def ohlc(self,
df,
title=None,
series_name='',
xlabel=None,
ylabel=None,
layout=None):
""" timeseries OHLC
Args:
df (DataFrame): df requires columns open, high, low, close
title, xlabel, ylabel (str): title is required and others are optional
"""
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': 'ohlc'
}],
'staticPlot': False,
'name': series_name
}
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def line(self,
df,
title=None,
xlabel=None,
ylabel=None,
lines=None,
layout=None):
""" plot a df as a line plot
Args:
df (DataFrame): df with index as x axis
title, xlabel, ylabel (str): title is required and others are optional
"""
# dict() to store info for plotting
plot_dict = {'data': [{'df': df, 'type': 'line'}], 'staticPlot': False}
if lines is not None:
plot_dict['lines'] = lines
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def multi(self,
dfs,
types,
title=None,
xlabel=None,
ylabel=None,
y2_axis=None,
y2label=None,
layout=None):
""" plot multiple plot types on the same plot
Args:
dfs (list of DataFrames)
types (list of strings): list of plot types corresponding to dfs
title, xlabel, ylabel (str): title is required and others are optional
y2_axis (list of booleans): booleans indicating whether y values should be plotted on secondary y axis (optional)
y2label (str): label for secondary y axis (optional)
"""
data = []
for i in range(len(dfs)):
if y2_axis == None:
data.append({'df': dfs[i], 'type': types[i]})
else:
data.append({'df': dfs[i], 'type': types[i], 'y2': y2_axis[i]})
# dict() to store info for plotting
plot_dict = {'data': data, 'staticPlot': False}
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel, y2label)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def errline(self,
df,
title=None,
xlabel=None,
ylabel=None,
fillcolor='rgba(0,100,80,0.2)',
layout=None):
""" plot a df as a continuous error line chart
Args:
df (DataFrame): df with index as x axis, column 1 as y value, column 2 as symmetric error
title, xlabel, ylabel (str): title is required and others are optional
fillcolor (str rgba()): rgba value for fill, default is 'rgba(0,100,80,0.2)'
"""
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': 'continuousErrorBars',
'fillcolor': fillcolor
}],
'staticPlot':
False
}
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def errbar(self,
df,
title=None,
xlabel=None,
ylabel=None,
symmetric=True,
layout=None):
""" plot a df as an error bar chart
Args:
df (DataFrame): df with index as x axis, column 1 as y value, column 2 as positive (or symmetric) error, column 3 as negative (optional) error
title, xlabel, ylabel (str): title is required and others are optional
"""
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': 'scatter',
'errorBars': {
'symmetric': symmetric,
}
}],
'staticPlot':
False
}
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def bar(self,
df,
title=None,
xlabel=None,
ylabel=None,
stacked=False,
horizontal=False,
markers=None,
layout=None):
""" plot a df as a bar chart
Args:
df (DataFrame): df with index as x axis
title, xlabel, ylabel (str): title is required and others are optional
"""
# stacked vs normal bar plots
plot_type = 'bar'
if stacked:
plot_type = 'stackedBar'
# vertical vs horizontal bars
orientation = 'v'
if horizontal:
orientation = 'h'
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': plot_type,
'orientation': orientation
}],
'staticPlot': False
}
if markers is not None:
plot_dict['markers'] = markers
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def baro(self,
df,
title=None,
xlabel=None,
ylabel=None,
orientation='v',
markers=None,
widths=None,
opacities=None,
layout=None):
""" plot a df as an overlay bar chart
Args:
df (DataFrame): df with index as x axis for vertical, y axis for horizontal
title, xlabel, ylabel (str): title is required and others are optional
"""
plot_type = 'overlayBar'
plot_dict = {
'data': [{
'df': df,
'type': plot_type,
'orientation': orientation
}],
'staticPlot': False
}
if markers is not None:
