File size: 11,760 Bytes
91f38ae
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
db65cd7
91f38ae
 
 
 
 
9a8eaaf
91f38ae
 
 
 
 
 
 
 
b805749
 
91f38ae
0193c81
9a8eaaf
 
 
0193c81
91f38ae
 
 
 
3489bcc
91f38ae
 
 
3489bcc
9a8eaaf
533a3db
0193c81
533a3db
db65cd7
fbab372
3277cac
d9f847a
 
9203fec
db65cd7
 
0dde0c7
040e14b
db65cd7
 
 
0193c81
 
9203fec
 
91f38ae
 
b805749
 
 
533a3db
b805749
 
 
533a3db
b805749
533a3db
 
b805749
533a3db
9a8eaaf
b805749
533a3db
b805749
 
533a3db
b805749
 
 
9a8eaaf
 
 
 
b805749
 
533a3db
b805749
 
 
9a8eaaf
 
b805749
533a3db
264365c
 
 
b805749
 
 
 
 
 
9a8eaaf
 
b805749
264365c
b805749
533a3db
b805749
 
bc992a7
 
 
 
 
 
 
 
 
 
 
 
9a8eaaf
bc992a7
 
 
 
 
 
 
9a8eaaf
 
 
 
bc992a7
 
 
 
 
 
9a8eaaf
 
bc992a7
 
264365c
 
bc992a7
 
 
 
 
 
9a8eaaf
 
264365c
bc992a7
 
 
 
 
 
 
 
 
 
 
 
 
9a8eaaf
bc992a7
 
 
 
 
 
 
 
9a8eaaf
 
 
 
bc992a7
 
 
 
 
 
9a8eaaf
 
bc992a7
34cd950
264365c
 
bc992a7
 
 
 
 
 
9a8eaaf
 
bc992a7
264365c
bc992a7
 
 
b805749
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
# 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")