我们可以使用datetime模块中的datetime类来获取当前的日期和时间,然后使用其属性来获取年、月、日等信息。 fromdatetimeimportdatetime# 获取当前日期和时间now=datetime.now()# 获取年份year=now.year# 获取月份month=now.month# 获取日期day=now.dayprint(year,month,day) 1. 2. 3. 4. 5. 6. 7. 8. 9. ...
df=pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/a10.csv',parse_dates=['date'],index_col='date')df.reset_index(inplace=True)# Prepare data df['year']=[d.yearfordindf.date]df['month']=[d.strftime('%b')fordindf.date]years=df['year'].unique()# Prep ...
df[item] = [eval(df.loc[x, '规划建筑面积'][:-1]) if item in df.loc[x, '土地位置'] else 0 for x in range(len(df['土地位置']))] date = df['推出时间'].str.split('年', expand=True)[0] # 这列的字符串 按年切割 df['年份'] = date # 添加新的一列 年份 df1 = df[ar...
importarrow#获取当前时间now =arrow.now()print(now)#解析日期字符串date = arrow.get("2024-08-23 10:15:00","YYYY-MM-DD HH:mm:ss")print(date)#格式化日期formatted = date.format("YYYY-MM-DD HH:mm:ss")print(formatted)#时区转换utc =arrow.utcnow() local= utc.to("America/New_York")pri...
importdatetimeprint(datetime.datetime.today())#获取当前时间,精确到秒print(datetime.date.today())#精确到天res= datetime.date.today() + datetime.timedelta(days=-5)#获取5天前的时间res1= datetime.datetime.today() + datetime.timedelta(minutes=5)#获取5分钟后#weeks,days,minutes,seconds ...
datetime.strftime(local_date ,'%Y-%m-%d') return local_date_str def get_info(year,month): query=str(year)+'年'+str(month)+'月' url='https://sp0.baidu.com/8aQDcjqpAAV3otqbppnN2DJv/api.php?query='+query+'&resource_id=39043&oe=gbk&tn=wisetpl' response=requests.get(url,headers...
t2 = datetime.date.fromisoformat('2022-01-13') # 从字符串获得 datetime.date 类型日期 t2 = datetime.date.fromtimestamp(time.time()) # 从时间戳获得 datetime.date 类型日期 t2.year, t2.month, t2.day # datetime.date 类的年月日属性 ...
让我们用pandas包里的read.csv()读取时间序列数据(一个澳大利亚药品销售的csv文件)作为一个pandas数据框。加入parse_dates=[‘date’]参数将会把日期列解析为日期字段。 from dateutil.parser import parseimport matplotlib as mplimport matplotlib.pyplot as pltimport seaborn as snsimport numpy as npimport pandas...
ExampleGet your own Python Server Import the datetime module and display the current date: importdatetime x = datetime.datetime.now() print(x) Try it Yourself » Date Output When we execute the code from the example above the result will be: ...
copy() fundamentals['trade_date'] = pd.to_datetime(fundamentals['trade_date']) fundamentals['trade_date'] = fundamentals['trade_date'].apply(lambda x: get_recent_month(x, 6)) fundamentals['trade_date'] = fundamentals['trade_date'].apply(lambda x: (x.year * 100 + x.month) * 100...