Learn how to simulate a social network.
- [Instructor] In this demonstration, I'm going to show you…how to simulate a social network in three easy steps.…Those are, one: to generate a graph object and edgelist,…two: assign attributes to graph nodes,…and three: visualize the network.…In the next demonstration, I'm going to show you…how to analyze a social network for insights.…Now I want to show you how to use a graph generator…to simulate a social network.…In the process, you'll learn to assign attributes…to graph nodes, generate important network statistics,…and visualize results.…
So in this demonstration, you'll need Numpy and Pandas.…We're also going to import networkx as nx,…and bring in our matplotlib and seaborn.…Let's set the plot parameters for this Jupyter notebook.…We'll run these.…So now our notebook is set up for graphing.…Let's use the gn graph function to generate…a directional graph with seven nodes.…We'll call it DG, and we'll say nx.gn_graph(7)…and set our seed to 25.…
Next we need to generate an edgelist.…We'll use the generate_edgelist function to do that.…
AuthorLillian Pierson, P.E.
- Getting started with Jupyter Notebooks
- Visualizing data: basic charts, time series, and statistical plots
- Preparing for analysis: treating missing values and data transformation
- Data analysis basics: arithmetic, summary statistics, and correlation analysis
- Outlier analysis: univariate, multivariate, and linear projection methods
- Introduction to machine learning
- Basic machine learning methods: linear and logistic regression, Naïve Bayes
- Reducing dataset dimensionality with PCA
- Clustering and classification: k-means, hierarchical, and k-NN
- Simulating a social network with NetworkX
- Creating Plot.ly charts
- Scraping the web with Beautiful Soup
Skill Level Beginner
1. Data Munging Basics
2. Data Visualization Basics
3. Basic Math and Statistics
4. Dimensionality Reduction
Explanatory factor analysis6m 39s
5. Outlier Analysis
6. Cluster Analysis
7. Network Analysis with NetworkX
8. Basic Algorithmic Learning
9. Web-based Data Visualizations with Plotly
10. Web Scraping with Beautiful Soup
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