AutoViz performs automatic visualization of any dataset with a single line of Python code. Give it any input file (CSV, txt or json) of any size and AutoViz will visualize it.
https://t.co/bywRcRK6xD
College completely failed to teach me data analysis.
So I spent over 10,000 hours learning Python.
Then, I picked the 13 best libraries for machine learning and data analysis.
But unlike college, these won't cost you $120,000.
Here they are for free:
AutoViz performs automatic visualization of any dataset with a single line of Python code. Give it any input file (CSV, txt or json) of any size and AutoViz will visualize it.
https://t.co/bywRcRK6xD
Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN.
https://t.co/ZwldyKWfeb
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
https://t.co/wE5NyoN66G
pandas is a fast, powerful, flexible, and easy-to-use open source data analysis and manipulation tool, built on top of the Python programming language.
https://t.co/u92fVCtMtJ
Vaex is a high-performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets.
https://t.co/Vm9sIvG8pm
PyMC is a Python package for Bayesian statistical modeling focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.
https://t.co/52rGR8w2SF
statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models.
https://t.co/uui7vu0abv
Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.
https://t.co/09unmJ9ecq
Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar interface to query data living in other data storage systems.
https://t.co/walSiZp230
SparklingPandas aims to make it easy to use the distributed computing power of PySpark to scale your data analysis with Pandas. SparklingPandas builds on Spark's DataFrame class to give you a polished, pythonic, and Pandas-like API.
https://t.co/wMqx1FR83a
Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.
https://t.co/EhyiJEfLzr
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.
https://t.co/m29qsogDTt
Built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical Python code.
https://t.co/xVke1X4O62
Learn Python:
• Vaex
• Blaze
• PyMC
• bokeh
• PyCM
• Numba
• AutoViz
• pandas
• Superset
• NetworkX
• Plotly Dash
• statsmodels
• SparklingPandas
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College completely failed to teach me data analysis.
— PyQuant News (@pyquantnews) July 14, 2022
So I spent over 10,000 hours learning Python.
Then, I picked the 13 best libraries for machine learning and data analysis.
But unlike college, these won't cost you $120,000.
Here they are for free:
More from PyQuant News
20 Python libraries for market data everyone should know:
googlefinance
Python module to get stock data from Google Finance API. This module provides no delay, real time stock data in NYSE &
Wallstreet
Wallstreet is a Python 3 library for monitoring and analyzing real time Stock and Option data. Quotes are provided from the Google Finance
yfinance
Data for stocks (historic, intraday, fundamental), FX, crypto, and options. Uses Yahoo Finance so any data available through Yahoo is available through
Stock Extractor
This package includes a series of stock data extractor class from a few widely used sources, such as Yahoo Finance, https://t.co/Bsoz2ROIiV,
googlefinance
Python module to get stock data from Google Finance API. This module provides no delay, real time stock data in NYSE &
Wallstreet
Wallstreet is a Python 3 library for monitoring and analyzing real time Stock and Option data. Quotes are provided from the Google Finance
yfinance
Data for stocks (historic, intraday, fundamental), FX, crypto, and options. Uses Yahoo Finance so any data available through Yahoo is available through
Stock Extractor
This package includes a series of stock data extractor class from a few widely used sources, such as Yahoo Finance, https://t.co/Bsoz2ROIiV,
