Pandas 将变量名传递给列名
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Pandas Passing Variable Names into Column Name
提问by JJSmith
I have a dataframe that contains 13 different column names, I have separated these headings into two lists. I now want to perform different operations on each of these lists.
我有一个包含 13 个不同列名的数据框，我将这些标题分成两个列表。我现在想对这些列表中的每一个执行不同的操作。
Is it possible to pass column names into pandas as a variable? My code at the moment can loop through the list fine but i am having trouble trying to pass the column name into the function
是否可以将列名作为变量传递给Pandas？我现在的代码可以很好地循环遍历列表，但是我在尝试将列名传递给函数时遇到了问题
Code
代码
CONT = ['age','fnlwgt','capital-gain','capital-loss']
#loops through columns
for column_name, column in df.transpose().iterrows():
if column_name in CONT:
X = column_name
print(df.X.count())
else:
print('')
采纳答案by jezrael
I think you can use subsetcreated from listCONT:
我认为您可以使用subset创建于listCONT：
print df
age fnlwgt capital-gain
0 a 9th 5
1 b 9th 6
2 c 8th 3
CONT = ['age','fnlwgt']
print df[CONT]
age fnlwgt
0 a 9th
1 b 9th
2 c 8th
print df[CONT].count()
age 3
fnlwgt 3
dtype: int64
print df[['capital-gain']]
capital-gain
0 5
1 6
2 3
Maybe better as listis dictionary, which is created by to_dict:
也许更好，因为list是dictionary，这是由创建to_dict：
d = df[CONT].count().to_dict()
print d
{'age': 3, 'fnlwgt': 3}
print d['age']
3
print d['fnlwgt']
3
回答by aiguofer
try:
尝试：
for column_name, column in df.transpose().iterrows():
if column_name in CONT:
print(df[column_name].count())
else:
print('')
edit:
编辑：
To answer your question more precisely:
You can use variables to select cols in 2 ways: df[list_of_columns]will return a DataFrame with the subset of cols in list_of_columns. df[column_name]will return the Series for column_name
更准确地回答您的问题：您可以使用变量以两种方式选择 cols：df[list_of_columns]将返回一个带有 cols 子集的 DataFrame in list_of_columns。df[column_name]将返回系列column_name
回答by Alexander
The following will print the count of each column in the dataframe if it is a subset of your CONT list.
如果它是您的 CONT 列表的子集，以下将打印数据框中每列的计数。
CONT = ['age', 'fnlwgt', 'capital-gain', 'capital-loss']
df = pd.DataFrame(np.random.rand(5, 2), columns=CONT[:2])
>>> df
age fnlwgt
0 0.079796 0.736956
1 0.120187 0.778335
2 0.698782 0.691850
3 0.421074 0.369500
4 0.125983 0.454247
Select the subset of columns and perform a transform.
选择列的子集并执行转换。
>>> df[[c for c in CONT if c in df]].count()
age 5
fnlwgt 5
dtype: int64
