Apply definition on multiple columns based on conditions- python

Question

i have dataframe that i want when one column equal to '02' apply the definition to 5 others columns. this is my code:

mask = (df['A']=='02')
z_valid = df[mask]
df.loc[((mask) & (df['B'] !=0)), 'B'] = z_valid['B'].apply(def)
df.loc[((mask) & (df['C'] !=0)), 'C'] = z_valid['C'].apply(def)
df.loc[((mask) & (df['D'] !=0)), 'D'] = z_valid['D'].apply(def)
df.loc[((mask) & (df['E'] !=0)), 'E'] = z_valid['E'].apply(def)
df.loc[((mask) & (df['F'] !=0)), 'F'] = z_valid['F'].apply(def)

i got this error: 'ValueError: Must have equal len keys and value when setting with an iterable'

but this code works when i apply def just on 2 columns:

mask = (df['A']=='02')
z_valid = df[mask]
df.loc[((mask) & (df['B'] !=0)), 'B'] = z_valid['B'].apply(def)
df.loc[((mask) & (df['C'] !=0)), 'C'] = z_valid['C'].apply(def)

how can i fix this error? thanks in advance.

please provide a meaningful reproducible example of your inputs and the matching expected output — mozway
– mozway, Commented Jun 7, 2023 at 9:20
Note: def has a specific usage in Python and is a reserved keyword. So not an appropriate name for a function to apply. — user19077881
– user19077881, Commented Jun 7, 2023 at 10:04
Hello so.n. Was my answer useful or do you still need help doing what you need? — user19077881
– user19077881, Commented Jun 14, 2023 at 16:40

Corralien · Accepted Answer · 2023-06-07 10:02:16Z

1

It raised an exception because 'D' is an empty Series:

Suppose the following dataframe:

df = pd.DataFrame({'A': ['01', '02', '02', '02'], 'B': [9, 1, 2, 3], 'C': [9, 1, 2, 3], 'D': [9, 0, 0, 0]})
print(df)

# Output:
    A  B  C  D
0  01  9  9  9
1  02  1  1  0
2  02  2  2  0
3  02  3  3  0

Now if I try your code:

def f(sr):
    return 2*sr

mask = (df['A']=='02')
z_valid = df[mask]
df.loc[((mask) & (df['B'] !=0)), 'B'] = z_valid['B'].apply(f)
df.loc[((mask) & (df['C'] !=0)), 'C'] = z_valid['C'].apply(f)
df.loc[((mask) & (df['D'] !=0)), 'D'] = z_valid['D'].apply(f)

Output:

----> 8 df.loc[((mask) & (df['D'] !=0)), 'D'] = z_valid['D'].apply(f)
...
ValueError: Must have equal len keys and value when setting with an iterable

The exception is raised on 'D':

# Left side
>>> df.loc[((mask) & (df['D'] !=0)), 'D']
Series([], Name: E, dtype: int64)  # <- Empty Series

# Right side
>>> z_valid['D'].apply(f)
1    0
2    0
3    0
Name: E, dtype: int64

answered Jun 7, 2023 at 10:02

Corralien

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1 Comment

so.n Over a year ago

I check my Dataframe, and you are right, when i apply the conditions the Left side is empty because of that i get the error. thanks alot

user19077881 · Accepted Answer · 2023-06-09 09:24:46Z

0

If I understand the requirement you can used .where and .applymap as in the example below:

import pandas as pd

df = pd.DataFrame({"x" : ['01', '02', '03', '04', '02', '05', '02'],
                  "y": [3,3,3,3,3,3,3],
                   'z': [6,6, 6, 6, 6, 6, 6]
                  })
cols = ['y', 'z']

def func(x):
    return 2*x

df[cols] = df[cols].where(df['x'] != '02', df[cols].applymap(func))

print(df)

which gives:

    x  y   z
0  01  3   6
1  02  6  12
2  03  3   6
3  04  3   6
4  02  6  12
5  05  3   6
6  02  6  12

edited Jun 9, 2023 at 9:24

answered Jun 7, 2023 at 10:30

user19077881

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