Tuesday, July 23, 2019

How Did Python Become the Language of Choice for Data Science?

Not long ago, R was the most popular data science language. That has changed now with Python overtaking R as the most preferred programming language by data scientists. We are left wondering how Python managed to knock R off and become the most popular language choice for data science.
The number of people using Python as a programming language has been going up yearly and perhaps this is because Python offers a lot. Python has numerous libraries that are suitable for any data science project. A lot of organizations in different industries are adopting Python as a language for data analysis and visualization.

We all know how important data is to business entities. If analyzed well, organizations can identify growth opportunities. We have several programming languages like SQL, R, and Matlab, but Python is way ahead because of the following:

Easy to learn and use

Nowadays, small and large business organizations collect huge amounts of data from various platforms, social media being a major one. There is a need to analyze this data to draw actionable insights. Small organizations cannot afford to source the services of data consultants. With Python, you can analyze your data even with little expertise in data analysis.

Python has been designed in a way that it can identify and associate various types of data automatically. This way, it becomes easy to use while also consuming little time. If you want to draw more actionable insights from your data, then you can seek the services of data consultants from activewizards.com.

General-purpose programming language

Once you have set up the Python language on your system, you can execute a lot of functions with it. In addition, Python is designed in a way that you can use it to do all data analysis related tasks.

With Python, you can create machine learning models and even design web applications with just one language. This way, you can make your project simpler, thus saving up time and money. It also has several algorithms that have been quite useful to data scientists for data processing.

Numerous libraries

There are several libraries that can be used by data scientists to analyze and visualize data. The most popular libraries used are available in Python. The fact that data experts can execute their tasks using a single language makes Python even more popular.

As time goes on, Python is adding more and more libraries. Apart from that, there is a platform where data scientists who have designed their own libraries can share them for others to use. Some of the most powerful libraries in Python are Pandas and Scikit-Learn.

The Python community is rising up

At the moment, we have several libraries in Python, most of which were created by data scientists in the Python community. NumPy is one of the libraries designed by the Python community that is used for scientific computing. At the Python community, you can also find discussions centered on jobs related to data science. You can also obtain answers to any questions you have regarding data science.

The Python language offers many benefits to data scientists and organizations at large. It is easy to learn, easy to use, and all of your favorite libraries can be found in it. Python is the best language of choice for data scientists and it is going to be that way for the foreseeable future.  
Not long ago, R was the most popular data science language. That has changed now with Python overtaking R as the most preferred programming language by data scientists. We are left wondering how Python managed to knock R off and become the most popular language choice for data science.
The number of people using Python as a programming language has been going up yearly and perhaps this is because Python offers a lot. Python has numerous libraries that are suitable for any data science project. A lot of organizations in different industries are adopting Python as a language for data analysis and visualization.

We all know how important data is to business entities. If analyzed well, organizations can identify growth opportunities. We have several programming languages like SQL, R, and Matlab, but Python is way ahead because of the following:

Easy to learn and use

Nowadays, small and large business organizations collect huge amounts of data from various platforms, social media being a major one. There is a need to analyze this data to draw actionable insights. Small organizations cannot afford to source the services of data consultants. With Python, you can analyze your data even with little expertise in data analysis.

Python has been designed in a way that it can identify and associate various types of data automatically. This way, it becomes easy to use while also consuming little time. If you want to draw more actionable insights from your data, then you can seek the services of data consultants from activewizards.com.

General-purpose programming language

Once you have set up the Python language on your system, you can execute a lot of functions with it. In addition, Python is designed in a way that you can use it to do all data analysis related tasks.

With Python, you can create machine learning models and even design web applications with just one language. This way, you can make your project simpler, thus saving up time and money. It also has several algorithms that have been quite useful to data scientists for data processing.

Numerous libraries

There are several libraries that can be used by data scientists to analyze and visualize data. The most popular libraries used are available in Python. The fact that data experts can execute their tasks using a single language makes Python even more popular.

As time goes on, Python is adding more and more libraries. Apart from that, there is a platform where data scientists who have designed their own libraries can share them for others to use. Some of the most powerful libraries in Python are Pandas and Scikit-Learn.

The Python community is rising up

At the moment, we have several libraries in Python, most of which were created by data scientists in the Python community. NumPy is one of the libraries designed by the Python community that is used for scientific computing. At the Python community, you can also find discussions centered on jobs related to data science. You can also obtain answers to any questions you have regarding data science.

The Python language offers many benefits to data scientists and organizations at large. It is easy to learn, easy to use, and all of your favorite libraries can be found in it. Python is the best language of choice for data scientists and it is going to be that way for the foreseeable future.  
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