英文:
Remove double quotes from a string- when inputting a value for a function so it can be written just once
问题
So, I have the following code:
corrresult = df1.drop("COMPRIMISED_ALERT", axis=1).apply(lambda x: x.corr(df1.COMPRIMISED_ALERT))
我有以下代码：
corrresult = df1.drop("COMPRIMISED_ALERT", axis=1).apply(lambda x: x.corr(df1.COMPRIMISED_ALERT))
I want to turn this into a function, so I can use different variables for both the dataframe and the column I'm dropping/ using for the correlation vector.
我想将这转化为一个函数，这样我可以使用不同的变量来表示数据框和用于相关向量的列。
The code below won't work, as y needs to be entered once with quotes marks and once without.
以下代码不起作用，因为 y 需要在带引号和不带引号的情况下分别输入。
def correlation_vector(d, v): corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d.v)) return corrresult
Any idea how to fix this without needing to add a third variable as follows (the third would literally be the second without speech marks):
有没有办法修复这个问题，而不需要像下面这样添加第三个变量（第三个变量实际上就是第二个去掉引号的版本）：
def correlation_vector(d, v, v2): corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d.v2)) return corrresult
If applied to the initial code:
如果应用于初始代码：
d = df1 v = "COMPRIMISED_ALERT" v2 = COMPRIMISED_ALERT
英文:
So, I have the following code:
corrresult = df1.drop("COMPRIMISED_ALERT", axis=1).apply(lambda x: x.corr(df1.COMPRIMISED_ALERT))
I want to turn this into a function, so I can use different variables for both the dataframe and the column I'm dropping/ using for the correlation vector
The code below won't work, as y needs to be entered once with quotes marks and once without.
def correlation_vector (d,v):
corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d.v))
return corrresult
Any idea how to fix this without needing to add a third variable as follows (the third would literally be the second without speech marks):
def correlation_vector (d,v,v2):
corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d.v2))
return corrresult
If applied to the initial code:
d = df1
v = "COMPRIMISED_ALERT"
v2 = COMPRIMISED_ALERT
答案1
得分: 0
尽管 DataFrame 中的列可以通过 类似字典 的方式 ["col_name"] 或使用 点属性符号 .col_name（其中列名是有效的 Python 变量名）来检索，但我建议您使用前者。
def correlation_vector(d, v):
corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d[v])) # <- d[v] 而不是 d.v
return corrresult
要调用您的函数，请使用：
correlation_vector(df1, "COMPRIMISED_ALERT")
英文:
Although the columns in a DataFrame can be retrieved either by dictionary-like notation ["col_name"] or by using the dot attribute notation .col_name (where the column name is a valid Python variable name), I suggest you to use the former.
def correlation_vector(d, v):
corrresult = d.drop(v, axis=1).apply(lambda x: x.corr(d[v])) # <- d[v] instead of d.v
return corrresult
To call your function, use :
correlation_vector(df1, "COMPRIMISED_ALERT")
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