Python script summary data separate by col

Question

I want to count the data base on certain column follow the condition from another columns.

Raw data:

Time	Lot	Error
1:00	A	X
2:00	A	X
2:12	B	X
2:30	B	Y
4:29	C	Z

Desired data show:

Lot	Error	Count
A	X	2
B	X	1
B	Y	1
C	Z	1

I tried using by "groupby" and "pivot" but it not work.

table = df.groupby(['Lot', 'Name']).sum('Name')

Answer 1

Try count(), for both columns.

df.groupby(['Lot', 'Error']).count()

Output Lot Error

A   X         2
B   X         1
    Y         1
C   Z         1

Also, if you need all the indexes that you have given, then you can do this:

df1 = df.groupby(['Lot', 'Error']).count().reset_index()
df1.rename(columns={'Time': 'count'}, inplace=True)

Output

  Lot Error  count
0   A     X      2
1   B     X      1
2   B     Y      1
3   C     Z      1