COVID_causal_impact.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interrogate the impact of the COVID lockdown in the economy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date\n",
    "import pandas as pd\n",
    "\n",
    "from src.data.download_stock import download_stocks\n",
    "from src.data.preprocessing import cacl_monthly_avg_kpi\n",
    "from src.models.causal_impact import causal_impact_analysis\n",
    "from src.utils.plots import timeline_px\n",
    "from src.utils.variables import pharma_companies, consumer_staples, retail, global_economy_indicators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "industry_tickers = {\"Pharma\" : pharma_companies,\n",
    "                    \"Consumables\" : consumer_staples,\n",
    "                    \"Retail\" : retail,\n",
    "                    \"Global Economy\" : global_economy_indicators}\n",
    "\n",
    "tickers = (list(pharma_companies.keys())\n",
    "          + list(consumer_staples.keys())\n",
    "          + list(retail.keys())\n",
    "          + list(global_economy_indicators.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_dir = \"./data/raw/\"\n",
    "start_date = date(2017, 1, 1)\n",
    "end_date = date(2020, 12, 30)\n",
    "event_date = date(2020, 3, 1) # Covid lockdown"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download stock market data from yahoo finance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Download stock market data\n",
    "# download_stocks(start_date, end_date, tickers, raw_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "kpi= \"Adj Close\"\n",
    "\n",
    "monthly_abj_close = pd.DataFrame()\n",
    "for ticker in tickers:\n",
    "    ticker_df = pd.read_csv(f\"{raw_dir}{ticker}.csv\", index_col=0)\n",
    "    ticker_df.index = pd.to_datetime(ticker_df.index)\n",
    "    ticker_df  = cacl_monthly_avg_kpi(ticker_df, kpi)\n",
    "    ticker_df.name = ticker\n",
    "    \n",
    "    monthly_abj_close = pd.concat([monthly_abj_close, ticker_df], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot timeline highlighting the start date of the first Covid lockdown, March 2020"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
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   "source": [
    "event_str = event_date.strftime(format=\"%Y-%m\")\n",
    "labels = {\"variable\":\"\", \"value\":kpi, \"index\":\"Month\"}\n",
    "\n",
    "for name, tickers_dict in industry_tickers.items():\n",
    "    tickers = list(tickers_dict.keys())\n",
    "    df = monthly_abj_close[tickers]\n",
    "    write_html =  f\"./figures/{name.lower()}.html\"\n",
    "    write_image = f\"./figures/{name.lower()}.png\"\n",
    "    timeline_px(df, event_str, name, None, write_image, labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def covid_causal_impact(tickers_dict:dict):\n",
    "    pre_period = [start_date, date(event_date.year, event_date.month-1, 1)]\n",
    "    pre_period = [pd.to_datetime(x) for x in pre_period]\n",
    "    post_period = [event_date, date(end_date.year, end_date.month-1, 1)]\n",
    "    post_period = [pd.to_datetime(x) for x in post_period]\n",
    "\n",
    "    for company in tickers_dict.keys():\n",
    "        print(f\"===== {tickers_dict[company]} =====\")\n",
    "        tickers = [company,]\n",
    "        tickers += list(global_economy_indicators.keys())\n",
    "        \n",
    "        df = monthly_abj_close[tickers]\n",
    "        df.dropna(axis=1, inplace=True)\n",
    "        ci = causal_impact_analysis(df, company, pre_period, post_period)\n",
    "        \n",
    "        ci.summary(output=\"summary\", path=f\"./figures/python/{company}.summary.txt\")\n",
    "        ci.summary(output=\"report\", path=f\"./figures/python/{company}.report.txt\") \n",
    "            \n",
    "        ci.plot(panels=['original', 'pointwise', 'cumulative'], figsize=(15,5), \n",
    "                fname=f\"./figures/python/{company}.png\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Pfizer Inc. =====\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                               Average      Cumulative\n",
      "Actual                              30             270\n",
      "Predicted                           23             208\n",
      "95% CI                        [18, 27]      [168, 248]\n",
      "                                                      \n",
      "Absolute Effect                      6              62\n",
      "95% CI                         [11, 2]       [102, 22]\n",
      "                                                      \n",
      "Relative Effect                  30.0%           30.0%\n",
      "95% CI                  [49.1%, 10.8%]  [49.1%, 10.8%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              30             270\n",
      "Predicted                           23             208\n",
      "95% CI                        [18, 27]      [168, 248]\n",
      "                                                      \n",
      "Absolute Effect                      6              62\n",
      "95% CI                         [11, 2]       [102, 22]\n",
      "                                                      \n",
      "Relative Effect                  30.0%           30.0%\n",
      "95% CI                  [49.1%, 10.8%]  [49.1%, 10.8%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 30.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 23. The 95% interval of\n",
      "this counterfactual prediction is [18, 27]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 6 with a 95% interval of [11, 2]. For a\n",
      "discussion of 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 270.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 208. The 95% interval of this prediction is [168, 248]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  30.0%. The 95% interval of this percentage is [49.1%, 10.8%]\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 6 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n",
      "===== Johnson & Johnson =====\n",
