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updating dashbaord
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@codeperfectplus
codeperfectplus committed Feb 18, 2022
1 parent 74e3169 commit 1a4229e
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2 changes: 1 addition & 1 deletion config.json
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@@ -1 +1 @@
[{"stock_name": "Vodafone Idea Ltd", "stock": "IDEA:NSE", "min_price": 10.5, "max_price": 11.5, "watch": true}, {"stock_name": "Steel Authority of India Limited", "stock": "SAIL:NSE", "min_price": 97.4, "max_price": 130, "watch": true}, {"stock_name": "Birlasoft Ltd", "stock": "BSOFT:NSE", "min_price": 434.5, "max_price": 500, "watch": true}, {"stock_name": "Trident Ltd", "stock": "TRIDENT:NSE", "min_price": 53.6, "max_price": 70, "watch": true}, {"stock_name": "KPIT Technologies Ltd", "stock": "KPITTECH:NSE", "min_price": 563.2, "max_price": 700, "watch": true}, {"stock_name": "Jubilant Ingrevia Ltd", "stock": "JUBLINGREA:NSE", "min_price": 523.25, "max_price": 700, "watch": false}, {"stock_name": "Infosys Ltd", "stock": "INFY:NSE", "min_price": 1700, "max_price": 2000, "watch": false}, {"stock_name": "Tata Power Company Limited", "stock": "TATAPOWER:NSE", "min_price": 227.95, "max_price": 241.1, "watch": true}, {"stock_name": "Tata Motors Limited", "stock": "TATAMOTORS:NSE", "min_price": 490, "max_price": 510, "watch": false}, {"stock_name": "Coforge Ltd", "stock": "COFORGE:NSE", "min_price": 4375.55, "max_price": 4759, "watch": false}, {"stock_name": "Bharti Airtel Limited", "stock": "BHARTIARTL:NSE", "min_price": 700, "max_price": 750, "watch": false}, {"stock_name": "Coal India Ltd", "stock": "COALINDIA:NSE", "min_price": 160, "max_price": 170, "watch": false}, {"stock_name": "Hindustan Copper Ltd.", "stock": "HINDCOPPER:NSE", "min_price": 124.85, "max_price": 150, "watch": false}, {"stock_name": "Indian Oil Corporation Ltd", "stock": "IOC:NSE", "min_price": 110, "max_price": 140, "watch": true}, {"stock_name": "Oil & Natural Gas Corporation Limited", "stock": "ONGC:NSE", "min_price": 160, "max_price": 171.35, "watch": true}, {"stock_name": "Reliance Industries Ltd", "stock": "RELIANCE:NSE", "min_price": 2350, "max_price": 2450, "watch": false}, {"stock_name": "Affle (India) Ltd", "stock": "AFFLE:NSE", "min_price": 1200, "max_price": 1300, "watch": false}, {"stock_name": "Borosil Renewables Ltd", "stock": "BORORENEW:NSE", "min_price": 600, "max_price": 700, "watch": false}, {"stock_name": "Gail India", "stock": "GAIL:NSE", "min_price": 139.7, "max_price": 150, "watch": true}, {"stock_name": "Zomato Ltd", "stock": "ZOMATO:NSE", "min_price": 86.7, "max_price": 100, "watch": false}, {"stock_name": "Yes Bank Limited", "stock": "YESBANK:NSE", "min_price": 13.8, "max_price": 14.05, "watch": true}, {"stock_name": "Larsen & Toubro Limited", "stock": "LT:NSE", "min_price": 1800, "max_price": 1900, "watch": false}, {"stock_name": "NTPC Limited", "stock": "NTPC:NSE", "min_price": 132.7, "max_price": 150, "watch": false}, {"stock_name": "ITC Ltd", "stock": "ITC:NSE", "min_price": 221.65, "max_price": 270, "watch": false}]
[{"stock_name": "Vodafone Idea Ltd", "stock": "IDEA:NSE", "min_price": 10.5, "max_price": 11.5, "watch": true}, {"stock_name": "Steel Authority of India Limited", "stock": "SAIL:NSE", "min_price": 97.4, "max_price": 130, "watch": true}, {"stock_name": "Birlasoft Ltd", "stock": "BSOFT:NSE", "min_price": 434.5, "max_price": 500, "watch": true}, {"stock_name": "Trident Ltd", "stock": "TRIDENT:NSE", "min_price": 53.6, "max_price": 70, "watch": true}, {"stock_name": "KPIT Technologies Ltd", "stock": "KPITTECH:NSE", "min_price": 563.2, "max_price": 700, "watch": true}, {"stock_name": "Jubilant Ingrevia Ltd", "stock": "JUBLINGREA:NSE", "min_price": 523.25, "max_price": 700, "watch": false}, {"stock_name": "Infosys Ltd", "stock": "INFY:NSE", "min_price": 1700, "max_price": 2000, "watch": false}, {"stock_name": "Tata Power Company Limited", "stock": "TATAPOWER:NSE", "min_price": 227.95, "max_price": 241.1, "watch": true}, {"stock_name": "Tata Motors Limited", "stock": "TATAMOTORS:NSE", "min_price": 490, "max_price": 510, "watch": false}, {"stock_name": "Coforge Ltd", "stock": "COFORGE:NSE", "min_price": 4375.55, "max_price": 4759, "watch": false}, {"stock_name": "Bharti Airtel Limited", "stock": "BHARTIARTL:NSE", "min_price": 700, "max_price": 750, "watch": false}, {"stock_name": "Coal India Ltd", "stock": "COALINDIA:NSE", "min_price": 160, "max_price": 170, "watch": false}, {"stock_name": "Hindustan Copper Ltd.", "stock": "HINDCOPPER:NSE", "min_price": 124.85, "max_price": 150, "watch": false}, {"stock_name": "Indian Oil Corporation Ltd", "stock": "IOC:NSE", "min_price": 110, "max_price": 140, "watch": true}, {"stock_name": "Oil & Natural Gas Corporation Limited", "stock": "ONGC:NSE", "min_price": 160, "max_price": 171.35, "watch": true}, {"stock_name": "Reliance Industries Ltd", "stock": "RELIANCE:NSE", "min_price": 2350, "max_price": 2450, "watch": false}, {"stock_name": "Affle (India) Ltd", "stock": "AFFLE:NSE", "min_price": 1200, "max_price": 1300, "watch": false}, {"stock_name": "Borosil Renewables Ltd", "stock": "BORORENEW:NSE", "min_price": 600, "max_price": 700, "watch": false}, {"stock_name": "Gail India", "stock": "GAIL:NSE", "min_price": 139.7, "max_price": 150, "watch": true}, {"stock_name": "Zomato Ltd", "stock": "ZOMATO:NSE", "min_price": 86.7, "max_price": 100, "watch": false}, {"stock_name": "Yes Bank Limited", "stock": "YESBANK:NSE", "min_price": 13.8, "max_price": 14.05, "watch": true}, {"stock_name": "Larsen & Toubro Limited", "stock": "LT:NSE", "min_price": 1800, "max_price": 1900, "watch": false}, {"stock_name": "NTPC Limited", "stock": "NTPC:NSE", "min_price": 132.6, "max_price": 150, "watch": false}, {"stock_name": "ITC Ltd", "stock": "ITC:NSE", "min_price": 221.65, "max_price": 270, "watch": false}]
21 changes: 8 additions & 13 deletions dashboard.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,7 @@ def get_filtered_data():
filtered_df = df[df['Last Update'].isin(lastest_date)]
filtered_df.sort_values(by=['difference'], inplace=True, ascending=False)
filtered_df["Last Update"] = filtered_df["Last Update"].apply(lambda x: x.strftime('%H:%M:%S'))
df["Last Update"] = df["Last Update"].apply(lambda x: x.strftime('%H:%M:%S'))
fd1 = filtered_df[filtered_df['watch'] == True]
fd2 = filtered_df[filtered_df['watch'] == False]
fd1 = fd1[columns]
Expand All @@ -45,18 +46,12 @@ def get_filtered_data():
df, fd1, fd2, latest_date = get_filtered_data()

