How do I compare two columns in a Pandas DataFrame and output values from other columns based on the match?

So I have a pandas dataframe.

A: 3, 4, 1, 2, 1,
B 1, 2, 3, 4
C Red, Blue, Yellow, Green
D Yes, No, Maybe, True

what I want to be able to do is sequentially check column A against column B, if there is a match then output C and D relative to B.

For example the data frame above would be converted into
A Yellow, Green, Red, Blue, Red
B Maybe, True, Yes, No, Yes

I am rather new to python and pandas so I might be missing something simple here but I cannot think of solutions for this problem and am unsure where to start to find an answer. Any help would be appreciated

-Smoggs

Many various ideas. I know I should be using iloc to target the value in the cell, but I am unsure how to output the result next to it. I'm really at a loss here

First, if you need to index columns according to another (like here B relative to C and D), you can use the set_index method on B.

df = pd.DataFrame({
    "A": [3, 4, 1, 2],
    "B": [1, 2, 3, 4],
    "C": ["Red", "Blue", "Yellow", "Green"],
    "D": ["Yes", "No", "Maybe", True]
})

df.set_index("B", inplace=True)

Note the inplace parameter which directly perform changes on df variable.

Then, you can get C and D using A indices:

print(df.loc[df["A"]][["C", "D"]])
# output:
#         C      D
# B               
# 3  Yellow  Maybe
# 4   Green   True
# 1     Red    Yes
# 2    Blue     No

Note that we use loc and not iloc here. The difference is that loc will use the dataframe index (even if string are used) whereas iloc will use position in the underlying data array (see the doc here for more details).