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KullyKully
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add sparkline file
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‎plotly/figure_factory/_sparkline.py

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from __future__ import absolute_import
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from plotly import exceptions, optional_imports
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from plotly.figure_factory import utils
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import plotly
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import plotly.graph_objs as go
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import numpy as np
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pd = optional_imports.get_module('pandas')
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VALID_CHART_TYPES = ['name', 'bullet', 'line', 'avg', 'bar']
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def create_sparkline(df, chart_types=('name', 'bullet', 'line', 'avg', 'bar'),
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colors=('rgb(181,221,232)', 'rgb(62,151,169)'),
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column_width=None, show_titles=True, left_aligned=False,
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scatter_options=None, **layout_options):
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"""
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Returns figure for sparkline.
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:param (pd.DataFrame | list | tuple) df: either a list/tuple of
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dictionaries or a pandas DataFrame.
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:param (list|tuple) chart_types: a sequence of any combination of valid
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chart types. The valid chart types are 'name', 'bullet', 'line', 'avg'
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and 'bar'
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:param (list|tuple) colors: a sequence of exactly 2 colors which are used
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to color the charts. Set the first color to your ___ color and the
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second color as your ___
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Default = ('rgb(181,221,232)', 'rgb(62,151,169)')
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:param (list) column_width: Specify a list that contains numbers where
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the amount of numbers in the list is equal to `chart_types`. Call
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`help(plotly.tools.make_subplots)` for more info on this subplot param
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:param (bool) show_titles: determines if title of chart type is displayed
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above their respective column
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:param (bool) left_aligned: determines if text cells are left-algined or
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right-aligned
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:param (dict) scatter_options: describes attributes for the scatter point
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in each bullet chart such as name and marker size. Call
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help(plotly.graph_objs.Scatter) for more information on valid params.
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:param layout_options: describes attributes for the layout of the figure
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such as title, height and width. Call help(plotly.graph_objs.Layout)
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for more information on valid params
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"""
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# validate dataframe
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if not pd:
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raise exceptions.ImportError(
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"'pandas' must be installed for this figure factory."
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)
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elif not isinstance(df, pd.DataFrame):
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raise exceptions.PlotlyError(
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'df must be a pandas DataFrame'
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)
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# validate list/tuple of colors
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if not utils.is_sequence(colors):
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raise exceptions.PlotlyError(
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'colors must be a list/tuple'
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)
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if len(colors) < 2:
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raise exceptions.PlotlyError(
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'colors must be a list/tuple with 2 colors inside'
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)
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plotly.colors.validate_colors(colors)
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num_of_chart_types = len(chart_types)
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# narrow columns that are 'name' or 'avg'
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narrow_cols = ['name', 'avg']
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narrow_idxs = []
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for i, chart in enumerate(chart_types):
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if chart in narrow_cols:
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narrow_idxs.append(i)
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if not column_width:
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column_width = [3.0] * num_of_chart_types
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for idx in narrow_idxs:
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column_width[idx] = 1.0
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fig = plotly.tools.make_subplots(
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len(df.columns), num_of_chart_types, print_grid=False,
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shared_xaxes=False, shared_yaxes=False,
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horizontal_spacing=0, vertical_spacing=0,
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column_width=column_width
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)
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# layout options
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fig['layout'].update(
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title='Sparkline Chart',
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annotations=[],
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showlegend=False
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)
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# update layout
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fig['layout'].update(layout_options)
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for key in fig['layout'].keys():
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if 'axis' in key:
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fig['layout'][key].update(
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showgrid=False,
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zeroline=False,
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showticklabels=False
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)
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# left aligned
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x = 0 if left_aligned else 1
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xanchor = 'left' if left_aligned else 'right'
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# scatter options
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default_scatter = {
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'mode': 'markers',
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'marker': {'size': 9,
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'symbol': 'diamond-tall',
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'color': colors[0]}
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}
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if not scatter_options:
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scatter_options = {}
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if scatter_options == {}:
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scatter_options.update(default_scatter)
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else:
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# add default options to scatter_options if they are not present
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for k in default_scatter['marker']:
