{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Example Data Research Workflow using Python.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOVd1j0ezmG21fWp22G6fRT",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/cyrus723/my-first-binder/blob/main/Example_Data_Research_Workflow_using_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zV1jX0Je8Hg3"
      },
      "source": [
        "#Example Data Research Workflow using Python\n",
        "## Source: WRDS https://wrds-www.wharton.upenn.edu/"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V9vLXLxQAvPF",
        "outputId": "2712522c-5166-43fd-aff9-9bcec0c9b4b6"
      },
      "source": [
        "!pip install wrds"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting wrds\n",
            "  Downloading wrds-3.1.1-py3-none-any.whl (12 kB)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from wrds) (1.21.6)\n",
            "Collecting psycopg2-binary\n",
            "  Downloading psycopg2_binary-2.9.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0 MB 4.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from wrds) (1.3.5)\n",
            "Requirement already satisfied: sqlalchemy in /usr/local/lib/python3.7/dist-packages (from wrds) (1.4.36)\n",
            "Collecting mock\n",
            "  Downloading mock-4.0.3-py3-none-any.whl (28 kB)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->wrds) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->wrds) (2022.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->wrds) (1.15.0)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.7/dist-packages (from sqlalchemy->wrds) (1.1.2)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from sqlalchemy->wrds) (4.11.3)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->sqlalchemy->wrds) (4.2.0)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->sqlalchemy->wrds) (3.8.0)\n",
            "Installing collected packages: psycopg2-binary, mock, wrds\n",
            "Successfully installed mock-4.0.3 psycopg2-binary-2.9.3 wrds-3.1.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ofJt5guG8HcX"
      },
      "source": [
        "The following series of stand-alone queries represents a basic example Python workflow using WRDS data. The commands in this workflow could be run interactively or submitted via a batch job using Python in the WRDS Cloud, or run locally from your computer using a Jupyter notebook. For this example, we'll use the CRSP Daily Stock File (```crsp.dsf```) data library\n",
        "\n",
        "In real-world Python programming, you would probably use the results of these queries to perform additional statistical analysis in your program. This document is meant as an introductory walkthrough.\n",
        "\n",
        "First, as with every Python program that intends to connect to WRDS, we must import the wrds module and make our connection:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "STKRvgnP8jg4"
      },
      "source": [
        "We must also have set up our pgpass file as described earlier in the documentation.\n",
        "\n",
        "Note: Class accounts and IPAuth / Daypass accounts are not permitted to access WRDS in this manner and will receive an error if trying this connection. You must have your own, dedicated WRDS account in order to access WRDS from MATLAB.\n",
        "\n",
        "Let's get started. The initial queries (metadata queries) have dedicated wrds module methods to give you the results you're looking for. Later queries (data queries) will use ```raw_sql()``` exclusively.\n",
        "\n",
        "1. To determine the libraries available at WRDS:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6iNswu3f8gqe"
      },
      "source": [
        "import wrds\n",
        "db = wrds.Connection()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nz8kNoTb8gs_",
        "outputId": "8a7af630-13e4-4ceb-f1eb-b415a11eabc7"
      },
      "source": [
        "db.list_libraries()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['compbd',\n",
              " 'compgd',\n",
              " 'compnad',\n",
              " 'compsegd',\n",
              " 'crspa',\n",
              " 'evts',\n",
              " 'issm',\n",
              " 'nastraq',\n",
              " 'wrds_lib_internal',\n",
              " 'tass',\n",
              " 'aha',\n",
              " 'estimize',\n",
              " 'toyo',\n",
              " 'levin',\n",
              " 'ahasamp',\n",
              " 'crspm',\n",
              " 'tresgsmp',\n",
              " 'trsdcgs',\n",
              " 'columnar',\n",
              " 'trws',\n",
              " 'lspd',\n",
              " 'twoiq',\n",
              " 'wcai',\n",
              " 'csmar',\n",
              " 'wind',\n",
              " 'wqa',\n",
              " 'tresg',\n",
              " 'markit',\n",
              " 'msrb_all',\n",
              " 'risk',\n",
              " 'custom_jl',\n",
              " 'centris',\n",
              " 'block_all',\n",
              " 'zacks',\n",
              " 'boardex_trial',\n",
              " 'audit',\n",
              " 'comp_na_monthly_all',\n",
              " 'emdb',\n",
              " 'auditsmp',\n",
              " 'boardsmp',\n",
              " 'calcbnch',\n",
              " 'comp_segments_hist',\n",
              " 'wrdsrpts_rep_usage',\n",
              " 'public_all',\n",
              " 'pwt_all',\n",
              " 'msfanly',\n",
              " 'etfg',\n",
              " 'cboe_all',\n",
              " 'wrdsapps_backtest_plus',\n",
              " 'pacap',\n",
              " 'ciqsamp_transcripts',\n",
              " 'ciq',\n",
              " 'tr_ds',\n",
              " 'ppublica',\n",
              " 'preqin',\n",
              " 'crsp_a_stock',\n",
              " 'fisdsamp',\n",
              " 'etfg_samp',\n",
              " 'windsmp',\n",
              " 'rent',\n",
              " 'wrdsapps_evtstudy_int_ginsight',\n",
              " 'compmcur',\n",
              " 'secsamp_all',\n",
              " 'rpna',\n",
              " 'ibes',\n",
              " 'rpa',\n",
              " 'wrdssec_midas',\n",
              " 'sdcsamp',\n",
              " 'cisdmsmp',\n",
              " 'snl',\n",
              " 'sprat',\n",
              " 'ciqsamp',\n",
              " 'cboe',\n",
              " 'sustain',\n",
              " 'trucost',\n",
              " 'sdc',\n",
              " 'fjc_linking',\n",
              " 'otc_endofday',\n",
              " 'optionm',\n",
              " 'compa',\n",
              " 'bank',\n",
              " 'blab',\n",
              " 'block',\n",
              " 'compb',\n",
              " 'compg',\n",
              " 'taqmsec',\n",
              " 'comp_execucomp',\n",
              " 'trsamp_ds_eq',\n",
              " 'contrib_ceo_turnover',\n",
              " 'cisdm',\n",
              " 'clrvt',\n",
              " 'clrvtsmp',\n",
              " 'compsamp',\n",
              " 'trdstrm',\n",
              " 'compm',\n",
              " 'compseg',\n",
              " 'comph',\n",
              " 'compsnap',\n",
              " 'comscore',\n",
              " 'sustainalyticssamp_all',\n",
              " 'ff_all',\n",
              " 'pitchbk',\n",
              " 'crspsamp',\n",
              " 'dmef',\n",
              " 'eursamp',\n",
              " 'contrib_kpss',\n",
              " 'auditsmp_all',\n",
              " 'ciqsamp_pplintel',\n",
              " 'execcomp',\n",
              " 'taqmsamp_all',\n",
              " 'crspq',\n",
              " 'boardex',\n",
              " 'ftse',\n",
              " 'cusipm',\n",
              " 'eureka',\n",
              " 'eventus',\n",
              " 'ftsesamp',\n",
              " 'ginsight',\n",
              " 'ktsamp',\n",
              " 'factset',\n",
              " 'ifgrsamp',\n",
              " 'imssamp',\n",
              " 'gmi',\n",
              " 'fisd',\n",
              " 'ff',\n",
              " 'fssamp',\n",
              " 'govpxsmp',\n",
              " 'hbsamp',\n",
              " 'hbase',\n",
              " 'ibeskpi',\n",
              " 'ifgr',\n",
              " 'ibescorp',\n",
              " 'mrktsamp_msf',\n",
              " 'iri',\n",
              " 'kld',\n",
              " 'govpx',\n",
              " 'hfr',\n",
              " 'lspdsamp',\n",
              " 'ims',\n",
              " 'ktmine',\n",
              " 'taq',\n",
              " 'aha_sample',\n",
              " 'calcbench_trial',\n",
              " 'ppubsamp_d4d',\n",
              " 'iss',\n",
