appStore/tapp_display.py

# set path
import glob, os, sys; 
sys.path.append('../utils')

#import needed libraries
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import streamlit as st
from st_aggrid import AgGrid
import logging
logger = logging.getLogger(__name__)
from io import BytesIO
import xlsxwriter
import plotly.express as px
from pandas.api.types import (
    is_categorical_dtype,
    is_datetime64_any_dtype,
    is_numeric_dtype,
    is_object_dtype,
    is_list_like)


           
            
def targets():
    if 'key1' in st.session_state:
        df = st.session_state['key1'].copy()
        idx = df['NetzeroLabel_Score'].idxmax()
        netzero_placeholder = df.loc[idx, 'text']
        df = df.drop(df.filter(regex='Score').columns, axis=1)
        df = df[df.TargetLabel==True].reset_index(drop=True)
        df['keep'] = True
        df.drop(columns = ['ActionLabel','PolicyLabel','PlansLabel'], inplace=True)
        st.session_state['target_hits'] = df
        st.session_state['netzero'] = netzero_placeholder
    
def target_display():
    if 'key1' in st.session_state:
           
        
        hits  = st.session_state['target_hits']
        if len(hits) !=0:
            # collecting some statistics
            count_target = sum(hits['TargetLabel'] == True)
            count_ghg = sum(hits['GHGLabel'] == True)
            count_netzero = sum(hits['NetzeroLabel'] == True)
            count_nonghg = sum(hits['NonGHGLabel'] == True)
            count_mitigation = sum(hits['MitigationLabel'] == True)
            count_adaptation = sum(hits['AdaptationLabel'] == True)
            
            st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Target Related Paragraphs Statistics </h4>", unsafe_allow_html=True)
            st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\
                          .format(os.path.basename(st.session_state['filename']),
                                 len(st.session_state['key0'])))
            
            c1, c2 = st.columns([1,1])
            with c1:
                st.write('**Target Related Paragraphs**: `{}`'.format(count_target))
                st.write('**Netzero Related Paragraphs**: `{}`'.format(count_netzero))
                st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation))
            with c2:
                st.write('**GHG Target Related Paragraphs**: `{}`'.format(count_ghg))
                st.write('**NonGHG Target Related Paragraphs**: `{}`'.format(count_nonghg))
                st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation))
            #st.write('----------------')

            
            
            cols = list(hits.columns)
            sector_cols = list(set(cols) - {'TargetLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'})
            sector_cols.sort()
            hits['Sector'] = hits.apply(lambda x: [col for col in sector_cols if x[col] == True],axis=1)
            hits['Sub-Target'] = hits.apply(lambda x: [col for col in ['GHGLabel','NetzeroLabel','NonGHGLabel'] if x[col] == True ],axis=1)
            st.session_state['target_hits'] = hits[['keep','text','Sector','Sub-Target','page','MitigationLabel','AdaptationLabel']]
            placeholder= []
            for col in sector_cols:
                placeholder.append({'Sector':col,'Count':sum(hits[col] == True)})
                hits['Sector']
            sector_df = pd.DataFrame.from_dict(placeholder)
            fig = px.bar(sector_df, x='Sector', y='Count')
            st.plotly_chart(fig,use_container_width= True)
            st.write('---------------------------')
            st.write('Explore the data')    
            
            #st.dataframe(hits[['text','page','keep','MitigationLabel','AdaptationLabel','Sector','Sub-Target',]])
        else:
            st.info("🤔 No Targets Found")



def actions():
    if 'key1' in st.session_state:
        df = st.session_state['key1'].copy()
        df = df.drop(df.filter(regex='Score').columns, axis=1)
        df = df[df.ActionLabel==True].reset_index(drop=True)
        df['keep'] = True
        df.drop(columns = ['TargetLabel','PolicyLabel','PlansLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True)
        st.session_state['action_hits'] = df
    
def action_display():
    if 'key1' in st.session_state: 
        
        hits  = st.session_state['action_hits']
        if len(hits) !=0:
            # collecting some statistics
            count_action = sum(hits['ActionLabel'] == True)
            count_mitigation = sum(hits['MitigationLabel'] == True)
            count_adaptation = sum(hits['AdaptationLabel'] == True)
            
            st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Action Related Paragraphs Statistics </h4>", unsafe_allow_html=True)
            st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\
                          .format(os.path.basename(st.session_state['filename']),
                                 len(st.session_state['key0'])))
            c1, c2 = st.columns([1,1])
            with c1:
                st.write('**Action Related Paragraphs**: `{}`'.format(count_action))
                st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation))
            with c2:
                st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation))
            #st.write('----------------')
            #st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Action Related Paragraphs Count </h4>", unsafe_allow_html=True)
            cols = list(hits.columns)
            sector_cols = list(set(cols) - {'ActionLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'})
            sector_cols.sort()
            hits['Sector'] = hits.apply(lambda x: [col for col in sector_cols if x[col] == True],axis=1)
            #hits['Sub-Target'] = hits.apply(lambda x: [col for col in ['GHGLabel','NetzeroLabel','NonGHGLabel'] if x[col] == True ],axis=1)
            placeholder= []
            for col in sector_cols:
                placeholder.append({'Sector':col,'Count':sum(hits[col] == True)})
            sector_df = pd.DataFrame.from_dict(placeholder)
            fig = px.bar(sector_df, x='Sector', y='Count')
            st.plotly_chart(fig,use_container_width= True)
            st.write('------------------------')
            st.write('Explore the data')
                
            st.dataframe(hits[['text','page','keep','MitigationLabel','AdaptationLabel','Sector']])
        else:
            st.info("🤔 No Actions Found")



def policy():
    if 'key1' in st.session_state:
        df = st.session_state['key1'].copy()
        df = df.drop(df.filter(regex='Score').columns, axis=1)
        df = df[df.PolicyLabel==True].reset_index(drop=True)
        df['keep'] = True
        df.drop(columns = ['TargetLabel','ActionLabel','PlansLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True)
        st.session_state['policy_hits'] = df
    
def policy_display():
    if 'key1' in st.session_state:
   
        
        hits  = st.session_state['policy_hits']
        if len(hits) !=0:
            # collecting some statistics
            count_action = sum(hits['PolicyLabel'] == True)
            count_mitigation = sum(hits['MitigationLabel'] == True)
            count_adaptation = sum(hits['AdaptationLabel'] == True)
            st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Policy Related Paragraphs Statistics </h4>", unsafe_allow_html=True)
            st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\
                          .format(os.path.basename(st.session_state['filename']),
                                 len(st.session_state['key0'])))
            c1, c2 = st.columns([1,1])
            with c1:
                st.write('**Policy Related Paragraphs**: `{}`'.format(count_action))
                st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation))
            with c2:
                st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation))
            #st.write('----------------')
            
            cols = list(hits.columns)
            sector_cols = list(set(cols) - {'PolicyLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'})
            sector_cols.sort()
            hits['Sector'] = hits.apply(lambda x: [col for col in sector_cols if x[col] == True],axis=1)
            placeholder= []
            for col in sector_cols:
                placeholder.append({'Sector':col,'Count':sum(hits[col] == True)})
            sector_df = pd.DataFrame.from_dict(placeholder)
            fig = px.bar(sector_df, x='Sector', y='Count')
            st.plotly_chart(fig,use_container_width= True)
            st.write('-------------------')
            st.write('Explore the data')
            st.dataframe(hits[['text','page','keep','MitigationLabel','AdaptationLabel','Sector']])
        else:
            st.info("🤔 No Policy Found")

def plans():
    if 'key1' in st.session_state:
        df = st.session_state['key1'].copy()
        df = df.drop(df.filter(regex='Score').columns, axis=1)
        df = df[df.PlansLabel==True].reset_index(drop=True)
        df['keep'] = True
        df.drop(columns = ['TargetLabel','PolicyLabel','ActionLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True)
        st.session_state['plan_hits'] = df
    
def plans_display():
    if 'key1' in st.session_state:  
        
        hits  = st.session_state['plan_hits']
        if len(hits) !=0:
            # collecting some statistics
            count_action = sum(hits['PlansLabel'] == True)
            count_mitigation = sum(hits['MitigationLabel'] == True)
            count_adaptation = sum(hits['AdaptationLabel'] == True)

            st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Plans Related Paragraphs Statistics </h4>", unsafe_allow_html=True)
            st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\
                          .format(os.path.basename(st.session_state['filename']),
                                 len(st.session_state['key0']))) 
            c1, c2 = st.columns([1,1])
            with c1:
                st.write('**Plans Related Paragraphs**: `{}`'.format(count_action))
                st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation))
            with c2:
                st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation))
            #st.write('----------------')
            
            cols = list(hits.columns)
            sector_cols = list(set(cols) - {'PlansLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'})
            sector_cols.sort()
            hits['Sector'] = hits.apply(lambda x: [col for col in sector_cols if x[col] == True],axis=1)
            placeholder= []
            for col in sector_cols:
                placeholder.append({'Sector':col,'Count':sum(hits[col] == True)})
            sector_df = pd.DataFrame.from_dict(placeholder)
            fig = px.bar(sector_df, x='Sector', y='Count')
            st.plotly_chart(fig,use_container_width= True)
            st.write('---------------')
            st.write('Explore the data')
                
            st.dataframe(hits[['text','page','keep','MitigationLabel','AdaptationLabel','Sector']])
        else:
            st.info("🤔 No Plans Found")