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        "description": "# IE Pandas\n---\n\nThis is Team C's final project in Advanced Python.\n\nA simple implementation of dataframe functionality\n\nThe library is available in [Pypi](https://pypi.org/project/ie_pandas/)\n\n### Installing\n---\n\n\nThe easiest way to install ie_pandas is through ```pip```\n\n```python\npip install ie_pandas\n```\n\nTo use it in your project, you must first import the library\n\n```python\nfrom ie_pandas import Dataframe\n```\n\nYou can create a frame by the following 4 methods:\n* A list of lists\n* A numpy array of lists\n* A dictionary of lists with keys being column names and values being the values for that column\n* A dictionary of numpy arrays (same as with lists)\n\n```python\ndictionary = {'c0': [1, 3, 5], 'c1': [7, 6, 2], 'c2': [2, 4, 7], 'c3': [5, 3, 9]}\ndf = DataFrame(dictionary)\n```\n#### Functionality\n* Create dataframes from list of lists, numpy arrays, dictionaries of lists and numpy arrays\n```python\ndictionary = {'c0': [1, 3, 5], 'c1': [7, 6, 2], 'c2': [2, 4, 7], 'c3': [5, 3, 9]}\ndf = DataFrame(dictionary)\n\n# You may optionally pass along two parameters, cols and index\n# cols determines the column names (if blank they will be numerical strings)\n# index determines the row names (if blank they will be numbers)\ndf = DataFrame(dictionary, cols = [\"col0\", \"col1\", \"col2\", \"col3\"], index = [\"row1\", \"row2\", \"row3\"])\n```\n* Access columns by name\n```python\ndf['column_1']\n```\n* Access rows by position or by row name\n```python\ndf.get_index(1)\n# or\ndf.get_index('row_1')\n```\n* Access data like a numpy array by name\n```python\ndf[0:2, 1:3]\n```\n* Modify dataframe\n```python\ndf[0,0] = 3\n```\n* Sum, median, mean, min, max methods (only work for numerical columns)\n```python\ndf.mean()\n```\n\nSince the underlying object of the dataframe is a numpy array, you may perform aditional functionality like\n```python\ndf[:, 1:2].sum()\n```\n* Visualize relationships between 2 entirely numerical columns (only for numerical columns)\n```python\ndf.visualize(df[:, 2], df[:, 3])\n# or\ndf.visualize(df[\"c1\"], df[\"c2\"])\n```\n\n#### Dependencies\n\nIE_Pandas only requires the following packages:\n* Numpy (>=1.16)\n* Matplotlib (>=3.0.2)\n\nHowever, for development purposes, the following packages are needed:\n* Pytest (>= 4.2)\n* Pytest-cov (>= 2.6)\n* Black (for PEP8 compliance)\n\n### Development\n---\nFor development purposes, you may download the files directly and install the library locally by placing your terminal in the downloaded folder and doing\n\n```python\npip install --editable .[dev]\n```\n\nThen, to execute the tests you just need to run\n\n```python\npytest --cov\n```\n\n### IE_Pandas Coding Style\n---\nIE_Pandas complies to PEP8 and uses ```black``` for coding standards\n\n### Versioning\n---\n[SemVer](http://semver.org/) is used for versioning. \n\n### License\n---\nThis project is licensed under the MIT License - see the [License](license.txt) file for details\n\n",
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