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{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"seo-split-testing.ipynb","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"QKZaP5f5CU0M","colab_type":"text"},"source":["<h1>SEO Split Testing</h1>\n","\n","\n","*CausalImpact is a Python Package for causal inference using Bayesian structural time-series models. This notebook is made by Natzir Turrado to work directly with the Google Analytics API.*\n","\n","\n","Installing (downgrading) the version packages that work with CausalImpact 1.4\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"gXJ7ZhUkD1i5","colab_type":"code","outputId":"0d86340f-36fa-42a7-c707-6c347a4ecd62","executionInfo":{"status":"ok","timestamp":1570517584202,"user_tz":-120,"elapsed":15443,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":311}},"source":["!wget -q https://anaconda.org/teamcore/causalimpact/0.1.4/download/linux-64/causalimpact-0.1.4-py36_0.tar.bz2\n","!tar xjf causalimpact-0.1.4-py36_0.tar.bz2\n","!cp -r lib/python3.6/site-packages/* /usr/local/lib/python3.6/dist-packages\n","!pip install statsmodels==0.8.0\n","!pip install scipy==1.2.0\n","!pip install numpy==1.15.4\n","!pip install pandas==0.23.4"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: statsmodels==0.8.0 in /usr/local/lib/python3.6/dist-packages (0.8.0)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from statsmodels==0.8.0) (0.23.4)\n","Requirement already satisfied: patsy in /usr/local/lib/python3.6/dist-packages (from statsmodels==0.8.0) (0.5.1)\n","Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from statsmodels==0.8.0) (1.2.0)\n","Requirement already satisfied: pytz>=2011k in /usr/local/lib/python3.6/dist-packages (from pandas->statsmodels==0.8.0) (2018.9)\n","Requirement already satisfied: python-dateutil>=2.5.0 in /usr/local/lib/python3.6/dist-packages (from pandas->statsmodels==0.8.0) (2.5.3)\n","Requirement already satisfied: numpy>=1.9.0 in /usr/local/lib/python3.6/dist-packages (from pandas->statsmodels==0.8.0) (1.15.4)\n","Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from patsy->statsmodels==0.8.0) (1.12.0)\n","Requirement already satisfied: scipy==1.2.0 in /usr/local/lib/python3.6/dist-packages (1.2.0)\n","Requirement already satisfied: numpy>=1.8.2 in /usr/local/lib/python3.6/dist-packages (from scipy==1.2.0) (1.15.4)\n","Requirement already satisfied: numpy==1.15.4 in /usr/local/lib/python3.6/dist-packages (1.15.4)\n","Requirement already satisfied: pandas==0.23.4 in /usr/local/lib/python3.6/dist-packages (0.23.4)\n","Requirement already satisfied: pytz>=2011k in /usr/local/lib/python3.6/dist-packages (from pandas==0.23.4) (2018.9)\n","Requirement already satisfied: numpy>=1.9.0 in /usr/local/lib/python3.6/dist-packages (from pandas==0.23.4) (1.15.4)\n","Requirement already satisfied: python-dateutil>=2.5.0 in /usr/local/lib/python3.6/dist-packages (from pandas==0.23.4) (2.5.3)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.5.0->pandas==0.23.4) (1.12.0)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"HCnLalSaD6Uy","colab_type":"text"},"source":["Importing libraries\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"Ibcm2CgBmV1o","colab_type":"code","outputId":"c8544d6f-effc-4137-c219-83f5f1b97701","executionInfo":{"status":"ok","timestamp":1570517595926,"user_tz":-120,"elapsed":764,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":54}},"source":["from causalimpact import CausalImpact\n","from statsmodels.tsa.statespace.structural import UnobservedComponents\n","import numpy as np\n","import pandas as pd\n","import matplotlib\n","import seaborn as sns\n","import httplib2 as lib2\n","import google.oauth2.credentials\n","from google_auth_httplib2 import AuthorizedHttp\n","from googleapiclient.discovery import build as google_build\n","from datetime import datetime, timedelta\n","from IPython.display import display"],"execution_count":2,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n"," from pandas.core import datetools\n"],"name":"stderr"}]},{"cell_type":"markdown","metadata":{"id":"vyZGUo81CQ5Y","colab_type":"text"},"source":["Create your Google Analytics tokens\n","<ul>\n","<li><a href=\"https://developers.google.com/oauthplayground/\">Get your access_token & refresh_token</a></li> \n","<li><a href=\"https://console.cloud.google.com/apis/library/analyticsreporting.googleapis.com\">Get your client_id & client_secret </a></li>\n","</ul>\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"iDpyyI3I0yCm","colab_type":"code","colab":{}},"source":["access_token = ''\n","refresh_token = ''\n","client_id = ''\n","client_secret = ''"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"CmUlmAAxEOJN","colab_type":"text"},"source":["Analytics client initialization & autorization\n","\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"9lO5WoHM0zEz","colab_type":"code","colab":{}},"source":["token_uri = 'https://accounts.google.com/o/oauth2/token'\n","credentials = google.oauth2.credentials.Credentials(access_token,refresh_token=refresh_token,token_uri='https://accounts.google.com/o/oauth2/token',client_id=client_id,client_secret=client_secret)\n","authorized = AuthorizedHttp(credentials=credentials)\n","api_name = 'analyticsreporting'\n","api_version = 'v4'\n","api_client = google_build(serviceName=api_name, version=api_version, http=authorized)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"RuuyItKRER0Y","colab_type":"text"},"source":["Insert here your view ID, dates & your segmentId for control & variation.\n","\n","\n","---\n","\n","\n"]},{"cell_type":"code","metadata":{"id":"H65g5CE501nz","colab_type":"code","colab":{}},"source":["sample_request_control = {\n"," 'viewId': '',\n"," 'segments': [{'segmentId': 'gaid::aiE-qMKkQ5eD9v3tFmT9iw'}],\n"," 'filtersExpression': 'ga:medium==organic',\n"," 'dateRanges': {\n"," 'startDate': '2019-06-01',\n"," 'endDate': '2019-10-06'\n"," },\n"," 'dimensions': [{'name': 'ga:date'},{ \"name\": \"ga:segment\" }],\n"," 'metrics': [{'expression': 'ga:sessions'}]\n","}\n","\n","sample_request_variation = {\n"," 'viewId': '',\n"," 'segments': [{'segmentId': 'gaid::l9rKOrqHRe-_HyKm5s06vw'}], \n"," 'filtersExpression': 'ga:medium==organic',\n"," 'dateRanges': {\n"," 'startDate': '2019-06-01',\n"," 'endDate': '2019-10-06'\n"," },\n"," 'dimensions': [{'name': 'ga:date'},{ \"name\": \"ga:segment\" }],\n"," 'metrics': [{'expression': 'ga:sessions'}]\n","}\n","\n","response_control = api_client.reports().batchGet(body={'reportRequests': sample_request_control}).execute()\n","\n","response_variation = api_client.reports().batchGet(body={'reportRequests': sample_request_variation}).execute()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"oKNgKfQp092M","colab_type":"code","colab":{}},"source":["#Parse the response of API\n","def parse_response(report):\n","\n"," \"\"\"Parses and prints the Analytics Reporting API V4 response\"\"\"\n"," result_list = []\n"," data_csv = []\n"," data_csv2 = []\n"," header_row = []\n","\n"," #Get column headers, metric headers, and dimension headers.\n"," columnHeader = report.get('columnHeader', {})\n"," metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])\n"," dimensionHeaders = columnHeader.get('dimensions', [])\n","\n"," #Combine all of those headers into the header_row, which is in a list format\n"," for dheader in dimensionHeaders:\n"," header_row.append(dheader)\n"," for mheader in metricHeaders:\n"," header_row.append(mheader['name'])\n","\n"," #Get data from each of the rows, and append them into a list\n"," rows = report.get('data', {}).get('rows', [])\n"," for row in rows:\n"," row_temp = []\n"," dimensions = row.get('dimensions', [])\n"," metrics = row.get('metrics', [])\n"," for d in dimensions:\n"," row_temp.append(d)\n"," for m in metrics[0]['values']:\n"," row_temp.append(m)\n"," data_csv.append(row_temp)\n","\n"," #In case of a second date range, do the same thing for the second request\n"," if len(metrics) == 2:\n"," row_temp2 = []\n"," for d in dimensions:\n"," row_temp2.append(d)\n"," for m in metrics[1]['values']:\n"," row_temp2.append(m)\n"," data_csv2.append(row_temp2)\n","\n"," #Putting those list formats into pandas dataframe, and append them into the final result\n"," result_df = pd.DataFrame(data_csv, columns=header_row)\n"," result_list.append(result_df)\n"," if data_csv2 != []:\n"," result_list.append(pd.DataFrame(data_csv2, columns=header_row))\n","\n"," return result_list"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jL_b8NXEIN3k","colab_type":"text"},"source":["DataFraming the response in the format that CausalImpact needs\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"pgEKMZwx1A_p","colab_type":"code","outputId":"9b435cbb-8e2a-47ec-ec84-76bb61442140","executionInfo":{"status":"ok","timestamp":1570517602150,"user_tz":-120,"elapsed":6941,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["response_data_control = response_control.get('reports', [])[0]\n","response_data_variation = response_variation.get('reports', [])[0]\n","\n","\n","df = parse_response(response_data_control)[0].drop(['ga:segment'], axis=1)\n","df_variation = parse_response(response_data_variation)[0].drop(['ga:segment','ga:date'], axis=1)\n","\n","\n","df_concat = pd.concat([df, df_variation], axis=1)\n","df_concat.columns = ['Date', 'Control', 'Variation']\n","df_concat['Date'] = pd.to_datetime(df_concat['Date'])\n","df_concat.set_index('Date',inplace=True)\n","df_concat.index.name = None\n","df_concat['Control'] = df_concat['Control'].astype('float64')\n","df_concat['Variation'] = df_concat['Variation'].astype('float64')\n","df_concat"],"execution_count":7,"outputs":[{"output_type":"execute_result","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>Control</th>\n"," <th>Variation</th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>2019-06-01</th>\n"," <td>145.0</td>\n"," <td>321.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-02</th>\n"," <td>138.0</td>\n"," <td>321.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-03</th>\n"," <td>189.0</td>\n"," <td>327.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-04</th>\n"," <td>214.0</td>\n"," <td>409.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-05</th>\n"," <td>239.0</td>\n"," <td>428.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-06</th>\n"," <td>151.0</td>\n"," <td>315.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-07</th>\n"," <td>182.0</td>\n"," <td>377.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-08</th>\n"," <td>138.0</td>\n"," <td>315.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-09</th>\n"," <td>164.0</td>\n"," <td>333.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-10</th>\n"," <td>233.0</td>\n"," <td>434.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-11</th>\n"," <td>201.0</td>\n"," <td>403.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-12</th>\n"," <td>201.0</td>\n"," <td>403.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-13</th>\n"," <td>164.0</td>\n"," <td>384.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-14</th>\n"," <td>157.0</td>\n"," <td>346.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-15</th>\n"," <td>157.0</td>\n"," <td>289.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-16</th>\n"," <td>151.0</td>\n"," <td>403.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-17</th>\n"," <td>170.0</td>\n"," <td>333.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-18</th>\n"," <td>151.0</td>\n"," <td>302.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-19</th>\n"," <td>164.0</td>\n"," <td>396.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-20</th>\n"," <td>132.0</td>\n"," <td>327.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-21</th>\n"," <td>101.0</td>\n"," <td>233.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-22</th>\n"," <td>101.0</td>\n"," <td>302.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-23</th>\n"," <td>182.0</td>\n"," <td>315.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-24</th>\n"," <td>157.0</td>\n"," <td>308.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-25</th>\n"," <td>164.0</td>\n"," <td>302.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-26</th>\n"," <td>101.0</td>\n"," <td>333.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-27</th>\n"," <td>164.0</td>\n"," <td>289.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-28</th>\n"," <td>120.0</td>\n"," <td>283.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-29</th>\n"," <td>75.0</td>\n"," <td>321.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-06-30</th>\n"," <td>107.0</td>\n"," <td>377.0</td>\n"," </tr>\n"," <tr>\n"," <th>...</th>\n"," <td>...</td>\n"," <td>...</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-07</th>\n"," <td>208.0</td>\n"," <td>201.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-08</th>\n"," <td>245.0</td>\n"," <td>289.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-09</th>\n"," <td>315.0</td>\n"," <td>264.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-10</th>\n"," <td>315.0</td>\n"," <td>258.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-11</th>\n"," <td>365.0</td>\n"," <td>264.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-12</th>\n"," <td>333.0</td>\n"," <td>289.