Pandas 重置索引深度总结程序员

今天我们来讨论 Pandas 中的 reset_index() 方法，包括为什么我们需要在 Pandas 中重置 DataFrame 的索引，以及我们应该如何应用该方法
在本文我们将使用 Kaggle 上的数据集样本 Animal Shelter Analytics 来作为我们的测试数据
Pandas 中的 Reset_Index() 是什么？如果我们使用 Pandas 的 read_csv() 方法读取 csv 文件而不指定任何索引，则生成的 DataFrame 将具有默认的基于整数的索引，第一行从 0 开始，随后每行增加 1：

import pandas as pd import numpy as npdf = pd.read_csv('Austin_Animal_Center_Intakes.csv').head() df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

在某些情况下，我们可能希望拥有更有意义的行标签，因此我们将选择 DataFrame 的其中一列作为 DataFrame 索引。我们可以使用 read_csv() 方法的 index_col 参数直接执行此操作：

df = pd.read_csv('Austin_Animal_Center_Intakes.csv', index_col='Animal ID').head() df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

或者我们还可以使用 set_index() 方法将 DataFrame 的任何列设置为 DataFrame 索引：

df = pd.read_csv('Austin_Animal_Center_Intakes.csv').head() df.set_index('Animal ID', inplace=True) df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

如果在某个时候我们需要恢复默认的数字索引呢，这时就可以使用 reset_index()函数了

df.reset_index()

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

此方法的默认行为包括用默认的基于整数的索引替换现有的 DataFrame 索引，并将旧索引转换为与旧索引同名的新列（或名称索引）。此外，默认情况下，reset_index() 方法会从 MultiIndex 中删除所有级别并且不会影响原始 DataFrame 数据，而是创建一个新的
何时使用 Reset_Index() 方法 reset_index() 方法将 DataFrame 索引重置为默认数字索引，在以下情况下特别有用：

执行数据整理时——尤其是过滤数据或删除缺失值等预处理操作，会导致较小的 DataFrame 具有不再连续的数字索引
当索引应该被视为一个常见的 DataFrame 列时
当索引标签没有提供有关数据的任何有价值的信息时

如何调整 Reset_Index() 方法前面的讨论中，我们看到了当我们不向它传递任何参数时，reset_index() 方法是如何工作的，当然如果有需要，我们可以通过调整方法的各种参数来更改此默认行为。让我们看看最有用的三种参数：level、drop 和 inplace
level
此参数采用整数、字符串、元组或列表作为可能的数据类型，并且仅适用于具有 MultiIndex 的 DataFrame，如下所示：

df_multiindex = pd.read_csv('Austin_Animal_Center_Intakes.csv', index_col=['Animal ID', 'Name']).head() df_multiindex

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

事实上，如果现在我们检查上面 DataFrame 的索引，我们会发现它不是一个常见的 DataFrame 索引，而是一个 MultiIndex 对象：

df_multiindex.index

Output:

MultiIndex([('A786884','*Brock'), ('A706918','Belle'), ('A724273', 'Runster'), ('A665644',nan), ('A682524','Rio')], names=['Animal ID', 'Name'])

默认情况下，reset_index() 方法参数 level (level=None) 会移除 MultiIndex 的所有级别：

df_multiindex.reset_index()

【Pandas 重置索引深度总结】Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

我们看到 DataFrame 的两个索引都被转换为通用 DataFrame 列，而索引被重置为默认的基于整数的索引
相反，如果我们显式传递 level 的值，则此参数会从 DataFrame 索引中删除选定的级别，并将它们作为常见的 DataFrame 列返回（除非我们选择使用 drop 参数从 DataFrame 中完全删除此信息）。比较以下操作：

df_multiindex.reset_index(level='Animal ID')

Output:

NameAnimal IDDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor *BrockA78688401/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor BelleA70691807/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver RunsterA72427304/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White NaNA66564410/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico RioA68252406/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

最开始 Animal ID 是 DataFrame 的索引之一，当我们设置 level 参数后，将其从索引中删除并作为称为 Animal ID 的公共列插入到 DataFrame 中

df_multiindex.reset_index(level='Name')

