08 - pandas DataFrames

We learn about pandas DataFrames, a powerful tool for working with tabluar data in Python.

Summary:
- pandas DataFrames are a powerful way of storing and working with tabular (row/column) data
- pandas columns and rows can have names
- pandas row names are called *indexes* which are numeric by default, but can be given other labels
- Use the `.iloc[]` method with a DataFrame to select values by integer location, using [row, column] format
- Use the `.loc[]` method with a DataFrame to select rows and/or columns, using named slices
- Use `:` on its own to mean all columns or all rows
- Result of slicing can be used in further operations
- Use comparisons to select data based on value
- Select values or `NaN` using a Boolean mask
- use split-apply-combine to derive analytics from groupings within a DataFrame

From the course, NESC 3505 Neural Data Science, by Aaron J Newman, Dalhousie University, Halifax, NS, Canada.

[shehanijayalath]

A neuroscience student here, diving into neural data science with your help. Your open educational resources on YouTube and the online book have been tremendously useful to me. Thank you so much for your hard work, I really appreciate it!

[arnaudpautrat]

As a fellow neuroscientist, I wanted to say a BIG "thank you" to you, Pr. Newman, for this high quality content. Your videos and website are a gold mine of informations, and you made it in open access. Kudos from France !

[brenojust]

When I put "df = there appears an error message "FileNotFoundError"
Does anyone know how to correct it?
I'm copying the text directly from the textbook available, so it may not be a spelling error