# Pandas: How to Add Subtotals to Pivot Table

Often you may want to add subtotals to a pandas pivot table.

Fortunately this is easy to do using built-in functions in pandas.

The following example shows how to do so.

## Example: Add Subtotals to Pandas Pivot Table

Suppose we have the following pandas DataFrame that contains information about various basketball players:

```import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],
'position': ['G', 'G', 'F', 'F', 'G', 'F', 'F', 'F'],
'all_star': ['Y', 'N', 'Y', 'Y', 'N', 'N', 'N', 'Y'],
'points': [4, 4, 6, 8, 9, 5, 5, 12]})

#view DataFrame
print(df)

team position all_star  points
0    A        G        Y       4
1    A        G        N       4
2    A        F        Y       6
3    A        F        Y       8
4    B        G        N       9
5    B        F        N       5
6    B        F        N       5
7    B        F        Y      12```

We can use the following code to create a pivot table in pandas that shows the sum of points for each combination of team, all_star, and position in the DataFrame:

```#create pivot table
my_table = pd.pivot_table(df, values='points',
index=['team', 'all_star'],
columns='position',
aggfunc='sum')

#view pivot table
print(my_table)

position          F    G
team all_star
A    N          NaN  4.0
Y         14.0  4.0
B    N         10.0  9.0
Y         12.0  NaN```

Now suppose we would like to add a subtotals row that shows the subtotal of points for each team and position.

We can use the following syntax to do so:

```#add subtotals row to pivot table
pd.concat([
y.append(y.sum().rename((x, 'Total')))
for x, y in my_table.groupby(level=0)
]).append(my_table.sum().rename(('Grand', 'Total')))

position	F	G
team	all_star
A	       N	NaN	4.0
Y	7.0	4.0
Total	7.0	8.0
B	       N	5.0	9.0
Y	12.0	NaN
Total	17.0	9.0
Grand	   Total	24.0	17.0
```

We now have two subtotal rows that show the subtotal of points for each team and position, along with a grand total row that shows the grand total of each column.

Note: You can find the complete documentation for the pandas pivot_table() function here.