A quartile divides ordered numeric observations into four equal parts. Pandas describe() reports the three commonly used cut points: Q1 at 25%, Q2 at 50%, and Q3 at 75%. section 4.2.1
Use quartiles to inspect the distribution of numeric columns alongside other summary measures:
- Q1 marks the 25th percentile, Q2 the median, and Q3 the 75th percentile. section 4.2.1
- Quartiles complement the mean, standard deviation, minimum, and maximum when visual inspection alone is insufficient. section 4.2.1
Pandas summary
For the 20-record mds dataset, describe() reports stage1 quartiles of 165.75, 190.00, and 221.25, and stage2 quartiles of 199.00, 255.00, and 289.00. section 4.2.1
>>> import pandas as pd
>>> mds = pd.read_csv('mds.csv')
Load the dataset with pandas before computing quartiles through describe(). section 4.2.1
