Create Vertical Barchart group

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Tags: #plotly #chart #verticalbarchart #group #dataviz #snippet
Author: Florent Ravenel​
Input
Import libraries
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import naas
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import plotly.graph_objects as go
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import pandas as pd
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Variables
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title = "Sales Evolution (group)"
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​
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# Output paths
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output_image = f"{title}.png"
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output_html = f"{title}.html"
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Get data
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x_axis = [1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012]
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y_axis_value1 = [219, 146, 112, 127, 124, 180, 236, 207, 236, 263, 350, 430, 474, 526, 488, 537, 500, 439]
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y_axis_value2 = [16, 13, 10, 11, 28, 37, 43, 55, 56, 88, 105, 156, 270, 299, 340, 403, 549, 499]
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​
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df1 = pd.DataFrame(zip(x_axis, y_axis_value1), columns=["LABEL", "VALUE"])
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df1["GROUPS"] = "USA"
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​
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df2 = pd.DataFrame(zip(x_axis, y_axis_value2), columns=["LABEL", "VALUE"])
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df2["GROUPS"] = "Rest of world"
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​
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df = pd.concat([df1, df2])
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df
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Model
Create Vertical Barchart stacked
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def create_barchart(df, label, groups, value, title):
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    fig = go.Figure()
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    list_groups = df[groups].unique()
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    for group in list_groups:
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        tmp_df = df[df[groups] == group]
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        fig.add_trace(go.Bar(x=tmp_df[label],
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                             y=tmp_df[value],
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                             name=group))
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    fig.update_layout(
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        title=title ,
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        plot_bgcolor="#ffffff",
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        width=1200,
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        height=800,
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        xaxis_tickfont_size=14,
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        legend=dict(
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            bgcolor='white',
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            bordercolor='white'
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        ),
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        barmode='group',
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        bargap=0.1, # gap between bars of adjacent location coordinates.
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        bargroupgap=0.1 # gap between bars of the same location coordinate.
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    )
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    config = {'displayModeBar': False}
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    fig.show(config=config)
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    return df
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​
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fig = create_barchart(df, label="LABEL", groups="GROUPS", value="VALUE", title=title)
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Output
Export in PNG and HTML
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fig.write_image(output_image, width=1200)
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fig.write_html(output_html)
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Generate shareable assets
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link_image = naas.asset.add(output_image)
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link_html = naas.asset.add(output_html, {"inline":True})
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​
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#-> Uncomment the line below to remove your assets
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# naas.asset.delete(output_image)
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# naas.asset.delete(output_html)
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Input

Model

Output