              " 'ciqsamp_common',\n",
              " 'comp_na_daily_all',\n",
              " 'compdcur',\n",
              " 'otc',\n",
              " 'mrktsamp',\n",
              " 'contrib_general',\n",
              " 'preqsamp_all',\n",
              " 'twoiq_samp',\n",
              " 'msrb',\n",
              " 'msrbsamp',\n",
              " 'mrktsamp_cdx',\n",
              " 'phlx_all',\n",
              " 'zacksamp_all',\n",
              " 'fjc_litigation',\n",
              " 'mfl',\n",
              " 'etfgsamp',\n",
              " 'sustsamp',\n",
              " 'phlx',\n",
              " 'ppubsamp',\n",
              " 'preqsamp',\n",
              " 'wrdsapps_evtstudy_lr',\n",
              " 'ciqsamp_keydev',\n",
              " 'crsp_a_ccm',\n",
              " 'crsp',\n",
              " 'tfn',\n",
              " 'wappsamp',\n",
              " 'revere',\n",
              " 'toyosamp',\n",
              " 'zacksamp',\n",
              " 'wrdsrpts',\n",
              " 'eurekahedge_sample',\n",
              " 'ims_obp_trial',\n",
              " 'comp_na_annual_all',\n",
              " 'compsamp_snapshot',\n",
              " 'rq_all',\n",
              " 'comp_bank_daily',\n",
              " 'infogroupsamp_business',\n",
              " 'comp_segments_hist_daily',\n",
              " 'infogroupsamp_residential',\n",
              " 'ktmine_patents_samp',\n",
              " 'djones_all',\n",
              " 'doe_all',\n",
              " 'factsamp_all',\n",
              " 'wrdsapps_eushort',\n",
              " 'wrdsapps_subsidiary',\n",
              " 'wrdsappssamp_all',\n",
              " 'wrdsapps_link_datastream_wscope',\n",
              " 'wrdsapps_patents',\n",
              " 'wrdsapps_link_comp_eushort',\n",
              " 'dmef_all',\n",
              " 'macrofin_comm_trade',\n",
              " 'mrktsamp_cds',\n",
              " 'pitchsmp',\n",
              " 'totalq_all',\n",
              " 'toyosamp_all',\n",
              " 'trsamp_dscom',\n",
              " 'trsamp_dsecon',\n",
              " 'reprisk',\n",
              " 'rpnasamp',\n",
              " 'comp',\n",
              " 'audit_corp_legal',\n",
              " 'trcstsmp',\n",
              " 'trsamp_dsfut',\n",
              " 'wrdsapps_backtest_basic',\n",
              " 'wrdsapps_link_supplychain',\n",
              " 'wrdsapps',\n",
              " 'wrdssec',\n",
              " 'audit_common',\n",
              " 'contrib_intangible_value',\n",
              " 'ciqsamp_capstrct',\n",
              " 'contrib_char_returns',\n",
              " 'tr_dealscan',\n",
              " 'crsp_q_indexhist',\n",
              " 'bvd',\n",
              " 'hfrsamp_hfrdb',\n",
              " 'factsamp_revere',\n",
              " 'frb_all',\n",
              " 'trown',\n",
              " 'hbase_sample',\n",
              " 'secsamp',\n",
              " 'lvnsamp_all',\n",
              " 'optionmsamp_europe',\n",
              " 'optionmsamp_us',\n",
              " 'reprisk_sample',\n",
              " 'risksamp_all',\n",
              " 'snlsamp_fig',\n",
              " 'ravenpack_trial',\n",
              " 'wrdsapps_finratio_ccm',\n",
              " 'trace_standard',\n",
              " 'trace_enhanced',\n",
              " 'bvdsamp',\n",
              " 'contrib',\n",
              " 'wrdsapps_link_crsp_bond',\n",
              " 'djones',\n",
              " 'doe',\n",
              " 'frb',\n",
              " 'hfrsamp',\n",
              " 'lvnsamp',\n",
              " 'macrofin',\n",
              " 'midas',\n",
              " 'omtrial',\n",
              " 'public',\n",
              " 'pwt',\n",
              " 'repsamp',\n",
              " 'risksamp',\n",
              " 'snapsamp',\n",
              " 'snlsamp',\n",
              " 'taqsamp',\n",
              " 'totalq',\n",
              " 'trdssamp',\n",
              " 'fjc',\n",
              " 'trace',\n",
              " 'wrdsapps_link_crsp_factset',\n",
              " 'wrdsapps_link_crsp_taq',\n",
              " 'comp_bank',\n",
              " 'trsamp',\n",
              " 'twoiqsmp',\n",
              " 'audit_audit_comp',\n",
              " 'wrdsapps_finratio',\n",
              " 'dealscan',\n",
              " 'crsp_a_indexes',\n",
              " 'msfinst',\n",
              " 'taqmsamp']"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iOMIZY4b8tgQ"
      },
      "source": [
        "2. Let's work with the CRSP library. From the above results, that's crsp. What datasets are available within this library?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MWp4cHDq8whY",
        "outputId": "ccc0a750-c7ae-4723-dbe6-685fe287c5bf"
      },
      "source": [
        "db.list_tables('crsp')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['acti',\n",
              " 'asia',\n",
              " 'asib',\n",
              " 'asic',\n",
              " 'asio',\n",
              " 'asix',\n",
              " 'bmdebt',\n",
              " 'bmheader',\n",
              " 'bmpaymts',\n",
              " 'bmquotes',\n",
              " 'bmyield',\n",
              " 'bndprt06',\n",
              " 'bndprt12',\n",
              " 'bxcalind',\n",
              " 'bxdlyind',\n",
              " 'bxmthind',\n",
              " 'bxquotes',\n",
              " 'bxyield',\n",
              " 'cap',\n",
              " 'ccm_lookup',\n",
              " 'ccm_qvards',\n",
              " 'ccmxpf_linktable',\n",
              " 'ccmxpf_lnkhist',\n",
              " 'ccmxpf_lnkrng',\n",
              " 'ccmxpf_lnkused',\n",
              " 'comphead',\n",
              " 'comphist',\n",
              " 'compmaster',\n",
              " 'contact_info',\n",
              " 'crsp_cik_map',\n",
              " 'crsp_daily_data',\n",
              " 'crsp_header',\n",
              " 'crsp_monthly_data',\n",
              " 'crsp_names',\n",
              " 'crsp_portno_map',\n",
              " 'crsp_ziman_daily_index',\n",
              " 'crsp_ziman_monthly_index',\n",
              " 'cs20yr',\n",
              " 'cs5yr',\n",
              " 'cs90d',\n",
              " 'cst_hist',\n",
              " 'daily_nav',\n",
              " 'daily_nav_ret',\n",
              " 'daily_returns',\n",
              " 'dividends',\n",
              " 'dport1',\n",
              " 'dport2',\n",
              " 'dport3',\n",
              " 'dport4',\n",
              " 'dport5',\n",
              " 'dport6',\n",
              " 'dport7',\n",
              " 'dport8',\n",
              " 'dport9',\n",
              " 'dsbc',\n",
              " 'dsbo',\n",
              " 'dse',\n",
              " 'dse62',\n",
              " 'dse62delist',\n",
              " 'dse62dist',\n",
              " 'dse62exchdates',\n",
              " 'dse62names',\n",
              " 'dse62nasdin',\n",
              " 'dse62shares',\n",
              " 'dseall',\n",
              " 'dseall62',\n",
              " 'dsedelist',\n",
              " 'dsedist',\n",
              " 'dseexchdates',\n",
              " 'dsenames',\n",
              " 'dsenasdin',\n",
              " 'dseshares',\n",
              " 'dsf',\n",
              " 'dsf62',\n",
              " 'dsfhdr',\n",
              " 'dsfhdr62',\n",
              " 'dsi',\n",
              " 'dsi62',\n",
              " 'dsia',\n",
              " 'dsib',\n",
              " 'dsic',\n",
              " 'dsio',\n",
              " 'dsir',\n",
              " 'dsix',\n",
              " 'dsiy',\n",
              " 'dsp500',\n",
              " 'dsp500list',\n",
              " 'dsp500p',\n",
              " 'dssc',\n",
              " 'dsso',\n",
              " 'eod_cap',\n",
              " 'eod_sector',\n",
              " 'eod_vg',\n",
              " 'erdport1',\n",
              " 'erdport2',\n",
              " 'erdport3',\n",
              " 'erdport4',\n",
              " 'erdport5',\n",
              " 'erdport6',\n",
              " 'erdport7',\n",
              " 'erdport8',\n",
              " 'erdport9',\n",
              " 'ermport1',\n",
              " 'ermport2',\n",
              " 'ermport3',\n",
              " 'ermport4',\n",
              " 'ermport5',\n",
              " 'fbpri',\n",
              " 'fbyld',\n",
              " 'front_load',\n",
              " 'front_load_det',\n",
              " 'front_load_grp',\n",
              " 'fund_fees',\n",
              " 'fund_flows',\n",
              " 'fund_hdr',\n",
              " 'fund_hdr_hist',\n",
              " 'fund_names',\n",
              " 'fund_style',\n",
              " 'fund_summary',\n",
              " 'fund_summary2',\n",
              " 'fwdask06',\n",
              " 'fwdask12',\n",
              " 'fwdave06',\n",
              " 'fwdave12',\n",
              " 'fwdbid06',\n",
              " 'fwdbid12',\n",
              " 'hldask06',\n",
              " 'hldask12',\n",
              " 'hldave06',\n",
              " 'hldave12',\n",
              " 'hldbid06',\n",
              " 'hldbid12',\n",
              " 'holdings',\n",
              " 'holdings_co_info',\n",
              " 'index_descriptions',\n",
              " 'index_type_map',\n",
              " 'mbi',\n",
              " 'mbmdat',\n",
              " 'mbmhdr',\n",
              " 'mbx',\n",
              " 'mbxid',\n",
              " 'mcti',\n",
              " 'mfdbname',\n",
              " 'mhista',\n",
              " 'mhistn',\n",
              " 'mhistq',\n",
              " 'monthly_nav',\n",
              " 'monthly_returns',\n",
              " 'monthly_tna',\n",
              " 'monthly_tna_ret_nav',\n",
              " 'mport1',\n",
              " 'mport2',\n",
              " 'mport3',\n",
              " 'mport4',\n",
              " 'mport5',\n",
              " 'mse',\n",
              " 'mse62',\n",
              " 'mse62delist',\n",
              " 'mse62dist',\n",
              " 'mse62exchdates',\n",
              " 'mse62names',\n",
              " 'mse62nasdin',\n",
              " 'mse62shares',\n",
              " 'mseall',\n",
              " 'mseall62',\n",
              " 'msedelist',\n",
              " 'msedist',\n",
              " 'mseexchdates',\n",
              " 'msenames',\n",
              " 'msenasdin',\n",
              " 'mseshares',\n",
              " 'msf',\n",
              " 'msf62',\n",
              " 'msfhdr',\n",
              " 'msfhdr62',\n",
              " 'msi',\n",
              " 'msi62',\n",
              " 'msia',\n",
              " 'msib',\n",
              " 'msic',\n",
              " 'msio',\n",
              " 'msir',\n",
              " 'msix',\n",
              " 'msiy',\n",
              " 'msp500',\n",
              " 'msp500list',\n",
              " 'msp500p',\n",
              " 'portnomap',\n",
              " 'priask06',\n",
              " 'priask12',\n",
              " 'priave06',\n",
              " 'priave12',\n",
              " 'pribid06',\n",
              " 'pribid12',\n",
              " 'price_type',\n",
              " 'property_type',\n",
              " 'qcti',\n",
              " 'qsia',\n",
              " 'qsib',\n",
              " 'qsic',\n",
              " 'qsio',\n",
              " 'qsix',\n",
              " 'rear_load',\n",
              " 'rear_load_det',\n",
              " 'rear_load_grp',\n",
              " 'rebala',\n",
              " 'rebaln',\n",
              " 'rebalq',\n",
              " 'reit_type',\n",
              " 'riskfree',\n",
              " 's6z_agg_ann',\n",
              " 's6z_agg_mth',\n",
              " 's6z_agg_qtr',\n",
              " 's6z_del',\n",
              " 's6z_dind',\n",
              " 's6z_dis',\n",
              " 's6z_dp_dly',\n",
              " 's6z_ds_dly',\n",
              " 's6z_hdr',\n",
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          "metadata": {},
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    },
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      "source": [
        "\n",
        "3. The results show that many datasets are available within the crsp library. Let's work with the Daily Stock File (```dsf```) dataset, and take a look at the list of available data variables (column names) in that dataset:\n"
      ]
    },
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        "db.describe_table('crsp', 'dsf')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Approximately 101070400 rows in crsp.dsf.\n"
          ]
        },
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              "       name  nullable              type\n",
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          "text": [
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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          },
          "metadata": {},
          "execution_count": 6
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        "outputId": "d9b433c0-9675-475e-9bd3-1f427f639c07"
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      "source": [
        "db.describe_table('crsp', 'crsp_header')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Approximately 673 rows in crsp.crsp_header.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      name  nullable              type\n",
              "0   permno      True  DOUBLE_PRECISION\n",
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              "3    enddt      True              DATE\n",
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        "db.describe_table('crsp', 'comphead')"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Approximately 51232 rows in crsp.comphead.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        name  nullable              type\n",
              "0      gvkey      True        VARCHAR(6)\n",
              "1        cik      True       VARCHAR(10)\n",
              "2        ein      True       VARCHAR(10)\n",
              "3       conm      True      VARCHAR(256)\n",
              "4     costat      True        VARCHAR(1)\n",
              "5      dlrsn      True        VARCHAR(8)\n",
              "6     priusa      True        VARCHAR(8)\n",
              "7     prican      True        VARCHAR(8)\n",
              "8     prirow      True        VARCHAR(8)\n",
              "9    idbflag      True        VARCHAR(1)\n",
              "10       fic      True        VARCHAR(3)\n",
              "11       loc      True        VARCHAR(3)\n",
              "12    incorp      True        VARCHAR(8)\n",
              "13     state      True        VARCHAR(8)\n",
              "14    county      True      VARCHAR(100)\n",
              "15      city      True      VARCHAR(104)\n",
              "16     naics      True        VARCHAR(8)\n",
              "17     conml      True      VARCHAR(100)\n",
              "18    weburl      True       VARCHAR(60)\n",
              "19     phone      True       VARCHAR(18)\n",
              "20       fax      True       VARCHAR(18)\n",
              "21      add1      True       VARCHAR(65)\n",
              "22      add2      True       VARCHAR(65)\n",
              "23      add3      True       VARCHAR(65)\n",
              "24      add4      True       VARCHAR(65)\n",
              "25    addzip      True       VARCHAR(24)\n",
              "26   busdesc      True     VARCHAR(2000)\n",
              "27   ipodate      True              DATE\n",
              "28     dldte      True              DATE\n",
              "29      stko      True  DOUBLE_PRECISION\n",
              "30      fyrc      True  DOUBLE_PRECISION\n",
              "31       sic      True  DOUBLE_PRECISION\n",
              "32   gsector      True  DOUBLE_PRECISION\n",
              "33    ggroup      True  DOUBLE_PRECISION\n",
              "34      gind      True  DOUBLE_PRECISION\n",
              "35   gsubind      True  DOUBLE_PRECISION\n",
              "36  spcindcd      True  DOUBLE_PRECISION\n",
              "37  spcseccd      True  DOUBLE_PRECISION"
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              "      <th>6</th>\n",
              "      <td>priusa</td>\n",
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              "      <th>7</th>\n",
              "      <td>prican</td>\n",
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              "      <td>idbflag</td>\n",
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              "      <th>10</th>\n",
              "      <td>fic</td>\n",
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              "      <td>VARCHAR(3)</td>\n",
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              "      <th>11</th>\n",
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              "      <th>12</th>\n",
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              "      <td>True</td>\n",
              "      <td>VARCHAR(8)</td>\n",
