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        "author": "Samyak Ratna Tamrakar",
        "author_email": "samyak.r.tamrakar@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Database :: Database Engines/Servers"
        ],
        "description": "# GiantPandas\nSome special functions and connectors for Pandas.\n\n## Requirements\n\n* Python 3+ (Tested in 3.7)\n* numpy>=1.13.3\n* pandas>=0.25.0\n* pytest>=5.0.1\n* psycopg2-binary>=2.8.3\n* Unidecode>=1.0.22\n* xlrd>=1.2.0\n* XlsxWriter>=1.0.2\n* DailyLogger>=0.1.2\n* FreqObjectOps>=0.1.0\n\n\n## Install with pip\n```bash\n$ pip install GiantPandas\n```\n\n## Usage\n1. Import the library.\n    ```python\n    from GiantPandas import PandasOps, ExcelConnector, PsqlConnector\n    ```\n1. Each of the imported submodules has several functions. Please refer to respective help for more information.\n\n#### ```PandasOps```\n\n1. ```PandasOps.get_row_count(dataframe)```: get row count of a dataframe\n1. ```PandasOps.get_dict_from_two_columns(dataframe, key_column, value_column, keep_duplicate_keys)```: get dictionary from two dataframe columns\n1. ```PandasOps.get_dataframe_with_all_permutations_from_dict(dict_with_list_values)```: create dataframe with all possible permutations from dict with values of type list\n1. ```PandasOps.set_column_as_index(dataframe, column_name, drop_original_column)```: set column as an index\n1. ```PandasOps.get_dict_of_column_name_to_type(dataframe)```: get dict of column name to their dtype\n1. ```PandasOps.get_column_names_by_type(dataframe, column_dtype)```: get all columns of desired dtype\n1. ```PandasOps.contains_all_integer_in_float_column(dataframe, column_name)```: check if all non-nan values in float columns are int\n1. ```PandasOps.set_column_names_to_alpha_numeric(dataframe)```: convert column name to alpha numeric\n1. ```PandasOps.set_column_names_to_snake_case(dataframe)```: convert column name to snake case\n1. ```PandasOps.exists_unnamed_headers(dataframe)```: check if a dataframe contains any unnamed headers\n1. ```PandasOps.exists_column(dataframe, column_name_list)```: check if a dataframe contains desired column\n1. ```PandasOps.get_maximum_length_of_dtype_object_values(dataframe, column_name)```: get maximum length of object in a column\n\n#### ```ExcelConnector```\n1. \t```ExcelConnector.get_sheet_names(file)```: get all sheet names\n1. \t```ExcelConnector.get_dataframe_from_excel(file, sheet_name, skip_rows_list)```: read excel sheet into a dataframe\n1. \t```ExcelConnector.send_dataframe_to_excel(file, dataframe_to_sheet_name_tuple_list, write_index)```: write dataframe to an excel sheet\n\n#### ```PsqlConnector```\nFirst, an instance must be created for establishing connection.\n```python\npsql_connector = PsqlConnector(host='localhost',\n                               dbname='postgres',\n                               username='postgres',\n                               password='',\n                               port='5432')\n```\nThen,\n1. ```psql_connector.get_psql_query_results_as_dataframe(query)```: get results of a psql query as a dataframe\n1. ```psql_connector.send_dataframe_to_psql(dataframe, schema_name, table_name, if_exists)```: upload dataframe to psql\n\n\n#### Demo\n\nDemo script for saving results of PostgreSQL query into an excel file.\n```bash\n$ python3 demo/Psql2Excel.py -f test2.xlsx -H localhost -d postgres -u postgres -t test_table -sn Sheet1\n```\n\nDemo script for uploading a table from excel sheet into a PSQL database.\n```bash\n$ python3 demo/Excel2Psql.py -f tests/test.xlsx -H localhost -d postgres -u postgres -t test_table\n```\n\n**© [Samyak Ratna Tamrakar](https://www.linkedin.com/in/srtamrakar/)**, 2019.",
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