Python Resources - Basic Python, ML, DataScience, BigData

#PracticeCode: 0033 🎯 FORWARD IF YOU LIKE IT 🎯 Task: Input a list of Numbers(int or float). You have to print their sum unless they are danger(13 to 19). Danger number counts as 0. Number 14 and 17 are exception, there not taken as danger numbers. Sample Run :- input → (4,16,9) output → 29 input → (6,8,12,14) output → 26 GOOD LUCK! ««« Discuss your solution @python_programmers_club and proper solutions will be added to our Github page »»» ««« Click here for the Solution »»» 🔥Ready to take this challenge? 🔥 #python #practiceCode #samples #interviewQuestions #conditions

#interviewQuestions : 0009 Q: What can we do using Python Q: Applications of Python Q: Explain some of the areas where we can use Python As mentioned before, Python is one of the most widely used language over the web. It is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. To list few of them here: ○ Databases − Python provides interfaces to all major commercial databases. There by making it useful to create tools or GUI of databases, and also to use with an application which involves interacting with data. ○ Web Applications - We can use Python to develop web applications. - It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser etc. - There are many well-known web Frameworks such as Django, FastAPI, Pyramid, Flask etc to design and develop web based applications. ○ Desktop GUI Programming − - Python supports GUI applications that can be installed and run locally on systems like Windows, Linux, iOS etc. - Python provides Tk GUI library to develop user interface in python based application. - Some other useful toolkits wxWidgets, Kivy, pyqt that are useable on several platforms. The Kivy is popular for writing multitouch applications. ○ BigData and Data Science - - Python and Big Data is an inseparable combination when we consider a programming language for big data development phase. Being Open Source, wide community, and a huge library, its best suited for Big Data projects. - Python has become the number 1 language in Data Science projects. - Some important packages Pandas, Numpy, SciPy, Theano, Scikit-learn, etc provide everything that a developer needs to work on Big Data and machine learning projects. - PySpark is also an example of its use. - Compatible with Hadoop. As Python big data is compatible, similarly Hadoop and big data are synonymous with each other. Hence, Python has been made inherently compatible with Hadoop to work with big data. Python consists of Pydoop package which helps in accessing HDFS API and also writing Hadoop MapReduce programming. Besides that Pydoop enables MapReduce programming to solve complex big data problems with minimal effort. - An example is IBM using python, they even have a Python SDK for Watson, and they use python extensively. - Netflix, Spotify use extensively for their recommendation and analytics engine. ○ Console Based Application - We can use Python to develop console based applications. IPython is the best example for this. ○ Multimedia Applications - Python is awesome to perform multiple tasks and can be used to develop audio and video applications. ○ Python is can also be used to develop - 3D CAD Applications - Enterprise Applications - Image Processors and editors There are several such applications which can be developed using Python

#DataWrangling : Task: 0003 ——————————————————— Continued from 0002 🎯 »»»» FORWARD IF YOU LIKE IT «««« 🎯 Task: The categories column contains the category and a list of sub-categories. Extract them into separate columns, with names as Category suffixed by a number depending on the hierarchy. The level of hierarchy is not the same for all, you need to handle it. Optional Tasks: »» Clean up the newly created Categories columns by removing additional spaces. Try using regex. 📝 ———»»» Click here for the dataset ««« ——— ««« Send your solution @hbabureddy and proper solutions will be added to our Github page »»» 🔥Ready to take this challenge? 🔥 ««« Click here for the Solution »»» #python #practiceCode #samples #DataWrangling #pandas

#interviewQuestions : 0008 List.copy() does a shallow copy of the list, but when we check their id's they point to different address? Why? A shallow copy means constructing a new collection object and then populating it with references to the child objects found in the original. Hence, when you check their id's they both point to different address. check out this code L1 = 1, 2, 3, 4 # Using copy() to create a shallow copy L2 = L1.copy() print(id(L1), id(L2)) >>> 2763664559240 2763665433480 In the above result, address are different, they both point to different locations. But, the elements will be pointing to the same objects in both the lists. Check this code: print(id(L10), id(L20)) >>> 140703554137856 140703554137856 See the result, the elements point to the same address in memory. #list #collection #shallowCopy

