how to make a for loop with multiple if conditions

I have a df (shape (5928, 22)) and I'm trying to create a new column and add values based on multiple conditions.

The conditions would be:

    if CH == 20 then value = 268,34
    if CH == 24 then value = 322,02
    if CH == 30 then value = 492,65
    if CH == 40 then value = 536,69

    and

    if CH == 20 & ID in (5105561300, 5105561301, 5105561302, 5105561304) then value = 417,43
    if CH == 24 & ID in (5105561300, 5105561301, 5105561302, 5105561304) then value = 500,91
    if CH == 30 & ID in (5105561300, 5105561301, 5105561302, 5105561304) then value = 626,34
    if CH == 40 & ID in (5105561300, 5105561301, 5105561302, 5105561304) then value = 834,85

When I try to add a new column and append the values based on the first block of conditions it works perfectly.

new_value = []

for row in df['CH']:
    if row == 20:
        new_value.append(268.34)
    elif row == 24:
        new_value.append(322.02)
    elif row == 30:
        new_value.append(402.65)
    elif row == 40:
        new_value.append(536.69)
    else:
        new_value.append(0)

df['new_value'] = new_value

When I tried to add other conditions it wont work. Code would be something like:

new_value = []

for row in df['CH']:
    if row == 20 and df['ID'] not in ((5105561300, 5105561301, 5105561302, 5105561304):
         new_value.append(268.34)
    elif row == 20 and df['ID'] in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(417.43)
    elif row == 24 and df['ID'] not in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(268.34)
    elif row == 24 and df['ID'] in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(500.91)
    elif row == 30 and df['ID'] not in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(268.34)
    elif row == 30 and df['ID'] in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(626.34)
    elif row == 40 and df['ID'] not in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(268.34)
    elif row == 40 and df['ID'] in ((5105561300, 5105561301, 5105561302, 5105561304):
        new_value.append(834.85)
    else:
        new_value.append(0)

    df['new_value'] = new_value

When I try the code above I get the following error message:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I don't know how to go from here. In SQL would two simple WHERE but I cannot get it to work in python.

I would appreciate any help!