Analyzing Spreadsheet Data with Python
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Master analyzing spreadsheet data with Python. Learn how to manipulate, clean, and visualize data from Excel and CSV files using Python libraries like Pandas, and gain essential skills for data analysis in business and research contexts.
At a Glance
We all know how hard it can be to sift through spreadsheets sometimes. With hundreds upon hundreds of rows and columns, there’s a lot of data to get through! But not to worry, we have some good news for you: all that data can be analyzed in Python with just a few lines of code. No longer do you have to scroll through your lagging spreadsheets! With only a few keystrokes, you can cherry pick the data that you need. Get your spreadsheets ready because with this project, you’ll be able to launch your journey into the world of data analysis!
A Look At the Project Ahead
- Load data from a spreadsheet to Python
- Use Pandas, a Python library, to perform spreadsheet operations such as subsetting, filtering and calculating column mean, median and max
- Export your data table to an Excel spreadsheet
What You’ll Need
Otherwise, all you’ll need is a web browser!
Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to JupyterLab. This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.
Instructor
Other Contributors
Yasmine Hemmati, IBM
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