Group and Plot Quarterly Sales
Description:
This code groups daily sales data into quarters and plots the total sales per quarter using a bar chart.
Code Explanation:
-
A list of sales is spread across 6 months (approx. 2 quarters).
-
The data is grouped into quarters (Jan–Mar = Q1, Apr–Jun = Q2, etc.).
-
We sum sales in each quarter using
resample('Q'). -
A bar chart shows how each quarter's total sales compare.
-
It helps to identify seasonal trends and performance across time.
Program:
import pandas as pd
import matplotlib.pyplot as plt
# Sample sales data over multiple months
data = {
'Date': pd.date_range(start='2024-01-01', periods=180, freq='D'),
'Sales': [100 + i % 30 for i in range(180)] # Simulated sales data
}
df = pd.DataFrame(data)
# Convert date to datetime and set as index
df['Date'] = pd.to_datetime(df['Date'])
df.set_index('Date', inplace=True)
# Group by quarter and calculate total sales
quarterly_sales = df.resample('Q').sum()
# Plot
plt.figure(figsize=(8, 5))
plt.bar(quarterly_sales.index.strftime('%Y-Q%q'), quarterly_sales['Sales'], color='skyblue')
# Formatting
plt.title('Quarterly Sales')
plt.xlabel('Quarter')
plt.ylabel('Total Sales')
plt.grid(axis='y')
plt.tight_layout()
# Show the plot
plt.show()
Output:
