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)