#PracticeCode: 0032 🎯 FORWARD IF YOU LIKE IT 🎯 Task: An ATM machine has 2 denominations of currency notes , $10 & $50. Accept the number of currency notes available in the machine and the withdrawal amount. Than calculate if with the available denominations , whether a user can withdraw the amount or not. Sample Run :- input → $10 = 3 , &50 = 1 , W.A. = $80 output → True input → $10 = 3 , $50 = 1 , W.A. = $90 output → False GOOD LUCK! ««« Discuss your solution @python_programmers_club and proper solutions will be added to our Github page »»» ««« Click here for the Solution »»» 🔥Ready to take this challenge? 🔥 #python #practiceCode #samples #interviewQuestions #conditions

#interviewQuestions : 0007 What is the output of the following statement? Explain Why? 16//-3 Output: -6 // (Floor division) It gives the floor value of the quotient produced by dividing the two operands. In other words, the floor division // rounds the result down to the nearest whole number. print(x/y) print(x//y) Notice that we are using the same values for x and y operands. But the result is quite different between / and //. When the result of floor division (//) is positive, it is as though the fractional portion is truncated off, leaving only the integer portion. When the result is negative, the result is floored, i.e., rounded away from zero (towards negative infinity). In other words, rounded down to the next smallest (greater negative) integer. Let us see some more examples. print(float(x)//float(y)) # Notice the result will also be a float. x = -13 # Notice the value of `x` is assigned by with a unary negation (`-`) operator y = 3 print(x//y) # Notice the result. # Instead of rounding up to 4 like in the case of a positive result, it round up to -5, the lesser value x= -13.0 # We changed the type of `x` from int to float. No change in value. print(x//y) # What will be the result. Unlike the standard division (/), the result is not always a float. But when one of the operands is a float, then the result will also be a float. Division by zero will yield in the same error as above.

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#PracticeCode: 0031 🎯 FORWARD IF YOU LIKE IT 🎯 Task: You have to create a program in which two strings has to given as input. Now you to print True or "yes" if any one of the strings is present at the end or start of the other. Else print False or "No". Sample Run :- input → 'Hiabc' , 'abc' output → True NOTE :- It's should not be case sensitive. GOOD LUCK! ««« Discuss your solution @python_programmers_club and proper solutions will be added to our Github page »»» ««« Click here for the Solution »»» 🔥Ready to take this challenge? 🔥 #python #practiceCode #samples #interviewQuestions #conditions

#interviewQuestions : 0006 What is pep 8? PEP 8, sometimes spelled PEP8 or PEP-8, is a document that provides guidelines and best practices on how to write Python code. It was written in 2001 by Guido van Rossum, Barry Warsaw, and Nick Coghlan. The primary focus of PEP 8 is to improve the readability and consistency of Python code. PEP stands for Python Enhancement Proposal, and there are several of them. A PEP is a document that describes new features proposed for Python and documents aspects of Python, like design and style, for the community.

Retouch Image - Nvidia InPainting The algorithms can replace images or remove unnecessary details in the photo. To do this, upload a photo and use the brush to create a mask of the desired object. https://www.nvidia.com/research/inpainting/

#interviewQuestions : 0005 Is Python interpreted or compiled? A common question: “Is Python interpreted or compiled?” Usually, the asker has a simple model of the world in mind, and as is typical, the world is more complicated. In the simple model of the world, “compile” means to convert a program in a high-level language into a binary executable full of machine code (CPU instructions). When you compile a C program, this is what happens. The result is a file that your operating system can run for you. In the simple definition of “interpreted”, executing a program means reading the source code a line at a time, and doing what it says. Compiling is a more general idea: take a program in one language (or form), and convert it into another language or form. In Python, the source code is compiled into a much simpler form called bytecode. These are instructions similar in spirit to CPU instructions, but instead of being executed by the CPU, they are executed by software called a virtual machine. So, if you can explain all this, then you can say its both a compiled and interpreted language. But, if you want to give a simple and short answer, then say it is a interpreted language.

Cheat sheet for choosing ML algorithm: https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-cheat-sheet #machineLearning #algorithm #tips #cheatSheet

Aspects for choosing ML algorithm. Not nesessary only for Azure pipelines: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-select-algorithms #machineLearning #algorithm #tips