Python Programming Level 3: Data Science Techniques with NumPy and Pandas Course Outline
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; work with pandas to analyze data; and work with matplotlib from within pandas.
Students already familiar with Python programming.
Basic Python programming experience. In particular, you should be very comfortable
with: working with strings, lists, tuples and dictionaries; loops and conditionals; and writing your own
1. Jupyter Notebook
Getting Started with Jupyter Notebook
Creating Your First Jupyter Notebook
Jupyter Notebook Modes
Useful Shortcut Keys
Getting Basic Information about an Array
NumPy Arrays Compared to Python Lists
Modifying Parts of an Array
Adding a Row Vector to All Rows
Series and DataFrames
Accessing Elements from a Series
Comparing One Series with Another
Creating a DataFrame from NumPy Array
Creating a DataFrame from Series
Creating a DataFrame from a CSVl
Getting Columns and Rows
Combining Row and Column Selection
Scalar Data: at and iat
Plotting with matplotlib
View outline in Word
Attend hands-on, instructor-led Python Programming Level 3: Data Science Techniques with NumPy and Pandas training classes at ONLC's more than 300 locations.
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For additional training options, check out our list of Python Courses and select the one that's right for you.