Merge pull request #637 from OpenSourcePolicyCenter/634_btax_dataframes

Handle data from new BTAX Version

conda-requirements.txt

@@ -1,6 +1,6 @@
 nomkl
 taxcalc==0.10.2
-btax==0.1.8
+btax==0.1.9
 numba==0.33.0
 pandas
 gevent

deploy/fab/dropq_environment.yml

@@ -4,7 +4,7 @@ dependencies:
 - pandas>=0.20.1
 - flask
 - greenlet
-- bokeh
+- bokeh>=0.12.7
 - xlrd
 - redis
 - pip:

deploy/taxbrain_server/celery_tasks.py

@@ -178,8 +178,16 @@ def ogusa_async(user_mods, ogusa_params, guid):
 def btax_async(user_mods):
     print("user mods: ", user_mods)
     results = {}
-    results.update(runner_json_tables(**user_mods))
-    #Add taxcalc version to results
+    tables = runner_json_tables(**user_mods)
+    if tables.get("json_table"):
+        results.update(tables["json_table"])
+        if tables.get("dataframes"):
+            dataframes = json.loads(tables["dataframes"])
+            for x, y in dataframes.items():
+                dataframes[x] = json.loads(y)
+            results["dataframes"] = dataframes
+    else:
+        results.update(tables)
     vinfo = taxcalc._version.get_versions()
     results['taxcalc_version'] = vinfo['version'] + '.' + vinfo['full'][:6]
     results['dropq_version'] = vinfo['version'] + '.' + vinfo['full'][:6]

templates/btax/not_ready.html

@@ -33,24 +33,28 @@ <h4>About <span id="eta"></span> remaining</h4>
         $('#eta').text(moment.duration(eta, 'minutes').humanize());
     }
 
+    var interval;
     function ajaxEta() {
         $.ajax(window.location.href, {
             type: 'post',
             data: { csrfmiddlewaretoken: $('meta[name="csrf-token"]').attr('content') },
             success: function(data, textStatus, xhr) {
                 if (xhr.status === 202) {
                     insertEta(data.eta);
+                    clearInterval(interval);
+                    interval = setInterval(ajaxEta, data.wait_interval);
                 } else if (xhr.status === 200) {
+                    clearInterval(interval);
                     insertEta(data.eta);
                     setTimeout(function() {
                         window.location.reload(1);
                     }, 5000)
                 }
-            }
+            },
         });
     }
     ajaxEta();
-    setInterval(ajaxEta, 7000);
+    interval = setInterval(ajaxEta, 7000);
 });
 </script>
 {% endblock %}

templates/btax/results.html

@@ -7,6 +7,12 @@
 <link href="{% static 'js/vendor/DataTables/datatables.min.css' %}" rel="stylesheet"></link>
 <link href="{% static 'css/vendor/bootstrap/bootstrap.min.css' %}" rel="stylesheet"></link>
 <link href="https://cdn.datatables.net/1.10.12/css/jquery.dataTables.min.css" rel="stylesheet">
+<link rel='stylesheet' href={{cdn_css|safe}} type="text/css"/>
+<script type="text/javascript" src={{cdn_js|safe}}></script>
+<link
+  href="https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css"
+  rel="stylesheet" type="text/css">
+<script src="https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.js"></script>
 
 <style>
   .btn {
@@ -49,6 +55,10 @@
   #results-container {
   }
 
+  .bk-root .bk-grid-column {
+    margin: 0 auto;
+  }
+
   .controls-row {
     margin-left:100px;
     margin-right:100px;
@@ -84,6 +94,12 @@ <h1>{% flatblock "ccc_results_header" %}</h1>
      <a href="/ccc/edit/{{ unique_url.pk }}/" class="text-white btn btn-secondary">Edit Parameters</a>
   </div>
   <br>
+
+  <div class="center-block">
+    {{ bubble_div|safe }}
+    {{ bubble_js|safe }}
+  </div>
+
   <div id="results-container" class="container">
 	  <div class="row controls-row">
           <div id="view_by_inputs" class="col-sm-12">
@@ -147,6 +163,7 @@ <h2>Output Format:</h2>
                 </label>
           </div>
 	  </div>
+
 	  <div class="row">
 		  <div id="results-table-area" class="col-sm-12">
           </div>

webapp/apps/btax/bubble_plot/bubble_plot_tabs.py

@@ -0,0 +1,241 @@
+import pandas as pd
+from os import path
+import json
+pd.options.mode.chained_assignment = None
+
+# importing Bokeh libraries
+from bokeh.plotting import figure
+from bokeh.models import ColumnDataSource, Title, CustomJS
+from bokeh.models.widgets import Select, Panel, Tabs, RadioButtonGroup
+from bokeh.models import HoverTool, WheelZoomTool, ResetTool, SaveTool
+from bokeh.models import NumeralTickFormatter
+from bokeh.layouts import gridplot
+from bokeh.embed import components
+from bokeh.resources import CDN
+
+# import styles and callback
+from styles import (PLOT_FORMATS, TITLE_FORMATS, RED, BLUE)
+from controls_callback_script import CONTROLS_CALLBACK_SCRIPT
+
+
+def bubble_plot_tabs(dataframes):
+    dataframes = dataframes.copy()
+
+    # convert asset dicts to pandas dataframes
+    base_df = pd.DataFrame.from_dict(dataframes['base_output_by_asset'])
+    reform_df = pd.DataFrame.from_dict(dataframes['reform_output_by_asset'])
+    change_df = pd.DataFrame.from_dict(dataframes['changed_output_by_asset'])
+
+    list_df = [base_df, change_df, reform_df]
+    list_string = ['base', 'change', 'reform']
+
+    data_sources = {}
+    for i, df in enumerate(list_df):
+        # remove data from Intellectual Property, Land, and Inventories Categories
+        df = df[~df['asset_category'].isin(['Intellectual Property','Land','Inventories'])].copy()
+        df = df.dropna()
+
+        # define the size DataFrame, if change, use base sizes
+        if list_string[i] == 'base':
+            SIZES = list(range(20, 80, 15))
+            size = pd.qcut(df['assets_c'].values, len(SIZES), labels=SIZES)
+            size_c = pd.qcut(df['assets_c'].values, len(SIZES), labels=SIZES)
+            size_nc = pd.qcut(df['assets_nc'].values, len(SIZES), labels=SIZES)
+            df['size'] = size
+            df['size_c'] = size_c
+            df['size_nc'] = size_nc
+        else:
+            df['size'] = size
+            df['size_c'] = size_c
+            df['size_nc'] = size_nc
+
+        # form the two Categories: Equipment and Structures
+        equipment_df = df[(~df.asset_category.str.contains('Structures')) & (~df.asset_category.str.contains('Buildings'))]
+        structure_df = df[(df.asset_category.str.contains('Structures')) | (df.asset_category.str.contains('Buildings'))]
+
+        format_fields = ['metr_c', 'metr_nc', 'metr_c_d', 'metr_nc_d',
+                         'metr_c_e', 'metr_nc_e', 'mettr_c', 'mettr_nc',
+                         'mettr_c_d', 'mettr_nc_d', 'mettr_c_e', 'mettr_nc_e',
+                         'rho_c', 'rho_nc', 'rho_c_d', 'rho_nc_d', 'rho_c_e',
+                         'rho_nc_e', 'z_c', 'z_nc', 'z_c_d', 'z_nc_d', 'z_c_e',
+                         'z_nc_e']
+
+        # Make short category
+        make_short = {'Instruments and Communications Equipment': 'Instruments and Communications',
+                      'Office and Residential Equipment': 'Office and Residential',
+                      'Other Equipment': 'Other',
+                      'Transportation Equipment': 'Transportation',
+                      'Other Industrial Equipment': 'Other Industrial',
+                      'Nonresidential Buildings': 'Nonresidential Bldgs',
+                      'Residential Buildings': 'Residential Bldgs',
+                      'Mining and Drilling Structures': 'Mining and Drilling',
+                      'Other Structures': 'Other',
+                      'Computers and Software': 'Computers and Software',
