从第二列到第 N 列的 Pandas Loc 键错误

Question

我有一个非常简单的代码，由于某种原因，当我选择第二列到最后一列时，它会返回一个关键错误。但由于某种原因，第一个按预期工作。

import csv
import pandas as pd
import sys

#terminal parameter:
csv_data = sys.argv[1]

df = pd.read_csv(csv_data)

print(df)
print("\n")

col_heading = str(input("Enter Column Heading: "))
value = str(input("Enter Lookup Value: "))


print(df.loc[df[col_heading] == value])

CSV 如下所示：

Last name, First name, SSN,        Test1, Test2, Test3, Test4, Final, Grade
Alfalfa,   Aloysius,   123-45-6789, 40.0,    90.0,   100.0,    83.0,    49.0,   D-
Alfred,    University, 123-12-1234, 41.0,    97.0,    96.0,    97.0,    48.0,   D+
Gerty,     Gramma,     567-89-0123, 41.0,    80.0,    60.0,    40.0,    44.0,   C
Android,   Electric,   087-65-4321, 42.0,    23.0,    36.0,    45.0,    47.0,   B-
Bumpkin,   Fred,       456-78-9012, 43.0,    78.0,    88.0,    77.0,    45.0,   A-
Rubble,    Betty,      234-56-7890, 44.0,    90.0,    80.0,    90.0,    46.0,   C-
Noshow,    Cecil,      345-67-8901, 45.0,    11.0,    -1.0,     4.0,    43.0,   F
Buff,      Bif,        632-79-9939, 46.0,    20.0,    30.0,    40.0,    50.0,   B+
Airpump,   Andrew,     223-45-6789, 49.0      1.0,    90.0,   100.0,    83.0,   A
Backus,    Jim,        143-12-1234, 48.0,     1.0,    97.0,    96.0,    97.0,   A+
Carnivore, Art,        565-89-0123, 44.0,     1.0,    80.0,    60.0,    40.0,   D+
Dandy,     Jim,        087-75-4321, 47.0,     1.0,    23.0,    36.0,    45.0,   C+
Elephant,  Ima,        456-71-9012, 45.0,     1.0,    78.0,    88.0,    77.0,   B-
Franklin,  Benny,      234-56-2890, 50.0,     1.0,    90.0,    80.0,    90.0,   B-
George,    Boy,        345-67-3901, 40.0,     1.0,    11.0,    -1.0,     4.0,   B
Heffalump, Harvey,     632-79-9439, 30.0,     1.0,    20.0,    30.0,    40.0,   C

这是我收到的错误消息：

Traceback (most recent call last):
  File "C:\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3621, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas\_libs\index.pyx", line 136, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 163, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 5198, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 5206, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'First name'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\krbss\Documents\PlanIT Testing Automation Testing\Challenge 7.py", line 18, in <module>
    print(df.loc[df[col_heading] == value])
  File "C:\Python310\lib\site-packages\pandas\core\frame.py", line 3505, in __getitem__
    indexer = self.columns.get_loc(key)
  File "C:\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3623, in get_loc
    raise KeyError(key) from err
KeyError: 'First name'

我们将不胜感激。

Answer 1

您需要删除前导和尾随空格。假设您不想删除两者之间的空格（例如“姓氏”更改为“姓氏”）。我建议使用条删除前导和尾随空格。应该对列名和数据执行此操作。你可以这样做

df.columns = df.columns.str.strip() #For column names
df.columns = [col.strip() for col in df.columns] #For data in each column

最后还要更改您的打印语句，以便同时处理浮点数和字符串

if df[col_heading].dtype == 'float64':
    print("Float my boat")
    print(df.loc[df[col_heading] == float(value)])
else:
    print(df.loc[df[col_heading] == value])

这应该使您能够打印字符串和浮点类型的匹配行

Answer 2

数据框中的列和值被前导空格污染，您可以使用这些打印语句进行验证（在加载数据框之后）：

print("Columns: ")
print(df.columns)

print("Example data: ")
print(df[" First name"].values)

输出：

Columns: 
Index(['Last name', ' First name', ' SSN', '        Test1', ' Test2', ' Test3',
       ' Test4', ' Final', ' Grade'],
      dtype='object')
Example data: 
['   Aloysius' '    University' '     Gramma' '   Electric' '   Fred'
 '    Betty' '    Cecil' '      Bif' '   Andrew' '    Jim' ' Art'
 '     Jim' '  Ima' '  Benny' '    Boy' ' Harvey']

请注意，第一列“姓氏”没有前导空格，而其他列有，这解释了为什么您可以访问第一列而不能访问其他列。

要解决此问题，您可以告诉 pd.read_csv 跳过分隔符后的初始空格（请参阅 skipinitialspaces https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html）

df = pd.read_csv(csv_data, skipinitialspace=True)

现在列和数据没有不必要的空格，您的代码应该可以按预期工作。

Columns: 
Index(['Last name', 'First name', 'SSN', 'Test1', 'Test2', 'Test3', 'Test4',
       'Final', 'Grade'],
      dtype='object')
Example data: 
['Aloysius' 'University' 'Gramma' 'Electric' 'Fred' 'Betty' 'Cecil' 'Bif'
 'Andrew' 'Jim' 'Art' 'Jim' 'Ima' 'Benny' 'Boy' 'Harvey']

您还可以使用df.columns = [col.strip() for col in df.columns] 之类的方法显式删除空格，这将修复您的列名，但您必须对数据执行相同操作，因此我认为在这种情况下设置skipinitialspaces=True 是最干净的解决方案。