<jupyter_start><jupyter_text>![circle plot](circle4.png)<jupyter_code>tail = dict()
for c in range(1,150):
    tail[c] = len(list(filter(lambda e: abs(e) >= c/100, [sums[i]/i**.5 for i in range(1, len(sums))])))/(len(sums)-1)
tail[10]
plt.style.use('ggplot')
tailxs = [c/100 for c in range(1,150)]
tailys = [tail[c] for c in range(1, 150)]
myplot.make_one_plot_by_pts(tailxs, tailys, xmin=0, ymin=0, xmax = 1.5, ymax=1,
                            xtick_mult=.2, ytick_mult=.2, figname='tailplot', save_format="png",
                           usecolor=True, figsize_x=6, figsize_y=6)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18566775244299674, 'fraction_numerical': 0.05374592833876222, 'mean_word_length': 3.92, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, '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': '622292', 'license': 'MIT', 'n_tokens_mistral': 275, 'n_tokens_neox': 256, 'n_words': 47, 'path': 'Experimentation/size_of_satotate_sums.ipynb', 'repo_name': 'davidlowryduda/notebooks', 'size': '614'}