Update dash_plotly_QC_scRNA.py

dash_plotly_QC_scRNA.py

@@ -47,15 +47,15 @@ filepath = f"az://{path_parquet}"
 storage_options={'account_name': AZURE_STORAGE_ACCOUNT, 'account_key': AZURE_STORAGE_ACCESS_KEY,'anon': False}
 #azfs = AzureBlobFileSystem(**storage_options )
 
+# Setup the app
+external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
+app = dash.Dash(__name__, external_stylesheets=external_stylesheets) #, requests_pathname_prefix='/dashboard1/'
+
 #df = pl.read_parquet(filepath,storage_options=storage_options)
 df = pl.DataFrame()
 #abfs = AzureBlobFileSystem(account_name=accountname,account_key=accountkey)
 #df = df.rename({"__index_level_0__": "Unnamed: 0"})
 
-# Setup the app
-external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
-app = dash.Dash(__name__, external_stylesheets=external_stylesheets) #, requests_pathname_prefix='/dashboard1/'
-
 tab0_content = html.Div([
     html.Label("Dataset chosen"),    
     dcc.Dropdown(id='dpdn1', value="d1011/10xflexd1011_umap_clusres", multi=False,
@@ -69,7 +69,7 @@ def update_dataset(dataset_chosen):
     global df
     filepath = f"az://data10xflex/{dataset_chosen}.parquet"
     df = pl.read_parquet(filepath, storage_options=storage_options)
-    return html.Pre(df.to_string())
+    return df
 
 min_value = df[col_features].min()
 max_value = df[col_features].max()