Best tools for data science job in 2021

In recent years, data science is one of the 10 most popular jobs in the hiring market and still a rising career in the following years. It requires knowledge from separate and individual fields including computer science, statistics and programming. Since data science processes are completed by different tools, you must remember a lot of tools with syntax and function. Additionally, when you spend time learning how to use it, it reduces your job performance.

This article represents how to use popular tools for handling data science tasks and how to integrate them for creating flexible environment work. Enjoy it and share your experience in the comment section.

Python

Python is a good solution for dealing with almost any data science process. It has many modules built from a large community to solve common data science tasks. Python provides a powerful tool to handle any challenge when working with data, however, it has some disadvantages such as using code instead of interface interaction.

How to using Python

1. You need to install Python environment on your computer before you can use them (Installer).
2. After that, you need an editor to begin programming with Python. You can use Visual Studio Code or Jupyter notebook
3. You should create a virtual environment to contain libraries such as numpy, pandas. I recommended using Anaconda to manage your packages in Python.

You are ready to explore knowledge from data. Let’s started.

Data collecting

In some projects, you need to collect data by yourself instead of being available. You can use some packages in the table below to crawl data from web pages. It is an incredible tool to help you extract pieces of data from the internet.

Module	Description
beautifulsoup	A Python library helps you extract data from HTML and XML content.
request	Send a HTTP request to the web for getting content automatically.
selenium	Interact with a web browser to emulate user activities such as mouse click and select text area.

You can read this article to understand how to crawl data using the above packages.

I will continue updating next time.