Within Raphtory we have implemented many of the standard algorithms you may expect within a graph library, but have also added several temporal algorithms such as
Temporal Reachability and
Temporal Motifs. You can check out the full list of available algorithms here and edit the code snippets below in your own notebook to test them out.
Before we look at the different types of algorithms, let's first load in some data. For these examples we are going to use the One graph to rule them all dataset, which maps the co-occurrence of characters within the Lord of The Rings books. This dataset is a simple edge list, consisting of the source character, destination character and the sentence they occurred together in (which we shall use as a timestamp). The dataframe for this can be seen in the output below.
from raphtory import Graph import pandas as pd df = pd.read_csv("data/lotr.csv") print(df) lotr_graph = Graph.load_from_pandas(edges_df=df, src="src", dst="dst", time="time")
src dst time 0 Gandalf Elrond 33 1 Frodo Bilbo 114 2 Blanco Marcho 146 3 Frodo Bilbo 205 4 Thorin Gandalf 270 ... ... ... ... 2644 Merry Galadriel 32666 2645 Merry Sam 32666 2646 Galadriel Sam 32666 2647 Pippin Merry 32671 2648 Pippin Merry 32674 [2649 rows x 3 columns]