Pandas: Drop a row if it contains a condition

Question

I have a large dataframe and I need to exclude some rows containing a value that is a confound for me.

I have in mind a if statement nested in a for loop like this

for x in range (6655):
test = pseudoF2['Match'][x]

if test[:2].lower() == 'ab':
    pseudoF2.drop(test, inplace=True)

the problem is that I am constantly getting a key error "not found in axis"

just to have an idea, my dataframe is something like this:

Word    Match   Value1  Value2
1   Ab-art  Un-ans  1.95    0.15
2   Ab-art  An-ans  1.95    0.15
3   Ab-art  Um-ans  1.90    0.10
4   Ab-art  Tu-ort  2.15    0.35
5   Ab-drift    An-klift    2.90    0.25
(...)

Thank you for your help.

Answer 1

You can try regular expression to check whether there is ab in Match column, then you can drop those indices

As suggested by Jezreal more elegant solution

df[~df['Match'].str.contains(r'(?i)^ab')]

Old solution

df.drop(df[df['Match'].str.contains(r'(?i)^ab')].index, inplace=True)