football_data | Python scripts used to scrape data

by BenKite Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(6)Vulnerabilities Install Support

kandi X-RAY | football_data Summary

football_data is a Python library typically used in Telecommunications, Media, Media, Entertainment applications. football_data has no bugs, it has no vulnerabilities and it has low support. However football_data build file is not available. You can download it from GitHub.

Python scripts used to scrape data from pro-football-reference.com

Support

Quality

Security

License

Reuse

Support

football_data has a low active ecosystem.

It has 8 star(s) with 9 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1260 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of football_data is current.

Quality

football_data has no bugs reported.

Security

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

License

football_data 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

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

football_data has no build file. You will be need to create the build yourself to build the component from source.

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football_data Key Features

No Key Features are available at this moment for football_data.

football_data Examples and Code Snippets

No Code Snippets are available at this moment for football_data.

Community Discussions

Trending Discussions on football_data

Python - argument passed through lambda function not retaining its state

Calculate percentage of SQL Group BY

Connect to Secured Elastic Search using java

Keras - how to predict two values instead of one value?

Keras predicts same result for any input

R: Group by 2 columns but only when 2nd column doesn't match

QUESTION

Python - argument passed through lambda function not retaining its state

Asked 2021-Apr-21 at 15:05

I have an module that produces the following form (using Python Tkinter):

As you can see the form could have three states:

Uneditable - entry boxes are disabled - Cancel and Edit button active
Editable with no changes - entry boxes are active, Cancel button and the Edit button becomes a disabled Save button and
Editable with changes - entry boxes are active, Cancel button becomes a revert button and the Save button becomes active

My code used to achieve this is as follows:

...

ANSWER

Answered 2021-Apr-21 at 13:41

Any change you do to a local variable, like _editable in make_editable_process, is only visible inside that function, so see that change outside, you need to either return it, save into some external to the function given mutable object (like those various button thing), or declare it as either global or nonlocal

For your case I think the nonlocal would suffice.

example

what you're experimenting is this

Source https://stackoverflow.com/questions/67196271

QUESTION

Calculate percentage of SQL Group BY

Asked 2021-Feb-04 at 13:00

The following SQL statement:

...

ANSWER

Answered 2021-Feb-04 at 12:51

You can use window functions, if I understand correctly:

Source https://stackoverflow.com/questions/66045981

QUESTION

Connect to Secured Elastic Search using java

Asked 2020-Feb-12 at 10:43

I want to connect with my secured ElasticSearch and load my index data and store it in the variable. I found RestHighLevelClient in java which helped me in connecting with elastic search.

Here's the Code:

...

ANSWER

Answered 2020-Feb-12 at 10:43

Created this by elastic search docs. You should refer them . For now do the following...

Source https://stackoverflow.com/questions/60182233

QUESTION

Keras - how to predict two values instead of one value?

Asked 2019-Sep-22 at 19:40

I'm learning machine learning and my dataset consists of 7 columns:

...

ANSWER

Answered 2019-Sep-22 at 19:40

Since you now want to predict scores, i.e. a continuous quantity (although integer), this is no more a classification problem but a regression one.

To do that, you need two changes in your existing model; the first is to modify your final layer to

Source https://stackoverflow.com/questions/58051767

QUESTION

Keras predicts same result for any input

Asked 2019-Sep-21 at 20:23

I'm learning machine learning and my dataset consists from 6 columns:

...

ANSWER

Answered 2019-Sep-21 at 20:23

The fact that you convert the first two columns (team names) to integers does not make any sense. This way you would be implying that teams that have similar IDs, such as 1146 and 1179, will perform similar and that teams with completely different IDs, such as 4 and 6542, would perform very differently. Usually this kind of data would be presented in a different manner or even excluded from the dataset.

I would exclude those columns in this case since the odds seem to contain all necessary data, I wouldn't even use neural networks for this but just compare the odds. However I understand that you want to use a simple dataset for learning purposes in which case only using the odds would be fine.

Mind though that the neural network will probably learn to assign the win to the team with the biggest odds of winning, like the following:

Source https://stackoverflow.com/questions/58043606

QUESTION

R: Group by 2 columns but only when 2nd column doesn't match

Asked 2018-Jun-07 at 21:09

I'm new to R (and dplyr) and I'm currently working with some seasonal football data and need some help. Currently if a player transfers to another club in the same league then the row of data and all metrics is simply duplicated but with a new team_id. However if the player transfers to another league then the metrics are split.

For consistency's sake I need to resolve this which means that I have to:

Group by player_id where comp_id does not match

(football regulations dictate that you can only play for a max. of 2 clubs in a season so this negates further complications and so this simple rule resolves everything)

so in other words if there are duplicates sum all rows but only if the comp_id differs

I was trying to do this in dplyr and was hoping that there would be some way of writing this such as:

...

ANSWER

Answered 2018-Jun-07 at 21:09

Essentially, you want to

get the player-level sum of the metric variables, grouped by comp
join them back into the full dataframe.

Source https://stackoverflow.com/questions/50749432

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

Vulnerabilities

No vulnerabilities reported

Install football_data

You can download it from GitHub.
You can use football_data 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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