How to maintain order when selecting rows in pandas dataframe?

Question

I want to select rows in a particular order given in a list. For example

This dataframe

a=[['car',1],['bike',3],['jewel',2],['tv',5],['phone',6]]

df=pd.DataFrame(a,columns=['items','quantity'])

>>> df
   items  quantity
0    car         1
1   bike         3
2  jewel         2
3     tv         5
4  phone         6

I want to get the rows with this order ['tv','car','phone'], that is, first row tv and then car and then phone. I tried this method but it doesn't maintain order

arr=['tv','car','phone']

df.loc[df['items'].isin(arr)]

   items  quantity
0    car         1
3     tv         5
4  phone         6

Answer 1

Here's a non-intrusive solution using Index.get_indexer that doesn't involve setting the index:

df.iloc[pd.Index(df['items']).get_indexer(['tv','car','phone'])]

   items  quantity
3     tv         5
0    car         1
4  phone         6

Note that if this is going to become a frequent thing (by thing, I mean "indexing" with a list on a column), you're better off turning that column into an index. Bonus points if you sort it.

df2 = df.set_index('items')
df2.loc[['tv','car','phone']]  

       quantity
items          
tv            5
car           1
phone         6