Update dash_plotly_QC_scRNA.py

dash_plotly_QC_scRNA.py

@@ -396,12 +396,18 @@ def update_graph_and_pie_chart(batch_chosen, s_chosen, g2m_chosen, condition1_ch
     # Melt wide format DataFrame into long format
     # Specify batch column as string type and gene columns as float type
     dff_pre = dff.select(["batch","Cdc45","Mcm5"])
+
+    #cols_to_cast = ["Cdc45", "Mcm5", "batch"]  # add more column names here as needed
+
+    # Dynamically select and cast the specified columns to f64, except for "batch" which is cast to Utf8
+    #dff_pre = dff.select([pl.col(c).cast(pl.Float64) if c != "batch" else pl.col(c).cast(pl.Utf8) for c in dff.columns])
+
     
     # Melt wide format DataFrame into long format
-    dff_long = df.melt(id_vars="Region", variable_name="Gene", value_name="Expression")
+    dff_long = dff_pre.melt(id_vars="batch", variable_name="Gene", value_name="Expression")
 
     # Calculate the mean expression levels for each gene in each region
-    expression_means = dff_long.group_by(["Region", "Gene"]).agg(pl.mean("Expression"))
+    expression_means = dff_long.group_by(["batch", "Gene"]).agg(pl.mean("Expression"))
     
     fig_pie = px.pie(names=labels, values=values, title=pie_title,template="seaborn")