Subset pandas dataframe using function applied to a column/series

user_5905425 0
Viewed 231

I have a pandas dataframe df that I would like to subset based on the result of running Name through a certain function is_valid()

import pandas as pd

data = [['foo', 10], ['baar', 15], ['baz', 14]]
df = pd.DataFrame(data, columns = ['name', 'age'])
df

    name    age
0   foo     10
1   baar    15
2   baz     14

The function checks if the length of the input string is 3 and returns either True or False:

def is_valid(x):
    assert isinstance(x, str)
    return True if len(x) == 3 else False

My goal is to subset df where this function returns True, which would return an output of

    name    age
0   foo     10
2   baz     14

The following syntax returns an error; what is the correct syntax for applying a function to values of a column (series) and subsetting a dataframe if the output meets a condition (in this case = True) ?

df[is_valid(df['name'])]
pandas subset dataframe lambda python
2 Answers

Try:

df[df['name'].str.len()==3]

Or use your code with apply:

df[df['name'].apply(is_valid)]
user_42384080

Use Series.str.len with Series.eq for mask:

df = df[df['name'].str.len().eq(3)]

Or use Series.apply for pass custom function:

df = df[df['name'].apply(is_valid)]
print (df)
  name  age
0  foo   10
2  baz   14
user_29010020
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