Getting started on medical insurance cost dataset: csv usage

I can’t figure out how to import the csv file to use the data, this is my code:

import csv
with open(“insurance.csv”, newline = “”, ) as insurance_data:
insurance_reader = csv.DictReader(insurance_data)

and then i cant figure out what to do next to be able to use that data set, currently set up as a dictionary. I keep getting the I/O closed file error.

To import a CSV file, you can use the csv module in Python. Here is an example of how you can import a CSV file and read its data:

import csv

# Open the insurance.csv file in read mode
with open('insurance.csv', 'r') as insurance_data:
  # Create a CSV reader object
  insurance_reader = csv.DictReader(insurance_data)

  # Iterate over the rows of the CSV file and print their values
  for row in insurance_reader:

In this code, we first import the csv module. Then, we open the insurance.csv file in read mode using the open() function. We pass the 'r' argument to the open() function to indicate that we want to read the file.

Next, we create a CSV reader object using the csv.DictReader() function, which takes the opened file as an argument. This reader object allows us to iterate over the rows of the CSV file and access its values as dictionaries.

Finally, we use a for loop to iterate over the rows of the CSV file and print their values. The row variable will be a dictionary with the keys being the column names and the values being the data in that column for each row.

If you are still getting an I/O error, it could be because the insurance.csv file is not in the same directory as your Python script. In that case, you need to specify the path to the file in the open() function like this:

with open('/path/to/insurance.csv', 'r') as insurance_data:

Replace /path/to/insurance.csv with the actual path to the insurance.csv file on your computer. For example, if the file is in a folder called data on your desktop, the path would be 'Desktop/data/insurance.csv'.

  1. CSV
    CSV stands for comma-separated values. A CSV file contains data separated by commas (,) instead of tabs or spaces. In order to open a CSV file, you need to use a text editor that supports opening files in this format. 2. Pandas
    Pandas is a Python library that provides high performance, easy-to-use tools for analyzing and manipulating data frames. It is commonly used for data analysis and machine learning tasks. To install pandas, type the following command in the terminal: pip install pandas.
  2. Numpy
    Numpy is a Python package that provides highly optimized linear algebra routines. It is commonly used to perform array operations. To install numpy, type the following command: pip install numpy.