10 Python Libraries For Data Visualization

• gleam

  1 249 0.0 JavaScript

  Creating interactive visualizations with Python (by dgrtwo)

gleam The gleam library is similar to the R’s Shiny package. It converts analyses into interactive web apps using Python scripts. It creates a web interface that lets anyone play with the data in real-time. One interesting capability of this library is that fields can be created on top of the graphic and users can filter and sort data by choosing appropriate fields. Download here > gleam

• seaborn

  76 11,958 8.4 Python

  Statistical data visualization in Python

seaborn The seaborn library couples the power of the Matplotlib library to create artistic charts with very few lines of code. The seaborn library follows creative styles and rich color palettes, which allows you to create visualization plots to be more attractive and modern. Today’s visualization graph is mainly plotted in seaborn rather than Matplotlib, primarily because of the seaborn library’s rich color palettes and graphic styles that are much more stylish and sophisticated than Matplotlib. As seaborn is considered to be a higher-level library, there are certain special visualization tools such as violin plots, heat maps, and time series plots that can be created using this library. Download here > seaborn

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• missingno

  5 3,771 1.9 Python

  Missing data visualization module for Python.

missingno The missingno library can deal with missing data and can quickly measure the wholeness of a dataset with a visual summary, instead of managing through a table. The data can be filtered and arranged based on completion or spot correlations with a dendrogram or heatmap. Download here > missingno

• cheatsheets

  126 7,238 7.0 Python

  Official Matplotlib cheat sheets (by matplotlib)

  

Matplotlib The Matplotlib is the most common standard Python library used for plotting 2D data visualizations. This library was created by John D. Hunter and is currently maintained by a team of Python developers. The Matplotlib library is mainly used for creating plots that can be zoomed in on a section of the plot and pan around the plot using the toolbar in the plot window. It is the first data visualization library to be developed in Python, and later many other libraries were built on top of it for various other ways of visualizations. This library is used to create a variety of visualization graphs such as line plots, pie charts, scatter plots, bar charts, histograms, stem plots, and spectrograms. The Matplotlib allows easy use of labels, axes titles, grids, legends, and other graphic requirements with customizable values and text. Download here > Matplotlib

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