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

Last update on April 03 2025 13:11:36 (UTC/GMT +8 hours)

78. Replace Value Based on Last Largest Value

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

For more Practice: Solve these Related Problems:

Write a Pandas program to iterate through a column and replace any value lower than the maximum seen so far with zero.
Write a Pandas program to update a column such that if the current value is less than the previous maximum, it is set to a default value.
Write a Pandas program to compare each value with the cumulative maximum of the column and then replace values that do not meet the criterion.
Write a Pandas program to compute the cumulative maximum of a column and then conditionally replace current values based on that maximum.

Python-Pandas Code Editor:

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