This project involves the analysis of sales data obtained from Kaggle. The goal is to explore and draw meaningful insights from the dataset.

Data Acquisition

• The dataset was accessed from the Kaggle store and stored locally.

Data Cleaning

• Cleaned the dataset to handle missing values, empty columns and other inconsistencies.

Exploratory Data Analysis (EDA)

• Analyzed individual columns using various data science techniques.
• Explored patterns, distributions, and relationships within the dataset.

Conclusions Drawn

• Summarized findings and drew conclusions based on the analysis.

To reproduce the analysis and draw conclusions, follow these steps:

• Ensure you have the required dependencies installed. You can use the following command to install them:

  pip install -r requirements.txt

• Open the Jupyter Notebook file analysis.ipynb in your preferred Jupyter Notebook environment.

• Run the notebook cell by cell to execute the analysis and view the conclusions.

• pandas
• matplotlib
• seaborn