如何在Python Pandas中使用字典序切片选择子集数据？

介绍

Pandas具有使用索引位置或索引标签选择数据子集的双重选择功能。在本文中，我将向您展示如何“使用字典序切片选择子集数据”。

Google充满了数据集。在kaggle.com中搜索电影数据集。本文使用来自kaggle的电影数据集。

如何操作

1. 仅使用此示例所需的列导入电影数据集。

import pandas as pd
import numpy as np
movies = pd.read_csv("https://raw.githubusercontent.com/sasankac/TestDataSet/master/movies_data.csv",index_col="title",
usecols=["title","budget","vote_average","vote_count"])
movies.sample(n=5)

title	budget	vote_average	vote_count
Little Voice	0	6.6	61
Grown Ups 2	80000000	5.8	1155
The Best Years of Our Lives	2100000	7.6	143
Tusk	2800000	5.1	366
Operation Chromite	0	5.8	29

2. 我总是建议对索引进行排序，特别是如果索引由字符串组成。如果索引已排序，您将注意到在处理巨大数据集时的差异。

如果不对索引进行排序怎么办？

没关系，您的代码将永远运行。开玩笑，如果索引标签未排序，则Pandas必须逐个遍历所有标签以匹配查询。就像没有索引页的牛津字典，你该怎么办？如果索引排序，则您可以快速跳转到要提取的标签，Pandas也是如此。

首先，我们检查索引是否已排序。

# check if the index is sorted or not ?
movies.index.is_monotonic

False

3. 显然，索引未排序。我们将尝试选择以A％开头的电影。这就像写

select * from movies where title like'A%'

movies.loc["Aa":"Bb"]

---------------------------------------------------------------------------
ValueErrorTraceback (most recent call last):
~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, labe l, side, kind)
4844try:
    -> 4845return self._searchsorted_monotonic(label, side) 4846except ValueError:
~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in _searchsorted_monotonic(se lf, label, side)
4805
    -> 4806raise ValueError("index must be monotonic increasing or decreasing")
4807
ValueError: index must be monotonic increasing or decreasing

During handling of the above exception, another exception occurred:

KeyErrorTraceback (most recent call last):
in
----> 1 movies.loc["Aa": "Bb"]

~\anaconda3\lib\site-packages\pandas\core\indexing.py in getitem (self, key)
1766
1767maybe_callable = com.apply_if_callable(key, self.obj)
    -> 1768return self._getitem_axis(maybe_callable, axis=axis) 1769
1770def _is_scalar_access(self, key: Tuple):

~\anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
1910if isinstance(key, slice):
1911self._validate_key(key, axis)
    -> 1912return self._get_slice_axis(key, axis=axis) 1913elif com.is_bool_indexer(key):
1914return self._getbool_axis(key, axis=axis)

~\anaconda3\lib\site-packages\pandas\core\indexing.py in _get_slice_axis(self, slice_ob j, axis)
1794
1795labels = obj._get_axis(axis)
    -> 1796indexer = labels.slice_indexer(
1797slice_obj.start, slice_obj.stop, slice_obj.step, kind=self.name 1798)

~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in slice_indexer(self, start, end, step, kind)
4711slice(1, 3)
4712"""
    -> 4713start_slice, end_slice = self.slice_locs(start, end, step=step, kind=ki nd)
4714
4715# return a slice

~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in slice_locs(self, start, en d, step, kind)
4924start_slice = None
4925if start is not None:
    -> 4926start_slice = self.get_slice_bound(start, "left", kind) 4927if start_slice is None:
4928start_slice = 0

~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, labe l, side, kind)
4846except ValueError:
4847# raise the original KeyError
    -> 4848raise err
4849
4850if isinstance(slc, np.ndarray):

~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, labe l, side, kind)
4840# we need to look up the label
4841try:
    -> 4842slc = self.get_loc(label) 4843except KeyError as err:
4844try:

~\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method,

tolerance)
2646return self._engine.get_loc(key)
2647except KeyError:
    -> 2648return self._engine.get_loc(self._maybe_cast_indexer(key))
2649indexer = self.get_indexer([key], method=method, tolerance=tolerance) 2650if 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\index.pyx in pandas._libs.index.IndexEngine._get_loc_duplicates()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine._maybe_get_bool_indexer()

KeyError: 'Aa'