Creating Charts Using Matplotlib

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

Bar Plot of Radish Votes:
Let's see how to generate bar plot of the data.We will display the individual counts of radish variety across the 

data.

 matplotlib to generate a bar graph

import matplotlib.pyplot as plth 

matplotlib can also output charts in other formats like image files.

plt.bar(range(len(counts)), counts.values(), align='center')

Bar code : Use below python code to generate bar Graph to display the vote counts from the radish variety program
plt.show()

Here the graph with no information of x and y axis is of no use, So to label x-axis and y-axis from which we can extract the information or observations

plt.ylabel(s = "Votes")
plt.xticks(range(len(counts)), counts.keys(),rotation=90)

We create a range of indexes for the X values in the graph, one entry for each entry in the "counts" dictionary (ie len(counts)), numbered 0,1,2,3,etc.This will spread out the graph bars evenly across the X axis on the plot.

np.arange is a NumPy function like the range() function in Python, only the result it produces is a "NumPy array".

plt.xticks() specifies a range of values to use as labels ("ticks") for the X axis.

x + 0.5 is a special expression because x is a NumPy array. NumPy arrays have some special capabilities that normal lists orrange() objects don't have.

The above part is from opentechschool.python tutorial.

Reference : http://opentechschool.github.io/python-data-intro/core/charts.html