How to install python for data science with conda

How to install python for data science with conda

Downloading

You can choose right version for your system from https://docs.conda.io/en/latest/miniconda.html.

Windows users should follow the tutorial from https://docs.conda.io/projects/conda/en/latest/user-guide/install/windows.html.

Linux users can run the following script:

In terminal execute the following line:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\
    -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda

Mac users can also run the same script changing
Miniconda3-latest-Linux-x86_64.sh into Miniconda3-latest-MacOSX-x86_64.sh.

Adding conda to PATH (Mac and Linux)

Then add conda to $PATH by running

export PATH="$HOME/miniconda/bin:$PATH"

If you do not want to run it each time you start the system you can add this line to ~/.bashrc (or .zshrc). For example by calling

nano ~/.bashrc

(Mac .zshrc) and adding these lines at the end of the file. Then run

source ~/.bashrc

Update conda (all platforms)

conda init
conda update conda

Creating and activating environment

conda create -n conda3.7 python=3.7
source activate conda3.7

You can deactivate it with source deactive. More info on https://conda.io/docs/user-guide/tasks/manage-environments.html

Installing python (with numpy, jupyter and matplotlib)

conda install numpy jupyter
conda install -c conda-forge matplotlib 

Install other useful packages

conda install pandas scikit-learn plotly
conda install -c conda-forge seaborn

Run jupyter and test it

After activating environment run

jupyter notebook

When the web page opens, click on button “New”, choose “Python 3”.

Then copy the following into the cell and press Control+Enter.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from sklearn import datasets, linear_model
%matplotlib inline

diabetes = datasets.load_diabetes()

X = diabetes.data[:, [2]]
y = diabetes.target

from sklearn.linear_model import LinearRegression
reg = LinearRegression()
reg.fit(X, y)

Updated: 2020-06-14