<jupyter_start><jupyter_text>Field<jupyter_code>f = mps.field()
f = mps.field(color="green",figsize=8)<jupyter_output><empty_output><jupyter_text>Heatmap<jupyter_code>ax = mps.field(show=False)
ax.scatter(x,y,s=2); plt.show()

matrix = mps.count(x,y,n=20,m=20)
hm = mps.heatmap(matrix)<jupyter_output><empty_output><jupyter_text>Actions<jupyter_code>start = 499604
delta = 13
for i in range(1):
    phase = actions[start+i*delta:start+delta+i*delta].copy()
    phase["team"] = phase.full_name
    phase["player"] = phase.soccer_name
    phase = phase[["team","player","time_seconds","type_name","result","start_x","start_y","end_x","end_y"]]

    # Full field
    mps.actions(phase,figsize = 8)

    ## Zoomed in
    mps.actions(phase[2:11],color="green",zoom=True,figsize=8)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18509316770186335, 'fraction_numerical': 0.024844720496894408, 'mean_word_length': 7.574468085106383, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '390655', 'license': 'MIT', 'n_tokens_mistral': 347, 'n_tokens_neox': 329, 'n_words': 33, 'path': 'experimental-notebooks/demo.ipynb', 'repo_name': 'TomDecroos/matplotsoccer', 'size': '805'}