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Currently we get as far as reading JSON into a deeply nested dict. In general data science is easier to do with dedicated data structures like Pandas dataframes and/or Numpy arrays.
Should we explicitly give examples of pulling down JSON data and turning it into a Pandas dataframe, and then doing some analysis on it?
Would it be useful to do the same for a CSV-returning API, potentially as a stepping stone to decoding JSON?
The text was updated successfully, but these errors were encountered:
Currently we get as far as reading JSON into a deeply nested
dict. In general data science is easier to do with dedicated data structures like Pandas dataframes and/or Numpy arrays.Should we explicitly give examples of pulling down JSON data and turning it into a Pandas dataframe, and then doing some analysis on it?
Would it be useful to do the same for a CSV-returning API, potentially as a stepping stone to decoding JSON?
The text was updated successfully, but these errors were encountered: