Add initial transformed_data tests

tests/test_transformed_data.py

@@ -0,0 +1,102 @@
+from altair.utils.execeval import eval_block
+from tests import examples_methods_syntax
+import pkgutil
+import pytest
+
+
+@pytest.mark.parametrize("filename,rows,cols", [
+    ("annual_weather_heatmap.py", 366, ["monthdate_date_end", "max_temp_max"]),
+    ("anscombe_plot.py", 44, ["Series", "X", "Y"]),
+    ("bar_chart_sorted.py", 6, ["site", "sum_yield"]),
+    ("bar_chart_trellis_compact.py", 27, ["p", "p_end"]),
+    ("beckers_barley_trellis_plot.py", 120, ["year", "site"]),
+    ("beckers_barley_wrapped_facet.py", 120, ["site", "median_yield"]),
+    ("bump_chart.py", 100, ["rank", "yearmonth_date"]),
+    ("comet_chart.py", 120, ["variety", "delta"]),
+    ("connected_scatterplot.py", 55, ["miles", "gas"]),
+    ("diverging_stacked_bar_chart.py", 40, ["value", "percentage_start"]),
+    ("donut_chart.py", 6, ["value_start", "value_end"]),
+    ("gapminder_bubble_plot.py", 187, ["income", "population"]),
+    ("grouped_bar_chart2.py", 9, ["Group", "Value_start"]),
+    ("hexbins.py", 84, ["xFeaturePos", "mean_temp_max"]),
+    ("histogram_heatmap.py", 378, ["bin_maxbins_40_Rotten_Tomatoes_Rating", "__count"]),
+    ("histogram_scatterplot.py", 64, ["bin_maxbins_10_Rotten_Tomatoes_Rating", "__count"]),
+    ("interactive_legend.py", 1708, ["sum_count_start", "series"]),
+    ("iowa_electricity.py", 51, ["net_generation_start", "year"]),
+    ("isotype.py", 37, ["animal", "x"]),
+    ("isotype_grid.py", 100, ["row", "col"]),
+    ("lasagna_plot.py", 492, ["yearmonthdate_date", "sum_price"]),
+    ("layered_area_chart.py", 51, ["source", "net_generation"]),
+    ("layered_bar_chart.py", 51, ["source", "net_generation"]),
+    ("layered_histogram.py", 113, ["bin_maxbins_100_Measurement"]),
+    ("line_chart_with_cumsum.py", 52, ["cumulative_wheat"]),
+    ("line_percent.py", 30, ["sex", "perc"]),
+    ("line_with_log_scale.py", 15, ["year", "sum_people"]),
+    ("multifeature_scatter_plot.py", 150, ["petalWidth", "species"]),
+    ("natural_disasters.py", 686, ["Deaths", "Year"]),
+    ("normalized_stacked_area_chart.py", 51, ["source", "net_generation_start"]),
+    ("normalized_stacked_bar_chart.py", 60, ["site", "sum_yield_start"]),
+    ("parallel_coordinates.py", 600, ["key", "value"]),
+    ("percentage_of_total.py", 5, ["PercentOfTotal", "TotalTime"]),
+    ("pie_chart.py", 6, ["category", "value_start"]),
+    ("pyramid.py", 3, ["category", "value_start"]),
+    ("stacked_bar_chart_sorted_segments.py", 60, ["variety", "site"]),
+    ("stem_and_leaf.py", 100, ["stem", "leaf"]),
+    ("streamgraph.py", 1708, ["series", "sum_count"]),
+    ("top_k_items.py", 10, ["rank", "IMDB_Rating_start"]),
+    ("top_k_letters.py", 9, ["rank", "letters"]),
+    ("top_k_with_others.py", 10, ["ranked_director", "mean_aggregate_gross"]),
+    ("trellis_area_sort_array.py", 492, ["date", "price"]),
+    ("trellis_histogram.py", 20, ["Origin", "__count"]),
+    ("us_population_over_time.py", 38, ["sex", "people_start"]),
