Arts-of-coding commited on
Commit
cd21e59
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1 Parent(s): cb0f528

Update dash_plotly_QC_scRNA.py

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Files changed (1) hide show
  1. dash_plotly_QC_scRNA.py +23 -17
dash_plotly_QC_scRNA.py CHANGED
@@ -54,32 +54,38 @@ external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
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  app = dash.Dash(__name__, external_stylesheets=external_stylesheets) #, requests_pathname_prefix='/dashboard1/'
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  tab0_content = html.Div([
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- html.Label("Dataset chosen"),
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  dcc.Dropdown(id='dpdn1', value="d1011/10xflexd1011_umap_clusres", multi=False,
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  options=["corg/10xflexcorg_umap_clusres","d1011/10xflexd1011_umap_clusres"])
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  ])
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  @app.callback(
 
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  Input(component_id='dpdn1', component_property='value')
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  )
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-
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- def update_dataset(dataset_chosen): #batch_chosen,
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  filepath = f"az://data10xflex/{dataset_chosen}"
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- df = pl.read_parquet(filepath,storage_options=storage_options)
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- return df
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- min_value = df[col_features].min()
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- max_value = df[col_features].max()
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-
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- min_value_2 = df[col_counts].min()
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- min_value_2 = round(min_value_2)
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- max_value_2 = df[col_counts].max()
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- max_value_2 = round(max_value_2)
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-
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- min_value_3 = df[col_mt].min()
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- min_value_3 = round(min_value_3, 1)
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- max_value_3 = df[col_mt].max()
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- max_value_3 = round(max_value_3, 1)
 
 
 
 
 
 
 
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  # Loads in the conditions specified in the yaml file
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  app = dash.Dash(__name__, external_stylesheets=external_stylesheets) #, requests_pathname_prefix='/dashboard1/'
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  tab0_content = html.Div([
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+ html.Label("Dataset chosen"),
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  dcc.Dropdown(id='dpdn1', value="d1011/10xflexd1011_umap_clusres", multi=False,
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  options=["corg/10xflexcorg_umap_clusres","d1011/10xflexd1011_umap_clusres"])
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  ])
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  @app.callback(
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+ Output('dynamic-table', 'children'),
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  Input(component_id='dpdn1', component_property='value')
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  )
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+ def update_table(dataset_chosen):
 
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  filepath = f"az://data10xflex/{dataset_chosen}"
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+ df = pl.read_parquet(filepath, storage_options=storage_options)
 
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+ min_value = df[col_features].min().item()
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+ max_value = df[col_features].max().item()
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+
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+ min_value_2 = round(df[col_counts].min())
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+ max_value_2 = round(df[col_counts].max())
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+
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+ min_value_3 = round(df[col_mt].min(), 1)
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+ max_value_3 = round(df[col_mt].max(), 1)
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+
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+ # Create other visualizations or perform calculations below using the updated df variable
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+
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+ return [
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+ html.H5(f'Minimum Value - {col_features}: {min_value}'),
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+ html.H5(f'Maximum Value - {col_features}: {max_value}'),
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+ html.H5(f'Minimum Value - {col_counts}: {min_value_2}'),
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+ html.H5(f'Maximum Value - {col_counts}: {max_value_2}'),
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+ html.H5(f'Minimum Value - {col_mt}: {min_value_3}'),
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+ html.H5(f'Maximum Value - {col_mt}: {max_value_3}'),
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+ ]
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  # Loads in the conditions specified in the yaml file
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