Python Data Analysis with JupyterLab Training
- 2 days
- Jupyter notebooks.
- The purpose of NumPy.
- One-dimensional NumPy arrays.
- Two-dimensional NumPy arrays.
- Using boolean arrays to create new arrays.
- The purpose of pandas.
- Series objects and one-dimensional data.
- DataFrame objects to two-dimensional data.
- Creating plots with matplotlib.
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private classes are delivered for groups at your offices or a location of your choice.
Learn at your own pace with 24/7 access to an On-Demand course.
- Exercise: Creating a Virtual Environment
- Exercise: Getting Started with JupyterLab
- Jupyter Notebook Modes
- Exercise: More Experimenting with Jupyter Notebooks
- Exercise: Playing with Markdown
- Magic Commands
- Exercise: Playing with Magic Commands
- Getting Help
- Exercise: Demonstrating Efficiency of NumPy
- NumPy Arrays
- Exercise: Multiplying Array Elements
- Multi-dimensional Arrays
- Exercise: Retrieving Data from an Array
- More on Arrays
- Using Boolean Arrays to Get New Arrays
- Random Number Generation
- Exploring NumPy Further
- Getting Started with pandas
- Introduction to Series
- Accessing Elements in a Series
- Exercise: Retrieving Data from a Series
- Series Alignment
- Exercise: Using Boolean Series to Get New Series
- Comparing One Series with Another
- Element-wise Operations and the apply() Method
- Series: A More Practical Example
- Introduction to DataFrames
- Creating a DataFrame using Existing Series as Rows
- Creating a DataFrame using Existing Series as Columns
- Creating a DataFrame from a CSV
- Exploring a DataFrame
- Exercise: Practice Exploring a DataFrame
- Changing Values
- Getting Rows
- Combining Row and Column Selection
- Boolean Selection
- Pivoting DataFrames
- Be careful using properties!
- Exercise: Series and DataFrames
- Plotting with matplotlib
- Exercise: Plotting a DataFrame
- Other Kinds of Plots
Each student will receive 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:
Instructor-led courses are offered via a live Web connection, at client sites throughout Europe, and at our Geneva Training Center.