我在python中有一个dataframe，看起来像这样
dt = pd.DataFrame({"language1": ["english", "english123", "ingles", "ingles123", "14.0", "13", "french"],
"language2": ["englesh", "english123", "ingles", "ingles123", "14", "13", "french"],
"language3": ["englesh", "engl", "ingles", "ingles123", "14", "13", "spanish"]})
我想做的是复制这个R代码，但是在python中
dt[,language4:=ifelse(!language1%in%c("french"),paste0(language2,"_win"),paste0(language3,"_lose"))]
我试过了，但不起作用
dt['language4'] = dt.apply(lambda x: ~x['language1'].isin(['french']), x['language2'] + "_win", x['language3']+"_lose")
所以我想出了这个
dt.loc[~dt['language1'].isin(["french"]),'language4'] = surv_dt_sd['language2'] + \
"_win"
但我不知道如何在一行中实现else位
最佳答案
numpy.where 将在这里工作:
dt['language4'] = np.where("french" not in dt['language1'], dt['language2'] + '_win', dt['language2'] + '_lose')
关于python - 如何使用Python中的现有列以其他列为条件创建新列，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/46220892/