In this Python data visualization tutorial we learn how to make scatter plots in Python.
We will specifically use Pandas scatter to create a scatter plot. However, Pandas method for creating scatter plots are a bit limited.
We will therefore continue the visualization tutorial by using the Seaborn library. This library works very good together with Pandas dataframes and have, at least, two methods that enables us to make a scatter plot in Python.
First, we will use regplot (sns.regplot()) to create a simple scatter plot. Second, we will use lmplot (sns.lmplot()) to create a scatter plot in which we can group the data. This comes handy when we may want to plot different regression lines and, thus, relationships that we may expect.
Data visualization using Seaborn will also enable us to change the markers, the color on the plot, and many more. That is, in a very easy way.
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» Pandas Scatter Method Documentation:
http://pandas.pydata.org/pandas-docs/...
» Seaborn regplot documentation:
https://seaborn.pydata.org/generated/...
» Seaborn lmplot documentation:
https://seaborn.pydata.org/generated/...
» Check this Color Palettes tutorial if you want to play around with the colors on your Seaborn plots:
https://seaborn.pydata.org/tutorial/c...
» A working Jupyter Notebook containing the code:
http://bit.ly/pythonscatterplot
» Learn how to install Pandas:
• How to Call R from Python - an Rpy2 Tutorial
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