plot_dict['markers'] = markers
if widths is not None:
plot_dict['widths'] = widths
if opacities is not None:
plot_dict['opacities'] = opacities
if layout is not None:
plot_dict['layout'] = layout
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def pie(self,
df,
title=None,
hole=None,
markers=None,
margin=None,
layout=None):
""" plot a df as a pie chart
Args:
df (DataFrame): df with index as label / category, first column as value
title (str): title is required and others are optional
hole (num [0-1]): percentage of pie to cut out for donut (optional)
"""
if hole is not None:
plot_dict = {
'data': [{
'df': df,
'type': 'pie',
'hole': hole
}],
'staticPlot': False,
}
else:
plot_dict = {
'data': [{
'df': df,
'type': 'pie'
}],
'staticPlot': False,
}
if markers is not None:
plot_dict['markers'] = markers
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def scatter(self,
df,
title=None,
xlabel=None,
ylabel=None,
markers=None,
margin=None,
hide_legend=False,
layout=None):
""" plot a df as a scatter plot
Args:
df (DataFrames): df with index as x axis
title, xlabel, ylabel (str): title is required and others are optional
"""
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': 'scatter'
}],
#'staticPlot': False
}
if markers is not None:
plot_dict['markers'] = markers
if margin is not None:
plot_dict['margin'] = margin
if hide_legend:
plot_dict['hide_legend'] = hide_legend
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def time(self,
df,
title=None,
gap_time_format=None,
xlabel=None,
ylabel=None,
lines=None,
layout=None):
""" plot a df as a timeseries
Args:
df (DataFrame): df with index as x axis
gap_time_format (str): If specified, then skip gaps and format timestamps using this str
title, xlabel, ylabel (str): title is required and others are optional
"""
# remove nan and replace timestamps as strings to handle gaps in time
if gap_time_format is not None:
is_one_dim = (len(df.shape) == 1) or (df.shape[1] == 1)
if is_one_dim:
df = df[df.notnull()]
else:
df = df[df.notnull().any(axis=1)]
df.index = df.index.map(lambda dt: dt.strftime(gap_time_format))
# dict() to store info for plotting
plot_dict = {'data': [{'df': df, 'type': 'line'}], 'staticPlot': False}
if lines is not None:
plot_dict['lines'] = lines
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
def histo(self,
df,
title=None,
xlabel=None,
ylabel=None,
markers=None,
layout=None):
""" plot a df as a histogram
Args:
df (DataFrame): df with index as x axis
title, xlabel, ylabel (str): title is required and others are optional
"""
# stacked vs normal bar plots
plot_type = 'histogram'
# dict() to store info for plotting
plot_dict = {
'data': [{
'df': df,
'type': plot_type
}],
'staticPlot': False
}
if markers is not None:
plot_dict['markers'] = markers
if layout is not None:
plot_dict['layout'] = layout
# plot labels + create HTML
plot_dict = self._add_labels(plot_dict, title, xlabel, ylabel)
if self.reporter:
self.reporter.h += create_html.plot(plot_dict)
return plot_dict
'labelX': 'x',
'labelY': 'ya',
'labelY2': 'yb',
}
output_path = '/home/jason/ideal/reports/sample_report/output'
output_file = os.path.join(output_path, 'sample_plots.html')
r = Reporter(title='Sample Plots', output_file=output_file)
# report start
r.h += htmltag.h3('This report provides an overivew of the different plot types.')
# bar charts
r.h += htmltag.h4('Bar Charts')
r.plot.bar(df=dfhb, title='Vertical Bar Chart by Reporter', xlabel='Entity', ylabel='%')
r.h += ch.plot(bar_plot)
r.plot.barh(df=dfsb, title='Horizontal Stacked Bar Chart by Reporter', stacked=True, xlabel='$')
r.h += ch.plot(stacked_bar_plot)
# line charts
r.h += htmltag.h4('Line Charts')
r.plot.line(df=dfl, title='Line Chart by Reporter', xlabel='Entity', ylabel='%')
r.h += ch.plot(line_plot)
# scatter plots
r.h += htmltag.h4('Scatter Plots')
r.plot.scatter(df=dfsp, title='Scatter Plot by Reporter', xlabel='alpha', ylabel='beta')
r.h += ch.plot(scatter_plot)
# mixed plot types
r.h += htmltag.h4('Multi Series, Mixed Type Plots')