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nfl_data_py.egg-info/PKG-INFO

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+Metadata-Version: 2.1
+Name: nfl-data-py
+Version: 0.1.0
+Summary: Package for working with NFL data
+Home-page: https://github.com/cooperdff/nfl_data_py
+Author: cooperdff
+Author-email: [email protected]
+License: MIT
+Description: # nfl_data_py
+
+        nfl_data_py is a Python library for interacting with NFL data sourced from nflfastR (https://github.com/nflverse/nflfastR-data/) and nfldata (https://github.com/nflverse/nfldata/).
+
+        ## Installation
+
+        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install nfl_data_py.
+
+        ```bash
+        pip install nfl_data_py
+        ```
+
+        ## Usage
+
+        ```python
+        import nfl_data_py as nfl
+        ```
+
+        **Working with play-by-play data**
+        ```python
+        nfl.import_pbp_data(years, columns)
+        ```
+        Returns play-by-play data for the years and columns specified
+
+        years
+        : required, list of years to pull data for (earliest available is 1999)
+
+        columns
+        : optional, list of columns to pull data for
+
+        ```python
+        nfl.see_pbp_cols()
+        ```
+        returns list of columns available in play-by-play dataset
+
+        **Working with weekly data**
+        ```python
+        nfl.import_weekly_data(years, columns)
+        ```
+        Returns weekly data for the years and columns specified
+
+        years
+        : required, list of years to pull data for (earliest available is 1999)
+
+        columns
+        : optional, list of columns to pull data for
+
+        ```python
+        nfl.see_weekly_cols()
+        ```
+        returns list of columns available in weekly dataset
+
+        **Working with seasonal data**
+        ```python
+        nfl.import_seasonal_data(years)
+        ```
+        Returns seasonal data, including various calculated market share stats
+
+        years
+        : required, list of years to pull data for (earliest available is 1999)
+
+        **Additional data imports**
+        ```python
+        nfl.import_rosters(years, columns)
+        ```
+        Returns roster information for years and columns specified
+
+        years
+        : required, list of years to pull data for (earliest available is 1999)
+
+        columns
+        : optional, list of columns to pull data for
+
+        ```python
+        nfl.import_win_totals(years)
+        ```
+        Returns win total lines for years specified
+        years
+        : optional, list of years to pull
+
+        ```python
+        nfl.import_sc_lines(years)
+        ```
+        Returns scoring lines for years specified
+        years
+        : optional, list of years to pull
+
+        ```python
+        nfl.import_officials(years)
+        ```
+        Returns official information by game for the years specified
+        years
+        : optional, list of years to pull
+
+        ```python
+        nfl.import_draft_picks()
+        ```
+        Returns list of draft picks for the years specified
+        years
+        : optional, list of years to pull
+
+        ```python
+        nfl.import_draft_values()
+        ```
+        Returns relative values by generic draft pick according to various popular valuation methods
+        ```python
+        nfl.import_team_desc()
+        ```
+        Returns dataframe with color/logo/etc information for all NFL team
+
+        ```python
+        nfl.import_schedules(years)
+        ```
+        Returns dataframe with schedule information for years specified
+
+        years: required, list of years to pull data for (earliest available is 1999)
+
+        **Additional features**
+        ```python
+        nfl.clean_nfl_data(df)
+        ```
+        Runs descriptive data (team name, player name, etc.) through various cleaning processes
+
+        df
+        : required, dataframe to be cleaned
+
+        ## Recognition
+        I'd like to recognize all of [Ben Baldwin](https://twitter.com/benbbaldwin), [Sebastian Carl](https://twitter.com/mrcaseb), and [Lee Sharpe](https://twitter.com/LeeSharpeNFL) for making this data freely available and easy to access. I'd also like to thank [Tan Ho](https://twitter.com/_TanH), who has been an invaluable resource as I've worked through this project, and Josh Kazan for the resources and assistance he's provided.
+
+        ## Contributing
+        Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
+
+        ## License
+        [MIT](https://choosealicense.com/licenses/mit/)
+
+Platform: UNKNOWN
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Requires-Python: >=3.6
+Description-Content-Type: text/markdown

nfl_data_py.egg-info/SOURCES.txt

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+README.md
+setup.py
+nfl_data_py.egg-info/PKG-INFO
+nfl_data_py.egg-info/SOURCES.txt
+nfl_data_py.egg-info/dependency_links.txt
+nfl_data_py.egg-info/requires.txt
+nfl_data_py.egg-info/top_level.txt

nfl_data_py.egg-info/dependency_links.txt

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+

nfl_data_py.egg-info/requires.txt

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+numpy>1
+pandas>1
+datetime>3.5
+fastparquet>0.5
+python-snappy>0.5
+snappy>1

nfl_data_py.egg-info/top_level.txt

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+nfl_data_py

setup.py

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+from setuptools import setup
+
+# read the contents of your README file
+from os import path
+this_directory = path.abspath(path.dirname(__file__))
+with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
+    long_description = f.read()
+
+setup(
+	name='nfl_data_py',
+	version='0.1.0',
+	description='Package for working with NFL data',
+    author='cooperdff',
+    author_email='[email protected]',
+    url='https://github.com/cooperdff/nfl_data_py',
+    license='MIT',
+    classifiers=[
+    'Development Status :: 5 - Production/Stable',
+    'License :: OSI Approved :: MIT License',
+    'Programming Language :: Python :: 3.6',
+    'Programming Language :: Python :: 3.7',
+    'Programming Language :: Python :: 3.8',
+    'Programming Language :: Python :: 3.9',
+],
+	packages=['nfl_data_py'],
+	package_dir={'nfl_data_py': ''},
+    python_requires='>=3.6',
+    install_requires=[
+        'numpy>1',
+        'pandas>1',
+        'datetime>3.5',
+        'fastparquet>0.5',
+        'python-snappy>0.5',
+        'snappy>1',
+    ],
+    long_description=long_description,
+    long_description_content_type='text/markdown'
+)