<jupyter_start><jupyter_text>Unicode minusBy default, tick labels at negative values are rendered using a `Unicodeminus`__ (U+2212) rather than an ASCII hyphen (U+002D).  This can be controlledby setting :rc:`axes.unicode_minus`.__ https://en.wikipedia.org/wiki/Plus_and_minus_signsCharacter_codesThe replacement is performed at draw time of the tick labels (usually during a`.pyplot.show()` or `.pyplot.savefig()` call). Therefore, all tick labels ofthe figure follow the same setting and we cannot demonstrate both glyphs onreal tick labels of the same figure simultaneously.Instead, this example simply showcases the difference between the two glyphsin a magnified font.<jupyter_code>import matplotlib.pyplot as plt

fig = plt.figure(figsize=(4, 2))
fig.text(.15, .6, "Unicode minus:", fontsize=20)
fig.text(.85, .6, "\N{MINUS SIGN}1", ha='right', fontsize=20)
fig.text(.15, .3, "ASCII hyphen:", fontsize=20)
fig.text(.85, .3, "-1", ha='right', fontsize=20)
plt.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12187812187812187, 'fraction_numerical': 0.030969030969030968, 'mean_word_length': 5.958333333333333, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, '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': '482595', 'license': 'MIT', 'n_tokens_mistral': 343, 'n_tokens_neox': 316, 'n_words': 109, 'path': 'matplotlib/gallery_jupyter/text_labels_and_annotations/unicode_minus.ipynb', 'repo_name': 'kingreatwill/penter', 'size': '1001'}