Importing Packages and Datasets
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.rand(4, 3)*100,
columns=['Physics','Çhemistry','Maths'],
index = ['Student 1', 'Student 2','Student 3','Student 4'])
data
| Physics | Çhemistry | Maths |
|---|
| Student 1 | 59.488944 | 14.888411 | 52.794760 |
|---|
| Student 2 | 21.872113 | 66.481646 | 87.190572 |
|---|
| Student 3 | 9.885919 | 54.449674 | 58.696036 |
|---|
| Student 4 | 33.804378 | 6.286295 | 30.373699 |
|---|
Applymap
RoundUpto2Decimal = lambda x: round(x,2)
data.applymap(RoundUpto2Decimal)
| Physics | Çhemistry | Maths |
|---|
| Student 1 | 59.49 | 14.89 | 52.79 |
|---|
| Student 2 | 21.87 | 66.48 | 87.19 |
|---|
| Student 3 | 9.89 | 54.45 | 58.70 |
|---|
| Student 4 | 33.80 | 6.29 | 30.37 |
|---|
Apply
AverageMarks = lambda x: np.mean(x)
data.apply(AverageMarks)
Physics 31.262839
Çhemistry 35.526506
Maths 57.263767
dtype: float64
data.apply(AverageMarks,axis = 1)
Student 1 42.390705
Student 2 58.514777
Student 3 41.010543
Student 4 23.488124
dtype: float64
data.apply(lambda x: (x-np.min(x))/(np.max(x)-np.min(x)))
| Physics | Çhemistry | Maths |
|---|
| Student 1 | 1.000000 | 0.142903 | 0.394620 |
|---|
| Student 2 | 0.241642 | 1.000000 | 1.000000 |
|---|
| Student 3 | 0.000000 | 0.800118 | 0.498485 |
|---|
| Student 4 | 0.482198 | 0.000000 | 0.000000 |
|---|
Map
SquareOfMarks = lambda x: x**2
data['Physics'].map(SquareOfMarks)
Student 1 3538.934482
Student 2 478.389328
Student 3 97.731389
Student 4 1142.735997
Name: Physics, dtype: float64
Notebook Link - Applying functions over pandas dataframe using apply, applymap and map