From 475f00673bb1f48c4c256030588b8dd3e2a1527d Mon Sep 17 00:00:00 2001 From: ConnectedSystems Date: Sat, 5 Mar 2022 15:51:25 +1100 Subject: [PATCH] Initial column selection for Issue #2 --- Top-down/notebooks/Flood.ipynb | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/Top-down/notebooks/Flood.ipynb b/Top-down/notebooks/Flood.ipynb index ee96798..8fac2a3 100644 --- a/Top-down/notebooks/Flood.ipynb +++ b/Top-down/notebooks/Flood.ipynb @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "edbaddbc-650e-4e4e-9033-770c64281177", "metadata": {}, "outputs": [], @@ -238,7 +238,7 @@ " EAI_cols = [f\"RP{rp_i}_EAI\" for rp_i in valid_RPs]\n", " result_df.loc[:, exp_sum_cols + EAI_cols] = 0\n", " \n", - " # Get, and store, total exposure for each ADM region\n", + " # Get total exposure for each ADM region\n", " exp_per_ADM = gen_zonal_stats(vectors=adm_data[\"geometry\"], raster=exp_raster_fn, stats=[\"sum\"])\n", " result_df[f\"{adm_name}_{exp_cat}\"] = [x['sum'] for x in exp_per_ADM]\n", "\n", @@ -365,6 +365,12 @@ " with output:\n", " if analysis_type == \"Function\":\n", " display(result_df.explore(column=f'{exp_cat}_EAI', cmap='plasma'))\n", + "\n", + " exp_total = result_df.columns.str.contains(f'_{exp_cat}_tot')\n", + " exp_imp = result_df.columns.str.contains(f'_{exp_cat}_imp')\n", + " exp_EAI = result_df.columns.str.contains(f'_{exp_cat}_EAI')\n", + " \n", + " result_df.loc[:, ]\n", " elif analysis_type == \"Classes\":\n", " # TODO: C1 Column selected for example display only!\n", " display(result_df.explore(column=f'RP10_{exp_cat}_C1', cmap='plasma'))\n"