https://github.com/shriram-vibhute/data-analysis

This repository offers a comprehensive collection of data analysis techniques using NumPy Pandas, Matplotlib and Seaborn.
https://github.com/shriram-vibhute/data-analysis

data-aggregation data-analysis data-visualization data-wrangling matplotlib numpy pandas seaborn

Last synced: 21 days ago
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This repository offers a comprehensive collection of data analysis techniques using NumPy Pandas, Matplotlib and Seaborn.

• Host: GitHub
• URL: https://github.com/shriram-vibhute/data-analysis
• Owner: Shriram-Vibhute
• Created: 2024-08-16T19:19:07.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-12-04T05:26:58.000Z (2 months ago)
• Last Synced: 2024-12-04T06:25:02.631Z (2 months ago)
• Topics: data-aggregation, data-analysis, data-visualization, data-wrangling, matplotlib, numpy, pandas, seaborn
• Language: Jupyter Notebook
• Homepage: https://github.com/Shriram-Vibhute/Data-Analysis
• Size: 5.93 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Complete Data Analysis with Numpy, Pandas, Matplotlib, and Seaborn.

This repository contains Jupyter notebooks for learning and practicing data analysis.

### Numpy

- **numpy**: Introduction to Numpy, covering array creation methods and key functionalities for numerical operations.

### Pandas

- **1 - Series and DataFrames**

  - **Series**: Introduction to Pandas Series and its creation methods.

  - **Dataframe**: Overview of DataFrame creation and manipulation.

  

- **2 - Data Loading, Storage and File Formats**

  - **Data_Loading**: Techniques for loading data from various formats (CSV, JSON, etc.).

- **3 - Data Cleaning and Preprocessing**

  - **data_cleaning_and_preperation**: Methods for handling missing data and data transformation.

- **4 - Data Wrangling - Join Combine & Reshape**

  - **data_wrangling**: Techniques for hierarchical indexing, merging datasets, and reshaping data.

- **5 - Data Aggregation and Group Operation**

  - **data_aggregation**: GroupBy mechanics and data aggregation techniques.

### Matplotlib

- **Matplotlib**: Introduction to Matplotlib for data visualization.

- **QQ_Plots**: Creating QQ plots to assess normality of data distributions.

### Seaborn

- **seaborn_plots**: Visualization techniques using Seaborn, including pair plots and distribution plots.

Hope you find this repository helpful in your data analysis journey!

Happy analyzing! 🎉