KeyError读取csv文件并传输到数组

Question

我有一个名为csv的文件示例'r2.csv':

Factory | Product_Number |   Date     | Avg_Noshow | Walk_Cost | Room_Rev
-------------------------------------------------------------------------
   A    |      1         | 01APR2017  |   5.6      |  125      |  275
-------------------------------------------------------------------------
   A    |      1         | 02APR2017  |   4.5      |  200      |  300
-------------------------------------------------------------------------
   A    |      1         | 03APR2017  |   6.6      |  150      |  250
-------------------------------------------------------------------------
   A    |      1         | 04APR2017  |   7.5      |  175      |  325
-------------------------------------------------------------------------

我有以下python代码来读取csv文件并将列传输到数组:

# Read csv file
import csv
with open('r2.csv', 'r') as infile:

   reader = csv.DictReader(infile)
   data = {}
   for row in reader:
       for header, value in row.items():
          try:
                data[header].append(value)
          except KeyError:
                data[header] = [value]

 # Transfer the column from list to arrays for later computation.

mu = data['Avg_Noshow']
cs = data['Walk_Cost']
co = data['Room_Rev']

mu = map(float,mu)
cs = map(float,cs)
co = map(float,co)

它运行正常,除了最后一行,并有以下错误消息:

File "<stdin>", line 1, in <module>
  KeyError: 'Room_Rev'

我怎么能避免它？

Answer 1

我无法使用此代码的清理版本重现问题：

# Read csv file
import csv
with open('r2.csv', 'r') as infile:
    reader = csv.DictReader(infile)
    data = {}
    for row in reader:
        print('row: {}'.format(row))
        for header, value in row.items():
            try:
                data[header].append(value)
            except KeyError:
                data[header] = [value]

print('')
from pprint import pprint
pprint(data)

# Transfer the column from list to arrays for later computation.

mu = data['Avg_Noshow']
cs = data['Walk_Cost']
co = data['Room_Rev']

mu = map(float, mu)
cs = map(float, cs)
co = map(float, co)

这是它产生的打印输出：

# Read csv file
import csv
with open('r2.csv', 'r') as infile:
    reader = csv.DictReader(infile)
    data = {}
    for row in reader:
        print('row: {}'.format(row))
        for header, value in row.items():
            try:
                data[header].append(value)
            except KeyError:
                data[header] = [value]

print('')
from pprint import pprint
pprint(data)

# Transfer the column from list to arrays for later computation.

mu = data['Avg_Noshow']
cs = data['Walk_Cost']
co = data['Room_Rev']

mu = map(float, mu)
cs = map(float, cs)
co = map(float, co)

这是r2.csv我自己创建并使用的测试，因为您没有提供测试：

 row: {'Walk_Cost': '125', 'Factory': 'A', 'Avg_Noshow': '5.6', 'Product_Number': '1', 'Date': '01APR2017', 'Room_Rev': '275'}
 row: {'Walk_Cost': '200', 'Factory': 'A', 'Avg_Noshow': '4.5', 'Product_Number': '1', 'Date': '02APR2017', 'Room_Rev': '300'}
 row: {'Walk_Cost': '150', 'Factory': 'A', 'Avg_Noshow': '6.6', 'Product_Number': '1', 'Date': '03APR2017', 'Room_Rev': '250'}
 row: {'Walk_Cost': '175', 'Factory': 'A', 'Avg_Noshow': '7.5', 'Product_Number': '1', 'Date': '04APR2017', 'Room_Rev': '325'}

 {'Avg_Noshow': ['5.6', '4.5', '6.6', '7.5'],
  'Date': ['01APR2017', '02APR2017', '03APR2017', '04APR2017'],
  'Factory': ['A', 'A', 'A', 'A'],
  'Product_Number': ['1', '1', '1', '1'],
  'Room_Rev': ['275', '300', '250', '325'],
  'Walk_Cost': ['125', '200', '150', '175']}