Setting up a minimal data-science environment in Windows using WSL (part II)

code

linux

setup

Set up a conda environment for data-science

Now that we have conda installed, let us set up a conda environment called ds (for data-science). Open WSL, then run

conda create -n ds

Activate the environment:

conda activate ds

When you now run python3, it will launch the version of the python interpreter that came with anaconda (in the previous step), not the version that comes pre-installed with WSL.

You can now install the following basic data-science packages:

conda install numpy scipy matplotlib seaborn scikit-learn pandas Jupyter

Installing packages through conda forge

Conda official repository only feature a few verified packages. A vast portion of python packages that are otherwise available through pip are installed through community led channel called conda-forge. You can visit their site to learn more about it. To do this, install your other packages package1 and package2 (say), by specifying the conda-forge channel :

conda install -c conda-forge package1 package2

Test your installation:

We now test the installation by using the following workflow:

Create a python script using the Windows text editor of your choice, save it in your ~/Downloads folder.
Execute the script from Bash.

Create a new file called test.py in ~/Downloads with the following content:

import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from scipy import stats

# Generate some random data
np.random.seed(42)
x = np.random.normal(size=100)
y = np.random.normal(size=100)

# Create a DataFrame from the data
df = pd.DataFrame({'x': x, 'y': y})

# Plot a scatter plot using Seaborn
sns.scatterplot(data=df, x='x', y='y')

# Add a regression line using SciPy
slope, intercept, r_value, p_value, std_err = stats.linregress(x, y)
plt.plot(x, slope * x + intercept, color='red')

# Set the x and y labels using Matplotlib
plt.xlabel('X')
plt.ylabel('Y')

# Show the plot
plt.show()

and run it with

python3 ~/Downloads/test.py