# we fill a df with the data of interest and create a groupby pandas object
df = flowers[["petal_length", "petal_width", "species"]]
xyvalues = g = df.groupby("species")
# here we only drop that groupby object into a dict ..
pdict = OrderedDict()
for i in g.groups.keys():
labels = g.get_group(i).columns
xname = labels[0]
yname = labels[1]
x = getattr(g.get_group(i), xname)
y = getattr(g.get_group(i), yname)
pdict[i] = zip(x, y)
# any of the following commented are valid Scatter inputs
#xyvalues = pdict
#xyvalues = pd.DataFrame(xyvalues)
#xyvalues = xyvalues.values()
#xyvalues = np.array(xyvalues.values())
TOOLS = "resize,crosshair,pan,wheel_zoom,box_zoom,reset,previewsave"
scatter = Scatter(xyvalues,
filename="iris_scatter.html",
tools=TOOLS,
ylabel='petal_width',
facet=False)
scatter.title("iris dataset").legend("top_left")
scatter.width(600).height(400).show()
from bokeh.charts import Scatter
# we fill a df with the data of interest and create a groupby pandas object
df = flowers[["petal_length", "petal_width", "species"]]
xyvalues = g = df.groupby("species")
# here we only drop that groupby object into a dict ..
pdict = OrderedDict()
for i in g.groups.keys():
labels = g.get_group(i).columns
xname = labels[0]
yname = labels[1]
x = getattr(g.get_group(i), xname)
y = getattr(g.get_group(i), yname)
pdict[i] = zip(x, y)
# any of the following commented are valid Scatter inputs
#xyvalues = pdict
#xyvalues = pd.DataFrame(xyvalues)
#xyvalues = xyvalues.values()
#xyvalues = np.array(xyvalues.values())
TOOLS="resize,crosshair,pan,wheel_zoom,box_zoom,reset,previewsave"
scatter = Scatter(
xyvalues, filename="iris_scatter.html", tools=TOOLS, ylabel='petal_width',
facet=False
)
scatter.title("iris dataset").legend("top_left")
scatter.width(600).height(400).show()
