Python is a simple programming language and it helps to automate most of our daily tasks. You must have gone through many tutorials to understand each topic. However, programming becomes comfortable only through practice. In this series, we will try to create simple programs using 2 or 3 concepts to help you get familiar and comfortable with Python Automation. If this sounds interesting, feel free to join us in this "Python Mini Program Series" journey. Happy Coding!!
Here, we take word to be searched as an input from the user and sends http request to google search page. We read the response from the 'knowledge panel' and displays it as a result to the user. For cases where no result is returned from the knowledge pane, this programs displays the link of the topmost search.
Here, we take input from the user in form of paragrapgh.txt file that contains the content to be read. We do the basic data cleaning such as removing the punctuation, converting to standard case and removing the stop words. The program generates the 3 most commonly used words by finding the frequency of each word.
Here, we takes two inputs from the user - 1) The word to be searched and 2) A text file in form of sample_input.txt file that contains the content to be read. The program generates an ouput file named sample_output.txt with the searched word highlighted.
This program deals with Image detection and Extraction It will detect various objects of interest and store them in separate image files.
This program gives the details on how to connect to sqllite database. It also explains how to create tables and insert the data. Finally, you can execute your own queries to build insights from the underlying data
This program aims at exploring openpyxl module. It gives details on how can we write Python Dictionary Elements into an excel file
This program is used to generate random alpha-numeric password of 8 characters
This program is takes 2 string as input and check the amount of similarity between them. Here, we have used the concept of finding cosine of angle between the vector. Smaller the angle(i.e higher the cosine value), more similar are the sentences
This program illustrates simple step by step process of developing a Python module that can be used generically across multiple Python Projects
This program illustrates how you can create your own sentiment analysis algorithm to check for the percentage of positive and negative words. There are cases where "not good" is used to indicate "bad" and "not bad" is used to indicate "good". You can play around with this code to include your own cases and have fun.
This program illustrates how you leverage Python Debugger for tracking bugs instead of clumsy print statements. Pdb is a great tool in Python standard distribution to make use of.
This program illustrates how you create a file splitter that can split your large files into smaller files based on the number of splits you desire.
This program illustrates how you scrape a website using selenium package. The package is very easy to use if one understands the html dom elements.
This program illustrates how you scrape a website using selenium package. The package is very easy to use if one understands the html dom elements. The python code will help in image data download in your local folder
This contains end to end analysis of health insurance dataset using Python. It also covers the code for machine learning modelling to predict the charges of health insurance for the customers based on age, bmi index and other factors.
This code is written to provide a beginner tutorial to demonstrate how flask can be used to deploy the model. We have developed a model, stored in pickle file, created a code using flask to use the pickle file to render the result on a web page.
This code is written to provide an introductory approach to embed powerbi report into Jupyter Notebook. The process though simple, requires some considerations before beginning. The aim is to provide hassle free pointers for integration.
This code is written to provide an introductory tutorial for common spark commands used for data analysis. This code will help in comparing pandas and spark operations on the placement data. Apache spark is an open source unified analytics engine for large scale data processing. It is 100 times faster in operation and hence preferred for big data analysis.
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