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renderDashboard.py
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renderDashboard.py
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import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
import dash_table
import pandas as pd
from dash.dependencies import Input, Output
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
BUTTON_STYLE = {
'margin': '15px'
}
df = pd.read_csv('./output.csv')
# print(df)
# Adding new columns for fatality and survival ratio
df['Fatality Rate %'] = round(df['Death'].astype(float) * 100 / df['Total Confirmed cases'], 2)
df['Survival Rate %'] = round(df['Cured/Discharged'].astype(float) * 100 / df['Total Confirmed cases'], 2)
# Calculate KPIs here
states_effected = len(df)
confirmed = df['Total Confirmed cases'].sum()
cured = df['Cured/Discharged'].sum()
deaths = df['Death'].sum()
recovered_perc = round(float(cured * 100 / confirmed),2)
serious = confirmed - cured - deaths
fatality_ratio = round(float(deaths * 100 / confirmed), 2)
state_most_cases = df[df['Total Confirmed cases'] == df['Total Confirmed cases'].max()]
state_kpi1 = state_most_cases['Name of State / UT'] + " " + str(state_most_cases['Total Confirmed cases'].values)
state_most_cured = df[df['Cured/Discharged'] == df['Cured/Discharged'].max()]
# If more than one state have same number of cured cases, pick one with `higher Survival Rate %`
if len(state_most_cured.index) > 1:
state_most_cured = state_most_cured[state_most_cured['Survival Rate %'] == state_most_cured['Survival Rate %'].max()]
state_kpi2 = state_most_cured['Name of State / UT'] + " " + str(state_most_cured['Cured/Discharged'].values)
# print(df)
app.layout = html.Div([
html.H1(children='COVID-19 India Impact Dashboard', style={
'textAlign': 'center',
}),
dcc.Tabs([
dcc.Tab(label='Table', children=[
dash_table.DataTable(
id='datatable-interactivity',
columns=[
{"name": i, "id": i, "deletable": True, "selectable": True} for i in df.columns
],
data=df.to_dict('records'),
editable=False,
filter_action="native",
sort_action="native",
sort_mode="single",
column_selectable="single",
row_selectable="multi",
row_deletable=True,
selected_columns=[],
selected_rows=[],
page_action="native",
page_current=0,
page_size=30,
style_header={'fontWeight': 'bold'},
style_cell={'textAlign': 'left', 'fontSize': 14, 'font-family': 'sans-serif', 'width': 'auto'}
)
]),
dcc.Tab(label='Bar-Graphs', children=[
dcc.Loading(
id="loading-icon",
children=[
html.Div(id='datatable-interactivity-container')
],
type="circle"
)
]),
dcc.Tab(label='KPIs', children=[
html.Div([
dcc.Interval(id='interval1', interval=1000, n_intervals=-1000),
html.H1(id='label1', children='')
]),
html.Br(),
dbc.Button(
["Confirmed Cases", dbc.Badge(confirmed, color="light", className="ml-1 h1")],
color="dark", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["Serious", dbc.Badge(serious, color="light", className="ml-1 h1")],
color="warning", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["Recovered Cases",
dbc.Badge(str(cured) + " (" + str(recovered_perc) + "%)", color="light", className="ml-1 h1")],
color="success", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["Deaths", dbc.Badge(deaths, color="light", className="ml-1 h1")],
color="danger", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["Fatality Ratio", dbc.Badge(str(fatality_ratio) + "%", color="light", className="ml-1 h1")],
color="primary", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["States/UT Effected", dbc.Badge(str(states_effected) + " / 36", color="light", className="ml-1 h1")],
color="secondary", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["States/UT Most Cases", dbc.Badge(state_kpi1, color="light", className="ml-1 h1")],
color="warning", style=BUTTON_STYLE),
html.Br(),
dbc.Button(
["States/UT Most Cured", dbc.Badge(state_kpi2, color="light", className="ml-1 h1")],
color="success", style=BUTTON_STYLE)
])
])
])
@app.callback(Output("loading-icon", "children"))
@app.callback(
Output('datatable-interactivity', 'style_data_conditional'),
[Input('datatable-interactivity', 'selected_columns')]
)
def update_styles(selected_columns):
return [{
'if': {'column_id': i},
'background_color': '#D2F3FF'
} for i in selected_columns]
@app.callback(
Output('datatable-interactivity-container', "children"),
[Input('datatable-interactivity', "derived_virtual_data"),
Input('datatable-interactivity', "derived_virtual_selected_rows")])
def update_graphs(rows, derived_virtual_selected_rows):
# When the table is first rendered, `derived_virtual_data` and
# `derived_virtual_selected_rows` will be `None`. This is due to an
# idiosyncracy in Dash (unsupplied properties are always None and Dash
# calls the dependent callbacks when the component is first rendered).
# So, if `rows` is `None`, then the component was just rendered
# and its value will be the same as the component's dataframe.
# Instead of setting `None` in here, you could also set
# `derived_virtual_data=df.to_rows('dict')` when you initialize
# the component.
if derived_virtual_selected_rows is None:
derived_virtual_selected_rows = []
dff = df if rows is None else pd.DataFrame(rows)
colors = ['#7FDBFF' if i in derived_virtual_selected_rows else '#0074D9'
for i in range(len(dff))]
return [
dcc.Graph(
id=column,
figure={
"data": [
{
"x": dff["Name of State / UT"],
"y": dff[column],
"type": "bar",
"text": dff[column],
"textposition": 'auto',
"marker": {"color": colors},
"hoverinfo": 'skip'
}
],
"layout": {
"xaxis": {"automargin": True},
"yaxis": {
"automargin": True,
},
"title": {
"text": column,
'xanchor': 'center',
'yanchor': 'top'
},
"height": 250,
"margin": {"t": 20, "l": 10, "r": 10},
},
},
)
# check if column exists - user may have deleted it
# If `column.deletable=False`, then you don't
# need to do this check.
for column in ["Total Confirmed cases", "Cured/Discharged", "Death"] if
column in dff
]
if __name__ == '__main__':
app.run_server(debug=True)