Update app.py

app.py

@@ -5,7 +5,7 @@ import pandas as pd
 import sklearn
 import xgboost
 import shap
-import streamlit.components.v1 as components
+st.set_option('deprecation.showPyplotGlobalUse', False)
 seed=42
 
 data = pd.read_csv("annotations_dataset.csv")
@@ -70,7 +70,6 @@ if len(gene_list) > 1:
     summary_plot = shap.summary_plot(shap_values, df, show=False)
     st.caption("SHAP Summary Plot of All Input Genes")
     st.pyplot(fig=summary_plot)
-    #components.html(summary_plot, scrolling = True)
 
 else:
     pass
@@ -80,7 +79,8 @@ input_gene = st.text_input("Input individual HGNC gene:")
 df2 = df_total[df_total.index == input_gene]
 st.dataframe(df2)
 df2.drop(columns='XGB_Score', inplace=True)
-if len(input_gene) == 1:
+
+if input_gene:
     shap_values = explainer.shap_values(df2)
     shap.initjs()
     force_plot = shap.force_plot(
@@ -88,7 +88,6 @@ if len(input_gene) == 1:
     shap_values.values,
     df2, 
     show=False)
-    #components.html(force_plot,  scrolling = True)
     st.pyplot(fig=force_plot)
 else:
     pass