Merge pull request #601 from bashtage/update-examples

DOC: Update examples and reduce warnings

Author: bashtage

examples/asset-pricing_examples.ipynb

@@ -412,7 +412,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/asset-pricing_formulas.ipynb

@@ -139,7 +139,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/iv_absorbing-regression.ipynb

@@ -151,7 +151,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/iv_advanced-examples.ipynb

@@ -572,7 +572,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "nbsphinx": {
    "allow_errors": true

examples/iv_basic-examples.ipynb

@@ -802,7 +802,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/iv_using-formulas.ipynb

@@ -192,7 +192,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/panel_data-formats.ipynb

@@ -47,7 +47,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "mi_data = data.set_index([\"fcode\", \"year\"])\n",
+    "orig_mi_data = data.set_index([\"fcode\", \"year\"])\n",
+    "# Subset to the relevant columns and drop missing to avoid warnings\n",
+    "mi_data = orig_mi_data[[\"lscrap\",\"hrsemp\"]]\n",
+    "mi_data = mi_data.dropna(axis=0, how=\"any\")\n",
+    "\n",
     "print(mi_data.head())"
    ]
   },
@@ -88,9 +92,9 @@
    "source": [
     "import numpy as np\n",
     "\n",
-    "np_data = np.asarray(mi_data)\n",
-    "np_lscrap = np_data[:, mi_data.columns.get_loc(\"lscrap\")]\n",
-    "np_hrsemp = np_data[:, mi_data.columns.get_loc(\"hrsemp\")]\n",
+    "np_data = np.asarray(orig_mi_data)\n",
+    "np_lscrap = np_data[:, orig_mi_data.columns.get_loc(\"lscrap\")]\n",
+    "np_hrsemp = np_data[:, orig_mi_data.columns.get_loc(\"hrsemp\")]\n",
     "nentity = mi_data.index.levels[0].shape[0]\n",
     "ntime = mi_data.index.levels[1].shape[0]\n",
     "np_lscrap = np_lscrap.reshape((nentity, ntime)).T\n",
@@ -104,6 +108,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Warnings are inevitable when using NumPy with missing data\n",
+    "# since the arrays must be rectangular, and not ragged\n",
     "res = PanelOLS(np_lscrap, np_hrsemp, entity_effects=True).fit()\n",
     "print(res)"
    ]
@@ -224,7 +230,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/panel_examples.ipynb

@@ -427,7 +427,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/panel_using-formulas.ipynb

@@ -182,7 +182,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {

examples/system_examples.ipynb

@@ -780,7 +780,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {