DataFrame中根据字典键匹配插入对应值的问题求助

你的代码返回空列表的核心问题是：直接遍历了字符串的单个字符，而非分割后的单词。比如处理"vs, vscode"时，for word in row_value会逐个取出'v'、's'、','这类字符，这些字符不在字典键中，自然返回空列表。

修正方案 #

调整逻辑，先分割字符串为单词列表，再匹配字典值，最后处理结果格式：

import pandas as pd
import numpy as np

df = pd.DataFrame({'key' : ["vs, vscode", "jupyter, jupyterlab", "python, vs", "python", "it was spyder before dawn"]})

my_dict = {'vscode' : 'is gross',
           'jupyter' : 'is not so awesome, but hes ok, ig',
           'vs' : 'is awesome',
           'jupyterlab' : 'is rad',
          'python' : "booya"}

def cascade_col(row_value):
    # 按", "分割字符串，得到单词列表
    words = row_value.split(', ')
    matched_values = []
    for word in words:
        if word in my_dict:
            matched_values.append(my_dict[word])
    # 有匹配值则拼接成字符串，无匹配则返回np.nan
    return ', '.join(matched_values) if matched_values else np.nan

df['Corresponding Value(s)'] = df['key'].apply(cascade_col)

print(df)

运行结果 #

输出完全符合你的预期：

key                          Corresponding Value(s)
0                      vs, vscode                          is awesome, is gross
1            jupyter, jupyterlab  is not so awesome, but hes ok, ig, is rad
2                   python, vs                          booya, is awesome
3                          python                                        booya
4  it was spyder before dawn                                         NaN

内容的提问来源于stack exchange，提问作者ahhhgetit