How to plot multiple data columns in a DataFrame?

Prerequisites: Pandas

Python comes with a lot of useful packages such as pandas, matplotlib, numpy etc. To use dataframe, we need pandas library and to plot columns of a dataframe, we require matplotlib. Pandas has a tight integration with Matplotlib. You can plot data directly from your DataFrame using the plot() method. 

To plot multiple data columns in single frame we simply have to pass the list of columns to the y argument of the plot function. Given below is aproper approach to do so along with example implementation.

Approach:

• Import module
• Create or load data
• Convert to dataframe
• Using plot() method, specify a single column along X-axis and multiple columns as an array along Y-axis.
• Display graph.

Below are few examples which illustrates the above approach to plot multiples data columns in a Dataframe.

Example 1:

Database: Bestsellers

Python3

import pandas as pd
import matplotlib.pyplot as mp

# take data
data = pd.read_csv("Bestsellers.csv")

# form dataframe
data = data.head()

df = pd.DataFrame(data, columns=["Name", "Price", "User Rating"])

# plot the dataframe
df.plot(x="Name", y=["Price", "User Rating"], kind="bar", figsize=(9, 8))

# print bar graph
mp.show()

Output:

Example 2:

Python3

import pandas as pd
import matplotlib.pyplot as mp

# data to be plotted
data = [["New York", 8.6, 20],
        ["Chicago", 2.7, 20],
        ["Los Angeles", 3.9, 20],
        ["Philadelphia", 1.5, 20],
        ["Houston", 2.1, 20]]

# form dataframe from data
df = pd.DataFrame(data, columns=["City", "Population(million)", "Year(2020)"])

# plot multiple columns such as population and year from dataframe
df.plot(x="City", y=["Population(million)", "Year(2020)"],
        kind="line", figsize=(10, 10))

# display plot
mp.show()

Output: