munich example for docs

chainladder/core/base.py

@@ -618,11 +618,11 @@ def complete_date_range(origin_date, development_date,
             ''' Determines origin/development combinations in full.  Useful for
                 when the triangle has holes in it. '''
             origin_unique = \
-                pd.PeriodIndex(start=origin_date.min(),
+                pd.period_range(start=origin_date.min(),
                                end=origin_date.max(),
                                freq=origin_grain).to_timestamp()
             development_unique = \
-                pd.PeriodIndex(start=origin_date.min(),
+                pd.period_range(start=origin_date.min(),
                                end=development_date.max(),
                                freq=development_grain).to_timestamp()
             development_unique = TriangleBase.period_end(development_unique)

docs/auto_examples/index.rst

@@ -126,6 +126,26 @@ Gallery of Chainladder Functionality
    :hidden:
 
    /auto_examples/plot_triangle_from_pandas
+
+.. raw:: html
+
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to adjust LDFs by the relationship between Paid and Incurred usin...">
+
+.. only:: html
+
+    .. figure:: /auto_examples/images/thumb/sphx_glr_plot_munich_thumb.png
+
+        :ref:`sphx_glr_auto_examples_plot_munich.py`
+
+.. raw:: html
+
+    </div>
+
+
+.. toctree::
+   :hidden:
+
+   /auto_examples/plot_munich
 .. raw:: html
 
     <div style='clear:both'></div>

docs/auto_examples/plot_munich.ipynb

@@ -0,0 +1,54 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Munich Adjustment Example\n\n\nThis example demonstrates how to adjust LDFs by the relationship between Paid\nand Incurred using the MunichAdjustment.\n.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import chainladder as cl\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nsns.set_style('whitegrid')\nsns.set_palette('muted')\n\n# Load data\nmcl = cl.load_dataset('mcl')\n# Volume weighted (default) LDFs\ndev = cl.Development().fit_transform(mcl)\n# Traditional Chainladder\ncl_traditional = cl.Chainladder().fit(dev)\n# Munich Adjustment\ndev_munich = cl.MunichAdjustment(paid_to_incurred={'paid':'incurred'}).fit_transform(dev)\ncl_munich = cl.Chainladder().fit(dev_munich)\n\n# Plot data\nfig, (ax, ax2) = plt.subplots(ncols=2, sharex=True, figsize=(10,5))\nplot1_data = cl_munich.ultimate_['paid'].to_frame()\nplot1_data.columns = ['Paid Ultimate']\nplot1_data['Incurred Ultimate'] = cl_munich.ultimate_['incurred'].to_frame()\nplot2_data = (cl_munich.ultimate_['paid']/cl_munich.ultimate_['incurred']).to_frame()\nplot2_data.columns = ['Munich']\nplot2_data['Traditional'] = (cl_traditional.ultimate_['paid']/cl_traditional.ultimate_['incurred']).to_frame()\nplot1_data.plot(kind='bar', ax=ax)\nax.set_ylabel('Ultimate')\nax.set_xlabel('Accident Year')\nax.set_title('Munich Chainladder')\nplot2_data.plot(kind='bar', ax=ax2, ylim=(0,1.25))\nax2.set_title('P/I Ratio Comparison')\nax2.set_xlabel('Accident Year')\ng = plt.ylabel('Paid Ultimate / Incurred Ultimate')"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.6.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

docs/auto_examples/plot_munich.py

@@ -0,0 +1,42 @@
+"""
+=========================
+Munich Adjustment Example
+=========================
+
+This example demonstrates how to adjust LDFs by the relationship between Paid
+and Incurred using the MunichAdjustment.
+.
+"""
+
+import chainladder as cl
+import seaborn as sns
+import matplotlib.pyplot as plt
+sns.set_style('whitegrid')
+sns.set_palette('muted')
+
+# Load data
+mcl = cl.load_dataset('mcl')
+# Volume weighted (default) LDFs
+dev = cl.Development().fit_transform(mcl)
+# Traditional Chainladder
+cl_traditional = cl.Chainladder().fit(dev)
+# Munich Adjustment
+dev_munich = cl.MunichAdjustment(paid_to_incurred={'paid':'incurred'}).fit_transform(dev)
+cl_munich = cl.Chainladder().fit(dev_munich)
+
+# Plot data
+fig, (ax, ax2) = plt.subplots(ncols=2, sharex=True, figsize=(10,5))
+plot1_data = cl_munich.ultimate_['paid'].to_frame()
+plot1_data.columns = ['Paid Ultimate']
+plot1_data['Incurred Ultimate'] = cl_munich.ultimate_['incurred'].to_frame()
+plot2_data = (cl_munich.ultimate_['paid']/cl_munich.ultimate_['incurred']).to_frame()
+plot2_data.columns = ['Munich']
+plot2_data['Traditional'] = (cl_traditional.ultimate_['paid']/cl_traditional.ultimate_['incurred']).to_frame()
+plot1_data.plot(kind='bar', ax=ax)
+ax.set_ylabel('Ultimate')
+ax.set_xlabel('Accident Year')
+ax.set_title('Munich Chainladder')
+plot2_data.plot(kind='bar', ax=ax2, ylim=(0,1.25))
+ax2.set_title('P/I Ratio Comparison')
+ax2.set_xlabel('Accident Year')
+g = plt.ylabel('Paid Ultimate / Incurred Ultimate')

