Course Description
This is a rapid introduction to NumPy, pandas and matplotlib for experienced Python programmers who are new to those libraries. Students will learn to use NumPy to work with arrays and matrices of numbers; learn to work with pandas to analyze data; and learn to work with matplotlib from within pandas.
Python Programming for Data Analysis Dec 2025Python Programming for Data Analysis
One-dimensional Arrays
Multi-dimensional Arrays
Getting Basic Information about an Array
NumPy Arrays Compared to Python Lists
Universal Functions
Modifying Parts of an Array
Adding a Row Vector to All Rows
Random Sampling
PandasSeries and DataFramesAccessing Elements from a SeriesSeries AlignmentComparing One Series with AnotherElement-wise OperationsCreating a DataFrame from a NumPy ArrayCreating a DataFrame from SeriesCreating a DataFrame from a CSVGetting Columns and RowsCleaning DataCombining Row and Column SelectionScalar Data: at[] and iat[]Boolean SelectionPlotting with matplotlib
Series and DataFrames
Accessing Elements from a Series
Series Alignment
Comparing One Series with Another
Element-wise Operations
Creating a DataFrame from a NumPy Array
Creating a DataFrame from Series
Creating a DataFrame from a CSV
Getting Columns and Rows
Cleaning Data
Combining Row and Column Selection
Scalar Data: at[] and iat[]
Boolean Selection
Plotting with matplotlib
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