Using Dash with Python to create interactive Dashboard Visualization

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What is DASH?

DASH is a newly introduced library in the rich portfolio of components ready to use with Python code. It uses the FLASK infrastructure as a base and has capability to map HTML tags to python code and produce interactive dashboards.

With the commencement of time, python is replacing and hovering over the become the first preferences for all the different flavors of software development. Interactive web portals was a field where python was lacking a bit and PHP was the first preference of majority of developers. But in the recent advancements, some open source libraries has been released which has the functionality of building web pages using python as a base development environment. One of such library is DASH.

Here, are the very basic commands using which one can prepare an interactive dashboard which will be hosted through a web page.

For this we need to first install DASH using-

pip install dash

then using the following base code:

from dash import Dash from dash import dcc from dash import html data = pd.read_csv("emissions.csv") data=data.groupby(['Vehicle class']).agg({'Co2': 'sum'}).reset_index() app = Dash(__name__) app.layout = html.Div( children=[ html.H1(children="Emissions"), html.H3("Sprint 1 - Annual Emissions, on a scale of 100"), dcc.Graph( figure=fig, ), html.H3("Sprint 2 - Emission based on Vehicle Type "), dcc.Graph( figure={ "data": [ { "x": data["Vehicle class"], "y": data["Co2"], "type": "lines", }, ], "layout": {"title" : "Emissions"}, }, ), ] ) if __name__ == "__main__": app.run_server(debug=True)

emissions.csv file:

Vehicle class	Time of day	Mon	Tue	Co2	Nox
car	1	11.4	9.8	19826.18	60.99766
car	2	6.1	5.4	10754.77	33.08835
car	3	4.5	4.1	8042.694	24.74433
car	4	5.4	4.6	9351.97	28.77248
car	5	11	8.9	18610.42	57.25724
car	6	35	31.4	62097.08	191.0493
car	7	88.8	87.2	164594.7	506.3956
car	8	174.9	176.7	328815.3	1011.64
car	9	198.5	202.7	375201	1154.352
car	10	140.8	144.7	266998.7	821.4543
car	11	133.9	130.1	246892	759.5935
car	12	139.8	132.7	254841.2	784.0501
car	13	143.3	138.2	263258	809.9453
car	14	143.3	139.7	264660.7	814.2612
car	15	151.7	149.8	281961.9	867.4903
car	16	172.9	175.5	325822.6	1002.433
car	17	202	208.1	383524.3	1179.959
car	18	217.4	224.5	413263.5	1271.456
car	19	161.1	171.3	310859.5	956.3972
car	20	105.6	113.7	205088.7	630.9805
car	21	72.3	76.8	139437.9	428.9977
car	22	53.3	58.2	104274.5	320.8132
car	23	35.6	41.1	71729.61	220.6849
car	24	18.7	21.2	37314.36	114.8022
light vehicle	1	10.8	10	24282.13	74.70694
light vehicle	2	7.1	6.7	16110.26	49.56518
light vehicle	3	6	6	14008.92	43.10016
light vehicle	4	7.9	7.4	17861.37	54.9527
light vehicle	5	16.7	13.9	35722.75	109.9054
light vehicle	6	45.4	39.7	99346.6	305.652
light vehicle	7	115.4	114.4	268270.8	825.3681
light vehicle	8	204.6	208.5	482257.1	1483.723
light vehicle	9	214	220	506656	1558.789
light vehicle	10	172.7	176.4	407542.9	1253.855
light vehicle	11	155.6	155.6	363298	1117.731
light vehicle	12	156.7	156.2	365282.6	1123.837
light vehicle	13	157.1	157.5	367267.2	1129.943
light vehicle	14	157.6	158.8	369368.5	1136.408
light vehicle	15	166.1	171.2	393767.4	1211.474
light vehicle	16	192.4	199.8	457858.2	1408.657
light vehicle	17	212.6	221.3	506539.2	1558.43
light vehicle	18	194	204.4	465096.2	1430.925