Reasons Why Python Language is famous among Data Scientists?

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As there is an increase in demand for machine learning and artificial intelligence field, the data scientists are focusing more on Python Language

So let’s discuss the reasons for Python language popularity is?

The first question is what Data scientists do.

They try to explore the data by using scientific techniques, algorithms, and other ways. Data scientist processes that data and extracts useful information from it which is most important for business purpose. 

What is the Python Language and why to use it?

Checking programming code
Checking programming code

Now try to understand what the python language is.

Python is easy to learn a dynamic language that is the first choice of Data scientists. With the use of python, it is easy to develop things quickly and interface with other algorithms.

Python is the choice of data scientists using which they can perform their daily tasks. You can think of it as a tool to be used in the industry. The fluent and natural style code written in the python language is called Pythonic. Sounds Cool!!!

The main reason for using the Python language is the digitalization of business. Recently every online business is generating a lot of data that hides the predictive information that is useful for marketing benefits.

The predictive information hidden inside this data can help the online business to grow faster, measure performance, and also helps in the identification of any problems.

So to get useful insights from the available data, there is a need for a business analyst or Data Scientist. However, the overall role of the Data Scientist is to manipulate data and analyze it

I think You are getting the understanding.

Reasons for Python language Popularity

The popularity of Python language is because it is an easy language as compared to C and Java. With the help of python, it is easy to implement algorithms. Besides, python facilitates users with extensibility and helpful in managing the data.

You can learn the python language bit easily because it has many inbuilt APIs that will help you to write fewer code lines. Sometimes data analysts need to integrate data with web applications that are easy to perform with python language.

The python language facilitates users with community participation through various resources and libraries. Python provides fast programs and prototype runs.

A survey shows that for years an approx 48% of data scientists prefer the python language because of its easy to use environment.

Also read An introduction Flask Python |Top Ways to Install Flask?

Why Data Scientists need Python Language?

Data scientists need to extract useful information from data, registers, and stats. But actually, that data is not sorted, which means you have to put extra effort to obtain meaning from this. So to easily do this task, python language is the first choice.

With the use of python, you can generate CSV output for data reading. Python is such a programming language that supports a structured, functional, and object-oriented approach.

You can say that python is a fast language as compared to R and Matlab. The reason that data scientists prefer python is that it provides them more flexibility and robustness as compared to other data processing languages.

Python makes data processing very easy with the help of various data science libraries such as Scikit- learn, pandas, Matplotlib, and Numpy.

As I told you, python language is open source and providing libraries for scientific computation and technical work, so it is the best option for data scientists. Overall you can say Numpy and pandas are very helpful to explore the data in python.

On average, it provides approximately 70,000 libraries that kept on increasing. Here are a few specific advantages related to the use of python libraries.

  • Scikit-learn library in python used for machine learning purposes.
  • To process data related to data science, you can use the panda library.
  • You can use the Matplotlib library for visualization tasks and the generation of charts.
  • To perform a mathematical and statistical operation using python, the library used is Numpy.

The syntax of python language is simple, because of which Data scientists prefer it mostly. There are few other reasons for adopting python is it provides quick prototyping and easy understanding to beginners.

List of Python Libraries

If a Data scientist is willing to learn the Python language, the scientist should have excellent mathematical and statistical knowledge. The python language is famous in a complete aspect where the R language is preferable for academics and research.

But in data science, you need the python language use at every single step. In this topic, I am briefly giving a list of various python libraries that can be used by data scientists as follows:

  • SciPy
  • StatsModels
  • Eli5
  • NLTK
  • Scrapy
  • Spacy
  • Tensorflow
  • Scikit-learn
  • Bokeh
  • Pandas
  • Seaborn
  • Matplotlib
  • Numpy
  • Plotly
  • XGBoost
  • Pydot
  • Keras
  • Dist-Keras
  • Gensim
  • PyTorch

Through this topic, you are now well familiar with python’s first benefit that is easy to learn. It is easy for data scientists to learn and write code quickly using python language. For anyone who is having less time to learn new technology, it is a great choice.

Python languages also excel in the case of scalability. Scalability is provided to data scientists by availing them with various ways to solve any problem. Due to the reason of scalability, YouTube also adopted this language.

The popularity of python is also due to the Python community. Many volunteers are serving the community by creating various data science libraries. The ultimate task of the python community is to provide solutions for challenging problems.

