Slice Pandas dataframe by index values that are (not) in a list

Question

I have a pandas dataframe, df.

I want to select all indices in df that are not in a list, blacklist.

Now, I use list comprehension to create the desired labels to slice.

ix=[i for i in df.index if i not in blacklist]   df_select=df.loc[ix] 

Works fine, but may be clumsy if I need to do this often.

Is there a better way to do this?

Answer 1

Use isin on the index and invert the boolean index to perform label selection:

In [239]:  df = pd.DataFrame({'a':np.random.randn(5)}) df Out[239]:           a 0 -0.548275 1 -0.411741 2 -1.187369 3  1.028967 4 -2.755030 In [240]:  t = [2,4] df.loc[~df.index.isin(t)] Out[240]:           a 0 -0.548275 1 -0.411741 3  1.028967 

Answer 2

You could use set() to create the difference between your original indices and those that you want to remove:

df.loc[set(df.index) - set(blacklist)] 

It has the advantage of being parsimonious, as well as being easier to read than a list comprehension.