Exercise 10: Pickling Iris

NITIN GUPTA

 

Problem Statement:

The task you have to perform is “Pickling Iris.” For this, Check the UC Irvine Machine Learning Repository site to get the dataset. You can search the Iris dataset through their searchable interface. Follow the following steps to download the dataset:

  • Go to https://archive.ics.uci.edu/ml/index.php
  • On Most Popular Data Sets, you will see the name “Iris.”
  • Open the Iris dataset.
  • Click on the Data folder. A new tab will open, which contains some files.
  • Click on the Iris. data file to download the text file.

After saving Iris. data file, parse it using the split() function or using a new line approach. The method of parsing is up to you.

The main task is to get the list of lists that you will pickle. And after creating the pickle, write a code to read it. For downloading the Iris dataset, use the request module.

Have you solved this task? If yes, then it is time to check your solution. The solution is discussed in tutorial#94.

Keep supporting and stay up to date with codewithharry.

Code as described/written in the video


# pickle
# Use requests module to download the iris dataset

#I have done three things in this program 1. Downloading 2.Converting to txt 3. Pickling

# pickle
# Use requests module to download the iris dataset

import requests
import pickle

data = requests.get("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data").text
# print(data)

# l1 = data.split("\n")
# print(l1)

l2 =[item.split(",") for item in data.split("\n") if len(item)!=0]
# print(l2)

with open("myiris.pkl", "wb") as f:
    pickle.dump(l2, f)


# To read this pickle file you can use this code
# import pickle
# with open("myiris.pkl", "rb") as f:
#     print(pickle.load(f))

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