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              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>state</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>county</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(100)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>city</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(104)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>naics</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(8)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>conml</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(100)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>weburl</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(60)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>phone</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(18)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>fax</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(18)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>add1</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(65)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>add2</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(65)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>add3</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(65)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>add4</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(65)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>addzip</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(24)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>busdesc</td>\n",
              "      <td>True</td>\n",
              "      <td>VARCHAR(2000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>ipodate</td>\n",
              "      <td>True</td>\n",
              "      <td>DATE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>dldte</td>\n",
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              "      <th>29</th>\n",
              "      <td>stko</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>fyrc</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>sic</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>gsector</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>ggroup</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>gind</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>gsubind</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>spcindcd</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>spcseccd</td>\n",
              "      <td>True</td>\n",
              "      <td>DOUBLE_PRECISION</td>\n",
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          "metadata": {},
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      "source": [
        "db.describe_table('crsp', 'crsp_names')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Approximately 2642 rows in crsp.crsp_names.\n"
          ]
        },
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    {
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        "id": "4CYSNMhFEWlu"
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      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
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          "height": 568
        },
        "id": "y1IBHijUFFtc",
        "outputId": "2e7a5179-0c52-4380-b991-d8740dbacb98"
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      "source": [
        "db.describe_table('crsp', 'stocknames')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Approximately 77779 rows in crsp.stocknames.\n"
          ]
        },
        {
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              "\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-17d03e49-2067-4ea9-bad9-65e0e83faf38');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ov1rrZeSEWoM"
      },
      "source": [
        "stocknames=db.get_table('crsp', 'stocknames')"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 679
        },
        "id": "4GwsJaiTqnOm",
        "outputId": "cbdeb6a7-d1f4-433f-e7f8-101b8f25095f"
      },
      "source": [
        "stocknames"
      ],
      "execution_count": 12,
      "outputs": [
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          "data": {
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              "        permno      namedt   nameenddt  shrcd  exchcd   siccd    ncusip  \\\n",
              "0      10000.0  1986-01-07  1987-06-11   10.0     3.0  3990.0  68391610   \n",
              "1      10001.0  1986-01-09  1993-11-21   11.0     3.0  4920.0  39040610   \n",
              "2      10001.0  1993-11-22  2008-02-04   11.0     3.0  4920.0  29274A10   \n",
              "3      10001.0  2008-02-05  2009-08-03   11.0     3.0  4920.0  29274A20   \n",
              "4      10001.0  2009-08-04  2009-12-17   11.0     3.0  4920.0  29269V10   \n",
              "...        ...         ...         ...    ...     ...     ...       ...   \n",
              "77774  93433.0  2013-04-24  2016-12-22   11.0     3.0  9999.0  92870X30   \n",
              "77775  93434.0  2010-06-14  2022-03-31   11.0     3.0  9999.0  78513510   \n",
              "77776  93435.0  2010-06-14  2012-05-18   11.0     3.0  6163.0  82936G20   \n",
              "77777  93436.0  2010-06-29  2017-02-01   11.0     3.0  9999.0  88160R10   \n",
              "77778  93436.0  2017-02-02  2022-03-31   11.0     3.0  9999.0  88160R10   \n",
              "\n",
              "      ticker                     comnam shrcls   permco  hexcd     cusip  \\\n",
              "0      OMFGA  OPTIMUM MANUFACTURING INC      A   7952.0    3.0  68391610   \n",
              "1       GFGC         GREAT FALLS GAS CO   None   7953.0    2.0  36720410   \n",
              "2       EWST            ENERGY WEST INC   None   7953.0    2.0  36720410   \n",
              "3       EWST            ENERGY WEST INC   None   7953.0    2.0  36720410   \n",
              "4       EGAS                 ENERGY INC   None   7953.0    2.0  36720410   \n",
              "...      ...                        ...    ...      ...    ...       ...   \n",
              "77774   VLTC               VOLTARI CORP   None  53451.0    3.0  92870X30   \n",
              "77775   SANW              S & W SEED CO   None  53427.0    3.0  78513510   \n",
              "77776   SCEI      SINO CLEAN ENERGY INC   None  53452.0    3.0  82936G20   \n",
              "77777   TSLA           TESLA MOTORS INC   None  53453.0    3.0  88160R10   \n",
              "77778   TSLA                  TESLA INC   None  53453.0    3.0  88160R10   \n",
              "\n",
              "          st_date    end_date  namedum  \n",
              "0      1986-01-07  1987-06-11      2.0  \n",
              "1      1986-01-09  2017-08-03      2.0  \n",
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              "3      1986-01-09  2017-08-03      2.0  \n",
              "4      1986-01-09  2017-08-03      2.0  \n",
              "...           ...         ...      ...  \n",
              "77774  2010-06-18  2016-12-22      2.0  \n",
              "77775  2010-06-14  2022-03-31      2.0  \n",
              "77776  2010-06-14  2012-05-18      2.0  \n",
              "77777  2010-06-29  2022-03-31      2.0  \n",
              "77778  2010-06-29  2022-03-31      2.0  \n",
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              "      <td>EWST</td>\n",
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              "      <td>EWST</td>\n",
              "      <td>ENERGY WEST INC</td>\n",
              "      <td>None</td>\n",
              "      <td>7953.0</td>\n",
              "      <td>2.0</td>\n",
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              "      <td>EGAS</td>\n",
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              "      <td>78513510</td>\n",
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              "      <td>SINO CLEAN ENERGY INC</td>\n",
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              "      <td>3.0</td>\n",
              "      <td>88160R10</td>\n",
              "      <td>2010-06-29</td>\n",
              "      <td>2022-03-31</td>\n",
              "      <td>2.0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>77779 rows × 16 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e0160bd7-aed6-4e38-bb6b-c2df911972bc')\"\n",
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              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-e0160bd7-aed6-4e38-bb6b-c2df911972bc button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e0160bd7-aed6-4e38-bb6b-c2df911972bc');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U6hDvCekqndW",
        "outputId": "e7e03d83-2453-4df6-a913-a0f976a60260"
      },
      "source": [
