Calculating Quartile

The quantile() method on a DataFrame is the tool for calculating quartiles. A quartile divides a sorted dataset into four equal parts. The method takes a parameter q that specifies which quartile you want. The first quartile (Q1) corresponds to q = 0.25 — it marks the value below which 25% of the data falls. The second quartile (Q2) is the median, given by q = 0.50. The third quartile (Q3) is q = 0.75, below which 75% of the data lies.

If you call df.quantile() with no argument, it defaults to q = 0.5 and returns the median of every numeric column. For example, on a DataFrame df containing marks for five subjects, df.quantile() would output the median marks for Maths, Science, S.St, Hindi, and English.

To get a specific quartile, pass the q parameter. df.quantile(q=0.25) gives the first quartile for each column. df.quantile(q=0.75) gives the third quartile. The output is a Series with the column names as the index and the quartile value as the data, labelled with the q value you used.

You can also pass a list of quartiles to q to get multiple quartiles at once. For instance, dfSubject.quantile([0.25, 0.75]) returns a DataFrame where the rows are labelled 0.25 and 0.75, and the columns are the subject names. Each cell contains the corresponding quartile value for that subject.