Dropping rows in pandas with .index

Question

I came across the below line of code, which gives an error when '.index' is not present in it.

print(df.drop(df[df['Quantity'] == 0].index).rename(columns={'Weight': 'Weight (oz.)'}))

What is the purpose of '.index' while using drop in pandas?

Answer 1

As explained in the documentation, you can use drop with index:

   A  B   C   D
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11

df.drop([0, 1]) # Here 0 and 1 are the index of the rows

Output:

   A  B   C   D
2  8  9  10  11

In this case it will drop the first 2 rows. With .index in your example, you find the rows where Quantity=0and retrieve their index(and then use like in the documentation)