parkrun | simple functions in Python to manipulate and analyse | Data Visualization library

by jobar8 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | parkrun Summary

parkrun is a Python library typically used in Analytics, Data Visualization applications. parkrun has no bugs, it has no vulnerabilities and it has low support. However parkrun build file is not available. You can download it from GitHub.

This is a collection of simple functions in Python to manipulate and analyse parkrun data. The library requires pandas and matplotlib to work.

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Support

parkrun has a low active ecosystem.

It has 6 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

parkrun has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of parkrun is current.

Quality

parkrun has no bugs reported.

Security

parkrun has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

parkrun does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

parkrun releases are not available. You will need to build from source code and install.

parkrun has no build file. You will be need to create the build yourself to 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 parkrun and discovered the below as its top functions. This is intended to give you an instant insight into parkrun implemented functionality, and help decide if they suit your requirements.

Plot a time histogram
Convert a number of minutes to a time string

Get all kandi verified functions for this library.

parkrun Key Features

No Key Features are available at this moment for parkrun.

parkrun Examples and Code Snippets

No Code Snippets are available at this moment for parkrun.

Community Discussions

Trending Discussions on parkrun

Dynamic numpy reshape of a web-scraped table in python

Using IMPORTHTML against Parkrun data and returning N/A

How to combine tibbles with common but non-identical columns?

QUESTION

Dynamic numpy reshape of a web-scraped table in python

Asked 2020-May-06 at 17:57

I am having trouble getting a usable data frame from scraping a website. I know I need to turn my list into a list of lists, and that's easy to do with a static data frame. But here's the rub: my scraped data changes daily, and I want to automate the data frame creation. First, I scrape the data:

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ANSWER

Answered 2020-May-06 at 17:57

Relatively simple fix, all it took was for me to ignore work for a bit, and play around with numpy outside of the loop:

Source https://stackoverflow.com/questions/61621547

QUESTION

Using IMPORTHTML against Parkrun data and returning N/A

Asked 2018-Jun-27 at 21:20

I am using the following call in google sheets

=IMPORTHTML("http://www.parkrun.org.uk/harrogate/results/eventhistory","table",1)

this used to pull in the table beautifully but has recently stopped working.

Anyone know why?

Cheers

Jon

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ANSWER

Answered 2018-Jun-27 at 21:20

I'm guessing:

A change in their robots.txt file, which presently mentions:

robots.txt for parkrun event websites http://www.parkrun.org.uk http://www.parkrun.dk etc parkrun results are Copyright (c) parkrun. Results are made available for personal, non-commercial use only. We request that automated scraping does not take place. If you have a legitimate requirement, please contact techsupport@parkrun.com so we can discuss your requirements. See also http://www.parkrun.org.uk/scraper.html

and Disallow: includes:

Source https://stackoverflow.com/questions/51024131

QUESTION

How to combine tibbles with common but non-identical columns?

Asked 2017-Aug-11 at 21:57

I have two tibbles, each with up to 4 columns. Each column name will either be common to both or missing from one or the other. I need to combine these into one tibble with two rows, and NA in columns where they are missing. I need to do this generically, so it works with more or less missing columns. Here's the code which produces the tibbles from two example web pages;

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ANSWER

Answered 2017-Aug-11 at 21:57

Your problem is that one of the columns of r2 has a NA for name. Thus, most functions that pair matrix like objects on the basis of column names will fail. To solve it, add this line to your function: names(tib)[is.na(names(tib))] <- "Blank"

Source https://stackoverflow.com/questions/45643886

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

Vulnerabilities

No vulnerabilities reported

Install parkrun

You can download it from GitHub.
You can use parkrun 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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