Contents
Project Workflow Recap
The Weather Data Analysis project followed a structured Data Science workflow.
Step 1: Understanding the Dataset
We explored the weather dataset and identified the available variables.
Step 2: Loading the Data
The dataset was imported into a Pandas DataFrame for analysis.
Step 3: Data Cleaning
Missing values were identified and handled appropriately.
Step 4: Feature Engineering
Additional features such as month and day were extracted from the date column.
Step 5: Trend Analysis
Temperature, humidity, rainfall, and weather conditions were analyzed using statistical methods.
Step 6: Data Visualization
Multiple charts and graphs were created to communicate insights clearly.
Step 7: Insight Generation
Observations and patterns were identified from the visualizations and statistical analysis.
Weather Data Analysis and Visualization Using Python
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