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ydata-profiling download for Windows

Free download ydata-profiling Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named ydata-profiling whose latest release can be downloaded as v4.6.0.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named ydata-profiling with OnWorks for free.

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- 1. Downloaded this application in your PC.

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- 3. Upload this application in such filemanager.

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- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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ydata-profiling


DESCRIPTION

ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json.



Features

  • Automatic detection of columns’ data types (Categorical, Numerical, Date, etc.)
  • A summary of the problems/challenges in the data that you might need to work on (missing data, inaccuracies, skewness, etc.)
  • Descriptive statistics (mean, median, mode, etc) and informative visualizations such as distribution histograms
  • Correlations, a detailed analysis of missing data, duplicate rows, and visual support for variables pairwise interaction
  • Different statistical information relative to time dependent data such as auto-correlation and seasonality, along ACF and PACF plots
  • Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic)


Programming Language

Python


Categories

Data Quality

This is an application that can also be fetched from https://sourceforge.net/projects/ydata-profiling.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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