+                      'Industrial Machinery': 'Industrial Machinery'}
+        equipment_df['short_category'] = equipment_df['asset_category'].map(make_short)
+        structure_df['short_category'] = structure_df['asset_category'].map(make_short)
+
+        # Add the Reform and the Baseline to Equipment Asset
+        for f in format_fields:
+            equipment_copy = equipment_df.copy()
+            equipment_copy['rate'] = equipment_copy[f]
+            equipment_copy['hover'] = equipment_copy.apply(lambda x: "{0:.1f}%".format(x[f] * 100), axis=1)
+            simple_equipment_copy = equipment_copy.filter(items=['size', 'size_c', 'size_nc', 'rate', 'hover', 'short_category', 'Asset'])
+            data_sources[list_string[i] + '_equipment_' + f] = ColumnDataSource(simple_equipment_copy)
+
+        # Add the Reform and the Baseline to Structures Asset
+        for f in format_fields:
+            structure_copy = structure_df.copy()
+            structure_copy['rate'] = structure_copy[f]
+            structure_copy['hover'] = structure_copy.apply(lambda x: "{0:.1f}%".format(x[f] * 100), axis=1)
+            simple_structure_copy = structure_copy.filter(items=['size', 'size_c', 'size_nc', 'rate', 'hover', 'short_category', 'Asset'])
+            data_sources[list_string[i] + '_structure_' + f] = ColumnDataSource(simple_structure_copy)
+
+        # Create initial data sources to plot on load
+        if list_string[i] == 'base':
+            equipment_copy = equipment_df.copy()
+            equipment_copy['rate'] = equipment_copy['mettr_c']
+            equipment_copy['hover'] = equipment_copy.apply(lambda x: "{0:.1f}%".format(x[f] * 100), axis=1)
+            simple_equipment_copy = equipment_copy.filter(items=['size', 'size_c', 'size_nc', 'rate', 'hover', 'short_category', 'Asset'])
+            data_sources['equip_source'] = ColumnDataSource(simple_equipment_copy)
+
+            structure_copy = structure_df.copy()
+            structure_copy['rate'] = structure_copy['mettr_c']
+            structure_copy['hover'] = structure_copy.apply(lambda x: "{0:.1f}%".format(x[f] * 100), axis=1)
+            simple_structure_copy = structure_copy.filter(items=['size', 'size_c', 'size_nc', 'rate', 'hover', 'short_category', 'Asset'])
+            data_sources['struc_source'] = ColumnDataSource(simple_structure_copy)
+
+    # Define categories for Equipments assets
+    equipment_assets = ['Computers and Software',
+                        'Instruments and Communications',
+                        'Office and Residential',
+                        'Transportation',
+                        'Industrial Machinery',
+                        'Other Industrial',
+                        'Other']
+
+    # Define categories for Structures assets
+    structure_assets = ['Residential Bldgs',
+                        'Nonresidential Bldgs',
+                        'Mining and Drilling',
+                        'Other']
+
+    # Equipment plot
+    p = figure(plot_height=540,
+               plot_width=990,
+               y_range=list(reversed(equipment_assets)),
+               tools='hover',
+               background_fill_alpha=0
+               )
+    p.add_layout(Title(text='Marginal Effective Tax Rates on Corporate Investments in Equipment', **TITLE_FORMATS), "above")
+
+    hover = p.select(dict(type=HoverTool))
+    hover.tooltips = [('Asset', ' @Asset (@hover)')]
+
+    p.xaxis.axis_label = "Marginal Effective Tax Rate"
+    p.xaxis[0].formatter = NumeralTickFormatter(format="0.1%")
+
+    p.toolbar_location = None
+    p.min_border_right = 5
+
