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
- Create line plots
- Make bar charts
- Plot histograms
- 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.