seda url, animation basemap, and harmonize to gdf

geosnap/_data.py

@@ -193,7 +193,11 @@ def seda(
             "gcs",
             "cs",
         ], "`standardize` argument must be either 'cs' for cohort-standardized or 'gcs' for grade-cohort-standardized"
-        fn = f"seda_{level}_{pooling}_{standardize}_4.1"
+        if pooling=='poolsub':
+            fn = f"seda_{level}_{pooling}_{standardize}_4.1_corrected"
+        else:
+            fn = f"seda_{level}_{pooling}_{standardize}_4.1"
+
         local_path = pathlib.Path(self.data_dir, "seda", f"{fn}.parquet")
         remote_path = f"https://stacks.stanford.edu/file/druid:xv742vh9296/{fn}.csv"
         msg = (

geosnap/harmonize/harmonize.py

@@ -156,7 +156,7 @@ def harmonize(
     if intensive_variables is not None:
         for i in intensive_variables:
             allcols.append(i)
-   
+
     with tqdm(total=len(times), desc=f"Converting {len(times)} time periods") as pbar:
         for i in times:
             pbar.set_description(f"Harmonizing {i}")
@@ -172,10 +172,10 @@ def harmonize(
                         allocate_total=allocate_total,
                     )
                 else:
-                # if there are NaNs, tobler will raise lots of warnings, that it's filling
-                # with implicit 0s. Those warnings are superfluous most of the time
+                    # if there are NaNs, tobler will raise lots of warnings, that it's filling
+                    # with implicit 0s. Those warnings are superfluous most of the time
                     with warnings.catch_warnings():
-                        warnings.simplefilter("ignore")                 
+                        warnings.simplefilter("ignore")
                         interpolation = area_interpolate(
                             source_df,
                             target_df.copy(),
@@ -225,7 +225,8 @@ def harmonize(
             pbar.update(1)
         pbar.set_description("Complete")
         pbar.close()
-    interpolated_dfs.append(target_df[allcols].set_index(unit_index))
+    if target_year is not None:
+        interpolated_dfs.append(target_df[allcols].set_index(unit_index))
 
     harmonized_df = gpd.GeoDataFrame(pd.concat(interpolated_dfs), crs=crs)
 

geosnap/visualize/mapping.py

@@ -266,6 +266,9 @@ def plot_timeseries(
             axs.format(suptitle=column)
         else:
             axs.format(suptitle=title)
+    else:
+        if title:
+            plt.suptitle(title)
 
     if save_fig:
         f.savefig(save_fig, dpi=dpi, bbox_inches="tight")