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New Data Type + Action: Automatic geographic attribute visualizations (…
…#253) * Merge upstream * Add new default action for geographic data types (longitude and latitude): geoshape * Add 'country' as a new secondary geographical feature * Reformat * remove unneeded file and run black * Rename to , remove vega_datasets from tests * Clean up intents in map.py * Add support to aggregate quantitative attributes * Format and test * Format with black * Replace vega dependency * Formatting * SIGNIFICANT CHANGES: Reuse univariate action, modify symbolmap, modify tests, use PandasExecutor * Format via black * Clean up helper functions for detecting geotypes * Resolve PR comments * Add exportability for choropleths * ARemove zero padding from fips and iso codes * Resolve comments from @caitlynachen Co-authored-by: Doris Lee <dorisjunglinlee@gmail.com>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,180 @@ | ||
| # Copyright 2019-2020 The Lux Authors. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| from lux.vislib.altair.AltairChart import AltairChart | ||
| import altair as alt | ||
| import us | ||
| from iso3166 import countries | ||
|
|
||
| alt.data_transformers.disable_max_rows() | ||
|
|
||
|
|
||
| class Choropleth(AltairChart): | ||
| """ | ||
| Choropleth is a subclass of AltairChart that renders choropleth maps. | ||
| All rendering properties for proportional symbol maps are set here. | ||
| See Also | ||
| -------- | ||
| altair-viz.github.io | ||
| """ | ||
|
|
||
| us_url = "https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/us-10m.json" | ||
| world_url = "https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/world-110m.json" | ||
|
|
||
| def __init__(self, dobj): | ||
| super().__init__(dobj) | ||
|
|
||
| def __repr__(self): | ||
| return f"Proportional Symbol Map <{str(self.vis)}>" | ||
|
|
||
| def initialize_chart(self): | ||
| x_attr = self.vis.get_attr_by_channel("x")[0] | ||
| y_attr = self.vis.get_attr_by_channel("y")[0] | ||
|
|
||
| x_attr_abv = str(x_attr.attribute) | ||
| y_attr_abv = str(y_attr.attribute) | ||
|
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| background, background_str = self.get_background(x_attr_abv.lower()) | ||
| geographical_name = self.get_geographical_name(x_attr_abv.lower()) | ||
| geo_map, geo_map_str, map_type, map_translation = self.get_geomap(x_attr_abv.lower()) | ||
| self.data[x_attr_abv] = self.data[x_attr_abv].apply(map_translation) | ||
|
|
||
| if len(x_attr_abv) > 25: | ||
| x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:] | ||
| if len(y_attr_abv) > 25: | ||
| y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:] | ||
|
|
||
| if isinstance(x_attr.attribute, str): | ||
| x_attr.attribute = x_attr.attribute.replace(".", "") | ||
| if isinstance(y_attr.attribute, str): | ||
| y_attr.attribute = y_attr.attribute.replace(".", "") | ||
|
|
||
| self.data = AltairChart.sanitize_dataframe(self.data) | ||
| height = 175 | ||
| width = int(height * (5 / 3)) | ||
|
|
||
| points = ( | ||
| alt.Chart(geo_map) | ||
| .mark_geoshape() | ||
| .encode( | ||
| color=f"{y_attr_abv}:Q", | ||
| ) | ||
| .transform_lookup(lookup="id", from_=alt.LookupData(self.data, x_attr_abv, [y_attr_abv])) | ||
| .project(type=map_type) | ||
| .properties( | ||
| width=width, height=height, title=f"Mean of {y_attr_abv} across {geographical_name}" | ||
| ) | ||
| ) | ||
|
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| chart = background + points | ||
|
|
||
| ###################################### | ||
| ## Constructing Altair Code String ## | ||
| ##################################### | ||
|
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||
| self.code += "import altair as alt\n" | ||
| dfname = "placeholder_variable" | ||
| self.code += f"""nan=float('nan') | ||
| df = pd.DataFrame({str(self.data.to_dict())}) | ||
| background = {background_str} | ||
| points = alt.Chart({geo_map_str}).mark_geoshape().encode( | ||
| color='{y_attr_abv}:Q', | ||
| ).transform_lookup( | ||
| lookup='id', | ||
| from_=alt.LookupData({dfname}, "{x_attr_abv}", ["{y_attr_abv}"]) | ||
| ).project( | ||
| type="{map_type}" | ||
| ).properties( | ||
| width={width}, | ||
| height={height}, | ||
| title="Mean of {y_attr_abv} across {geographical_name}" | ||
| ) | ||
| chart = background + points | ||
| """ | ||
| return chart | ||
|
|
||
| def get_background(self, feature): | ||
| """Returns background projection based on geographic feature.""" | ||
| maps = { | ||
| "state": ( | ||
| alt.topo_feature(Choropleth.us_url, feature="states"), | ||
| "albersUsa", | ||
| f"alt.topo_feature('{Choropleth.us_url}', feature='states')", | ||
| ), | ||
| "country": ( | ||
| alt.topo_feature(Choropleth.world_url, feature="countries"), | ||
| "equirectangular", | ||
| f"alt.topo_feature('{Choropleth.world_url}', feature='countries')", | ||
| ), | ||
| } | ||
| assert feature in maps | ||
| height = 175 | ||
| background = ( | ||
| alt.Chart(maps[feature][0]) | ||
| .mark_geoshape(fill="lightgray", stroke="white") | ||
| .properties(width=int(height * (5 / 3)), height=height) | ||
| .project(maps[feature][1]) | ||
| ) | ||
| background_str = f"(alt.Chart({maps[feature][2]}).mark_geoshape(fill='lightgray', stroke='white').properties(width=int({height} * (5 / 3)), height={height}).project('{maps[feature][1]}'))" | ||
| return background, background_str | ||
|
|
||
| def get_geomap(self, feature): | ||
| """Returns topological encoding, topological style, | ||
| and translation function based on geographic feature""" | ||
| maps = { | ||
| "state": ( | ||
| alt.topo_feature(Choropleth.us_url, feature="states"), | ||
| f"alt.topo_feature('{Choropleth.us_url}', feature='states')", | ||
| "albersUsa", | ||
| self.get_us_fips_code, | ||
| ), | ||
| "country": ( | ||
| alt.topo_feature(Choropleth.world_url, feature="countries"), | ||
| f"alt.topo_feature('{Choropleth.world_url}', feature='countries')", | ||
| "equirectangular", | ||
| self.get_country_iso_code, | ||
| ), | ||
| } | ||
| assert feature in maps | ||
| return maps[feature] | ||
|
|
||
| def get_us_fips_code(self, attribute): | ||
| """Returns FIPS code given a US state""" | ||
| if not isinstance(attribute, str): | ||
| return attribute | ||
| try: | ||
| return int(us.states.lookup(attribute).fips) | ||
| except: | ||
| return attribute | ||
|
|
||
| def get_country_iso_code(self, attribute): | ||
| """Returns country ISO code given a country""" | ||
| if not isinstance(attribute, str): | ||
| return attribute | ||
| try: | ||
| return int(countries.get(attribute).numeric) | ||
| except: | ||
| return attribute | ||
|
|
||
| def get_geographical_name(self, feature): | ||
| """Returns geographical location label based on secondary feature.""" | ||
| maps = {"state": "United States", "country": "World"} | ||
| return maps[feature] | ||
|
|
||
| def encode_color(self): | ||
| # Setting tooltip as non-null | ||
| self.chart = self.chart.configure_mark(tooltip=alt.TooltipContent("encoding")) | ||
| self.code += f"""chart = chart.configure_mark(tooltip=alt.TooltipContent('encoding'))""" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -8,3 +8,5 @@ matplotlib>=3.0.0 | |
| # psycopg2>=2.8.5 | ||
| # psycopg2-binary>=2.8.5 | ||
| lux-widget>=0.1.4 | ||
| us | ||
| iso3166 | ||
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