无法将时间对象转换为datetime64[ns]

Question

我的主要目的是找出每个工作所花的总时间。我确实尝试减去两个时间列，但出现了一个错误：<class 'datetime.time'> is not convertible to datetime。你知道吗

我运行了.info（）并看到时间列是对象。在excel文件中，格式仅为时间，而不是日期时间格式。我尝试将第一时间列转换为日期时间格式，结果如下：

import pandas as pd
df = pd.read_excel('C:/users/paul/desktop/data project/July.xls', index_col=0)
hrs_st = (pd.to_datetime(df['AST'].str.strip(), format='%H:%M:%S'))
print (hrs_st)

工作指令

BAEBRO-906063           NaT
BAEBRO-906191           NaT
BAEBRO-906207           NaT
BAEBRO-906079           NaT
BAEBRO-906095           NaT
BAEBRO-906159           NaT
...

Answer 1

说实话有点混乱。你能不能更具体一点，你的主要目标是什么，并提供更多的资料，日期是如何显示在你的excel文件。你知道吗

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第二次编辑* |我试着用代码注释我写的东西。你知道吗

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我举了一个类似的例子，只是想知道我能帮你什么。你知道吗

我的excel文件如下所示：

这就是以非常简单的方式读取和计算差异的代码：

import pandas as pd

df = pd.read_excel('dates.xlsx') #reading my excel

timeStart = [] #declaring 2 lists where I'm gonna put my records 
timeEnd = [] 

#Here I append my values from the excel to my lists
for value in df.get('col1'):
    timeStart.append(value)
for value in df.get('col2'):
    timeEnd.append(value)


#I suppose they both have the same amount of elements in list
#therefore I can iterate for the len of any list between timeStart and timeEnd
for i in range(len(timeStart)):
    #datetime.time object doesn't allow '-' operator to catch it's time difference,
    #you can calculate it like this having how much hours, minutes or seconds
    #spent working. Or you can just concatenate all 3 results to get it all.
    hours = timeEnd[i].hour - timeStart[i].hour #hours difference
    minutes = timeEnd[i].minute - timeStart[i].minute #minutes difference
    seconds = timeEnd[i].second - timeStart[i].second #second difference
    print(type(hours), type(minutes), type(seconds)) #all my results are int
    print(hours, minutes, seconds) #I can see the difference from one time to another

这是我在输出中得到的：

<class 'int'> <class 'int'> <class 'int'> #Here you can see I have 3 int types
1 30 15 #read as 1 hour 30 minutes and 15 seconds
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
<class 'int'> <class 'int'> <class 'int'>
1 30 15
[Finished in 0.5s]

Answer 2

我想出了一个更好的解决方案，对我原来的问题非常有效，那就是计算出完成一个工作单所花费的总时间。这个解决方案有助于克服excel时间格式这是一个对象类型。一旦转换为datetime[64]启用，一列减去另一列。你知道吗

import pandas as pd from datetime import time from datetime import timedelta

df = pd.read_excel('C:/Users/Nativ_Zero/Desktop/work data/July.xls', index_col =0)

df_work = df[['WorkType', 'AST','AFT']]

#to convert time format column which is an object to datetime[64 df_work['AFT'] = pd.to_datetime(df_work['AFT'], format='%H:%M:%S', errors='coerce') df_work['AST'] = pd.to_datetime(df_work['AST'], format='%H:%M:%S', errors='coerce')

rm_work = df_work[df_work.WorkType == 'RM'] hrs_ft = rm_work['AFT'] hrs_st = rm_work['AST']

hrs_t = hrs_ft - hrs_st

Print(hrs_t)