如何让python代码接受任何csv列名

Question

i want my code to identify csv columns with specific numbers like coordinate number(3°12'45.5") and split the coordinate number i mean i want the code to accept any csv column name. in the code below, the code can only accept column name("lat","long") being assigned to the csv file.if i decide to read another csv file with different column name, i have to change the column name in the code. my aim is I dont want to change column name in the code despite changing the csv file. this is the sample of the table in the csv file below

lat           long
3°34'45.5"N   8°18'45.5"E
3°56'60.5"N   8°12'72.5"E
3°12'45.5"N   8°12'45.5"E
3°03'55.5"N   7°16'45.5"E

The code I have so far is:

import pandas as pd

read= pd.read_csv(r"C:\Users\Temmy\Documents\COORD.csv", sep=",",
              engine="python",names=None)

#### csv column name is called "lat"#####
latt=pd.DataFrame(read['lat'].str.split(r'[°\'"]',3).tolist(),columns= ['degree','m','s','t'])
df=latt.drop('t',1)
df=df.apply(pd.to_numeric)
divide= df/[1,60,3600]
df["latitude"]=divide.sum(axis=1)
print(df["latitude"])

#### csv column name is called "long"#####
longg=pd.DataFrame(read['long'].str.split(r'[°\'"]',3).tolist(),columns= ['degree','m','s','t'])
df1=longg.drop('t',1)
df1=df1.apply(pd.to_numeric)
divide= df1/[1,60,3600]
df1["longitude"]=divide.sum(axis=1)
print(df1["longitude"])

mergee= pd.concat([df1["longitude"],df["latitude"]], axis=1)
print(mergee)

Answer 1

If I understood your problem correctly this should help:

pd.read_csv(r"C:\Users\Temmy\Documents\COORD.csv", skiprows=1, names=['lat', 'long'])

Here you can read more about read_csv parameters: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html