How to generate BAR plot using Pandas DataFrame in Python

A bar plot is a way to visualize data using rectangular bars. The length of each bar represents the value of the data. In Python, you can use the Pandas library to create a bar plot.

First, you’ll need to install Pandas if you don’t already have it. You can do this by running pip install pandas in your command line.

Next, you’ll need to import the Pandas library and load your data into a DataFrame. A DataFrame is a two-dimensional table that can hold data in a tabular format. You can load data from a CSV file, for example, by using the read_csv() function.

Once you have your data in a DataFrame, you can use the plot() function to create a bar plot. The plot() function takes several parameters, but the most important one is kind, which tells it what kind of plot to create. To create a bar plot, you’ll set kind to “bar”.

Here is an example of how to create a bar plot using Pandas:

import pandas as pd 
df = pd.read_csv("data.csv")

The above code will create a bar plot using the data in the “data.csv” file and display it on the screen. By default, the plot function will use the DataFrame’s index for the x-axis and the columns as individual bars, however you can modify the X, Y and legend labels as per your data.

You can also modify the look of the plot by passing additional parameters to the plot() function. For example, you can change the color of the bars or add a title to the plot.

By using the above steps, you can easily generate bar plots using Pandas DataFrame in Python.

In this Learn through Codes example, you will learn: How to generate BAR plot using Pandas DataFrame in Python.