根据 Pandas python

鉴于您想坚持使用原始数据结构，解决方案可能是使用 df.loc 在 cell_types 列中查找与“基因对”列中的给定值匹配的所有值，将其转换为列出并检查定义“通用发件人”的预定义单元格类型列表中的所有值是否都出现在该列表中：

import pandas as pd

data = [ { "Gene pairs": "gene4_gene5","cell_types": "cell1_cell2" },{ "Gene pairs": "gene1_gene2","cell_types": "cell1_cell1" },"cell_types": "cell1_cell3" },{ "Gene pairs": "gene2_gene3","cell_types": "cell3_cell2" },{ "Gene pairs": "gene4_gene5","cell_types": "cell1_cell3" } ]
df=pd.DataFrame(data)
df['new column'] = df['Gene pairs'].apply(lambda x: "universal sender" if all(item in df.loc[df['Gene pairs'] == x]['cell_types'].tolist() for item in ["cell1_cell2","cell1_cell3","cell1_cell1"]) else NonE)

输出：

|    | Gene pairs   | cell_types   | new column       |
|---:|:-------------|:-------------|:-----------------|
|  0 | gene4_gene5  | cell1_cell2  | universal sender |
|  1 | gene1_gene2  | cell1_cell1  |                  |
|  2 | gene1_gene2  | cell1_cell3  |                  |
|  3 | gene2_gene3  | cell3_cell2  |                  |
|  4 | gene4_gene5  | cell1_cell1  | universal sender |
|  5 | gene4_gene5  | cell1_cell3  | universal sender |

或者您可以将其包装在一个函数中以提高可读性，或者如果您想添加其他过滤器：

def lookup(row):
  cells = sorted(df.loc[df['Gene pairs'] == row['Gene pairs']]['cell_types'].tolist())
  if all(item in cells for item in ["cell1_cell2","cell1_cell1"]):
    return_value = "universal sender" 
  else:
    return_value = None
  return return_value

df['new column'] = df.apply(lambda row: lookup(row),axis=1)