# change min and max time from 9 to 16
min_time = today_date + ' 09:00:00'
max_time = today_date + ' 16:00:00'
min_time = '09:00:00'
max_time = '16:00:00'

#change str date to datetime
min_time = datetime.datetime.strptime(min_time, '%d-%m-%Y %H:%M:%S')
max_time = datetime.datetime.strptime(max_time, '%d-%m-%Y %H:%M:%S')

if latest_date < max_time:
max_time = latest_date

print('Min Time: ', min_time)
print('Max Time: ', max_time)
min_time = datetime.datetime.strptime(min_time, '%H:%M:%S')
max_time = datetime.datetime.strptime(max_time, '%H:%M:%S')

def get_dash_table(table_id, df):
return dash_table.DataTable(
Expand Down Expand Up @@ -121,7 +116,8 @@ def get_dash_table(table_id, df):
]),
# graph by stock name select box
html.Div([
html.Label('Select Stock Name', style={'font-family': 'Courier New', 'font-size': '20px', 'font-weight': 'bold'}),
html.H3('Graph for Stock Data', style={'textAlign': 'center', 'color': '#0099ff', 'font-family': 'Courier New',
'font-size': '30px', 'font-weight': 'bold', 'margin-top': '20px'}),
dcc.Dropdown(
id='stock-name-select',
options=[{'label': i, 'value': i} for i in df['Stock Name'].unique()],
Expand Down Expand Up @@ -205,8 +201,7 @@ def update_graph(stock_name, n):
'xanchor':"right",
'x':2,
'yaxis': {'range': [min(filtered_df['Minimum(Threshold)']) - 10, max(filtered_df['Maximum(Threshold)']) + 10]},
'xaxis': {'range': [min_time, max_time]}

'xaxis': {'range': [min_time, max_time]},
}
}

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