Date = type('Date', (), {'Show': show}) Date.Show() 1. 2. 3. 4. 5. 输出为: 自定义元类 __metaclass__属性自定义元类: 可以在定义一个类的时候为其添加__metaclass__属性。Python会在类的定义中寻找__metaclass__属性,如果找到了,Python就会用它来创建类Foo,如果没有找到,就会用内建的type...
data = {'name':['A','B','C'],'HireDate':['10/24/1979 12:00:00 AM','09/25/2006 12:00:00 AM','11/28/2014 12:00:00 AM'],'GrossPay':[100,200,300]} df = pd.DataFrame(data) df 1. 2. 3. 4. 5. 6. df.HireDate = pd.to_datetime(df.HireDate) df 1. 2. type(...
date_diff = second_date - first_date # Function to convert datetime to string defdt_string(date, date_format="%B %d, %Y"): returndate.strftime(date_format) print(f"The number of days and hours between{dt_string(first_date)}and{dt_string(second_date)}is{date_diff}.") Output: The ...
The DATETIME type is used for values that contain both date and time parts. MySQL retrieves and displays DATETIME values in 'YYYY-MM-DD hh:mm:ss' format. The supported range is '1000-01-01 00:00:00' to '9999-12-31 23:59:59'. The TIMESTAMP data type is used for values that con...
Python String Data Type String is a sequence of characters represented by either single or double quotes. For example, name ='Python'print(name) message ='Python for beginners'print(message) Run Code Output Python Python for beginners In the above example, we have created string-type variables...
date.weekday():返回weekday,如果是星期一,返回0;如果是星期2,返回1,以此类推;data.isoweekday():返回weekday,如果是星期一,返回1;如果是星期2,返回2,以此类推;date.isocalendar():返回格式如(year,month,day)的元组;date.isoformat():返回格式如'YYYY-MM-DD’的字符串;date.strftime(fmt):自定义格式化...
importpandasaspd# 创建一个时间序列数据框data={'value':[1,2,3,4,5]}index=pd.date_range(start...
在Python 3.7(PEP 557)后引入一个新功能是装饰器@dataclass,它通过自动生成特殊方法(如__init__() 和__repr__() ...等魔术方法)来简化数据类的创建。 数据类和普通类一样,但设计用于存储数据、结构简单、用于将相关的数据组织在一起、具有清晰字段的类。
# pandas.core.frame.DataFrametype(df)# pandas.core.series.Seriestype(df['some_data'])# numpy.ndarraytype(df['some_data'].values)# numpy.int64type(df['some_data'].values[0])# strtype(df['a_col'].values[0])# datetime.datetype(df['b_col'].values[0])# numpy.float64type(df['c...
from pyecharts.globals import CurrentConfig, ThemeType CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/' df = pd.read_excel('real_estate_info.xlsx').loc[:, ['推出时间', '土地面积', '规划建筑面积']] date = df['推出时间'].str.split('年', expand=True)[0] ...