File Handling with Python || Python programming tutorial

-

In File Handling, we will be working on a file in our computer and doing various operations on it. Check out my previous blog on Python programming if you want to learn from scratch.

Let us say we have a file name poem.txt and we need to perform various operations on that file.

Reading the whole file and printing it

  1. First, we need to open that text file in our python program using a function open().
  2. The open() function will take two arguments filename and set our intentions.
  3. Now, you must be wondering about the second argument i.e. we need to specify our purpose of using that file Read, Write and Append
  4. Above all operations can be specified by with different alphabets:
    • Read - 'r'
    • Write - 'w'
    • Append - 'a'
Now we will implement programs with this knowledge

Program - 
f = open("poem.txt", "r")
f.read()

Counting Number of Lines in our file

We will divide this process into various steps :
To read a single line of a file we can use readline method

Program - 

f = open("poem.txt", "r")
number_of_lines = 0
while f.readline()!="":
    number_of_lines += 1
print("Number of Lines in a file is ", number_of_lines)

Output - Number of Lines in a file is 18

Note - Before running these programs make sure you have your text file in the same directory where you have your python file. Otherwise, you need to give the correct path of a file

This code is also available on my GitHub you can check it out - Click Here

I hope this article was helpful to you and you learned from it. Make sure to check it out in future as I will be updating this blog and adding some more operation on files. Thank you for reading.
Location: India

Comments

Post a Comment

If you have any questions do let me know and also give your valuable feedback for this blog.

Popular posts from this blog

Hierarchical Clustering - An Unsupervised Learning Algorithm

-
Image
Introduction Unsupervised learning  is a type of Machine learning in which we use unlabeled data and we try to find a pattern among the data. Clustering algorithms falls under the category of unsupervised learning. In these algorithms, we try to make different clusters among the data. Hierarchical Clustering algorithms build a hierarchy of clusters where each node is a cluster consisting of the clusters of its children node. To check it's implementation in Python  CLICK HERE There are various strategies in Hierarchical Clustering such as : Divisive Agglomerative This type of diagram is called  Dendrogram. Divisive - It is a Top-down approach. So we start with all observations in a large cluster and break it down into smaller ones. Agglomerative - It is the opposite of Divisive as it is a Bottom-Up approach. Here, each observation starts in its cluster and pairs of the cluster are merged as they move up the hierarchy.  (Generally, Agglomerative is used more as compared to Divisive
Read more

Implementing Hierarchical Clustering - In Python Programming language

-
Image
Introduction to Hierarchical Clustering Unsupervised learning  is a type of Machine learning in which we use unlabeled data and we try to find a pattern among the data. Clustering algorithms  falls under the category of unsupervised learning. In these algorithms, we try to make different clusters among the data. Hierarchical Clustering  algorithms build a hierarchy of clusters where each node is a cluster consisting of the clusters of its children node. fig. 1 Check out my blog on Hierarchical Clustering - An Unsupervised learning Algorithm  to learn more about it. Implementing it with Python and SciKit-Learn We will use the python programming language for its implementation. In python language, we will be using SciKit-Learn library. So let's start with implementation - We will be using our own dataset which will be generated by us.     1.  Importing necessary Libraries - To create a machine learning model we will use SciKit-Learn (sklearn) library and to create our dataset we will
Read more

Getting Started with your first Machine Learning Algorithm - Linear Regression || First step towards ML

-
Image
Linear Regression is a Supervised Learning Algorithm. This is probably the first algorithm taught when you start learning ML. Now as a beginner you must be wondering "What is a Supervised Learning??". So machine learning can be divided mainly into 3 types: Supervised Learning Unsupervised Learning Reinforcement Learning Supervised Learning is a technique in which we use a labelled dataset to train a model. In short, you can say there is a supervisor who will tell whether the predictions model is making is correct or not. This supervisor decides about based on the labels provided in the datasets. Labels are the correct values for a particular training example. We will deal later with the other two techniques of ML. In supervised learning, we can classify problems into 2 different categories: Regression - problems in which we need to predict continuous value as an output. Classification - where we need to classify the training examples in a particular category. We plot all t
Read more