Visualizing a dataset by basic plotting

Plots are a great way to visualize a dataset and gauge possible relationships between the columns of a dataset. There are various kinds of plots that can be drawn. For example, a scatter plot, histogram, box-plot, and so on.

Let's import the Customer Churn Model dataset and try some basic plots:

import pandas as pd
data=pd.read_csv('E:/Personal/Learning/Predictive Modeling Book/Book Datasets/Customer Churn Model.txt')

While plotting any kind of plot, it helps to keep these things in mind:

• If you are using IPython Notebook, write % matplotlib inline in the input cell and run it before plotting to see the output plot inline (in the output cell).

• To save a plot in your local directory as a file, you can use the savefig method. Let's go back to the example where we plotted four scatter plots in a 2x2 panel. The name of this image is specified in the beginning of the snippet, as a figure parameter of the plot. To save this image one can write the following code...