[英]Converting ints to timedelta with pandas
I have some values in a pandas df that are positive and negative ints, and I want to convert them to timedeltas so I can put them into a DurationField in a Django model. 我在pandas df中有一些正负整数值,我想将它们转换为timedeltas,以便可以将它们放入Django模型的DurationField中。
date dep_time dep_delay arr_time arr_delay cancelled carrier \
103992 2014-05-11 10:13:00 -2 12:47:00 -13 0 B6
103993 2014-05-11 19:29:00 -1 22:15:00 -24 0 B6
103994 2014-05-11 11:17:00 5 13:55:00 9 0 B6
103995 2014-05-11 07:36:00 -10 09:24:00 -18 0 B6
103996 2014-05-11 13:40:00 0 16:47:00 10 0 B6
tailnum flight origin dest air_time distance duration
103992 N630JB 925 JFK TPA 137 1005 1013
103993 N632JB 225 JFK TPA 137 1005 1929
103994 N635JB 127 EWR MCO 126 937 1117
103995 N637JB 1273 JFK CHS 92 636 0736
103996 N637JB 213 JFK LGB 352 2465 1340
With this data, I want to express dep_delay, arr_delay, air_time and duration as timedeltas, but I keep getting zeroed-out values? 有了这些数据,我想将dep_delay,arr_delay,air_time和duration表示为timedelta,但是我一直在获取零值吗? I'm using
我正在使用
data['air_time'] = pd.to_timedelta(data['air_time'], errors='coerce')
If you are getting all 00:00:00.000000
values, then your air_time
values might be strings. 如果获取所有
00:00:00.000000
值,则air_time
值可能是字符串。 (You can check the data type of the air_time
column by inspecting data.info()
. If the dtype says object
then the values are Python objects (such as str
s) instead of a NumPy integer data type. You can then confirm they are strings by inspecting set(map(type, data['air_time']))
.) (您可以通过检查
data.info()
来检查air_time
列的数据类型。如果data.info()
表示object
则值是Python对象(例如str
),而不是NumPy整数数据类型。然后可以确认它们是通过检查set(map(type, data['air_time']))
。
If they are strings, you can convert them to ints first by using: 如果它们是字符串,则可以先使用以下命令将它们转换为int:
data['air_time'] = data['air_time'].astype(int)
If 137 means 137 minutes then use 如果137表示137分钟,请使用
data['air_time'] = pd.to_timedelta(data['air_time'], unit='m', errors='coerce')
If, on the other hand, 137 means 1 hour and 37 minutes, then use 另一方面,如果137表示1小时37分钟,则使用
data['air_time'] = pd.to_timedelta(
(data['air_time']//100)*60 + (data['air_time'] % 100), unit='m',
errors='coerce')
The unit='m'
argument tells pd.to_timedelta
to interpret the values as minutes. unit='m'
参数告诉pd.to_timedelta
将值解释为分钟。
For example, 例如,
import pandas as pd
data = pd.DataFrame({'air_time':['137','137','126','92','352']})
data['air_time'] = data['air_time'].astype(int)
data['air_time'] = pd.to_timedelta(data['air_time'], unit='m', errors='coerce')
yields 产量
air_time
0 02:17:00
1 02:17:00
2 02:06:00
3 01:32:00
4 05:52:00
Note that pd.to_timedelta
can also accepts strings as input if the strings contain the desired units . 请注意, 如果字符串包含所需的单位 ,则
pd.to_timedelta
也可以接受字符串作为输入。 For example, 例如,
import pandas as pd
data = pd.DataFrame({'air_time':['137','137','126','92','352']})
data['air_time'] = data['air_time'] + ' minutes'
# air_time
# 0 137 minutes
# 1 137 minutes
# 2 126 minutes
# 3 92 minutes
# 4 352 minutes
data['air_time'] = pd.to_timedelta(data['air_time'], errors='coerce')
yields the same result. 产生相同的结果。
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