      "The mean absolute percentage error in the pre period is 0.02%\n",
      "                              Average     Cumulative\n",
      "Actual                            131           1186\n",
      "Predicted                         111           1005\n",
      "95% CI                      [98, 125]    [884, 1125]\n",
      "                                                    \n",
      "Absolute Effect                    20            181\n",
      "95% CI                        [33, 6]      [301, 60]\n",
      "                                                    \n",
      "Relative Effect                 18.0%          18.0%\n",
      "95% CI                  [30.0%, 6.1%]  [30.0%, 6.1%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                            131           1186\n",
      "Predicted                         111           1005\n",
      "95% CI                      [98, 125]    [884, 1125]\n",
      "                                                    \n",
      "Absolute Effect                    20            181\n",
      "95% CI                        [33, 6]      [301, 60]\n",
      "                                                    \n",
      "Relative Effect                 18.0%          18.0%\n",
      "95% CI                  [30.0%, 6.1%]  [30.0%, 6.1%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 131.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 111. The 95% interval of\n",
      "this counterfactual prediction is [98, 125]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 20 with a 95% interval of [33, 6].\n",
      "For a discussion of 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 1186.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 1005. The 95% interval of this prediction is [884, 1125]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  18.0%. The 95% interval of this percentage is [30.0%, 6.1%]\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 20 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
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      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
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    {
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     "text": [
      "===== Novartis AG =====\n",
      "The mean absolute percentage error in the pre period is 0.02%\n",
      "                               Average      Cumulative\n",
      "Actual                              75             680\n",
      "Predicted                           71             642\n",
      "95% CI                        [64, 78]      [576, 708]\n",
      "                                                      \n",
      "Absolute Effect                      4              37\n",
      "95% CI                        [11, -3]      [103, -28]\n",
      "                                                      \n",
      "Relative Effect                   5.9%            5.9%\n",
      "95% CI                  [16.2%, -4.4%]  [16.2%, -4.4%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              75             680\n",
      "Predicted                           71             642\n",
      "95% CI                        [64, 78]      [576, 708]\n",
      "                                                      \n",
      "Absolute Effect                      4              37\n",
      "95% CI                        [11, -3]      [103, -28]\n",
      "                                                      \n",
      "Relative Effect                   5.9%            5.9%\n",
      "95% CI                  [16.2%, -4.4%]  [16.2%, -4.4%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 75.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 71. The 95% interval of\n",
      "this counterfactual prediction is [64, 78]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 4 with a 95% interval of [11, -3]. For a\n",
      "discussion of 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 680.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 642. The 95% interval of this prediction is [576, 708]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  5.9%. The 95% interval of this percentage is [16.2%, -4.4%]\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 4 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Roche Holding AG =====\n",
      "The mean absolute percentage error in the pre period is 0.05%\n",
      "                               Average      Cumulative\n",
      "Actual                             112            1015\n",
      "Predicted                           85             767\n",
      "95% CI                       [49, 121]     [443, 1091]\n",
      "                                                      \n",
      "Absolute Effect                     27             248\n",
      "95% CI                        [63, -8]      [572, -75]\n",
      "                                                      \n",
      "Relative Effect                  32.3%           32.3%\n",
      "95% CI                  [74.6%, -9.9%]  [74.6%, -9.9%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                             112            1015\n",
      "Predicted                           85             767\n",
      "95% CI                       [49, 121]     [443, 1091]\n",
      "                                                      \n",
      "Absolute Effect                     27             248\n",
      "95% CI                        [63, -8]      [572, -75]\n",
      "                                                      \n",
      "Relative Effect                  32.3%           32.3%\n",
      "95% CI                  [74.6%, -9.9%]  [74.6%, -9.9%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 112.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 85. The 95% interval of\n",
      "this counterfactual prediction is [49, 121]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 27 with a 95% interval of [63, -8].\n",
