使用分类变量解包时间数据

time_data = ['2021-08-01 12:30:45', '2021-08-02 14:45:30', '2021-08-03 09:15:10']

import pandas as pd

# 将字符串列表转换为 pandas 的 DateTimeIndex 对象
time_index = pd.to_datetime(time_data)

# 提取分类变量
years = time_index.year
months = time_index.month
days = time_index.day
hours = time_index.hour
minutes = time_index.minute
seconds = time_index.second

# 输出结果
print("Years:", years)
print("Months:", months)
print("Days:", days)
print("Hours:", hours)
print("Minutes:", minutes)
print("Seconds:", seconds)

time_data <- c("2021-08-01 12:30:45", "2021-08-02 14:45:30", "2021-08-03 09:15:10")

# 将字符串向量转换为 POSIXlt 对象
time_data_lt <- as.POSIXlt(time_data)

# 提取分类变量
years <- time_data_lt$year + 1900 # POSIXlt 中的年份是从 1900 年开始计算的
months <- time_data_lt$mon + 1 # POSIXlt 中的月份是从 0 开始计算的
days <- time_data_lt$mday
hours <- time_data_lt$hour
minutes <- time_data_lt$min
seconds <- time_data_lt$sec

# 输出结果
print(paste("Years:", years))
print(paste("Months:", months))
print(paste("Days:", days))
print(paste("Hours:", hours))
print(paste("Minutes:", minutes))
print(paste("Seconds:", seconds))