docs/auto_examples/plot_munich.py.md5

@@ -0,0 +1 @@
+242c50127e7690e88516533290192901

docs/auto_examples/plot_munich.rst

@@ -0,0 +1,92 @@
+.. note::
+    :class: sphx-glr-download-link-note
+
+    Click :ref:`here <sphx_glr_download_auto_examples_plot_munich.py>` to download the full example code
+.. rst-class:: sphx-glr-example-title
+
+.. _sphx_glr_auto_examples_plot_munich.py:
+
+
+=========================
+Munich Adjustment Example
+=========================
+
+This example demonstrates how to adjust LDFs by the relationship between Paid
+and Incurred using the MunichAdjustment.
+.
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_munich_001.png
+    :class: sphx-glr-single-img
+
+
+
+
+
+.. code-block:: python
+
+
+    import chainladder as cl
+    import seaborn as sns
+    import matplotlib.pyplot as plt
+    sns.set_style('whitegrid')
+    sns.set_palette('muted')
+
+    # Load data
+    mcl = cl.load_dataset('mcl')
+    # Volume weighted (default) LDFs
+    dev = cl.Development().fit_transform(mcl)
+    # Traditional Chainladder
+    cl_traditional = cl.Chainladder().fit(dev)
+    # Munich Adjustment
+    dev_munich = cl.MunichAdjustment(paid_to_incurred={'paid':'incurred'}).fit_transform(dev)
+    cl_munich = cl.Chainladder().fit(dev_munich)
+
+    # Plot data
+    fig, (ax, ax2) = plt.subplots(ncols=2, sharex=True, figsize=(10,5))
+    plot1_data = cl_munich.ultimate_['paid'].to_frame()
+    plot1_data.columns = ['Paid Ultimate']
+    plot1_data['Incurred Ultimate'] = cl_munich.ultimate_['incurred'].to_frame()
+    plot2_data = (cl_munich.ultimate_['paid']/cl_munich.ultimate_['incurred']).to_frame()
+    plot2_data.columns = ['Munich']
+    plot2_data['Traditional'] = (cl_traditional.ultimate_['paid']/cl_traditional.ultimate_['incurred']).to_frame()
+    plot1_data.plot(kind='bar', ax=ax)
+    ax.set_ylabel('Ultimate')
+    ax.set_xlabel('Accident Year')
+    ax.set_title('Munich Chainladder')
+    plot2_data.plot(kind='bar', ax=ax2, ylim=(0,1.25))
+    ax2.set_title('P/I Ratio Comparison')
+    ax2.set_xlabel('Accident Year')
+    g = plt.ylabel('Paid Ultimate / Incurred Ultimate')
+
+**Total running time of the script:** ( 0 minutes  0.433 seconds)
+
+
+.. _sphx_glr_download_auto_examples_plot_munich.py:
+
+
+.. only :: html
+
+ .. container:: sphx-glr-footer
+    :class: sphx-glr-footer-example
+
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Python source code: plot_munich.py <plot_munich.py>`
+
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Jupyter notebook: plot_munich.ipynb <plot_munich.ipynb>`
+
+
+.. only:: html
+
+ .. rst-class:: sphx-glr-signature
+
+    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_

docs/modules/generated/chainladder.Chainladder.examples

@@ -56,3 +56,21 @@ Examples using ``chainladder.Chainladder``
 .. only:: not html
 
     * :ref:`sphx_glr_auto_examples_plot_bf_apriori_from_cl.py`
+
+.. raw:: html
+
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to adjust LDFs by the relationship between Paid and Incurred usin...">
+
+.. only:: html
+
+    .. figure:: /auto_examples/images/thumb/sphx_glr_plot_munich_thumb.png
+
+        :ref:`sphx_glr_auto_examples_plot_munich.py`
+
+.. raw:: html
+
+    </div>
+
+.. only:: not html
+
+    * :ref:`sphx_glr_auto_examples_plot_munich.py`

docs/modules/generated/chainladder.Development.examples

@@ -38,3 +38,21 @@ Examples using ``chainladder.Development``
 .. only:: not html
 
