<jupyter_start><jupyter_text>Bokeh Tutorial  1.3 Plotting - Worldmap **Exercise: Draw a worldmap with the plotting interface***Note: For your convienience, I've written a script world_countries.py that parses the XML of country polygons from the dataset:* `World_Country_Boundaries.csv.gz`<jupyter_code># Get data
import utils.world_countries as wc
world_countries = wc.data.copy()
import pandas as pd
from bokeh.plotting import figure, show, output_notebook
# Process data
worldmap = pd.DataFrame.from_dict(world_countries, orient='index')
# Output option
output_notebook()
# Create your plot
p = figure(plot_height=500, plot_width=900, toolbar_location="left",
    x_axis_type=None, y_axis_type=None)

p.patches(xs=worldmap['lons'], ys=worldmap['lats'], fill_color="white", fill_alpha=0,
    line_color="black", line_width=0.5)
# Show plot
show(p)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10921501706484642, 'fraction_numerical': 0.012514220705346985, 'mean_word_length': 7.224299065420561, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '286297', 'license': 'MIT', 'n_tokens_mistral': 308, 'n_tokens_neox': 298, 'n_words': 76, 'path': '1.3 Plotting - Worldmap.ipynb', 'repo_name': 'adarsh0806/scipy2015-blaze-bokeh', 'size': '879'}