NIH_RePORTER_database.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Intro"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, you will find the instructions to download and preprocess the NIH RePORTER dataset starting from 1985.\n",
    "\n",
    "You will also find the steps to build the tables for a Microsoft SQL Server database that is hosted at OST (UQÀM)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Download the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First of all, you need to manually download the CSV files you need and put them in your folder `content/downloads/zipped`. NIH now prevents us from webscraping the files.\n",
    "\n",
    "* Download the files here: https://reporter.nih.gov/exporter\n",
    "\n",
    "There is one data dump (i.e. CSV file) per year. Download the files from 1985 to the current year."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Take a look at the NIH RePORTER documentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset is quite complex. Please refer to the following links to understand what the fields and acronyms are:\n",
    "\n",
    "* Fields description: https://report.nih.gov/exporter-data-dictionary\n",
    "* Glossary: https://grants.nih.gov/grants/glossary.htm\n",
    "* Activity codes: https://grants.nih.gov/grants/funding/ac_search_results.htm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xtqSHg8_3i05"
   },
   "source": [
    "# Imports and variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "module_path = os.path.abspath(os.path.join('..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "    \n",
    "import glob\n",
    "import zipfile\n",
    "import csv\n",
    "import pandas as pd\n",
    "import itertools\n",
    "import re\n",
    "from datetime import datetime\n",
    "from utils.csv_headers import *\n",
    "from collections import OrderedDict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "CURRENT_PATH = os.getcwd()\n",
    "UNZIPPED_DIR = os.path.join(CURRENT_PATH,'content/downloads/unzipped')\n",
    "OUTPUT_FILE = os.path.join(CURRENT_PATH,'content/output_sql.tsv')\n",
    "ENHANCED_FILE = os.path.join(CURRENT_PATH,'content/enhanced-output_sql.tsv')\n",
    "TABLE_DIR = os.path.join(CURRENT_PATH,'content/tables/')\n",
    "\n",
    "# These parameters should work best with Microsoft SQL Server - unfortunately, it doesn't work well with standard CSV files\n",
    "OUTPUT_ENCODING = 'utf-8' # tried with others, but utf-8 is better because multiple encodings in input file & gender file \n",
    "NEWLINE = '' # Mario from OST told me to use that\n",
    "DELIMITER = '\\t' # Mario from OST told me to use that"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check the file encoding, run `file --mime-encoding *`:                                                                      \n",
    "\n",
    "| Filename | Encoding |\n",
    "| :--- | :--- |\n",
    "| RePORTER_PRJ_C_FY1985.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1986.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1987.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1988.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1989.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1990.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1991.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1992.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1993.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1994.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1995.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1996.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1997.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1998.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY1999.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2000.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2001.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2002.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2003.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2004.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2005.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2006.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2007.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2008.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2009.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2010.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2011.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2012.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2013.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2014.csv: | us-ascii |\n",
    "| RePORTER_PRJ_C_FY2015.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2016_new.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2017_new.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2018_new.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2019_new.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2020.csv: | iso-8859-1 |\n",
