英文:
Key error "not in index" when sum a list of columns in pandas
问题
"Key error 'not in index' when sum a list of columns in pandas"
我有一个包含大约100列的数据框。我想要创建一个新的列，其中包含我要对某些列求和的结果，而我有一个包含要求和的列名的列表。
例如，我的列是：
'Col1', 'Col2', 'Col3', ... , 'Col100'
而我的要求和的列的列表是：
sumlist = ['col2', 'col17', 'col44', 'col63', 'col72', 'col21', 'col95']
要求和的列的列表可能会变化，因此我不能像这样操作：
df['total'] = df['col2'] + df['col17'] + df['col44']
我的代码如下：
df['total'] = df[sumlist].sum(axis=1)
但是我遇到了一个错误，说我的数据框中的所有列都不在索引中：
KeyError: "['Col1', 'Col2', 'Col3', ... , 'Col100'] not in index"
然后我尝试重置索引：df.reset_index()，但没有起作用。
英文:
Key error "not in index" when sum a list of columns in pandas
I have a dataframe with about 100 columnns. I want to create a new column with sum of some my columns and i have a list with names of columns to sum.
For example, my columns are:
'Col1', 'Col2', 'Col3', ... , 'Col100'
and my list of columns to sum is:
sumlist = ['col2', 'col17', 'col44', 'col63', 'col72', 'col21', 'col95']
List of columns to sum can change so i can't do something like this:
df['total'] = df['col2'] + df['col17'] + df['col44']
My code:
df['total'] = df[sumlist].sum(axis=1)
But i have an error all my columns in dataframe are not in index:
>KeyError: "['Col1', 'Col2', 'Col3', ... , 'Col100'] not in index"
Then i try to reset index: df.reset_index() but it doesnt work.
答案1
得分: 1
df = pd.DataFrame({'col2':[5,8],
'col17':[1,2],
'col44':[7,0]})
sumlist = ['col2', 'col17', 'col44', 'col63', 'col72', 'col21', 'col95']
df['total'] = df[df.columns.intersection(sumlist)].sum(axis=1)
print (df)
col2 col17 col44 total
0 5 1 7 13
1 8 2 0 10
另一个想法 - 也许需要大写列名？
sumlist = ['Col2', 'Col17', 'Col44', 'Col63', 'Col72', 'Col21', 'Col95']
英文:
Use Index.intersection:
df = pd.DataFrame({'col2':[5,8],
'col17':[1,2],
'col44':[7,0]})
sumlist = ['col2', 'col17', 'col44', 'col63', 'col72', 'col21', 'col95']
df['total'] = df[df.columns.intersection(sumlist)].sum(axis=1)
print (df)
col2 col17 col44 total
0 5 1 7 13
1 8 2 0 10
Another idea - maybe need capitalize columns names?
sumlist = ['Col2', 'Col17', 'Col44', 'Col63', 'Col72', 'Col21', 'Col95']
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