在pandas df中创建新列并有条件地分配字符串值

Question

我是新手pandas，试图在 Pandas Dataframe 中创建一个新列，并根据函数分配一个字符串值，但结果仅向所有 5,000 列输出 1 个值（'住宅）。知道我的代码有什么问题吗？谢谢def programType(c):if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':    return 'Residential'elif c['Primary Property Type - Self Selected'] == 'Bank Branch' or 'Hotel' or 'Financial Office' \or 'Retail Store' or 'Distribution Center' or 'Non-Refrigerated Warehouse' or 'Fitness Center/Health Club/Gym' \or 'Mixed Use Property' or 'Self-Storage Facility' or 'Wholesale Club/Supercenter' or 'Supermarket/Grocery Store':    return 'Commercial'  elif c['Primary Property Type - Self Selected'] == 'Senior Care Community' or 'K-12 School' or 'College/University' \or 'Worship Facility' or 'Medical Office' or 'Hospital (General Medical & Surgical)':    return 'Institutional'elif c['Primary Property Type - Self Selected'] == 'Manufacturing/Industrial Plant':     return 'Industrial'else:    return 'Other'新列称为“程序类型”datav3['Program Type'] = datav3.apply(programType, axis=1)

Answer 1

如果存在矢量化解决方案，在 Pandas 中最好避免循环（应用是引擎盖下的循环），因为循环很慢。

我尝试重写您的代码 - 创建带有输出和值列表的字典，用值交换键并调用map，最后为不匹配的值添加fillna：

d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],

     'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center', 

                   'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',

                   'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],

     'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',

                     'Medical Office', 'Hospital (General Medical & Surgical)'],

     'Industrial':  ['Manufacturing/Industrial Plant'] }

d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}

print (d1)

{

    'Multifamily Housing': 'Residential',

    'Residence Hall/Dormitory': 'Residential',

    'Bank Branch': 'Commercial',

    'Hotel': 'Commercial',

    'Financial Office': 'Commercial',

    'Retail Store': 'Commercial',

    'Distribution Center': 'Commercial',

    'Non-Refrigerated Warehouse': 'Commercial',

    'Fitness Center/Health Club/Gym': 'Commercial',

    'Mixed Use Property': 'Commercial',

    'Self-Storage Facility': 'Commercial',

    'Wholesale Club/Supercenter': 'Commercial',

    'Supermarket/Grocery Store': 'Commercial',

    'Senior Care Community': 'Institutional',

    'K-12 School': 'Institutional',

    'College/University': 'Institutional',

    'Worship Facility': 'Institutional',

    'Medical Office': 'Institutional',

    'Hospital (General Medical & Surgical)': 'Institutional',

    'Manufacturing/Industrial Plant': 'Industrial'

}

datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',

                                       'Residence Hall/Dormitory',

                                       'Manufacturing/Industrial Plant','House']})

datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')

print (datav3)

                          Program   Program Type

0                  Medical Office  Institutional

1                           Hotel     Commercial

2        Residence Hall/Dormitory    Residential

3  Manufacturing/Industrial Plant     Industrial

4                           House          Other

Answer 2

问题在于您的 if 循环。您之后比较的方式or不正确。

写作or 'Residence Hall/Dormitory' 将永远是true，因此，if每次只评估第一个，并且您进入Residential所有行。

取而代之的是：

if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':

做这个：

if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':

或者

if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):

只需进行上述更改，您的代码就应该符合预期。希望这很清楚。