      "For a discussion of 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 1015.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 767. The 95% interval of this prediction is [443, 1091]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  32.3%. The 95% interval of this percentage is [74.6%, -9.9%]\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 27 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Merck & Co., Inc. =====\n",
      "The mean absolute percentage error in the pre period is 0.04%\n",
      "                               Average      Cumulative\n",
      "Actual                              68             612\n",
      "Predicted                           53             484\n",
      "95% CI                        [45, 62]      [406, 561]\n",
      "                                                      \n",
      "Absolute Effect                     14             128\n",
      "95% CI                         [22, 5]       [206, 51]\n",
      "                                                      \n",
      "Relative Effect                  26.6%           26.6%\n",
      "95% CI                  [42.6%, 10.7%]  [42.6%, 10.7%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              68             612\n",
      "Predicted                           53             484\n",
      "95% CI                        [45, 62]      [406, 561]\n",
      "                                                      \n",
      "Absolute Effect                     14             128\n",
      "95% CI                         [22, 5]       [206, 51]\n",
      "                                                      \n",
      "Relative Effect                  26.6%           26.6%\n",
      "95% CI                  [42.6%, 10.7%]  [42.6%, 10.7%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 68.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 53. The 95% interval of\n",
      "this counterfactual prediction is [45, 62]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 14 with a 95% interval of [22, 5]. For a\n",
      "discussion of 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 612.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 484. The 95% interval of this prediction is [406, 561]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  26.6%. The 95% interval of this percentage is [42.6%, 10.7%]\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 14 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Sanofi =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                              Average     Cumulative\n",
      "Actual                             43            393\n",
      "Predicted                          37            336\n",
      "95% CI                       [32, 42]     [292, 380]\n",
      "                                                    \n",
      "Absolute Effect                     6             56\n",
      "95% CI                        [11, 1]      [101, 12]\n",
      "                                                    \n",
      "Relative Effect                 16.9%          16.9%\n",
      "95% CI                  [30.0%, 3.8%]  [30.0%, 3.8%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                             43            393\n",
      "Predicted                          37            336\n",
      "95% CI                       [32, 42]     [292, 380]\n",
      "                                                    \n",
      "Absolute Effect                     6             56\n",
      "95% CI                        [11, 1]      [101, 12]\n",
      "                                                    \n",
      "Relative Effect                 16.9%          16.9%\n",
      "95% CI                  [30.0%, 3.8%]  [30.0%, 3.8%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 43.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 37. The 95% interval of\n",
      "this counterfactual prediction is [32, 42]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 6 with a 95% interval of [11, 1]. For a\n",
      "discussion of 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 393.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 336. The 95% interval of this prediction is [292, 380]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  16.9%. The 95% interval of this percentage is [30.0%, 3.8%]\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 6 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== GlaxoSmithKline plc =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                              Average     Cumulative\n",
      "Actual                             33            301\n",
      "Predicted                          29            263\n",
      "95% CI                       [25, 33]     [229, 298]\n",
      "                                                    \n",
      "Absolute Effect                     4             37\n",
      "95% CI                         [8, 0]        [72, 3]\n",
      "                                                    \n",
      "Relative Effect                 14.4%          14.4%\n",
      "95% CI                  [27.5%, 1.2%]  [27.5%, 1.2%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                             33            301\n",
      "Predicted                          29            263\n",
      "95% CI                       [25, 33]     [229, 298]\n",
      "                                                    \n",
      "Absolute Effect                     4             37\n",
      "95% CI                         [8, 0]        [72, 3]\n",
      "                                                    \n",
      "Relative Effect                 14.4%          14.4%\n",
      "95% CI                  [27.5%, 1.2%]  [27.5%, 1.2%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 33.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 29. The 95% interval of\n",
      "this counterfactual prediction is [25, 33]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 4 with a 95% interval of [8, 0]. For a\n",
