concat() for stacking DataFrames in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the concat() function do in pandas?

The concat() function joins multiple DataFrames together either vertically (stacking rows) or horizontally (stacking columns).

beginner

How do you stack two DataFrames vertically using concat()?

Use pd.concat([df1, df2]) to stack rows of df2 below df1. By default, it stacks vertically (axis=0).

beginner

What parameter controls whether concat() stacks DataFrames horizontally or vertically?

The axis parameter: axis=0 stacks vertically (rows), axis=1 stacks horizontally (columns).

intermediate

What happens if the DataFrames have different columns when stacked vertically with concat()?

Missing columns in each DataFrame become NaN in the result, so all columns from all DataFrames appear.

intermediate

How can you reset the index after stacking DataFrames with concat()?

Use ignore_index=True inside concat() to reset the index in the combined DataFrame.

What is the default axis value for pd.concat() when stacking DataFrames?

A 0 (vertical stacking)

B 1 (horizontal stacking)

C -1 (reverse stacking)

D None (no stacking)

The default axis=0 stacks DataFrames vertically by rows.

If two DataFrames have different columns, what does concat() do when stacking vertically?

A Fills missing columns with NaN

B Duplicates columns

C Raises an error

D Drops columns not common to both

Missing columns are filled with NaN so all columns appear in the result.

How do you stack DataFrames side-by-side (horizontally) using concat()?

A Set <code>axis=0</code>

B Use <code>join='outer'</code>

C Use <code>ignore_index=True</code>

D Set <code>axis=1</code>

Setting axis=1 stacks DataFrames horizontally by columns.

What does ignore_index=True do in concat()?

A Keeps original indexes

B Resets index in the combined DataFrame

C Drops duplicate rows

D Sorts the DataFrame

It resets the index so the new DataFrame has a continuous index starting at 0.

Which pandas function is used to stack DataFrames?

A groupby()

B merge()

C concat()

D pivot()

concat() is used to stack DataFrames either vertically or horizontally.

Explain how to stack two DataFrames vertically using concat() and how to handle their indexes.

Think about stacking rows and index resetting.

Describe what happens when you stack DataFrames with different columns using concat().

Consider how pandas handles missing data in combined DataFrames.