In “NumPy and Pandas Basics for Future Data Scientists,” learn programming techniques using Python's NumPy and pandas libraries to write efficient and bug-free code for numerical computing.
NumPy and Pandas Basics for Future Data Scientists
NumPy and Pandas Basics for Future Data Scientists
This course is part of Data-Oriented Python Programming and Debugging Specialization
Instructors: Elle O'Brien
Access provided by New York State Department of Labor
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
19 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Create and manipulate NumPy arrays, including performing basic arithmetic operations and handling missing data.
Apply advanced NumPy techniques such as broadcasting, masking, and aggregation functions.
Construct and modify pandas DataFrames and Series, use methods to filter and inspect data, and handle missing data.
Utilize pandas for data aggregation, summary statistics, and dataframe merging to analyze a real dataset.
Details to know
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Taught in English
Recently updated!
March 2025
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This course is part of the Data-Oriented Python Programming and Debugging 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
What's included
9 videos3 readings1 programming assignment1 discussion prompt2 ungraded labs
What's included
6 videos1 reading1 programming assignment2 ungraded labs
What's included
6 videos1 programming assignment2 ungraded labs
What's included
8 videos2 readings1 programming assignment2 ungraded labs
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