pandas :索引更新和更改按位置访问的值 [英] Pandas: Index updating and changing value accessed by location

问题描述

关于Python Pandas数据框，我有两个与索引相关的问题.

I have two index-related questions on Python Pandas dataframes.

import pandas as pd
import numpy as np
df = pd.DataFrame({'id' : range(1,9),
                'B' : ['one', 'one', 'two', 'three',
                       'two', 'three', 'one', 'two'],
                'amount' : np.random.randn(8)})

df = df.ix[df.B != 'three'] # remove where B = three
df.index
>>  Int64Index([0, 1, 2, 4, 6, 7], dtype=int64) # the original index is preserved.

1)我不理解为什么修改数据框后索引不会自动更新.有没有一种方法可以在修改数据框时自动更新索引?如果没有，最有效的手动方法是什么?

1) I do not understand why the indexing is not automatically updated after I modify the dataframe. Is there a way to automatically update the indexing while modifying a dataframe? If not, what is the most efficient manual way to do this?

2)我希望能够将df的第5个元素的B列设置为三个".但是df.iloc[5]['B'] = 'three'不会那样做.我检查了手册，但没有涵盖如何更改通过位置访问的特定单元格值.

2) I want to be able to set the B column of the 5th element of df to 'three'. But df.iloc[5]['B'] = 'three' does not do that. I checked on the manual but it does not cover how to change a specific cell value accessed by location.

如果按行名访问，可以执行:df.loc[5,'B'] = 'three'，但是我不知道什么是等效的索引访问.

If I were accessing by row name, I could do: df.loc[5,'B'] = 'three' but I don't know what the index access equivalent is.

P.S. Link1 和

P.S. Link1 and link2 are relevant answers to my second question. However, they do not answer my question.

推荐答案

1)我不明白为什么修改数据框后索引不会自动更新.

1) I do not understand why the indexing is not automatically updated after I modify the dataframe.

如果要在删除/添加行后重置索引，可以执行以下操作:

If you want to reset the index after removing/adding rows you can do this:

df = df[df.B != 'three'] # remove where B = three
df.reset_index(drop=True)

       B    amount  id
0    one    -1.176137    1
1    one     0.434470    2
2    two    -0.887526    3
3    two     0.126969    5
4    one     0.090442    7
5    two    -1.511353    8

索引是用来对行进行标签/标记/标识的...所以您可能会考虑将"id"列作为索引，然后您将欣赏到熊猫在删除时不会自动更新"索引行.

Indexes are meant to label/tag/id a row... so you might think about making your 'id' column the index, and then you'll appreciate that Pandas doesn't 'automatically update' the index when deleting rows.

df.set_index('id')

       B    amount
id      
1    one    -0.410671
2    one     0.092931
3    two    -0.100324
4    three   0.322580
5    two    -0.546932
6    three  -2.018198
7    one    -0.459551
8    two     1.254597

2)我希望能够将df的第5个元素的B列设置为三".但是df.iloc [5] ['B'] ='三'不会那样做.我查看了手册，但没有涵盖如何更改通过位置访问的特定单元格值.

2) I want to be able to set the B column of the 5th element of df to 'three'. But df.iloc[5]['B'] = 'three' does not do that. I checked on the manual but it does not cover how to change a specific cell value accessed by location.

杰夫已经回答了这个问题...

Jeff already answered this...

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