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import streamlit as st
import pandas as pd
def show_table(p1_df, p2_df):
st.write("------------------")
p1_df = p1_df.reset_index(drop=True)
p2_df = p2_df.reset_index(drop=True)
for i in range(len(p1_df) - 1, -1, -2):
match_df = pd.DataFrame()
row_from_p1 = p1_df.iloc[[i]]
row_from_p2 = p2_df.iloc[[i]]
# Correctly append rows to match_df
match_df = pd.concat([row_from_p1, row_from_p2], ignore_index=True)
st.dataframe(
match_df[["similarity", "iati_id", "title_main", "orga_abbreviation", "client", "description_main", "country", "sgd_pred_code", "crs_3_code", "crs_5_code"]],
use_container_width = True,
height = 35 + 35 * len(match_df),
column_config={
"similarity": st.column_config.TextColumn(
"Similarity",
help="simialrity",
disabled=True
),
"iati_id": st.column_config.TextColumn(
"IATI ID",
help="IATI Project ID",
disabled=True
),
"orga_abbreviation": st.column_config.TextColumn(
"Organization",
help="If description not in English, description in other language provided",
disabled=True
),
"client": st.column_config.TextColumn(
"Client",
help="Client organization of customer",
disabled=True
),
"title_main": st.column_config.TextColumn(
"Title",
help="If title not in English, title in other language provided",
disabled=True
),
"description_main": st.column_config.TextColumn(
"Description",
help="If description not in English, description in other language provided",
disabled=True
),
"country": st.column_config.TextColumn(
"Country",
help="Country of project",
disabled=True
),
"sgd_pred_code": st.column_config.TextColumn(
"SDG Prediction",
help="Prediction of SDG's",
disabled=True
),
"crs_3_code": st.column_config.TextColumn(
"CRS 3",
help="CRS 3 code given by organization",
disabled=True
),
"crs_5_code": st.column_config.TextColumn(
"CRS 5",
help="CRS 5 code given by organization",
disabled=True
),
},
hide_index=True,
)
st.write("------------------") |