Data Processing with Python (February 8 Early)
Master using Python for data munging, processing, visualization and exploratory data analysis.
Thursdays, 12:00PM EST
What will I learn?
- Get hands-on experience with data processing and analysis using Python.
- Learn how to translate everything you do in Excel into Python code.
- Perform advanced data transformations using Python.
- Learn how to do time series analysis in Python.
- Master building insightful visualizations of your data.
- Learn the ins and outs of the Pandas and Numpy libraries.
Learn the fundamentals of ndarrays and how to perform operations with them.
Learn how to work with data using Pandas series and dataframes.
Advanced Pandas I
Practice data cleaning, grouping and pivoting with Pandas.
Advanced Pandas II
Learn how to aggregate data and how to automate your analysis.
Data Visualization with Pandas & Matplotlib
Learn how to create insightful data visualizations using Pandas and Matplotlib.
With your instructor's guidance, use what you've learned in this class to build an end-to-end data analysis workflow.
Live, Online, Instructor-Led
Learn face-to-face in live online sessions with your instructor and peers from anywhere in the world.
All our trainings involve in-class, hands on practice that is relevant to your team's goals. At the end of the training, your team will be ready to hit the ground running.
Learn from an elite team of industry experts who have taught at universities such as Harvard, and have trained teams at companies such as ANZ Bank.
Help When You Need It
Forget about the frustration of getting stuck while watching online videos. Our instructors are here to help in-between sessions, so you can have a smooth learning experience.
Get started now
Your registration covers:
- Access to all 6 live instructor-led sessions
- Recordings of all 6 live sessions.
- Practice problems and projects with solutions.
- Comprehensive resources.
- Personalized feedback and support.
1. INTRODUCTION TO NUMPY
- The ndarray class
- Operations on ndarrays
2. INTRODUCTION TO PANDAS
- Pandas Series
- Pandas DataFrame
- Loading data into Pandas
- Pandas indices and selecting and slicing data
- Adding and dropping data
- Filtering data
- Combining multiple DataFrames
- Sorting DataFrames
- Dealing with missing values
3. ADVANCED PANDAS
- Data transformations and function applications
- String operations and transformations
- Aggregating data by groups
- Automating and repeating data analysis
- Exporting DataFrames
- Pandas best practices
- Handling time series data
4. DATA VISUALIZATION
- Line graphs
- Bar graphs
- Scatter plots
- Exporting plots