nfl-stats | getting NFL team , player and game data | Analytics library

 by   jeremyjbowers Python Version: Current License: Non-SPDX

kandi X-RAY | nfl-stats Summary

kandi X-RAY | nfl-stats Summary

nfl-stats is a Python library typically used in Analytics applications. nfl-stats has no bugs, it has no vulnerabilities, it has build file available and it has low support. However nfl-stats has a Non-SPDX License. You can download it from GitHub.

A suite of tools for getting NFL team, player and game data, as well as real-time statistics.
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            kandi-support Support

              nfl-stats has a low active ecosystem.
              It has 22 star(s) with 9 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 3 open issues and 1 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of nfl-stats is current.

            kandi-Quality Quality

              nfl-stats has 0 bugs and 0 code smells.

            kandi-Security Security

              nfl-stats has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              nfl-stats code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              nfl-stats has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              nfl-stats releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed nfl-stats and discovered the below as its top functions. This is intended to give you an instant insight into nfl-stats implemented functionality, and help decide if they suit your requirements.
            • Get the data for the week
            • Set fields of this object
            • Read file contents
            • Write the game data to disk
            Get all kandi verified functions for this library.

            nfl-stats Key Features

            No Key Features are available at this moment for nfl-stats.

            nfl-stats Examples and Code Snippets

            No Code Snippets are available at this moment for nfl-stats.

            Community Discussions

            QUESTION

            Beautiful Soup - having trouble on a specific page
            Asked 2018-Oct-09 at 05:38

            I've successfully been able to use beautiful soup in the past (I'm still learning how to use it), but I'm getting stuck on how to get this one specific table here:

            https://fantasydata.com/nfl-stats/point-spreads-and-odds?season=2017&seasontype=1&week=1

            In the past, it's as simple as doing:

            ...

            ANSWER

            Answered 2018-Aug-09 at 22:46

            You don't need BeautifulSoup or Selenium for this. Data is available as python dictionary on POSTing query to https://fantasydata.com/NFLTeamStats/Odds_Read.

            Source https://stackoverflow.com/questions/51776555

            QUESTION

            python beautifulsoup - pull a list/dictionary
            Asked 2018-Aug-18 at 12:46

            I'm still leaning how to utilize beautifulsoup. I've managed to use tags and what not to pull the data from Depth Chart table at https://fantasydata.com/nfl-stats/team-details/CHI

            But now I'm try to pull the Full Roster table. I can't quite seem to figure out the tags for that. I do notice in the source though that the info is in a list with dictionaries, as seen:

            ...

            ANSWER

            Answered 2018-Aug-18 at 12:46

            One possible solution is to use a regular expression to extract the raw JSON object which then can be loaded using the json library.

            Source https://stackoverflow.com/questions/51907544

            QUESTION

            Python - Web Scraping concurrent to improve my code?
            Asked 2017-Sep-11 at 11:07

            So I'm pulling statistics of NFL players. The table only shows max 50 rows, so I have to filter it down to make sure I don't miss any stats, which means I'm iterating through the pages to collect all the data by Season, by Position, by Team, by Week.

            I figured out how the url changes to cycle through these, but the iteration process takes so long, and was thinking: we're able to open multiple webpages at one time, couldn't I be able to run these processes parallel, where each process simultaneously collects the data from each page, stores it in its temp_df, then merge them all at the end...instead of collecting one url, by one url, then merge, then next url, then merge, then next,......at a time. Meaning this iterates through 6,144 times (if I'm not iterating through the positions), but with the positions, over 36,000 iteration through.

            But I'm stuck on how to implement it, or if it's even possible.

            Here's the code I'm currently using. I eliminated the cycle through position to just give an idea of how its working, which for quarterbacks, the p = 2.

            So it starts at season 2005 = 1, team 1 = 1, week 1 =0, then iterates all those to the last season 2016 = 12, team 32 = 33, and week 16 = 17:

            ...

            ANSWER

            Answered 2017-Sep-11 at 11:03

            1/ Create a dict of season, team, weeks and urls.

            2/ Use multiprocessing pool to call urls and get data.

            Or use a dedicated scraping tool like Scrapy.

            Source https://stackoverflow.com/questions/46153998

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install nfl-stats

            You can download it from GitHub.
            You can use nfl-stats like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            CLONE
          • HTTPS

            https://github.com/jeremyjbowers/nfl-stats.git

          • CLI

            gh repo clone jeremyjbowers/nfl-stats

          • sshUrl

            git@github.com:jeremyjbowers/nfl-stats.git

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