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
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NumPy and Pandas Basics for Future Data Scientists
This course is part of Data-Oriented Python Programming and Debugging Specialization
Instructors: Elle O'Brien
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Intermediate level
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2 weeks to complete
at 10 hours a week
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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.
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Taught in English
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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
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