    "| RePORTER_PRJ_C_FY2021.csv: | iso-8859-1 |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, after several tests, it seems like the tool that guesses the encodings made some errors. I did not manage to process any file with `us-ascii` encoding. So I tried with `iso-8859-1` for all the files and it worked (see a few cells below)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wwMeFO8IA9EC"
   },
   "source": [
    "# Data preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dkRq4gKiWxtx"
   },
   "source": [
    "## Unzip the CSV files and concatenate them in a single file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def is_integer(string):\n",
    "    try:\n",
    "        int(string)\n",
    "        return True\n",
    "    except ValueError as a:\n",
    "        return False\n",
    "    \n",
    "def is_corrupted(dict_row):\n",
    "    empty_column = None in dict_row\n",
    "    is_application_id_not_integer = not is_integer(dict_row[APPLICATION_ID])   \n",
    "    return empty_column or is_application_id_not_integer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7aPtvpzIC0oh",
    "outputId": "3ee8057d-dfaf-4495-a02f-808bdb75b161"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2021.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2020.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2019_new.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2018_new.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2017_new.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2016_new.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2015.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2014.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2013.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2012.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2011.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2010.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2009.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2008.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2007.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2006.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2005.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2004.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2003.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2002.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2001.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY2000.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1999.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1998.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1997.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1996.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1995.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1994.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1993.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1992.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1991.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1990.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1989.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1988.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1987.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1986.csv\n",
      "/home/sarah/code/scameronp/nih-reporter/content/downloads/unzipped/RePORTER_PRJ_C_FY1985.csv\n"
     ]
    }
   ],
   "source": [
    "with open(OUTPUT_FILE, 'w', encoding=OUTPUT_ENCODING, newline=NEWLINE) as output_file:\n",
    "    writer = csv.DictWriter(output_file, fieldnames=ORDERED_HEADERS, delimiter=DELIMITER)\n",
    "    writer.writeheader()\n",
    "\n",
    "    csv_files = sorted(glob.glob(UNZIPPED_DIR + \"/*.csv\"), reverse=True)\n",
    "\n",
    "    for csv_file_name in csv_files:\n",
    "        print(csv_file_name)\n",
    "\n",
    "        with open(csv_file_name, 'r', encoding='iso-8859-1', newline=NEWLINE) as csv_file_descriptor:\n",
    "            reader = csv.DictReader(csv_file_descriptor, delimiter=',', quotechar='\"')\n",
    "            \n",
    "            for index, dict_row in enumerate(reader):\n",
    "                if is_corrupted(dict_row):\n",
    "                    print(csv_file_name, index, dict_row[APPLICATION_ID])\n",
    "                else:\n",
    "                    upper_dict = dict()\n",
    "                    for key, value in dict_row.items():\n",
    "                        try:\n",
    "                            # letter case uniformization\n",
    "                            upper_dict[key.upper()] = value.replace(\"\\n\", \"\").replace(\"\\t\", \" \")\n",
    "                        except Exception as e:\n",
    "                            print(e)\n",
    "                            print(dict_row)\n",
    "                            print(csv_file_name)\n",
    "                            #raise e\n",
    "                    writer.writerow(upper_dict)\n",
    "                \n",
    "#         break # uncomment to test with only the most recent file\n",
    "\n",
    "# I manually corrected 3 files where double-quotes in PI name were not properly escaped (Firstname \"Julie\" Lastname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-SeT387SDQ9L"
   },
   "source": [
    "## Enhance the dataset\n",
    "\n",
    "* Extract the contact PI first name & assign the most probable gender based on US census dataset\n",
    "* Add application type name from NIH documentation & match on application type code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "id": "mm4-ol6lWmtG"
   },
   "outputs": [],
   "source": [
    "# Functions used for gender identification\n",
    "def string_to_list(string):\n",
    "    pi_list = []\n",
    "    for string_part in string.rstrip('; ').split(';'):\n",
    "        string_part = string_part.strip(', ').replace('\"', '')\n",
    "        if string_part != '':\n",
    "            pi_list.append(string_part)\n",
    "    return pi_list\n",
    "\n",
    "\n",
    "def filter_contact_pi(pi_ids_or_names_list):\n",
    "    filtered_list = []\n",
    "    for item in pi_ids_or_names_list: \n",
    "         if '(contact)' in item:\n",
    "            filtered_list.append(item)\n",
    "    return filtered_list\n",
    "\n",
    "\n",
    "def extract_contact_pi(pi_ids_or_names_list):\n",
    "    if len(pi_ids_or_names_list) == 0:\n",
    "        return None, \"no_value\"\n",
    "    elif len(pi_ids_or_names_list) == 1:\n",
    "        return pi_ids_or_names_list[0], \"single_value\"\n",
    "    else:              \n",
    "        filtered_pi_ids_or_names = filter_contact_pi(pi_ids_or_names_list)\n",
    "        if len(filtered_pi_ids_or_names) == 0:\n",
    "            return pi_ids_or_names_list[0], \"multiple_values_but_no_explicit_contact_first_chosen\"\n",
    "        elif len(filtered_pi_ids_or_names) == 1:\n",
    "            return filtered_pi_ids_or_names[0], \"multiple_values_and_single_explicit_contact\"\n",
    "        else:\n",
    "            return filtered_pi_ids_or_names[0], \"multiple_values_and_multiple_explicit_contacts_first_chosen\"\n",
    "\n",
    "\n",
    "def normalize_first_name(first_name):\n",
    "    first_name = re.sub('[\\.\\-\\;\\,]', '', first_name)\n",
    "    first_name = re.sub(' +', ' ', first_name)\n",
    "    first_name_parts = first_name.strip(' ').split(' ')\n",
    "    l = []\n",
    "    for part in first_name_parts:\n",
    "        if len(part) > 1:\n",
    "            l.append(part)\n",
    "    return ' '.join(l).upper()\n",
    "\n",
    "\n",
    "def extract_pi_first_name(full_name):\n",
    "    if full_name is None:\n",
    "        return None\n",
    "    else:\n",
    "        full_name_list = full_name.split(',')\n",
    "        if len(full_name_list) <= 1:\n",
    "            return None\n",
    "        else:\n",
    "            return normalize_first_name(full_name_list[1].replace('(contact)', ''))\n",
    "        \n",
    "        \n",
    "# Function used to add application type name\n",
    "def application_type_name(application_type):\n",
    "    \n",
    "    if application_type == \"\":\n",
    "        return None\n",
    "    else:\n",
    "        application_type_num = int(float(application_type))\n",
    "        application_type_mapping = {\n",
    "            1: \"New application\",\n",
    "            2: \"Competing continuation\",\n",
    "            3: \"Application for additional support\",\n",
    "            4: \"Competing extension for an R37 award or first non-competing year of a Fast-Track SBIR/STTR award\",\n",
    "            5: \"Non-competing continuation\",\n",
    "            7: \"Change of grantee institution\",\n",
    "            9: \"Change of NIH awarding Institute or Division\"\n",
    "        }\n",
    "        return application_type_mapping.get(application_type_num)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "id": "TxWmUc8oXPrL"
   },
   "outputs": [],
   "source": [
    "# upload and clean gender_US_names.csv list\n",
    "GENDER_FILE = os.path.join(CURRENT_PATH,'content/gender_US_names.csv')\n",
    "\n",
    "with open(GENDER_FILE, 'r', encoding='UTF-8-sig', newline=NEWLINE) as csv_file_descriptor:\n",
    "    gender_dataset = csv.DictReader(csv_file_descriptor, delimiter=',', quotechar='\"')\n",
    "\n",
    "    gender_dict = {}\n",
    "\n",
    "    for item in gender_dataset:\n",
    "        normalized_first_name = normalize_first_name(item['Name'])\n",
    "        gender_dict[normalized_first_name] = item['Gender']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "id": "uJ2PoiZ0Dckb"
   },
   "outputs": [],
   "source": [
    "# enhance output.csv file with contact PIs extraction and gender assignment & application type name\n",
    "with open(ENHANCED_FILE, 'w', encoding=OUTPUT_ENCODING, newline=NEWLINE) as output_file:\n",
    "    writer = csv.DictWriter(output_file, fieldnames=[\n",
    "        APPLICATION_ID,\n",
    "        ACTIVITY,\n",
    "        ADMINISTERING_IC,\n",
    "        APPLICATION_TYPE,\n",
    "        APPLICATION_TYPE_NAME,\n",
    "        ARRA_FUNDED,\n",
    "        AWARD_NOTICE_DATE,\n",
    "        BUDGET_START,\n",
    "        BUDGET_END,\n",
    "        CFDA_CODE,\n",
    "        CORE_PROJECT_NUM,\n",
    "        ED_INST_TYPE,\n",
    "        FOA_NUMBER,\n",
    "        FULL_PROJECT_NUM,\n",
    "        FUNDING_ICS,\n",
    "        FUNDING_MECHANISM,\n",
    "        FY,\n",
    "        IC_NAME,\n",
    "        NIH_SPENDING_CATS,\n",
    "        ORG_CITY,\n",
    "        ORG_COUNTRY,\n",
    "        ORG_DEPT,\n",
    "        ORG_DISTRICT,\n",
    "        ORG_DUNS,\n",
    "        ORG_FIPS,\n",
    "        ORG_IPF_CODE,\n",
    "        ORG_NAME,\n",
    "        ORG_STATE,\n",
    "        ORG_ZIPCODE,\n",
    "        PHR,\n",
    "        PI_IDS,\n",
    "        PI_NAMES,\n",
    "        NB_PI_IDS,\n",
    "        NB_PI_NAMES,\n",
    "        CONTACT_PI_ID, \n",
    "        CONTACT_PI_NAME, \n",
    "        CONTACT_PI_ID_STATUS, \n",
    "        CONTACT_PI_NAME_STATUS,\n",
    "        CONTACT_PI_FIRST_NAME,\n",
    "        CONTACT_PI_GENDER,\n",
    "        PROGRAM_OFFICER_NAME,\n",
    "        PROJECT_START,\n",
    "        PROJECT_END,\n",
    "        PROJECT_TERMS,\n",
    "        PROJECT_TITLE,\n",
    "        SERIAL_NUMBER,\n",
    "        STUDY_SECTION,\n",
    "        STUDY_SECTION_NAME,\n",
    "        SUBPROJECT_ID,\n",
    "        SUFFIX,\n",
    "        SUPPORT_YEAR,\n",
    "        DIRECT_COST_AMT,\n",
    "        INDIRECT_COST_AMT,\n",
    "        TOTAL_COST,\n",
    "        TOTAL_COST_SUB_PROJECT\n",
    "    ], delimiter=DELIMITER)\n",
    "    writer.writeheader()\n",
    "\n",
    "\n",
    "    with open(OUTPUT_FILE, 'r', encoding=OUTPUT_ENCODING, newline=NEWLINE) as input_file:\n",
    "        reader = csv.DictReader(input_file, delimiter=DELIMITER)\n",
    "\n",
    "        for index, input_row in enumerate(reader):\n",
    "            \n",
    "            pi_ids_list = string_to_list(input_row[PI_IDS])\n",
    "            pi_names_list = string_to_list(input_row[PI_NAMES])\n",
    "\n",
    "            try:\n",
    "                contact_pi_id, pi_id_status = extract_contact_pi(pi_ids_list)\n",
    "                contact_pi_name, pi_name_status = extract_contact_pi(pi_names_list)\n",
    "            except Exception as e:\n",
    "                print('APPLICATION_ID', input_row[APPLICATION_ID])\n",
    "                print('PI_IDS', input_row[PI_IDS])\n",
    "                print('PI_NAMES', input_row[PI_NAMES])\n",
    "                print('+++')\n",
    "                print(pi_ids_list)\n",
    "                print(pi_names_list)\n",
    "                print(e)\n",
    "                print('----------------')\n",
    "\n",
    "            contact_pi_first_name = extract_pi_first_name(contact_pi_name)\n",
    "\n",
    "            dict_row = {\n",
    "                APPLICATION_ID: input_row[APPLICATION_ID],\n",
    "                ACTIVITY: input_row[ACTIVITY],\n",
    "                ADMINISTERING_IC: input_row[ADMINISTERING_IC],\n",
    "                APPLICATION_TYPE: input_row[APPLICATION_TYPE],\n",
    "                APPLICATION_TYPE_NAME: application_type_name(input_row[APPLICATION_TYPE]),\n",
    "                ARRA_FUNDED: input_row[ARRA_FUNDED],\n",
    "                AWARD_NOTICE_DATE: input_row[AWARD_NOTICE_DATE],\n",
    "                BUDGET_START: input_row[BUDGET_START],\n",
    "                BUDGET_END: input_row[BUDGET_END],\n",
    "                CFDA_CODE: input_row[CFDA_CODE],\n",
    "                CORE_PROJECT_NUM: input_row[CORE_PROJECT_NUM],\n",
    "                ED_INST_TYPE: input_row[ED_INST_TYPE],\n",
    "                FOA_NUMBER: input_row[FOA_NUMBER],\n",
    "                FULL_PROJECT_NUM: input_row[FULL_PROJECT_NUM],\n",
    "                FUNDING_ICS: input_row[FUNDING_ICS],\n",
    "                FUNDING_MECHANISM: input_row[FUNDING_MECHANISM],\n",
    "                FY: input_row[FY],\n",
    "                IC_NAME: input_row[IC_NAME],\n",
    "                NIH_SPENDING_CATS: input_row[NIH_SPENDING_CATS],\n",
    "                ORG_CITY: input_row[ORG_CITY],\n",
    "                ORG_COUNTRY: input_row[ORG_COUNTRY],\n",
    "                ORG_DEPT: input_row[ORG_DEPT],\n",
    "                ORG_DISTRICT: input_row[ORG_DISTRICT],\n",
    "                ORG_DUNS: input_row[ORG_DUNS],\n",
    "                ORG_FIPS: input_row[ORG_FIPS],\n",
    "                ORG_IPF_CODE: input_row[ORG_IPF_CODE],\n",
    "                ORG_NAME: input_row[ORG_NAME],\n",
    "                ORG_STATE: input_row[ORG_STATE],\n",
    "                ORG_ZIPCODE: input_row[ORG_ZIPCODE],\n",
    "                PHR: input_row[PHR],\n",
    "                PI_IDS: input_row[PI_IDS],\n",
    "                PI_NAMES: input_row[PI_NAMES],\n",
    "                NB_PI_IDS: len(pi_ids_list),\n",
    "                NB_PI_NAMES: len(pi_names_list),\n",
    "                CONTACT_PI_ID: contact_pi_id, \n",
    "                CONTACT_PI_NAME: contact_pi_name, \n",
    "                CONTACT_PI_ID_STATUS: pi_id_status, \n",
    "                CONTACT_PI_NAME_STATUS: pi_name_status,\n",
    "                CONTACT_PI_FIRST_NAME: contact_pi_first_name,\n",
    "                CONTACT_PI_GENDER: gender_dict.get(contact_pi_first_name),\n",
    "                PROGRAM_OFFICER_NAME: input_row[PROGRAM_OFFICER_NAME],\n",
    "                PROJECT_START: input_row[PROJECT_START],\n",
    "                PROJECT_END: input_row[PROJECT_END],\n",
    "                PROJECT_TERMS: input_row[PROJECT_TERMS],\n",
    "                PROJECT_TITLE: input_row[PROJECT_TITLE],\n",
    "                SERIAL_NUMBER: input_row[SERIAL_NUMBER],\n",
    "                STUDY_SECTION: input_row[STUDY_SECTION],\n",
    "                STUDY_SECTION_NAME: input_row[STUDY_SECTION_NAME],\n",
    "                SUBPROJECT_ID: input_row[SUBPROJECT_ID],\n",
    "                SUFFIX: input_row[SUFFIX],\n",
    "                SUPPORT_YEAR: input_row[SUPPORT_YEAR],\n",
    "                DIRECT_COST_AMT: input_row[DIRECT_COST_AMT],\n",
    "                INDIRECT_COST_AMT: input_row[INDIRECT_COST_AMT],\n",
    "                TOTAL_COST: input_row[TOTAL_COST],\n",
    "                TOTAL_COST_SUB_PROJECT: input_row[TOTAL_COST_SUB_PROJECT]\n",
    "            }\n",
    "            writer.writerow(dict_row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Design and build a Microsoft SQL Server database"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Context and table schema"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Database design is here: https://dbdiagram.io/d/61fd59c585022f4ee53e2950\n",
    "* Database type: Microsoft SQL Server\n",
    "* To be hosted at: Observatoire des sciences et technologies (OST) at UQÀM\n",
    "* Purpose: usage by the Canada Research Chair on the Transformations of Scholarly Communication team members"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Field max length"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check longest value in a cell to make sure import in SQL doesn't crash."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_longest_item_in_tsv_column(filepath, column):\n",
    "    '''\n",
    "    Returns the longest line in a given file.\n",
    "    '''\n",
    "\n",
    "    with open(filepath, 'r', encoding=OUTPUT_ENCODING, newline=NEWLINE) as input_file:\n",
    "        reader = csv.DictReader(input_file, delimiter=DELIMITER)\n",
    "        \n",
    "        longest_item = max((len(row[column]) for row in reader))\n",
    "        \n",
    "        return longest_item        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "APPLICATION_ID: \n",
      "8\n",
      "----------------\n",
      "ACTIVITY: \n",
      "3\n",
      "----------------\n",
      "ADMINISTERING_IC: \n",
      "2\n",
      "----------------\n",
      "APPLICATION_TYPE: \n",
      "1\n",
      "----------------\n",
      "APPLICATION_TYPE_NAME: \n",
      "96\n",
      "----------------\n",
      "ARRA_FUNDED: \n",
      "1\n",
      "----------------\n",
      "AWARD_NOTICE_DATE: \n",
      "19\n",
      "----------------\n",
      "BUDGET_START: \n",
      "10\n",
      "----------------\n",
      "BUDGET_END: \n",
      "10\n",
      "----------------\n",
      "CFDA_CODE: \n",
      "23\n",
      "----------------\n",
      "CORE_PROJECT_NUM: \n",
      "32\n",
      "----------------\n",
      "ED_INST_TYPE: \n",
      "70\n",
      "----------------\n",
      "FOA_NUMBER: \n",
      "14\n",
      "----------------\n",
      "FULL_PROJECT_NUM: \n",
      "37\n",
      "----------------\n",
      "FUNDING_ICS: \n",
      "295\n",
      "----------------\n",
      "FUNDING_MECHANISM: \n",
      "23\n",
      "----------------\n",
      "FY: \n",
      "4\n",
      "----------------\n",
      "IC_NAME: \n",
      "79\n",
      "----------------\n",
      "NIH_SPENDING_CATS: \n",
      "2232\n",
      "----------------\n",
      "ORG_CITY: \n",
      "27\n",
      "----------------\n",
      "ORG_COUNTRY: \n",
      "14\n",
      "----------------\n",
      "ORG_DEPT: \n",
      "30\n",
      "----------------\n",
      "ORG_DISTRICT: \n",
      "2\n",
      "----------------\n",
      "ORG_DUNS: \n",
      "75\n",
      "----------------\n",
      "ORG_FIPS: \n",
      "2\n",
      "----------------\n",
      "ORG_IPF_CODE: \n",
      "8\n",
      "----------------\n",
      "ORG_NAME: \n",
      "92\n",
      "----------------\n",
      "ORG_STATE: \n",
      "2\n",
      "----------------\n",
      "ORG_ZIPCODE: \n",
      "10\n",
      "----------------\n",
      "PHR: \n",
      "32003\n",
      "----------------\n",
      "PI_IDS: \n",
      "262\n",
      "----------------\n",
      "PI_NAMES: \n",
      "533\n",
      "----------------\n",
      "NB_PI_IDS: \n",
      "2\n",
      "----------------\n",
      "NB_PI_NAMES: \n",
      "2\n",
      "----------------\n",
      "CONTACT_PI_ID: \n",
      "18\n",
      "----------------\n",
      "CONTACT_PI_NAME: \n",
      "54\n",
      "----------------\n",
      "CONTACT_PI_ID_STATUS: \n",
      "43\n",
      "----------------\n",
      "CONTACT_PI_NAME_STATUS: \n",
      "52\n",
      "----------------\n",
      "CONTACT_PI_FIRST_NAME: \n",
      "33\n",
      "----------------\n",
      "CONTACT_PI_GENDER: \n",
      "1\n",
      "----------------\n",
      "PROGRAM_OFFICER_NAME: \n",
      "39\n",
      "----------------\n",
      "PROJECT_START: \n",