        "db"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<wrds.sql.Connection at 0x7f3a1a602950>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wxnrdyIOrxn0",
        "outputId": "10efc2e2-57a7-41d6-af75-fdff9e8f1174"
      },
      "source": [
        "stocknames.info()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 77779 entries, 0 to 77778\n",
            "Data columns (total 16 columns):\n",
            " #   Column     Non-Null Count  Dtype  \n",
            "---  ------     --------------  -----  \n",
            " 0   permno     77779 non-null  float64\n",
            " 1   namedt     77779 non-null  object \n",
            " 2   nameenddt  77779 non-null  object \n",
            " 3   shrcd      77779 non-null  float64\n",
            " 4   exchcd     77779 non-null  float64\n",
            " 5   siccd      77779 non-null  float64\n",
            " 6   ncusip     72335 non-null  object \n",
            " 7   ticker     72881 non-null  object \n",
            " 8   comnam     77779 non-null  object \n",
            " 9   shrcls     5108 non-null   object \n",
            " 10  permco     77779 non-null  float64\n",
            " 11  hexcd      77779 non-null  float64\n",
            " 12  cusip      77779 non-null  object \n",
            " 13  st_date    77779 non-null  object \n",
            " 14  end_date   77779 non-null  object \n",
            " 15  namedum    77779 non-null  float64\n",
            "dtypes: float64(7), object(9)\n",
            "memory usage: 9.5+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9EDz9jaAsxU4",
        "outputId": "9a4f0137-7848-4fca-e03d-01d56ded246a"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount(\"/content/gdrive\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bpcPd86ysxeL"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mI7-yC5Ua816",
        "outputId": "644d0807-a2c4-4508-8b65-505f23a5eb91"
      },
      "source": [
        "cd /content/gdrive/My Drive/Colab Notebooks/"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/gdrive/My Drive/Colab Notebooks\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SrSuHLKZsxlh"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Cl5xEmZKEWrJ"
      },
      "source": [
        "stocknames.to_csv('crsp_stocknames.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "crNiGqa_EWta"
      },
      "source": [
        "ls"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OArlgLOvEWvc"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RQpSxijNEWyW"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5XF8rnnt83bj"
      },
      "source": [
        "4. Now that we've examined the structure of our data by looking through its metadata, let's begin querying the data itself. First, let's take a peek at the first 100 rows of this database to see what we're working with. Using the LIMIT keyword to only return a small sample of the data, greatly speeding up the query a we only wish to get a quick summary.\n",
        "\n",
        "Both get_table() and raw_sql() can be used for this:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "id": "lLYHq5ra8gyB",
        "outputId": "8658a203-9e48-4fd1-894b-8d6ed3d0fd4a"
      },
      "source": [
        "db.get_table('crsp', 'dsf', obs=100)\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       cusip   permno   permco   issuno  hexcd  hsiccd        date    bidlo  \\\n",
              "0   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-05   0.5000   \n",
              "1   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-08   0.4250   \n",
              "2   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-09   0.5101   \n",
              "3   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-10   0.5419   \n",
              "4   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-11   0.5200   \n",
              "..       ...      ...      ...      ...    ...     ...         ...      ...   \n",
              "95  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-21  18.8125   \n",
              "96  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-24  18.6250   \n",
              "97  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-25  18.1250   \n",
              "98  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-26  17.8750   \n",
              "99  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-27  17.8125   \n",
              "\n",
              "      askhi      prc       vol       ret      bid      ask   shrout  cfacpr  \\\n",
              "0    0.6090   0.5999    9986.0 -0.045961   0.5999   0.6000   9296.0     1.0   \n",
              "1    0.6010   0.5700   31417.0 -0.049842   0.5699   0.5760   9296.0     1.0   \n",
              "2    0.5788   0.5788    9362.0  0.015439   0.5400   0.5770   9296.0     1.0   \n",
              "3    0.6000   0.5700    3878.0 -0.015204   0.5699   0.5700   9296.0     1.0   \n",
              "4    0.5600   0.5299    7930.0 -0.070351   0.5299   0.5300   9296.0     1.0   \n",
              "..      ...      ...       ...       ...      ...      ...      ...     ...   \n",
              "95  19.3125  19.0000  340136.0  0.006623  18.9375  19.1875  56689.0     1.0   \n",
              "96  19.2500  18.7500  173722.0 -0.013158  18.7500  18.8750  56689.0     1.0   \n",
              "97  18.7500  18.1875  322610.0 -0.030000  18.0000  18.1875  56689.0     1.0   \n",
              "98  18.2500  18.0625  357611.0 -0.006873  18.0000  18.0625  56689.0     1.0   \n",
              "99  18.1875  17.9375   50878.0 -0.006920  17.8125  17.9375  56689.0     1.0   \n",
              "\n",
              "    cfacshr  openprc  numtrd      retx  \n",
              "0       1.0   0.5000    39.0 -0.045961  \n",
              "1       1.0   0.6000    53.0 -0.049842  \n",
              "2       1.0   0.5200    35.0  0.015439  \n",
              "3       1.0   0.6000    14.0 -0.015204  \n",
              "4       1.0   0.5600    21.0 -0.070351  \n",
              "..      ...      ...     ...       ...  \n",
              "95      1.0  19.0000    76.0  0.006623  \n",
              "96      1.0  19.0000    51.0 -0.013158  \n",
              "97      1.0  18.7500    98.0 -0.030000  \n",
              "98      1.0  18.0000   130.0 -0.006873  \n",
              "99      1.0  18.1875    42.0 -0.006920  \n",
              "\n",
              "[100 rows x 20 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f4d129dc-b4d7-4938-bb69-0fa68b879cc2\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>cusip</th>\n",
              "      <th>permno</th>\n",
              "      <th>permco</th>\n",
              "      <th>issuno</th>\n",
              "      <th>hexcd</th>\n",
              "      <th>hsiccd</th>\n",
              "      <th>date</th>\n",
              "      <th>bidlo</th>\n",
              "      <th>askhi</th>\n",
              "      <th>prc</th>\n",
              "      <th>vol</th>\n",
              "      <th>ret</th>\n",
              "      <th>bid</th>\n",
              "      <th>ask</th>\n",
              "      <th>shrout</th>\n",
              "      <th>cfacpr</th>\n",
              "      <th>cfacshr</th>\n",
              "      <th>openprc</th>\n",
              "      <th>numtrd</th>\n",
              "      <th>retx</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-05</td>\n",
              "      <td>0.5000</td>\n",
              "      <td>0.6090</td>\n",
              "      <td>0.5999</td>\n",
              "      <td>9986.0</td>\n",
              "      <td>-0.045961</td>\n",
              "      <td>0.5999</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5000</td>\n",
              "      <td>39.0</td>\n",
              "      <td>-0.045961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-08</td>\n",
              "      <td>0.4250</td>\n",
              "      <td>0.6010</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>31417.0</td>\n",
              "      <td>-0.049842</td>\n",
              "      <td>0.5699</td>\n",
              "      <td>0.5760</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>53.0</td>\n",
              "      <td>-0.049842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-09</td>\n",
              "      <td>0.5101</td>\n",
              "      <td>0.5788</td>\n",
              "      <td>0.5788</td>\n",
              "      <td>9362.0</td>\n",
              "      <td>0.015439</td>\n",
              "      <td>0.5400</td>\n",
              "      <td>0.5770</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5200</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0.015439</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-10</td>\n",
