# Calculate Quantiles by Group in pandas DataFrame in Python (2 Examples)

On this page you’ll learn how to compute quantiles in the columns of a pandas DataFrame by group in the Python programming language.

## Preparing the Examples

`import pandas as pd # Import pandas library in Python`
```my_df = pd.DataFrame({'A':range(110, 122), # Construct pandas DataFrame 'B':[6, 3, 5, 2, 3, 7, 4, 6, 4, 8, 6, 5], 'C':range(0, 12), 'GRP_a':['C', 'B', 'B', 'A', 'C', 'A', 'A', 'B', 'C', 'A', 'C', 'B'], 'GRP_b':['x', 'x', 'x', 'x', 'x', 'x', 'x', 'y', 'y', 'y', 'y', 'y']}) print(my_df) # A B C GRP_a GRP_b # 0 110 6 0 C x # 1 111 3 1 B x # 2 112 5 2 B x # 3 113 2 3 A x # 4 114 3 4 C x # 5 115 7 5 A x # 6 116 4 6 A x # 7 117 6 7 B y # 8 118 4 8 C y # 9 119 8 9 A y # 10 120 6 10 C y # 11 121 5 11 B y```

## Example 1: Calculate Quantiles by Single Group

```print(my_df.groupby('GRP_a').quantile(0.01)) # Find first percentile by group # A B C # GRP_a # A 113.06 2.06 3.06 # B 111.03 3.06 1.03 # C 110.12 3.03 0.12```

## Example 2: Calculate Quantiles by Group & Subgroup

```print(my_df.groupby(['GRP_a', 'GRP_b']).quantile(0.25)) # Find first quartile by multiple groups # A B C # GRP_a GRP_b # A x 114.00 3.00 4.00 # y 119.00 8.00 9.00 # B x 111.25 3.50 1.25 # y 118.00 5.25 8.00 # C x 111.00 3.75 1.00 # y 118.50 4.50 8.50```