Python属性错误 AttributeError 回溯（最近一次呼叫最后一次） 在（） 3行程输入=['201309\u行程数据.csv'] 4 trip_out='201309_trip_summary.csv' 5总结数据（跳闸输入、车站数据、跳闸输出） 6. 7#加载数据文件并打印出前几行 在总结_数据时（在， 车站（数据，跳闸） 问题3a：在下面添加一个数学运算### 31####将持续时间从秒转换为分钟### 32新点['duration']=浮动（行['duration']）________ 33 34#将日期字符串重新格式化为多列 在这里输入代码 AttributeError:“float”对象没有属性“\uuuuuuuuuuuuuuuuuuuuuuuuuuu”

您的错误在第32行：

32新点['duration']=float（行['duration']）________

您的代码类型将

行['duration']

的值强制转换为浮点数，然后使用句点（

）调用属性/或方法。代码中没有浮点属性

'.\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu。正如Klaus D所指出的，看起来您使用的是一个模板，并且没有像您所期望的那样填写值。如果您可以更彻底地阅读模板说明或在此处发布更多代码，您可能会得到更好的支持

看起来这一切都在函数中，
summary_data（）
，因此如果需要更多帮助，您可能应该从该函数中编写更多上下文

AttributeError                            
Traceback (most recent call last)

<ipython-input-15-568a9b76d0da> in <module>()
       3 trip_in = ['201309_trip_data.csv']
       4 trip_out = '201309_trip_summary.csv'
       5 summarise_data(trip_in, station_data, trip_out)
       6 
       7 # Load in the data file and print out the first few rows

       <ipython-input-6-8a5a5140f3e9> in summarise_data(trip_in,     
       station_data, trip_out)
       30### Question 3a: Add a mathematical operation below   ###
       31### to convert durations from seconds to minutes.     ###
       32new_point['duration'] = float(row['Duration']). ________
       33 
       34# reformat datestrings into multiple columns
       enter code here
       AttributeError: 'float' object has no attribute '________'

任何测试成功的关键步骤都是理解任务。在这里，您似乎应该填写一些内容，但您没有填写。这是什么：
new_point['duration']=float（row['duration']）________？你的问题是什么？这个代码应该做什么？错误消息与您发布的代码片段有何关联？我添加了新的_点['duration']=float（行['duration']）/60。“问题3a：在下面添加一个数学运算，将持续时间从秒转换为分钟。”，“模板”是一个轻描淡写的说法。虽然此代码可能回答了这个问题，提供关于此代码为什么和/或如何回答此问题的附加上下文可提高其长期价值。
AttributeError                            
Traceback (most recent call last)

<ipython-input-15-568a9b76d0da> in <module>()
       3 trip_in = ['201309_trip_data.csv']
       4 trip_out = '201309_trip_summary.csv'
       5 summarise_data(trip_in, station_data, trip_out)
       6 
       7 # Load in the data file and print out the first few rows

       <ipython-input-6-8a5a5140f3e9> in summarise_data(trip_in,     
       station_data, trip_out)
       30### Question 3a: Add a mathematical operation below   ###
       31### to convert durations from seconds to minutes.     ###
       32new_point['duration'] = float(row['Duration']). ________
       33 
       34# reformat datestrings into multiple columns
       enter code here
       AttributeError: 'float' object has no attribute '________'

def summarise_data(trip_in, station_data, trip_out):
"""
This function takes trip and station information and outputs a new
data file with a condensed summary of major trip information. The
trip_in and station_data arguments will be lists of data files for
the trip and station information, respectively, while trip_out
specifies the location to which the summarized data will be written.
"""
# generate dictionary of station - city mapping
station_map = create_station_mapping(station_data)

with open(trip_out, 'w') as f_out:
    # set up csv writer object        
    out_colnames = ['duration', 'start_date', 'start_year',
                    'start_month', 'start_hour', 'weekday',
                    'start_city', 'end_city', 'subscription_type']        
    trip_writer = csv.DictWriter(f_out, fieldnames = out_colnames)
    trip_writer.writeheader()

    for data_file in trip_in:
        with open(data_file, 'r') as f_in:
            # set up csv reader object
            trip_reader = csv.DictReader(f_in)

            # collect data from and process each row
            for row in trip_reader:
                new_point = {}

                # convert duration units from seconds to minutes
                ### Question 3a: Add a mathematical operation below   ###
                ### to convert durations from seconds to minutes.     ###
                new_point['duration'] = float(row['Duration'])/60
                # reformat datestrings into multiple columns
                ### Question 3b: Fill in the blanks below to generate ###
                ### the expected time values.                         ###
                trip_date = datetime.strptime(row['Start Date'], '%m/%d/%Y %H:%M')
                new_point['start_year']  = trip_date.strftime('%Y')
                new_point['start_month'] = trip_date.strftime('%m')
                new_point['start_hour']  = trip_date.strftime('%H')
                new_point['weekday']     = trip_date.strftime('%A')

                # remap start and end terminal with start and end city
                new_point['start_city'] = station_map[row['Start Terminal']]
                new_point['end_city'] = station_map[row['End Terminal']]
                # two different column names for subscribers depending on file
                if 'Subscription Type' in row:
                    new_point['subscription_type'] = row['Subscription Type']
                else:
                    new_point['subscription_type'] = row['Subscriber Type']

                # write the processed information to the output file.
                trip_writer.writerow(new_point)


    # Process the data by running the function we wrote above.
    station_data = ['201402_station_data.csv']
    trip_in = ['201309_trip_data.csv']
    trip_out = '201309_trip_summary.csv' 
    summarise_data(trip_in, station_data, trip_out)

    # Load in the data file and print out the first few rows
    sample_data = pd.read_csv(trip_out)
    display(sample_data.head())

    # Verify the dataframe by counting data points matching each of the      
    time features.