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import streamlit as st
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import pandas as pd
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"""
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Result table of the Single Project Matching
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"""
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def show_single_table(selected_project_index, projects_df, result_df):
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"""
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TODO: Add this to preprocessing
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"""
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result_df['crs_3_code_list'] = result_df['crs_3_name'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";")[:-1])
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)
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result_df['crs_5_code_list'] = result_df['crs_5_name'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";")[:-1])
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)
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result_df['sdg_list'] = result_df['sgd_pred_code'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";"))
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)
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result_df['orga_abbreviation'] = result_df['orga_abbreviation'].str.upper()
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result_df['country_flag'] = result_df.apply(
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lambda row: None if pd.isna(row['country_name']) else row['country_flag'],
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axis=1
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)
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sel_p_row = projects_df.iloc[[selected_project_index]]
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sel_p_row['crs_3_code_list'] = sel_p_row['crs_3_name'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";")[:-1])
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)
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sel_p_row['crs_5_code_list'] = sel_p_row['crs_5_name'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";")[:-1])
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)
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sel_p_row['sdg_list'] = sel_p_row['sgd_pred_code'].apply(
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lambda x: [""] if x is None else (str(x).split(";")[:-1] if str(x).endswith(";") else str(x).split(";"))
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)
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sel_p_row['orga_abbreviation'] = sel_p_row['orga_abbreviation'].str.upper()
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st.subheader("Reference Project")
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st.dataframe(
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sel_p_row[["iati_id", "title_main", "orga_abbreviation", "description_main", "country_name", "country_flag", "sdg_list", "crs_3_code_list", "crs_5_code_list", "Project Link"]],
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use_container_width = True,
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height = 35 + 35 * len(sel_p_row),
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column_config={
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"iati_id": st.column_config.TextColumn(
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"IATI ID",
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help="IATI Project ID",
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disabled=True,
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width="small"
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),
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"orga_abbreviation": st.column_config.TextColumn(
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"Organization",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="small"
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),
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"title_main": st.column_config.TextColumn(
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"Title",
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help="If title not in English, title in other language provided",
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disabled=True,
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width="large"
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),
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"description_main": st.column_config.TextColumn(
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"Description",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="large"
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),
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"country_name": st.column_config.TextColumn(
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"Country",
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help="Country of project",
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disabled=True,
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width="small"
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),
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"country_flag": st.column_config.ImageColumn(
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"Flag",
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help="country flag",
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width="small"
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),
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"sdg_list": st.column_config.ListColumn(
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"SDG Prediction",
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help="Prediction of SDG's",
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width="small"
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),
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"crs_3_code_list": st.column_config.ListColumn(
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"CRS 3",
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help="CRS 3 code given by organization",
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width="medium"
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),
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"crs_5_code_list": st.column_config.ListColumn(
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"CRS 5",
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help="CRS 5 code given by organization",
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width="medium"
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),
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"Project Link": st.column_config.TextColumn(
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"Project Link",
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help="Link to the project",
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disabled=True,
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width="small"
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),
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},
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hide_index=True,
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)
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if len(result_df) == 0:
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st.write("No results found!")
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else:
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result_df = result_df.reset_index(drop=True)
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result_df['similarity'] = (result_df['similarity'] * 100).round(4)
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st.write("----------------------")
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st.subheader("Similar Projects")
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st.dataframe(
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result_df[["similarity", "iati_id", "title_main", "orga_abbreviation", "description_main", "country_name", "country_flag", "sdg_list", "crs_3_code_list", "crs_5_code_list", "Project Link"]],
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use_container_width = True,
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height = 35 + 35 * len(result_df),
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column_config={
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"similarity": st.column_config.ProgressColumn(
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"Similarity",
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help="Similarity",
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format=" %f %%",
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min_value=0,
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max_value=100,
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),
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"iati_id": st.column_config.TextColumn(
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"IATI ID",
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help="IATI Project ID",
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disabled=True,
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width="small"
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),
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"orga_abbreviation": st.column_config.TextColumn(
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"Organization",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="small"
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),
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"title_main": st.column_config.TextColumn(
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"Title",
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help="If title not in English, title in other language provided",
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disabled=True,
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width="large"
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),
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"description_main": st.column_config.TextColumn(
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"Description",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="large"
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),
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"country_name": st.column_config.TextColumn(
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"Country",
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help="Country of project",
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disabled=True,
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width="small"
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),
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"country_flag": st.column_config.ImageColumn(
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"Flag",
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help="country flag",
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width="small"
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),
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"sdg_list": st.column_config.ListColumn(
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"SDG Prediction",
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help="Prediction of SDG's",
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width="small"
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),
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"crs_3_code_list": st.column_config.ListColumn(
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"CRS 3",
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help="CRS 3 code given by organization",
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width="medium"
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),
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"crs_5_code_list": st.column_config.ListColumn(
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"CRS 5",
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help="CRS 5 code given by organization",
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width="medium"
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),
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},
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hide_index=True,
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)
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