The python community has many programmers that can help you if you struck somewhere to find the answer to any issue.

Features of Python Language

Python also provides graphics for data scientists. With the use of various libraries like Seaborn and ggplot, scientists can gain access to many data charts, graphical plots, and web-ready plots.

I am also giving a few points about why it is the best choice to be used by data scientists as follows:

Easier learning and usability

Python is not complicated at all and focuses only on natural language. Data scientists use python language code that can be write down with ease and faster to execute as compared to other programming languages codes. 

Corporate sponsors help to glow

With the help of sponsors, languages grow faster. So same is the case of python language as Facebook, Amazon, and Google support it.

Availability of various python libraries and frameworks

Python language provides several libraries and frameworks to use that helps the developers by reducing their time and effort for development.

The popularity of the python language

The development of the python language started 30 years ago. Due to this fact, the python language got a lot of time to grow and mature. There are various tutorials, videos, and documents available for the python language that are useful to understand this language. 

Reliable and robust

The python language can be used in various types of environment and provides high performance always. The trustworthy nature of the python language attracts many data scientists. 

Open source

Python is quite famous due to the reason that it is open source. Python language has the support of the community where a lot of people are contributing. Being open-source python language helps developers and learns the most.

Interpreted and object-oriented language

Python is an interpreted and object-oriented language that is why it is popular among data scientists.

High in demand

Python language is the first choice of data scientists and developers. It is high in need due to the development and digitalization of business. 

Used in academics and research

Several students and researchers use python language for data analysis purposes. So you can say python language is a good career option if someone wants to be a data scientist or data analyst.

Easy automation

Python facilitates data scientists with various tools and modules that can help them in tasks related to automation. There is a need for only a few lines of code for automation tools.

Flexible and scalable environment

Python language gives the data scientist such an environment using which he can develop something new. Using python language, you can make different types of applications.

The simplicity of language

There is no limit to the functional capabilities of the python language. Python is fast in writing as compared to java language. 

Web development facility

Python language used for web development. The famous frameworks used for web development are Django and Flask. Through python language, it is very much easy to write the code in a few minutes as compared to other languages.

Supports test automation through python frameworks

For testing purposes, python language facilitates data scientists with a robust framework, pytest, behave, lettuce, and unit test.

Overall growth

Young confident female marketer showing graph of financial development
Graph of financial development

Python provides various growth opportunities to data scientists. Python is itself also a powerful language that is growing day by day. By learning the Python language, you can even switch to various other python related jobs.

With the help of the python language, there has occurred a great revolution in the field of Deep Learning.

So python language is an adapting language that is supposed to learn by Data scientists. It is the preference of machine learners to make fraud detection algorithms and provide network security.

So, Data scientists also make use of python language for natural language processing and sentimental analysis. In short, the few features facilitated by python language are:

  • It is a bit easy to implement python language, as it takes less time to implement.
  • It provides various easy-to-use libraries for machine learning, artificial intelligence, deep learning, natural language processing, and neural network.
  • You can develop your library also and upload it.
  • Python is the requirement of various companies such as Netflix, IBM, Dropbox.
  • It is a trustworthy language used for data science and web development also.
  • Python is well tested and ready to use the language; only you have to write a code.
  • Python is also a user-friendly language, so it gained its popularity.
  • Using this language, scientists can easily express their thinking.
  • You can write code using this language, which is easily readable and modifiable.
  • It supports automatic deployment and web development.
  • Python can reduce your working time to be spent on any task from hours to minutes.

Conclusion

You can think that the python language is a quite useful programming language, especially for data scientists. You cannot say that the python language will overcome by some other language one day because it is still getting updates and releases.

As there is an increase in the need for ML and big data, the python demand will also grow so that you can use it in the business and government sectors.

I am not saying that the current market isn’t full of competition but, the python language is the cool language I have ever found. It is a kind of base language for data scientists, and its popularity is at a peak level. 

To start working with the python language, Data scientists only need to have a little knowledge of programming. So the demand for the python language is rising as the number of data scientists is increasing.

As the demand for data science will increase in the next years, the python language is going to become the mandatory language for analysis purposes. With the notes, I can say Python language is the best language for data scientists.

I could be wrong at some points so, do correct me with your valuable suggestions.