1.8.11

* #191: improving outlier filter suggestions
* #190: hide "Animate" inputs when "Percentage Sum" or "Percentage Count" aggregations are used
* #189: hide "Barsort" when grouping is being applied
* #187: missing & outlier tooltip descriptions on column headers
* #186: close "Describe" tab after clicking "Update Grid"
* #122: editable cells
* npm package upgrades
* circleci build script refactoring

.prettierrc

@@ -2,6 +2,7 @@
     "trailingComma": "es5",
     "printWidth": 120,
     "jsxBracketSameLine": true,
+    "arrowParens": "avoid",
     "overrides": [
     {
         "files": "*.css",

README.md

@@ -9,6 +9,7 @@
 
 [![CircleCI](https://circleci.com/gh/man-group/dtale.svg?style=shield&circle-token=4b67588a87157cc03b484fb96be438f70b5cd151)](https://circleci.com/gh/man-group/dtale)
 [![PyPI](https://img.shields.io/pypi/pyversions/dtale.svg)](https://pypi.python.org/pypi/dtale/)
+![PyPI](https://img.shields.io/pypi/v/dtale)
 [![ReadTheDocs](https://readthedocs.org/projects/dtale/badge)](https://dtale.readthedocs.io)
 [![codecov](https://codecov.io/gh/man-group/dtale/branch/master/graph/badge.svg)](https://codecov.io/gh/man-group/dtale)
 [![Downloads](https://pepy.tech/badge/dtale)](https://pepy.tech/project/dtale)

dtale/dash_application/charts.py

@@ -944,7 +944,7 @@ def heatmap_builder(data_id, export=False, **inputs):
                 code += agg_code
         if not len(data):
             raise Exception('No data returned for this computation!')
-        check_exceptions(data[dupe_cols], agg not in ['corr', 'raw'], unlimited_data=True)
+        check_exceptions(data[dupe_cols], agg in ['corr', 'raw'], unlimited_data=True)
         dtypes = {c: classify_type(dtype) for c, dtype in get_dtypes(data).items()}
         data_f, _ = chart_formatters(data)
         data = data_f.format_df(data)

dtale/dash_application/layout.py

@@ -407,17 +407,20 @@ def bar_input_style(**inputs):
     """
     Sets display CSS property for bar chart inputs
     """
-    return dict(display='block' if inputs.get('chart_type') == 'bar' else 'none')
+    chart_type, group_col = (inputs.get(p) for p in ['chart_type', 'group'])
+    show_bar = chart_type == 'bar'
+    show_barsort = show_bar and group_col is None
+    return dict(display='block' if show_bar else 'none'), dict(display='block' if show_barsort else 'none')
 
 
 def colorscale_input_style(**inputs):
     return dict(display='block' if inputs.get('chart_type') in ['heatmap', 'maps'] else 'none')
 
 
 def animate_styles(df, **inputs):
-    chart_type, cpg = (inputs.get(p) for p in ['chart_type', 'cpg'])
+    chart_type, agg, cpg = (inputs.get(p) for p in ['chart_type', 'agg', 'cpg'])
     opts = []
-    if cpg:
+    if cpg or agg in ['pctsum', 'pctct']:
         return dict(display='none'), dict(display='none'), opts
     if chart_type in ANIMATION_CHARTS:
         return dict(display='block'), dict(display='none'), opts
@@ -512,7 +515,7 @@ def charts_layout(df, settings, **inputs):
     show_input = show_input_handler(chart_type)
     show_cpg = show_chart_per_group(**inputs)
     show_yaxis = show_yaxis_ranges(**inputs)
-    bar_style = bar_input_style(**inputs)
+    bar_style, barsort_input_style = bar_input_style(**inputs)
     animate_style, animate_by_style, animate_opts = animate_styles(df, **inputs)
 
     options = build_input_options(df, **inputs)
@@ -803,7 +806,7 @@ def show_map_style(show):
                         ), className='col-auto addon-min-width', style=bar_style, id='barmode-input'),
                         build_input('Barsort', dcc.Dropdown(
                             id='barsort-dropdown', options=barsort_options, value=inputs.get('barsort')
-                        ), className='col-auto addon-min-width', style=bar_style, id='barsort-input'),
+                        ), className='col-auto addon-min-width', style=barsort_input_style, id='barsort-input'),
                         html.Div(
                             html.Div(
                                 [

dtale/dash_application/views.py

@@ -262,15 +262,15 @@ def input_toggles(_ts, inputs, pathname):
         group_style = {'display': 'block' if show_input('group') else 'none'}
         rolling_style = {'display': 'inherit' if agg == 'rolling' else 'none'}
         cpg_style = {'display': 'block' if show_chart_per_group(**inputs) else 'none'}
-        bar_style = bar_input_style(**inputs)
+        bar_style, barsort_style = bar_input_style(**inputs)
         yaxis_style = {'display': 'block' if show_yaxis_ranges(**inputs) else 'none'}
 
         data_id = get_data_id(pathname)
         df = global_state.get_data(data_id)
         animate_style, animate_by_style, animate_opts = animate_styles(df, **inputs)
 
         return (
-            y_multi_style, y_single_style, z_style, group_style, rolling_style, cpg_style, bar_style, bar_style,
+            y_multi_style, y_single_style, z_style, group_style, rolling_style, cpg_style, bar_style, barsort_style,
             yaxis_style, animate_style, animate_by_style, animate_opts
         )
 

dtale/static/css/main.css

@@ -1702,7 +1702,7 @@ select.form-control-lg:not([size]):not([multiple]), .input-group-lg > select.for
   margin-left: 0.75rem;
 }
 
