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You may also take a look at the source code.
The networks in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["baseball/player-player"]
(and likewise for the other networks available.)

baseball — Baseball steroid use (2008)


Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.1

  1. Description obtained from the ICON project. 

Social Offline Weighted Projection
Upstream URL OK
Tip: click on the table header to sort the list. Hover your mouse over it to obtain a legend.
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
player-player 72 1,089 30.25 18.59 44.00 2.56 0.99 1.00 2 0.62 Undirected Unipartite name 2 KiB 5 KiB 5 KiB 4 KiB
user-provider 84 84 2.00 4.78 1.73 6.60 -0.45 0.00 4 0.56 Undirected Bipartite name 2 KiB 3 KiB 3 KiB 2 KiB
player-player drawing
user-provider drawing