Learners will gain the ability to manipulate, analyze, and visualize data effectively using Python’s Pandas library. By the end of this course, they will be able to filter and transform datasets, apply grouping and aggregation, handle missing values, manage indexes, and reshape data for advanced analytics. They will also master techniques for working with time series, pivot tables, crosstabs, and exporting data to CSV and Excel.
Pandas with Python: Analyze, Transform & Export Data
Pandas with Python: Analyze, Transform & Export Data
This course is part of Data Analysis with NumPy and Pandas Specialization
Instructor: EDUCBA
Access provided by D Y Patil University Pune
Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Filter, group, aggregate, and reshape datasets using Pandas.
Handle missing values, manage indexes, and analyze time series.
Create pivot tables, crosstabs, and export data to CSV/Excel.
Skills you'll gain
Details to know
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Assessments
16 assignments
Taught in English
Recently updated!
October 2025
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This course is part of the Data Analysis with NumPy and Pandas Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
This module introduces learners to the Pandas library, its installation, and the Jupyter environment for hands-on coding. It covers Pandas’ core data structures, including Series and DataFrames, and explores fundamental operations for working with rows and columns. Learners build a strong foundation for effective data handling.
What's included
9 videos4 assignments1 plugin
This module focuses on advanced filtering, selection, and transformation of data. Learners explore indexing by labels and positions, handle data types, apply string methods, and group data for aggregation. It also emphasizes working with Series, plotting, and handling null values.
What's included
12 videos4 assignments
This module introduces indexing concepts and parameters that enhance data manipulation. Learners explore memory management, sampling strategies, dummy coding, handling duplicates, working with date/time functions, and avoiding common pitfalls like copy warnings.
What's included
16 videos4 assignments
This module covers advanced reshaping, merging, and exporting functionalities in Pandas. Learners gain expertise in display options, formatting, working with pivot tables, crosstab functions, and exporting data to external formats like CSV and Excel for practical applications.
What's included
22 videos4 assignments
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