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INTRODUCTION TO PYTHON FOR HUMANISTS

PREFACE

Preface

PART ONE: The Basics of Python

1. Introduction to Python
2. Data and Data Structures
- 2.1. Introduction to Data
- 2.2. Introduction to Data Structures
3. Loops and Logic
- 3.1. Introduction to Loops
- 3.2. Conditionals
4. Formal Coding: Functions, Classes, and Libraries
5. Working with External Data
6. Working with Data on the Web
- 6.1. Introduction to HTML
- 6.2. Scraping Web Pages with Requests and BeautifulSoup

PART TWO: Data Analysis with Pandas (Work in Progress)

1. Introduction to Pandas
- 1.1. Introduction to Pandas
- 1.2. The Basics of Pandas
2. Working with Data in Pandas
3. Searching for Data
4. Advanced Pandas

PART THREE: Natural Language Processing with spaCy

1. Introduction to spaCy
2. Rules-Based spaCy
3. Solving a Domain-Specific Problem: A Case Study with Holocaust NER

PART FOUR: OTHER APPLICATIONS OF PYTHON

1. Topic Modeling in Python
2. Text Analysis with BookNLP
3. Social Network Analysis

PART FIVE: DESIGNING AN APPLICATION WITH STREAMLIT

1. Introduction to Streamlit
2. Advanced Streamlit Features
3. Building a Database Query Application
- 3.1. Building a Database Query Application
- 3.2. Deploying an App in the Cloud with Streamlit Share

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Social Network Analysis

3. Social Network Analysis#

In this chapter, we will shift away from NLP and examine Social network analysis (SNA). SNA is the process by which researchers study the networks of social relationships. These can be familial (parents to children), social (friends), etc. The goal of SNA is to reveal insights about a network or group of individuals by studying them collectively and often through visualization methods.

By William J.B. Mattingly