ViTables | ViTables , a GUI for PyTables

by uvemas Python Version: 3.0.3 License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | ViTables Summary

ViTables is a Python library typically used in User Interface, Qt5 applications. ViTables has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install ViTables' or download it from GitHub, PyPI.

ViTables is a graphical tool for browsing and editing files in both PyTables and HDF5 format. With ViTables you can easily navigate through the data hierarchy, view and modify metadata, view actual data and more. ViTables has been developed using Python and PyQt, a binding to Qt libraries, so it should run on any platform that support these components (this includes Windows, Mac OS X, Linux and many other Unices). The interface and features are the same in all platforms. At the moment, ViTables has been heavily tested on Linux and Windows platforms. For installation instructions see INSTALL.txt. Feel free to subscribe to the ViTables users group [1]_ and to report bugs and send suggestions or features requests.

Support

Quality

Security

License

Reuse

Support

ViTables has a low active ecosystem.

It has 142 star(s) with 50 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 26 open issues and 55 have been closed. On average issues are closed in 283 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ViTables is 3.0.3

Quality

ViTables has 0 bugs and 0 code smells.

Security

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

ViTables code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ViTables is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

ViTables saves you 4932 person hours of effort in developing the same functionality from scratch.

It has 10392 lines of code, 609 functions and 112 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Launch a file save as dialog
Copy the file to the destination
Format exception information
Returns the opendb document for the given filepath
Fill the user attributes page
Export to CSV file
Gets the export info dialog
Adds an entry to the menu
Inserts entries in a menu
Add actions to the target widget
Paste the selected node
Removes all sessions from the database
Rename a node
Display information about ViTables dialog
Setup the UI
Parse the contents of a csv file
Convert csv file to csv
Customise the model
Create a table from csv file
Process command line arguments
Convert csv to EArray
Create new group
Set model data
Update the window menu
Drag the slider
Delete the user attribute

Get all kandi verified functions for this library.

ViTables Key Features

No Key Features are available at this moment for ViTables.

ViTables Examples and Code Snippets

No Code Snippets are available at this moment for ViTables.

Community Discussions

Trending Discussions on ViTables

Iteratively append pandas dataframes in a single group to h5 file

QUESTION

Iteratively append pandas dataframes in a single group to h5 file

Asked 2020-Apr-03 at 19:37

I have a small script meant to read csv files from a user input directory and convert them to a single HDF5 file:

...

ANSWER

Answered 2020-Apr-03 at 19:37

import glob
import os
import pandas as pd

# inputs
path = input('Insert the directory path:')
group = input('Insert a group name: ')

# create a list of file paths
file_list = [file for file in glob.glob(path)]
# dict comprehension to create keys from file name and values from the csv files
dfs = {os.path.basename(os.path.normpath(filename)).split('.')[0]: pd.read_csv(filename) for filename in file_list}

# loop though the dataframes
for k,df in dfs.items():
    # store the HDF5 file
    store = pd.HDFStore('test.h5')
    # append df to a group and assign the key with f-strings
    store.append(f'{group}/{k}', df, format='table', data_columns=df.columns)
    # close the file
    store.close()

Source https://stackoverflow.com/questions/61018053

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

Vulnerabilities

No vulnerabilities reported

Install ViTables

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