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Data Analysis with Python

Table of Contents

Lab-1: Introduction

This notebook provides an introduction to data acquisition and basic insights using the Pandas library. It covers data loading, exploration, and statistical summaries.

Topics

  • Data acquisition: Loading dataset from local or online sources using Pandas.
  • Basic insights: Data types, statistical summaries, and dataset information.

Prerequisites

  • Python and Jupyter Notebook.
  • Basic understanding of Python programming and data manipulation.

Dataset

Automobile Dataset (CSV Format)

Libraries Used

  • Pandas: Data manipulation and analysis.
  • NumPy: Numerical computations.

Lab-2: Data Wrangling

This notebook focuses on data wrangling tasks, which involve preparing and cleaning data for analysis.

Topics

  • Identify & Handle missing values
    • Identify & Deal with missing values
    • Correct data format
  • Standardizing & Normalizing data.
  • Binning Numerical Variables.
  • Indicator Variable (Dummy Variable).

Prerequisites

  • Lab-1 Introduction
  • Familiarity with Pandas library.

Dataset

Automobile Dataset (CSV Format)

Libraries Used

  • Pandas
  • NumPy
  • Matplotlib: Data visualization.