      "10\n",
      "----------------\n",
      "PROJECT_END: \n",
      "10\n",
      "----------------\n",
      "PROJECT_TERMS: \n",
      "32767\n",
      "----------------\n",
      "PROJECT_TITLE: \n",
      "200\n",
      "----------------\n",
      "SERIAL_NUMBER: \n",
      "6\n",
      "----------------\n",
      "STUDY_SECTION: \n",
      "4\n",
      "----------------\n",
      "STUDY_SECTION_NAME: \n",
      "116\n",
      "----------------\n",
      "SUBPROJECT_ID: \n",
      "4\n",
      "----------------\n",
      "SUFFIX: \n",
      "6\n",
      "----------------\n",
      "SUPPORT_YEAR: \n",
      "2\n",
      "----------------\n",
      "DIRECT_COST_AMT: \n",
      "9\n",
      "----------------\n",
      "INDIRECT_COST_AMT: \n",
      "8\n",
      "----------------\n",
      "TOTAL_COST: \n",
      "9\n",
      "----------------\n",
      "TOTAL_COST_SUB_PROJECT: \n",
      "8\n",
      "----------------\n"
     ]
    }
   ],
   "source": [
    "# Pretty inefficient and long to run - only run once a year when adding new data\n",
    "\n",
    "# fieldnames=[\n",
    "#         APPLICATION_ID,\n",
    "#         ACTIVITY,\n",
    "#         ADMINISTERING_IC,\n",
    "#         APPLICATION_TYPE,\n",
    "#         APPLICATION_TYPE_NAME,\n",
    "#         ARRA_FUNDED,\n",
    "#         AWARD_NOTICE_DATE,\n",
    "#         BUDGET_START,\n",
    "#         BUDGET_END,\n",
    "#         CFDA_CODE,\n",
    "#         CORE_PROJECT_NUM,\n",
    "#         ED_INST_TYPE,\n",
    "#         FOA_NUMBER,\n",
    "#         FULL_PROJECT_NUM,\n",
    "#         FUNDING_ICS,\n",
    "#         FUNDING_MECHANISM,\n",
    "#         FY,\n",
    "#         IC_NAME,\n",
    "#         NIH_SPENDING_CATS,\n",
    "#         ORG_CITY,\n",
    "#         ORG_COUNTRY,\n",
    "#         ORG_DEPT,\n",
    "#         ORG_DISTRICT,\n",
    "#         ORG_DUNS,\n",
    "#         ORG_FIPS,\n",
    "#         ORG_IPF_CODE,\n",
    "#         ORG_NAME,\n",
    "#         ORG_STATE,\n",
    "#         ORG_ZIPCODE,\n",
    "#         PHR,\n",
    "#         PI_IDS,\n",
    "#         PI_NAMES,\n",
    "#         NB_PI_IDS,\n",
    "#         NB_PI_NAMES,\n",
    "#         CONTACT_PI_ID, \n",
    "#         CONTACT_PI_NAME, \n",
    "#         CONTACT_PI_ID_STATUS, \n",
    "#         CONTACT_PI_NAME_STATUS,\n",
    "#         CONTACT_PI_FIRST_NAME,\n",
    "#         CONTACT_PI_GENDER,\n",
    "#         PROGRAM_OFFICER_NAME,\n",
    "#         PROJECT_START,\n",
    "#         PROJECT_END,\n",
    "#         PROJECT_TERMS,\n",
    "#         PROJECT_TITLE,\n",
    "#         SERIAL_NUMBER,\n",
    "#         STUDY_SECTION,\n",
    "#         STUDY_SECTION_NAME,\n",
    "#         SUBPROJECT_ID,\n",
    "#         SUFFIX,\n",
    "#         SUPPORT_YEAR,\n",
    "#         DIRECT_COST_AMT,\n",
    "#         INDIRECT_COST_AMT,\n",
    "#         TOTAL_COST,\n",
    "#         TOTAL_COST_SUB_PROJECT\n",
    "#     ]\n",
    "\n",
    "# for fieldname in fieldnames:\n",
    "#     print(fieldname + ': ')\n",
    "#     print(get_longest_item_in_tsv_column(ENHANCED_FILE, fieldname))\n",
    "#     print('----------------')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Fieldname | Longest line lenght |\n",
    "| :--- | :--- |\n",
    "| APPLICATION_ID | 8 |\n",
    "| ACTIVITY | 3 |\n",
    "| ADMINISTERING_IC | 2 |\n",
    "| APPLICATION_TYPE | 1 |\n",
    "| APPLICATION_TYPE_NAME | 96 |\n",
    "| ARRA_FUNDED | 1 |\n",
    "| AWARD_NOTICE_DATE | 19 |\n",
    "| BUDGET_START | 10 |\n",
    "| BUDGET_END | 10 |\n",
    "| CFDA_CODE | 23 |\n",
    "| CORE_PROJECT_NUM | 32 |\n",
    "| ED_INST_TYPE | 70 |\n",
    "| FOA_NUMBER | 14 |\n",
    "| FULL_PROJECT_NUM | 37 |\n",
    "| FUNDING_ICS | 295 |\n",
    "| FUNDING_MECHANISM | 23 |\n",
    "| FY | 4 |\n",
    "| IC_NAME | 79 |\n",
    "| NIH_SPENDING_CATS | 2232 |\n",
    "| ORG_CITY | 27 |\n",
    "| ORG_COUNTRY | 14 |\n",
    "| ORG_DEPT | 30 |\n",
    "| ORG_DISTRICT | 2 |\n",
    "| ORG_DUNS | 75 |\n",
    "| ORG_FIPS | 2 |\n",
    "| ORG_IPF_CODE | 8 |\n",
    "| ORG_NAME | 92 |\n",
    "| ORG_STATE | 2 |\n",
    "| ORG_ZIPCODE | 10 |\n",
    "| PHR | 32003 |\n",
    "| PI_IDS | 262 |\n",
    "| PI_NAMES | 533 |\n",
    "| NB_PI_IDS | 2 |\n",
    "| NB_PI_NAMES | 2 |\n",
    "| CONTACT_PI_ID | 18 |\n",
    "| CONTACT_PI_NAME | 54 |\n",
    "| CONTACT_PI_ID_STATUS | 43 |\n",
    "| CONTACT_PI_NAME_STATUS | 52 |\n",
    "| CONTACT_PI_FIRST_NAME | 33 |\n",
    "| CONTACT_PI_GENDER | 1 |\n",
    "| PROGRAM_OFFICER_NAME | 39 |\n",
    "| PROJECT_START | 10 |\n",
    "| PROJECT_END | 10 |\n",
    "| PROJECT_TERMS | 32767 |\n",
    "| PROJECT_TITLE | 200 |\n",
    "| SERIAL_NUMBER | 6 |\n",
    "| STUDY_SECTION | 4 |\n",
    "| STUDY_SECTION_NAME | 116 |\n",
    "| SUBPROJECT_ID | 4 |\n",
    "| SUFFIX | 6 |\n",
    "| SUPPORT_YEAR | 2 |\n",
    "| DIRECT_COST_AMT | 9 |\n",
    "| INDIRECT_COST_AMT | 8 |\n",
    "| TOTAL_COST | 9 |\n",
    "| TOTAL_COST_SUB_PROJECT | 8 |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create the tables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split enhanced output file into different tables according to database design"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def is_not_duplicated(row):\n",
