Objectives:

Master the Pandas library for data manipulation, including data loading, cleaning, filtering, grouping, and merging. This workshop will equip participants with valuable skills that are in high demand in the data science field, enabling them to work with data effectively and create impactful data-driven applications.

Together we will learn about following:

• How to manage large dataframe
• How to clean data
• How to read CSV and Excel
• How to check for NULL values

Where Pandas is used:

• Data Cleaning: Used to clean and preprocess messy data, handling missing values and outliers.
• Data Analysis: Ideal for data exploration, summarization, and generating descriptive statistics.
• Data Transformation: Performs data transformations, such as pivoting, melting, and reshaping data.
• Data Integration: Merges and combines data from multiple sources for analysis.
• Time Series Analysis: Supports time-based data analysis, making it valuable in financial and scientific research.
• Statistical Analysis: Provides tools for statistical modeling and hypothesis testing.
• Machine Learning: Used for data preparation and feature engineering in machine learning projects.