Numpy select returning boolean error message

Question

I would like to find matching strings in a path and use np.select to create a new column with labels dependant on the matches I found.

This is what I have written

Answer 1

The .str methods operate on object columns. It's possible to have non-string values in such columns, and as a result pandas returns NaN for these rows instead of False. np then complains because this is not a Boolean.

Luckily, there's an argument to handle this: na=False

a["properties_path"].str.contains('blog', na=False)

Alternatively, you could change your conditions to:

a["properties_path"].str.contains('blog') == True
#or
a["properties_path"].str.contains('blog').fillna(False)

---

Sample

import pandas as pd
import numpy as np

df = pd.DataFrame({'a': [1, 'foo', 'bar']})
conds = df.a.str.contains('f')
#0      NaN
#1     True
#2    False
#Name: a, dtype: object

np.select([conds], ['XX'])
#ValueError: invalid entry 0 in condlist: should be boolean ndarray

conds = df.a.str.contains('f', na=False)
#0    False
#1     True
#2    False
#Name: a, dtype: bool

np.select([conds], ['XX'])
#array(['0', 'XX', '0'], dtype='<U11')

Answer 2

Your data seem to have nan, so conditions have nan, which breaks np.select. To fix this, you can do:

s = a["properties_path"].fillna('')

and replace a['properties_path'] in each condition with s.