    "    return row['APPLICATION_ID'] != '7916889' \n",
    "    # there was 1 duplicated application_id (supposed to be unique), so I removed both rows to prevent SQL import from crashing\n",
    "\n",
    "\n",
    "def filter_columns(\n",
    "    source_file, target_file, subset_headers, \n",
    "    default_row_filter=is_not_duplicated, row_filter=lambda row: True):\n",
    "    \n",
    "    subset_headers_set = set(subset_headers)\n",
    "    \n",
    "    with open(source_file, 'r', encoding=OUTPUT_ENCODING, newline=NEWLINE) as csv_file_descriptor:\n",
    "        reader = csv.DictReader(csv_file_descriptor, delimiter=DELIMITER)\n",
    "\n",
    "        with open(target_file, 'w', encoding=OUTPUT_ENCODING, newline=NEWLINE) as output_file:\n",
    "            writer = csv.DictWriter(output_file, fieldnames=subset_headers, delimiter=DELIMITER)\n",
    "            writer.writeheader()\n",
    "\n",
    "            for row in reader:\n",
    "                if default_row_filter(row) == False:\n",
    "                    continue\n",
    "                    \n",
    "                if row_filter(row) == False:\n",
    "                    continue\n",
    "                \n",
    "                subset_row = {}\n",
    "                for key, value in row.items():\n",
    "                    if key in subset_headers_set:\n",
    "                        subset_row[key] = value\n",
    "                writer.writerow(subset_row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First test for SQL import with only a few columns\n",
    "# In command line, go to the right folder and run `head -n 5 test.tsv > test_head.tsv` to output only the first 5 rows\n",
    "# Use `test_head.tsv` to try the import in SQL\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'test.tsv', [\n",
    "    APPLICATION_ID, # use as primary key \n",
    "    APPLICATION_TYPE, \n",
    "    PHR])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE PROJECTS\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'PROJECTS.tsv', [\n",
    "    APPLICATION_ID, # use as primary key\n",
    "    CORE_PROJECT_NUM, \n",
    "    ACTIVITY, \n",
    "    ADMINISTERING_IC, \n",
    "    APPLICATION_TYPE, \n",
    "    ARRA_FUNDED, \n",
    "    AWARD_NOTICE_DATE, \n",
    "    CFDA_CODE, \n",
    "    FOA_NUMBER, \n",
    "    FUNDING_ICS, \n",
    "    FUNDING_MECHANISM, \n",
    "    NIH_SPENDING_CATS, \n",
    "    ORG_IPF_CODE, \n",
    "    PHR, \n",
    "    PROGRAM_OFFICER_NAME, \n",
    "    PROJECT_START, \n",
    "    PROJECT_END, \n",
    "    PROJECT_TERMS, \n",
    "    PROJECT_TITLE,  \n",
    "    STUDY_SECTION])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE SUBPROJECTS\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'SUBPROJECTS.tsv', [\n",
    "    CORE_PROJECT_NUM,\n",
    "    SUBPROJECT_ID, \n",
    "    PROJECT_TITLE, \n",
    "    TOTAL_COST_SUB_PROJECT], \n",
    "                 row_filter=lambda row: row[SUBPROJECT_ID] != \"\" and row[SUBPROJECT_ID] is not None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE APPLICATION_TYPE\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'APPLICATION_TYPE.tsv', [\n",
    "    APPLICATION_TYPE, \n",
    "    APPLICATION_TYPE_NAME])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE PRINCIPAL_INVESTIGATORS\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'PRINCIPAL_INVESTIGATORS.tsv', [\n",
    "    APPLICATION_ID, \n",
    "    PI_IDS, \n",
    "    PI_NAMES, \n",
    "    NB_PI_IDS, \n",
    "    NB_PI_NAMES, \n",
    "    CONTACT_PI_ID, \n",
    "    CONTACT_PI_NAME, \n",
    "    CONTACT_PI_FIRST_NAME, \n",
    "    CONTACT_PI_GENDER])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE FUNDING_PER_FISCAL_YEAR\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'FUNDING_PER_FISCAL_YEAR.tsv', [\n",
    "    APPLICATION_ID, \n",
    "    FULL_PROJECT_NUM, \n",
    "    FY, \n",
    "    BUDGET_START, \n",
    "    BUDGET_END, \n",
    "    SUPPORT_YEAR, \n",
    "    DIRECT_COST_AMT, \n",
    "    INDIRECT_COST_AMT, \n",
    "    TOTAL_COST])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE GRANTEE_ORGANIZATION\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'GRANTEE_ORGANIZATION.tsv', [\n",
    "    ORG_IPF_CODE, \n",
    "    ORG_DUNS, \n",
    "    ORG_NAME, \n",
    "    ORG_DEPT, \n",
    "    ORG_FIPS, \n",
    "    ORG_COUNTRY, \n",
    "    ORG_STATE, \n",
    "    ORG_DISTRICT, \n",
    "    ORG_CITY, \n",
    "    ORG_ZIPCODE, \n",
    "    ED_INST_TYPE])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE INSTITUTE_OR_CENTER\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'INSTITUTE_OR_CENTER.tsv', [\n",
    "    ADMINISTERING_IC, \n",
    "    IC_NAME])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE STUDY_SECTION\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'STUDY_SECTION.tsv', [\n",
    "    STUDY_SECTION, \n",
