The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() when using multiple conditions

Question

I just wanted to post this in case anyone else experiences this error. I was trying to filter on a previously filtered dataset, on multiple conditions when I received the above error.

As you can see from the sidebar, this `ambiguity` error has come up often. While the error mentions `any/and`, the actual fix depends on the context. It results from creating a boolean array (or Pandas Series) in a statement that expects a scalar boolean. Python `if, `and` and `or` are common problem contexts. Understanding the problem is the first step to fixing it. — hpaulj, Jun 14 '21 at 21:35

score 0 · Answer 1 · answered Jun 14 '21 at 20:22

After some searching and trial and error, I realized I had to use np.logical_and instead of the and.

bad code:

filter_RM = (boston_df_filtered_CHAS['RM'].values > 5 and boston_df_filtered_CHAS['RM'].values < 7.5)

boston_df_filtered_RM = boston_df_filtered_CHAS[filter_RM] boston_df_filtered_RM

good code:

    filter_RM = np.logical_and(boston_df_filtered_CHAS['RM'].values > 5, boston_df_filtered_CHAS['RM'].values < 7.5)

boston_df_filtered_RM = boston_df_filtered_CHAS[filter_RM] boston_df_filtered_RM

I hope this might be useful to someone.

The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() when using multiple conditions

1 Answers1