Course Description:
Data Manipulation with Pandas is a course designed to teach learners how to efficiently manipulate, clean, and preprocess data using the powerful Pandas library in Python. Pandas is widely used in the data science field for its flexible data structures and comprehensive data manipulation capabilities. This course covers essential concepts and techniques for working with data using Pandas.
Data Importing and Exporting
This module will cover the following topics:
Importing data from various file formats
Exporting data to different file formats
Handling different data structures and file types
Explore sources of data
Evaluate data and statistics
Data Cleaning and Preprocessing
This module will cover the following topics:
Handling missing values in the dataset
Dealing with duplicates and outliers
Handling inconsistent data and data types
Data standardization and normalization
Explore data insights
Data Manipulation, Aggregation and Grouping
This module will cover the following topics:
Selecting and indexing data from a DataFrame
Filtering and subsetting data based on specific criteria
Modifying, updating, sorting and reordering data in the DataFrame
Grouping data and performing aggregation operations
Custom aggregation functions and reshaping and pivoting data
Time Series Analysis
This module will cover the following topics:
Working with time series data in Pandas
Handling date and time data
Resampling and frequency conversion
Time series visualization and analysis
Visualizing time series data
Course Achievements
Throughout the course, learners will engage in hands-on exercises and projects that involve manipulating and analyzing real-world datasets using Pandas. They will gain practical experience in cleaning, transforming, and preprocessing data, enabling them to handle and prepare data effectively for analysis and modeling tasks.
Strong foundation in using Pandas for data manipulation tasks
proficient in cleaning data
proficient in transforming data
proficient in preprocessing data
