Data Science Foundations Tools and Techniques: Core Skills for Quantitative Analysis with R and Git PDF BOOK FREE FULL 2022.
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Data Science Foundations Tools and Techniques: Core Skills for Quantitative Analysis with R and Git PDF BOOK FREE FULL 2022.
Why we love Python for data science:
Introduction:
Aptude has served as expert data consultants for some of the world’s best-known companies, some of which we cannot name.
Our clients cover almost all sectors and ask us to help them in a variety of projects, including full stack development; IT services management, data dashboard and UX/UI.
And while we can do almost anything, some of our best work involves deep data science expertise, especially when it comes to Python plus Data Science.
We love data science and Python so much that we have developed a Python Centre of Excellence in Mexico City, Mexico, to attract, train and place experienced talent in local and remote projects.
In this article, we will explore why we love Python so much for data science, especially compared to other languages such as R or Scala.
The languages of data science:
First, it is useful to understand why programming languages are necessary for data science.
The first thing to know is that data has always used some kind of programming language to work.
Relational databases, for example, use SQL forms (including T-SQL) to tell the database what to do with the 0 and 1 that make up the database data. Because data is just that - static fields with (often) structured information. That’s right.
The second thing to know is that data science involves manipulating extremely large datasets ('big data') using complex mathematical algorithms.
Where SQL involves simple commands to join data lines, add or delete data and create simple «views», advanced data science programming languages manipulate data in a way that would It's so expensive, and it's really impossible to do it manually or even in a spreadsheet.
Some of the languages available for data science are:
R
Python
Matlab
Java
Hadoop
Julia
Scala
Ruby
For our money, Python is where he is. And it’s not just because, survey after survey, Python is the most sought-after, popular and beloved language.
Python is used for 1:
Desktop GUI
Scripting
Web development
Game development
Machine Learning
Data science
Data analysis
Artificial intelligence
Internet of Things (IoT)
Computer vision
Web Scraping
Natural language processing
Scientific and numerical computation
Development of software applications
Network programming
Data Science From Love Things We Work On In Python Programming Language
Python is an excellent programming language for data science work.
This is why we love it…
Python is easy to learn. From a programming point of view, Python is one of the easiest languages to learn, This means it’s also one of the best at building larger teams of experienced developers and it’s easier for our customers to maintain those teams once our core work is complete. We are also likely to find Python already used in client organizations because of this learning facility.
(Of course, learning and working on data in terms of forecasting and analysis is a different issue.)
Python is flexible. It works on almost all platforms, including Windows and MacOS. As a language, it works quite well for a variety of uses, making it versatile and flexible.
Python programmers are more affordable. Although you can do a lot with Java, R and the Hadoop framework… This does not mean that work has an affordable price.
Industry leaders trust Python. Google, Youtube, Instagram, NASA, IBM, Netflix, Spotify, Uber, Pinterest, Reddit and many others use Python.
Python is an effective code. For what you can accomplish in R, you will use much less code by writing it in Python.
Python has many libraries and data science tools:
NumPy and pandas
Scikit-Learn for Machine Learning (ML)
PyBrain
Tensorflow
PyMySQL for MySQL databases
Python notebook for interactive programming
matplotlib for data visualization And many others
