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. 

Course Outline

  1. NumPy
    • 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
  2. pandas
    • 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


Basic Python programming experience. In particular working with strings; working with lists, tuples and dictionaries; loops and conditionals; and writing your own functions.


12 Hours | 2 Days or 4 Nights

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Section Title
Python Programming for Data Analysis
M, W
5:30PM to 8:30PM
Feb 01, 2021 to Feb 10, 2021
Schedule and Location
# of Course Hours
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Course Fee(s)
Rate non-credit $1,295.00
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