Trying to drop NaN indexed row in dataframe

Question

I'm using python 2.7.3 and Pandas version 0.12.0.

I want to drop the row with the NaN index so that I only have valid site_id values.

print df.head()             special_name site_id NaN          Banana OMG          Apple  df.drop(df.index[0])  TypeError: 'NoneType' object is not iterable 

If I try dropping a range, like this:

df.drop(df.index[0:1]) 

I get this error:

AttributeError: 'DataFrame' object has no attribute 'special_name' 

Answer 1

With pandas version >= 0.20.0 you can:

df = df[df.index.notnull()] 

With older versions:

df = df[pandas.notnull(df.index)] 

To break it down:

notnull generates a boolean mask, e.g. [False, False, True], where True denotes the value at the corresponding position is null (numpy.nan or None). We then select the rows whose index corresponds to a true value in the mask by using df[boolean_mask].