quantile python code example

Example 1: calculate percentile pandas dataframe

import pandas as pd
import random

A = [ random.randint(0,100) for i in range(10) ]
B = [ random.randint(0,100) for i in range(10) ]

df = pd.DataFrame({ 'field_A': A, 'field_B': B })
df
#    field_A  field_B
# 0       90       72
# 1       63       84
# 2       11       74
# 3       61       66
# 4       78       80
# 5       67       75
# 6       89       47
# 7       12       22
# 8       43        5
# 9       30       64

df.field_A.mean()   # Same as df['field_A'].mean()
# 54.399999999999999

df.field_A.median() 
# 62.0

# You can call `quantile(i)` to get the i'th quantile,
# where `i` should be a fractional number.

df.field_A.quantile(0.1) # 10th percentile
# 11.9

df.field_A.quantile(0.5) # same as median
# 62.0

df.field_A.quantile(0.9) # 90th percentile
# 89.10000000000001

Example 2: how to sort values of pandas dataframe for iqr

def mod_outlier(df):
        df1 = df.copy()
        df = df._get_numeric_data()


        q1 = df.quantile(0.25)
        q3 = df.quantile(0.75)

        iqr = q3 - q1

        lower_bound = q1 -(1.5 * iqr) 
        upper_bound = q3 +(1.5 * iqr)


        for col in col_vals:
            for i in range(0,len(df[col])):
                if df[col][i] < lower_bound[col]:            
                    df[col][i] = lower_bound[col]

                if df[col][i] > upper_bound[col]:            
                    df[col][i] = upper_bound[col]    


        for col in col_vals:
            df1[col] = df[col]

        return(df1)

Example 3: np.quantile

numpy.quantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False)

Example 4: calculate quantiles python

>>> np.percentile(df.time_diff, 25)  # Q1
0.48333300000000001

>>> np.percentile(df.time_diff, 50)  # Q2 (median)
0.5

>>> np.percentile(df.time_diff, 75)  # Q3
0.51666699999999999