              "      <td>0.5419</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>3878.0</td>\n",
              "      <td>-0.015204</td>\n",
              "      <td>0.5699</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>14.0</td>\n",
              "      <td>-0.015204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-11</td>\n",
              "      <td>0.5200</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>7930.0</td>\n",
              "      <td>-0.070351</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>0.5300</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>21.0</td>\n",
              "      <td>-0.070351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-21</td>\n",
              "      <td>18.8125</td>\n",
              "      <td>19.3125</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>340136.0</td>\n",
              "      <td>0.006623</td>\n",
              "      <td>18.9375</td>\n",
              "      <td>19.1875</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>76.0</td>\n",
              "      <td>0.006623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-24</td>\n",
              "      <td>18.6250</td>\n",
              "      <td>19.2500</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>173722.0</td>\n",
              "      <td>-0.013158</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>18.8750</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>51.0</td>\n",
              "      <td>-0.013158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-25</td>\n",
              "      <td>18.1250</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>322610.0</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>98.0</td>\n",
              "      <td>-0.030000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-26</td>\n",
              "      <td>17.8750</td>\n",
              "      <td>18.2500</td>\n",
              "      <td>18.0625</td>\n",
              "      <td>357611.0</td>\n",
              "      <td>-0.006873</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>18.0625</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>130.0</td>\n",
              "      <td>-0.006873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-27</td>\n",
              "      <td>17.8125</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>17.9375</td>\n",
              "      <td>50878.0</td>\n",
              "      <td>-0.006920</td>\n",
              "      <td>17.8125</td>\n",
              "      <td>17.9375</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>42.0</td>\n",
              "      <td>-0.006920</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f4d129dc-b4d7-4938-bb69-0fa68b879cc2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f4d129dc-b4d7-4938-bb69-0fa68b879cc2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f4d129dc-b4d7-4938-bb69-0fa68b879cc2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "id": "O_tNOkwQ8g1S",
        "outputId": "d1b202da-afcf-46c9-eb41-63e5b4db2777"
      },
      "source": [
        "db.raw_sql('select * from crsp.dsf LIMIT 100')"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       cusip   permno   permco   issuno  hexcd  hsiccd        date    bidlo  \\\n",
              "0   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-05   0.5000   \n",
              "1   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-08   0.4250   \n",
              "2   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-09   0.5101   \n",
              "3   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-10   0.5419   \n",
              "4   75747910  88371.0  37740.0  23794.0    3.0  7379.0  2016-02-11   0.5200   \n",
              "..       ...      ...      ...      ...    ...     ...         ...      ...   \n",
              "95  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-21  18.8125   \n",
              "96  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-24  18.6250   \n",
              "97  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-25  18.1250   \n",
              "98  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-26  17.8750   \n",
              "99  91705J20  88372.0  16512.0  23775.0    3.0  4832.0  2000-07-27  17.8125   \n",
              "\n",
              "      askhi      prc       vol       ret      bid      ask   shrout  cfacpr  \\\n",
              "0    0.6090   0.5999    9986.0 -0.045961   0.5999   0.6000   9296.0     1.0   \n",
              "1    0.6010   0.5700   31417.0 -0.049842   0.5699   0.5760   9296.0     1.0   \n",
              "2    0.5788   0.5788    9362.0  0.015439   0.5400   0.5770   9296.0     1.0   \n",
              "3    0.6000   0.5700    3878.0 -0.015204   0.5699   0.5700   9296.0     1.0   \n",
              "4    0.5600   0.5299    7930.0 -0.070351   0.5299   0.5300   9296.0     1.0   \n",
              "..      ...      ...       ...       ...      ...      ...      ...     ...   \n",
              "95  19.3125  19.0000  340136.0  0.006623  18.9375  19.1875  56689.0     1.0   \n",
              "96  19.2500  18.7500  173722.0 -0.013158  18.7500  18.8750  56689.0     1.0   \n",
              "97  18.7500  18.1875  322610.0 -0.030000  18.0000  18.1875  56689.0     1.0   \n",
              "98  18.2500  18.0625  357611.0 -0.006873  18.0000  18.0625  56689.0     1.0   \n",
              "99  18.1875  17.9375   50878.0 -0.006920  17.8125  17.9375  56689.0     1.0   \n",
              "\n",
              "    cfacshr  openprc  numtrd      retx  \n",
              "0       1.0   0.5000    39.0 -0.045961  \n",
              "1       1.0   0.6000    53.0 -0.049842  \n",
              "2       1.0   0.5200    35.0  0.015439  \n",
              "3       1.0   0.6000    14.0 -0.015204  \n",
              "4       1.0   0.5600    21.0 -0.070351  \n",
              "..      ...      ...     ...       ...  \n",
              "95      1.0  19.0000    76.0  0.006623  \n",
              "96      1.0  19.0000    51.0 -0.013158  \n",
              "97      1.0  18.7500    98.0 -0.030000  \n",
              "98      1.0  18.0000   130.0 -0.006873  \n",
              "99      1.0  18.1875    42.0 -0.006920  \n",
              "\n",
              "[100 rows x 20 columns]"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cusip</th>\n",
              "      <th>permno</th>\n",
              "      <th>permco</th>\n",
              "      <th>issuno</th>\n",
              "      <th>hexcd</th>\n",
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              "      <th>date</th>\n",
              "      <th>bidlo</th>\n",
              "      <th>askhi</th>\n",
              "      <th>prc</th>\n",
              "      <th>vol</th>\n",
              "      <th>ret</th>\n",
              "      <th>bid</th>\n",
              "      <th>ask</th>\n",
              "      <th>shrout</th>\n",
              "      <th>cfacpr</th>\n",
              "      <th>cfacshr</th>\n",
              "      <th>openprc</th>\n",
              "      <th>numtrd</th>\n",
              "      <th>retx</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-05</td>\n",
              "      <td>0.5000</td>\n",
              "      <td>0.6090</td>\n",
              "      <td>0.5999</td>\n",
              "      <td>9986.0</td>\n",
              "      <td>-0.045961</td>\n",
              "      <td>0.5999</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5000</td>\n",
              "      <td>39.0</td>\n",
              "      <td>-0.045961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-08</td>\n",
              "      <td>0.4250</td>\n",
              "      <td>0.6010</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>31417.0</td>\n",
              "      <td>-0.049842</td>\n",
              "      <td>0.5699</td>\n",
              "      <td>0.5760</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>53.0</td>\n",
              "      <td>-0.049842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-09</td>\n",
              "      <td>0.5101</td>\n",
              "      <td>0.5788</td>\n",
              "      <td>0.5788</td>\n",
              "      <td>9362.0</td>\n",
              "      <td>0.015439</td>\n",
              "      <td>0.5400</td>\n",
              "      <td>0.5770</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5200</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0.015439</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-10</td>\n",
