visualize difficulty/slope plots

openskistats/analyze.py

@@ -482,6 +482,7 @@ def ski_rose_the_world(min_combined_vertical: int = 10_000) -> None:
     from openskistats.plot_runs import (
         RunLatitudeBearingHistogram,
         plot_bearing_by_latitude_bin,
+        plot_run_difficulty_histograms_by_slope,
     )
     from openskistats.plot_ski_areas import (
         plot_ski_area_metric_ecdfs,
@@ -491,6 +492,12 @@ def ski_rose_the_world(min_combined_vertical: int = 10_000) -> None:
     figures["latitude_histogram"] = (
         RunLatitudeBearingHistogram().plot_latitude_histogram().draw()
     )
+    figures["slope_by_difficulty_distributions_full"] = (
+        plot_run_difficulty_histograms_by_slope(condense_difficulty=False).draw()
+    )
+    figures["slope_by_difficulty_distributions_condensed"] = (
+        plot_run_difficulty_histograms_by_slope(condense_difficulty=True).draw()
+    )
     lorenz_plot, gini_plot = plot_ski_area_metric_ecdfs()
     figures["ski_area_lorenz_curves"] = lorenz_plot.draw()
     figures["ski_area_gini_bars"] = gini_plot.draw()

openskistats/plot_runs.py

@@ -13,6 +13,7 @@
     get_cut_bearing_bins_df,
 )
 from openskistats.models import SkiRunDifficulty
+from openskistats.plot import NARROW_SPACE
 from openskistats.utils import pl_flip_bearing, pl_hemisphere
 
 
@@ -347,7 +348,7 @@ def plot_run_difficulty_histograms_by_slope(
         )
         .with_columns(
             label=pl.struct("runs_count", "combined_vertical").map_elements(
-                lambda x: f"{x['runs_count']:,} runs\n{x['combined_vertical'] / 1_000:,.0f} km vert",
+                lambda x: f"{x['runs_count']:,} runs\n{x['combined_vertical'] / 1_000:,.0f}{NARROW_SPACE}km vert",
                 return_dtype=pl.String,
             )
         )
@@ -384,12 +385,12 @@ def plot_run_difficulty_histograms_by_slope(
             breaks=np.arange(0, 90, 10),
             labels=lambda values: [f"{x:.0f}°" for x in values],
             expand=(0, 0),
-            limits=(0, 42),
         )
         + pn.scale_y_continuous(
             name="Combined Vertical (km)",
             labels=lambda values: [f"{x / 1_000:.0f}" for x in values],
         )
+        + pn.coord_cartesian(xlim=(0, 42))
         + pn.theme_bw()
         + pn.theme(
             figure_size=(3, len(colormap)),