How do I successfully create ordered categorical data from an existing column?

Here's a dataframe - 'dist_copy' - with values I would like to change to categorical. I've only included one column, but there are additional columns I want to convert as well.

state	dist_id	pct_free_reduced_lunch
Illinois	1111	80% - 100%
Illinois	1112	0 - 20%
Illinois	2365	40% - 60%

dist_copy.pct_free_reduced_lunch.unique()

returns

array(['80% - 100%', '60% - 80%', '0 - 20%', '20% - 40%', '40% - 60%'], dtype=object)

Previously, I used pd.Categorical to change all the values in the 'pct_free_reduced_lunch' column to 'categorical', and established the order, with this code:

dist_copy['pct_free_reduced_lunch'] = pd.Categorical(dist_copy['pct_free_reduced_lunch'], 
     categories=['0 — 20%','20% — 40%', '40% — 60%', '60% — 80%',  '80% - 100%'], ordered=True)

Today, this code isn't working, and only retains the first value, changing all other values to NaN.

state	dist_id	pct_free_reduced_lunch
Illinois	1111	80% - 100%
Illinois	1112	NaN
Illinois	2365	NaN

What am I doing wrong, or misunderstanding?

UPDATE: The above code began to work AFTER I copy-pasted each categorical value from the array returned by unique() into the categories array inside the pd.Categorical function, in the desired order.

When I merely entered them from scratch, NaNs were created.

WHY? I would really love to know!

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