+    p.outline_line_width = 5
+    p.border_fill_alpha = 0
+    p.xaxis.major_tick_line_color = "firebrick"
+    p.xaxis.major_tick_line_width = 3
+    p.xaxis.minor_tick_line_color = "orange"
+
+    p.outline_line_width = 1
+    p.outline_line_alpha = 1
+    p.outline_line_color = "black"
+
+    p.circle(x='rate',
+             y='short_category',
+             color=BLUE,
+             size='size',
+             line_color="#333333",
+             fill_alpha=.4,
+             source=data_sources['equip_source'],
+             alpha=.4
+             )
+
+    # Style the tools
+    p.add_tools(WheelZoomTool(), ResetTool(), SaveTool())
+    p.toolbar_location = "right"
+    p.toolbar.logo = None
+
+    # Structures plot
+    p2 = figure(plot_height=540,
+                plot_width=990,
+                y_range=list(reversed(structure_assets)),
+                tools='hover',
+                background_fill_alpha=0)
+    p2.add_layout(Title(text='Marginal Effective Tax Rates on Corporate Investments in Structures', **TITLE_FORMATS),"above")
+
+    hover = p2.select(dict(type=HoverTool))
+    hover.tooltips = [('Asset', ' @Asset (@hover)')]
+    p2.xaxis.axis_label = "Marginal Effective Tax Rate"
+    p2.xaxis[0].formatter = NumeralTickFormatter(format="0.1%")
+    p2.toolbar_location = None
+    p2.min_border_right = 5
+    p2.outline_line_width = 0
+    p2.border_fill_alpha = 0
+
+    p2.xaxis.major_tick_line_color = "firebrick"
+    p2.xaxis.major_tick_line_width = 3
+    p2.xaxis.minor_tick_line_color = "orange"
+
+
+    p2.circle(x='rate',
+              y='short_category',
+              color=RED,
+              size='size',
+              line_color="#333333",
+              fill_alpha=.4,
+              source=data_sources['struc_source'],
+              alpha=.4)
+
+    p2.outline_line_width = 1
+    p2.outline_line_alpha = 1
+    p2.outline_line_color = "black"
+
+    # Style the tools
+    p2.add_tools(WheelZoomTool(), ResetTool(), SaveTool())
+    p2.toolbar_location = "right"
+    p2.toolbar.logo = None
+
+    # add buttons
+    controls_callback = CustomJS(args=data_sources,
+                                 code=CONTROLS_CALLBACK_SCRIPT)
+
+    c_nc_buttons = RadioButtonGroup(labels=['Corporate', 'Noncorporate'],
+                                    active=0, callback=controls_callback)
+    controls_callback.args['c_nc_buttons'] = c_nc_buttons
+
+    format_buttons = RadioButtonGroup(labels=['Baseline', 'Reform', 'Change'],
+                                    active=0, callback=controls_callback)
+    controls_callback.args['format_buttons'] = format_buttons
+
+    interest_buttons = RadioButtonGroup(labels=['METTR', 'METR', 'Cost of Capital', 'Depreciation'],
+                                        active=0, width=700, callback=controls_callback)
+    controls_callback.args['interest_buttons'] = interest_buttons
+
+    type_buttons = RadioButtonGroup(labels=['Typically Financed', 'Equity Financed', 'Debt Financed'],
+                                    active=0, width=700, callback=controls_callback)
+    controls_callback.args['type_buttons'] = type_buttons
+
+    # Create Tabs
+    tab = Panel(child=p, title='Equipment')
+    tab2 = Panel(child=p2, title='Structures')
+    tabs = Tabs(tabs=[tab, tab2])
+    layout = gridplot(
+        children=[[tabs],
+                  [c_nc_buttons, interest_buttons],
+                  [format_buttons, type_buttons]]
+    )
+
+    # Create components
+    js, div = components(layout)
+    cdn_js = CDN.js_files[0]
+    cdn_css = CDN.css_files[0]
+
+    return js, div, cdn_js, cdn_css