from string to timedelta in pandas

Question

I have a dataframe where the timestamp is in the format HHHHH:MM

timestamp = pd.Series([\'34:23\',\'125:26\',\'15234:52\'], index=index)

I

Answer 1

You can use pandas.Series.apply, i.e.:

def convert(args):
    return timedelta(hours=int(args[:-3]),minutes=int(args[-2:]))
s = pd.Series(['34:23','125:26','15234:52'])
s = s.apply(convert)

Answer 2

You can use column-wise Pandas methods:

s = pd.Series(['34:23','125:26','15234:52'])

v = s.str.split(':', expand=True).astype(int)
s = pd.to_timedelta(v[0], unit='h') + pd.to_timedelta(v[1], unit='m')

print(s)

0     1 days 10:23:00
1     5 days 05:26:00
2   634 days 18:52:00
dtype: timedelta64[ns]

Answer 3

Parse the delta in seconds as an argument to pd.to_timedelta like this,

In [1]: import pandas as pd
In [2]: ts = pd.Series(['34:23','125:26','15234:52'])
In [3]: secs = 60 * ts.apply(lambda x: 60*int(x[:-3]) + int(x[-2:]))
In [4]: pd.to_timedelta(secs, 's')
Out[4]:
0     1 days 10:23:00
1     5 days 05:26:00
2   634 days 18:52:00
dtype: timedelta64[ns]

Edit: missed erncyp's answer which would work as well but you need to multiply the argument to pd.to_timedelta by 60 since if I recall correctly minutes aren't an available as a measure of elapsed time except modulo the previous hour.

Answer 4

This is how I would do it:

timestamp = pd.Series(['34:23','125:26','15234:52'])
x = timestamp.str.split(":").apply(lambda x: int(x[0])*60 + int(x[1]))
timestamp = pd.to_timedelta(x, unit='s')