+    ("us_population_over_time_facet.py", 285, ["year", "sum_people"]),
+    ("wilkinson-dot-plot.py", 21, ["data", "id"]),
+    ("window_rank.py", 12, ["team", "diff"]),
+])
+def test_primitive_chart_examples(filename, rows, cols):
+    source = pkgutil.get_data(examples_methods_syntax.__name__, filename)
+    chart = eval_block(source)
+    df = chart.transformed_data()
+    assert len(df) == rows
+    assert set(cols).issubset(set(df.columns))
+
+
+@pytest.mark.parametrize("filename,all_rows,all_cols", [
+    ("errorbars_with_std.py", [10, 10], [["upper_yield"], ["extent_yield"]]),
+    ("candlestick_chart.py", [44, 44], [["low"], ["close"]]),
+    ("co2_concentration.py", [713, 7, 7], [["first_date"], ["scaled_date"], ["end"]]),
+    ("falkensee.py", [2, 38, 38], [["event"], ["population"], ["population"]]),
+    ("heat_lane.py", [10, 10], [["bin_count_start"], ["y2"]]),
+    ("histogram_responsive.py", [20, 20], [["__count"], ["__count"]]),
+    ("histogram_with_a_global_mean_overlay.py", [9, 1], [["__count"], ["mean_IMDB_Rating"]]),
+    ("horizon_graph.py", [20, 20], [["x"], ["ny"]]),
+    ("interactive_cross_highlight.py", [64, 64, 13], [["__count"], ["__count"], ["Major_Genre"]]),
+    ("interval_selection.py", [123, 123], [["price_start"], ["date"]]),
+    ("layered_chart_with_dual_axis.py", [12, 12], [["month_date"], ["average_precipitation"]]),
+    ("layered_heatmap_text.py", [9, 9], [["Cylinders"], ["mean_horsepower"]]),
+    ("multiline_highlight.py", [560, 560], [["price"], ["date"]]),
+    ("multiline_tooltip.py", [300, 300, 300, 0, 300], [["x"], ["y"], ["y"], ["x"], ["x"]]),
+    ("pie_chart_with_labels.py", [6, 6], [["category"], ["value"]]),
+    ("radial_chart.py", [6, 6], [["values"], ["values_start"]]),
+    ("scatter_linked_table.py", [392, 14, 14, 14], [["Year"], ["Year"], ["Year"], ["Year"]]),
+    ("scatter_marginal_hist.py", [34, 150, 27], [["__count"], ["species"], ["__count"]]),
+    ("scatter_with_layered_histogram.py", [2, 19], [["gender"], ["__count"]]),
+    ("scatter_with_minimap.py", [1461, 1461], [["date"], ["date"]]),
+    ("scatter_with_rolling_mean.py", [1461, 1461], [["date"], ["rolling_mean"]]),
+    ("seattle_weather_interactive.py", [1461, 5], [["date"], ["__count"]]),
+    ("select_detail.py", [20, 1000], [["id"], ["x"]]),
+    ("simple_scatter_with_errorbars.py", [5, 5], [["x"], ["upper_ymin"]]),
+    ("stacked_bar_chart_with_text.py", [60, 60], [["site"], ["site"]]),
+    ("us_employment.py", [120, 1, 2], [["month"], ["president"], ["president"]]),
+    ("us_population_pyramid_over_time.py", [19, 38, 19], [["gender"], ["year"], ["gender"]]),
+])
+def test_compound_chart_examples(filename, all_rows, all_cols):
+    source = pkgutil.get_data(examples_methods_syntax.__name__, filename)
+    chart = eval_block(source)
+    print(chart)
+
+    dfs = chart.transformed_data()
+    assert len(dfs) == len(all_rows)
+    for df, rows, cols in zip(dfs, all_rows, all_cols):
+        assert len(df) == rows
+        assert set(cols).issubset(set(df.columns))