[Plotly Unacast Template] #plotly

unacast_template.py

!pip install plotly==4.8

# Quick way to install hind font
!npm install -g google-font-installer
!gfi install hind -v 300

import plotly.graph_objs as go
import plotly.io as pio

pd.options.plotting.backend = "plotly"


pio.templates['unacast'] = go.layout.Template({
    'data': {'scatter': [{'marker': {'size': 20, 'symbol': 'hexagon'}, 'type': 'scatter'}]},
    'layout': {'autosize': True,
               'colorscale': {'diverging': [[0, '#8e0152'], [0.1, '#c51b7d'],
                                            [0.2, '#de77ae'], [0.3, '#f1b6da'],
                                            [0.4, '#fde0ef'], [0.5, '#f7f7f7'],
                                            [0.6, '#e6f5d0'], [0.7, '#b8e186'],
                                            [0.8, '#7fbc41'], [0.9, '#4d9221'], [1,
                                            '#276419']],
                              'sequential': [[0.0, '#0d0887'],
                                             [0.1111111111111111, '#46039f'],
                                             [0.2222222222222222, '#7201a8'],
                                             [0.3333333333333333, '#9c179e'],
                                             [0.4444444444444444, '#bd3786'],
                                             [0.5555555555555556, '#d8576b'],
                                             [0.6666666666666666, '#ed7953'],
                                             [0.7777777777777778, '#fb9f3a'],
                                             [0.8888888888888888, '#fdca26'], [1.0,
                                             '#f0f921']],
                              'sequentialminus': [[0.0, '#0d0887'],
                                                  [0.1111111111111111, '#46039f'],
                                                  [0.2222222222222222, '#7201a8'],
                                                  [0.3333333333333333, '#9c179e'],
                                                  [0.4444444444444444, '#bd3786'],
                                                  [0.5555555555555556, '#d8576b'],
                                                  [0.6666666666666666, '#ed7953'],
                                                  [0.7777777777777778, '#fb9f3a'],
                                                  [0.8888888888888888, '#fdca26'],
                                                  [1.0, '#f0f921']]},
               'colorway': ['#FF8000', '#1A4D60', '#00B39B', '#34768F', '#C42240',
                            '#C42240', '#404040'],
               'font': {'color': '#1C1C1C', 'family': 'Hind'},
               'hoverlabel': {'align': 'left'},

               'height': 600,
               'width': 1400,
               'images': [{'sizex': 0.3,
                           'sizey': 0.3,
                           'source': ('https://proptechzone.com/wp-content/uploads/2019/10/unacast-3b04492b-4fe9-4b70-9dc7-43fb22aa6d5c-1.png'),
                           #'source': "https://global-uploads.webflow.com/5dc3e2af6a906d9cc232e1bc/5dc3e2af6a906dceb532e551_unacast-symbol-uc_orange-rgb.png",
                           'x': 1.0,
                           'xanchor': 'center',
                           'xref': 'paper',
                           'y': -0.22,
                           'yanchor': 'bottom',
                           'yref': 'paper',
                           'name': 'uc-logo'}],
               'margin': {'b': 60, 'l': 60, 'r': 60, 't': 60},
               'paper_bgcolor': '#FFFFFF',
               'plot_bgcolor': '#F5F6F7',
               'title': {'font': {'size': 25}},
              'xaxis': {'automargin': True,
                         'gridcolor': 'white',
                         'linecolor': 'white',
                         'showgrid': True,
                         'tickcolor': 'rgb(51,51,51)',
                         'ticks': 'outside',
                         'title': {'standoff': 15},
                         'zerolinecolor': 'white'},
               'yaxis': {'automargin': True,
                         'gridcolor': 'white',
                         'linecolor': 'white',
                         'showgrid': True,
                         'tickcolor': 'rgb(51,51,51)',
                         'ticks': 'outside',
                         'title': {'standoff': 15},
                         'zerolinecolor': 'white'}}
})



def plot_trend(df, date_col, value_col, name="", color="black", title="",
               width=1000, height=400, template="unacast"):
    """
    Plot a single temporal trend.
    """
    df.sort_values(by=date_col, inplace=True)
    
    fig = go.Figure()
    fig.add_trace(go.Scatter(
                    x = df[date_col],
                    y = df[value_col],
                    name = name,
                    line_color = color))

    # Use date string to set xaxis range
    fig.update_layout(
        title_text = title,
        width=width, 
        height=height,
        template="unacast"
    )

    fig.show()
    

    
def plot_trends(df, category_col, date_col, value_col, name="", colors=["black"], title="",
               width=1000, height=400, yaxis_type="linear"):
    """
    Plot a series of temporal trends.
    """
    df.sort_values(by=date_col, inplace=True)
    
    fig = go.Figure()
    
    ix = 0
    for cat, cat_df in df.groupby(category_col):

        #color = dict(enumerate(colors)).get(ix, "black")
        
        fig.add_trace(go.Scatter(
                        x = cat_df[date_col],
                        y = cat_df[value_col],
                        name = cat))
        ix += 1

    # Use date string to set xaxis range
    fig.update_layout(
        title_text = title,
        width=width, 
        height=height,
        yaxis_type=yaxis_type,
        template="unacast"
    )

    if(yaxis_type == "log"):
        fig.update_layout(xaxis_type="log", yaxis_type="log")

    fig.show()