is python enough for data science

Is Python Enough for Data Science? (Explained)

Data Science has become one of the most demandable domains in recent years and python has become one of the most popular programming languages used for data science. But most people, often confused about is python enough for data science or not? so, I have done a ton of research about this topic and in this article, I am going to share with you some essential information about this topic.

According to Wikipedia, data science is a field where data scientists put all the scientific processes, methods, and algorithms to extract knowledge from structured and unstructured data and apply knowledge from data across a broad range of applications domains. And the python programming language and the R programming language have become the most popular languages used for data science.

So, is python enough for data science? the answer is no, python is very much needed for data science, but it is not enough for data science. Besides the Python language, the R programming language is also very much required for data science purposes. And besides, that to learn data science you should have to learn some math and logic concepts. In the below section I have discussed why python programming language is not enough for data science, so stick to the end of this article.

Why Python is Not Enough for Data Science?

As I mention in the upper section, the python language is not enough for data science, to learn all the data science concepts you have to gain some more information, and here I state those-

Data Analysis:

There is not any doubt that python is the most suitable programming language used for data science, but in some areas python language is not so useful, such as within data science the data analysis and statistical modeling portion are mainly developed with the help of R programming language.

So, for the data science purpose, the R programming language is equally important with the python language.

Basic Programming Knowledge:

Besides the Python language, several languages are very much required within this data science field. Most people were started their data science career with python language but after some time, they leave the path, this is mainly happening because they do not acquire any basic concept of programming language.

And according to my recommendation before jumping into this data science field, you have to always learn the basic languages like- C language, C++ language, etc.

Maths Concepts:

Besides the Python language, math concepts are also very much required within this data science field. If you are not good at math then data science will become very very difficult for you.

Without math, the learning of data science will become very complicated for you, because every aspect of data science- such as features concepts, and modules concepts everywhere math is required.

So, if you are not good at math, then try to learn the concepts of math, otherwise, learning of data science will become a dream for you.

Statistics:

Here the term statistics suggests the data, within data science, everything is co-related to the data. So, all the mathematical equations that you are going to apply you will be applying based on some specific data.

So, within data science, math and statistics are very very much important.

Databases:

The databases are also very much required within this data science field. And at least you have to learn some basic concepts of databases. Because database plays a very very important role in data science projects.

All the data is initially stored in some databases and you just pick the data from that place then you perform the data science works. So, for this reason, some basic knowledge of databases is required.

And you can learn the basics of any database such as SQL, Mongo DB, etc. And if you jump into the data science field after learning the database portion, then you will be called a full-stack data scientist because you know all the portions of data science such as yu know programming concepts, database concepts, maths concepts, statistics concepts, etc.

These are some of the skills that you need as a data scientist as long as with python programming concepts. So, it is proved that python is not enough for data science, besides python language these skills are equally important.

How much Python do data scientists need?

To learn data science there is no need to learn all the concepts of python programming, and here I mention the topics and if you learn these python topics then it is enough for the data science-

  • First started with the basics of python language such as (Arrays, functions, data type, variables, and syntax).
  • After learning the basics of python then started to learn about the regular expression of the python language.
  • After that move to scientific libraries of python programming- such as NumPy, SciPy, Pandas, etc.
  • And finally, learn the concepts of data visualization.

If you have learned these things then these skills are enough for data science.

Is Python the best language for data science?

There were several programming languages are available, but not all languages are suitable for data science. And within the data science field, the main competitor of python is the R programming language, and this language can perform all the data analytics and modeling used for data science.

So, because of the availability of the R programming language, it can not be said that Python is the best programming language, but it is can be said that python is one of the most useful programming languages used for data science.

In Conclusion:

In this article, I have discussed whether is python enough for data science or not? and based on all the facts it can be said that only python concepts are not enough for data science, besides python, you have to learn lots of other things.

I hope you have liked this article and if you have any kind of query then you can ask me in the comment section, share this article with your friend and follow this website regularly for these kinds of informational and helpful articles.

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