<jupyter_start><jupyter_text>Bokeh Vbar Glyph<jupyter_code>from bokeh.plotting import figure, output_file, show
from bokeh.models import Range1d
from math import radians

line_color = '#1f78b4'
fill_color = 'black'
output_file("../../figures/glyph-vbar.html")

p = figure(plot_width=400, plot_height=400)
p.vbar(y=0, left=-0.5, right=1.50, height=0.5, fill_alpha=1,fill_color=fill_color,
         line_alpha=1, line_color=line_color, line_dash='solid', line_width=5)
p.vbar(y=1, left=-0.5, right=0.5, height=0.75, fill_alpha=0.8, fill_color=fill_color, 
         line_alpha=1, line_color=line_color, line_dash='dotdash', line_width=8)
p.x_range = Range1d(-0.5,1.5, bounds=(-1,2))
p.y_range = Range1d(-0.5,1.5, bounds=(-1,2))
show(p)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.16666666666666666, 'fraction_numerical': 0.06299212598425197, 'mean_word_length': 6.064814814814815, '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': '445310', 'license': 'MIT', 'n_tokens_mistral': 339, 'n_tokens_neox': 327, 'n_words': 50, 'path': 'visualizations/bokeh/notebooks/glyphs/.ipynb_checkpoints/vbar-checkpoint.ipynb', 'repo_name': 'martinpeck/apryor6.github.io', 'size': '762'}