尝试使用.loc方法对数据帧的行和列进行切片，但无法对df的行进行切片（它具有日期时间索引）
我正在使用的数据框具有537行和10列。第一个日期是2018年1月1日，但我希望它对其进行切片，以便仅显示2019年的日期。
df.info()
<class 'pandas.core.frame.DataFrame'>
Index: 536 entries, 2018-01-01 00:00:00 to 2019-06-20 00:00:00
Data columns (total 10 columns):
link_clicks 536 non-null int64
customer_count 536 non-null int64
transaction_count 536 non-null int64
customers_per_click 536 non-null float64
transactions_per_click 536 non-null float64
14_day_ma 523 non-null float64
14_day_std 523 non-null float64
Upper14 523 non-null float64
Lower14 523 non-null float64
lower_flag 536 non-null bool
dtypes: bool(1), float64(6), int64(3)
memory usage: 42.4+ KB
df.loc['2019-01-01':'2019-06-01', ['customers_per_click', '14_day_ma', 'Upper14', 'Lower14']]
预期结果是返回该日期范围内的过滤数据帧。但是，当我执行该行代码时，会出现以下错误：
（显然这是索引的问题，但是我只是不确定正确的语法是什么，并且在网上查找解决方案时遇到了麻烦。）
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind)
4804 try:
-> 4805 return self._searchsorted_monotonic(label, side)
4806 except ValueError:
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in _searchsorted_monotonic(self, label, side)
4764
-> 4765 raise ValueError('index must be monotonic increasing or decreasing')
4766
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-599-5bdb485482ff> in <module>
----> 1 merge2.loc['2019-11-01':'2019-02-01', ['customers_per_click', '14_day_ma', 'Upper14', 'Lower14']].plot(figsize=(15,5))
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexing.py in __getitem__(self, key)
1492 except (KeyError, IndexError, AttributeError):
1493 pass
-> 1494 return self._getitem_tuple(key)
1495 else:
1496 # we by definition only have the 0th axis
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexing.py in _getitem_tuple(self, tup)
886 continue
887
--> 888 retval = getattr(retval, self.name)._getitem_axis(key, axis=i)
889
890 return retval
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis)
1865 if isinstance(key, slice):
1866 self._validate_key(key, axis)
-> 1867 return self._get_slice_axis(key, axis=axis)
1868 elif com.is_bool_indexer(key):
1869 return self._getbool_axis(key, axis=axis)
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexing.py in _get_slice_axis(self, slice_obj, axis)
1531 labels = obj._get_axis(axis)
1532 indexer = labels.slice_indexer(slice_obj.start, slice_obj.stop,
-> 1533 slice_obj.step, kind=self.name)
1534
1535 if isinstance(indexer, slice):
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_indexer(self, start, end, step, kind)
4671 """
4672 start_slice, end_slice = self.slice_locs(start, end, step=step,
-> 4673 kind=kind)
4674
4675 # return a slice
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in slice_locs(self, start, end, step, kind)
4870 start_slice = None
4871 if start is not None:
-> 4872 start_slice = self.get_slice_bound(start, 'left', kind)
4873 if start_slice is None:
4874 start_slice = 0
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind)
4806 except ValueError:
4807 # raise the original KeyError
-> 4808 raise err
4809
4810 if isinstance(slc, np.ndarray):
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind)
4800 # we need to look up the label
4801 try:
-> 4802 slc = self._get_loc_only_exact_matches(label)
4803 except KeyError as err:
4804 try:
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in _get_loc_only_exact_matches(self, key)
4770 get_slice_bound.
4771 """
-> 4772 return self.get_loc(key)
4773
4774 def get_slice_bound(self, label, side, kind):
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2657 return self._engine.get_loc(key)
2658 except KeyError:
-> 2659 return self._engine.get_loc(self._maybe_cast_indexer(key))
2660 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
2661 if indexer.ndim > 1 or indexer.size > 1:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: '2019-11-01'
答案 0 :(得分：1)
如果索引的类型为“ datetime”，请尝试：
from datetime import datetime
df.loc[(df.index>=datetime(2019,1,1)) & (df.index<= datetime(2019,6,1)), ['customers_per_click', '14_day_ma', 'Upper14', 'Lower14']]
答案 1 :(得分：0)
在没有所有细节的情况下，我提出了以下代码：
index = pd.date_range('1/1/2018', periods=1100)
ts = pd.Series(np.random.normal(0.5, 2, 1100), index)
grouped = ts.groupby(lambda x: x.year)
grouped.size()
2018 365
2019 365
2020 366
2021 4
dtype: int64
您可以使用以下方式选择年份（一组）：
grouped.get_group(2019)
len(grouped.get_group(2019))
365
您需要更具体的内容吗？