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Merge pull request #601 from bashtage/update-examples
DOC: Update examples and reduce warnings
2 parents 360054b + d58224a commit 9288df3

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-16
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‎examples/asset-pricing_examples.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/asset-pricing_formulas.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/iv_absorbing-regression.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/iv_advanced-examples.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"nbsphinx": {
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"allow_errors": true

‎examples/iv_basic-examples.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/iv_using-formulas.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/panel_data-formats.ipynb

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

‎examples/panel_examples.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/panel_using-formulas.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/system_examples.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/system_formulas.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

‎examples/system_three-stage-ls.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.10.12"
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},
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"pycharm": {
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"stem_cell": {

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