How to match leading and trailing hyphen - regex

Question

I have a Pandas dataframe with decimal values like below.
'+' and '-' signs can either be leading or trailing.
df = pd.DataFrame({'amt': ['11.11', '+22.22', '33.33+', '-44.44', '55.55-', '66.66', '77.77', '8a8', '99', '97-9']})
df['amt']
0 11.11
1 +22.22
2 33.33+
3 -44.44
4 55.55-
5 66.66
6 77.77
7 8a8
8 99
9 97-9
Name: amt, dtype: object
My requirement is to:
Remove leading and trailing '+'
Move trailing '-' to leading '-'
This is what I have done so far:
abs_ser = pd.to_numeric(df['amt'].str.strip().str.strip('+|-'), errors='coerce')
abs_ser
0 11.11
1 22.22
2 33.33
3 44.44
4 55.55
5 66.66
6 77.77
7 NaN
8 99.00
9 NaN
Name: amt, dtype: float64
df['clean_amt'] = np.where(df['amt'].str.match(r'(^-|-$)'), abs_ser * -1, abs_ser)
df[['amt', 'clean_amt']]
amt clean_amt
0 11.11 11.11
1 +22.22 22.22
2 33.33+ 33.33
3 -44.44 -44.44
4 55.55- 55.55
5 66.66 66.66
6 77.77 77.77
7 8a8 NaN
8 99 99.00
9 97-9 NaN
The regular expression is not matching the trailing '-'.
Can someone help with correcting the regular expression?
I have tried the following and it gives me the desired result. However, I prefer the regex if it can do it in one pass of 'amt' column.
df['clean_amt'] = np.where((df['amt'].str.startswith('-') | df['amt'].str.endswith('-')), abs_ser * -1, abs_ser)

Answer 1

You can use
abs_ser = pd.to_numeric(df['amt'].str.strip().str.replace(r'^\+|\+$|^(.+)(-)$', r'\2\1'), errors='coerce')
See the regex demo.
Details
^\+ - finds a + at the start
\+$ - finds a + at the end
^(.+)(-)$ - captures any one or more chars at the start of the string (capturing the text into Group 1) and then captures a - at the end of the string into Group 2.
The replacement is the concatenated Group 2 and 1 values.

Answer 2

You could do the following:
# strip +
df['amt'] = df['amt'].str.strip('+')
# move -
mask = df['amt'].str.contains('-$')
df.loc[mask, 'amt'] = '-' + df.loc[mask, 'amt'].str.rstrip('-')
# transform to numeric
res = pd.to_numeric(df['amt'], errors='coerce')
print(res)
Output
0 11.11
1 22.22
2 33.33
3 -44.44
4 -55.55
5 66.66
6 77.77
7 NaN
8 99.00
9 NaN
Name: amt, dtype: float64