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Pandas: Replace current value in a dataframe column based on last largest value

Pandas: DataFrame Exercise-78 with Solution

Write a Pandas program to replace the current value in a dataframe column based on last largest value. If the current value is less than last largest value replaces the value with 0.

Test data: rnum
0 23
1 21
2 27
3 22
4 34
5 33
6 34
7 31
8 25
9 22
10 34
11 19
12 31
13 32
14 19

Sample Solution :

Python Code :

import pandas as pd
df1=pd.DataFrame({'rnum':[23, 21, 27, 22, 34, 33, 34, 31, 25, 22, 34, 19, 31, 32, 19]})
print("Original DataFrame:")
print(df1)
df1['rnum']=df1.rnum.where(df1.rnum.eq(df1.rnum.cummax()),0)
print("\nReplace current value in a dataframe column based on last largest value:")
print(df1)

Sample Output:

Original DataFrame:
    rnum
0     23
1     21
2     27
3     22
4     34
5     33
6     34
7     31
8     25
9     22
10    34
11    19
12    31
13    32
14    19

Replace current value in a dataframe column based on last largest value:
    rnum
0     23
1      0
2     27
3      0
4     34
5      0
6     34
7      0
8      0
9      0
10    34
11     0
12     0
13     0
14     0

Python Code Editor:


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Next: Write a Pandas program to create a DataFrame from the clipboard (data from an Excel spreadsheet or a Google Sheet).

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Python: Tips of the Day

Dictionary comprehension:

>>> m = {x: x ** 2 for x in range(5)}
>>> m
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