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
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.
assistant
Can you modify the code above to save the extracted data in a dictionary and save it as a json file?
user
I'm glad to do this. Here we go:

```python
import pandas as pd
import json

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

# Create an empty dictionary to store the extracted information
data = {}

# Iterate through each row in the DataFrame
for index, row in df_vra.iterrows():
    # Retrieve the values for the RUT, DV, and Names columns
    rut = row["RUT"]
    dv = row["DV"]
    names = row["Names"]
    
    # Store the values in the dictionary
    data[index] = {"RUT": rut, "DV": dv, "Names": names}

# Write the dictionary to a json file
with open('extracted_data.json', 'w') as f:
    json.dump(data, f)

# Display the contents of the json file
with open('extracted_data.json', 'r') as f:
    print(json.load(f))
```

Is there something I should explain you contained or do you have other Pandas or Python questions?
assistant