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. Install pandas now!
pandas - Python Data Analysis Library
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. Install pandas now!
Indicating the statistically significant difference in bar graph
I use a bar graph to indicate the data of each group. Some of these bars differ significantly from each other. How can I indicate the significant difference in the bar plot? import numpy as np import matplotlib.pyplot as plt menMeans = (5, 15, 30, 40) menStd = (2, 3, 4, 5) ind = np.arange(4) # the x locations for the groups width=0.35 p1 = plt.bar(ind, menMeans, width=width, color='r', yerr=menStd
Plotly
Plotly Open Source Graphing Library for Python Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts. Plotly.py is free and open source and you can view the source, report issues or contribute on
Example gallery — seaborn 0.13.2 documentation
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How to make beautiful data visualizations in Python with matplotlib | Dr. Randal S. Olson
Published on June 28, 2014 by Dr. Randal S. Olson graphic design matplotlib python tutorial visualization 14 min READ Want to learn more about data visualization with Python? Take a look at my Data Visualization Basics with Python video course on O'Reilly. It's been well over a year since I wrote my last tutorial, so I figure I'm overdue. This time, I'm going to focus on how you can make beautiful
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patsy - Describing statistical models in Python — patsy 0.5.1+dev documentation
statsmodels
http://seaborn.pydata.org/introduction.html
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