pandas 熊猫数据框中的日期时间不会相互减去
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Datetime in pandas dataframe will not subtract from each other
提问by Graham Streich
I am trying to find the difference in times between two columns in a pandas dataframe both in datetime format.
我试图找到日期时间格式的Pandas数据框中两列之间的时间差异。
Below is some of the data in my dataframe and the code I have been using. I have triple checked that these two columns dtypes are datetime64.
下面是我的数据框中的一些数据和我一直在使用的代码。我已经三重检查这两列数据类型是 datetime64。
My data:
我的数据：
date_updated date_scored
2016-03-30 08:00:00.000 2016-03-30 08:00:57.416
2016-04-07 23:50:00.000 2016-04-07 23:50:12.036
My code:
我的代码：
data['date_updated'] = pd.to_datetime(data['date_updated'],
format='%Y-%m-%d %H:%M:%S')
data['date_scored'] = pd.to_datetime(data['date_scored'],
format='%Y-%m-%d %H:%M:%S')
data['Diff'] = data['date_updated'] - data['date_scored']
The error message I receive:
我收到的错误消息：
TypeError: data type "datetime" not understood
Any help would be appreciated, thanks!
任何帮助将不胜感激，谢谢！
My work around solution:
我的解决方案：
for i in raw_data[:10]:
scored = i.date_scored
scored_date = pd.to_datetime(scored, format='%Y-%m-%d %H:%M:%S')
if type(scored_date) == "NoneType":
pass
elif scored_date.year >= 2016:
extracted = i.date_extracted
extracted = pd.to_datetime(extracted, format='%Y-%m-%d %H:%M:%S')
bank = i.bank.name
diff = scored - extracted
datum = [str(bank), str(extracted), str(scored), str(diff)]
data.append(datum)
else:
pass
回答by ac2001
I encountered the same error using the above syntax (worked on another machine though):
我使用上述语法遇到了同样的错误（虽然在另一台机器上工作）：
data['Diff'] = data['date_updated'] - data['date_scored']
It worked on my new machine with:
它适用于我的新机器：
data['Diff'] = data['date_updated'].subtract(data['date_scored'])
回答by Roberto Valerio
You need to update pandas. I've just ran into the same issue with an old code that used to run without issues. After updating pandas (0.18.1-np111py35_0) to a newer version (0.20.2-np113py35_0) the issue was resolved.
您需要更新Pandas。我刚刚遇到了同样的问题，旧代码曾经运行没有问题。将 pandas (0.18.1-np111py35_0) 更新到更新版本 (0.20.2-np113py35_0) 后，问题得到解决。
回答by Romain
It works like a charm. You can even simplify your code since to_datetimeis smart enough to guess the format for you.
它就像一个魅力。您甚至可以简化您的代码，因为to_datetime它足够聪明，可以为您猜测格式。
import io
import pandas as pd
# Paste the text by using of triple-quotes to span String literals on multiple lines
zz = """date_updated,date_scored
2016-03-30 08:00:00.000, 2016-03-30 08:00:57.416
2016-04-07 23:50:00.000, 2016-04-07 23:50:12.036"""
data = pd.read_table(io.StringIO(zz), delim_whitespace=False, delimiter=',')
data['date_updated'] = pd.to_datetime(data['date_updated'])
data['date_scored'] = pd.to_datetime(data['date_scored'])
data['Diff'] = data['date_updated'] - data['date_scored']
print(data)
# date_updated date_scored Diff
# 0 2016-03-30 08:00:00 2016-03-30 08:00:57.416 -1 days +23:59:02.584000
# 1 2016-04-07 23:50:00 2016-04-07 23:50:12.036 -1 days +23:59:47.964000
