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        "author": "Dibya Ghosh",
        "author_email": "dibya.ghosh@berkeley.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Database",
            "Topic :: Database :: Front-Ends",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Mathematics"
        ],
        "description": "dbTable\n^^^^^^^\n\ndbTable is a innovative library built on the Python SQLite Library that\nallows you to manipulate views on tables in Databases, select data from\nthem, and modify them in many ways. This library abstracts out all SQL\nqueries with native Python syntax, and has built-in lazy computation as\nwell. Furthermore, this library provides an interface to load tables\nfrom SQLite into in-memory table structures like Pandas DataFrames or\nNumpy Array for further analysis.\n\nCheck out the full documentation at `DOCUMENTATION`_\n\nQuickstart Guide:\n\n1) Installation\n\nMake sure you have numpy and tabulate installed\n\n::\n\n    pip install numpy\n    pip install tabulate\n\nInstall dbTable through PyPI (This\u2019ll automatically install numpy and\ntabulate)\n\n::\n\n    pip install dbTable\n\nYou can also install the built distribution in the dist/ folder, or for\nportable cases, just download the dbTable.py file, and place it in your\nproject folder\n\n2) Load dbTable into your interpreter/project\n\n.. code:: python\n\n    import dbTable\n\n3) Make a connection to a database\n\n.. code:: python\n\n    db = Database('test.db') # Replace with your database or use \":memory:\" to load an in-memory database\n\n4) Select a table:\n\n.. code:: python\n\n    table1 = db['table1'] \n\n5) Exporting / Importing\n\nTo convert a dbTable to any other form, use:\n\n.. code:: python\n\n    new_df = db['table1'].to_df() # Returns a Pandas DataFrame Object\n    new_table = db['table1'].to_table() # Returns a UCB Datascience Table \n    new_ndarray = db['table1'].to_numpy_array() # Returns a Numpy Array\n\nTo save a DataFrame, UCB Table, or Numpy Array, use:\n\n.. code:: python\n\n    db.store_table(new_df,'newtablename')\n\nHere\u2019s a sampling of modifications and filters you can do with dbTable\n\n.. code:: python\n\n    table2 = table1.select(['col1','col2']) # Selecting columns from database\n    table3 = table2.where(table2['col1']> 20) # Filters\n    table4 = table3.sort('col2',descending=False) # Sort data\n    grouped_table = table4.group(table4['col1'])\n    table4['col2'] = table4['col1']*10 # Modify columns\n    table4['col3'] = table4['col1']+table4['col2']\n    table4['col3'] *= 2\n\nHave fun!\n\nCheck out the full documentation at `DOCUMENTATION`_\n\n.. _DOCUMENTATION: http://dibya.xyz/dbTable/documentation.html",
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        "keywords": "datascience data science numpy database sqlite table column",
        "license": "MIT",
        "maintainer": "",
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        "name": "dbTable",
        "package_url": "https://pypi.org/project/dbTable/",
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