https://github.com/ranish-shrestha/sales_data_analysis
Sales data analysis using Python.
https://github.com/ranish-shrestha/sales_data_analysis
data-analysis-python python-project
Last synced: 2 months ago
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Sales data analysis using Python.
- Host: GitHub
- URL: https://github.com/ranish-shrestha/sales_data_analysis
- Owner: Ranish-Shrestha
- Created: 2024-11-07T02:33:13.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2024-11-07T03:02:57.000Z (about 1 year ago)
- Last Synced: 2025-01-24T22:47:32.828Z (11 months ago)
- Topics: data-analysis-python, python-project
- Language: Jupyter Notebook
- Homepage:
- Size: 556 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Sales Data Analysis
This project is an exploratory analysis of Diwali sales data, using Python libraries such as Pandas, Matplotlib, and Seaborn to analyze and visualize trends based on various factors like gender.
### Project Overview
This analysis aims to identify sales patterns during the Diwali season, with a particular focus on understanding how different demographics contribute to overall sales. Through data cleaning, transformation, and visualization, the project provides insights into consumer behavior by Gender, Age, State, Marital Status, Occupation, and Product Category.
### Requirements
Install following Python libraries to run the code:
- `numpy`
- `pandas`
- `matplotlib`
- `seaborn`
To install these dependencies, use the following command:
```sh
pip install numpy pandas matplotlib seaborn
```
### Usage
To run the code, load the `Diwali Sales Data.csv` file into the same directory as your script, then execute the script in a Jupyter notebook or your preferred Python environment.
### Conclusion
This analysis provides insights into consumer behavior based on gender, age, states and occupation during the Diwali season. It can guide marketing and sales strategies by highlighting which demographics contribute more significantly to sales.