March 2019
Intermediate to advanced
256 pages
4h 57m
French
Content preview from Machine learning : les fondamentauxBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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CHAPITRE 5 Nettoyage des données
Pour vous aider à bien nettoyer les données, nous pouvons utiliser des outils génériques, comme ceux de pandas ou des outils spécialisés comme pyjanitor.
Renommage des colonnes
Il n’est pas inutile de rendre les noms des colonnes compatibles avec les conventions Python pour permettre un accès plus facile aux attributs avec pandas. Voyons la fonction clean_names de pyjanitor qui renvoie une structure DataFrame après avoir forcé les noms des colonnes et remplacé tous les espaces par des caractères de soulignement :
>>> import janitor as jn >>> Xbad = pd.DataFrame( ... { ... "A": [1, None, 3], ... " sales numbers ": [20.0, 30.0, None], ... } ... ) >>> jn.clean_names(Xbad) a _sales_numbers_ 0 1.0 20.0 1 NaN 30.0 2 3.0 ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.