AISSCE-2024-25
INFORMATICS PRACTICES PROJECT FILE
Sales Data Analysis System
Submitted To: Mr. A.B. Teacher
Submitted By: Student Name
Class: 12th C
Roll No: 15
Preface
This project explores the analysis of sales data using Python's Pandas and Matplotlib
libraries. It aims to demonstrate the power of data manipulation and visualization for
decision-making.
Introduction
The 'Sales Data Analysis System' is designed to analyze sales performance data. It processes
and visualizes sales trends, helping businesses understand patterns and make informed
decisions.
Objective of the Project
The primary objectives of this project are:
1. To explore sales data using Python.
2. To demonstrate data manipulation using Pandas.
3. To visualize trends using Matplotlib.
Scope of the Project
This project focuses on providing insights into sales performance by analyzing historical
data. It is useful for businesses to optimize their strategies based on data-driven decisions.
Existing System
The existing system relies on manual analysis of sales data, which is time-consuming and
prone to errors.
Proposed System
The proposed system automates sales data analysis, providing quick and accurate insights
using Python.
Input/Output Requirements
Input: CSV file containing sales data.
Output: Graphs and tables representing trends and insights.
System Design
The system is designed to read a CSV file, process data using Pandas, and visualize results
using Matplotlib.
Tables and Fields
Fields in the dataset:
1. Product ID
2. Category
3. Sales
4. Quantity
5. Region
Source Code
import pandas as pd
import matplotlib.pyplot as plt
# Load dataset
df = pd.read_csv('SalesData.csv')
# Display all records
print(df)
# Analyze total sales by category
category_sales = df.groupby('Category')['Sales'].sum()
print(category_sales)
# Plot sales by region
plt.bar(df['Region'], df['Sales'])
plt.title('Sales by Region')
plt.xlabel('Region')
plt.ylabel('Sales')
plt.show()
Output Screens
The following output graphs represent sales data analysis.
Conclusion
This project demonstrates the effectiveness of Python in analyzing and visualizing data. The
'Sales Data Analysis System' successfully identifies sales trends and aids decision-making.
References/Bibliography
1. https://pandas.pydata.org/
2. https://matplotlib.org/
