Length: 2 Days
This is a rapid introduction to NumPy, pandas, and matplotlib for experienced Python programmers who are new to those libraries.
Experience in the following is required for this Python class:
- Basic Python programming experience. In particular, you should be very comfortable with:
- Working with strings.
- Working with lists, tuples and dictionaries.
- Loops and conditionals.
- Writing your own functions.
WHAT YOU’LL LEARN
- Learn to work with Jupyter Notebook.
- Learn to use NumPy to work with arrays and matrices of numbers.
- Learn to work with pandas to analyze data.
- Learn to work with matplotlib from within pandas.
• 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
• Series and DataFrames
• Accessing Elements from a Series
• Series Alignment
• Comparing One Series with Another
• Element-wise Operations
• Creating a DataFrame from NumPy Array
• Creating a DataFrame from Series
• Creating a DataFrame from a CSVl
• Getting Columns and Rows
• Cleaning Data
• Combining Row and Column Selection
• Scalar Data: at and iat
• Boolean Selection
• Plotting with matplotlib