Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant:  Human: using python use the following dataset: "df_vra = pd.read_csv('externos.csv', sep=';')" and loop through each row and get the value of the columns "RUT", "DV", and "Names"

Assistant: 
You shouldn't use a for loop in this instance. Pandas has a built in method to get a subset of the columns in a dataframe. You give a list of the column names you want as an index like so:

columns = [ "RUT", "DV", "Names"]
df_vra[columns]

Should return what you want. Here is an example of how you can use the pandas library in Python to read the externos.csv dataset, loop through each row, and extract the values of the columns "RUT", "DV", and "Names":

import pandas as pd

# Read the externos.csv file into a Pandas DataFrame
df_vra = pd.read_csv('externos.csv', sep=';')

# Loop through each row in the DataFrame
for index, row in df_vra.iterrows():
    # Extract the values of the RUT, DV, and Names columns
    rut = row["RUT"]
    dv = row["DV"]
    names = row["Names"]

    # Print the values
    print("RUT:", rut)
    print("DV:", dv)
    print("Names:", names)

This code uses the read_csv method of the pandas library to read the externos.csv file into a Pandas DataFrame named df_vra. The sep argument specifies the separator used in the CSV file, which is a semicolon in this case.

The code then uses the iterrows method of the DataFrame to loop through each row, where index is the index of the row and row is a Series containing the values of the row. The values of the columns "RUT", "DV", and "Names" can be accessed using the square bracket notation and the name of the column.

Finally, the code prints the values of the columns for each row. Here's an example of how to loop through each row in the dataframe df_vra and extract the values of the columns "RUT", "DV", and "Names":

import pandas as pd

# Read the CSV file into a dataframe
df_vra = pd.read_csv('externos.csv', sep=';')

# Loop through each row in the dataframe
for index, row in df_vra.iterrows():
    # Extract the values of the columns "RUT", "DV", and "Names"
    rut = row["RUT"]
    dv = row["DV"]
    name = row["Names"]
    
    # Print the values for each row
    print("RUT: ", rut)
    print("DV: ", dv)
    print("Name: ", name)

This code uses the iterrows() function to loop through each row in the dataframe. For each row, it extracts the values of the columns "RUT", "DV", and "Names" using the square bracket notation, and stores these values in variables rut, dv, and name, respectively. Finally, it prints the values for each row.