Machine-Learning Python Data Analysis / Data Visualization

Back

1. DataVisualization

A Github Repository Where you can Learn Datavisualizatoin Basics to Intermediate level.

2. Cartopy

Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.

3. SciPy

A Python-based ecosystem of open-source software for mathematics, science, and engineering.

4. NumPy

A fundamental package for scientific computing with Python.

5. AutoViz

6. Numba

Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.

7. Mars

A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.

8. NetworkX

A high-productivity software for complex networks.

9. igraph

General purpose graph library.

10. Pandas

A library providing high-performance, easy-to-use data structures and data analysis tools.

11. ParaMonte

A general-purpose Python library for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found [here](https://www.cdslab.org/paramonte/).

12. PyMC

Markov Chain Monte Carlo sampling toolkit.

13. zipline

A Pythonic algorithmic trading library.

14. PyDy

Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.

15. SymPy

A Python library for symbolic mathematics.

16. statsmodels

Statistical modeling and econometrics in Python.

17. astropy

A community Python library for Astronomy.

18. matplotlib

A Python 2D plotting library.

19. bokeh

Interactive Web Plotting for Python.

20. plotly

Collaborative web plotting for Python and matplotlib.

21. altair

A Python to Vega translator.

22. d3py

A plotting library for Python, based on [D3.js](https://d3js.org/).

23. PyDexter

Simple plotting for Python. Wrapper for D3xterjs; easily render charts in-browser.

24. ggfortify

Unified interface to ggplot2 popular R packages.

25. Kartograph.py

Rendering beautiful SVG maps in Python.

26. pygal

A Python SVG Charts Creator.

27. PyQtGraph

A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.

28. Petrel

Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python.

29. Blaze

NumPy and Pandas interface to Big Data.

30. emcee

The Python ensemble sampling toolkit for affine-invariant MCMC.

31. windML

A Python Framework for Wind Energy Analysis and Prediction.

32. vispy

GPU-based high-performance interactive OpenGL 2D/3D data visualization library.

33. SparklingPandas

34. Seaborn

A python visualization library based on matplotlib.

35. bqplot

An API for plotting in Jupyter (IPython).

36. pastalog

Simple, realtime visualization of neural network training performance.

37. Superset

A data exploration platform designed to be visual, intuitive, and interactive.

38. Dora

Tools for exploratory data analysis in Python.

39. Ruffus

Computation Pipeline library for python.

40. SOMPY

Self Organizing Map written in Python (Uses neural networks for data analysis).

41. somoclu

42. HDBScan

used for clustering

43. scikit-plot

A visualization library for quick and easy generation of common plots in data analysis and machine learning.

44. Bowtie

A dashboard library for interactive visualizations using flask socketio and react.

45. lime

Lime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.

46. PyCM

PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters

47. Dash

A framework for creating analytical web applications built on top of Plotly.js, React, and Flask

48. Lambdo

A workflow engine for solving machine learning problems by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation via user-defined (Python) functions.

49. TensorWatch

Debugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training.

50. dowel

A little logger for machine learning research. Output any object to the terminal, CSV, TensorBoard, text logs on disk, and more with just one call to `logger.log()`.