Setting up your environment


Setting up environment can sometime be a difficult process, and choosing between different can be confusing. So in this article we will cover how to setup your own data science on your machine, this article is not operating system dependent, procedures followed in this article can be used for any operating system.

Instead of comparing all the different environment for data science purposes, we will cover complete setting up of anaconda environment which is by far most used environment among data scientist, by saying that it does not means other environment is not powerful.

It is recommended that you download only 64bit version.

Installing python

There are two popular major versions of python 2. and python 3, for data science purpose we mostly use python 3. It is recommended that you install 3.6 with any patch number for now.

Downloading python 3.6 for windows :

Downloading python 3.6 for linux :,  though linux users have many choices over type of installation, like rpm tar etc. Choose according to your own operating system.

Downloading python 3.6 for mac:

while installing you must check add to path file,

Downloading anaconda:

Downloading anaconda and installing it is quite easy process after downloading it from here , just double click on the setup and you are done.

after installation chances are it will become the default python interpreter in case of mac and linux , so it is recommended that you install it in separate directory.

After installing launch anaconda navigator, by clicking anaconda navigator from start menu,

after anaconda launches you will see a dashboard,

, There are couple of ways launching these applications but the simplest way is by running them from anaconda navigator.

Most of the time as a beginner you will spend time on jupyter notebook. Jupyter is a ipython notebook i.e a editor with html features in it. go ahead and launch jupyter notebook.

jupyter notebook will be launch in a browser window, the default workspace of jupyter notebook is itself users account. Working with jupyter notebook is extremely easy just try different options present.

There is another important application present Spyder, it is more of  a matlab like tool for python with simple design.

Anaconda comes with almost all basic necessary  data science library pre-installed but  if you wish to install some additional libraries then click on anaconda prompt from start menu.

it will open a command prompt window with anaconda default environment or which ever environment you have choose. Using anaconda prompt you can install any library you require using conda package manager.

For current installed libraries, just type conda list

After following all above procedure you must be able to start working on data science problems using anaconda. There might be instances where you will face difficulty installing it, like .net framework error or c++ libraries not present or some root permissions not present etc. In those situations don’t get frustrated just leave the comment below or google it, at the end tackling error is what programmers do their entire life.

About the author


I write blogs about Machine Learning and data science

By abhinavsinghml

Most common tags

%d bloggers like this: