是否有任何现有的库能够将日期时间列分隔成只包含它的一个变量的列，例如年、月、日、小时、分钟等。
我这样做是为了对数据进行预处理，我打算尝试在(Kaggle 纽约出租车费)上使用机器学习。
这是数据集中日期时间列的样子:
我已经能够使用以下方法做到这一点:
df_raw["pickup_year"] = df_raw['pickup_datetime'].dt.year
df_raw["pickup_month"] = df_raw['pickup_datetime'].dt.month
df_raw["pickup_day"] = df_raw['pickup_datetime'].dt.day
df_raw["pickup_hour"] = df_raw['pickup_datetime'].dt.hour
df_raw["pickup_minute"] = df_raw['pickup_datetime'].dt.minute
df_raw["pickup_second"] = df_raw['pickup_datetime'].dt.second
df_raw["pickup_dayofyear"] = df_raw['pickup_datetime'].dt.dayofyear
df_raw["pickup_week"] = df_raw['pickup_datetime'].dt.week
df_raw["pickup_weekofyear"] = df_raw['pickup_datetime'].dt.weekofyear
df_raw["pickup_dayofweek"] = df_raw['pickup_datetime'].dt.dayofweek
df_raw["pickup_weekday"] = df_raw['pickup_datetime'].dt.weekday
df_raw["pickup_quarter"] = df_raw['pickup_datetime'].dt.quarter
df_raw.head()
但我在想，这肯定是以前在图书馆的某个地方做过的吧？
最佳答案
您可以按属性列表循环并按 getattr 创建新列:
L = ['year', 'month', 'day', 'hour', 'minute', 'second', 'dayofyear',
'week', 'weekofyear', 'dayofweek', 'weekday', 'quarter']
for i in L:
df[i] = getattr(df['Dates'].dt, i)
#jpp data sample
print (df)
Dates year month day hour minute second dayofyear \
0 2017-12-11 01:00:00 2017 12 11 1 0 0 345
1 2017-12-12 01:00:01 2017 12 12 1 0 1 346
2 2019-05-12 15:15:00 2019 5 12 15 15 0 132
3 2019-06-22 03:25:14 2019 6 22 3 25 14 173
4 2020-05-11 04:40:02 2020 5 11 4 40 2 132
5 2020-11-30 01:00:00 2020 11 30 1 0 0 335
week weekofyear dayofweek weekday quarter
0 50 50 0 0 4
1 50 50 1 1 4
2 19 19 6 6 2
3 25 25 5 5 2
4 20 20 0 0 2
5 49 49 0 0 4
关于Python Pandas Dataframe 日期时间列分隔函数，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/51799339/