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Pandas lessons (30/42)

Pandas — Visualization

Basic plots

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

# Line plot
df.plot()
plt.show()

# Bar plot
df.plot(kind='bar')
plt.show()

# Scatter
df.plot.scatter(x='A', y='B')
plt.show()

Histogram

df['A'].hist()
plt.show()

Box plot

df.boxplot()
plt.show()

Customize

df.plot(title='My Plot', xlabel='X', ylabel='Y', figsize=(10, 6))
plt.show()

Mini Practice

  1. Create line plots
  2. Make bar charts
  3. Plot histograms
  4. Customize plots

Up Next

Continue with Style - DataFrame styling.

Related Topics

Frequently Asked Questions about Visualization

What is Visualization in Pandas?

Visualization is a fundamental concept in Pandas. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn Visualization?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn Visualization.

Why is Visualization important in Pandas?

Visualization is essential for Pandas development. Understanding this concept will help you write better code and solve real-world problems more effectively.