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 pdimport matplotlib.pyplot as mp# take datadata = pd.read_csv("Bestsellers.csv")# form dataframedata = data.head()df = pd.DataFrame(data, columns=["Name", "Price", "User Rating"])# plot the dataframedf.plot(x="Name", y=["Price", "User Rating"], kind="bar", figsize=(9, 8))# print bar graphmp.show() |
Output:
Example 2:
Python3
import pandas as pdimport matplotlib.pyplot as mp# data to be plotteddata = [["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 datadf = pd.DataFrame(data, columns=["City", "Population(million)", "Year(2020)"])# plot multiple columns such as population and year from dataframedf.plot(x="City", y=["Population(million)", "Year(2020)"], kind="line", figsize=(10, 10))# display plotmp.show() |
Output:
