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Learning pandas - Second Edition by Michael Heydt

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Preparation

During preparation, raw data is made ready for exploration. This preparation is often a very interesting process. It is very frequently the case that data from is fraught with all kinds of issues related to quality. You will likely spend a lot of time dealing with these quality issues, and often this is a very non-trivial amount of time.

Why? Well there are a number of reasons:

  • The data is simply incorrect
  • Parts of the dataset are missing
  • Data is not represented using measurements appropriate for your analysis
  • The data is in formats not convenient for your analysis
  • Data is at a level of detail not appropriate for your analysis
  • Not all the fields you need are available from a single source
  • The representation of data differs depending ...

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