      2012  \n",
       "235984                   0.0        0.0    male      2013  \n",
       "287171                   0.0     1966.0    male      2008  \n",
       "306586                   0.0        0.0    male      2010  \n",
       "345241                   0.0        0.0  female      2016  \n",
       "315231                   0.0        0.0    male      2011  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_non_only.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(115554, 8)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_non_only.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_std_only = df.drop(df[df.VolType == 0].index).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8439, 7)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_std_only.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_std_only = df_std_only.drop_duplicates('ContactId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6147, 7)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_std_only.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>ContactId</th>\n",
       "      <th>Year</th>\n",
       "      <th>PledgeTotal</th>\n",
       "      <th>VolType</th>\n",
       "      <th>VolunteerActivityCnt</th>\n",
       "      <th>BirthYear</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>380035</td>\n",
       "      <td>59a5c761-f825-e311-a975-4040184c1c1a</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>382378</td>\n",
       "      <td>1fbd9c37-6a79-e811-80ea-0050569e2a4f</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>380017</td>\n",
       "      <td>799de6a1-130e-e511-adf0-26d4160798d6</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>380641</td>\n",
       "      <td>d34bb1d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>380140</td>\n",
       "      <td>5d38d021-c2ef-e211-a0e0-4040184c1c1a</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year  PledgeTotal   VolType  \\\n",
       "380035  59a5c761-f825-e311-a975-4040184c1c1a  2013          0.0  Standard   \n",
       "382378  1fbd9c37-6a79-e811-80ea-0050569e2a4f  2018          0.0  Standard   \n",
       "380017  799de6a1-130e-e511-adf0-26d4160798d6  2015          0.0  Standard   \n",
       "380641  d34bb1d1-11cd-e111-941f-00259073dc22  2010          0.0  Standard   \n",
       "380140  5d38d021-c2ef-e211-a0e0-4040184c1c1a  2013          0.0  Standard   \n",
       "\n",
       "        VolunteerActivityCnt  BirthYear  Gender  \n",
       "380035                   1.0        0.0  female  \n",
       "382378                   1.0        0.0  female  \n",
       "380017                   1.0        0.0       0  \n",
       "380641                   1.0        0.0  female  \n",
       "380140                   1.0        0.0  female  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_std_only.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a new dataframe\n",
    "new_df = pd.merge(df_non_only, df_std_only, how='left', left_on=['ContactId'], right_on = ['ContactId'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(115554, 14)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = new_df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>ContactId</th>\n",
       "      <th>Year_x</th>\n",
       "      <th>PledgeTotal_x</th>\n",
       "      <th>VolType_x</th>\n",
       "      <th>VolunteerActivityCnt_x</th>\n",
       "      <th>BirthYear_x</th>\n",
       "      <th>Gender_x</th>\n",
       "      <th>min_year</th>\n",
       "      <th>Year_y</th>\n",
       "      <th>PledgeTotal_y</th>\n",
       "      <th>VolType_y</th>\n",
       "      <th>VolunteerActivityCnt_y</th>\n",
       "      <th>BirthYear_y</th>\n",
       "      <th>Gender_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>42371</td>\n",
       "      <td>285bb7d0-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2011</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>58153</td>\n",
       "      <td>133edbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112990</td>\n",
       "      <td>4c58b89b-e759-e811-80e1-0050569e2a4f</td>\n",
       "      <td>2017</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111606</td>\n",
       "      <td>740e7681-ac89-e611-a7f7-26d4160798d6</td>\n",
       "      <td>2016</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10445</td>\n",
       "      <td>98bb99cf-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2008</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year_x  PledgeTotal_x  \\\n",
       "42371   285bb7d0-11cd-e111-941f-00259073dc22    2011          100.0   \n",
       "58153   133edbce-11cd-e111-941f-00259073dc22    2007           52.0   \n",
       "112990  4c58b89b-e759-e811-80e1-0050569e2a4f    2017           50.0   \n",
