import streamlit as st import pandas as pd def show_multi_table(p1_df, p2_df): st.write("------------------") p1_df = p1_df.reset_index(drop=True) p2_df = p2_df.reset_index(drop=True) actual_ind = 0 for i in range(len(p1_df) - 1, -1, -2): # stepsize because project matchs in both ways and it should only display a match one time actual_ind += 1 match_df = pd.DataFrame() row_from_p1 = p1_df.iloc[[i]] row_from_p2 = p2_df.iloc[[i]] # INTEGRATE IN PREPROCESSING !!! # transform strings to list try: row_from_p1["crs_3_code_list"] = [row_from_p1['crs_3_name'].item().split(";")[:-1]] row_from_p2["crs_3_code_list"] = [row_from_p2['crs_3_name'].item().split(";")[:-1]] except: row_from_p1["crs_3_code_list"] = [""] row_from_p2["crs_3_code_list"] = [""] try: row_from_p1["crs_5_code_list"] = [row_from_p1['crs_5_name'].item().split(";")[:-1]] row_from_p2["crs_5_code_list"] = [row_from_p2['crs_5_name'].item().split(";")[:-1]] except: row_from_p1["crs_5_code_list"] = [""] row_from_p2["crs_5_code_list"] = [""] row_from_p1["sdg_list"] = [row_from_p1['sgd_pred_code'].item()] row_from_p2["sdg_list"] = [row_from_p2['sgd_pred_code'].item()] try: row_from_p1["flag"] = f"https://flagicons.lipis.dev/flags/4x3/{row_from_p1['country'].item()[:2].lower()}.svg" row_from_p2["flag"] = f"https://flagicons.lipis.dev/flags/4x3/{row_from_p2['country'].item()[:2].lower()}.svg" except: row_from_p1["flag"] = "https://flagicons.lipis.dev/flags/4x3/xx.svg" row_from_p2["flag"] = "https://flagicons.lipis.dev/flags/4x3/xx.svg" #print(row_from_p1["flag"].item()) # Correctly append rows to match_df #st.subheader(f"#{actual_ind}") #st.caption(f"Similarity: {round(row_from_p1['similarity'].item(), 4) * 100}%") match_df = pd.concat([row_from_p1, row_from_p2], ignore_index=True) col1, col2 = st.columns([1, 12]) with col1: # remove arrow from standart st.metric() st.write( """ """, unsafe_allow_html=True, ) st.metric(label="Match", value=f"{actual_ind}", delta=f"~ {str(round(row_from_p1['similarity'].item(), 5) * 100)[:4]} %") with col2: st.write(" ") st.dataframe( match_df[["iati_id", "title_main", "orga_abbreviation", "client", "description_main", "country_name", "flag", "sdg_list", "crs_3_code_list", "crs_5_code_list"]], use_container_width = True, height = 35 + 35 * len(match_df), column_config={ "iati_id": st.column_config.TextColumn( "IATI ID", help="IATI Project ID", disabled=True, width="small" ), "orga_abbreviation": st.column_config.TextColumn( "Organization", help="If description not in English, description in other language provided", disabled=True, width="small" ), "client": st.column_config.TextColumn( "Client", help="Client organization of customer", disabled=True, width="small" ), "title_main": st.column_config.TextColumn( "Title", help="If title not in English, title in other language provided", disabled=True, width="large" ), "description_main": st.column_config.TextColumn( "Description", help="If description not in English, description in other language provided", disabled=True, width="large" ), "country_name": st.column_config.TextColumn( "Country", help="Country of project", disabled=True, width="small" ), "flag": st.column_config.ImageColumn( "Flag", help="country flag", width="small" ), "sdg_list": st.column_config.ListColumn( "SDG Prediction", help="Prediction of SDG's", width="small" ), "crs_3_code_list": st.column_config.ListColumn( "CRS 3", help="CRS 3 code given by organization", width="medium" ), "crs_5_code_list": st.column_config.ListColumn( "CRS 5", help="CRS 5 code given by organization", width="medium" ), }, hide_index=True, ) st.write("------------------")