Sales Data Analysis

Overview

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

Steps Taken

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.

Running 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.

Dependencies

• pandas
• matplotlib
• seaborn