Extracting, analysing, processing and visualising data to solve real-world problems is the daily life of a data scientist. Understanding the business need and convert it to a technical problem and solve it using the best tools of the previous ones is our job.
So to do that, you need to use the best tools in the market to be efficient, effective and pragmatic.
Here in this article, I will share what I am using after several years of experiences.
Here a list of almost all tools I used:
Pycharm
Pycharm is an Integrated Development Environment (IDE). This IDE, like any other IDE, will allow you coding, test and debug your code.
If you are looking for a new IDE for data project, I will advice you Pycharm, it’s one of the best on the market and it’s made by JetBrains.
PyCharm is an excellent choice for data science, but you may have to pay for the Professional Edition to access the data science tools but the community version (free version) is very powerful too and it’s more than enough for our daily needs.
Pycharm supports the following list:
- Supports Python, SQL, and more
- Code editor
- Error highlighting
