-
Notifications
You must be signed in to change notification settings - Fork 10
/
application.py
172 lines (154 loc) · 9.31 KB
/
application.py
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
import dash_bootstrap_components as dbc
import dash_html_components as html
import dash
import plotly.express as px
import dash_core_components as dcc
from dash.dependencies import Input, Output
import plotly.express as px
import pandas as pd
import plotly.graph_objects as go
import dash_daq as daq
import ast
from assets.CustomerReviewGraphs import CustomerReviewAnalysis
#from assets.CusomerReviewKeywords import CustomerReviewKeywords
def drawTrendsBarFigure(fig=None):
if(fig is None):
fig=resp['timeseries_bar_fig']
return html.Div([dbc.Card(dbc.CardBody([html.P('Review Trends'),
dcc.Graph(figure=fig.update_layout(
template='plotly_dark',plot_bgcolor= 'rgba(0, 0, 0, 0)',paper_bgcolor= 'rgba(0, 0, 0, 0)',),config={
'displayModeBar': False})])),])
def drawRatings(fig=None):
if(fig is None):
fig=resp['rating_fig']
return html.Div([dbc.Card(dbc.CardBody([html.P('Ratings Visualization'),
dcc.Graph(figure=fig.update_layout(template='plotly_dark',plot_bgcolor= 'rgba(0, 0, 0, 0)',
paper_bgcolor= 'rgba(0, 0, 0, 0)',),
config={'displayModeBar': False
})])), ])
def drawTimeSeriesFigure(fig=None):
if(fig is None):
fig=resp['timeseries_line_fig']
return html.Div([dbc.Card(dbc.CardBody([html.P('Review Sentiments Trend'),dcc.Graph(figure=fig.update_layout(template='plotly_dark',
plot_bgcolor= 'rgba(0, 0, 0, 0)',paper_bgcolor= 'rgba(0, 0, 0, 0)',),
config={'displayModeBar': False})])), ])
def drawPieFigure(fig=None):
if(fig is None):
fig=resp['sentiment_fig']
return html.Div([dbc.Card(dbc.CardBody([html.P('Review Sentiments'),dcc.Graph(
figure=fig.update_layout(template='plotly_dark',
plot_bgcolor= 'rgba(0, 0, 0, 0)',paper_bgcolor= 'rgba(0, 0, 0, 0)',),
config={'displayModeBar': False}) ])),])
def map_sentiment(rating):
if(int(rating)==3):
return 2
elif(int(rating)<3):
return 3
else:
return 1
def drawTrendingWords(pos_keywords=None,neg_kewords=None):
return html.Div([
dbc.Card(
dbc.CardBody([html.P('Trending Keywords'),dbc.ListGroup([
dbc.ListGroupItem(pos_keywords[0], color="success"),
dbc.ListGroupItem(neg_kewords[0], color="danger"),
dbc.ListGroupItem(pos_keywords[1], color="success"),
dbc.ListGroupItem(neg_kewords[1], color="danger"),
dbc.ListGroupItem(pos_keywords[2], color="danger"),
dbc.ListGroupItem(neg_kewords[2], color="danger"),
dbc.ListGroupItem(pos_keywords[3], color="success"),
dbc.ListGroupItem(neg_kewords[3], color="danger"),
dbc.ListGroupItem(neg_kewords[4], color="danger")
])])),], style={'textAlign': 'center'})
def drawRecentReviews(data):
return html.Div([
dbc.Card(
dbc.CardBody([html.P('Recent Reviews'),
dbc.Table.from_dataframe(data, striped=False, bordered=False, hover=True,dark=True,responsive=True)
])),], style={'textAlign': 'center',"maxHeight": "500px", "overflow": "scroll"})
review_business_data_merged = pd.read_csv('data/yelp_reviews_business_merged.csv')
review_sentiments=[map_sentiment(s) for s in review_business_data_merged['stars_x']]
review_business_data_merged['sentiments']=review_sentiments
review_business_data_merged['date']=pd.to_datetime(review_business_data_merged.date)
data_most_reviewed_store=review_business_data_merged[review_business_data_merged['business_id']=='4CxF8c3MB7VAdY8zFb2cZQ'].sort_values(by=['date'])
date_str=[en.strftime('%Y') for en in data_most_reviewed_store['date']]
data_most_reviewed_store['date']=date_str
data_most_reviewed_store_timeseries_pos=data_most_reviewed_store[data_most_reviewed_store['sentiments']==1].groupby('date')['date','sentiments'].sum()
data_most_reviewed_store_timeseries_neg=data_most_reviewed_store[data_most_reviewed_store['sentiments']==3].groupby('date')['date','sentiments'].sum()
data_most_reviewed_store_timeseries_neu=data_most_reviewed_store[data_most_reviewed_store['sentiments']==2].groupby('date')['date','sentiments'].sum()
data_most_reviewed_store_timeseries_pos['rating']=['Positive' for i in range(len(data_most_reviewed_store_timeseries_pos))]
data_most_reviewed_store_timeseries_neg['rating']=['Negative' for i in range(len(data_most_reviewed_store_timeseries_neg))]
data_most_reviewed_store_timeseries_neu['rating']=['Neutral' for i in range(len(data_most_reviewed_store_timeseries_neu))]
data_most_reviewed_store_timeseries=pd.concat([data_most_reviewed_store_timeseries_pos,data_most_reviewed_store_timeseries_neg])
data_most_reviewed_store_timeseries=pd.concat([data_most_reviewed_store_timeseries,data_most_reviewed_store_timeseries_neu])
