将函数应用于每行python
[英]Apply a function to each row python
问题描述
I am trying to convert from UTC time to LocaleTime in my dataframe. 
我正在尝试从数据帧中的UTC时间转换为LocaleTime。 I have a dictionary where I store the number of hours I need to shift for each country code. 我有一dictionary ，用于存储每个国家/地区代码需要转移的小时数。 So for example if I have df['CountryCode'][0]='AU' and I have a df['UTCTime'][0]=2016-08-12 08:01:00 I want to get df['LocaleTime'][0]=2016-08-12 19:01:00 which is 因此，例如，如果我有df['CountryCode'][0]='AU'并且我有df['UTCTime'][0]=2016-08-12 08:01:00我想获取df['LocaleTime'][0]=2016-08-12 19:01:00这是
df['UTCTime'][0]+datetime.timedelta(hours=dateDic[df['CountryCode'][0]])
I have tried to do it with a for loop but since I have more than 1 million rows it's not efficient. 我尝试过使用for loop来完成此操作，但是由于我有超过一百万行，因此效率不高。 I have looked into the apply function but I can't seem to be able to put it to take inputs from two different columns. 我已经研究了apply函数，但似乎无法将其用于接受来自两个不同列的输入。
Can anyone help me? 谁能帮我？
1 个解决方案
解决方案1
0 2016-12-08 01:33:05
如果没有更具体的示例，这很困难，但是请尝试以下操作：
pd.to_timedelta(df.CountryCode.map(dateDict), 'h') + df.UTCTime
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