      "discussion of 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 301.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 263. The 95% interval of this prediction is [229, 298]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  14.4%. The 95% interval of this percentage is [27.5%, 1.2%]\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 4 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== AstraZeneca PLC =====\n",
      "The mean absolute percentage error in the pre period is 0.05%\n",
      "                              Average     Cumulative\n",
      "Actual                             48            437\n",
      "Predicted                          40            361\n",
      "95% CI                       [34, 46]     [306, 416]\n",
      "                                                    \n",
      "Absolute Effect                     8             76\n",
      "95% CI                        [14, 2]      [130, 21]\n",
      "                                                    \n",
      "Relative Effect                 21.1%          21.1%\n",
      "95% CI                  [36.2%, 5.9%]  [36.2%, 5.9%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                             48            437\n",
      "Predicted                          40            361\n",
      "95% CI                       [34, 46]     [306, 416]\n",
      "                                                    \n",
      "Absolute Effect                     8             76\n",
      "95% CI                        [14, 2]      [130, 21]\n",
      "                                                    \n",
      "Relative Effect                 21.1%          21.1%\n",
      "95% CI                  [36.2%, 5.9%]  [36.2%, 5.9%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 48.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 40. The 95% interval of\n",
      "this counterfactual prediction is [34, 46]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 8 with a 95% interval of [14, 2]. For a\n",
      "discussion of 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 437.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 361. The 95% interval of this prediction is [306, 416]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  21.1%. The 95% interval of this percentage is [36.2%, 5.9%]\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 8 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Eli Lilly and Company =====\n",
      "The mean absolute percentage error in the pre period is 0.04%\n",
      "                               Average      Cumulative\n",
      "Actual                             142            1282\n",
      "Predicted                          130            1173\n",
      "95% CI                      [112, 147]    [1016, 1330]\n",
      "                                                      \n",
      "Absolute Effect                     12             109\n",
      "95% CI                        [29, -5]      [266, -47]\n",
      "                                                      \n",
      "Relative Effect                   9.3%            9.3%\n",
      "95% CI                  [22.7%, -4.1%]  [22.7%, -4.1%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                             142            1282\n",
      "Predicted                          130            1173\n",
      "95% CI                      [112, 147]    [1016, 1330]\n",
      "                                                      \n",
      "Absolute Effect                     12             109\n",
      "95% CI                        [29, -5]      [266, -47]\n",
      "                                                      \n",
      "Relative Effect                   9.3%            9.3%\n",
      "95% CI                  [22.7%, -4.1%]  [22.7%, -4.1%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 142.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 130. The 95% interval of\n",
      "this counterfactual prediction is [112, 147]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 12 with a 95% interval of [29, -5].\n",
      "For a discussion of 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 1282.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 1173. The 95% interval of this prediction is [1016, 1330]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  9.3%. The 95% interval of this percentage is [22.7%, -4.1%]\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 12 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== AbbVie Inc. =====\n",
      "The mean absolute percentage error in the pre period is 0.05%\n",
      "                               Average      Cumulative\n",
      "Actual                              77             700\n",
      "Predicted                           89             808\n",
      "95% CI                       [72, 107]      [651, 965]\n",
      "                                                      \n",
      "Absolute Effect                    -12            -108\n",
      "95% CI                        [5, -29]      [48, -265]\n",
      "                                                      \n",
      "Relative Effect                 -13.4%          -13.4%\n",
      "95% CI                  [6.0%, -32.9%]  [6.0%, -32.9%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              77             700\n",
      "Predicted                           89             808\n",
      "95% CI                       [72, 107]      [651, 965]\n",
      "                                                      \n",
      "Absolute Effect                    -12            -108\n",
      "95% CI                        [5, -29]      [48, -265]\n",
      "                                                      \n",
      "Relative Effect                 -13.4%          -13.4%\n",
      "95% CI                  [6.0%, -32.9%]  [6.0%, -32.9%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 77.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 89. The 95% interval of\n",
      "this counterfactual prediction is [72, 107]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is -12 with a 95% interval of [5, -29].\n",
