Initial column selection for Issue #2

GFDRR · Mar 5, 2022 · 475f006 · 475f006
1 parent 5af86a9
commit 475f006
Showing 1 changed file with 8 additions and 2 deletions.
diff --git 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"