Fill NAs in a Column with samples from itself

Question

Simple toy dataframe:

df = pd.DataFrame({'mycol':['foo','bar','hello','there',np.nan,np.nan,np.nan,'foo'],
                  'mycol2':'this is here to make it a DF'.split()})
print(df)

   mycol mycol2
0    foo   this
1    bar     is
2  hello   here
3  there     to
4    NaN   make
5    NaN     it
6    NaN      a
7    foo     DF

I'm trying to fill the NaNs in mycol with samples from itself, e.g. I want the NaNs to be replaced with samples of foo,bar,hello etc.

# fill NA values with n samples (n= number of NAs) from df['mycol']

df['mycol'].fillna(df['mycol'].sample(n=df.isna().sum(), random_state=1,replace=True).values)

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

# fill NA values with n samples, n=1. Dropna from df['mycol'] before sampling:

df['mycol'] = df['mycol'].fillna(df['mycol'].dropna().sample(n=1, random_state=1,replace=True)).values

# nothing happens

Expected Output: Nas filled with random samples from mycol:

   mycol mycol2
0    foo   this
1    bar     is
2  hello   here
3  there     to
4    foo   make
5    foo     it
6  hello      a
7    foo     DF

edit for answer: @Jezrael's answer below sorted it, I had a problem with my indexes.

df['mycol'] = (df['mycol'] 
               .dropna()
               .sample(n=len(df),replace=True) 
               .reset_index(drop=True))

Answer 1

Interesting problem.

For me working set values with loc with converting values to numpy array for avoid data alignment:

a = df['mycol'].dropna().sample(n=df['mycol'].isna().sum(), random_state=1,replace=True)
print (a)
3    there
7      foo
0      foo
Name: mycol, dtype: object

#pandas 0.24+
df.loc[df['mycol'].isna(), 'mycol'] = a.to_numpy()
#pandas below
#df.loc[df['mycol'].isna(), 'mycol'] = a.values
print (df)
   mycol mycol2
0    foo   this
1    bar     is
2  hello   here
3  there     to
4  there   make
5    foo     it
6    foo      a
7    foo     DF

Your solution should working if length of Series and index same like original DataFrame:

s = df['mycol'].dropna().sample(n=len(df), random_state=1,replace=True)
s.index = df.index
print (s)
0    there
1      foo
2      foo
3      bar
4    there
5      foo
6      foo
7      bar
Name: mycol, dtype: object

df['mycol'] = df['mycol'].fillna(s)
print (df)

#   mycol mycol2
0    foo   this
1    bar     is
2  hello   here
3  there     to
4  there   make
5    foo     it
6    foo      a
7    foo     DF