Custom-Function-As-Lambda

title: "Custom Function as Lambda" author: "Rj" date: 2019-04-22 description: "-" type: technical_note draft: false

import numpy as np
import pandas as pd

def apply_math_special(row):
    return (row.maths *2 + (row.language/2) + (row.history/3) + (row.science/4))

df = pd.read_csv('abc.csv')

df

	student	language	science	maths	history
0	kumar	90	56	34	34
1	kevin	10	34	32	67
2	sammy	90	23	12	32
3	janice	20	67	90	45
4	peter	30	56	45	65
5	prem	90	45	45	34
6	carrol	50	90	45	23

df['math_special'] = df.apply(apply_math_special, axis=1).astype(int)

df

	student	language	science	maths	history	math_special
0	kumar	90	56	34	34	138
1	kevin	10	34	32	67	99
2	sammy	90	23	12	32	85
3	janice	20	67	90	45	221
4	peter	30	56	45	65	140
5	prem	90	45	45	34	157
6	carrol	50	90	45	23	145

We just doubled the math marks and reduced the marks of other subjects by 2, 3, 4 and then assigned the new value as a new column

Score: 5

Category: data-wrangling