second round

Author: spjuhel

doc/tutorial/climada_engine_unsequa.ipynb

@@ -177,7 +177,7 @@
     "# Here x_exp is the input uncertainty parameter and exp_func the inputvar.func.\n",
     "def exp_func(x_exp, exp_base=exp_base):\n",
     "    exp = exp_base.copy()\n",
-    "    exp.gdf.value *= x_exp\n",
+    "    exp.gdf["value"] *= x_exp\n",
     "    return exp"
    ]
   },
@@ -989,7 +989,7 @@
     "exp_base.assign_centroids(haz)\n",
     "def exp_base_func(x_exp, exp_base):\n",
     "    exp = exp_base.copy()\n",
-    "    exp.gdf.value *= x_exp\n",
+    "    exp.gdf["value"] *= x_exp\n",
     "    return exp\n",
     "from functools import partial\n",
     "exp_func = partial(exp_base_func, exp_base=exp_base)"
@@ -2462,7 +2462,7 @@
     "exp_base.assign_centroids(haz)\n",
     "def exp_base_func(x_exp, exp_base):\n",
     "    exp = exp_base.copy()\n",
-    "    exp.gdf.value *= x_exp\n",
+    "    exp.gdf["value"] *= x_exp\n",
     "    return exp\n",
     "from functools import partial\n",
     "exp_func = partial(exp_base_func, exp_base=exp_base)"
@@ -2797,7 +2797,7 @@
     "    from climada.util.constants import ENT_DEMO_TODAY\n",
     "    entity = Entity.from_excel(ENT_DEMO_TODAY)\n",
     "    entity.exposures.ref_year = 2018\n",
-    "    entity.exposures.gdf.value *= x_ent\n",
+    "    entity.exposures.gdf["value"] *= x_ent\n",
     "    return entity\n",
     "\n",
     "# Entity in the future has a +- 10% uncertainty in the cost of all the adapatation measures\n",
@@ -5267,7 +5267,7 @@
     "\n",
     "def exp_func(cnt, x_exp, exp_list=exp_list):\n",
     "    exp = exp_list[int(cnt)].copy()\n",
-    "    exp.gdf.value *= x_exp\n",
+    "    exp.gdf["value"] *= x_exp\n",
     "    return exp\n",
     "\n",
     "exp_distr = {\"x_exp\": sp.stats.uniform(0.9, 0.2),\n",
@@ -5527,7 +5527,7 @@
     "        exp_base.gdf["filename"] = str(filename)\n",
     "\n",
     "    exp = exp_base.copy()\n",
-    "    exp.gdf.value *= x_exp\n",
+    "    exp.gdf["value"] *= x_exp\n",
     "    return exp\n",
     "\n",
     "exp_distr = {\"x_exp\": sp.stats.uniform(0.9, 0.2),\n",