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

在这里，Name 最初是 DataFrame 的索引之一，设置完level参数后，就变成了一个常用的列，叫做Name
drop
此参数决定在索引重置后是否将旧索引保留为通用 DataFrame 列，或者将其从 DataFrame 中完全删除。默认情况下 (drop=False) 是进行保留的，正如我们在前面的所有示例中看到的那样。否则，如果我们不想将旧索引保留为列，我们可以在索引重置后将其从 DataFrame 中完全删除（drop=True）：

df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

增加 drop 参数

df.reset_index(drop=True)

Output:

NameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

在上面的 DataFrame 中，旧索引中包含的信息已完全从 DataFrame 中删除了
drop 参数也适用于具有 MultiIndex 的 DataFrame，就像我们之前创建的那样：

df_multiindex

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

增加 drop 参数

df_multiindex.reset_index(drop=True)

Output:

DateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 001/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 107/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 204/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 310/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 406/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

两个旧索引都已从 Dataframe 中完全删除，并且索引已重置为默认值
当然，我们可以结合 drop 和 level 参数，指定要从 DataFrame 中完全删除哪些旧索引：

df_multiindex.reset_index(level='Animal ID', drop=True)

Output:

DateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor Name *Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

旧索引 Animal ID 已从索引和 DataFrame 本身中删除，另一个索引 Name 被保留为 DataFrame 的当前索引
inplace
该参数决定是直接修改原来的 DataFrame 还是新建一个 DataFrame 对象。默认情况下，它会使用新索引 (inplace=False) 创建一个新的 DataFrame，并保持原始 DataFrame 不变。让我们使用默认参数再次运行 reset_index() 方法，然后将结果与原始 DataFrame 进行比较：

df.reset_index()

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

即使我们将索引重置为运行第一段代码的默认数字，原始 DataFrame 仍然保持不变。如果我们需要将原始 DataFrame 重新分配给对其应用 reset_index() 方法的结果，我们可以直接重新分配它（df = df.reset_index()）或将参数 inplace=True 传递给该方法：

df.reset_index(inplace=True) df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

我们看到现在更改已直接应用于原始 DataFrame 之上了
应用实例：删除缺失值后重置索引让我们将到目前为止讨论的所有内容付诸实践，看看当我们从 DataFrame 中删除缺失值时，重置 DataFrame 索引是如何有用的
首先，让我们恢复我们最开始时创建的第一个 DataFrame，它具有默认数字索引：

df = pd.read_csv('Austin_Animal_Center_Intakes.csv').head() df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A665644NaN10/21/2013 07:59:00 AM10/21/2013 07:59:00 AMAustin (TX)StraySickCatIntact Female4 weeksDomestic Shorthair MixCalico 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

我们看到 DataFrame 中有一个缺失值，让我们使用 dropna() 方法删除具有缺失值的整行

df.dropna(inplace=True) df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 4A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

该行已从 DataFrame 中删除，但是索引不再是连续的：0、1、2、4。让我们重新设置它：

df.reset_index()

Output:

indexAnimal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 00A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 11A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 22A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 34A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

现在索引是连续的了，但是由于我们没有显式传递 drop 参数，旧索引被转换为列，具有默认名称 index，下面让我们从 DataFrame 中完全删除旧索引：

df.reset_index(drop=True)

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

现在我们彻底摆脱了无意义的旧索引，当前索引是连续的。最后一步是使用 inplace 参数将这些修改保存到我们的原始 DataFrame 中：

df.reset_index(drop=True, inplace=True) df

Output:

Animal IDNameDateTimeMonthYearFound LocationIntake TypeIntake ConditionAnimal TypeSex upon IntakeAge upon IntakeBreedColor 0A786884*Brock01/03/2019 04:19:00 PM01/03/2019 04:19:00 PM2501 Magin Meadow Dr in Austin (TX)StrayNormalDogNeutered Male2 yearsBeagle MixTricolor 1A706918Belle07/05/2015 12:59:00 PM07/05/2015 12:59:00 PM9409 Bluegrass Dr in Austin (TX)StrayNormalDogSpayed Female8 yearsEnglish Springer SpanielWhite/Liver 2A724273Runster04/14/2016 06:43:00 PM04/14/2016 06:43:00 PM2818 Palomino Trail in Austin (TX)StrayNormalDogIntact Male11 monthsBasenji MixSable/White 3A682524Rio06/29/2014 10:38:00 AM06/29/2014 10:38:00 AM800 Grove Blvd in Austin (TX)StrayNormalDogNeutered Male4 yearsDoberman Pinsch/Australian Cattle DogTan/Gray

总结今天我们从多个方面讨论了 reset_index() 方法