<jupyter_start><jupyter_text>Análisis: Ocurrencia<jupyter_code>import pandas as pd
from techminer import RecordsDataFrame

rdf = RecordsDataFrame(
    pd.read_json(
        'part-07.json', 
        orient='records', 
        lines=True))<jupyter_output><empty_output><jupyter_text>Authors<jupyter_code>rdf.ocurrence(
    column='Authors', 
    sep=',', 
    top_n=20).tomatrix()
rdf.ocurrence(
    column='Authors', 
    sep=',', 
    top_n=20).heatmap(figsize=(10,8))
rdf.ocurrence(
    column='Authors', 
    sep=',', 
    top_n=20).ocurrence_map()<jupyter_output>/usr/local/lib/python3.6/dist-packages/networkx/drawing/nx_pylab.py:579: MatplotlibDeprecationWarning: 
The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.
  if not cb.iterable(width):<jupyter_text>Keywords<jupyter_code>rdf.ocurrence(
    column='keywords (cleaned)', 
    sep=';',
    top_n=20).tomatrix()
rdf.ocurrence(
    column='keywords (cleaned)', 
    sep=';',
    top_n=10).heatmap(figsize=(9,8))
rdf.ocurrence(
    column='keywords (cleaned)', 
    sep=';',
    top_n=20).heatmap(figsize=(11,10))
rdf.ocurrence(
    column='keywords (cleaned)', 
    sep=';',
    top_n=30).heatmap(figsize=(12,11))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15885623510722796, 'fraction_numerical': 0.030182684670373314, 'mean_word_length': 4.502183406113537, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, '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': '293445', 'license': 'MIT', 'n_tokens_mistral': 525, 'n_tokens_neox': 483, 'n_words': 66, 'path': 'part-12-ocurrence.ipynb', 'repo_name': 'juancamilo1203unal/CFIE-2019-charla', 'size': '1259'}