Convert string hours to minute pd.eval-CodePudding

I want to convert all rows of my DataFrame that contains hours and minutes into minutes only. I have a dataframe that looks like this:

I'm using the following method to convert:

df['time'] = pd.eval(
    df['time'].replace(['h'], ['*60 '], regex=True))

Output

SyntaxError: invalid syntax

I think the error comes from the format of the hour, maybe pd.evalcant accept 08h30 or 8h0, how to solve this probleme ?

CodePudding user response：

To avoid having to trim leading zeros, an alternative approach:

df[['h', 'm']] = df['time'].str.split('h', expand=True).astype(int)
df['total_min'] = df['h']*60   df['m']

Result:

    time   h   m      total_min
0   8h30   8  30            510
1  14h07  14   7            847
2  08h30   8  30            510
3   7h50   7  50            470
4    8h0   8   0            480
5   8h15   8  15            495
6   6h15   6  15            375

CodePudding user response：

Pandas can already handle such strings if the units are included in the string. While 14h07 can't be parse (why assume 07 is minutes?), 14h07 can be converted to a Timedelta :

>>> pd.to_timedelta("14h07m")
Timedelta('0 days 14:07:00')

Given this dataframe :

d1 = pd.DataFrame(['8h30m', '14h07m', '08h30m', '8h0m'],
                  columns=['time'])

You can convert the time series into a Timedelta series with pd.to_timedelta :

>>> d1['tm'] = pd.to_timedelta(d1['time'])
>>> d1
     time              tm
0   8h30m 0 days 08:30:00
1  14h07m 0 days 14:07:00
2  08h30m 0 days 08:30:00
3    8h0m 0 days 08:00:00

To handle the missing minutes unit in the original data, just append m:

d1['tm'] = pd.to_timedelta(d1['time']   'm')

Once you have a Timedelta you can calculate hours and minutes.

The components of the values can be retrieved with Timedelta.components

>>> d1.tm.dt.components.hours
0     8
1    14
2     8
3     8
Name: hours, dtype: int64

To get the total minutes, seconds or hours, change the frequency to minutes:

>>> d1.tm.astype('timedelta64[m]')
0    510.0
1    847.0
2    510.0
3    480.0
Name: tm, dtype: float64

Bringing all the operations together :

>>> d1['tm'] = pd.to_timedelta(d1['time'])
>>> d2 = (d1.assign(h=d1.tm.dt.components.hours,
...                 m=d1.tm.dt.components.minutes,
...                 total_minutes=d1.tm.astype('timedelta64[m]')))
>>>
>>> d2
     time              tm   h   m  total_minutes
0   8h30m 0 days 08:30:00   8  30          510.0
1  14h07m 0 days 14:07:00  14   7          847.0
2  08h30m 0 days 08:30:00   8  30          510.0
3    8h0m 0 days 08:00:00   8   0          480.0