I have this sample column:

Reference
A3V345 1/2
763SDDY 2/2
645BRW0 1OF4
645BRW0 2OF4
GRYUGBM-A
67AQSD-B
EW21Z31
4GH5477BM 1/3

I would like to create a new column where the result is the same value in the reference column with "-B, -A, 2OF4, 1OF4, 2/2, 1/2" removed or replaced with ""; the desired output would be this:

new_value
A3V345
763SDDY
645BRW0
645BRW0
GRYUGBM
67AQSD
EW21Z31
4GH5477BM

So far I have attempted at least three different things with different error messages in the output:

1. str.endswith and concatenation of strings to identify position and somehow slice value after True value in cell

output_table_1["new_value"] = output_table_1["Reference"].str.endswith((" 1/2", " 2/2", " 1/3", "1OF4", "2OF4", "-A", "-B"), na = False)
output_table_1["concat"] = output_table_1["Reference"] + str(output_table_1["new_value"])
output_table_1

The output is a long text I didn't expect to see, for instance, for 4GH5477BM this is the result:

4GH5477BM 1/30 False\n1 False\n2 False\n3 False\n4 False\n ... 

Cell expanded: 4GH5477BM 1/30 False\n1 False\n2 False\n3 False\n4 False\n ... \n1014 False\n1015 False\n1016 False\n1017 True\n1018 True\nName: new_value, Length: 1019, dtype: bool

2. str.replace if condition (only one parameter as example) applies

if output_table_1[output_table_1["Reference"].str.endswith(" 1/2", na=False)]:
    output_table_1["new_value"] = output_table_1["Reference"].apply(lambda x: x.replace(" 1/2", ""))
else:
    output_table_1["new_value"] = output_table_1["Reference"]
Output:
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

3. str.find to check position at the end of string

positionA = output_table_1["Reference"].str.len() - 4
positionB = output_table_1["Reference"].str.len()
output_table_1["set_value"] = output_table_1["Reference"].str.find(" 1/2", start = positionA, end = positionB)

The output is NaN for all the cells in that column, even though I believe it should return -1 if there was no match when searching the substring. Even if it worked, I still would be limited as it only accepts one string to search. As in the first try, I wanted to return the index where the occurrence happened and then use slicing to delete just before the searched substring.

I still lack skill in Python, more so in Pandas. Any help will be appreciated.