     * :ref:`sphx_glr_auto_examples_plot_mack.py`
+
+.. raw:: html
+
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to adjust LDFs by the relationship between Paid and Incurred usin...">
+
+.. only:: html
+
+    .. figure:: /auto_examples/images/thumb/sphx_glr_plot_munich_thumb.png
+
+        :ref:`sphx_glr_auto_examples_plot_munich.py`
+
+.. raw:: html
+
+    </div>
+
+.. only:: not html
+
+    * :ref:`sphx_glr_auto_examples_plot_munich.py`

docs/modules/generated/chainladder.MunichAdjustment.examples

@@ -0,0 +1,22 @@
+
+
+Examples using ``chainladder.MunichAdjustment``
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. raw:: html
+
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to adjust LDFs by the relationship between Paid and Incurred usin...">
+
+.. only:: html
+
+    .. figure:: /auto_examples/images/thumb/sphx_glr_plot_munich_thumb.png
+
+        :ref:`sphx_glr_auto_examples_plot_munich.py`
+
+.. raw:: html
+
+    </div>
+
+.. only:: not html
+
+    * :ref:`sphx_glr_auto_examples_plot_munich.py`

docs/modules/generated/chainladder.load_dataset.examples

@@ -92,3 +92,21 @@ Examples using ``chainladder.load_dataset``
 .. only:: not html
 
     * :ref:`sphx_glr_auto_examples_plot_bf_apriori_from_cl.py`
+
+.. raw:: html
+
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to adjust LDFs by the relationship between Paid and Incurred usin...">
+
+.. only:: html
+
+    .. figure:: /auto_examples/images/thumb/sphx_glr_plot_munich_thumb.png
+
+        :ref:`sphx_glr_auto_examples_plot_munich.py`
+
+.. raw:: html
+
+    </div>
+
+.. only:: not html
+
+    * :ref:`sphx_glr_auto_examples_plot_munich.py`

docs/themes/scikit-learn/layout.html

@@ -138,8 +138,8 @@
 		      <img src="_images/sphx_glr_plot_triangle_slicing_thumb.png"></a>
 		  </div>
 		  <div class="item">
-		    <a href="{{ pathto('auto_examples/cluster/plot_cluster_comparison') }}">
-		      <img src="_images/sphx_glr_plot_cluster_comparison_thumb.png"></a>
+		    <a href="{{ pathto('auto_examples/cluster/plot_munich') }}">
+		      <img src="_images/sphx_glr_plot_munich_thumb.png"></a>
 		  </div>
 		  <div class="item">
 		    <a href="{{ pathto('auto_examples/ensemble/plot_adaboost_twoclass') }}">

examples/plot_munich.py

@@ -0,0 +1,42 @@
+"""
+=========================
+Munich Adjustment Example
+=========================
+
+This example demonstrates how to adjust LDFs by the relationship between Paid
+and Incurred using the MunichAdjustment.
+.
+"""
+
+import chainladder as cl
+import seaborn as sns
+import matplotlib.pyplot as plt
+sns.set_style('whitegrid')
+sns.set_palette('muted')
+
+# Load data
+mcl = cl.load_dataset('mcl')
+# Volume weighted (default) LDFs
+dev = cl.Development().fit_transform(mcl)
+# Traditional Chainladder
+cl_traditional = cl.Chainladder().fit(dev)
+# Munich Adjustment
+dev_munich = cl.MunichAdjustment(paid_to_incurred={'paid':'incurred'}).fit_transform(dev)
+cl_munich = cl.Chainladder().fit(dev_munich)
+
+# Plot data
+fig, (ax, ax2) = plt.subplots(ncols=2, sharex=True, figsize=(10,5))
+plot1_data = cl_munich.ultimate_['paid'].to_frame()
+plot1_data.columns = ['Paid Ultimate']
+plot1_data['Incurred Ultimate'] = cl_munich.ultimate_['incurred'].to_frame()
+plot2_data = (cl_munich.ultimate_['paid']/cl_munich.ultimate_['incurred']).to_frame()
+plot2_data.columns = ['Munich']
+plot2_data['Traditional'] = (cl_traditional.ultimate_['paid']/cl_traditional.ultimate_['incurred']).to_frame()
+plot1_data.plot(kind='bar', ax=ax)
+ax.set_ylabel('Ultimate')
+ax.set_xlabel('Accident Year')
+ax.set_title('Munich Chainladder')
+plot2_data.plot(kind='bar', ax=ax2, ylim=(0,1.25))
+ax2.set_title('P/I Ratio Comparison')
+ax2.set_xlabel('Accident Year')
+g = plt.ylabel('Paid Ultimate / Incurred Ultimate')