├── .gitignore ├── .idea ├── .name ├── Big-Data-Workbooks.iml ├── encodings.xml ├── misc.xml ├── modules.xml ├── vcs.xml └── workspace.xml ├── 02. Database Basics ├── Data_and_databases-sqlalchemy.ipynb ├── Data_and_databases.ipynb ├── README.md └── requirements.txt ├── 03. Visualization ├── README.md ├── Visualization_for_Big_Data-Data_Prep.ipynb └── Visualization_for_Big_Data-Using_Tableau.ipynb ├── 04. Social Media and APIs ├── .idea │ ├── .name │ ├── 04. Social Media and APIs.iml │ ├── misc.xml │ ├── modules.xml │ ├── vcs.xml │ └── workspace.xml ├── Book Examples │ ├── 1. Programming against an API - Crossref.ipynb │ ├── 2. Using the ORCID API via a wrapper.ipynb │ └── 3. Working in practice.ipynb ├── Exercise 1 - Interacting with online services.ipynb ├── Exercise 2 - Working with DOI lists and Article Level Metrics.ipynb ├── README.md └── modules │ ├── orcid-python │ ├── .gitignore │ ├── LICENSE-MIT.txt │ ├── MANIFEST.in │ ├── README.rst │ ├── orcid │ │ ├── __init__.py │ │ ├── constants.py │ │ ├── exceptions.py │ │ ├── rest.py │ │ └── utils.py │ ├── requirements.txt │ └── setup.py │ └── pyalm │ ├── LICENSE │ ├── README.md │ ├── _coveragerc │ ├── _gitignore │ ├── _travis.yml │ ├── dexy.conf.txt │ ├── dexy.yaml │ ├── dexyplugin.yaml │ ├── docs │ ├── examples │ │ └── example.py │ └── index.md │ ├── pyalm.egg-info │ ├── PKG-INFO │ ├── SOURCES.txt │ ├── dependency_links.txt │ ├── not-zip-safe │ ├── requires.txt │ └── top_level.txt │ ├── pyalm │ ├── __init__.py │ ├── api_key.example.py │ ├── api_key.py │ ├── cleanup.py │ ├── config.py │ ├── events.py │ ├── pyalm.py │ ├── utilities │ │ ├── __init__.py │ │ └── plossearch.py │ └── utils.py │ ├── requirements.txt │ ├── setup.py │ └── test │ ├── __init__.py │ ├── test_data_history.json │ ├── test_events.py │ ├── test_plossearch.py │ └── test_pyalm.py ├── 05. Text Analysis ├── README.md ├── Topic Modeling.docx ├── Topic Modeling.ipynb └── requirements.txt ├── 06. Networks ├── .gitignore ├── .idea │ ├── .name │ ├── Big-Data-Workbooks.iml │ ├── encodings.xml │ ├── misc.xml │ ├── modules.xml │ ├── vcs.xml │ └── workspace.xml ├── Installing_neo4j.docx ├── README.md ├── data │ ├── award_data.csv │ ├── employee_data.csv │ └── student_data.csv ├── networks_exercise.ipynb ├── networks_with_neo4j.ipynb ├── previous_classes │ ├── graph.ipynb │ ├── graph_class_exercise.ipynb │ └── graph_class_exercise_solution.ipynb └── requirements.txt ├── 07. Machine Learning ├── Machine Learning.ipynb ├── README.md └── requirements.txt ├── 08. Data Linkage ├── Datasets │ ├── nsf_awards_2010-2012.csv │ └── ucpay2011.csv └── Record Linkage.ipynb ├── 10. Samples and Statistical Inference └── README.md ├── Anaconda_Installation_Guide.docx ├── Data_Dictionary-Homework_Tables.docx ├── Database_Installation_Guide.docx ├── README.md ├── Style Guide.ipynb ├── XX. 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