Strip strings in pandas columns

Question

I have a small dataframe with entries regarding motorsport balance of performance.

I try to get rid of the string after "@"

This is working fine with the code:

for col in df_engine.columns[1:]:
df_engine[col] = df_engine[col].str.rstrip(r"[ @ d.[0-9]+]")

but is leaving last column unchanged, and I do not understand why.
The Ferrari column also has a NaN entry as last position, just as additional info.

Can anyone provide some help?

Thank you in advance!

Asked By: Andrei Filep

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Source

Answer 1

rstrip does not work with regex. As per the documentation,

to_strip str or None, default None

Specifying the set of characters to
be removed. All combinations of this set of characters will be
stripped. If None then whitespaces are removed.

>>> "1.76 @ 0.88".rstrip("[ @ d.[0-9]+]")
'1.76 @ 0.88'
>>> "1.76 @ 0.88".rstrip("[ @ d.[0-8]+]") # It's not treated as regex, instead All combinations of characters(`[ @ d.[0-8]+]`) stripped
'1.76'

You could use the replace method instead.

for col in df.columns[1:]:
    df[col] = df[col].str.replace(r"s@s[d.]+$", "", regex=True)

Answered By: Abdul Niyas P M

Answer 2

What about str.split() ?
https://pandas.pydata.org/docs/reference/api/pandas.Series.str.split.html#pandas.Series.str.split

The function splits a serie in dataframe columns (when expand=True) using the separator provided.

The following example split the serie df_engine[col] and produce a dataframe. The first column of the new dataframe contains values preceding the first separator char ‘@’ found in the value

df_engine[col].str.split('@', expand=True)[0]

Answered By: Marco Vaccari

Strip strings in pandas columns

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