      "For a discussion of 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 700.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 808. The 95% interval of this prediction is [651, 965]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  a decrease\n",
      "of  -13.4%. The 95% interval of this percentage is [6.0%, -32.9%]\n",
      "\n",
      "\n",
      " This  means that the negative effect observed during the intervention period is statistically significant. If the\n",
      "experimenter had expected a positive effect, it is recommended to double-check whether anomalies in the control\n",
      "variables may have caused an overly optimistic expectation of what should have happened in the response variable in the\n",
      "absence of the intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "covid_causal_impact(pharma_companies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Amazon.com, Inc. =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                               Average      Cumulative\n",
      "Actual                             138            1247\n",
      "Predicted                          135            1216\n",
      "95% CI                      [124, 146]    [1118, 1314]\n",
      "                                                      \n",
      "Absolute Effect                      3              30\n",
      "95% CI                        [14, -7]      [128, -66]\n",
      "                                                      \n",
      "Relative Effect                   2.5%            2.5%\n",
      "95% CI                  [10.6%, -5.5%]  [10.6%, -5.5%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                             138            1247\n",
      "Predicted                          135            1216\n",
      "95% CI                      [124, 146]    [1118, 1314]\n",
      "                                                      \n",
      "Absolute Effect                      3              30\n",
      "95% CI                        [14, -7]      [128, -66]\n",
      "                                                      \n",
      "Relative Effect                   2.5%            2.5%\n",
      "95% CI                  [10.6%, -5.5%]  [10.6%, -5.5%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 138.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 135. The 95% interval of\n",
      "this counterfactual prediction is [124, 146]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 3 with a 95% interval of [14, -7].\n",
      "For a discussion of 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 1247.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 1216. The 95% interval of this prediction is [1118, 1314]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  2.5%. The 95% interval of this percentage is [10.6%, -5.5%]\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 3 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Industria de Diseño Textil, S.A. =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                               Average      Cumulative\n",
      "Actual                              21             196\n",
      "Predicted                           25             229\n",
      "95% CI                        [21, 29]      [195, 263]\n",
      "                                                      \n",
      "Absolute Effect                     -3             -33\n",
      "95% CI                         [0, -7]        [0, -67]\n",
      "                                                      \n",
      "Relative Effect                 -14.5%          -14.5%\n",
      "95% CI                  [0.3%, -29.3%]  [0.3%, -29.3%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              21             196\n",
      "Predicted                           25             229\n",
      "95% CI                        [21, 29]      [195, 263]\n",
      "                                                      \n",
      "Absolute Effect                     -3             -33\n",
      "95% CI                         [0, -7]        [0, -67]\n",
      "                                                      \n",
      "Relative Effect                 -14.5%          -14.5%\n",
      "95% CI                  [0.3%, -29.3%]  [0.3%, -29.3%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 21.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 25. The 95% interval of\n",
      "this counterfactual prediction is [21, 29]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is -3 with a 95% interval of [0, -7]. For a\n",
      "discussion of 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 196.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 229. The 95% interval of this prediction is [195, 263]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  a decrease\n",
      "of  -14.5%. The 95% interval of this percentage is [0.3%, -29.3%]\n",
      "\n",
      "\n",
      " This  means that the negative effect observed during the intervention period is statistically significant. If the\n",
      "experimenter had expected a positive effect, it is recommended to double-check whether anomalies in the control\n",
      "variables may have caused an overly optimistic expectation of what should have happened in the response variable in the\n",
      "absence of the intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Hennes & Mauritz AB =====\n",
      "The mean absolute percentage error in the pre period is 0.05%\n",
      "                                Average       Cumulative\n",
      "Actual                                2               24\n",
      "Predicted                             2               25\n",
      "95% CI                           [1, 3]         [17, 32]\n",
      "                                                        \n",
      "Absolute Effect                       0                0\n",
      "95% CI                           [0, 0]          [6, -8]\n",
      "                                                        \n",
      "Relative Effect                   -3.7%            -3.7%\n",
