Python获取时间的操作示例详解

# 注意时区的设置 import time # 获得当前时间时间戳 now = int(time.time()) # 转换为其他日期格式，如："%Y-%m-%d %H:%M:%S" timeArr = time.localtime(now) other_StyleTime = time.strftime("%Y-%m-%d %H:%M:%S", timeArr) print(other_StyleTime) 

import datetime # 获得当前时间 now = datetime.datetime.now() other_StyleTime = now.strftime("%Y-%m-%d %H:%M:%S") print(other_StyleTime) 

import datetime def getYesterday(): today = datetime.date.today() oneday = datetime.timedelta(days=1) yesterday = today - oneday return yesterday print("昨天的日期：", getYesterday()) 

# 引入日历模块 import calendar # 输入指定年月 yy = int(input("输入年份：")) mm = int(input("输入月份：")) # 显示指定年月 print(calendar.month(yy, mm)) 

import calendar ​​​​​​​monthRange = calendar.monthrange(2022, 4) print(monthRange) 

import time import datetime # 先获得时间数组格式的日期 threeDayAgo = (datetime.datetime.now() - datetime.timedelta(days=3)) # 转换为时间戳 timeStamp = int(time.mktime(threeDayAgo.timetuple())) # 转换为其他字符串格式 otherStyleTime = threeDayAgo.strftime("%Y-%m-%d %H:%M:%S") print(otherStyleTime) 

import time import datetime # 给定时间戳 timeStamp1 = 1643892140 dateArray = datetime.datetime.utcfromtimestamp(timeStamp1) threeDayAgo = dateArray - datetime.timedelta(days=3) print(threeDayAgo) 

import time timeStamp = 1825135462 timeArr = time.localtime(timeStamp) other_StyleTime = time.strftime("%Y-%m-%d %H:%M:%S", timeArr) print(other_StyleTime) 

import datetime timeStamp = 2022020321 dateArr = datetime.datetime.utcfromtimestamp(timeStamp) other_StyleTime = dateArray.strftime("%Y-%m-%d %H:%M:%S") print(other_StyleTime) 

# -*- coding = utf-8 -*- # @Time : 2022/7/22 19:46 # @Author : lxw_pro # @File : pandas-5 练习.py # @Software : PyCharm import pandas as pd 

df = pd.read_excel('test-5.xlsx') print("EXCEL数据如下：\n", df) print() 

print("df数据前5行为：\n", df.head()) print() 

import re def func(df): zfg = df['popularity'].split('-') smin = int(zfg[0].strip('f')) smax = int(zfg[1].strip('f')) df['popularity'] = int((smin+smax)/2) return df df = df.apply(func, axis=1) print(df) print() 

fzj = df.groupby('project').mean() print("分组后的平均分为:\n", fzj) print() 

df['date'] = df['test_time'].dt.date df['time'] = df['test_time'].dt.time print(df.head()) df.to_excel('text5.xlsx')	# 也可将所运行的结果导入另一个新的EXCEL