    "    STUDY_SECTION_NAME])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE SUPPLEMENT - for useless fields that we still want to keep\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'SUPPLEMENT.tsv', [\n",
    "    APPLICATION_ID,\n",
    "    SERIAL_NUMBER,\n",
    "    SUFFIX])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TABLE ADMIN - for more information on the output of the gender identification\n",
    "filter_columns(ENHANCED_FILE, TABLE_DIR + 'ADMIN.tsv', [\n",
    "    APPLICATION_ID,\n",
    "    CONTACT_PI_ID_STATUS, \n",
    "    CONTACT_PI_NAME_STATUS])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## QA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APPLICATION_ID</th>\n",
       "      <th>PI_IDS</th>\n",
       "      <th>PI_NAMES</th>\n",
       "      <th>NB_PI_IDS</th>\n",
       "      <th>NB_PI_NAMES</th>\n",
       "      <th>CONTACT_PI_ID</th>\n",
       "      <th>CONTACT_PI_NAME</th>\n",
       "      <th>CONTACT_PI_FIRST_NAME</th>\n",
       "      <th>CONTACT_PI_GENDER</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10229388</td>\n",
       "      <td>1902986;</td>\n",
       "      <td>PERLMAN, STANLEY ;</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1902986</td>\n",
       "      <td>PERLMAN, STANLEY</td>\n",
       "      <td>STANLEY</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10229500</td>\n",
       "      <td>1869110;</td>\n",
       "      <td>SEMPOWSKI, GREGORY D;</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1869110</td>\n",
       "      <td>SEMPOWSKI, GREGORY D</td>\n",
       "      <td>GREGORY</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10234175</td>\n",
       "      <td>11404564;</td>\n",
       "      <td>NEUNUEBEL, MARIA RAMONA;</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11404564</td>\n",
       "      <td>NEUNUEBEL, MARIA RAMONA</td>\n",
       "      <td>MARIA RAMONA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10107767</td>\n",
       "      <td>11433979 (contact); 12250285;</td>\n",
       "      <td>LAVINE, KORY J. (contact); STURGEON, CHRISTOPH...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11433979 (contact)</td>\n",
       "      <td>LAVINE, KORY J. (contact)</td>\n",
       "      <td>KORY</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10144347</td>\n",
       "      <td>1861963;</td>\n",
       "      <td>GANGULI, MARY ;</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1861963</td>\n",
       "      <td>GANGULI, MARY</td>\n",
       "      <td>MARY</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   APPLICATION_ID                          PI_IDS  \\\n",
       "0        10229388                       1902986;    \n",
       "1        10229500                       1869110;    \n",
       "2        10234175                      11404564;    \n",
       "3        10107767  11433979 (contact); 12250285;    \n",
       "4        10144347                       1861963;    \n",
       "\n",
       "                                            PI_NAMES  NB_PI_IDS  NB_PI_NAMES  \\\n",
       "0                                 PERLMAN, STANLEY ;          1            1   \n",
       "1                              SEMPOWSKI, GREGORY D;          1            1   \n",
       "2                           NEUNUEBEL, MARIA RAMONA;          1            1   \n",
       "3  LAVINE, KORY J. (contact); STURGEON, CHRISTOPH...          2            2   \n",
       "4                                    GANGULI, MARY ;          1            1   \n",
       "\n",
       "        CONTACT_PI_ID            CONTACT_PI_NAME CONTACT_PI_FIRST_NAME  \\\n",
       "0             1902986           PERLMAN, STANLEY               STANLEY   \n",
       "1             1869110       SEMPOWSKI, GREGORY D               GREGORY   \n",
       "2            11404564    NEUNUEBEL, MARIA RAMONA          MARIA RAMONA   \n",
       "3  11433979 (contact)  LAVINE, KORY J. (contact)                  KORY   \n",
       "4             1861963              GANGULI, MARY                  MARY   \n",
       "\n",
       "  CONTACT_PI_GENDER  \n",
       "0                 M  \n",
       "1                 M  \n",
       "2               NaN  \n",
       "3                 M  \n",
       "4                 F  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Take a look at the different tables to make sure they contain the right data\n",
    "test_df = pd.read_csv(TABLE_DIR + 'PRINCIPAL_INVESTIGATORS.tsv', \n",
    "                      delimiter=DELIMITER, encoding=OUTPUT_ENCODING, low_memory=False)\n",
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    2621672\n",
       "dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.duplicated(subset=['APPLICATION_ID']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# test_df[test_df.duplicated(['APPLICATION_ID'], keep=False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import each table into Microsoft SQL Management Studio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, you should sync with OST and if needed ask for help with the import.\n",
    "\n",
    "Good luck!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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