concat() for stacking DataFrames in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the pandas concat() function do when stacking DataFrames?

It combines multiple DataFrames either vertically (one below another) or horizontally (side by side) into a single DataFrame.

beginner

What parameter in concat() controls whether DataFrames are stacked vertically or horizontally?

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

intermediate

If DataFrames have different columns, what does concat() do by default?

It includes all columns from all DataFrames, filling missing values with NaN where data is absent.

intermediate

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

Use the parameter ignore_index=True in concat() to create a new continuous index in the combined DataFrame.

intermediate

What is the difference between concat() and append() in pandas?

append() is a simpler method to stack DataFrames vertically but is deprecated. concat() is more flexible and recommended for stacking.

Which axis value stacks DataFrames vertically using concat()?

A -1

B 1

C None

D 0

Setting axis=0 stacks DataFrames vertically (one below another).

What happens to columns not shared by all DataFrames when using concat()?

A They are dropped

B They cause an error

C They are included with NaN in missing places

D They are renamed automatically

Columns not present in all DataFrames appear with NaN where data is missing.

How do you combine DataFrames side by side using concat()?

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

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

C Use <code>join='inner'</code>

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

Setting axis=1 stacks DataFrames horizontally (side by side).

Which parameter resets the index after concatenation?

A ignore_index=True

B reset_index=True

C drop_index=True

D index=False

ignore_index=True resets the index to a new continuous range.

Why is concat() preferred over append()?

A Because <code>append()</code> works only on Series

B Because <code>append()</code> is deprecated

C Because <code>concat()</code> is slower

D Because <code>concat()</code> cannot stack horizontally

append() is deprecated; concat() is more flexible and recommended.

Explain how to stack two DataFrames vertically using pandas concat(). Include how to handle index resetting.

Think about stacking rows and making the index continuous.

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

Consider how pandas handles missing data in combined tables.