-
Notifications
You must be signed in to change notification settings - Fork 1
/
app.py
224 lines (203 loc) · 8.78 KB
/
app.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
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
import dash
from dash import dcc
from dash import html
from dash.dependencies import Output, Input
import plotly.graph_objects as go
import random
import process
regions = {}
column_names = []
date = None # Initialize to any data type
external_stylesheets = [
{
"href": "https://fonts.googleapis.com/css2?"
"family=Lato:wght@400;700&display=swap",
"rel": "stylesheet",
},
]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
server = app.server
app.title = "Covid-19 Cases | Namibia"
def app_layouts():
app.layout = html.Div(
children=[
html.Div(
children=[
html.P(children="🦠", className="header-emoji"),
html.H1(
children="Covid-19 Analysis", className="header-title"
),
html.P(
children="The novel COVID-19 has devastated and brought economies world-over to a standstill. "
"COVID-19 is a new respiratory virus first identified in Wuhan, Hubei Province, "
"China. Building on your first assignment, this assignment requires you to develop "
"automatic dashboards. The dashboard should allow users to query and customize "
"visualisations.",
className="header-description",
),
],
className="header",
),
html.Div(
children=[
html.Div(className='column',
children=[
html.Div(children="Region", className="menu-title"),
dcc.Dropdown(
id="region-filter",
options=[{"label": r, "value": r} for r in regions.keys()],
value="Khomas",
clearable=False,
className="dropdown",
),
]
),
html.Div(className='column',
children=[
html.Div(children="Attribute", className="menu-title"),
dcc.Dropdown(
id="attribute-filter",
options=[{"label": c, "value": c} for c in column_names if c != 'Date'],
value="Active Cases",
clearable=False,
# searchable=False,
className="dropdown",
),
],
),
html.Div(className='column',
children=[
html.Div(
children="Date Range", className="menu-title"
),
dcc.DatePickerRange(
id="date-range",
min_date_allowed=date.min().date(),
max_date_allowed=date.max().date(),
start_date=date.min().date(),
end_date=date.max().date(),
),
]
),
],
className="menu",
),
html.Div(className='content',
children=[
html.Div(
children=[
html.Div(
children=dcc.Graph(
id="line-chart",
config={"displayModeBar": False},
),
className="card",
),
],
className="wrapper",
),
html.Div(
children=[
html.Div(
children=dcc.Graph(
id="bar-chart",
config={"displayModeBar": False},
),
className="card",
),
],
className="wrapper",
),
html.Div(
children=[
html.Div(
children=dcc.Graph(
id="pie-chart",
config={"displayModeBar": False},
),
className="card",
),
],
className="wrapper",
),
]
)
]
)
# Create random color
# https://stackoverflow.com/questions/28999287/generate-random-colors-rgb#comment104784319_50218895
def rgb():
color = f"#{random.randrange(0x1000000):06x}"
return color
def bar(filtered_data, column):
b = go.Bar(
x=filtered_data['Date'],
y=filtered_data[column],
name=column,
marker=dict(color=rgb())
)
return b
@app.callback(
[
Output("line-chart", "figure"),
Output("bar-chart", "figure"),
Output("pie-chart", "figure")
],
[
Input("region-filter", "value"),
Input("attribute-filter", "value"),
Input("date-range", "start_date"),
Input("date-range", "end_date"),
],
)
def update_line_graph(region, attribute, start_date, end_date):
reg_data = regions[region]
mask = ((reg_data['Date'] >= start_date) & (reg_data['Date'] <= end_date))
filtered_data = reg_data.loc[mask, :]
# Line graph
line_graph = go.Figure([go.Scatter(x=filtered_data['Date'], y=filtered_data[attribute],
name=attribute, line=dict(color='#17B897')
)])
line_graph.update_traces(line_shape="spline")
line_graph.update_layout(title='Line Graph for ' + attribute + ' in ' + region,
xaxis_title='Dates per Day', yaxis_title='Covid Cases',
plot_bgcolor='#ffffff',
)
line_graph.update_xaxes(showgrid=True, gridwidth=1, gridcolor='#efefef')
line_graph.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#efefef')
# Stacked Bar graph
# df.resample converts the column used to index column, so convert back
resampled_data = filtered_data.resample('M', on='Date').sum()
# https://stackoverflow.com/a/54276300/8050183
resampled_data = resampled_data.rename_axis('Date').reset_index()
bar_graph = go.Figure(data=[bar(resampled_data, c) for c in column_names[1:]])
bar_graph.update_layout(title='Stacked Bar Graph for ' + region,
barmode='stack', xaxis_title='Dates per Month (Click/double click right menu to toggle '
'visibility)',
yaxis_title='Covid Cases',
plot_bgcolor='#ffffff',
)
bar_graph.update_xaxes(showgrid=True, gridwidth=1, gridcolor='#efefef')
bar_graph.update_yaxes(showgrid=True, gridwidth=1, gridcolor='#efefef')
# Pie Chart
# This creates a series, then we iterate through the series
# to get labels and values
pie_data = filtered_data.sum(numeric_only=True)
labels, values = [], []
[(labels.append(i[0]), values.append(i[1])) for i in pie_data.items()]
pie_chart = go.Figure([go.Pie(labels=labels, values=values)])
pie_chart.update_layout(title='Pie Chart for ' + region)
return [line_graph, bar_graph, pie_chart]
# Import the data from process.py
def data():
global regions, column_names, date
# To process data from `dataset/raw`, uncomment the line below, and comment `process.read_data()`
# process.process_data()
process.read_data() # Read processed data
regions = process.regions
column_names = process.column_names
date = regions['Khomas']['Date']
data()
app_layouts()
if __name__ == "__main__":
app.run_server(debug=True)