wetterdienst | Open weather data for humans | Predictive Analytics library

by earthobservations Python Version: 0.81.0 License: MIT

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

kandi X-RAY | wetterdienst Summary

wetterdienst is a Python library typically used in Travel, Transportation, Logistics, Analytics, Predictive Analytics applications. wetterdienst has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However wetterdienst build file is not available. You can install using 'pip install wetterdienst' or download it from GitHub, PyPI.

Open weather data for humans.

Support

Quality

Security

License

Reuse

Support

wetterdienst has a low active ecosystem.

It has 266 star(s) with 41 fork(s). There are 9 watchers for this library.

There were 10 major release(s) in the last 6 months.

There are 15 open issues and 207 have been closed. On average issues are closed in 201 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of wetterdienst is 0.81.0

Quality

wetterdienst has 0 bugs and 0 code smells.

Security

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

wetterdienst code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

wetterdienst is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

wetterdienst releases are available to install and integrate.

Deployable package is available in PyPI.

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

Top functions reviewed by kandi - BETA

kandi has reviewed wetterdienst and discovered the below as its top functions. This is intended to give you an instant insight into wetterdienst implemented functionality, and help decide if they suit your requirements.

Get all values for a given provider
Parse an enumeration from a template
Return an instance of the given provider
Returns a Wetter instance
Collect parameter data for a given station
Create a DataFrame containing the file index for a given dataset
Get the date ranges for the given station
Fix timestamps in a DataFrame
Returns a pandas dataframe of all available cache entries
Fetch all stations for a given parameter
Render a station map
Render a status response
Command line interface
Returns a pandas DataFrame with all available stations
Creates the heat plot
Returns a pandas DataFrame of all available stations
Parse parameter
List stations
Return a dataframe for a given station
Discovers the given filters
Creates a plot of hohenpeissenberg damping
Adjust datetimes
Fetch data from API
Generate a mosmix test
Create map of weather stations
Extract data from the time series

Get all kandi verified functions for this library.

wetterdienst Key Features

No Key Features are available at this moment for wetterdienst.

wetterdienst Examples and Code Snippets

No Code Snippets are available at this moment for wetterdienst.

Community Discussions

Trending Discussions on Predictive Analytics

will TensorFlow utilize GPU for predictive Analysis?

Restructuring Pandas Dataframe for large number of columns

Display data from two json files in react native

QUESTION

will TensorFlow utilize GPU for predictive Analysis?

Asked 2020-Nov-21 at 21:35

GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?

note: predictive Analysis requires no graphics processing.

...

ANSWER

Answered 2020-Nov-21 at 21:35

The short answer: yes, it will! The slightly longer answer:

The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.

The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.

If you want to know more about this, I'd recommend you start here or here.

some things to consider:

how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.

Source https://stackoverflow.com/questions/64948197

QUESTION

Restructuring Pandas Dataframe for large number of columns

Asked 2020-Nov-01 at 19:39

I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.

The current structure is as below.

What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):

Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.

...

ANSWER

Answered 2020-Nov-01 at 19:39

You might want try pivoting your table:

Source https://stackoverflow.com/questions/64630691

QUESTION

Display data from two json files in react native

Asked 2020-May-17 at 23:55

I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files

...

ANSWER

Answered 2020-May-17 at 23:55

The new object to get params in React Navigation 5 is:

Source https://stackoverflow.com/questions/61859411

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

Vulnerabilities

No vulnerabilities reported

Install wetterdienst

You can install using 'pip install wetterdienst' or download it from GitHub, PyPI.
You can use wetterdienst 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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