因此，在我将毫秒添加到日期/时间字段之前，我已经对数据进行了所有处理。
selected = selected['2017-02-20 16:10:05':'2017-02-20 16:20:06'] 是我过滤 data_frame 的声明**
以下数据在毫秒为 0000 时有效
正确填充毫秒后出现以下数据错误
更新: 我试过了
selected.sort_index()
selected.ix['2017-02-20 16:10:05':'2017-02-20 16:20:06']
selected.ix[datetime.date(year=2017,month=2,day=20):datetime.date(year=2017,month=2,day=21)]
TypeError: '>' 不支持 'str' 和 'datetime.date' 的实例
然后我得到以下内容
ValueError Traceback (most recent call last)
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in get_slice_bound(self, label, side, kind)
3121 try:
-> 3122 return self._searchsorted_monotonic(label, side)
3123 except ValueError:
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in _searchsorted_monotonic(self, label, side)
3087
-> 3088 raise ValueError('index must be monotonic increasing or decreasing')
3089
ValueError: index must be monotonic increasing or decreasing
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-43-a7bf11322082> in <module>()
11 selected = selected.query('y_acc < 0.4 and z_acc > -0.4')
12 selected = selected.query('z_acc < 0.4 and z_acc > -0.4')
---> 13 selected = selected['2017-02-20 16:10:05':'2017-02-20 16:20:06']
14
15 #%pylab inline
/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
2045
2046 # see if we can slice the rows
-> 2047 indexer = convert_to_index_sliceable(self, key)
2048 if indexer is not None:
2049 return self._getitem_slice(indexer)
/usr/local/lib/python3.6/site-packages/pandas/core/indexing.py in convert_to_index_sliceable(obj, key)
1772 idx = obj.index
1773 if isinstance(key, slice):
-> 1774 return idx._convert_slice_indexer(key, kind='getitem')
1775
1776 elif isinstance(key, compat.string_types):
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in _convert_slice_indexer(self, key, kind)
1236 else:
1237 try:
-> 1238 indexer = self.slice_indexer(start, stop, step, kind=kind)
1239 except Exception:
1240 if is_index_slice:
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in slice_indexer(self, start, end, step, kind)
2995 """
2996 start_slice, end_slice = self.slice_locs(start, end, step=step,
-> 2997 kind=kind)
2998
2999 # return a slice
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in slice_locs(self, start, end, step, kind)
3174 start_slice = None
3175 if start is not None:
-> 3176 start_slice = self.get_slice_bound(start, 'left', kind)
3177 if start_slice is None:
3178 start_slice = 0
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in get_slice_bound(self, label, side, kind)
3123 except ValueError:
3124 # raise the original KeyError
-> 3125 raise err
3126
3127 if isinstance(slc, np.ndarray):
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in get_slice_bound(self, label, side, kind)
3117 # we need to look up the label
3118 try:
-> 3119 slc = self.get_loc(label)
3120 except KeyError as err:
3121 try:
/usr/local/lib/python3.6/site-packages/pandas/indexes/base.py in get_loc(self, key, method, tolerance)
2134 return self._engine.get_loc(key)
2135 except KeyError:
-> 2136 return self._engine.get_loc(self._maybe_cast_indexer(key))
2137
2138 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4433)()
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4279)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13742)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13696)()
KeyError: '2017-02-20 16:10:05'
请您参考如下方法:
按日期时间索引过滤
selected_subset = selected.ix['2017-02-20 16:10:05':'2017-02-20 16:20:06']
引用:filtering pandas dataframes on dates
我试过了，它对我有用:
import pandas as pd
import numpy as np
from datetime import datetime
date_time_1 = datetime.now()
date_time_2 = datetime.now()
data = [{'time': date_time_1, 'val': 1}, {'time': date_time_2, 'val':2}]
df = pd.DataFrame.from_dict(data, orient='columns')
df.set_index(['time'], inplace=True)
df = df.sort_index() # This is an important step if 'time' field is not sorted
df
val
time
2017-02-28 19:19:00.777225 1
2017-02-28 19:19:04.605302 2
df.ix['2017-02-28 19:19:00':'2017-02-28 19:19:03']
val
time
2017-02-28 19:19:00.777225 1
