Get Column Value Based On Another Column With List Of Strings In Pandas Dataframe

I tried the link. But it doesnt work for my example given below. I tried the loc[0] for the output. I tried .item(). But none of these help me. >>> df2 = pd.DataFrame({ '

Solution 1:

I believe you need str for remove first and last [] or use str.strip:

mask = df2['Item'].str[1:-1] == 'Phone'#alternative solution#mask = df2['Item'].str.strip('[]') == 'Phone'print (mask)
0True1False2False3False4False
Name: Item, dtype: bool

If no missing values is possible use list comprehension, what is faster if large data:

mask = [x[1:-1] == 'Phone'for x in df2['Item']]

mask = [x.strip('[]') == 'Phone'for x in df2['Item']]
print (mask)

[True, False, False, False, False]

Last for select multiple columns use list:

df3 = df2.loc[mask, ['RelatedItem', 'CountinInventory']]
print (df3)
     RelatedItem CountinInventory
0  [Phone cover]               20

Solution 2:

You could also use:

df.loc[df['Item'].str.contains('Phone'), ['RelatedItem',  'CountinInventory']]

The error too many indexers is because df.loc[] expects an array of labels, list or slice object with labels. But you have given a sequence of 'labels'.