Add the Overall Title Above All Subplots
Description:
This program creates a figure with three vertically arranged subplots for Sales, Revenue, and Units Sold, and adds a main title above all subplots using plt.suptitle().
Code Explanation:
-
We have 3 types of data: Sales, Revenue, and Units Sold.
-
We use
plt.subplots()to create 3 stacked plots. -
Each subplot shows a different line graph for each metric.
-
plt.suptitle()adds one big title on top of all subplots — like a headline. -
plt.tight_layout(rect=[0, 0, 1, 0.95])keeps spacing clean and avoids overlap with the main title. -
It's useful when you want to summarize multiple plots under one main topic.
Program:
import matplotlib.pyplot as plt
import pandas as pd
# Sample data
data = {
'Date': pd.date_range(start='2024-01-01', periods=7, freq='D'),
'Sales': [100, 120, 90, 140, 160, 130, 150],
'Revenue': [1000, 1500, 1200, 1800, 2000, 1700, 1900],
'Units': [10, 12, 9, 14, 16, 13, 15]
}
df = pd.DataFrame(data)
# Create subplots
fig, axs = plt.subplots(3, 1, figsize=(10, 8), sharex=True)
# Plot each metric
axs[0].plot(df['Date'], df['Sales'], color='blue', marker='o')
axs[0].set_title('Sales Over Time')
axs[1].plot(df['Date'], df['Revenue'], color='green', marker='s')
axs[1].set_title('Revenue Over Time')
axs[2].plot(df['Date'], df['Units'], color='red', marker='^')
axs[2].set_title('Units Sold Over Time')
# Rotate x-axis labels
plt.xticks(rotation=45)
# Add overall title
plt.suptitle('Business Metrics Over Time', fontsize=16, fontweight='bold')
# Adjust layout
plt.tight_layout(rect=[0, 0, 1, 0.95]) # Leave space for the suptitle
# Show the plot
plt.show()
Output:
