Understanding the Claremont Independent

• Read the article here.
• See the dataset of Collegiate Network publications here.
• Assess the methodolgy of linguistic and backlink visualizations here.

Continue reading this page to set up a coding environment where you can explore our data for yourself.

Getting Started

Step 1: Download Anaconda (MacOS)

# Ensure the path to the "conda" command is in your $PATH
cd
vi .bash_profile

# You should see the following somewhere in the file;
export PATH="/Users/{your-user-name}/anaconda3/bin:$PATH"

# To exit the file viewer, type:
:q

Step 2: Make Project Directory

# Create project folder on your desktop.
cd Dekstop
mkdir Claremont-Independent-Report
cd Claremont-Independent-Report

Step 3: Create Virtual Environment

# Create virtual environment in which to install packages.
conda create --name ci-report

# Install all packages needed for analysis:
# - Requests
# - Beautiful Soup
# - Jupyter Lab
conda install --name ci-report requests beautifulsoup4
conda install --name ci-report -c conda-forge jupyterlab

# Activate the environment. The comand line prompt should now start with (ci-report).
source activate ci-report

Referece: Setting Up a Conda Environtment

Step 4: Install Mozcape Package

# Clone mozscape package from github and install the contents.
git clone https://github.com/seomoz/SEOmozAPISamples.git
cd SEOmozAPISamples/python
pip install .

Reference: Mozscape API - Python Code Examples

Step 5: Launch Jupyter Lab

# Go back to root of project folder and launch jupyter.
cd ../..
jupyter lab

Reference: Jupyter Documenation

Step 6: Import Necessary Libaries

# Imports for python code to function properly
import pprint, os, csv, json, pickle, requests, html5lib
from bs4 import BeautifulSoup

# Import mozscape and give API credentials
from mozscape import Mozscape
client = Mozscape('my_access_id', 'my_secret_key')

# Print in format easier to read
pp = pprint.PrettyPrinter(indent=4)

Reference: Mozscape API - Python Code Examples