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-13</th>\n"," <td>258.0</td>\n"," <td>214.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-14</th>\n"," <td>315.0</td>\n"," <td>245.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-15</th>\n"," <td>390.0</td>\n"," <td>289.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-16</th>\n"," <td>365.0</td>\n"," <td>201.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-17</th>\n"," <td>289.0</td>\n"," <td>239.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-18</th>\n"," <td>214.0</td>\n"," <td>315.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-19</th>\n"," <td>245.0</td>\n"," <td>245.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-20</th>\n"," <td>270.0</td>\n"," <td>201.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-21</th>\n"," <td>258.0</td>\n"," <td>308.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-22</th>\n"," <td>321.0</td>\n"," <td>239.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-23</th>\n"," <td>302.0</td>\n"," <td>308.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-24</th>\n"," <td>270.0</td>\n"," <td>270.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-25</th>\n"," <td>245.0</td>\n"," <td>264.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-26</th>\n"," <td>277.0</td>\n"," <td>302.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-27</th>\n"," <td>189.0</td>\n"," <td>296.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-28</th>\n"," <td>333.0</td>\n"," <td>220.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-29</th>\n"," <td>289.0</td>\n"," <td>302.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-09-30</th>\n"," <td>371.0</td>\n"," <td>283.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-01</th>\n"," <td>315.0</td>\n"," <td>327.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-02</th>\n"," <td>434.0</td>\n"," <td>359.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-03</th>\n"," <td>277.0</td>\n"," <td>252.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-04</th>\n"," <td>346.0</td>\n"," <td>321.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-05</th>\n"," <td>226.0</td>\n"," <td>245.0</td>\n"," </tr>\n"," <tr>\n"," <th>2019-10-06</th>\n"," <td>421.0</td>\n"," <td>308.0</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>128 rows × 2 columns</p>\n","</div>"],"text/plain":[" Control Variation\n","2019-06-01 145.0 321.0\n","2019-06-02 138.0 321.0\n","2019-06-03 189.0 327.0\n","2019-06-04 214.0 409.0\n","2019-06-05 239.0 428.0\n","2019-06-06 151.0 315.0\n","2019-06-07 182.0 377.0\n","2019-06-08 138.0 315.0\n","2019-06-09 164.0 333.0\n","2019-06-10 233.0 434.0\n","2019-06-11 201.0 403.0\n","2019-06-12 201.0 403.0\n","2019-06-13 164.0 384.0\n","2019-06-14 157.0 346.0\n","2019-06-15 157.0 289.0\n","2019-06-16 151.0 403.0\n","2019-06-17 170.0 333.0\n","2019-06-18 151.0 302.0\n","2019-06-19 164.0 396.0\n","2019-06-20 132.0 327.0\n","2019-06-21 101.0 233.0\n","2019-06-22 101.0 302.0\n","2019-06-23 182.0 315.0\n","2019-06-24 157.0 308.0\n","2019-06-25 164.0 302.0\n","2019-06-26 101.0 333.0\n","2019-06-27 164.0 289.0\n","2019-06-28 120.0 283.0\n","2019-06-29 75.0 321.0\n","2019-06-30 107.0 377.0\n","... ... ...\n","2019-09-07 208.0 201.0\n","2019-09-08 245.0 289.0\n","2019-09-09 315.0 264.0\n","2019-09-10 315.0 258.0\n","2019-09-11 365.0 264.0\n","2019-09-12 333.0 289.0\n","2019-09-13 258.0 214.0\n","2019-09-14 315.0 245.0\n","2019-09-15 390.0 289.0\n","2019-09-16 365.0 201.0\n","2019-09-17 289.0 239.0\n","2019-09-18 214.0 315.0\n","2019-09-19 245.0 245.0\n","2019-09-20 270.0 201.0\n","2019-09-21 258.0 308.0\n","2019-09-22 321.0 239.0\n","2019-09-23 302.0 308.0\n","2019-09-24 270.0 270.0\n","2019-09-25 245.0 264.0\n","2019-09-26 277.0 302.0\n","2019-09-27 189.0 296.0\n","2019-09-28 333.0 220.0\n","2019-09-29 289.0 302.0\n","2019-09-30 371.0 283.0\n","2019-10-01 315.0 327.0\n","2019-10-02 434.0 359.0\n","2019-10-03 277.0 252.0\n","2019-10-04 346.0 321.0\n","2019-10-05 226.0 245.0\n","2019-10-06 421.0 308.0\n","\n","[128 rows x 2 columns]"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"markdown","metadata":{"id":"010vWB4XHVlY","colab_type":"text"},"source":["Insert here the dates before and after the change\n","\n","\n","---"]},{"cell_type":"code","metadata":{"id":"50G6cUBIme0M","colab_type":"code","colab":{}},"source":["pre_period = [pd.to_datetime(date) for