How Python Became the Language of Choice for Data Science

Python has risen in popularity across a number of industries and professions. The rise of the programming language can be attributed to its ease of accessibility and its numerous libraries and frameworks. A survey conducted indicates that Python is used the most by many technology professionals to execute various jobs. Just like Python, data science has grown in popularity in recent years. With data science, we can convert big amounts of data into meaningful marketing strategies. Interpreting data correctly is very important for any organization. That is why companies require data science consultancy services to help in complex areas of data science such as data analytics. Data analysts require tools like Python to help them draw meaningful insights from the huge amounts of raw data. Python is preferred by many for the following reasons.

Easy to Learn and Use

Having this attribute is fairly unique when compared to other programming languages. This has made Python a top choice in the fields of analytical and quantitative computing. It has been used in several industries such as scientific computing, finance, processing signal industries and many more. It has also been applied in the creation of apps like YouTube. The language is able to coordinate a large number of clusters of computer graphics and can be quite useful during the production of movies. This has been largely possible due to its versatility .

Flexible and OpenSourced

This is a further reason why Python is becoming increasingly popular. The language is made up of numerous libraries that are easy to learn and use for every data analyst, an attribute which has proven to be quite useful in data manipulation. Anybody who has used other programming languages such as Java or Visual Basic will find that Python is far more accessible and applicable . It is an independent platform and can be integrated easily into the available platforms, not forgetting its exceptional abilities in solving complex problems. Python has become more powerful over the years, as it can be run everywhere, is friendly and communicates well with other programs .

Multiple Uses

Python is simply the best programming language as far as data analytics is concerned. Even a person who is new to the field of data analytics can use Python to help them get started in the field. While banks can use Python for data crunching, other entities use it as a tool for data analysis and visualization. Not only can it be used in transforming big data into useful information, Python can also be used to create applications, making it even more popular.

Contains Powerful Statistical and Numerical Packages

Python has packages such as NumPy and Pandas which enable you to easily read and manipulate data . It also has a package known as Matplotib which is crucial in the creation of powerful data visualizations. Scikit-learn is another package that allows you to use machine learning in making predictions.

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