How to find out if a field is not empty('') and not null in a pandas dataframe?
I am using if not value and pd.notna(value):
Is it correct or there is a better API which handles this logic directly?
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2 Answers
You could replace fields with empty strings or containing only blank spaces with np.nan or None in your dataframe and then use notna to find valid values.
df.replace(r'^\s*$', np.nan, regex=True, inplace=True)
Moreover, if not value and pd.notna(value) does not work for an empty string or a field containing only blank spaces:
value = ''
not value and pd.notna(value) # this is True
value = None
not value and pd.notna(value) # this is False
value = np.nan
not value and pd.notna(value) # this is False
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How about changing empty value to NaN and then check. Kr.
df = pd.DataFrame({"a": [np.nan, 1, ""]})
df = df.replace('', np.nan)
print(df.isnull())
which returns:
a
0 True
1 False
2 True
Alternative is to fill NaN by empty '' then check:
df = pd.DataFrame({"a": [np.nan, 1, ""]})
df = df.fillna('')
print(df=='')
which returns:
a
0 True
1 False
2 True
Comments
