pandas:如何通过比较其他列值来修改dataframe中列的值

行之间的测试值 in 并分别申请处理每一行:

m = df.apply(lambda x: x['source'] in x['website'], axis=1)

或使用 zip 列表理解:

m = [a in b for a, b in zip(df['source'], df['website'])]

然后通过添加新值 numpy.where :

df['type'] += np.where(m, '_1stParty',  '_3rdParty')
#'long' alternative
#df['type'] = df['type'] + np.where(m, '_1stParty',  '_3rdParty')
print (df)
        website            type         source
0       bbc.com  image_1stParty            bbc
1       cnn.com  audio_3rdParty         google
2    google.com  image_3rdParty  stackoverflow
3  facebook.com  video_1stParty       facebook

你可以用apply方法

df["type"] = df.apply(lambda row: f"{row.type}_1stparty" if row.source in row.website \
                      else f"{row.type}_thirdparty", axis=1)
df

这个解决方案必须比其他使用 apply() :

df.type += df.website.str.split('.').str[0].eq(df.source).\
           replace({True: '_1stParty', False: '_3rdParty'})