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python-3.x - 当我尝试处理熊猫中的缺失值时，某些方法不起作用

问题描述

我正在尝试处理数据集中的一些缺失值。这是我用来学习的教程的链接。下面是我用来读取数据的代码。

import pandas as pd
import numpy as np

questions = pd.read_csv("./archive/questions.csv")

print(questions.head())

这就是我的数据的样子

在此处输入图像描述

这些是我用来处理缺失值的方法。他们都没有工作。

questions.replace(to_replace = np.nan, value = -99)
questions = questions.fillna(method ='pad')
questions.interpolate(method ='linear', limit_direction = 'forward')

然后我尝试删除缺少值的行。他们都没有工作。他们都返回空数据框。

questions.dropna()
questions.dropna(how = "all")
questions.dropna(axis = 1)

我做错了什么？

编辑：

值来自questions.head()

[[1 '2008-07-31T21:26:37Z' nan '2011-03-28T00:53:47Z' 1 nan 0.0]
 [4 '2008-07-31T21:42:52Z' nan nan 458 8.0 13.0]
 [6 '2008-07-31T22:08:08Z' nan nan 207 9.0 5.0]
 [8 '2008-07-31T23:33:19Z' '2013-06-03T04:00:25Z' '2015-02-11T08:26:40Z'
  42 nan 8.0]
 [9 '2008-07-31T23:40:59Z' nan nan 1410 1.0 58.0]]

字典形式的值questions.head()。

{'Id': {0: 1, 1: 4, 2: 6, 3: 8, 4: 9}, 'CreationDate': {0: '2008-07-31T21:26:37Z', 1: '2008-07-31T21:42:52Z', 2: '2008-07-31T22:08:08Z', 3: '2008-07-31T23:33:19Z', 4: '2008-07-31T23:40:59Z'}, 'ClosedDate': {0: nan, 1: nan, 2: nan, 3: '2013-06-03T04:00:25Z', 4: nan}, 'DeletionDate': {0: '2011-03-28T00:53:47Z', 1: nan, 2: nan, 3: '2015-02-11T08:26:40Z', 4: nan}, 'Score': {0: 1, 1: 458, 2: 207, 3: 42, 4: 1410}, 'OwnerUserId': {0: nan, 1: 8.0, 2: 9.0, 3: nan, 4: 1.0}, 'AnswerCount': {0: 0.0, 1: 13.0, 2: 5.0, 3: 8.0, 4: 58.0}}

有关数据集的信息

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 17203824 entries, 0 to 17203823
Data columns (total 7 columns):
 #   Column        Dtype  
---  ------        -----  
 0   Id            int64  
 1   CreationDate  object 
 2   ClosedDate    object 
 3   DeletionDate  object 
 4   Score         int64  
 5   OwnerUserId   float64
 6   AnswerCount   float64
dtypes: float64(2), int64(2), object(3)
memory usage: 918.8+ MB

标签： python-3.xpandasdataframenanmissing-data

解决方案

您可以尝试axis明确指定并查看它是否有效吗？另一个 fillna() 应该在没有轴的情况下仍然可以工作，但是对于 pad 你需要它，所以它知道如何填充缺失的值。

>>> questions.fillna(method='pad', axis=1)
  Id          CreationDate            ClosedDate          DeletionDate Score OwnerUserId AnswerCount
0  1  2008-07-31T21:26:37Z  2008-07-31T21:26:37Z  2011-03-28T00:53:47Z     1           1           0
1  4  2008-07-31T21:42:52Z  2008-07-31T21:42:52Z  2008-07-31T21:42:52Z   458           8          13
2  6  2008-07-31T22:08:08Z  2008-07-31T22:08:08Z  2008-07-31T22:08:08Z   207           9           5
3  8  2008-07-31T23:33:19Z  2013-06-03T04:00:25Z  2015-02-11T08:26:40Z    42          42           8
4  9  2008-07-31T23:40:59Z  2008-07-31T23:40:59Z  2008-07-31T23:40:59Z  1410           1          58

刚刚fillna()应用于整个 DataFrame 按预期工作。

>>> questions.fillna('-')

   Id          CreationDate            ClosedDate          DeletionDate  Score OwnerUserId  AnswerCount
0   1  2008-07-31T21:26:37Z                     -  2011-03-28T00:53:47Z      1           -          0.0
1   4  2008-07-31T21:42:52Z                     -                     -    458           8         13.0
2   6  2008-07-31T22:08:08Z                     -                     -    207           9          5.0
3   8  2008-07-31T23:33:19Z  2013-06-03T04:00:25Z  2015-02-11T08:26:40Z     42           -          8.0
4   9  2008-07-31T23:40:59Z                     -                     -   1410           1         58.0

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