Effective Data Manipulation with pandas/

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Solution: Looping, Aggregation, and apply() Method

Solution: Looping, Aggregation, and apply() Method

See the solution to the problems related to looping, aggregation, and the apply() method.

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Problem 1: Solution

Given the following dataset:

100 56 17
12  23 1
49  3  65
32 19  41
99 100 41

Create a DataFrame named df. Loop over each row and calculate the maximum and minimum values.

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import numpy as np
import pandas as pd
 
matrix = [(100, 56, 17),
   (12, 23, 1),
   (49, 3, 65),
   (32, 19, 43),
   (99, 100, 41)
   ]
# Create a DataFrame
df = pd.DataFrame(matrix, index = list('abcde'), columns = list('xyz'))
# iterate through each row and select
 
for i in range(len(df)):
   print("max value in row", i,": ",max(df.iloc[i, 0], df.iloc[i,1], df.iloc[i, 2]))
   print("min value in row", i,": ",min(df.iloc[i, 0], df.iloc[i,1], df.iloc[i, 2]))
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