pandas 如何使用数据帧 between_time() 函数
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how to use dataframe between_time() function
提问by lserlohn
I am trying to use the between_timefunction. I have formatted the string type time to datetime
我正在尝试使用该between_time功能。我已将字符串类型时间格式化为日期时间
dataset['TimeStamp'] = pd.to_datetime(dataset['TimeStamp'],format)
and I defined search start time and end time:
我定义了搜索开始时间和结束时间：
start = datetime.time(9,40,0)
end = datetime.time(10,00,0)
then I call dataset['TimeStamp'].between_time(start, end)
然后我打电话 dataset['TimeStamp'].between_time(start, end)
This is the error I get:
这是我得到的错误：
TypeError: Index must be DatetimeIndex
Please how can I fix it. Thank you
请问我该如何解决。谢谢
回答by furas
Example - I use info from comments:
示例 - 我使用评论中的信息：
import pandas as pd
import StringIO
import datetime
data = '''time --- value
1984-12-12 14:08:00 --- 1
1984-12-12 14:25:00 --- 2
1984-12-12 14:47:00 --- 4
1984-12-12 16:37:00 --- 3
1984-12-12 16:37:00 --- 9
1984-12-12 16:37:00 --- 5
1984-12-12 17:52:00 --- 3
1984-12-12 17:52:00 --- 7
1984-12-12 19:29:00 --- 2'''
#------------------------------------------------
df = pd.read_csv(StringIO.StringIO(data), sep=' --- ')
df['time'] = pd.DatetimeIndex(df['time'])
print "\nDataFrame:\n", df
print '\nIndex:', type(df.index)
#------------------------------------------------
df.set_index(keys='time', inplace=True)
print "\nDataFrame:\n", df
print '\nIndex:', type(df.index)
#------------------------------------------------
start = datetime.time(14,50,0)
end = datetime.time(18,0,0)
print "\nResult:\n", df['value'].between_time(start, end)
Results:
结果：
DataFrame:
time value
0 1984-12-12 14:08:00 1
1 1984-12-12 14:25:00 2
2 1984-12-12 14:47:00 4
3 1984-12-12 16:37:00 3
4 1984-12-12 16:37:00 9
5 1984-12-12 16:37:00 5
6 1984-12-12 17:52:00 3
7 1984-12-12 17:52:00 7
8 1984-12-12 19:29:00 2
Index: <class 'pandas.core.index.Int64Index'>
DataFrame:
value
time
1984-12-12 14:08:00 1
1984-12-12 14:25:00 2
1984-12-12 14:47:00 4
1984-12-12 16:37:00 3
1984-12-12 16:37:00 9
1984-12-12 16:37:00 5
1984-12-12 17:52:00 3
1984-12-12 17:52:00 7
1984-12-12 19:29:00 2
Index: <class 'pandas.tseries.index.DatetimeIndex'>
Result:
time
1984-12-12 16:37:00 3
1984-12-12 16:37:00 9
1984-12-12 16:37:00 5
1984-12-12 17:52:00 3
1984-12-12 17:52:00 7
Name: value, dtype: int64
