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Joining Data with pandas
4.8(9,195)223k studentsINTERMEDIATEEnglish
Korshub's take
Advanced DataFrame Merging in Python
Combining multi-source datasets is a fundamental task in Python data science. This intermediate course dives into the core mechanics of pandas, enabling you to manipulate, merge, and reshape multiple DataFrames with precision.
What You Will Explore
- Data Integration: Master methods for combining, organizing, joining, and reshaping complex DataFrames in Python.
- Real Datasets: Work directly with actual data sourced from the World Bank and the City of Chicago.
- Course Features: Access video transcripts, a comprehensive glossary, and an assessment qualified for CPE credits upon scoring 70% or higher.
Who Should Attend
Data science practitioners and Python users who want to expand their pandas toolkit for handling multi-table analytical pipelines.
About this course
Being able to combine and work with multiple datasets is an essential skill for any aspiring Data Scientist. pandas is a crucial cornerstone of the Python data science ecosystem, with Stack Overflow recording 5 million views for pandas questions. Learn to handle multiple DataFrames by combining, organizing, joining, and reshaping them using pandas. You'll work with datasets from the World Bank and the City Of Chicago. You will finish the course with a solid skillset for data-joining in pandas.
The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.
The course glossary can be found on the right in the resources section.
To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.
Price
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