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"
user
Yes, that's correct. You can use a for loop to iterate through each row in the dataframe `df_vra`. Here's how you can do it in Python:

```python
for index, row in df_vra.iterrows():
    rut = row['RUT']
    dv = row['DV']
    names = row['Names']
    print(f'RUT: {rut}, DV: {dv}, Names: {names}')
```

In this code, `index` is the row index, `row` is a dictionary-like object that contains all the columns for that row, and `iterrows()` returns an iterator of (index, row) tuples. The `f-string` is used for easy formatting of output.
assistant
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"
user
Sure, you can use the pandas library in Python to read the CSV file and loop through each row. Here's how you can do it:

```python
import pandas as pd

# Load the dataset
df_vra = pd.read_csv('externos.csv', sep=';')

# Loop through each row
for index, row in df_vra.iterrows():
    # Get the value of the columns "RUT", "DV", and "Names"
    rut = row['RUT']
    dv = row['DV']
    name = row['Names']

    # Print the values
    print('RUT: ', rut)
    print('DV: ', dv)
    print('Name: ', name)
    print('\n')
```

This will print the values of the "RUT", "DV", and "Names" columns for each row in the dataset. Please replace 'RUT', 'DV', and 'Names' with the actual column names in your CSV file if they are different.
assistant