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Python 行上指定范围内的单元格值_Python_Python 3.x_Pandas_Csv - Fatal编程技术网

Python 行上指定范围内的单元格值

Python 行上指定范围内的单元格值,python,python-3.x,pandas,csv,Python,Python 3.x,Pandas,Csv,我想从指定的单元格范围中获取相应温度时间戳的温度值。 e、 g希望获得27-04-2020 05:32至27-04-2020 05:33之间相应温度时间戳的温度值。 我正在使用pandas来读取python中的文件 Temperature_TimeStamp Temperature 27-04-2020 05:31 91.75 27-04-2020 05:31 91.73 27-04-2020 05:32 91.75 27-04-2020 05:32

我想从指定的单元格范围中获取相应温度时间戳的温度值。 e、 g希望获得27-04-2020 05:32至27-04-2020 05:33之间相应温度时间戳的温度值。 我正在使用pandas来读取python中的文件

Temperature_TimeStamp   Temperature
27-04-2020 05:31        91.75
27-04-2020 05:31        91.73
27-04-2020 05:32        91.75
27-04-2020 05:32        91.73
27-04-2020 05:32        91.77
27-04-2020 05:33        91.73
27-04-2020 05:33        91.69
27-04-2020 05:34        91.69
27-04-2020 05:34        91.69

如果您只是查找一个时间戳,并希望获得所有相应的温度:

timestamp = '27-04-2020 05:31'
mask = df.Temperature_TimeStamp.eq(timestamp)
df.loc[mask, 'Temperature']
如果你想在一段时间内取样

# Make sure df['Temperature_TimeStamp'] is in datetime format
df['Temperature_TimeStamp'] = pd.to_datetime(df['Temperature_TimeStamp'])

start_time = pd.to_datetime('27-04-2020 05:30')
end_time = pd.to_datetime('27-04-2020 05:32')

mask = (df['Temperature_TimeStamp'] > start_time) & (df['Temperature_TimeStamp'] <= end_time)
df.loc[mask, 'Temperature']
#确保df['Temperature\u TimeStamp']为datetime格式
df['Temperature\u TimeStamp']=pd.to\u datetime(df['Temperature\u TimeStamp']))
开始时间=pd.至日期时间('27-04-2020 05:30')
结束时间=截止日期时间('27-04-2020 05:32')

掩码=(df['Temperature\u TimeStamp']>start\u time)和(df['Temperature\u TimeStamp']首先将列的valeus转换为datetimes,方法是使用
dayfirst=True
参数,然后根据in进行过滤列
温度

df['Temperature_TimeStamp'] = pd.to_datetime(df['Temperature_TimeStamp'], dayfirst=True)

mask = df['Temperature_TimeStamp'].between('2020-04-27 05:30:00','2020-04-27 05:32:00')
temp = df.loc[mask, 'Temperature']
print (temp)
0    91.75
1    91.73
2    91.75
3    91.73
4    91.77
Name: Temperature, dtype: float64