Sales Analysis Dashboard

Sales Analysis Dashboard is a web-based data visualization project that aims to provide insights into a retail company's sales data. The main goal of the project is to help the company understand its sales performance, identify trends, and make data-driven decisions to improve profitability and customer satisfaction.

Features

• Interactive Dashboard: The project includes an interactive web-based dashboard that allows users to explore and analyze the sales data visually. Users can interact with different charts and graphs to gain deeper insights into the data.
• Sales by Category: The dashboard provides a breakdown of sales across different product categories. It helps the company identify which product categories are performing well and which ones may need improvement.
• Customer Segmentation: The project enables the company to analyze sales based on customer segments. By understanding the sales distribution across different customer types (e.g., corporate, consumer, home office), the company can tailor its marketing and sales strategies for different customer segments.
• Geographical Analysis: The dashboard includes a map visualization that displays sales data for different geographical regions. This helps the company identify potential target areas and analyze sales performance in different regions.

Technologies Used

• Python
• Pandas
• Plotly
• Dash (Python framework for building web applications)

Installation

1. Clone the repository:

git clone https://github.com/your_username/sales-analysis-dashboard.git

2. Install the required dependencies:

pip install pandas plotly dash

Usage

1. Navigate to the project directory:

cd sales-analysis-dashboard

2. Run the dashboard:

python app.py

3. Open a web browser and go to http://127.0.0.1:8050/ to access the dashboard.

IMPORTANT NOTE:

Since Github doesn't show the interactive map, this is what does it look like:

Code:

fig = px.choropleth_mapbox(df, geojson='https://raw.githubusercontent.com/python-visualization/folium/master/tests/us-states.json', 
                           locations='State', 
                           featureidkey="properties.name",
                           color='Sales',
                           color_continuous_scale="Viridis",
                           range_color=(0, 12),
                           mapbox_style="carto-positron",
                           zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
                           opacity=1,
                           labels={'Sales':'Sales'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

Data Source

The project uses a sample sales dataset that is included in the sales.xlsx file. The dataset contains information about orders, customers, products, sales, profits and much more.

License

This project is licensed under the MIT License - see the LICENSE file for details.