Course Outline
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
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
Suggested Prerequisites
- Basic Python programming experience, including:
- Working with strings
- Working with lists, tuples, and dictionaries
- Loops and conditionals
- Writing functions
Questions? Speak with our team today—email info@workforcecenter.slu.edu or call 314-977-3226.
Certificate Pathway
Want to Earn the Python Programming Certificate?
In addition to Python Programming for Data Analysis | PYT300, enroll in the following:
