Pandas Online Course
This course is designed to help you harness the power of the Pandas library for efficient and effective data analysis. You’ll start with the fundamentals, including how to install and set up Pandas, before diving into its core components such as data structures, data types, and indexing techniques.
You’ll gain hands-on experience with key features of the library—working with various data formats, slicing and indexing datasets, and managing missing values. As you progress, the course will guide you through essential data analysis and modeling techniques, along with creating visual representations like plots and charts to present your insights.
Throughout the course, you’ll apply your learning through practical, real-world examples and use cases, gradually building your proficiency. By the end, you'll have a strong foundation in Pandas and be fully prepared to tackle a wide range of data science tasks with confidence.
Who should take this Course?
The Pandas Online Course is ideal for data analysts, data scientists, Python programmers, and researchers who want to efficiently manipulate, analyze, and visualize data using the Pandas library. It’s also suitable for students and professionals working with large datasets in fields like finance, marketing, or academia. A basic understanding of Python and data handling concepts is recommended to make the most of this course.
Course Curriculum
Initial Configuration and Getting Data into Pandas
- The Course Overview
- Installing and Setting Up Python
- Installing Pandas and Other Dependent Python Modules
- Setting Up and Using Jupyter Notebooks
- Importing Data (CSV) into Pandas
Exploring and Analyzing Data
- Exploring the Imported Dataset
- Manipulating and Reshaping the Dataset
- Handling Missing Data in Pandas
- Analyzing the Imported Dataset
Visualizing Data Using Matplotlib
- Using Pandas and Matplotlib to Draw Plots and Charts
- Drawing Bar Charts
- Making Histograms
- Drawing Box Plots
- Drawing Some Other Kinds of Plots with Matplotlib
Exporting Data Out of Pandas
- Exporting Transformed and Processed Data Out of Pandas
- Exporting to Some Popular File Formats
- Exporting to SQL-Based Databases