python - compare value with panda groupby, multiple rows

Question

pic1

I have a dataframe that have an identical value in the column of "code" for every two rows.

I want to create a column name ['test'] on the far right side that compares the value of "V" from every groupby ['code'] and return true or false in the column of ['test']

for example,

I want to compare the value in "V"(30367315) in the first "code" of 0050 to the vale of "V"(14029981) with the second value of "0050"

0050 if 30367315 > 14029981, ['test'] return true.

0051 if 56966 > 46687, ['test'] return true.

0052 if 2447344 > 2798834, ['test'] return false.

here is what've tried:

container=[]
for _df in td2.groupby(['code']):
    _df = pd.DataFrame(_df)
    num1 = _df.iloc[1,0]
    num2 = _df.iloc[1,1]
    _df['test'] = num2 > num1
    container.append(_df)
    ch_ = pd.concat(container)

this is expected result: pic2

Today, my result returned as

IndexError: single positional indexer is out-of-bounds

but the other day I tried this code, it worked. I am not sure what I did. My jupyter notebook autosaved, and I must have touch the code somewhere and I can't figure it out why.

Answer 1

等待大神解答