In statistics, quartiles are values that split up a dataset into four equal parts.
When analyzing a distribution, we’re typically interested in the following quartiles:
- First Quartile (Q1): The value located at the 25th percentile
- Second Quartile (Q2): The value located at the 50th percentile
- Third Quartile (Q3): The value located at the 75th percentile
You can use the following methods to calculate the quartiles for columns in a pandas DataFrame:
Method 1: Calculate Quartiles for One Column
df['some_column'].quantile([0.25, 0.5, 0.75])
Method 2: Calculate Quartiles for Each Numeric Column
df.quantile(q=[0.25, 0.5, 0.75], axis=0, numeric_only=True)
The following examples show how to use each method in practice with the following pandas DataFrame:
import pandas as pd
#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'],
'points': [12, 14, 14, 16, 24, 26, 28, 30, 31, 35],
'assists': [2, 2, 3, 3, 4, 6, 7, 8, 10, 15]})
#view DataFrame
print(df)
team points assists
0 A 12 2
1 B 14 2
2 C 14 3
3 D 16 3
4 E 24 4
5 F 26 6
6 G 28 7
7 H 30 8
8 I 31 10
9 J 35 15
Example 1: Calculate Quartiles for One Column
The following code shows how to calculate the quartiles for the points column only:
#calculate quartiles for points column
df['points'].quantile([0.25, 0.5, 0.75])
0.25 14.5
0.50 25.0
0.75 29.5
Name: points, dtype: float64
From the output we can see:
- The first quartile is located at 14.5.
- The second quartile is located at 25.
- The third quartile is located at 29.5.
By only knowing these three values, we have a pretty good idea of how the values are distributed in the points column.
Example 2: Calculate Quartiles for Each Numeric Column
The following code shows how to calculate the quartiles for each numeric column in the DataFrame:
#calculate quartiles for each numeric column in DataFrame
df.quantile(q=[0.25, 0.5, 0.75], axis=0, numeric_only=True)
points assists
0.25 14.5 3.00
0.50 25.0 5.00
0.75 29.5 7.75
The output displays the quartiles for the two numeric columns in the DataFrame.
Note that there is more than one way to calculate quartiles for a distribution.
Refer to the pandas documentation page to see the various methods that the pandas quantile() function uses to calculate quartiles.
Additional Resources
The following tutorials explain how to perform other common tasks in pandas:
How to Calculate Percent Change in Pandas
How to Calculate Cumulative Percentage in Pandas
How to Calculate Percentage of Total Within Group in Pandas
