/Data-Analysis

This repository offers a comprehensive collection of data analysis techniques using NumPy Pandas, Matplotlib and Seaborn.

Primary LanguageJupyter Notebook

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! 🎉