Data Visualization in Python

visualization with Pandas, Matplotlib and Seaborn

Line Plot:

In Matplotlib we can create a line chart by calling the plot method. We can also plot multiple columns in one graph, by looping through the columns we want and plotting each column on the same axis.

import matplotlib.pyplot as plt
 
x  = [1, 2, 3, 4, 5, 6, 7, 8, 9]
y1 = [1, 3, 5, 3, 1, 3, 5, 3, 1]
y2 = [2, 4, 6, 4, 2, 4, 6, 4, 2]
plt.plot(x, y1, label="line L")
plt.plot(x, y2, label="line H")
plt.plot()
plt.grid()

plt.xlabel("x axis")
plt.ylabel("y axis")
plt.title("Line Graph Example")
plt.legend()
plt.show()

Histogram

import numpy as np
import matplotlib.pyplot as plt
x=np.random.randn(1000)
plt.hist(x,bins=range(-4,5))
plt.xlabel('x values')
plt.title('histogram example ')
plt.grid()
plt.show()

Bar Chart

import matplotlib.pyplot as plt

# Look at index 4 and 6, which demonstrate overlapping cases.
x1 = [1, 3, 4, 5, 6, 7, 9]
y1 = [4, 7, 2, 4, 7, 8, 3]

x2 = [2, 4, 6, 8, 10]
y2 = [5, 6, 2, 6, 2]

plt.bar(x1, y1, label="Blue Bar", color='b')
plt.bar(x2, y2, label="Green Bar", color='g')
plt.plot([8,-8],[0,0],'h--')#k-- to print the x -axis in dashed,otherwise line
plt.plot([0,0],[8,-8],'y--')
plt.axis((-8,8,-8,8))# x-axis negative,x-axis positive,y-axis -ve,y-axis +ve


plt.plot()
plt.xlabel("bar number")
plt.ylabel("bar height")
plt.title("Bar Chart Example")
plt.legend()
plt.show()

Scatter Plot