add changes to show financial impact

.gitignore

@@ -1,3 +1,5 @@
+bq-service-account.json
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

Dockerfile

@@ -3,6 +3,9 @@ FROM ebmdatalab/datalab-jupyter:python3.8.1-2328e31e7391a127fe7184dcce38d581a17b
 # Set up jupyter environment
 ENV MAIN_PATH=/home/app/notebook
 
+# Set path to BQ service account credentials
+ENV EBMDATALAB_BQ_CREDENTIALS_PATH=/tmp/bq-service-account.json
+
 # Install pip requirements
 COPY requirements.txt /tmp/
 # Hack until this is fixed https://github.com/jazzband/pip-tools/issues/823
@@ -18,3 +21,7 @@ COPY config/kernel.json /tmp/kernel_with_custom_path/kernel.json
 RUN jupyter kernelspec install /tmp/kernel_with_custom_path/ --user --name="python3"
 
 CMD cd ${MAIN_PATH} && PYTHONPATH=${MAIN_PATH} jupyter lab --config=config/jupyter_notebook_config.py
+
+# Copy BQ service account credentials into container
+# We work around the credentials not existing in CI with the glob
+COPY bq-service-account.jso[n] /tmp/

Untitled1.ipynb

@@ -0,0 +1,81 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import lxml\n",
+    "url = 'https://www.nhsbsa.nhs.uk/prescription-data/understanding-our-data/financial-forecasting'\n",
+    "dfs = pd.read_html(url,match='National Average Discount Percentage')\n",
+    "nadp = []\n",
+    "for i in range(len(dfs)):\n",
+    "    nadp.append(dfs[i])\n",
+    "nadp = pd.concat(nadp)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Used for Reports in  National Average Discount Percentage\n",
+      "0               May 23                                  5.83\n",
+      "1               Apr 23                                  5.87\n",
+      "0               Mar 23                                  6.26\n",
+      "1               Feb 23                                  6.25\n",
+      "2               Jan 23                                  6.31\n",
+      "..                 ...                                   ...\n",
+      "7               Aug 14                                  7.58\n",
+      "8               Jul 14                                  7.52\n",
+      "9               Jun 14                                  7.65\n",
+      "10              May 14                                  7.58\n",
+      "11              Apr 14                                  7.66\n",
+      "\n",
+      "[110 rows x 2 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(nadp)"
+   ]
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "cell_metadata_filter": "all",
+   "notebook_metadata_filter": "all,-language_info",
+   "text_representation": {
+    "extension": ".py",
+    "format_name": "light",
+    "format_version": "1.5",
+    "jupytext_version": "1.3.3"
+   }
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

data/.tariff.csv.7772cca87e2bdb9915f82cbd881818d5.tmp

@@ -0,0 +1 @@
+File created by /root/.pyenv/versions/3.8.1/lib/python3.8/site-packages/ebmdatalab/bq.py

data/annual_profile_df.csv

@@ -1,13 +1,13 @@
 mon,proportion
-7,0.998019361116844
-6,1.0011445161388608
-12,1.020719747207815
-9,0.983024391120719
-11,1.0103182599728644
-5,1.0132683003697376
-2,0.9300136715235
-1,1.0210364502878688
-8,1.018761368914048
-10,1.0180766373390042
-4,0.9743263654749805
-3,1.0112909305361506
+12,1.020719748393862
+9,0.9830243887130287
+5,1.0132683015464579
+2,0.930013672601688
+1,1.0210364514741121
+4,0.9743263630566492
+6,1.0011445173009053
+11,1.0103182611460548
+3,1.0112909317104446
+7,0.9980193622754345
+8,1.0187613665492745
+10,1.0180766349736152

data/nadp_fixed.csv

@@ -1,4 +1,10 @@
 month,nadp
+2023-02-01,6.25
+2023-01-01,6.31
+2022-12-01,6.51
+2022-11-01,6.50
+2022-10-01,6.62
+2022-09-01,6.53
 2022-08-01,6.55
 2022-07-01,6.5
 2022-06-01,6.45