Data Visualization: Visualizing the data is crucial for uncovering patterns and relationships. Pandas integrates well with popular data visualization libraries like Matplotlib and Seaborn. We can use functions like plot(), bar(), scatter(), and heatmap() to create insightful visualizations.

# Plotting line chart
data.plot(x='x_column', y='y_column')
plt.show()

# Creating a bar plot
data['column'].value_counts().plot(kind='bar')
plt.show()

# Generating a scatter plot
data.plot.scatter(x='x_column', y='y_column')
plt.show()

# Creating a heatmap
sns.heatmap(data.corr(), annot=True)
plt.show()