diff --git a/src/plots.py b/src/plots.py
index f9d36c1..c3f3a86 100644
--- a/src/plots.py
+++ b/src/plots.py
@@ -45,9 +45,9 @@ def plot_scatter():
         fig, ax = plt.subplots()
 
         ax.scatter(
-            adata.obs[x_col],
-            adata.obs[y_col],
-            c=adata.obs[color_col],
+            adata.obs[x_col].astype(float),
+            adata.obs[y_col].astype(float),
+            c=adata.obs[color_col].astype(float),
             s=dot_size,
             cmap="viridis",
         )
@@ -133,10 +133,12 @@ def plot_histograms():
 
         return fig
 
+    @output
     @render.text
     def n_cells():
         adata = _adata.get()
 
         if adata is not None:
-            n_cells = adata.n_obs
+            n_cells = int(adata.n_obs)
+            print(type(n_cells))
             return f"{n_cells} cells pass the current filtering thresholds"
diff --git a/src/sliders.py b/src/sliders.py
index 77c22a2..a4baa42 100644
--- a/src/sliders.py
+++ b/src/sliders.py
@@ -39,7 +39,7 @@ def slider_sample():
         if adata is None:
             return
 
-        n_obs = adata.n_obs
+        n_obs = int(adata.n_obs)
         return ui.input_slider(
             "random_sample_size",
             "Random sample size",
@@ -120,9 +120,9 @@ def slider_filters():
                 absolute = ui.input_slider(
                     f"{col}_absolute",
                     "Absolute value",
-                    distributions[col]["min"],
-                    distributions[col]["max"],
-                    [distributions[col]["min"], distributions[col]["max"]],
+                    float(distributions[col]["min"]),
+                    float(distributions[col]["max"]),
+                    [float(distributions[col]["min"]), float(distributions[col]["max"])],
                 )
                 panel = ui.accordion_panel(pretty_name, mads, absolute)
                 panels.append(panel)