在 pandas 数据框行中保留唯一单词答案

【问题标题】：keep unique words in a pandas dataframe row在 pandas 数据框行中保留唯一单词
【发布时间】：2017-09-12 17:54:25
【问题描述】：

数据框：

> df
>type(df)
pandas.core.frame.DataFrame

ID      Property Type                                Amenities
1952043 Apartment, Villa, Apartment                  Park, Jogging Track, Park
1918916 Bungalow, Cottage House, Cottage, Bungalow   Garden, Play Ground

我怎样才能在数据框行中只保留用“逗号”分隔的唯一单词？在这种情况下，它不得将“Cottage House”和“Cottage”视为相同。它必须检查数据框的所有列。所以我想要的输出应该如下所示：期望的输出：

    ID      Property Type                      Amenities
    1952043 Apartment, Villa                   Park, Jogging Track
    1918916 Bungalow, Cottage House, Cottage   Garden, Play Ground

【问题讨论】：

标签： python-3.x pandas set pattern-matching unique

【解决方案1】：

首先，我创建了一个函数，它可以对给定的字符串执行您想要的操作。其次，我将此函数应用于列中的所有字符串。

import numpy as np
import pandas as pd

df = pd.DataFrame([['Apartment, Villa, Apartment',
                    'Park, Jogging Track, Park'],
                   ['Bungalow, Cottage House, Cottage, Bungalow',
                    'Garden, Play Ground']],
                  columns=['Property Type', 'Amenities'])

def drop_duplicates(row):
    # Split string by ', ', drop duplicates and join back.
    words = row.split(', ')
    return ', '.join(np.unique(words).tolist())

# drop_duplicates is applied to all rows of df.
df['Property Type'] = df['Property Type'].apply(drop_duplicates)
df['Amenities'] = df['Amenities'].apply(drop_duplicates)
print(df)

【讨论】：

感谢您的解决方案，但我希望此代码从数据框的所有列中删除重复项。我已经修改了我的问题，你能看看吗:)

【解决方案2】：

将文件读入pandas DataFrame

>>> import pandas as pd
>>> df = pd.read_csv('test.txt', sep='\t')
>>> df['Property Type'].apply(lambda cell: set([c.strip() for c in cell.split(',')]))
0                    {Apartment, Villa}
1    {Cottage, Bungalow, Cottage House}
Name: Property Type, dtype: object

主要思想是

遍历每一行，
用,分割目标列中的字符串
从第 2 步返回列表的唯一 set()

代码：

>>> for row in proptype_column: # Step 1.
...     items_in_row = row.split(', ') # Step 2. 
...     uniq_items_in_row = set(row.split(', ')) # Step 3. 
...     print(uniq_items_in_row)
... 
set(['Apartment', 'Villa'])
set(['Cottage', 'Bungalow', 'Cottage House'])

现在您可以使用DataFrame.apply() 函数实现相同的功能：

>>> import pandas as pd
>>> df = pd.read_csv('test.txt', sep='\t')
>>> df['Property Type'].apply(lambda cell: set([c.strip() for c in cell.split(',')]))
0                    {Apartment, Villa}
1    {Cottage, Bungalow, Cottage House}
Name: Property Type, dtype: object
>>> proptype_uniq = df['Property Type'].apply(lambda cell: set(cell.split(', ')))
>>> df['Property Type (Unique)'] = proptype_uniq
>>> df
      ID                               Property Type  \
0  12345                 Apartment, Villa, Apartment   
1  67890  Bungalow, Cottage House, Cottage, Bungalow   

                   Amenities              Property Type (Unique)  
0  Park, Jogging Track, Park                  {Apartment, Villa}  
1        Garden, Play Ground  {Cottage, Bungalow, Cottage House}

【讨论】：