      "95% CI                  [26.0%, -33.4%]  [26.0%, -33.4%]\n",
      "                                                        \n",
      "P-value                            0.0%                 \n",
      "Prob. of Causal Effect           100.0%                 \n",
      "None\n",
      "                                Average       Cumulative\n",
      "Actual                                2               24\n",
      "Predicted                             2               25\n",
      "95% CI                           [1, 3]         [17, 32]\n",
      "                                                        \n",
      "Absolute Effect                       0                0\n",
      "95% CI                           [0, 0]          [6, -8]\n",
      "                                                        \n",
      "Relative Effect                   -3.7%            -3.7%\n",
      "95% CI                  [26.0%, -33.4%]  [26.0%, -33.4%]\n",
      "                                                        \n",
      "P-value                            0.0%                 \n",
      "Prob. of Causal Effect           100.0%                 \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 2.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 2. The 95% interval of\n",
      "this counterfactual prediction is [1, 3]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 0 with a 95% interval of [0, 0]. For a\n",
      "discussion of 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 24.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 25. The 95% interval of this prediction is [17, 32]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  a decrease\n",
      "of  -3.7%. The 95% interval of this percentage is [26.0%, -33.4%]\n",
      "\n",
      "\n",
      " This  means that the negative effect observed during the intervention period is statistically significant. If the\n",
      "experimenter had expected a positive effect, it is recommended to double-check whether anomalies in the control\n",
      "variables may have caused an overly optimistic expectation of what should have happened in the response variable in the\n",
      "absence of the intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== LVMH Moët Hennessy Louis Vuitton S.E. =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                              Average     Cumulative\n",
      "Actual                            368           3316\n",
      "Predicted                         327           2946\n",
      "95% CI                     [290, 363]   [2617, 3274]\n",
      "                                                    \n",
      "Absolute Effect                    41            370\n",
      "95% CI                        [77, 4]      [698, 42]\n",
      "                                                    \n",
      "Relative Effect                 12.6%          12.6%\n",
      "95% CI                  [23.7%, 1.4%]  [23.7%, 1.4%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                            368           3316\n",
      "Predicted                         327           2946\n",
      "95% CI                     [290, 363]   [2617, 3274]\n",
      "                                                    \n",
      "Absolute Effect                    41            370\n",
      "95% CI                        [77, 4]      [698, 42]\n",
      "                                                    \n",
      "Relative Effect                 12.6%          12.6%\n",
      "95% CI                  [23.7%, 1.4%]  [23.7%, 1.4%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 368.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 327. The 95% interval of\n",
      "this counterfactual prediction is [290, 363]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 41 with a 95% interval of [77, 4].\n",
      "For a discussion of 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 3316.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 2946. The 95% interval of this prediction is [2617, 3274]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  12.6%. The 95% interval of this percentage is [23.7%, 1.4%]\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 41 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Fast Retailing Co., Ltd. =====\n",
      "The mean absolute percentage error in the pre period is 0.06%\n",
      "                               Average       Cumulative\n",
      "Actual                           19835           178516\n",
      "Predicted                        12310           110796\n",
      "95% CI                   [8491, 16129]  [76425, 145167]\n",
      "                                                       \n",
      "Absolute Effect                   7524            67719\n",
      "95% CI                   [11343, 3705]  [102090, 33348]\n",
      "                                                       \n",
      "Relative Effect                  61.1%            61.1%\n",
      "95% CI                  [92.1%, 30.1%]   [92.1%, 30.1%]\n",
      "                                                       \n",
      "P-value                           0.0%                 \n",
      "Prob. of Causal Effect          100.0%                 \n",
      "None\n",
      "                               Average       Cumulative\n",
      "Actual                           19835           178516\n",
      "Predicted                        12310           110796\n",
      "95% CI                   [8491, 16129]  [76425, 145167]\n",
      "                                                       \n",
      "Absolute Effect                   7524            67719\n",
      "95% CI                   [11343, 3705]  [102090, 33348]\n",
      "                                                       \n",
      "Relative Effect                  61.1%            61.1%\n",
      "95% CI                  [92.1%, 30.1%]   [92.1%, 30.1%]\n",
      "                                                       \n",
      "P-value                           0.0%                 \n",
