Bar Chart using Python with pandas and matplotlib (Data Science)

Gradient Blur Hot Pink Oval Illustration Orange Blur Circle Illustration 3D Gradients Oversaturated Rainbow Color 3D Gradients Oversaturated Rainbow Color Generate a bar chart or histogram to visually represent the distribution of a categorical or continuous variable, such as the age distribution or gender composition within a population. This graphical representation offers a clear and insightful overview of the data’s patterns and trends.

Dataset : https://www.kaggle.com/datasets/abhishekvermasg1/support-vector-machine-svm

Steps:

Let’s say we want to visualize the distribution of the target variable “Personal Loan” in this SVM dataset.

Here’s how you can do it using Python with pandas and matplotlib:

```python
import pandas as pd
import matplotlib.pyplot as plt

# Load the dataset
data = pd.read_csv(“support-vector-machine-svm/UniversalBank.csv”)

# Plot the distribution of the ‘Personal Loan’ variable (target variable)
plt.figure(figsize=(8, 6))
data[‘Personal Loan’].value_counts().plot(kind=’bar’, color=[‘skyblue’, ‘salmon’])
plt.title(‘Distribution of Personal Loan (Class)’)
plt.xlabel(‘Personal Loan’)
plt.ylabel(‘Count’)
plt.xticks([0, 1], [‘Not Taken’, ‘Taken’], rotation=0)
plt.show()
```

This code will generate a bar chart showing the distribution of the “Personal Loan” variable in the dataset, indicating how many individuals have taken or not taken a personal loan.

Make sure to adjust the column names and visualization parameters according to your specific dataset and requirements. Let me know if you need further assistance!

@ByteUprise