Adding a PivotTableViz

panoramix/bin/panoramix

@@ -283,6 +283,20 @@ The source dataset came from [here](https://github.com/hadley/babynames)
         session.add(slc)
     slices.append(slc)
 
+    slice_name = "Pivot Table"
+    slc = session.query(Slice).filter_by(slice_name=slice_name).first()
+    if not slc:
+        slc = Slice(
+            slice_name=slice_name,
+            viz_type='pivot_table',
+            datasource_type='table',
+            table=tbl,
+            params=get_slice_json(
+                slice_name, viz_type="pivot_table", metrics=['sum__num'],
+                groupby=['name'], columns=['state']))
+        session.add(slc)
+    slices.append(slc)
+
     print("Creating a dashboard")
     Dash = models.Dashboard
     dash = session.query(Dash).filter_by(dashboard_title="Births").first()

panoramix/forms.py

@@ -91,6 +91,10 @@ def __init__(self, viz):
                 'Group by',
                 choices=self.choicify(datasource.groupby_column_names),
                 description="One or many fields to group by"),
+            'columns': SelectMultipleField(
+                'Columns',
+                choices=self.choicify(datasource.groupby_column_names),
+                description="One or many fields to pivot as columns"),
             'granularity': TextField(
                 'Time Granularity', default="one day",
                 description=(
@@ -182,6 +186,14 @@ def __init__(self, viz):
                 default='linear',
                 description="Line interpolation as defined by d3.js"),
             'code': TextAreaField("Code", description="Put your code here", default=''),
+            'pandas_aggfunc': SelectField(
+                "Aggregation function",
+                choices=self.choicify([
+                    'sum', 'mean', 'min', 'max', 'median', 'stdev', 'var']),
+                default='sum',
+                description=(
+                    "Aggregate function to apply when pivoting and "
+                    "computing the total rows and columns")),
             'size_from': TextField(
                 "Font Size From",
                 default="20",
@@ -241,6 +253,7 @@ def get_form(self, previous=False):
         field_css_classes = {k: ['form-control'] for k in px_form_fields.keys()}
         select2 = [
             'viz_type',
+            'viz_type', 'columns', 'pandas_aggfunc',
             'row_limit', 'rolling_type', 'series',
             'entity', 'x', 'y', 'size', 'rotation', 'metric', 'limit',
             'markup_type',]

panoramix/templates/panoramix/viz_pivot_table.html

@@ -0,0 +1,41 @@
+{% macro viz_html(viz) %}
+  {% if viz.request.args.get("async") == "true" %}
+  {{ viz.get_df().to_html(na_rep='', classes="dataframe table table-striped table-bordered table-condensed")|safe }}
+
+  {% else %}
+  <div id="{{ viz.token }}" style="display: none;overflow: auto; height: 100%;"></div>
+  <img src="{{ url_for("static", filename="img/loading.gif") }}" class="loading">
+  {% endif %}
+{% endmacro %}
+
+{% macro viz_js(viz) %}
+  {% if viz.form_data.get("async") != "true" %}
+  <script>
+  $( document ).ready(function() {
+    var url = "{{ viz.get_url(async="true", standalone="true", skip_libs="true")|safe }}";
+    var token = $("#{{ viz.token }}");
+    token.load(url, function(response, status, xhr){
+      if(status=="error"){
+        var err = '<div class="alert alert-danger">' + xhr.responseText  + '</div>';
+        token.html(err);
+        token.show();
+      }
+      else{
+        {% if viz.form_data.get('groupby')|length == 1 %}
+          var table = token.find('table').DataTable({
+            paging: false,
+            searching: false,
+          });
+          table.column('-1').order( 'desc' ).draw();
+        {% endif %}
+      }
+      token.show();
+      token.parent().find("img.loading").hide();
+    });
+  });
+  </script>
+  {% endif %}
+{% endmacro %}
+
+{% macro viz_css(viz) %}
+{% endmacro %}

panoramix/viz.py

@@ -222,6 +222,60 @@ def get_df(self):
         return df
 
 
+class PivotTableViz(BaseViz):
+    viz_type = "pivot_table"
+    verbose_name = "Pivot Table"
+    template = 'panoramix/viz_pivot_table.html'
+    css_files = ['lib/dataTables/dataTables.bootstrap.css']
+    is_timeseries = False
+    js_files = [
+        'lib/dataTables/jquery.dataTables.min.js',
+        'lib/dataTables/dataTables.bootstrap.js']
+    form_fields = [
+        'viz_type',
+        'granularity',
+        ('since', 'until'),
+        'groupby',
+        'columns',
+        'metrics',
+        'pandas_aggfunc',
+    ]
+
+    def query_obj(self):
+        d = super(PivotTableViz, self).query_obj()
+        groupby = self.form_data.get('groupby')
+        columns = self.form_data.get('columns')
+        metrics = self.form_data.get('metrics')
+        if not groupby:
+            raise Exception("Please choose at least one \"Group by\" field ")
+        if not metrics:
+            raise Exception("Please choose at least one metric")
+        if (
+                any(v in groupby for v in columns) or
+                any(v in columns for v in groupby)):
+            raise Exception("groupby and columns can't overlap")
+
+        d['groupby'] = list(set(d['groupby']) | set(self.form_data.get('columns')))
+        d['is_timeseries'] = False
+        d['timeseries_limit'] = None
+        return d
+
+    def get_df(self):
+        df = super(PivotTableViz, self).get_df()
+        if (
+                self.form_data.get("granularity") == "all" and
+                'timestamp' in df):
+            del df['timestamp']
+        df = df.pivot_table(
+            index=self.form_data.get('groupby'),
+            columns=self.form_data.get('columns'),
+            values=self.form_data.get('metrics'),
+            aggfunc=self.form_data.get('pandas_aggfunc'),
+            margins=True,
+        )
+        return df
+
+
 class MarkupViz(BaseViz):
     viz_type = "markup"
     verbose_name = "Markup Widget"
@@ -648,6 +702,7 @@ def get_json_data(self):
 
 viz_types_list = [
     TableViz,
+    PivotTableViz,
     NVD3TimeSeriesViz,
     NVD3CompareTimeSeriesViz,
     NVD3TimeSeriesStackedViz,