cmc/data-science

Personal data science learning files. data-science learning notebooks python

Commit 408fbe0a98

408fbe0a98ad8f5a667195b7d5beb947e25580fd

parent: ce4abbd687

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cmc <hello@cmc.pub> · 2025-03-11 23:26 UTC 

move from cleberg.net to cmc.pub

Layout: unified · split

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notebooks/Lincoln_Business_Clusters_Report.ipynb +4 −4
@@ -108,18 +108,18 @@
108 "6. Southeast (Purple)\n", 108 "6. Southeast (Purple)\n",
109 "\n", 109 "\n",
110 "#### Map of Clusters in Lincoln \n", 110 "#### Map of Clusters in Lincoln \n",
111 "![](https://img.cleberg.net/blog/014-ibm-data-science/04_clusters-min.png) \n", 111 "![](https://img.cmc.pub/blog/014-ibm-data-science/04_clusters-min.png) \n",
112 "\n", 112 "\n",
113 "These clusters closely follow the street layout shown on the map. The clusters with many businesses (0 - 3) are in the most populous areas of Lincoln, while clusters 4 - 5 are in the areas of the city with fewer streets.\n", 113 "These clusters closely follow the street layout shown on the map. The clusters with many businesses (0 - 3) are in the most populous areas of Lincoln, while clusters 4 - 5 are in the areas of the city with fewer streets.\n",
114 "\n", 114 "\n",
115 "#### Number of Venues by Cluster in Lincoln \n", 115 "#### Number of Venues by Cluster in Lincoln \n",
116 "![](https://img.cleberg.net/blog/014-ibm-data-science/05_venues_per_cluster-min.png) \n", 116 "![](https://img.cmc.pub/blog/014-ibm-data-science/05_venues_per_cluster-min.png) \n",
117 "\n", 117 "\n",
118 "Finally, we can show a deeper inspection of the venues in these clusters. For investors who may want to invest in Mexican restaurants, they would have to decide whether to invest in an area with many Mexican restaurants already (cluster #1) or a cluster with fewer restaurants. Likewise, we can see which areas are more popular for other business categories. \n", 118 "Finally, we can show a deeper inspection of the venues in these clusters. For investors who may want to invest in Mexican restaurants, they would have to decide whether to invest in an area with many Mexican restaurants already (cluster #1) or a cluster with fewer restaurants. Likewise, we can see which areas are more popular for other business categories. \n",
119 "\n", 119 "\n",
120 "#### Venue Categories by Clusters in Lincoln (>1) \n", 120 "#### Venue Categories by Clusters in Lincoln (>1) \n",
121 "![](https://img.cleberg.net/blog/014-ibm-data-science/06_categories_per_cluster_pt1-min.png) \n", 121 "![](https://img.cmc.pub/blog/014-ibm-data-science/06_categories_per_cluster_pt1-min.png) \n",
122 "![](https://img.cleberg.net/blog/014-ibm-data-science/07_categories_per_cluster_pt2-min.png) " 122 "![](https://img.cmc.pub/blog/014-ibm-data-science/07_categories_per_cluster_pt2-min.png) "
123 ] 123 ]
124 }, 124 },
125 { 125 {