<jupyter_start><jupyter_text>Análisis Exploratorio de Datos===**<NAME>**  <EMAIL>   Universidad Nacional de Colombia, Sede Medellín  Facultad de Minas  Medellín, Colombia---Haga click [aquí](https://github.com/jdvelasq/Python-for-descriptive-analytics/tree/master/) para acceder al repositorio online.Haga click [aquí](http://nbviewer.jupyter.org/github/jdvelasq/Python-for-descriptive-analytics/tree/master/) para explorar el repositorio usando `nbviewer`.  --- Haga click [aquí](https://github.com/jdvelasq/statistics-for-analytics/blob/master/04-analisis-exploratorio.ipynb) para acceder a un documento conceptual sobre análisis exploratorio de datos. --- **Preparación de los datos**.<jupyter_code>import pandas as pd
df = pd.read_csv('files/indicadores-mundiales.csv', encoding='latin-1')
df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1332533013205282, 'fraction_numerical': 0.003601440576230492, 'mean_word_length': 5.892561983471074, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 2, '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': '195897', 'license': 'MIT', 'n_tokens_mistral': 304, 'n_tokens_neox': 293, 'n_words': 56, 'path': '01-analisis-exploratorio.ipynb', 'repo_name': 'hagarciag/Python-for-descriptive-analytics', 'size': '866'}