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if k not in scatter_options['marker']:
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scatter_options['marker'][k] = default_scatter['marker'][k]
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# create and insert charts
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for j, key in enumerate(df):
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for c, chart in enumerate(chart_types):
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mean = np.mean(df[key])
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rounded_mean = round(mean, 2)
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if chart == 'name':
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fig['layout']['annotations'].append(
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dict(
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x=x,
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y=0.5,
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xref='x{}'.format(j * num_of_chart_types + c + 1),
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yref='y{}'.format(j * num_of_chart_types + c + 1),
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xanchor=xanchor,
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text=key,
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showarrow=False,
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font=dict(size=15),
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)
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)
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empty_data = go.Bar(
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x=[0],
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y=[0],
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visible=False
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)
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fig.append_trace(empty_data, j + 1, c + 1)
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elif chart == 'bullet':
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bullet_range = go.Bar(
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x=[rounded_mean],
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y=[0],
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marker=dict(
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color=colors[0]
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),
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orientation='h'
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)
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bullet_measure = go.Bar(
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x=[list(df[key])[-1]],
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y=[0],
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marker=dict(
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color=colors[1]
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),
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orientation='h',
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width=0.2,
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offset=-0.1
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)
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bullet_pt = go.Scatter(
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x=[max(df[key])],
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y=[0],
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**scatter_options
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)
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fig.append_trace(bullet_range, j + 1, c + 1)
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fig.append_trace(bullet_measure, j + 1, c + 1)
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fig.append_trace(bullet_pt, j + 1, c + 1)
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elif chart == 'line':
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trace_line = go.Scatter(
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x=range(len(df[key])),
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y=df[key].tolist(),
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mode='lines',
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marker=dict(
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color=colors[0]
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)
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)
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fig.append_trace(trace_line, j + 1, c + 1)
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trace_line_pt = go.Scatter(
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x=[len(df[key]) - 1],
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y=[list(df[key])[-1]],
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mode='markers',
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marker=dict(
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color=colors[1]
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)
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)
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fig.append_trace(trace_line_pt, j + 1, c + 1)
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elif chart == 'avg':
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fig['layout']['annotations'].append(
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dict(
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xref='x{}'.format(j * num_of_chart_types + c + 1),
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yref='y{}'.format(j * num_of_chart_types + c + 1),
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x=x,
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y=0.5,
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xanchor=xanchor,
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text='{}'.format(rounded_mean),
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showarrow=False,
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font=dict(size=15),
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)
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)
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empty_data = go.Bar(
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x=[0],
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y=[0],
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visible=False
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)
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fig.append_trace(empty_data, j + 1, c + 1)
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elif chart == 'bar':
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trace_bar = go.Bar(
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x=range(len(df[key])),
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y=df[key].tolist(),
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marker=dict(
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color=[colors[0] for _ in
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range(len(df[key]) - 1)] + [colors[1]]
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)
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)
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fig.append_trace(trace_bar, j + 1, c + 1)
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else:
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raise exceptions.PlotlyError(
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'Your chart type must be a list and may only contain any '
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'combination of the keys {}'.format(
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utils.list_of_options(
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VALID_CHART_TYPES, 'or')
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)
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)
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# show titles
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if show_titles:
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for k, header in enumerate(chart_types):
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label = utils.annotation_dict_for_label(
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header, k + 1, 5, subplot_spacing=0, row_col='col',
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flipped=False, column_width=column_width
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)
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fig['layout']['annotations'].append(label)
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# narrow columns with 'name' or 'avg' chart type
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for j in range(len(df.columns)):
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for idx in narrow_idxs:
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for axis in ['xaxis', 'yaxis']:
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fig['layout']['{}{}'.format(
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axis, j * num_of_chart_types + idx + 1
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)]['range'] = [0, 1]
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return fig

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