test: columns

pages/1_📈_Plotting.py

@@ -45,6 +45,8 @@ if not df_base.empty:
             st.caption(f"Selected number of samples: {n_plot}")
             df_plot = [ini_list.strip('][').split(',') for ini_list in df_plot[feature]]
             df_plot = pd.DataFrame(df_plot)
+            df_plot.columns = [str(column) for column in range(df_plot.columns)]
+            st.caption(f"Columns of df_plot: {list(df_plot.columns)}")
             st.caption(f"Axes of df_plot: {df_plot.axes}")
             if 'df_plot' not in st.session_state:
                 st.session_state['df_plot'] = df_plot
@@ -57,9 +59,9 @@ if 'df_plot' in list(st.session_state.keys()):
         st.caption("Your visualization:")
         st.caption("df_plot:")
         st.dataframe(st.session_state.df_plot)
-        st.line_chart(st.session_state.df_plot, y=[int(v) for v in list(df_plot.columns)])
+        st.line_chart(st.session_state.df_plot, y=list(df_plot.columns))
         st.caption("df_plot transposed:")
         st.dataframe(st.session_state.df_plot.transpose())
-        st.line_chart(st.session_state.df_plot.transpose(), y=[int(v) for v in list(df_plot.transpose().columns)])
+        st.line_chart(st.session_state.df_plot.transpose(), y=list(df_plot.transpose().columns))
 elif df_base.empty and file:
     st.warning("Consider running outlier detection to clean your data!", icon="⚠️")