      "Prob. of Causal Effect          100.0%                 \n",
      "During the post-intervention period, the response             variable had an average value of             approx.\n",
      "19835.  By contrast, in  the absence of an intervention, we would have expected an average response of 12310. The 95%\n",
      "interval of this counterfactual prediction is [8491, 16129]. Subtracting this prediction from the observed response\n",
      "yields an estimate of the causal effect the intervention had on the response variable. This effect is 7524 with a 95%\n",
      "interval of [11343, 3705]. For a discussion of 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 178516.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 110796. The 95% interval of this prediction is [76425, 145167]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  61.1%. The 95% interval of this percentage is [92.1%, 30.1%]\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 7524 to the original goal of the\n",
      "underlying intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "covid_causal_impact(retail)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== The Coca-Cola Company (KO) =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                                Average       Cumulative\n",
      "Actual                               43              387\n",
      "Predicted                            49              441\n",
      "95% CI                         [44, 53]       [401, 481]\n",
      "                                                        \n",
      "Absolute Effect                      -5              -53\n",
      "95% CI                        [-1, -10]       [-13, -93]\n",
      "                                                        \n",
      "Relative Effect                  -12.2%           -12.2%\n",
      "95% CI                  [-3.1%, -21.3%]  [-3.1%, -21.3%]\n",
      "                                                        \n",
      "P-value                            0.0%                 \n",
      "Prob. of Causal Effect           100.0%                 \n",
      "None\n",
      "                                Average       Cumulative\n",
      "Actual                               43              387\n",
      "Predicted                            49              441\n",
      "95% CI                         [44, 53]       [401, 481]\n",
      "                                                        \n",
      "Absolute Effect                      -5              -53\n",
      "95% CI                        [-1, -10]       [-13, -93]\n",
      "                                                        \n",
      "Relative Effect                  -12.2%           -12.2%\n",
      "95% CI                  [-3.1%, -21.3%]  [-3.1%, -21.3%]\n",
      "                                                        \n",
      "P-value                            0.0%                 \n",
      "Prob. of Causal Effect           100.0%                 \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 43.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 49. The 95% interval of\n",
      "this counterfactual prediction is [44, 53]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is -5 with a 95% interval of [-1, -10]. For\n",
      "a discussion of 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 387.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 441. The 95% interval of this prediction is [401, 481]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  a decrease\n",
      "of  -12.2%. The 95% interval of this percentage is [-3.1%, -21.3%]\n",
      "\n",
      "\n",
      " This  means that the negative effect observed during the intervention period is statistically significant. If the\n",
      "experimenter had expected a positive effect, it is recommended to double-check whether anomalies in the control\n",
      "variables may have caused an overly optimistic expectation of what should have happened in the response variable in the\n",
      "absence of the intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Colgate-Palmolive Company (CL): =====\n",
      "The mean absolute percentage error in the pre period is 0.02%\n",
      "                               Average      Cumulative\n",
      "Actual                              68             620\n",
      "Predicted                           61             551\n",
      "95% CI                        [53, 68]      [483, 620]\n",
      "                                                      \n",
      "Absolute Effect                      7              68\n",
      "95% CI                         [15, 0]        [137, 0]\n",
      "                                                      \n",
      "Relative Effect                  12.4%           12.4%\n",
      "95% CI                  [24.9%, -0.0%]  [24.9%, -0.0%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "None\n",
      "                               Average      Cumulative\n",
      "Actual                              68             620\n",
      "Predicted                           61             551\n",
      "95% CI                        [53, 68]      [483, 620]\n",
      "                                                      \n",
      "Absolute Effect                      7              68\n",
      "95% CI                         [15, 0]        [137, 0]\n",
      "                                                      \n",
      "Relative Effect                  12.4%           12.4%\n",
      "95% CI                  [24.9%, -0.0%]  [24.9%, -0.0%]\n",
      "                                                      \n",
      "P-value                           0.0%                \n",
      "Prob. of Causal Effect          100.0%                \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 68.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 61. The 95% interval of\n",
      "this counterfactual prediction is [53, 68]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 7 with a 95% interval of [15, 0]. For a\n",
