feat(script): Add breakdown by region visualization

scoping_review.qmd

@@ -638,6 +638,26 @@ many studies use income measurements and changes in income or income inequality
 
 {{++ TODO: describe inequality type distribution for overall dataset ++}}
 
+```{python}
+#| label: fig-region-counts
+#| fig-cap: Studies by regions analysed
+
+bib_df = (bib_df
+    .assign(
+        # create de-duplicated joins for all observations
+        region=lambda _df: _df["region"].apply(
+            lambda _cell: set([x.strip() for x in _cell.split(";")])
+        ),
+     )
+    .explode("region")
+)
+# bib_df["region"] = bib_df["region"].str.split(";").explode().str.strip()
+ax = sns.countplot(bib_df, x="region", order=bib_df["region"].value_counts().index)
+plt.setp(ax.get_xticklabels(), rotation=45, ha="right",
+         rotation_mode="anchor")
+plt.show()
+```
+
 # Synthesis of Evidence --- a multitude of lenses
 
 This section will present a synthesis of evidence from the scoping review.