[FIXED] How to replace cost of an item with the previous cost of the same item in a dataframe using Pandas?

Issue

Suppose I have the following dataframe:

data = {'ID': ['A', 'B', 'C', 'A', 'C', 'O', 'B', 'A', 'B', 'O'], 'Item':['Apple','Banana','Carrot','Apple', 'Carrot', 'Orange', 'Banana', 'Apple', 'Banana', 'Orange'], 'Cost':[10, 12, 15, 13, 54, 20, 73, 22, 19, 32]}
dataframe = pd.DataFrame(data)
dataframe

And I want to replace the cost of the current item with the cost of the previous item using Pandas, with the first instance of each item being deleted. So the above dataframe would become

data2 = {'ID': ['A', 'C', 'B', 'A', 'B', 'O'], 'Item':['Apple', 'Carrot', 'Banana', 'Apple', 'Banana', 'Orange'], 'Cost':[10, 15, 12, 13, 73, 20]}
dataframe2 = pd.DataFrame(data2)
dataframe2 

What's a good way to do it?

Solution

You can use groupby on Item as well. This gives you output in the same order you expected

data['Cost'] = data.groupby('Item')['Cost'].shift(fill_value=0)
data[data['Cost'] != 0]

This gives us expected output:

  ID    Item  Cost
3  A   Apple    10
4  C  Carrot    15
6  B  Banana    12
7  A   Apple    13
8  B  Banana    73
9  O  Orange    20

Answered By - Himanshuman

Answer Checked By - Mary Flores (PHPFixing Volunteer)