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Weather Data Analysis and Visualization Using Python

Weather Data Analysis and Visualization Using Python

The Weather Data Analysis Project is a beginner-friendly Data Science project that explores temperature, humidity, rainfall, and weather condition trends using Python. Through data cleaning, feature engineering, exploratory analysis, and visualization, learners gain practical experience working with real-world weather datasets and generating meaningful insights.

6 Modules

53 Lessons

English

1 Hr

Reading Plan

MODULE 1

Introduction to Weather Data Analysis

7 mins

Introduction to Weather Data Analysis

1 min

What is Data Science?

1 min

What is Weather Data Analysis?

1 min

Importance of Weather Data Analysis

1 min

Understanding the Weather Dataset

1 min

Project Objective

1 min

Expected Project Output

1 min

MODULE 2

Environment Setup and Data Loading

10 mins

Environment Setup and Data Loading

1 min

Technologies and Libraries Used

1 min

Importing Required Libraries

1 min

Loading the Dataset

1 min

Understanding DataFrames

1 min

Viewing the First Few Records

1 min

Understanding Dataset Dimensions

1 min

Exploring Dataset Information

1 min

Generating Statistical Summaries

1 min

Initial Observations

1 min

MODULE 3

Data Cleaning and Feature Engineering

10 mins

Data Cleaning and Feature Engineering

1 min

Identifying Missing Values

1 min

Handling Missing Values

1 min

Verifying Missing Value Removal

1 min

Converting the Date Column

1 min

Extracting Month Information

1 min

Extracting Day Information

1 min

Checking Data Types After Transformation

1 min

Creating an Analysis-Ready Dataset

1 min

Benefits of Feature Engineering

1 min

MODULE 4

Weather Trend Analysis

9 mins

Weather Trend Analysis

1 min

Analyzing Average Temperature

1 min

Finding Maximum and Minimum Temperature

1 min

Analyzing Average Humidity

1 min

Rainfall Analysis

1 min

Monthly Temperature Analysis

1 min

Understanding Relationships Between Variables

1 min

Basic Correlation Analysis

1 min

Summary of Findings

1 min

MODULE 5

Data Visualization and Insights

9 mins

Data Visualization and Insights

1 min

Creating a Temperature Trend Chart

1 min

Visualizing Humidity Trends

1 min

Creating a Rainfall Trend Chart

1 min

Weather Condition Frequency Chart

1 min

Monthly Average Temperature Chart

1 min

Temperature vs Humidity Scatter Plot

1 min

Correlation Heatmap

1 min

Understanding Visualization Results

1 min

MODULE 6

Project Conclusion and Assessment

8 mins

Project Conclusion and Assessment

1 min

Project Workflow Recap

1 min

Live Output and Visualization Overview

1 min

Key Concepts Learned

1 min

Learning Outcomes

1 min

Multiple Choice Questions (MCQs)

1 min

Real-World Applications

1 min

Resources

1 min

Contributors

Vishalini A

Weather Data Analysis and Visualization Using Python

Learn how to analyze weather data using Python and Data Science techniques. This beginner-friendly handbook covers data cleaning, feature engineering, trend analysis, and visualization to help you uncover meaningful insights from weather observations.

Weather Data Analysis Using Python – Beginner Data Science Project

This handbook provides hands-on experience in Data Science by building a complete Weather Data Analysis project from scratch. It guides learners through data loading, cleaning, feature engineering, trend analysis, and visualization while developing practical skills in Python-based data analytics.

Weather Data Analysis Using Python – Beginner Data Science Project

Prerequisites

This course is suitable for:

Basic knowledge of Python programming
Basic understanding of Data Analysis concepts
A Google account to access Google Colab
Basic familiarity with Pandas and Matplotlib
Internet connection to access datasets and libraries
Interest in Data Science and data visualization

Run & Test your Code with our very own IDE that supports 16 languages

Open IDE

6 Modules

53 Lessons

English

1 Hr

Contributors

Vishalini A

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