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Kaggle

Data Cleaning

via Kaggle

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Overview

Master efficient workflows for cleaning real-world, messy data.
  • Drop missing values, or fill them in with an automated workflow.
  • Transform numeric variables to have helpful properties.
  • Help Python recognize dates as composed of day, month, and year.
  • Avoid UnicoodeDecodeErrors when loading CSV files.
  • Efficiently fix typos in your data.

Syllabus

  • Handling Missing Values
  • Scaling and Normalization
  • Parsing Dates
  • Character Encodings
  • Inconsistent Data Entry

Taught by

Rachael Tatman

Reviews

5.0 rating, based on 2 Class Central reviews

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  • Profile image for Abdul Majeed Noonari
    Abdul Majeed Noonari
    This Data Cleaning Course exceeded my expectations. I feel equipped with the knowledge and skills necessary to excel in data preparation and cleaning, which is critical in the data science and analytics field.
  • Avinash Kumar Yadav
    The course helps us understand the course Data cleaning steps and makes it more easier by the trying the same steps on our own with a different data set.
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