       "111606  740e7681-ac89-e611-a7f7-26d4160798d6    2016          240.0   \n",
       "10445   98bb99cf-11cd-e111-941f-00259073dc22    2008           26.0   \n",
       "\n",
       "        VolType_x  VolunteerActivityCnt_x  BirthYear_x Gender_x  min_year  \\\n",
       "42371           0                     0.0          0.0     male      2011   \n",
       "58153           0                     0.0       1957.0   female      2007   \n",
       "112990          0                     0.0          0.0        0      2017   \n",
       "111606          0                     0.0          0.0     male      2016   \n",
       "10445           0                     0.0       1976.0     male      2008   \n",
       "\n",
       "        Year_y  PledgeTotal_y VolType_y  VolunteerActivityCnt_y  BirthYear_y  \\\n",
       "42371      0.0            0.0         0                     0.0          0.0   \n",
       "58153      0.0            0.0         0                     0.0          0.0   \n",
       "112990     0.0            0.0         0                     0.0          0.0   \n",
       "111606     0.0            0.0         0                     0.0          0.0   \n",
       "10445      0.0            0.0         0                     0.0          0.0   \n",
       "\n",
       "       Gender_y  \n",
       "42371         0  \n",
       "58153         0  \n",
       "112990        0  \n",
       "111606        0  \n",
       "10445         0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = new_df.drop(new_df[new_df.VolType_y != 'Standard'].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2981, 14)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>ContactId</th>\n",
       "      <th>Year_x</th>\n",
       "      <th>PledgeTotal_x</th>\n",
       "      <th>VolType_x</th>\n",
       "      <th>VolunteerActivityCnt_x</th>\n",
       "      <th>BirthYear_x</th>\n",
       "      <th>Gender_x</th>\n",
       "      <th>min_year</th>\n",
       "      <th>Year_y</th>\n",
       "      <th>PledgeTotal_y</th>\n",
       "      <th>VolType_y</th>\n",
       "      <th>VolunteerActivityCnt_y</th>\n",
       "      <th>BirthYear_y</th>\n",
       "      <th>Gender_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>43298</td>\n",
       "      <td>bb51b1d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2011</td>\n",
       "      <td>30.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2011</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>98814</td>\n",
       "      <td>9350b1d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2010</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2010</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>86901</td>\n",
       "      <td>33e774ce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>76238</td>\n",
       "      <td>7bcfa9d5-d13c-e311-b580-4040184c1c1a</td>\n",
       "      <td>2013</td>\n",
       "      <td>235.82</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2013</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18219</td>\n",
       "      <td>1a23f478-386a-e211-a0e0-4040184c1c1a</td>\n",
       "      <td>2013</td>\n",
       "      <td>96.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2013</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  ContactId  Year_x  PledgeTotal_x  VolType_x  \\\n",
       "43298  bb51b1d1-11cd-e111-941f-00259073dc22    2011          30.00          0   \n",
       "98814  9350b1d1-11cd-e111-941f-00259073dc22    2010          50.00          0   \n",
       "86901  33e774ce-11cd-e111-941f-00259073dc22    2007          80.00          0   \n",
       "76238  7bcfa9d5-d13c-e311-b580-4040184c1c1a    2013         235.82          0   \n",
       "18219  1a23f478-386a-e211-a0e0-4040184c1c1a    2013          96.00          0   \n",
       "\n",
       "       VolunteerActivityCnt_x  BirthYear_x Gender_x  min_year  Year_y  \\\n",
       "43298                     0.0       1990.0     male      2011  2014.0   \n",
       "98814                     0.0          0.0   female      2010  2011.0   \n",
       "86901                     0.0       1973.0     male      2007  2016.0   \n",
       "76238                     0.0       1977.0   female      2013  2015.0   \n",
       "18219                     0.0       1988.0   female      2013  2012.0   \n",
       "\n",
       "       PledgeTotal_y VolType_y  VolunteerActivityCnt_y  BirthYear_y Gender_y  \n",
       "43298           60.0  Standard                     1.0       1990.0     male  \n",
       "98814            0.0  Standard                     1.0          0.0   female  \n",
       "86901           85.0  Standard                     1.0       1973.0     male  \n",
       "76238            0.0  Standard                     1.0       1977.0   female  \n",
