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Analysis of Sales Data with Python🐍

This Python script analyzes sales data from a CSV file and performs various operations including data cleaning, basic analysis, and visualization.

🧾 Table of Contents

🛠️ Installation

  1. Clone the repository from Dragons Bootcamp LLC:

    git clone https://github.com/Mado007/bank-data-analysis.git

  2. Navigate to the project directory:

    cd bank-data-analysis

  3. Install the required Python dependencies:

    pip install -r requirements.txt

📊 Usage

  1. Ensure that the CSV file containing the sales data is placed in the project directory.

  2. Run the Python script banking_sales_analysis.py:

    python banking_sales_analysis.py

  3. Follow the prompts to perform data analysis and visualization.

📈 Data_Analysis_Methods

  • Data Visualization: Utilized matplotlib and seaborn libraries to create visual representations of the data including histograms

  • Descriptive Statistics: Calculated summary statistics such as mean, median, mode, and standard deviation to understand the central tendency and variability of the data.

  • Grouping and Aggregation: Grouped the data based on different categorical variables and performed aggregation functions to summarize the information within each group.

Data_Visualization

Distribution of Call Duration Numbers of calls in each month Distribution of calls

🔑License

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

© Credits

This assignment was completed as part of the Dragons Bootcamp LLC curriculum. Credit goes to Dragons Bootcamp LLC for providing the assignment and supporting materials.