Both rows and columns in a DataFrame have labels called indexes. In the vehicles DataFrame

• rows are labelled by numbers (0, 1, 2, etc.)
• columns are labelled with text (id, model, year, etc.)

If we talk about “the index” of a DataFrame, we’ll always be referring to the row index.

Default Index

By default, DataFrames come with a RangeIndex where the first row is labelled 0, the second row is labelled 1, and so on.

To confirm this, we can call the .index attribute on a DataFrame:

df.index

If the DataFrame has the default index, the output will be

RangeIndex(start=0,
    stop=number of rows,
    step=1)

indicating that the row labels

• start at 0
• increase by 1 for each row
• end before reaching the total number of rows (since we started counting at 0)

For example, a DataFrame with 3 rows might have the index RangeIndex(start=0, stop=3, step=1).

In this RangeIndex, we start labelling rows at 0, stop before 3, and increase by 1 each row:

• the first row has the label 0
• the second row has the label 1
• the third row has the label 2

Other Kinds of Index

Both DataFrames and Series (individual columns) can have other types of index. For example, let’s call .value_counts() on vehicle_type in our vehicles DataFrame:

vehicle_counts = vehicles['vehicle_type'].value_counts()
vehicle_counts

The output we’ll receive is

sedan/wagon                  1205
suv                           742
pickup                        373
van                           189
passenger van/shuttle bus       7
vocational/cab chassis          4

Here, each row is labeled with the vehicle type as text. If we call

vehicle_counts.index

we’ll receive the output

Index(['sedan/wagon', 'suv', 'pickup', 'van', 'passenger van/shuttle bus',
       'vocational/cab chassis'],
      dtype='object')

Unlike a RangeIndex, this is an Index consisting of a list of distinct objects/strings.

Resetting the Index

It is possible to restore a standard RangeIndex by calling the method .reset_index(). For example, if we call

vehicle_counts.reset_index()

we’ll receive the following output

Note that the column index in the .reset_index() DataFrame is no longer the index: it is a column containing the old index values pre-reset. The index after calling .reset_index() is the RangeIndex from 0 to 5.

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