-.invalianeld-feedback {
+.invalid-feedback {
   display: none;
   margin-top: .25rem;
   font-size: .875rem;
@@ -10124,6 +10124,9 @@ select.form-control:focus,
   position: relative;
   border-bottom: dashed 1px #004c93;
 }
+.cell.hoverable {
+  border-bottom: solid 1px rgba(170, 170, 170, 0.25);
+}
 .hoverable-click {
   display: inline;
   position: relative;
@@ -10139,6 +10142,9 @@ select.form-control:focus,
 li.hoverable:hover {
   border-bottom: solid 1px #a7b3b7;
 }
+.cell.hoverable:hover {
+  border-bottom: solid 1px rgba(170, 170, 170, 0.25);
+}
 
 .hoverable:focus {
   outline: 0;
@@ -10169,7 +10175,8 @@ li.hoverable:hover {
   text-align: left;
   color: #404040;
 }
-.hoverable__content.menu-description {
+.hoverable__content.menu-description,
+.hoverable__content.edit-cell {
     top: -0.8em;
     left: 13em;
 }
@@ -10196,6 +10203,12 @@ li.hoverable:hover {
   top: unset;
   bottom: 110%;
 }
+.hoverable__content.col-menu-desc {
+  padding: .5em .5em;
+  text-align: center;
+  top: unset;
+  bottom: 110%;
+}
 
 div.hoverable.label {
   border-bottom: none;
@@ -10224,13 +10237,21 @@ div.hoverable.label > div.hoverable__content {
     right: inherit;
     transform: rotate(270deg);
 }
+.hoverable__content.edit-cell::before {
+    left: -0.7em;
+    top: 2.75em;
+    right: inherit;
+    transform: rotate(270deg);
+}
 .hoverable__content.build-code::before,
 .hoverable__content.map-types::before {
     right: unset;
     left: 2em;
 }
-.hoverable__content.copy-tt-top::before {
+.hoverable__content.copy-tt-top::before,
+.hoverable__content.col-menu-desc::before {
     bottom: unset;
+    border-bottom: none;
     top: 95%;
     -moz-transform: rotate(180deg);
     -webkit-transform: rotate(180deg);
@@ -10258,12 +10279,19 @@ div.hoverable.label > div.hoverable__content {
     right: inherit;
     transform: rotate(270deg);
 }
+.hoverable__content.edit-cell::after {
+    left: -0.6em;
+    top: 2.75em;
+    right: inherit;
+    transform: rotate(270deg);
+}
 .hoverable__content.build-code::after,
 .hoverable__content.map-types::after {
     right: unset;
     left: 2em;
 }
-.hoverable__content.copy-tt-top::after {
+.hoverable__content.copy-tt-top::after,
+.hoverable__content.col-menu-desc::after {
     bottom: unset;
     top: calc(92% + .1em);
     -moz-transform: rotate(180deg);
@@ -10567,7 +10595,7 @@ div.container-fluid.filter > div#popup-content > div.modal-body {
 }
 
 div.container-fluid.code-popup > div#popup-content > div.modal-footer,
-div.container-fluid.code-export > div#popup-content > div.modal-footer, {
+div.container-fluid.code-export > div#popup-content > div.modal-footer {
   position: absolute;
   bottom: 0;
   width: 100%;

dtale/views.py

@@ -409,7 +409,7 @@ def _formatter(col_index, col):
             visible = prev_dtypes[col].get('visible', True)
         s = data[col]
         dtype_data = dict(name=col, dtype=dtype, index=col_index, visible=visible,
-                          hasMissing=bool(s.isnull().any()), hasOutliers=False)
+                          hasMissing=int(s.isnull().sum()), hasOutliers=0)
         classification = classify_type(dtype)
         if classification in ['F', 'I'] and not data[col].isnull().all() and col in data_ranges:  # floats/ints
             col_ranges = data_ranges[col]
@@ -419,11 +419,11 @@ def _formatter(col_index, col):
             # load outlier information
             o_s, o_e = calc_outlier_range(s)
             if not any((np.isnan(v) or np.isinf(v) for v in [o_s, o_e])):
-                dtype_data['hasOutliers'] = bool(((s < o_s) | (s > o_e)).any())
+                dtype_data['hasOutliers'] += int(((s < o_s) | (s > o_e)).sum())
                 dtype_data['outlierRange'] = dict(lower=o_s, upper=o_e)
 
         if classification == 'S' and not dtype_data['hasMissing']:
-            dtype_data['hasMissing'] = bool((s.str.strip() == '').any())
+            dtype_data['hasMissing'] += int((s.str.strip() == '').sum())
         return dtype_data
     return _formatter
 
@@ -1069,10 +1069,17 @@ def outliers(data_id, column):
         iqr_lower, iqr_upper = calc_outlier_range(s)
         formatter = find_dtype_formatter(find_dtype(df[column]))
         outliers = s[(s < iqr_lower) | (s > iqr_upper)].unique()
+        if not len(outliers):
+            return jsonify(outliers=[])
         top = len(outliers) > 100
         outliers = [formatter(v) for v in outliers[:100]]
-        query = '(({column} < {lower}) or ({column} > {upper}))'.format(column=column, lower=json_float(iqr_lower),
-                                                                        upper=json_float(iqr_upper))
+        queries = []
+        if iqr_lower > s.min():
+            queries.append('{column} < {lower}'.format(column=column, lower=json_float(iqr_lower)))
+        if iqr_upper < s.max():
+            queries.append('{column} > {upper}'.format(column=column, upper=json_float(iqr_upper)))
+        query = '(({}))'.format(') or ('.join(queries)) if len(queries) > 1 else queries[0]
+
         code = (
             "s = df['{column}']\n"
             "q1 = s.quantile(0.25)\n"
@@ -1114,7 +1121,7 @@ def rename_col(data_id, column):
         rename = get_str_arg(request, 'rename')
         data = global_state.get_data(data_id)
         if column != rename and rename in data.columns:
-            return jsonify(dict(error='Column name "{}" already exists!'))
+            return jsonify(error='Column name "{}" already exists!')
 
         data = data.rename(columns={column: rename})
         curr_history = global_state.get_history(data_id) or []
@@ -1132,6 +1139,71 @@ def rename_col(data_id, column):
         return jsonify_error(e)
 
 
+@dtale.route('/edit-cell/<data_id>/<column>')
+def edit_cell(data_id, column):
+    try:
+        row_index = get_int_arg(request, "rowIndex")
+        updated = get_str_arg(request, "updated")
+        updated_str = updated
+        curr_settings = global_state.get_settings(data_id)
+        data = run_query(
+            global_state.get_data(data_id),
+            build_query(data_id, curr_settings.get('query')),
+            global_state.get_context_variables(data_id),
+            ignore_empty=True,
+        )
+        dtype = find_dtype(data[column])
+
+        code = []
+        if updated in ['nan', 'inf']:
+            updated_str = 'np.{}'.format(updated)
+            updated = getattr(np, updated)
+            data.loc[row_index, column] = updated
+            code.append("df.loc[{row_index}, '{column}'] = {updated}".format(row_index=row_index, column=column,
+                                                                             updated=updated_str))
+        else:
+            classification = classify_type(dtype)
+            if classification == 'B':
+                updated = updated.lower() == 'true'
+                updated_str = str(updated)
+            elif classification == 'I':
+                updated = int(updated)
+            elif classification == 'F':
+                updated = float(updated)
+            elif classification == 'D':
+                updated_str = 'pd.Timestamp({})'.format(updated)
+                updated = pd.Timestamp(updated)
+            elif classification == 'TD':
+                updated_str = 'pd.Timedelta({})'.format(updated)
+                updated = pd.Timedelta(updated)
+            else:
+                if dtype.startswith('category') and updated not in data[column].unique():
+                    data[column].cat.add_categories(updated, inplace=True)
+                    code.append("data['{column}'].cat.add_categories('{updated}', inplace=True)".format(
+                        column=column, updated=updated))
+                updated_str = "'{}'".format(updated)
+            data.at[row_index, column] = updated
+            code.append("df.at[{row_index}, '{column}'] = {updated}".format(row_index=row_index, column=column,
+                                                                            updated=updated_str))
+        curr_history = global_state.get_history(data_id) or []
+        curr_history += code
+        global_state.set_history(data_id, curr_history)
+
+        data = global_state.get_data(data_id)
+        dtypes = global_state.get_dtypes(data_id)
+        ranges = {}
+        try:
+            ranges[column] = data[[column]].agg(['min', 'max']).to_dict()[column]
+        except ValueError:
+            pass
+        dtype_f = dtype_formatter(data, {column: dtype}, ranges)
+        dtypes = [dtype_f(dt['index'], column) if dt['name'] == column else dt for dt in dtypes]
+        global_state.set_dtypes(data_id, dtypes)
+        return jsonify(success=True)
+    except BaseException as e:
+        return jsonify_error(e)
+
+
 @dtale.route('/column-filter-data/<data_id>/<column>')
 def get_column_filter_data(data_id, column):
     try: