首先,我们导入了datetime模块,该模块提供了处理日期和时间的功能。 然后,我们定义了一个名为get_previous_year_end的函数,用于获取上一年的年末日期。 在函数内部,我们首先使用datetime.date.today()函数获取当前日期,并将其保存在current_date变量中。 接下来,我们使用datetime.timedelta(days=365)函数创建一个表示一年...
importdatetimedefget_previous_month(date):# 获取指定日期的前一个月year=date.year month=date.monthifmonth==1:year-=1month=12else:month-=1returndatetime.date(year,month,1)# 测试代码date=datetime.date(2022,1,15)previous_month=get_previous_month(date)print(previous_month)# 输出:2021-12-01 1...
'value',data=df.loc[df.year==y,:],color=mycolors[i],label=y)plt.text(df.loc[df.year==y,:].shape[0]-.9,df.loc[df.year==y,'value'][-1:].values[0],y,fontsize=12,color=mycolors[i])# Decoration
Pyenv does not officially support Windows and does not work in Windows outside the Windows Subsystem for Linux. Moreover, even there, the Pythons it installs are not native Windows versions but rather Linux versions running in a virtual machine -- so you won't get Windows-specific functionalit...
Source File: blog_calendar.py From simonwillisonblog with Apache License 2.0 5 votes def get_previous_month(date): if date.month == 1: return datetime.date(date.year - 1, 12, 1) else: return datetime.date(date.year, date.month - 1, 1) ...
# Prepare datadf['year'] = [d.year for d in df.date]df['month'] = [d.strftime('%b') for d in df.date]years = df['year'].unique() # Draw Plotfig, axes = plt.subplots(1, 2, figsize=(20,7), dpi= 80)sns.boxplo...
'year': # 上一年的日期 previous_date = current_date - datetime.timedelta(days=365) else: previous_date = None # 非法类别 return previous_date # 测试例子 print(get_previous_date('week')) # 获取上一周的日期 print(get_previous_date('month')) # 获取上一个月的日期 print(get_previous...
importdatetimeimportcalendardefget_last_day_of_previous_month():today=datetime.date.today()year=today.year month=today.month-1ifmonth==0:year=year-1month=12_,last_day=calendar.monthrange(year,month)returnlast_day 1. 2. 3. 4. 5.
(Ifind these bytryand error untilIgetwhatIwant)plt.subplots_adjust(left=0.075,right=0.895,bottom=0.1,top=0.93)plt.pcolormesh(dataplot.lon,dataplot.lat,dataplot,cmap='plasma',vmin=0,vmax=12)plt.title(f'Near-surface air temperature change: {model} ssp585, {dataplot.year.values} vs. 1980...
# Prepare datadf['year'] = [d.year for d in df.date]df['month'] = [d.strftime('%b') for d in df.date]years = df['year'].unique() # Prep Colorsnp.random.seed(100)mycolors = np.random.choice(list(mpl.colors.XKCD_COLORS.keys()), len(years), replace=False) ...