将小时列转换为日期时间失败
Convert Hour column to datetime failes
我在 pandas 中有以下 table:
>>>TIMESTAMP date Hour patient1 patient2 patient3 patient4 ....
0 2019-06-13 12:00:00 2019-06-13 12:00:00 -0.456 -0.124 -0.451 -2.257
1 2019-06-13 12:03:00 2019-06-13 12:03:00 -0.456 -0.134 -0.781 -2.357
2 2019-06-13 12:06:00 2019-06-13 12:06:00 -0.876 -0.238 -0.983 -1.824
...
2019-07-04 22:03:00 2019-07-04 12:03:00 -0.568 -0.532 -0.451 0.789
n 2019-07-04 22:06:00 2019-07-04 12:06:00 -0.021 -0.981 -0.293 1.824
我有时间戳列,它是日期时间,我有从 TIMESTAMP 列中拆分出来的日期和小时列,如下所示:
# #two cOlumns for hour and for date
df['Date'] = [d.date() for d in df['Timestamp']]
df['Hour'] = [d.time() for d in df['Timestamp']]
问题是我只想从我的数据库中 select 2019-06-20 到 2019-07-02 之间的行,并且小时将在 07:00 到 17:00。由于日期时间格式的问题,这不起作用。
我尝试使用 between:
df=df[(df['date'].between('2019-06-20','2019-07-02'))&(df['Hour'].between('07:00','17:00'))]
但后来我得到了这个错误:
TypeError: '>=' not supported between instances of 'datetime.date' and
'str'
所以我检查了数据类型,发现日期和小时是对象类型,所以我尝试像这样更改它们的类型:
df['date'] = pd.to_datetime(df['date']).dt.date
df['Hour'] = pd.to_datetime(df['Hour']).dt.time
但出现错误:
TypeError: <class 'datetime.time'> is not convertible to datetime
我的最终目标是能够 select 只有在我想要的日期和时间范围内的行(2019-06-20 到 2019-07-02 和小时将在 07:00 到 17:00 之间。
您最好将时间和日期更改为以下格式的数字(int):
日期至 -> YYYYMMDD
时间 -> HHMM
通过以下代码:
df['time'] = df['Timestamp'].dt.strftime('%H%M').astype(int)
df['date'] = df['Timestamp'].dt.strftime('%Y%m%d').astype(int)
然后你可以很容易地与整数进行比较:
df=df[(df['date'].between(20190620,20190702))&(df['Hour'].between(700,1700))]
使用 Series.dt.floor
代替删除时间 date
并使用 time
构造函数:
print (df)
date Hour patient1 patient2 patient3
TIMESTAMP
2019-06-13 12:00:00 2019-06-25 12:00:00 -0.456 -0.124 -0.451 <-date for match
2019-06-13 12:03:00 2019-06-13 12:03:00 -0.456 -0.134 -0.781
2019-06-13 12:06:00 2019-06-13 12:06:00 -0.876 -0.238 -0.983
2019-07-04 22:03:00 2019-07-04 12:03:00 -0.568 -0.532 -0.451
2019-07-04 22:06:00 2019-07-04 12:06:00 -0.021 -0.981 -0.293
from datetime import time
df['date'] = pd.to_datetime(df['date']).dt.floor('d')
#it looks already time column, so should be removed
#df['Hour'] = pd.to_datetime(df['Hour'].astype(str)).dt.time
df=df[(df['date'].between('2019-06-20','2019-07-02')&
df['Hour'].between(time(7,0,0),time(17,0,0)))]
print (df)
date Hour patient1 patient2 patient3
TIMESTAMP
2019-06-13 12:00:00 2019-06-25 12:00:00 -0.456 -0.124 -0.451
我在 pandas 中有以下 table:
>>>TIMESTAMP date Hour patient1 patient2 patient3 patient4 ....
0 2019-06-13 12:00:00 2019-06-13 12:00:00 -0.456 -0.124 -0.451 -2.257
1 2019-06-13 12:03:00 2019-06-13 12:03:00 -0.456 -0.134 -0.781 -2.357
2 2019-06-13 12:06:00 2019-06-13 12:06:00 -0.876 -0.238 -0.983 -1.824
...
2019-07-04 22:03:00 2019-07-04 12:03:00 -0.568 -0.532 -0.451 0.789
n 2019-07-04 22:06:00 2019-07-04 12:06:00 -0.021 -0.981 -0.293 1.824
我有时间戳列,它是日期时间,我有从 TIMESTAMP 列中拆分出来的日期和小时列,如下所示:
# #two cOlumns for hour and for date
df['Date'] = [d.date() for d in df['Timestamp']]
df['Hour'] = [d.time() for d in df['Timestamp']]
问题是我只想从我的数据库中 select 2019-06-20 到 2019-07-02 之间的行,并且小时将在 07:00 到 17:00。由于日期时间格式的问题,这不起作用。
我尝试使用 between:
df=df[(df['date'].between('2019-06-20','2019-07-02'))&(df['Hour'].between('07:00','17:00'))]
但后来我得到了这个错误:
TypeError: '>=' not supported between instances of 'datetime.date' and 'str'
所以我检查了数据类型,发现日期和小时是对象类型,所以我尝试像这样更改它们的类型:
df['date'] = pd.to_datetime(df['date']).dt.date
df['Hour'] = pd.to_datetime(df['Hour']).dt.time
但出现错误:
TypeError: <class 'datetime.time'> is not convertible to datetime
我的最终目标是能够 select 只有在我想要的日期和时间范围内的行(2019-06-20 到 2019-07-02 和小时将在 07:00 到 17:00 之间。
您最好将时间和日期更改为以下格式的数字(int): 日期至 -> YYYYMMDD 时间 -> HHMM
通过以下代码:
df['time'] = df['Timestamp'].dt.strftime('%H%M').astype(int)
df['date'] = df['Timestamp'].dt.strftime('%Y%m%d').astype(int)
然后你可以很容易地与整数进行比较:
df=df[(df['date'].between(20190620,20190702))&(df['Hour'].between(700,1700))]
使用 Series.dt.floor
代替删除时间 date
并使用 time
构造函数:
print (df)
date Hour patient1 patient2 patient3
TIMESTAMP
2019-06-13 12:00:00 2019-06-25 12:00:00 -0.456 -0.124 -0.451 <-date for match
2019-06-13 12:03:00 2019-06-13 12:03:00 -0.456 -0.134 -0.781
2019-06-13 12:06:00 2019-06-13 12:06:00 -0.876 -0.238 -0.983
2019-07-04 22:03:00 2019-07-04 12:03:00 -0.568 -0.532 -0.451
2019-07-04 22:06:00 2019-07-04 12:06:00 -0.021 -0.981 -0.293
from datetime import time
df['date'] = pd.to_datetime(df['date']).dt.floor('d')
#it looks already time column, so should be removed
#df['Hour'] = pd.to_datetime(df['Hour'].astype(str)).dt.time
df=df[(df['date'].between('2019-06-20','2019-07-02')&
df['Hour'].between(time(7,0,0),time(17,0,0)))]
print (df)
date Hour patient1 patient2 patient3
TIMESTAMP
2019-06-13 12:00:00 2019-06-25 12:00:00 -0.456 -0.124 -0.451