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    "info": {
        "author": "Reid Bradley",
        "author_email": "reidbradley.dev@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.5"
        ],
        "description": "\nProspecting\n===========\n\n\nGoogle Sheets with Pandas dataframes, useful when 'prospecting' in analytics work and hacking.\n\n\n____\n\n**Setup**\n\n  1. Create or select a project in `Google's developer console`__\n\n     - Also, you will need to enable the APIs you plan to use\n\n  #. Get a ``client_secrets.json`` credentials file from the `credentials section`__\n\n     - Select *OAuth client ID* from the dropdown in the `API access pane`__\n\n  #. Load the ``prospecting`` module in a Python session to initialize the ``~/.prospecting/`` folder in your home directory\n  #. Place the ``client_secrets.json`` file in the ``~/.prospecting/credentials/`` directory\n  #. Load an API class in a Python session, then run apiclass.authenticate() and follow steps\n\n     - You only need to setup authentication once per API unless creds change\n\n\n.. _DevConsole: https://console.developers.google.com/apis/dashboard\n__ DevConsole_\n\n.. _Credentials: https://console.developers.google.com/apis/credentials\n__ Credentials_\n\n.. _ApiPane: https://console.developers.google.com/apis/credentials\n__ ApiPane_\n\n\n**Examples**::\n\n    import prospecting as p\n\n---\n\nUse stats sheet to store stats and misc statistics (scopelist defaults to read-only, so pass scopes for writing)::\n\n    ss_stats = p.SheetsApi(spreadsheetid = 'PASTE_GOOGLE_SHEETID_HERE',\n                           scopelist=['https://www.googleapis.com/auth/spreadsheets',\n                                      'https://www.googleapis.com/auth/drive.metadata'])\n    ss_stats.authenticate()\n    ss_stats.update('Sheet1', somedataframe)\n\n\n---\n\nUse a reference sheet to provide a named entity list (or stopwords, vocabulary) for NLP preprocessing::\n\n    ss_reference = p.SheetsApi(spreadsheetid = 'PASTE_GOOGLE_SHEETID_HERE',\n                               scopelist=['https://www.googleapis.com/auth/spreadsheets',\n                                          'https://www.googleapis.com/auth/drive.metadata'])\n    ss_reference.authenticate()\n    named_entity_list = list(ss_reference.get('ne!A:B').iloc[:,0].values)\n\n\n---\n\nGet keywords sheet as dataframe, filter, take sampled subset, upload new df to other tab in spreadsheet::\n\n    ss_kw = p.SheetsApi(spreadsheetid = 'PASTE_GOOGLE_SHEETID_HERE',\n                        scopelist=['https://www.googleapis.com/auth/spreadsheets',\n                                   'https://www.googleapis.com/auth/drive.metadata'])\n    ss_kw.authenticate()\n\n    #  Get data using spreadsheet syntax like ('sheetname') or ('sheetname!A:B25')\n    df_query = ss_kw.get('queries')\n    df_query_subset = df_query[(df_query['raw_len'] > 1) &\n                               (df_query['reject'] != 1)]\n\n    #  Take a subsample of data\n    df_query_subset_sample = df_query_subset.sample(frac=0.5)\n    df_query_subset_sample.reset_index(drop=True, inplace=True)\n\n    #  Update 'sheetname' with dataframe object\n    ss_kw.update('queries_shuffled', df_query_subset_sample)\n\n\n____\n\n\nKey changes between 0.1.4 and 0.1.2:\n\n* Switched order of input arguments for ss.update() function::\n\n      From\n         ss.update(dataframe, 'sheetname')\n      To\n         ss.update('sheetname', dataframe)\n\n* Removed Docker files to simplify\n\n____\n\n\\\n\n____\n\n|hammer_and_pick| |hammer_and_pick| |hammer_and_pick|\n\n.. |hammer_and_pick| image:: https://storage.googleapis.com/prospecting-151803.appspot.com/hammer_and_pick_60x60.png\n\n",
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        "home_page": "https://github.com/reidbradley/prospecting",
        "keywords": "Pandas,Google Sheets,Google APIs",
        "license": "MIT",
        "maintainer": "",
        "maintainer_email": "",
        "name": "prospecting",
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        "summary": "Marketing toolset using Pandas & Google Sheets API, with classes for a variety of other Google APIs",
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