Data Analysis with Python

Table of Contents

• Lab-1 Introduction
• Lab-2 Data Wrangling

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.