Create a Line Chart for Monthly Sales
Description:
This program visualizes monthly sales trends using a line chart by processing and plotting daily sales data from sample order records.
Code Explanation:
● Created a DataFrame from the sample order data.
● Converted the 'Date' column to datetime format for proper time-based grouping.
● Calculated a new column 'Sales' by multiplying Quantity and Price.
● Grouped the data by 'Date' and summed the Sales to get daily total sales.
● Used plt.plot() to create a line chart showing daily sales trend.
● Added labels, grid, and layout adjustments for better readability.
Program:
import matplotlib.pyplot as plt
import pandas as pd
# Sample data
data = {
'OrderID': [101, 102, 103, 104],
'Product': ['Laptop', 'Tablet', 'Smartphone', 'Headphones'],
'Quantity': [2, 5, 3, 10],
'Price': [750, 300, 500, 50],
'Date': ['2025-01-01', '2025-01-01', '2025-01-02', '2025-01-02']
}
# Create DataFrame
df = pd.DataFrame(data)
# Convert 'Date' to datetime format
df['Date'] = pd.to_datetime(df['Date'])
# Calculate total sales per order
df['Sales'] = df['Quantity'] * df['Price']
# Group by date and sum sales
sales_per_day = df.groupby('Date')['Sales'].sum()
# Plotting the line chart
plt.figure(figsize=(8, 5))
plt.plot(sales_per_day.index, sales_per_day.values, marker='o', linestyle='-', color='blue')
plt.title('Daily Sales Line Chart')
plt.xlabel('Date')
plt.ylabel('Total Sales')
plt.grid(True)
plt.tight_layout()
plt.show()
Output:
