【发布时间】:2020-01-26 05:16:14
【问题描述】:
我曾尝试使用 pandas 数据系列对相同格式 'hh:mm:ss' 的多个值求和,它的数据类型是 datetime.time/object。但它得到了错误。请你指导我最好的方法。
代码如下:
import pandas as pd
school_diesel =pd.read_excel(r'*********************** Diesel Log 23-09-2019 17_59_05.xlsx',heading=[1,2])
school_running = pd.read_excel(r'*************Daily Log 23-09-2019 18_09_41.xlsx',0)
school_diesel.columns = school_diesel.iloc[0] # replace headings with next row values
school_running.columns = school_running.iloc[0] # replace headings with next row values
school_running.columns
school_diesel.columns
school_diesel.drop(school_diesel.head(1).index, inplace=True) #drop first row of the table- as this repeated heading
school_running.drop(school_running.head(1).index, inplace=True) #drop first row of the table- as this repeated heading
每个字段的数据类型是:
input: school_running.info()
output: <class 'pandas.core.frame.DataFrame'>
Int64Index: 12469 entries, 1 to 12469
Data columns (total 25 columns):
Sno 12468 non-null object
City 12467 non-null object
Zone 12467 non-null object
Branch 12467 non-null object
Building Code 12383 non-null object
Branch Type 12305 non-null object
AC or Non AC 11405 non-null object
Student Strength 12467 non-null object
Company Name 12381 non-null object
Gen SNo 12467 non-null object
Capacity KVA 12381 non-null object
Fuel Capacity 12467 non-null object
Last Diesel Purchase 12467 non-null object
Purchase Qty 12467 non-null object
Amount 12467 non-null object
Last Fuel Filled 12467 non-null object
Filling Qty 12467 non-null object
Diesel Opening Qty 12467 non-null object
Generator On Date 12467 non-null object
Generator Off Date 12467 non-null object
Running Hours 12466 non-null object
Consumed Units 12466 non-null object
Diesel Consumed 12466 non-null object
Diesel Balance Qty 12466 non-null object
Remarks 6267 non-null object
dtypes: object(25)
memory usage: 1.3+ MB
错误发生在行:
school_running['Running Hours'].sum()
error is :
----> 1 school_running['Running Hours'].sum()
**
TypeError: unsupported operand type(s) for +: 'datetime.time' and 'datetime.time'
预期输出是总运行时间的总和。
**时间数据为:**
school_running['Running Hours'].head(10)
1 00:00:00
2 00:00:00
3 00:25:00
4 00:00:00
5 00:00:00
6 00:00:00
7 00:00:00
8 00:00:00
9 00:00:00
10 01:20:00
Name: Running Hours, dtype: object
【问题讨论】: