chartify | Python library that makes it easy for data scientists | Data Visualization library

 by   spotify Python Version: 4.0.5 License: Apache-2.0

kandi X-RAY | chartify Summary

kandi X-RAY | chartify Summary

chartify is a Python library typically used in Analytics, Data Visualization applications. chartify has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can install using 'pip install chartify' or download it from GitHub, PyPI.

Python library that makes it easy for data scientists to create charts.
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            kandi-support Support

              chartify has a highly active ecosystem.
              It has 3345 star(s) with 304 fork(s). There are 87 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 43 open issues and 31 have been closed. On average issues are closed in 80 days. There are 6 open pull requests and 0 closed requests.
              OutlinedDot
              It has a negative sentiment in the developer community.
              The latest version of chartify is 4.0.5

            kandi-Quality Quality

              chartify has 0 bugs and 0 code smells.

            kandi-Security Security

              chartify has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              chartify code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              chartify is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              chartify releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              chartify saves you 2392 person hours of effort in developing the same functionality from scratch.
              It has 5346 lines of code, 363 functions and 26 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed chartify and discovered the below as its top functions. This is intended to give you an instant insight into chartify implemented functionality, and help decide if they suit your requirements.
            • Draw a scatter plot
            • Return a DataSource for the named column
            • Generate aannonical series name
            • Determines the color order of the data
            • Draw a line
            • Set the default format
            • Cast datetime to datetime
            • Convert hl to RGB
            • Convert from Hue to RGB
            • Convert a hexadecimal hexadecimal representation to a string
            • Convert hexadecimal to rgb
            • Show chart layout
            • Plot a categorical color palette type
            • Plot a color palette
            • Create a custom color palette
            • Plot examples
            • Convert hexadecimal to rgb
            • Generate example data
            • Display the figure
            • Style the color palette
            • Convert an RGB value to HSL
            • Convert web color to hex
            • Compute the area of a dataframe
            • Draws a line
            • Plots the radial radius chart
            • Return an RGB color from an object
            • Returns a DataFrame with the styling of the color palette
            Get all kandi verified functions for this library.

            chartify Key Features

            No Key Features are available at this moment for chartify.

            chartify Examples and Code Snippets

            No Code Snippets are available at this moment for chartify.

            Community Discussions

            QUESTION

            JavaScript canvas pie chart warping issue
            Asked 2022-Apr-08 at 01:47

            I am trying to create a custom HTML element that allows me to create pie charts easily. I have been very successful so far except for the fact that I cant seem to get the actual canvas drawing to be proportioned correctly.

            ...

            ANSWER

            Answered 2022-Apr-08 at 01:47

            The canvas element has default values for its height and width attributes of 150 and 300, respectively. If you need your canvas to be square, you need to specify these sizes to be the same.

            This example tweaks your el_width variable to read the width off the canvas directly, instead of using getBoundingClientRect. I've also tweaked the way the canvas element is created so it has width and height attributes, and its 100% width and height styles are set via CSS:

            Source https://stackoverflow.com/questions/71790600

            QUESTION

            Chartify: how to pass a Selenium WebDriver?
            Asked 2020-Jan-30 at 20:03

            The following example should work, but it requires the selenium package (as I understand, under the hood chartify builds an interactive chart using the bokeh package and takes a screenshot with selenium)

            ...

            ANSWER

            Answered 2020-Jan-30 at 20:03

            It looks like they have hardcoded the creation and configuration of the webdriver in a Chart method _initialize_webdriver.

            If you want something different than what they do, I think monkey-patching the Chart. _initialize_webdriver method to override it is the only current option. It might be worth opening a issue on their GH tracker to discuss adding the ability to customize webdriver creation.

            Source https://stackoverflow.com/questions/59993549

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

            Vulnerabilities

            No vulnerabilities reported

            Install chartify

            You can install using 'pip install chartify' or download it from GitHub, PyPI.
            You can use chartify 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 .
            Find more information at:

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            Install
          • PyPI

            pip install chartify

          • CLONE
          • HTTPS

            https://github.com/spotify/chartify.git

          • CLI

            gh repo clone spotify/chartify

          • sshUrl

            git@github.com:spotify/chartify.git

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