date in ['2019-06-01','2019-08-14']]\n","post_period =[pd.to_datetime(date) for date in ['2019-08-15','2019-10-06']]\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"ICUNTdchHTDM","colab_type":"code","colab":{}},"source":["impact = CausalImpact(df_concat, pre_period, post_period, model_args={\"niter\":5000, \"nseasons\":7})"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"WIrYWp3aZy72","colab_type":"code","colab":{}},"source":["impact.run()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"TfsJYim4mh6N","colab_type":"code","outputId":"b1512dd7-a038-4117-ce86-827417e0f254","executionInfo":{"status":"ok","timestamp":1570517602346,"user_tz":-120,"elapsed":7107,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":201}},"source":["results = impact.model.fit()\n","impact.summary()"],"execution_count":11,"outputs":[{"output_type":"stream","text":[" Average Cumulative\n","Actual 241 12812\n","Predicted 141 7486\n","95% CI [67, 214] [3594, 11377]\n"," \n","Absolute Effect 100 5325\n","95% CI [173, 27] [9217, 1434]\n"," \n","Relative Effect 71.1% 71.1%\n","95% CI [123.1%, 19.2%] [123.1%, 19.2%]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"P5-BIF7ImjiY","colab_type":"code","outputId":"602977ba-8989-4ee4-f1d3-a6e1cbd59bab","executionInfo":{"status":"ok","timestamp":1570517603943,"user_tz":-120,"elapsed":8692,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":732}},"source":["impact.plot()"],"execution_count":12,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA3kAAALLCAYAAABEhUsfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nG5k4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NZOnlFJKKaVUWxWuVNPSrl07Fi5cCMCjjz4amKcVKZfLFSgLjKTpiiUxMZG0tDRA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CJPJ1Oh8fj2a/1czabDYfDgdFoxGg0YjKZmv0YjcaEInUGg4GUlBTcbjfZ2dkJNXHvaahp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77gj0uecU7sRxiDuvjvizzyDyNq1KMyb50fXazIZrpoaiUSiYrKGMebZ6uOVqvuxHMsYfe01PY6z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\n7A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HJvkvSe+8DL6XXTwCHOpz7EGMn+84DivR6BfGsctHtGE9GzNM+/cQoWr7Px+mzC4lf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\nkiRJDWInT5IkSZIa5B+ylpbVD4IVowAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 1080x864 with 3 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"kw7NMvXuBYem","colab_type":"code","outputId":"72c9701e-3e08-409c-8c8b-7169238a32cb","executionInfo":{"status":"ok","timestamp":1570517603945,"user_tz":-120,"elapsed":8679,"user":{"displayName":"Natzir Turrado","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mAEUzl5NGriGoySmOIex5dVtfm_9qVPwa5t3UNQMBQ=s64","userId":"17654932228002969277"}},"colab":{"base_uri":"https://localhost:8080/","height":384}},"source":["impact.summary(\"report\")"],"execution_count":13,"outputs":[{"output_type":"stream","text":[" During the post-intervention period, the response variable had an average value of approx. 241. By contrast, in the\n","absence of an intervention, we would have expected an average response of 141. The 95% interval of this counterfactual\n","prediction is [67, 214]. Subtracting this prediction from the observed response yields an estimate of the causal effect\n","the intervention had on the response variable. This effect is 100 with a 95% interval of [173, 27]. For a discussion of\n","the significance of this effect, see below.\n","\n","\n"," Summing up the individual data points during the post-intervention period (which can only sometimes be meaningfully\n","interpreted), the response variable had an overall value of 12812. By contrast, had the intervention not taken place,\n","we would have expected a sum of 12812. The 95% interval of this prediction is [3594, 11377]\n","\n","\n"," The above results are given in terms of absolute numbers. In relative terms, the response variable showed an increase\n","of 71.1%. The 95% interval of this percentage is [123.1%, 19.2%]\n","\n","\n"," This means that the positive effect observed during the intervention period is statistically significant and unlikely\n","to be due to random fluctuations. It should be noted, however, that the question of whether this increase also bears\n","substantive significance can only be answered by comparing the absolute effect 100 to the original goal of the\n","underlying intervention.\n"],"name":"stdout"}]}]}
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