PYTHON

select rows which have nan values python

df[df['column name'].isna()]

dataframe find nan rows

df[df.isnull().any(axis=1)]

select rows with nan pandas

df[df['Col2'].isnull()]

count rows with nan pandas

 np.count_nonzero(df.isnull().values)   
 np.count_nonzero(df.isnull())           # also works  

select rows which have nan values python

df[df['column name'].isnull()]

Select rows without NaN in specific column

selected_rows = df[~df['Age'].isnull()]

pandas where retuning NaN

# Try using a loc instead of a where:
df_sub = df.loc[df.yourcolumn == 'yourvalue']

pandas select nan value in a column

df[df["A_col"].isnull()]