10 Tips Data Science With Pythonhttps://guttulus.com/wp-content/uploads/2018/12/IMG_0429-1024x670.jpg 1024 670 tony tony https://secure.gravatar.com/avatar/aa9bbdf8f1e6bbf534778ecea7c0c925?s=96&d=mm&r=g
Data science is very reliant on software to achieve its objectives. Although the hardware on which the software runs dictates things like computing abilities and speed, data science is down to the software and its building blocks.
In this blog post, Guttulus looks at one of the most important, if not the most important programming language of all time in data science; python. Hailed as arguably one of the best programming languages of this generation, python plays a very important role in data science.
Here is a closer look at data science with python and why the programming language is so significant in the world of statistics. Here are the 10 tips of data science with python;
10 Tips Data Science With Python
Here are some of the reasons why Python is still the most important programming language in data science:
Large number or libraries
Python has a large number of libraries which will help you to carry out a number of tasks in data science. These tasks include automation of the user graphic interface, handle multimedia data, handle databases and to process text data. These are all tasks which are very crucial in the world of data science.
Python is very flexible
Flexibility is the other reason why a lot of people prefer Python to the other data science programming languages. It affords its users the convenience of solving as many problems as possible in the shortest possible time. If you make exhaustive use of Python, there are endless possibilities as to what you can achieve.
Better analytics tools are built from Python
Data science is very reliant on data analytics. Data analytic tools provide information that helps shed light on given data patterns, provide better insights into the data and correlate data from big datasets. The best programming language when it comes to creating analytical tools.
Python is open source and free
The other thing that makes python ideal in the world of data science is the fact that it is open source. Anyone can therefore access it and the fact that it is cheap makes it ideal for any project. Anyone can access python and its large library and use it for whatever project you have in mind.
Python has a large community
The community using a programming language matters a lot. Without a large interactive community, using a programming language becomes very difficult as you can’t consult on problems and brainstorm on possible improvements. Fortunately, Python has one of the largest communities and user bases in the world. In case of a glitch or clarification that you need, there are millions of people from whom you can consult.
Visualization and graphics
Python has very many data visualization libraries and features which are needed in data science. Data visualization and presentation is very important in data science as it helps scientists to easily pick up trends and also debug their codes. Things like graphical representations are easier and more interactive when using python as the programming language.
Python is crucial in machine learning
With its packages such as Tensorflow, Keras and Theano, Python provides data scientists with an opportunity to come up with better learning algorithms. This makes python about more than just analyzing data sets. It is used in understanding neural networks and building artificial intelligence systems.
Python is very easy to learn and use
Python is very easy to use on a day to day basis. It is pretty straight forward to learn and once you have grasped the basic concepts, advancing to fundamentals will be very simple. The syntaxes of python are also very relatable and don’t need to be commented out for you to understand them.
Data preparation and presentation is easy
Preparing data for presentation using Python is very easy. Programming languages such as R and Java are not as ideal when it comes to presenting the data in a way that other people with little knowledge in programming can understand.
Python is not limited in terms of functionality
R and Java are bespoke in nature which means that they are limited in terms of functionality. Python on the other hand, is a general purpose programming language which means that it can carry out more than one purpose. This is very important in data science as there are very many facets to it and python can handle a lot of the functionalities.
Python classes and courses are available online for free
Good thing about Python is the fact that most of its basics and fundamentals courses are available online for free and anyone can advantage of them. If you are planning to get started on Python, all you need is to hop online today, look for an ideal course to get started and in no time, you will be making inroads in the world of data science.
Give Guttulus a shout to get started in Python programming
If you are looking for the best tips and guidance on Python programming in data science, you have every reason to give Guttulus a shout. Join our mailing list today and ensure that you read our blog on a regular basis for more tips and guides on how to get started in Python programming.