def get_dataframe_and_axes():
''' arbitrary data for now '''
from bokeh.sampledata.unemployment1948 import data
data['Year'] = data['Year'].astype(str)
data = data.set_index('Year')
data.drop('Annual', axis=1, inplace=True)
data.columns.name = 'Month'
years = list(data.index)
months = list(data.columns)
# reshape to 1D array or rates with a month and year for each row.
df = pd.DataFrame(data.stack(), columns=['rate']).reset_index()
return df, years, months
from math import pi
import pandas as pd
from bokeh.io import show
from bokeh.models import LinearColorMapper, BasicTicker, PrintfTickFormatter, ColorBar
from bokeh.plotting import figure
from bokeh.sampledata.unemployment1948 import data
data['Year'] = data['Year'].astype(str)
data = data.set_index('Year')
data.drop('Annual', axis=1, inplace=True)
data.columns.name = 'Month'
years = list(data.index)
months = list(data.columns)
# reshape to 1D array or rates with a month and year for each row.
df = pd.DataFrame(data.stack(), columns=['rate']).reset_index()
# this is the colormap from the original NYTimes plot
colors = ["#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1", "#cc7878", "#933b41", "#550b1d"]
mapper = LinearColorMapper(palette=colors, low=df.rate.min(), high=df.rate.max())
TOOLS = "hover,save,pan,box_zoom,reset,wheel_zoom"
p = figure(title="US Unemployment ({0} - {1})".format(years[0], years[-1]),
x_range=years, y_range=list(reversed(months)),
x_axis_location="above", plot_width=900, plot_height=400,
tools=TOOLS, toolbar_location='below',
tooltips=[('date', '@Month @Year'), ('rate', '@rate%')])
d[int(x[i]/2.5-1)][int(y[i]/2.5-1)] = z[i]
p = figure(x_range=(0,100), y_range=(0,100))
# must give a vector of image data for image parameter
p.image(image=[d], x=0, y=0, dw=100, dh=100, palette="Spectral11")
p.add_tools(HoverTool(tooltips=[("Cancer", "$x"), ("Chemical", "$y"), ("Percentile", "@image")]))
output_file("fff.html", title="image.py example")
show(p) # open a browser
'''
'''
from math import pi
import pandas as pd
from bokeh.io import show
from bokeh.models import LinearColorMapper, BasicTicker, PrintfTickFormatter, ColorBar
from bokeh.plotting import figure
from bokeh.sampledata.unemployment1948 import data
data['Year'] = data['Year'].astype(str)
data = data.set_index('Year')
data.drop('Annual', axis=1, inplace=True)
data.columns.name = 'Month'
years = list(data.index)
months = list(data.columns)
import cudf
import pandas as pd
from bokeh.sampledata.unemployment1948 import data
data["Year"] = data["Year"].astype(str)
data = data.set_index("Year")
data.drop("Annual", axis=1, inplace=True)
data.columns.name = "Month"
years = list(data.index)
months = list(data.columns)
# reshape to 1D array or rates with a month and year for each row.
df = pd.DataFrame(data.stack(), columns=["rate"]).reset_index()
df["Month"] = pd.to_datetime(df.Month, format="%b").dt.month
df["Year"] = df["Year"].astype("float64")
df["Month"] = df["Month"].astype("float64")
df = cudf.DataFrame.from_pandas(df)
