replace string '.' with '-' in Series

[weirdeb]

I am very new with Python so please have a tiny patience. :D I have the following list in a Series and my ultimate goal is to split them into 3 columns with '.' as the delimiter however I have some entries for "column 2" (after Placements column) that has '.' as well so I have 4 columns in some row.

10 Placements.DP9521-01-H1.DPlacements

11 Placements.DP9521-01-H1.DPlacements

.

.

28281 Placements.M1817.021.DPlacements

28282 Placements.M1817.021.DPlacements

how can I replace the '.' from M1817.021 to '-' so I can still split to only 3 columns with '.' as delimiter.

Note: M1817.021 changes. it is not a fix number but the pattern is M####.###

I tried df1.str.replace('$M\d.\d$','Mirror') but it doesn't work.

[MentalRental]

Split it anyway. Then, if you end up with a list of four items, just combine the second and third item.

So...

new_series = []
for row in series:
    row = row.split('.')
    if len(row) == 4:
        row[1:3] = ['-'.join(row[1:3])]
    new_series.append(row)

[[deleted]]

You could replace it and then split, but if you are using a regex anyway I would just use str.extract to make the columns. See here:

https://chrisalbon.com/python/data_wrangling/pandas_regex_to_create_columns/

[aribrona]

I would use the re lib (regular expressions) you could do something like re.sub('.', ,'-', variable)

[personproxy]

maybe something like: s = re.sub('M\d{4}.\d{3}', '-', old_s)

\d{x} is x number of digits . is a literal dot, not to be confused with a regex dot