import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.colors import Normalize
import matplotlib as mpl
import beautifulplots.beautifulplots as bp
[docs]def barplot(df, bar_columns, bar_values, barcurrency=None, barorientation="v", bardataformat="1.2f",
y2=None, estimator=sum, estimator2=sum,
ax=None, bardatalabels=False, test_mode=False, bardatafontsize=14,
**kwargs):
"""Bar plot function designed for ease of use and aesthetics.
The underlying barplot is ased on the Seaborn with additions, such as secondary axis, data labels,
and improved default parameters. Refer to beautifulplots plot_defaults for a complete list of options.
Args:
df (DataFrame): The input DataFrame containing colums corresponding to bar_plot values ("bar_values") and column names (see examples in documentation)
bar_columns: Datafrae columns corresponding to bar column names
bar_values: Dataframe column corresponding to bar column values
ax (axis): matplotlib axis (optional), default = None. If axis is None, then create a matplolib figure, axis to host the barplot
color: Matplotlib compatabile color name as text or RGB values, for example, color = [51/235,125/235,183/235].
palette: Matplotlib compatible color palette name, for example, "tab20"
hue: Name of hue dimension variable (i.e., DataFrame column name)
ci: Seaborn confidence interval parameter: float, sd, or None, default = None
barorientation: default = v (vertical), or h (horizontal)
barcurrency: default = False (bar values do not represent currency). True (bar values represent currency, append $ to the value)
bardatalabels (Boolean): default = False (data labels not included)
estimater: default = sum. Specifies how to aggregate plot bar data.
estimator2: default = None. Summarize y2 asis daa. Default is no aggregation, do not summarize y2 axis data.
additional options: see beautifulplot.plot_defaults for additional input variables.
Returns:
returns True if processing completes succesfully (without errors).
"""
plot_options = bp.get_kwargs(**kwargs)
errorbar = plot_options['errorbar']
errorbar2 = plot_options['errorbar2']
alpha = plot_options['alpha']
alpha2 = plot_options['alpha2']
hue = plot_options['hue']
palette = plot_options['palette']
palette2 = plot_options['palette2']
marker2 = plot_options['marker2']
marker2 = plot_options['marker2']
markers2 = plot_options['markers']
style2 = plot_options['style2']
color = plot_options['color']
color2 = plot_options['color2']
y2label=plot_options['y2_axis_label']
y2axisformat = plot_options['y2_axis_format']
y2currency = plot_options['y2_currency']
# if no hue then only one color
# if hue == None and color==None : color = [51/235,125/235,183/235] if plot_options['color'] == None else plot_options['color']
if barorientation == 'v': x,y = bar_columns, bar_values
else: x,y = bar_values, bar_columns
if ax == None:
mpl.rcParams.update(mpl.rcParamsDefault) # reset plot/figure parameters
plt.style.use(plot_options['pltstyle'])
fig,_ax = plt.subplots(nrows=1, ncols=1, figsize=plot_options['figsize'])
else: _ax = ax
g=sns.barplot(x=x, y=y, hue=hue, color = color, palette=palette, data=df, ax = _ax,
orient=barorientation, errorbar=errorbar, estimator=estimator, alpha=alpha)
# Bar labels ... iterate with hue
# Matplotlib
# https://matplotlib.org/stable/gallery/lines_bars_and_markers/bar_label_demo.html#sphx-glr-gallery-lines-bars-and-markers-bar-label-demo-py
# Geeks for Geeks bar data labels
# https://www.geeksforgeeks.org/how-to-show-values-on-seaborn-barplot/
if bardatalabels == True:
f = bardataformat
for i in g.containers:
if barcurrency!=None:
g.bar_label(i,fontsize=bardatafontsize,labels=[f'{barcurrency}{x:{f}}' for x in i.datavalues] )
else:
g.bar_label(i,fontsize=bardatafontsize,labels=[f'{x:{f}}' for x in i.datavalues] )
# yaxis tick label format
# https://matplotlib.org/stable/gallery/pyplots/dollar_ticks.html
# x or y format same as bars ... since this could be v or h graph
#y_ticks = _ax.get_yticks()
f='{x:'+ bardataformat +'}'
if isinstance(barcurrency,str): f= barcurrency + f
if barorientation=='v':
_ax.yaxis.set_major_formatter(f)
if barorientation=='h':
_ax.xaxis.set_major_formatter(f)
# secondary y-axis
if y2 != None:
# make sure y2 and marker2 are iterable
if not isinstance(y2,list): y2 = [y2]
if marker2 == None:
if not isinstance(marker2,list): marker2 = len(y2)*[marker2]
else:
if not isinstance(marker2,list): marker2 =[marker2]
_ax2 = _ax.twinx()
for _y2,_marker2 in zip(y2,marker2):
label = _y2 if hue == None else None
if plot_options['palette2'] !=None:
g = sns.lineplot(data=df,x=x, y =_y2, hue=hue, palette=palette2, ax=_ax2, label=label,
alpha = alpha2,errorbar = errorbar2, marker=_marker2, estimator=estimator2,
markers=markers2, style=style2)
elif plot_options['color2'] !=None:
g = sns.lineplot(data=df,x=x, y=_y2, hue=hue, color=color2, ax=_ax2, label=label,
alpha=alpha2, errorbar=errorbar2, marker=_marker2, estimator=estimator2,
markers=markers2, style=style2)
else:
g = sns.lineplot(data=df,x=x, y=_y2, hue=hue, ax=_ax2, label=label,
alpha=alpha2, errorbar=errorbar2, marker=_marker2, estimator=estimator2,
markers=markers2, style=style2)
_ax2.grid(visible=None)
# set axis params
bp.set_axisparams(plot_options,_ax,g) # axis parameters from the plot_options dictionary
# y2 axis params
if y2 != None:
plot_options["y_label"]=y2label
bp.set_axisparams(plot_options,_ax2,g) # axis parameters
# set ylims 2 after general axis parameters
if plot_options['y_lims2'] != None:
_ax2.set_ylim(plot_options['y_lims2'])
# axis 2 legend
handles, labels = _ax2.get_legend_handles_labels()
if y2 != None and handles==True:
_ax2.legend( loc=plot_options['legend_loc2'], prop={'size': plot_options['legend_size']})
bp.set_yaxis_format(_ax2,y2axisformat, y2currency)
if ax==None and test_mode==False: plt.show() # if barplot created the figure then plt.show()
return None