Data Analysis and Machine Learning Projects Repository

Welcome to my GitHub repository! This repository contains all projects that I worked on throughout my journey with ALX. It contains various projects focusing on data analysis, visualizations, and machine learning. ere's a brief overview of what you'll find:

Projects Overview:

1. Excel Projects:

Integrated project 1

Understanding the data

Description:

This project involves investigating the access to safe and affordable drinking water.

Skills Demonstrated:

Importing and cleaning raw sales data using Excel's data manipulation features. Designing dashboards using pivot tables, charts, and slicers. Implementing Excel functions (e.g.ROUND, SUM, QUARTILE, MODE) for data analysis and aggregation.

Files:

Estimates-on-the-use-of-water-(2020)-a-3712.csv: Contains the raw data.

Usage: Open Estimates-on-the-use-of-water-(2020)-a-3712.csv and ensure data is structured correctly. Open Integrated Project 1.xlsx to explore the report and interact with the data.

Integrated project 2

Transforming the data

Description:

In this project, I extended my investigation on access to safe and affordable drinking water.

Skills Demonstrated:

Importing and cleaning raw sales data using Excel's data manipulation features. Designing dashboards using pivot tables, charts, and slicers. Implementing Excel functions (e.g.AVERAGEIFS, COUNTIFS, UNIQUE, VLOOUP) for data analysis and aggregation.

Files:

Estimates of the use of water (2000-2020).csv and Regions.csv: Contain the raw data.

Usage: Open Estimates of the use of water (2000-2020).csv and Regions.csv and ensure data is structured correctly. Open Integrated Project 2.xlsx to explore the report and interact with the data.

2. SQL

This project involves analyzing a movie database to extract insights such as popular genres, actor collaborations, and box office performance.

Skills Demonstrated:

Crafting SQL queries to extract relevant information from a movie database. Utilizing aggregate functions (e.g., SUM, AVG, COUNT) to calculate metrics such as average ratings, total revenue, and movie counts. Implementing SQL joins to combine data from multiple tables (e.g., movies, genres, actors). Creating views to encapsulate frequently used queries and simplify data access.

Files:

TMDB.db file: Contains the raw movies data

Usage

Open the SQL Exam notebook and ensure your database is stored in the same location as the notebook

3. PowerBI

This project inolves building dashboards to communicate with transparency the problems causing Maji Ndogo's water crisis. I tracked the total budget against project completion, monitor teams' performance, and compared budgeted versus actual costs to flag potential corruption.

Skills Demonstrated:

Importing and transforming data from multiple sources into Power BI using Power Query Editor. Designing interactive dashboards with slicers, filters, buttons, and drill-down functionalities. Implementing custom visuals and calculated measures for advanced data analysis.

Files:

Md_water_services_data.xlsx: Contains the raw sales data. Maji Ndogo Analysis.pbix: Power BI file with the dashboards. MD_Provinces.json: Contains the map data to aid proper visualisations MD_Map.png: Contains the map outline

Usage:

Open Maji Ndogo Analysis.pbix in Power BI Desktop. Connect Md_water_services_data.xlsx as a data source and refresh data if necessary. Connect the MD_Provinces.json as well as the MD_Map.png Interact with the dashboard to explore insights and trends.

4. Python

This project involves analusing an agricultural csv file to test my python knowledge

Skills Demonstrated

Importing and exploring the dataset using pandas Wrangling the dataset using pandas to extract insights from the dataset. Using Matplotlib to create visualisations to better understand the data. Using scipy to perform statistics on the data

Files

MD_agric_exam-4313.csv: Contains the raw agricultural file Python exam.ipynb: Contains the python code used on the data

Usage

Open the Python exam.ipynb file in jupyter notebook, or any code editor Download and save the MD_agric_exam-4313.csv file in the same location as the notebook and begin testing out your won codes

Project Structure:

1. Excel: Contains Excel projects.
2. SQL: Contains SQL projects.
3. PowerBI: Contains Power BI projects.
4. Python: Contains Python projects.

Contributing:

Contributions are welcome! If you'd like to contribute to any project or have suggestions for improvement, feel free to open an issue or submit a pull request.