<jupyter_start><jupyter_text>Using subset-selector Create `SubsetSelector` with data and plot. `y` should be a multidimensional array. Each sample from a subset of `y` is graphed. You can scroll through subsets using the figure's toolbar, select graphs of interest, and get the data back from them later. Execute the cell below and click on some graphs to try it out.<jupyter_code>from subset_selector import SubsetSelector
ss = SubsetSelector(x, y)
ss.plot()<jupyter_output><empty_output><jupyter_text>Using saved data<jupyter_code>saved_data = ss.get_ydata()

figure, _ = plt.subplots(1, 2, figsize=(12, 2))

for data, ax in zip(saved_data, figure.get_axes()):
    ax.plot(x, data)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09396914446002805, 'fraction_numerical': 0.0070126227208976155, 'mean_word_length': 6.069306930693069, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '91038', 'license': 'MIT', 'n_tokens_mistral': 240, 'n_tokens_neox': 229, 'n_words': 80, 'path': 'examples/example.ipynb', 'repo_name': 'blbradley/subset-selector', 'size': '713'}