Level NaN must be same as name

Question

I am trying to count how many times NaN appears in a column of a dataframe using this code:

count = enron_df.loc['salary'].count('NaN')

But every time i run this i get the following error:

KeyError: 'Level NaN must be same as name (None)'

I searched around the web a lot trying to find a solution, but to no avail.

Answer 1

If NaNs are missing values:

enron_df = pd.DataFrame({'salary':[np.nan, np.nan, 1, 5, 7]})
print (enron_df)
   salary
0     NaN
1     NaN
2     1.0
3     5.0
4     7.0

count = enron_df['salary'].isna().sum()
#alternative
#count = enron_df['salary'].isnull().sum()
print (count)
2

If NaNs are strings:

enron_df = pd.DataFrame({'salary':['NaN', 'NaN', 1, 5, 'NaN']})
print (enron_df)
  salary
0    NaN
1    NaN
2      1
3      5
4    NaN

count = enron_df['salary'].eq('NaN').sum()
#alternative
#count = (enron_df['salary'] == 'NaN').sum()
print (count)
3

Answer 2

Try like this:

count = df.loc[df['salary']=='NaN'].shape[0]

Or maybe better:

count = df.loc[df['salary']=='NaN', 'salary'].size

And, going down your path, you'd need something like this:

count = df.loc[:, 'salary'].str.count('NaN').sum()