       "18219           96.0  Standard                     1.0       1988.0   female  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df_final = new_df[new_df.Year_x <= new_df.Year_y]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2504, 14)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df_final.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>ContactId</th>\n",
       "      <th>Year_x</th>\n",
       "      <th>PledgeTotal_x</th>\n",
       "      <th>VolType_x</th>\n",
       "      <th>VolunteerActivityCnt_x</th>\n",
       "      <th>BirthYear_x</th>\n",
       "      <th>Gender_x</th>\n",
       "      <th>min_year</th>\n",
       "      <th>Year_y</th>\n",
       "      <th>PledgeTotal_y</th>\n",
       "      <th>VolType_y</th>\n",
       "      <th>VolunteerActivityCnt_y</th>\n",
       "      <th>BirthYear_y</th>\n",
       "      <th>Gender_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>87443</td>\n",
       "      <td>d3f674ce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2007</td>\n",
       "      <td>2190.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>10000.00</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>63737</td>\n",
       "      <td>795cdbce-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2008</td>\n",
       "      <td>130.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2008</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>279.76</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8378</td>\n",
       "      <td>ca8555a8-2382-e411-9b7f-26d4160798d6</td>\n",
       "      <td>2008</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2008</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>69393</td>\n",
       "      <td>ebcd62d1-11cd-e111-941f-00259073dc22</td>\n",
       "      <td>2009</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>105731</td>\n",
       "      <td>8e84425a-5c2d-e411-ba26-26d4160798d6</td>\n",
       "      <td>2014</td>\n",
       "      <td>264.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2014</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>1020.07</td>\n",
       "      <td>Standard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ContactId  Year_x  PledgeTotal_x  \\\n",
       "87443   d3f674ce-11cd-e111-941f-00259073dc22    2007         2190.5   \n",
       "63737   795cdbce-11cd-e111-941f-00259073dc22    2008          130.0   \n",
       "8378    ca8555a8-2382-e411-9b7f-26d4160798d6    2008           52.0   \n",
       "69393   ebcd62d1-11cd-e111-941f-00259073dc22    2009           35.0   \n",
       "105731  8e84425a-5c2d-e411-ba26-26d4160798d6    2014          264.0   \n",
       "\n",
       "        VolType_x  VolunteerActivityCnt_x  BirthYear_x Gender_x  min_year  \\\n",
       "87443           0                     0.0       1950.0     male      2007   \n",
       "63737           0                     0.0       1969.0   female      2008   \n",
       "8378            0                     0.0       1958.0   female      2008   \n",
       "69393           0                     0.0       1976.0   female      2009   \n",
       "105731          0                     0.0       1985.0   female      2014   \n",
       "\n",
       "        Year_y  PledgeTotal_y VolType_y  VolunteerActivityCnt_y  BirthYear_y  \\\n",
       "87443   2016.0       10000.00  Standard                     1.0       1950.0   \n",
       "63737   2013.0         279.76  Standard                     1.0       1969.0   \n",
       "8378    2013.0          25.00  Standard                     1.0       1958.0   \n",
       "69393   2014.0         100.00  Standard                     1.0       1976.0   \n",
       "105731  2018.0        1020.07  Standard                     1.0       1985.0   \n",
       "\n",
       "       Gender_y  \n",
       "87443      male  \n",
       "63737    female  \n",
       "8378     female  \n",
       "69393    female  \n",
       "105731   female  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df_final.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.021669522474341"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2504/115554"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion:\n",
    "\n",
    "So, about **2.2%** of the non-volunteers become volunteers.  \n",
    "\n",
    "One caveat: the case where a non-volunteer donates and then volunteers in the same year is **excluded** because there is no way to know which event happened first.  In other words the supporter could have volunteered first and then donated later in the same year.  This would not make much of a difference in the final percentage.  \n",
    "\n",
    "A second caveat:  The supporter could eventually become a volunteer later in 2019 or in a later year."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}