如何使用 function 替换 dataframe 列值

Question

I'm working on a large CSV, where I need to map the IP Protocol Column from String to there IP Protocol Number. For example TCP -> 6.

I want to use this to map the values.

socket.getprotobyname("TCP")

My first option to map all the columns is to use a dictionary and then the replace function.

 ip_dict = {"TCP": socket.getprotobyname("TCP"), "UDP": socket.getprotobyname("UDP")ect...}

df.replace({"proto": ip_dict})

But I want to use the the socket function inside the replace function but I can't find a way to get the current value to pass it as argument

  df["protocol"] = df["protocol"].str.replace(this*, socket.getprotobyname(this*))

this is the the current value to be replaced.

Thanks!

Answer 1

You can use the apply method to create a new column by apply a function to each element of a given column.

So in your case, you can do this:

df["protocol"] = df["protocol"].apply(socket.getprotobyname)

Equivalently, applying a lambda function makes it clear that you're passing every element as an argument (as you intended to do in your attempt):

df["protocol"] = df["protocol"].apply(lambda this: socket.getprotobyname(this))