How to Plot Non-numeric Data in Python

In the world of data analysis, we often encounter situations where it is not just numbers, but we have to deal with non-numeric data, such as categories, text, or dates. This data introduces another layer of complexity and doesn’t lend itself easily to conventional numeric plotting techniques.

But with Python’s robust data manipulation libraries, this challenge can be effectively dealt with. Let’s delve into how Python can be used to visualize non-numeric data.

Step 1: Import Necessary Libraries

Firstly, we will need to import the necessary Python libraries. We will be using Pandas for data handling and Matplotlib and Seaborn for data visualization. The code block looks like this:

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

Step 2: Load Non-Numeric Data

Create a DataFrame containing non-numeric data using the pandas library. For this tutorial, we will be using a simple dataset with two categorical variables.

# Creating a sample DataFrame

data = {

'Product': ['Apple', 'Banana', 'Orange', 'Banana', 'Apple', 'Apple', 'Orange', 'Banana'],

'Quality': ['Good', 'Bad', 'Good', 'Good', 'Good', 'Bad', 'Bad', 'Good']

}

df = pd.DataFrame(data)

Your DataFrame (using

df.head()

) should look like:

  Product Quality
0   Apple    Good
1  Banana     Bad
2  Orange    Good
3  Banana    Good
4   Apple    Good

Step 3: Plotting the Data

For non-numeric data visualization, bar charts and box plots can be very helpful. We will plot our non-numeric data on a bar chart using the Seaborn library.

# Plotting data

sns.countplot(x='Product', hue='Quality', data=df)

plt.show()

Full Code

Here is the complete Python code: