Python Data Analysis with NumPy and pandas
This is a rapid introduction to NumPy, pandas and matplotlib for experienced Python programmers who are new to those libraries.
- 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
Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.
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.
Courses that can help you meet these prerequisites:
Preparing for Class