From 5cbb65584f551f89b71ecf393e564ccc11621d0a Mon Sep 17 00:00:00 2001 From: Ralph Liu Date: Tue, 1 Oct 2024 09:07:06 -0700 Subject: [PATCH] Changes --- notebooks/demo/accelerating_networkx.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/demo/accelerating_networkx.ipynb b/notebooks/demo/accelerating_networkx.ipynb index 8277666c0f..db15e738c1 100644 --- a/notebooks/demo/accelerating_networkx.ipynb +++ b/notebooks/demo/accelerating_networkx.ipynb @@ -8,7 +8,7 @@ "source": [ "# NetworkX - Easy Graph Analytics\n", "\n", - "NetworkX is the most popular library for graph analytics available in Python, or quite possibly any language. To illustrate this, NetworkX was downloaded more than 50 million times in April of 2024 alone, which is roughly 50 times more than the next most popular graph analytics library! [*](https://en.wikipedia.org/wiki/NetworkX) NetworkX has earned this popularity from its very easy-to-use API, the wealth of documentation and examples available, the large (and friendly) community behind it, and its easy installation which requires nothing more than Python.\n", + "NetworkX is the most popular library for graph analytics available in Python, or quite possibly any language. To illustrate this, NetworkX was downloaded more than 71 million times in September of 2024 alone, which is roughly 71 times more than the next most popular graph analytics library! [*](https://en.wikipedia.org/wiki/NetworkX) NetworkX has earned this popularity from its very easy-to-use API, the wealth of documentation and examples available, the large (and friendly) community behind it, and its easy installation which requires nothing more than Python.\n", "\n", "However, NetworkX users are familiar with the tradeoff that comes with those benefits. The pure-Python implementation often results in poor performance when graph data starts to reach larger scales, limiting the usefulness of the library for many real-world problems.\n", "\n",