This repository is a source code for the tasks that were assigned to me for my internship at Alfido Tech. The tasks include the following projects:
- Weather Data Analysis
- Uber Data Analysis
- Inventory Analysis Case
All the tasks were carried out using Python libraries such as Pandas, Matplotlib, and Seaborn.
Weather Data Analysis focuses on examining historical weather data to extract insights and patterns. This could include analyzing temperature trends, precipitation patterns, wind speeds, and more.
- Examination of historical weather data
- Extraction of insights and patterns
- Analysis of temperature trends
- Study of precipitation patterns
- Evaluation of wind speeds
To view or modify the source code for the Weather Data Analysis, navigate to the Weather Data Analysis Codes.py
This involves studying data related to Uber rides, such as ride times, locations, and user ratings. The analysis can be used to understand user behavior, driver patterns, and areas of high demand.
- Data Loading and Exploration.
- Data Cleaning.
- Exploratory Data Analysis(EDA).
- Time-related Analysis.
- Distance and Purpose Analysis.
- User and Driver Patterns.
- High-Demand Areas.
- Correlation Analysis.
- Limitations.
- Conclusion and Insights.
To view or modify the source code for the Uber Data Analysis, navigate to the Uber Data Analysis Codes.py
Inventory data analysis involves examining and interpreting data related to a company's inventory to gain insights, make informed decisions, and optimize inventory management processes.
- Data Examination.
- Insights and Patterns.
- Temperature Trends.
- Precipitation Patterns.
- Wind Speed Analysis.
- Visualizations.
- Insights and Recommendations.
To view or modify the source code for the Uber Data Analysis, navigate to the Inventory Analysis codes.py