Question

我想创建一个新列，其中包含行中所有不同的值。行中的每个值都是一个字符串（不是列表）。

这是数据框的外观：

+-----------------------------+-------------------------+---------------------------------------------+
|         first               |            second       |           third                             |  
+-----------------------------+-------------------------+---------------------------------------------+
|['able', 'shovel', 'door']   |['shovel raised']        |['shovel raised', 'raised', 'door', 'shovel']|
|['grade control']            |['grade']                |['grade']                                    |
|['light telling', 'love']    |['would love', 'closed'] |['closed', 'light']                          |
+-----------------------------+-------------------------+---------------------------------------------+

这是在创建具有不同值的新列之后数据框的外观。

df = pd.DataFrame({'first': "['able', 'shovel', 'door']" , 'second': "['shovel raised']", 'third': "['shovel raised', 'raised', 'door', 'shovel']", "Distinct_set": "['able', 'shovel', 'door', 'shovel raised', 'raised']" }, index = [0])

我该怎么办？

Answer 1

尝试一下：

df['new_col'] = df.apply(lambda x: list(set(x['first'] + x['second']+x['third'])), axis =1)

它创建的单个字符集，因为您单元格中的数据是字符串。

“ ['able'，'shovel'，'door']”

在下面更正此用法：

df['new_col'] = df.apply(lambda x: list(set(eval(x['first']) + eval(x['second'])+eval(x['third']))), axis =1)

Answer 2

如何？

import pandas as pd
import numpy as np

df = pd.DataFrame([[['able', 'shovel', 'door'], ['shovel raised'], ['shovel raised', 'raised', 'door', 'shovel']], [['grade control'], ['grade'], ['grade']], [['light telling', 'love'], ['would love', 'closed'], ['closed', 'light']]], columns=['first', 'second', 'third'])

df.apply(lambda row: [np.unique(np.hstack(row))], raw=True, axis=1)

最后一条命令产生：

0        [[able, door, raised, shovel, shovel raised]]
1                             [[grade, grade control]]
2    [[closed, light, light telling, love, would lo...

可以保存在数据框的新列中

df['Distinct_set'] = df.apply(lambda row: [np.unique(np.hstack(row))], raw=True, axis=1)

Answer 3

您可以在下面的代码段中试用

import json
def get_list_from_str(s):
    return json.loads(s.replace("'", '"'))

def flatten_list_rows(row):
    return (set(
        get_list_from_str(row['first']) + 
        get_list_from_str(row['second']) + 
        get_list_from_str(row['third']) 
    ))

df['Distinct_set'] = df.apply(flatten_list_rows, axis=1)

用新列更新熊猫数据框

3 个答案: