1.8.3

* [#143](#143), scattergeo map chart UI changes
* updated offline chart generation of maps to work without loading topojson from the web
* fix to allow correlations timeseries to handle when date columns jump between rolling & non-rolling
* added slider to animation and added animation to maps
* fixes for IE 11 compatibility issues
* labeling changes for "Reshape" popup
* added grouping to maps

.circleci/config.yml

@@ -5,7 +5,7 @@ defaults: &defaults
       CIRCLE_ARTIFACTS: /tmp/circleci-artifacts
       CIRCLE_TEST_REPORTS: /tmp/circleci-test-results
       CODECOV_TOKEN: b0d35139-0a75-427a-907b-2c78a762f8f0
-      VERSION: 1.8.2
+      VERSION: 1.8.3
       PANDOC_RELEASES_URL: https://github.com/jgm/pandoc/releases
     steps:
     - checkout

CHANGES.md

@@ -1,5 +1,14 @@
 ## Changelog
 
+### 1.8.3 (2020-4-4)
+* [#143](https://github.com/man-group/dtale/issues/143), scattergeo map chart UI changes
+* updated offline chart generation of maps to work without loading topojson from the web
+* fix to allow correlations timeseries to handle when date columns jump between rolling & non-rolling
+* added slider to animation and added animation to maps
+* fixes for IE 11 compatibility issues
+* labeling changes for "Reshape" popup
+* added grouping to maps
+
 ### 1.8.2 (2020-4-1)
  * [#129](https://github.com/man-group/dtale/issues/129), show dtype when hovering over header in "Highlight Dtypes" mode and description tooltips added to main menu
  * made "No Aggregation" the default aggregation in charts

README.md

@@ -1,6 +1,6 @@
 [![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/Title.png)](https://github.com/man-group/dtale)
 
-[Live Demo](http://andrewschonfeld.pythonanywhere.com)
+[Live Demo](http://alphatechadmin.pythonanywhere.com)
 
 -----------------
 
@@ -41,7 +41,7 @@ D-Tale was the product of a SAS to Python conversion.  What was originally a per
   - [Dimensions/Main Menu](#dimensionsmain-menu)
   - [Header](#header)
   - [Main Menu Functions](#main-menu-functions)
-    - [Describe](#describe), [Filter](#filter), [Building Columns](#building-columns), [Reshape](#reshape), [Charts](#charts), [Coverage (Deprecated)](#coverage-deprecated), [Correlations](#correlations), [Heat Map](#heat-map), [Instances](#instances), [Code Exports](#code-exports), [About](#about), [Resize](#resize), [Shutdown](#shutdown)
+    - [Describe](#describe), [Custom Filter](#custom-filter), [Building Columns](#building-columns), [Summarize Data](#summarize-data), [Charts](#charts), [Coverage (Deprecated)](#coverage-deprecated), [Correlations](#correlations), [Heat Map](#heat-map), [Instances](#instances), [Code Exports](#code-exports), [About](#about), [Resize](#resize), [Shutdown](#shutdown)
   - [Column Menu Functions](#column-menu-functions)
     - [Filtering](#filtering), [Moving Columns](#moving-columns), [Hiding Columns](#hiding-columns), [Lock](#lock), [Unlock](#unlock), [Sorting](#sorting), [Formats](#formats), [Column Analysis](#column-analysis)
   - [Menu Functions Depending on Browser Dimensions](#menu-functions-depending-on-browser-dimensions)
@@ -51,7 +51,7 @@ D-Tale was the product of a SAS to Python conversion.  What was originally a per
   - [Linting](#linting)
   - [Formatting JS](#formatting-js)
   - [Docker Development](#docker-development)
-- [Global State/Data Storage](#global-state_data-storage)
+- [Global State/Data Storage](https://github.com/man-group/dtale/blob/master/docs/GLOBAL_STATE.md)
 - [Startup Behavior](#startup-behavior)
 - [Documentation](#documentation)
 - [Requirements](#requirements)
@@ -333,8 +333,8 @@ View all the columns & their data types as well as individual details of each co
 |int|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/Describe_int.png)|Anything with standard numeric classifications (min, max, 25%, 50%, 75%) will have a nice boxplot with the mean (if it exists) displayed as an outlier if you look closely.|
 |float|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/Describe_float.png)||
 
-#### Filter
-Apply a simple pandas `query` to your data (link to pandas documentation included in popup)  
+#### Custom Filter
+Apply a custom pandas `query` to your data (link to pandas documentation included in popup)  
 
 Context Variables are user-defined values passed in via the `context_variables` argument to dtale.show(); they can be referenced in filters by prefixing the variable name with '@'.
 
@@ -371,7 +371,7 @@ This video shows you how to build the following:
  - Dates: retrieving date properties (hour, weekday, month...) as well as conversions (month end)
  - Random: columns of data type (int, float, string & date) populated with random uniformly distributed values.
 
-#### Reshape
+#### Summarize Data
 
 This is very powerful functionality which allows users to create a new data from currently loaded data.  The operations currently available are:
 - **Aggregation**: consolidate data by running different aggregations on columns by a specific index
@@ -416,6 +416,8 @@ Here are some examples:
 |heatmap|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/charts/heatmap.png)||
 |3D scatter|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/charts/3d_scatter.png)||
 |surface|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/charts/surface.png)||
+|Maps (Scatter GEO)|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/charts/scattergeo.png)||
+|Maps (Choropleth)|![](https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/charts/choropleth.png)||
 
 Y-Axis Toggling
 

docker/2_7/Dockerfile

@@ -44,4 +44,4 @@ WORKDIR /app
 
 RUN set -eux \
   ; . /root/.bashrc \
-  ; easy_install dtale-1.8.2-py2.7.egg
+  ; easy_install dtale-1.8.3-py2.7.egg

docker/3_6/Dockerfile

@@ -44,4 +44,4 @@ WORKDIR /app
 
 RUN set -eux \
   ; . /root/.bashrc \
-  ; easy_install dtale-1.8.2-py3.7.egg
+  ; easy_install dtale-1.8.3-py3.7.egg

docs/source/conf.py

@@ -64,9 +64,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = u'1.8.2'
+version = u'1.8.3'
 # The full version, including alpha/beta/rc tags.
-release = u'1.8.2'
+release = u'1.8.3'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

dtale/app.py

@@ -602,6 +602,6 @@ def offline_chart(df, chart_type=None, query=None, x=None, y=None, z=None, group
     instance = startup(url=None, data=df, data_id=999)
     output = instance.offline_chart(chart_type=chart_type, query=query, x=x, y=y, z=z, group=group, agg=agg,
                                     window=window, rolling_comp=rolling_comp, barmode=barmode, barsort=barsort,
-                                    yaxis=yaxis, filepath=filepath)
+                                    yaxis=yaxis, filepath=filepath, **kwargs)
     global_state.cleanup()
     return output

dtale/charts/utils.py

@@ -30,7 +30,7 @@ def valid_chart(chart_type=None, x=None, y=None, z=None, **inputs):
         map_type = inputs.get('map_type')
         if map_type == 'choropleth' and all(inputs.get(p) is not None for p in ['loc_mode', 'loc', 'map_val']):
             return True
-        elif map_type == 'scattergeo' and all(inputs.get(p) is not None for p in ['lat', 'lon', 'map_val']):
+        elif map_type == 'scattergeo' and all(inputs.get(p) is not None for p in ['lat', 'lon']):
             return True
         return False
 
@@ -144,6 +144,23 @@ def group_filter_handler(col_def, group_val, group_classifier):
     return "{col} == '{val}'".format(col=col_def, val=group_val)
 
 
+def build_group_inputs_filter(df, group_inputs):
+    dtypes = get_dtypes(df)
+
+    def _group_filter(group_val):
+        for gc, gv in group_val.items():
+            classifier = classify_type(dtypes[gc])
+            yield group_filter_handler(gc, gv, classifier)
+
+    def _full_filter():
+        for group_val in group_inputs:
+            group_filter = ' and '.join(list(_group_filter(group_val)))
+            yield group_filter
+
+    filters = list(_full_filter())
+    return '({})'.format(') or ('.join(filters))
+
+
 def retrieve_chart_data(df, *args, **kwargs):
     """
     Retrieves data from a dataframe for x, y, z & group inputs complete with date frequency
@@ -169,20 +186,7 @@ def retrieve_chart_data(df, *args, **kwargs):
     all_data = pd.concat(all_data, axis=1)
     all_code = ["chart_data = pd.concat(["] + all_code + ["], axis=1)"]
     if len(make_list(kwargs.get('group_val'))):
-        dtypes = get_dtypes(all_data)
-
-        def _group_filter(group_val):
-            for gc, gv in group_val.items():
-                classifier = classify_type(dtypes[gc])
-                yield group_filter_handler(gc, gv, classifier)
-
-        def _full_filter():
-            for group_val in kwargs['group_val']:
-                group_filter = ' and '.join(list(_group_filter(group_val)))
-                yield group_filter
-
-        filters = list(_full_filter())
-        filters = '({})'.format(') or ('.join(filters))
+        filters = build_group_inputs_filter(all_data, kwargs['group_val'])
         all_data = all_data.query(filters)
         all_code.append('chart_data = chart_data.query({})'.format(filters))
     return all_data, all_code
@@ -426,6 +430,6 @@ def weekday_tick_handler(col_data, col):
 
 def find_group_vals(df, group_cols):
     group_vals, _ = retrieve_chart_data(df, group_cols)
-    group_vals = group_vals.drop_duplicates()
+    group_vals = group_vals.drop_duplicates().sort_values(group_cols)
     group_f, _ = build_formatters(group_vals)
     return group_f.format_dicts(group_vals.itertuples())

dtale/cli/loaders/csv_loader.py

@@ -1,16 +1,10 @@
 import pandas as pd
 import requests
-from six import PY3
+from six import PY3, StringIO
 
 from dtale.app import show
 from dtale.cli.clickutils import get_loader_options
 
-if PY3:
-    from io import StringIO
-else:
-    from StringIO import StringIO
-
-
 '''
   IMPORTANT!!! These global variables are required for building any customized CLI loader.
   When build_loaders runs startup it will search for any modules containing the global variable LOADER_KEY.