ValueError：索引必須單調增加或減少：增加毫秒

因此，我已將所有內容都處理了數據，直到我向日期/時間字段添加了毫秒。選擇ValueError：索引必須單調增加或減少：增加毫秒

選定= [ '2017年2月20日16時10分05秒'： '2017年2月20日十六時20分06秒']是我的語句來過濾我data_frame **

的下面的數據工作時毫秒爲0000

下面的數據錯誤被正確填充毫秒時

更新：我試圖

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)]

類型錯誤： '>' '海峽' 和 'datetime.date' 的實例之間不支持

然後我得到以下

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'

來源

2017-02-28 Burf2000

有關排序指數'DF = df.sort_index（）'什麼？ – jezrael

謝謝，我想篩選我的數據在其索引 – Burf2000

你試過這個'selected.ix ['2017-02-20 16:10:05'：'2017-02-20 16:20:06']'： http://stackoverflow.com/questions/22898824/filtering-pandas-dataframes-on-dates –

按日期時間索引過濾

selected_subset = selected.ix['2017-02-20 16:10:05':'2017-02-20 16:20:06']

參考：filtering pandas dataframes on dates

我想這和它的工作對我來說：

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

來源

2017-02-28 14:05:55

問題竟然是它認爲日期指數的字符串。我發現了這一點使用：

selected.ix[datetime.date(year=2017,month=2,day=20):datetime.date(year=2017,month=2,day=21)]

其中返回的錯誤：類型錯誤：「>」不「海峽」和「datetime.date」的實例之間支持

我加入parse_dates =真 ro我的read_csv命令並解決了問題。

然後我可以只使用

selected = selected['2017-02-20 16:10:05':'2017-02-20 16:11:06']

來源

2017-02-28 14:19:55 Burf2000

ValueError：索引必須單調增加或減少：增加毫秒

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