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Data Science using Python Tutorials

Benefits of Learning Data Science with Python

In the last decade, we have witnessed the emergence of a new concept in Business Intelligence, and it has taken the whole world by storm. Yes, we are talking about Data Science. The amount of data each business is producing these days is enormous. It paved the way for the emergence of data science and other BI concepts. In the current scenario, the data scientists are in huge demand and enjoying lucrative careers. Data analysis using Python is the standard method followed by numerous organizations. Python is easy to implement, and versatile language learning data science with Python brings many advantages to developers. 

Ease of Learning 

Many people want to jump into the data analysis field, but the major hindrance is the lack of coding skills. Adding to this, the perceived difficulty in learning the coding is holding back many aspirants. But if you opt to learn data science with Python, you will be free from this problem. Python is very easy to understand, and people without any coding knowledge can start learning in a short time. Python’s syntax almost looks like English, and it becomes straightforward to read and understand the coding. Even with a non-technical background, people can read and understand the codes to some extent. 

Compatible with Hadoop 

When it comes to data management and analysis, one can’t simply deny the necessity of the Hadoop ecosystem. It is one of the basic needs if you want to handle the enormous amount of data sets. It helps to manage both structured and instructed data sets with ease. Learning Python provides you the advantage while using Hadoop because Hadoop supports Python programming language and many other popular languages. The PyDoop package of Python lets the developers access the API of the Hadoop platform. The task of data mining, data management, and data visualization becomes a comfortable task if you know Python and Hadoop. Hence, we see many developers do data mining using Python.

Easy for Data Visualization 

Data visualization is one of the critical things a data scientist must be aware of. Many businesses are now looking at the data visualization tools to get the most out of the data sets and derive meaningful insights to make the decision-making process more comfortable. Even for the data scientist’s visualization helps to understand the data better. The libraries, including NetworkX, Matplotlib, ggplot, etc., and other APIs enable you to create stunning visualization. Python supports all these tools. Also, you can integrate different data visualization tools if you know Python. Numerous organizations are conducting the process of data structures using Python

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Faster processing and development

The amount of data a data scientist had to deal with is unimaginable. Hence while dealing with big data sets, speed becomes a critical aspect. If the programming language you use is slow, then the process becomes very lengthy and ineffective. Python is one of the easiest and clean programming languages containing very few lines, even complex coding. It helps to cut down the time required to code the program; however, the slow execution is the major issue with Python. But with the Anaconda platform, this complaint is taken care of. Due to this, even we can see engineers are performing data scraping using Python.

Large community 

The most significant advantage of Python is the massive community support. This makes understanding and learning this language easier. Whenever you are stuck with any problem, you can ask in the community or read the resources and tackle the problem with ease. And many developers in the community develop new libraries and packages which help in varieties of situations. The strong community is one of the reasons you can find frequent updates and new features. 

Powerful packages

The packages and libraries make Python one of the most loved programming languages. It comes with a wide range of packages, including SciPy, NumPy, Pandas, PyBrain, etc. These packages enable the developers to code complex problems with ease. You can also find many libraries that facilitate Python’s integration with other languages, including SQL and C. These things make Python very powerful. Without a doubt, it helps to handle all data-related problems with ease. As a result, many are using python for Data Mining these days.

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