Are You Sure You Are Using The Correct Pandas Terminologies?

If not, let's revisit.

Many Pandas users use the dataframe subsetting terminologies incorrectly. So let's spend a minute to get it straight.

𝐒𝐔𝐁𝐒𝐄𝐓𝐓𝐈𝐍𝐆 means extracting value(s) from a dataframe. This can be done in four ways:

1) We call it 𝐒𝐄𝐋𝐄𝐂𝐓𝐈𝐍𝐆 when we extract one or more of its 𝐂𝐎𝐋𝐔𝐌𝐍𝐒 based on index location or name. The output contains some columns and all rows.

Selecting a dataframe

2) We call it 𝐒𝐋𝐈𝐂𝐈𝐍𝐆 when we extract one or more of its 𝐑𝐎𝐖𝐒 based on index location or name. The output contains some rows and all columns.

Slicing a dataframe

3) We call it 𝐈𝐍𝐃𝐄𝐗𝐈𝐍𝐆 when we extract both 𝐑𝐎𝐖𝐒 and 𝐂𝐎𝐋𝐔𝐌𝐍𝐒 based on index location or name.

Indexing a dataframe

4) We call it 𝐅𝐈𝐋𝐓𝐄𝐑𝐈𝐍𝐆 when we extract 𝐑𝐎𝐖𝐒 and 𝐂𝐎𝐋𝐔𝐌𝐍𝐒 based on conditions.

Filtering a dataframe

Of course, there are many other ways you can perform these four operations.

Here’s a comprehensive Pandas guide I prepared once: Pandas Map. Please refer to the “DF Subset” branch to read about various subsetting methods :)

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Find the code for my tips here: GitHub.

I like to explore, experiment and write about data science concepts and tools. You can read my articles on Medium. Also, you can connect with me on LinkedIn and Twitter.