dataframe的数据按时间区间进行提取

问题遇到的现象和发生背景

需要按时间区间提取dfdata中的Volume数据
例如：提取9:30:00到9:45:00时间内，volume列的数据求和

我想要达到的结果

可这样试试：

import pandas as pd
df=pd.read_csv('t20.csv')
s=df.loc[(df['Time']>='9:30:00') & (df['Time']<='9:45:00'),'Volume'].sum()
print(s)

不知道你这个问题是否已经解决, 如果还没有解决的话:

• 看下这篇博客，也许你就懂了，链接：dataframe行列索引设置与转换

如果你已经解决了该问题, 非常希望你能够分享一下解决方案, 以帮助更多的人 ^-^

。

import pandas as pd
import connectorx as cx
from datetime import datetime
import warnings

warnings.filterwarnings("ignore")

class time_slice:

def __init__(self, dataframe):
    self.dataframe = dataframe

def time_slice_number(self,):
    begin_day = self.dataframe.iloc[0, ].name.day
    end_day = self.dataframe.iloc[-1, ].name.day
    begin_month = self.dataframe.iloc[0, ].name.month
    end_month = self.dataframe.iloc[-1, ].name.month
    return begin_day, end_day, begin_month, end_month

def time_slice_need(self):
    begin_day, end_day, begin_month, end_month = time_slice(self.dataframe).time_slice_number()
    df = pd.DataFrame()

    if begin_day > end_day:
        begin_day_1 = end_day
        end_day_1 = begin_day

    for time in range(begin_day_1, end_day_1 + 1):
        for month in range(begin_month, end_month + 1):
            begin_date = str(datetime.now().replace(month=month, day=time, hour=9, minute=0, second=0, microsecond=0))
            mid_date_end = str(datetime.now().replace(month=month, day=time, hour=10, minute=0, second=0, microsecond=0))
            mid_date_begin = str(datetime.now().replace(month=month, day=time, hour=10, minute=30, second=0, microsecond=0))
            end_date = str(datetime.now().replace(month=month, day=time, hour=11, minute=30, second=0, microsecond=0))
            df_1 = self.dataframe[begin_date:mid_date_end][1:]
            df_1 = df_1.resample('s').mean().ffill()
            df_2 = self.dataframe[mid_date_begin:end_date][1:]
            df_2 = df_2.resample('s').mean().ffill()

            # 下午
            lunch_begin = str(datetime.now().replace(month=month, day=time, hour=13, minute=30, second=0, microsecond=0))
            lunch_end = str(datetime.now().replace(month=month, day=time, hour=14, minute=59, second=59, microsecond=0))
            df_3 = self.dataframe[lunch_begin:lunch_end][1:]
            df_3 = df_3.resample('s').mean().ffill()

            # 晚上
            even_begin = str(datetime.now().replace(month=month, day=time, hour=21, minute=0, second=0, microsecond=0))
            even_end = str(datetime.now().replace(month=month, day=time + 1, hour=2, minute=30, second=0, microsecond=0))
            df_4 = self.dataframe[even_begin:even_end][1:]
            df_4 = df_4.resample('s').mean().ffill()
            df = pd.concat([df, df_1, df_2, df_3, df_4])

    df["date"] = df.index
    return df[1:].iloc[::-1]