# Text field
def drawText(text='NA'):
return html.Div([
dbc.Card(
dbc.CardBody([html.Div([html.P('Selected Business',style={'color': 'white'}),html.H5(text,style={'color': 'yellow'}), ], style={'textAlign': 'center'})
])),])
def drawTextOverallRating(text='NA'):
return html.Div([
dbc.Card(dbc.CardBody([html.Div([html.P('Overall Rating',style={'color': 'white'}),html.H5(text,style={'color': 'yellow'}), ], style={'textAlign': 'center'})
])),])
def drawTotalReview(text='Text'):
return html.Div([
dbc.Card(
dbc.CardBody([html.Div([html.P('Total Review',style={'color': 'white'}),
html.H5(text,style={'color': 'yellow'}),
], style={'textAlign': 'center'}) ])),])
def drawBusinessName():
return html.Div([
html.H2('Customer Review Analysis',style={'height':'62px','width':'390px','padding':'1px'}),
dcc.Dropdown(id='business_name',
options=[
{'label': 'Voodoo Doughnut - Old Town', 'value': '4CxF8c3MB7VAdY8zFb2cZQ'},
{'label': 'Screen Door', 'value': 'OQ2oHkcWA8KNC1Lsvj1SBA'},
{'label': 'Mike Pastry', 'value': 'PrsvO1rzkgg6qFizlAoEtg'},
{'label': 'Neptune Oyster', 'value': 'y2w6rFaO0XEiG5mFfOsiFA'}
],
placeholder="Select business",)])
keywords=pd.read_csv('data/trending_keywords.csv')
def get_Keywords(keywords,id):
keywords=keywords[keywords['id']==id].iloc[0]
pos = ast.literal_eval(keywords['pos_keywords'])
neg = ast.literal_eval(keywords['neg_keywords'])
return pos,neg
def get_recent_reviews(review_business_data_merged,id):
data_most_reviewed_store=review_business_data_merged[review_business_data_merged['business_id']==id].sort_values(by=['date'],ascending=False)
sentimments_dict={3:'Negative',2:'Neutral',1:'Positive'}
sentiment_names=[sentimments_dict[int(i)] for i in data_most_reviewed_store['sentiments'].values]
data_most_reviewed_store['sentiment']=sentiment_names
data_most_reviewed_store=data_most_reviewed_store.drop(columns=['business_id','review_id','user_id','user_id','categories'])
data_most_reviewed_store=data_most_reviewed_store[['text','sentiment','date','stars_x']]
data_most_reviewed_store=data_most_reviewed_store.rename(columns={'stars_x':'rating','text':'review'})
return data_most_reviewed_store
# Build App
app = dash.Dash(external_stylesheets=[dbc.themes.SLATE])
application = app.server
cr=CustomerReviewAnalysis()
resp=cr.getReviewAnalysis(review_business_data_merged,'4CxF8c3MB7VAdY8zFb2cZQ')
recent_reviews=get_recent_reviews(review_business_data_merged,'4CxF8c3MB7VAdY8zFb2cZQ')
#ck=CustomerReviewKeywords()
#ck.get_trending_keywords(data_most_reviewed_store,num_keywords=10)
pos_keywords,neg_keywords=get_Keywords(keywords,'4CxF8c3MB7VAdY8zFb2cZQ')
app.layout = html.Div([dbc.Card(
dbc.CardBody([dbc.Row([dbc.Col([drawBusinessName()], width=3),dbc.Col([drawText()], width=3,id='sb01'),dbc.Col([drawTextOverallRating()], width=3,id='sb02'),dbc.Col([drawTotalReview()], width=3,id='sb03'),], align='center'), html.Br(),
dbc.Row([dbc.Col([drawPieFigure()], width=3,id='df02'),dbc.Col([drawTrendingWords(pos_keywords,neg_keywords)], width=3,id='sb04'),dbc.Col([drawRecentReviews(recent_reviews)], width=6,id='df04'),], align='center'), html.Br(),
dbc.Row([dbc.Col([drawTrendsBarFigure()], width=5,id='df03'),dbc.Col([drawTimeSeriesFigure()], width=4,id='df05'),dbc.Col([drawRatings()],width=3,id='df01')], align='center'),]), color = 'dark')])
@app.callback(
[Output(component_id='sb01', component_property='children'),
Output(component_id='sb02', component_property='children'),Output(component_id='sb03', component_property='children'),
Output(component_id='df01', component_property='children'),Output(component_id='df02', component_property='children'),
Output(component_id='df04', component_property='children'),Output(component_id='df03', component_property='children'),
Output(component_id='sb04', component_property='children')],
[Input(component_id='business_name', component_property='value')]
)
def update_output_div(input_value):
cr=CustomerReviewAnalysis()
resp=cr.getReviewAnalysis(review_business_data_merged,input_value)
pos_keywords,neg_keywords=get_Keywords(keywords,input_value)
recent_reviews=get_recent_reviews(review_business_data_merged,input_value)
return drawText(resp['business_name']),drawTextOverallRating(resp['business_rating']),drawTotalReview(resp['num_review']),drawRatings(resp['rating_fig']),drawPieFigure(resp['sentiment_fig']),drawRecentReviews(recent_reviews),drawTrendsBarFigure(resp['timeseries_bar_fig']),drawTrendingWords(pos_keywords,neg_keywords)
if __name__ == '__main__':
application.run_server(debug=False)