From a dataframe when I print data['words'].values
I get,
['from' 'fairest' 'creatures' 'we' 'desire' 'increase' nan 'that' 'thereby']
When I loop through like this how do I identify if the value is nan?
for w in data['words'].values:
check if w is nan ????
Detect missing values for an array-like object. This function takes a scalar or array-like object and indicates whether values are missing ( NaN in numeric arrays, None or NaN in object arrays, NaT in datetimelike).
The official documentation for pandas defines what most developers would know as null values as missing or missing data in pandas. Within pandas, a missing value is denoted by NaN .
Use the pandas method isnull
to test:
In [45]:
df = pd.DataFrame({'words':['from', 'fairest', 'creatures' ,'we' ,'desire', 'increase' ,nan ,'that' ,'thereby']})
df
Out[45]:
words
0 from
1 fairest
2 creatures
3 we
4 desire
5 increase
6 NaN
7 that
8 thereby
In [46]:
pd.isnull(df['words'])
Out[46]:
0 False
1 False
2 False
3 False
4 False
5 False
6 True
7 False
8 False
Name: words, dtype: bool
the question was about the if:
for i in range(150,160):
if (pd.isnull(df['Text'][i])):
print('is null')
or count all NaN:
cnt=0
for i in range(len(dframe)):
if (pd.isnull(dframe['Description'][i])):
cnt+=1
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