              "      <td>0.5419</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>3878.0</td>\n",
              "      <td>-0.015204</td>\n",
              "      <td>0.5699</td>\n",
              "      <td>0.5700</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>14.0</td>\n",
              "      <td>-0.015204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>37740.0</td>\n",
              "      <td>23794.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7379.0</td>\n",
              "      <td>2016-02-11</td>\n",
              "      <td>0.5200</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>7930.0</td>\n",
              "      <td>-0.070351</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>0.5300</td>\n",
              "      <td>9296.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>21.0</td>\n",
              "      <td>-0.070351</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-21</td>\n",
              "      <td>18.8125</td>\n",
              "      <td>19.3125</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>340136.0</td>\n",
              "      <td>0.006623</td>\n",
              "      <td>18.9375</td>\n",
              "      <td>19.1875</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>76.0</td>\n",
              "      <td>0.006623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-24</td>\n",
              "      <td>18.6250</td>\n",
              "      <td>19.2500</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>173722.0</td>\n",
              "      <td>-0.013158</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>18.8750</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0000</td>\n",
              "      <td>51.0</td>\n",
              "      <td>-0.013158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-25</td>\n",
              "      <td>18.1250</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>322610.0</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.7500</td>\n",
              "      <td>98.0</td>\n",
              "      <td>-0.030000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-26</td>\n",
              "      <td>17.8750</td>\n",
              "      <td>18.2500</td>\n",
              "      <td>18.0625</td>\n",
              "      <td>357611.0</td>\n",
              "      <td>-0.006873</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>18.0625</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.0000</td>\n",
              "      <td>130.0</td>\n",
              "      <td>-0.006873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>16512.0</td>\n",
              "      <td>23775.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4832.0</td>\n",
              "      <td>2000-07-27</td>\n",
              "      <td>17.8125</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>17.9375</td>\n",
              "      <td>50878.0</td>\n",
              "      <td>-0.006920</td>\n",
              "      <td>17.8125</td>\n",
              "      <td>17.9375</td>\n",
              "      <td>56689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.1875</td>\n",
              "      <td>42.0</td>\n",
              "      <td>-0.006920</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4c51ffe0-e209-4b79-9d95-7a42d63593f1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4c51ffe0-e209-4b79-9d95-7a42d63593f1');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nft0eD3H9IOA"
      },
      "source": [
        "5. From our results to #3 above, let's say we've decided to only work with the cusip, permno, date, bidlo, and askhi variables. We can request only those five specific columns by modifying the above like so, again using both get_table() and raw_sql():\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "1byJYBhu9PLX",
        "outputId": "08a962b4-bb87-4c12-d27c-2f8415f56bbd"
      },
      "source": [
        "db.get_table('crsp', 'dsf', columns=['cusip, permno, date, bidlo, askhi'], obs=100, )"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       cusip   permno        date    bidlo    askhi\n",
              "0   75747910  88371.0  2016-02-05   0.5000   0.6090\n",
              "1   75747910  88371.0  2016-02-08   0.4250   0.6010\n",
              "2   75747910  88371.0  2016-02-09   0.5101   0.5788\n",
              "3   75747910  88371.0  2016-02-10   0.5419   0.6000\n",
              "4   75747910  88371.0  2016-02-11   0.5200   0.5600\n",
              "..       ...      ...         ...      ...      ...\n",
              "95  91705J20  88372.0  2000-07-21  18.8125  19.3125\n",
              "96  91705J20  88372.0  2000-07-24  18.6250  19.2500\n",
              "97  91705J20  88372.0  2000-07-25  18.1250  18.7500\n",
              "98  91705J20  88372.0  2000-07-26  17.8750  18.2500\n",
              "99  91705J20  88372.0  2000-07-27  17.8125  18.1875\n",
              "\n",
              "[100 rows x 5 columns]"
            ],
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>2016-02-08</td>\n",
              "      <td>0.4250</td>\n",
              "      <td>0.6010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>2016-02-09</td>\n",
              "      <td>0.5101</td>\n",
              "      <td>0.5788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>2016-02-10</td>\n",
              "      <td>0.5419</td>\n",
              "      <td>0.6000</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>2016-02-11</td>\n",
              "      <td>0.5200</td>\n",
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              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>2000-07-21</td>\n",
              "      <td>18.8125</td>\n",
              "      <td>19.3125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>2000-07-24</td>\n",
              "      <td>18.6250</td>\n",
              "      <td>19.2500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>2000-07-25</td>\n",
              "      <td>18.1250</td>\n",
              "      <td>18.7500</td>\n",
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              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>2000-07-26</td>\n",
              "      <td>17.8750</td>\n",
              "      <td>18.2500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>91705J20</td>\n",
              "      <td>88372.0</td>\n",
              "      <td>2000-07-27</td>\n",
              "      <td>17.8125</td>\n",
              "      <td>18.1875</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3e46cca6-71ab-4835-9d57-c37496e24af7')\"\n",
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              "\n",
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              "          const element = document.querySelector('#df-3e46cca6-71ab-4835-9d57-c37496e24af7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "LEuK04z99QOv",
        "outputId": "0eac177a-2cd6-4bed-8043-b15bf6ebee57"
      },
      "source": [
        "db.raw_sql('select cusip, permno, date, bidlo, askhi  from crsp.dsf LIMIT 100')"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       cusip   permno        date    bidlo    askhi\n",
              "0   75747910  88371.0  2016-02-05   0.5000   0.6090\n",
              "1   75747910  88371.0  2016-02-08   0.4250   0.6010\n",
              "2   75747910  88371.0  2016-02-09   0.5101   0.5788\n",
              "3   75747910  88371.0  2016-02-10   0.5419   0.6000\n",
              "4   75747910  88371.0  2016-02-11   0.5200   0.5600\n",
              "..       ...      ...         ...      ...      ...\n",
              "95  91705J20  88372.0  2000-07-21  18.8125  19.3125\n",
              "96  91705J20  88372.0  2000-07-24  18.6250  19.2500\n",
              "97  91705J20  88372.0  2000-07-25  18.1250  18.7500\n",
              "98  91705J20  88372.0  2000-07-26  17.8750  18.2500\n",
              "99  91705J20  88372.0  2000-07-27  17.8125  18.1875\n",
              "\n",
              "[100 rows x 5 columns]"
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              "\n",
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              "      <td>0.6090</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>75747910</td>\n",
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              "      <td>0.4250</td>\n",
              "      <td>0.6010</td>\n",
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              "      <td>0.5101</td>\n",
              "      <td>0.5788</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>75747910</td>\n",
