Pandas Explained: Series, DataFrames, and Real Data in Python

Pandas turns Python into a data instrument. In this video we cover the two
structures everything else is built on, the Series and the DataFrame, then
put them to work on a real shareholder vote: loading a CSV, selecting and
filtering rows, adding computed columns, handling missing data, and
exporting the result.

You will learn:
- Series: one-dimensional data with meaningful labels
- DataFrames: columns of Series, sharing an index
- Reading data with read_csv, and inspecting it with head, info, and describe
- Selecting columns and filtering rows with boolean masks
- Creating columns, conditional assignment with .loc, and dropping columns
- Missing data: why an abstention and an unreturned ballot are not the same thing
- Aggregating with value_counts, crosstab, and groupby
- Exporting to CSV and to multi-sheet Excel files

⏱ Chapters
0:00 In a world drowning in raw data
0:25 Why pandas exists
1:03 Series and DataFrames
2:14 Building your first Series
3:53 DataFrames
5:31 Reading data from files
6:59 Selecting data
8:05 Adding and removing columns
9:49 Missing data
11:06 Aggregation
12:23 Exporting your results
13:39 Well done

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