You can use the following basic syntax to get the first row of each group in a pandas DataFrame:

df.groupby('column_name').nth(0)

The following example shows how to use this syntax in practice.

**Example: Get First Row of Each Group in Pandas**

Suppose we have the following pandas DataFrame:

**import pandas as pd
#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'],
'points': [18, 22, 19, 14, 14, 11, 20, 29],
'assists': [5, 19, 14, 8, 9, 12, 13, 8]})
#view DataFrame
df
team points assists
0 A 18 5
1 A 22 19
2 B 19 14
3 B 14 8
4 B 14 9
5 C 11 12
6 C 20 13
7 C 29 8
**

We can use the following code to get the first row for each team:

#get first row for each team df.groupby('team').nth(0) points assists team A 18 5 B 19 14 C 11 12

We can also specify **as_index=False** to keep the original index values:

#get first row for each team, keep original index values df.groupby('team', as_index=False).nth(0) team points assists 0 A 18 5 2 B 19 14 5 C 11 12

Also note that you can pass a list of values to the **nth()** function if you’d like to get the first n rows for each group.

For example, the following code shows how to get the first two rows for each group:

#get first two rows for each team, keep original index values df.groupby('team', as_index=False).nth((0, 1)) team points assists 0 A 18 5 1 A 22 19 2 B 19 14 3 B 14 8 5 C 11 12 6 C 20 13

**Note**: You can find the complete documentation for the **nth()** function here.

**Additional Resources**

The following tutorials explain how to perform other common operations in pandas:

How to Get First Row of Pandas DataFrame

How to Drop First Row in Pandas DataFrame

How to Insert a Row Into a Pandas DataFrame