              "      <td>88371.0</td>\n",
              "      <td>2016-02-10</td>\n",
              "      <td>0.5419</td>\n",
              "      <td>0.6000</td>\n",
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              "      <th>4</th>\n",
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              "      <th>95</th>\n",
              "      <td>91705J20</td>\n",
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              "      <td>18.8125</td>\n",
              "      <td>19.3125</td>\n",
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              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>91705J20</td>\n",
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              "      <td>18.6250</td>\n",
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              "      <th>97</th>\n",
              "      <td>91705J20</td>\n",
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              "      <td>18.1250</td>\n",
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              "      <td>17.8125</td>\n",
              "      <td>18.1875</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 5 columns</p>\n",
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        "\n",
        "6. Run the query again, but filter the query for 'permno', limiting results to a single day:\n",
        "\n",
        "Since you are now filtering by specific values for variables, use raw_sql() exclusively. All future examples will be shown using raw_sql().\n",
        "\n",
        "NOTE: Use single quotation marks around the date value and double quotation marks elsewhere as shown below.\n"
      ]
    },
    {
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        "db.raw_sql(\"select cusip, permno, date, bidlo, askhi \"\n",
        "           \"from crsp.dsf \"\n",
        "           \"where permno in (14593, 90319, 12490, 17778) \"\n",
        "           \"and date='2013-01-04'\")"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      cusip   permno        date          bidlo          askhi\n",
              "0  45920010  12490.0  2013-01-04     192.779999     194.460007\n",
              "1  03783310  14593.0  2013-01-04     525.828613     538.629883\n",
              "2  08467010  17778.0  2013-01-04  140047.000000  141003.796875\n",
              "3  02079K30  90319.0  2013-01-04     727.680115     741.469971"
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      "source": [
        "6. Determine high 'askhi' values by running a query to get a list of dates where 'permno' values posted an Ask Price over $2,000 between the years 2010 and 2013, no longer limiting the number of returned rows (as this is a pretty specific query):\n"
      ]
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        "db.raw_sql(\"select cusip,permno,date,bidlo,askhi from crsp.dsf where permno in (14593, 90319, 12490, 17778) and date between '2010-01-01' and '2013-12-31' and askhi > 2000\")\n"
      ],
      "execution_count": 22,
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              "         cusip   permno        date         bidlo     askhi\n",
              "0     08467010  17778.0  2010-01-04   99201.00000   99910.0\n",
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              "4     08467010  17778.0  2010-01-08   99700.00000  100300.0\n",
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              "1005  08467010  17778.0  2013-12-31  176793.00000  177950.0\n",
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              "  "
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BlyzFht69efQ"
      },
      "source": [
        "7. Only a single 'permno' posted a high Ask price during this date range. Open the search to all permnos that have ever posted an Ask Price over $2,000 in any date range (use distinct to return only one entry per matching permno). Since the query is against all permnos and the entire date range of the dataset, this query may take a little longer:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yK3Tkvq89fDw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "outputId": "0be7c77b-663d-425a-d9af-87295cbbbdf0"
      },
      "source": [
        "db.raw_sql('select distinct permno from crsp.dsf where askhi > 2000')"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     permno\n",
              "0   14542.0\n",
              "1   14752.0\n",
              "2   15395.0\n",
              "3   16280.0\n",
              "4   17486.0\n",
              "5   17778.0\n",
              "6   17881.0\n",
              "7   21709.0\n",
              "8   36281.0\n",
              "9   46068.0\n",
              "10  76605.0\n",
              "11  79785.0\n",
              "12  83443.0\n",
              "13  84788.0\n",
              "14  86783.0\n",
              "15  90319.0\n",
              "16  92221.0\n",
              "17  93436.0"
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tDsv6YWT9fK2"
      },
      "source": [
        "8. Retrieve all dates for which an Ask Price over $2000 was posted, along with the permnos that posted them. This will give a list of dates that match, with an additional entry for that date if additional permnos match as well. By 2011, there are two results:\n"
      ]
    },
    {
      "cell_type": "code",
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          "height": 424
        },
        "outputId": "5dad2269-978f-4a7a-ba21-70faec1949e3"
      },
      "source": [
        "db.raw_sql(\"select distinct date,permno from crsp.dsf where askhi > 2000 order by date\")\n"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             date   permno\n",
              "0      1926-12-23  14752.0\n",
              "1      1926-12-24  14752.0\n",
              "2      1927-01-07  14752.0\n",
              "3      1927-01-08  14752.0\n",
              "4      1948-05-15  16280.0\n",
              "...           ...      ...\n",
              "17986  2022-03-31  76605.0\n",
              "17987  2022-03-31  79785.0\n",
              "17988  2022-03-31  84788.0\n",
              "17989  2022-03-31  86783.0\n",
              "17990  2022-03-31  90319.0\n",
              "\n",
              "[17991 rows x 2 columns]"
            ],
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              "<p>17991 rows × 2 columns</p>\n",
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              "                                                     [key], {});\n",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ut3YEa1K9fXr"
      },
      "source": [
        "\n",
        "9. Query for the highest Ask ever posted (searching only through Asks over $2000), on what date it posted, and which permno posted it. Use limit 1 to speed up the search since only the top value is desired:\n"
      ]
    },
    {
      "cell_type": "code",
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        "id": "blJA--OY9fcy",
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          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "outputId": "59f30d33-95a1-43c2-fab5-234987be953e"
      },
      "source": [
        "db.raw_sql('select permno,askhi,date from crsp.dsf where askhi > 2000 order by askhi desc LIMIT 1')\n"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    permno      askhi        date\n",
              "0  17778.0  544389.25  2022-03-29"
            ],
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              "      <th></th>\n",
              "      <th>permno</th>\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1wu1hY2X9fh4"
      },
      "source": [
        "This is one example of how you might approach an analytical task using Python. It begins by gathering metadata information using list_libraries() and list_tables() to learn more about the data structure available, and then using that information to run meaningful queries from the data itself using get_table() and raw_sql()..\n",
        "\n",
        "A common next step would be to write a batch program that uses the above one-off queries together. An example might be a program that uses a loop to iterate over each permno that has ever posted an Ask Price over $2000 and to calculate how long the date range was able to maintain that height. Or perhaps certain dates were more prolific than others - tallying the number of high asks per date might be informative."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_6P3sJAa8Sv7"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}