beautify boxplot

src/main.py

@@ -229,7 +229,7 @@ def replace_cryptic_names(columns):
     return new_columns
 
 
-def translate_scales(scales):
+def translate_scales(scales, short=False):
     scales = list(scales)
     result = scales
     translations = {
@@ -254,6 +254,29 @@ def translate_scales(scales):
         'Akustik': "Acoustics",
         'Inhaltsseriosität': "Trustworth-\niness of \nContent"
     }
+    if short:
+        translations = {
+            'Inhaltsqualität': "Qua",
+            'Anpassbarkeit': "Ada",
+            'Durchschaubarkeit': "Dep",
+            'Effizienz': "Eff",
+            'Immersion': "Imm",
+            'Intuitive Bedienung': "Int",
+            'Nützlichkeit': "Use",
+            'Originalität': "Nov",
+            'visuelle Ästhetik': "Aes",
+            'Identität': "Id",
+            'Steuerbarkeit': "Cla",
+            'Stimulation': "Sti",
+            'Übersichtlichkeit': "Per",
+            'Verbundenheit': "Atm",
+            'Vertrauen': "Tru",
+            'Wertigkeit': "Val",
+            'Attraktivität': "Att",
+            'Haptik': "Hap",
+            'Akustik': "Aco",
+            'Inhaltsseriosität': "ToC"
+        }
     for i in range(len(scales)):
         result[i] = translations[scales[i]]
     return result
@@ -351,20 +374,24 @@ class Plotter:
         # make a nice plot surrounding
         sns.set_theme(style="whitegrid", palette="pastel")
         fig = plt.figure()
-        fig.suptitle(category_title.value, fontsize=14, fontweight='bold', y=0.1)
+        fig.suptitle(category_title.value, fontsize=14, fontweight='bold', y=0.09)
+        fig.set_figheight(6.0)
+
 
         # plot the plot
         boxprops = dict(linestyle='-', facecolor='k', linewidth=3, color='k')
         medianprops = dict(linestyle='-', linewidth=3, color='b')
         meanprops = dict(color='b')
         ax = fig.add_subplot(111)
+        ax.axhspan(4, 7, facecolor='green', alpha=0.2)
+        ax.axhspan(1, 4, facecolor='red', alpha=0.2)
         ax.grid(axis='y')
         ax.boxplot(df_category_area, showmeans=True, showfliers=True, patch_artist=True,
                    boxprops=boxprops, medianprops=medianprops, meanprops=meanprops)
         ax.set_ylim(0.5, 7.5)
 
         ax.set_xticks([tick + 1 for tick in range(len(df_category_area.columns))],
-                      labels=translate_scales(df_category_area.columns), rotation=0)
+                      labels=translate_scales(df_category_area.columns, True), rotation=0)
         ax.xaxis.set_label_position('top')
         ax.xaxis.tick_top()
 
@@ -489,11 +516,11 @@ if __name__ == '__main__':
     # plotter.plot_groups(variables.get_groups())
     # plotter.plot_sex()
     # plotter.plot_faculty()
-    example = Categories.VR
-    # plotter.plot_item(example, 'top')
-    plotter.plot_item(example, 'mid')
-    # plotter.plot_item(example, 'low')
-    plotter.plot_boxes(example, 6)
+    for example in Categories:
+        # plotter.plot_item(example, 'top')
+        plotter.plot_item(example, 'mid')
+        # plotter.plot_item(example, 'low')
+        plotter.plot_boxes(example, 6)
     print(statistics.calc_corr())
     print(statistics.similarity_by_ranked_scales(rankings.get_all_rankings()))
     print(time.strftime('%M:%S', time.gmtime(statistics.mean_time())))