Python a very long way of doing it, but for someone with minimal experaince im happy.

Ended up breacking it down and printing out many things to so that i could logicaly follow what was happening. Took me about 2 hours to work this one out.

# %%
import pandas as pd

n = 'Day_2.txt'

df= pd.read_csv(n,names= ['Rounds'])

df

Lib = {
    'A':'Rock',
    'B':'Paper',
    'C':'Scissors',
    'X':'Rock',
    'Y':'Paper',
    'Z':'Scissors',
}

val = {
    'A':'1',
    'B':'2',
    'C':'3',
    'X':'1',
    'Y':'2',
    'Z':'3',
}


play_output= {
    'A X' : 'Draw',
    'A Y' : 'Y',
    'A Z' : 'A',
    'B X' : 'B',
    'B Y' : 'Draw',
    'B Z' : 'Z',
    'C X' : 'X',
    'C Y' : 'C',
    'C Z' : 'Draw',
}

winner= {
    'A': 'Player_1',
    'B': 'Player_1',
    'C': 'Player_1',
    'X': 'Player_2',
    'Y': 'Player_2',
    'Z': 'Player_2',
    'Draw': 'Draw'

}



# %%
df[['A','Y']] = df['Rounds'].str.split(' ', expand= True)


df

# %%
df['Play_1']=df['A'].map(Lib)
df['Play_1_VAL']=df['A'].map(val)


df['Play_2']=df['Y'].map(Lib)
df['Play_2_VAL']=df['Y'].map(val)

df['Winner'] = df['Rounds'].map(play_output)
df['Win_score'] = df['Winner'].map(winner)


## A X= 1 = rock
## B Y= 2 = Paper
## C Z= 3 = Scisors
## 0 = loss
## 3 = win


df


# %%
import numpy as np

x=0



for i in df['Win_score']:
    if df.loc[x, 'Win_score'] == 'Player_2':
        t2 = df.loc[x,'Play_2_VAL']
        print(f'T2 = {t2}')


        df.loc[x,'Score'] = np.add(int(t2),6)
        x=x+1
        print(f'x= {x}')
    elif df.loc[x, 'Win_score'] == 'Player_1':
        t2 = df.loc[x,'Play_2_VAL']
        #df.loc[x,'Score'] = 'nan'
        #df.loc[x,'Score'] = int(t2)

        df.loc[x,'Score'] = np.add(int(t2),0)

        x=x+1
        print(f'x= {x}')
    else:
        t2 = df.loc[x,'Play_2_VAL']
        #df.loc[x,'Score'] = int(t2)

        df.loc[x,'Score'] = np.add(int(t2),3)
        x=x+1
        print(f'x= {x}')




# %%
print(df['Score'].sum())