Time Deltas

Parsing



In [1]:

    
import pandas as pd
import numpy as np



In [2]:

    
pd.Timedelta('-3 days'), pd.Timedelta('13 min'), pd.Timedelta(1, unit='M')









    Out[2]:





(Timedelta('-3 days +00:00:00'),
 Timedelta('0 days 00:13:00'),
 Timedelta('30 days 10:29:06'))



In [3]:

    
pd.to_timedelta('2 days'), pd.to_timedelta(np.arange(10), unit='M')









    Out[3]:





(Timedelta('2 days 00:00:00'), <class 'pandas.tseries.tdi.TimedeltaIndex'>
 ['0 days 00:00:00', ..., '273 days 22:21:54']
 Length: 10, Freq: None)

Operations



In [4]:

    
df = pd.DataFrame(dict(A = pd.Series(pd.date_range('2014/1/1/', periods=3)), B = [pd.Timedelta(days=i + 1) for i in range(3)]))
df['C'] = df['A'] + df['B']
df['D'] = df['C'] - max(df['B'])
df['E'] = df['D'] + pd.tseries.offsets.Day(10)
df

Reductions



In [5]:

    
df['B'].mean()









    Out[5]:





Timedelta('2 days 00:00:00')



In [6]:

    
df['B'].sum()









    Out[6]:





Timedelta('6 days 00:00:00')

Frequency conversion



In [7]:

    
s = pd.Series([pd.Timedelta(days=np.random.randint(10)) for i in range(5)])
s









    Out[7]:





0   3 days
1   7 days
2   8 days
3   9 days
4   7 days
dtype: timedelta64[ns]



In [8]:

    
s / np.timedelta64(1, 'D')









    Out[8]:





0    3
1    7
2    8
3    9
4    7
dtype: float64



In [9]:

    
s.astype('timedelta64[D]')









    Out[9]:





0    3
1    7
2    8
3    9
4    7
dtype: float64

Attributes



In [10]:

    
s.dt.days









    Out[10]:





0    3
1    7
2    8
3    9
4    7
dtype: int64



In [11]:

    
s.dt.components









    Out[11]:






  
    
      
      days
      hours
      minutes
      seconds
      milliseconds
      microseconds
      nanoseconds
    
  
  
    
      0
       3
       0
       0
       0
       0
       0
       0
    
    
      1
       7
       0
       0
       0
       0
       0
       0
    
    
      2
       8
       0
       0
       0
       0
       0
       0
    
    
      3
       9
       0
       0
       0
       0
       0
       0
    
    
      4
       7
       0
       0
       0
       0
       0
       0

TimedeltaIndex



In [12]:

    
pd.TimedeltaIndex(['1 days', '1 days 00:00:03', np.timedelta64(2, 'M')])









    Out[12]:





<class 'pandas.tseries.tdi.TimedeltaIndex'>
['1 days 00:00:00', ..., '60 days 20:58:12']
Length: 3, Freq: None



In [13]:

    
pd.timedelta_range(start='1 hours', freq='5H', periods=10)









    Out[13]:





<class 'pandas.tseries.tdi.TimedeltaIndex'>
['0 days 01:00:00', ..., '1 days 22:00:00']
Length: 10, Freq: <5 * Hours>

Using TimedeltaIndex



In [14]:

    
s = pd.Series(np.arange(100), index=pd.timedelta_range('1 days', periods=100, freq='H'))
s['1 days': '2 days']









    Out[14]:





1 days 00:00:00     0
1 days 01:00:00     1
1 days 02:00:00     2
1 days 03:00:00     3
1 days 04:00:00     4
1 days 05:00:00     5
1 days 06:00:00     6
1 days 07:00:00     7
1 days 08:00:00     8
1 days 09:00:00     9
1 days 10:00:00    10
1 days 11:00:00    11
1 days 12:00:00    12
1 days 13:00:00    13
1 days 14:00:00    14
1 days 15:00:00    15
1 days 16:00:00    16
1 days 17:00:00    17
1 days 18:00:00    18
1 days 19:00:00    19
1 days 20:00:00    20
1 days 21:00:00    21
1 days 22:00:00    22
1 days 23:00:00    23
2 days 00:00:00    24
2 days 01:00:00    25
2 days 02:00:00    26
2 days 03:00:00    27
2 days 04:00:00    28
2 days 05:00:00    29
2 days 06:00:00    30
2 days 07:00:00    31
2 days 08:00:00    32
2 days 09:00:00    33
2 days 10:00:00    34
2 days 11:00:00    35
2 days 12:00:00    36
2 days 13:00:00    37
2 days 14:00:00    38
2 days 15:00:00    39
2 days 16:00:00    40
2 days 17:00:00    41
2 days 18:00:00    42
2 days 19:00:00    43
2 days 20:00:00    44
2 days 21:00:00    45
2 days 22:00:00    46
2 days 23:00:00    47
dtype: int64



In [15]:

    
s['1 days 23 hours']









    Out[15]:





23



In [16]:

    
s[pd.Timedelta('3 days 2 hours')]









    Out[16]:





50

Operations

Conversions

Resampling



In [17]:

    
s.resample('D', how='sum')









    Out[17]:





1 days     276
2 days     852
3 days    1428
4 days    2004
5 days     390
dtype: int64

	A	B	C	D	E
0	2014-01-01	1 days	2014-01-02	2013-12-30	2014-01-09
1	2014-01-02	2 days	2014-01-04	2014-01-01	2014-01-11
2	2014-01-03	3 days	2014-01-06	2014-01-03	2014-01-13