To become a Data Scientist you have to learn Python programming very well because it is the most effective programming language used for Data Science purposes. In this article, I am going to explain some of the Best Python IDEs which are useful for Data Science.
Python has become one of the most prominent programming languages at the current time because of its uses. It can be used in several areas such as in artificial intelligence in machine learning as well as in data science. All these fields are very closely correlated with one another.
Data science is a field that combines several other fields. These fields include scientific method, statistics, data analysis, extracting data value, etc. As I mentioned in the upper section to become a data scientists you have to gain some sort of expertise within this Python programming language because it is the best language used for data science purposes.
IDE also known as the Integrated Development Environment, whenever any programmer wants to write some code they require some integrated development requirement so that it brings some easiness to write the code such as syntax highlighter, automatic filling up the code, variables, and other things.
So, what are some of the best Python IDEs used for Data Science? There are several IDEs are available which are useful for data science but here I mention 6 best IDEs name which is best among them-
- PyCharm
- Spyder
- Jupyter Notebook
- Visual Studio Code
- Atom
- Sublime Text Editor
In the below section I have mentioned some of the essential features of using these IDEs and the pros and cons of using these IDEs.
6 Best Python IDEs for Data Science and their Features
Pycharm:
It is one of the best IDE which used for Data Science and computer programming purpose. It is the most popular IDE used for Data Science.
This IDE was initially released in the year of 2010 and it was written with the help of Python and Java programming language and developed by the JetBrains company. This IDE is supportive of several operating systems such as macOS, Windows, and Linux.
Features:
- It has an integrated inbuilt debugger, so you will be able to debug the codes very easily.
- The debugging process is very very awesome and easier within Python programming.
- Open-source IDE which you can download freely.
- This IDE supports most of the web frameworks such as for Web2Py, Django, Flasks, and others.
- It is integrated with unit testing.
- This IDE is also supportive of scientific tools.
Spyder:
Spyder is a kind of open-source IDE which are available for the Python programming language. It is mainly used for scientific programming purposes and data science.
It has the features to integrate with the other Python programming packages Numpy, Ipython, Cython, and others.
This software released in the year 2009 and it is written within the Python programming language. There are several features are embedded with this software.
Features:
- This IDE is very good for the syntax highlighting
- This IDE supports multiple IPython consoles
- This IDE can edit the variables from a graphical user interface
- Some console information is placed within this IDE so whenever you execute the code any error that’s coming up you will be able to see and change.
- You can create different environments with the help of this IDE.
Jupyter Notebook:
This is another good IDE that you can use for Data Science. The main uses of this IDE are that you can create open-source software and open standard services with the help of several programming languages.
It was initially founded in the year 2015 and it consists of multiple advanced features.
Nowadays most cloud environments integrate with the Jupyter notebook. And this IDE is mainly used for studying purposes.
Here I mention some of the essential features of the Jupyter Notebook-
- Very useful IDE for the cloud environment and its integrations
- This integrated development environment is very much interactive for doing work.
- The visualizations and graphs can be very properly displayed in this IDE.
Visual Studio Code:
It is a very popular source code editor or IDE. It was created by Microsoft. It is compatible with various operating systems such as Windows, Linux, Mac Os, and others.
It was written in several languages such as Html, CSS, Javascript, Typescript, and others.
This version was initially released in the year of 2015 and it was developed by Microsoft.
There are numerous advanced features are there of this IDE or editor.
- It is a very good debugger
- It supports very good syntax highlighting
- Very good tools are attached to this IDE
- This IDE has very good community support therefore if you get any problem then you can easily take the help of the community.
Atom:
It is a kind of open-source code editor and this IDE or editor is suitable for all operating systems. This IDE is very much suitable for macOS, IOS, Windows, and other operating systems.
This code editor was originally released in the year 2014 and it is written in several languages such as -Html, Javascript, etc.
There are some very good features are available within this IDE or text editor.
Key features:
- It is considered a hackable text editor
- This editor can be customized very smoothly
- Being an open-source editor, everyone can use this text editor
- Supportable for several OS (Operating System).
- There are numerous plugins available within this IDE which are useful
- Good existence of syntax highlighter.
Sublime Text Editor:
It is a cross-platform source code editor and it is a very good IDE for developers because there are lots of advanced features integrated with this editor.
This editor was originally written in C++ and Python programming language, and it was initially released in the year of 2008 its original developer is John Skinner.
Here I mention some of the essential features of this IDE-
- This IDE provides multi-select editing features.
- Syntax highlighting feature is always there.
- Autosave feature is given.
- It is fully customizable with key assignments.
- Spell-check functions are enabled.
Final Verdict:
In this article, I have mentioned some of the essential IDEs and editors for Python programming which you can use for Data Science. And you can use any one of these editors for your needs.
I hope you have liked this article and if you have any kind of query then you can ask me in the comment section.
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