# coding: utf-8 # ## Plotting contents of an Excel File # # This notebook simply demonstrates how to plot the contents of an excel file using pandas an the bokeh `bokeh.charts` high level interface # In[ ]: import pandas as pd filepath = "http://databank.worldbank.org/data/download/catalog/climate_change_download_0.xls" # In[ ]: df = pd.ExcelFile(filepath).parse('Data') # In[ ]: emissions = df[df['Series name'] == "CO2 emissions, total (KtCO2)"].copy() for k in [2007, 2006, 2005]: emissions[k] = pd.to_numeric(emissions[k], errors='coerce') emissions = emissions.sort_values(2007, ascending=False) _remissions = emissions.iloc[:10, :] # In[ ]: columns = ['Country code', 'Country name', 2007, 2006, 2005] remissions = _remissions[columns] remissions.columns = [str(x) for x in remissions.columns] # In[ ]: from bokeh.plotting import figure, show, output_notebook, output_server, curdoc from bokeh.sampledata.autompg import autompg as df from bokeh.charts import Bar from bokeh.charts.operations import blend output_notebook() # In[ ]: palette = ['#f7fcf5', '#e5f5e0','#c7e9c0', '#a1d99b','#74c476','#41ab5d','#238b45','#005a32', '#5A6351', '#000000'] p = Bar(remissions, label='years', group='Country name', palette=palette, values= blend('2007', '2006', '2005', name='values', labels_name='years'), title='Emissions', color='Country name', legend=True, responsive=True) show(p) # In[ ]: greys = ['#ffffff', '#f0f0f0', '#d9d9d9', '#bdbdbd', '#969696', '#737373', '#525252', '#252525', '#000000'] blues = ["#f7fbff" ,"#deebf7" ,"#c6dbef" ,"#9ecae1" ,"#6baed6" ,"#4292c6" ,"#2171b5" ,"#084594"] p = Bar(remissions, label='Country name', group='year', palette = blues[1::3], values= blend('2007', '2006', '2005', name='values', labels_name='year'), title='Emissions', color='year', legend=True, responsive=True) show(p)