      "discussion of 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 620.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 551. The 95% interval of this prediction is [483, 620]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  12.4%. The 95% interval of this percentage is [24.9%, -0.0%]\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 7 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Kimberly-Clark Corporation (KMB) =====\n",
      "The mean absolute percentage error in the pre period is 0.02%\n",
      "                              Average     Cumulative\n",
      "Actual                            126           1134\n",
      "Predicted                         111           1002\n",
      "95% CI                      [98, 123]    [890, 1114]\n",
      "                                                    \n",
      "Absolute Effect                    14            131\n",
      "95% CI                        [27, 2]      [243, 19]\n",
      "                                                    \n",
      "Relative Effect                 13.1%          13.1%\n",
      "95% CI                  [24.3%, 2.0%]  [24.3%, 2.0%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                            126           1134\n",
      "Predicted                         111           1002\n",
      "95% CI                      [98, 123]    [890, 1114]\n",
      "                                                    \n",
      "Absolute Effect                    14            131\n",
      "95% CI                        [27, 2]      [243, 19]\n",
      "                                                    \n",
      "Relative Effect                 13.1%          13.1%\n",
      "95% CI                  [24.3%, 2.0%]  [24.3%, 2.0%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 126.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 111. The 95% interval of\n",
      "this counterfactual prediction is [98, 123]. Subtracting this prediction from the observed response yields an estimate\n",
      "of the causal effect the intervention had on the response variable. This effect is 14 with a 95% interval of [27, 2].\n",
      "For a discussion of 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 1134.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 1002. The 95% interval of this prediction is [890, 1114]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  13.1%. The 95% interval of this percentage is [24.3%, 2.0%]\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 14 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== Unilever (UL) =====\n",
      "The mean absolute percentage error in the pre period is 0.03%\n",
      "                              Average     Cumulative\n",
      "Actual                             50            451\n",
      "Predicted                          44            397\n",
      "95% CI                       [39, 49]     [351, 442]\n",
      "                                                    \n",
      "Absolute Effect                     5             53\n",
      "95% CI                        [11, 0]        [99, 8]\n",
      "                                                    \n",
      "Relative Effect                 13.5%          13.5%\n",
      "95% CI                  [25.0%, 2.1%]  [25.0%, 2.1%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "None\n",
      "                              Average     Cumulative\n",
      "Actual                             50            451\n",
      "Predicted                          44            397\n",
      "95% CI                       [39, 49]     [351, 442]\n",
      "                                                    \n",
      "Absolute Effect                     5             53\n",
      "95% CI                        [11, 0]        [99, 8]\n",
      "                                                    \n",
      "Relative Effect                 13.5%          13.5%\n",
      "95% CI                  [25.0%, 2.1%]  [25.0%, 2.1%]\n",
      "                                                    \n",
      "P-value                          0.0%               \n",
      "Prob. of Causal Effect         100.0%               \n",
      "During the post-intervention period, the response             variable had an average value of             approx. 50.\n",
      "By contrast, in  the absence of an intervention, we would have expected an average response of 44. The 95% interval of\n",
      "this counterfactual prediction is [39, 49]. Subtracting this prediction from the observed response yields an estimate of\n",
      "the causal effect the intervention had on the response variable. This effect is 5 with a 95% interval of [11, 0]. For a\n",
      "discussion of 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 451.  By contrast, had  the intervention not taken place, we\n",
      "would have expected a sum of 397. The 95% interval of this prediction is [351, 442]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  13.5%. The 95% interval of this percentage is [25.0%, 2.1%]\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 5 to the original goal of the underlying\n",
      "intervention.\n",
      "\n",
      "\n",
      "The probability of obtaining this effect by                 chance is very small (Bayesian one-sided tail-area\n",
      "probability 0.0). This means the                 causal effect can be considered statistically\n",
      "significant.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joanp\\AppData\\Local\\Temp\\ipykernel_39932\\4049619924.py:13: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "c:\\Users\\joanp\\anaconda3\\envs\\causal_inference_ts\\Lib\\site-packages\\statsmodels\\tsa\\statespace\\representation.py:374: FutureWarning:\n",
      "\n",
      "Unknown keyword arguments: dict_keys(['alpha']).Passing unknown keyword arguments will raise a TypeError beginning in version 0.15.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "covid_causal_impact(consumer_staples)"
   ]
  }
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