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# pandas.get_dummies

`pandas.``get_dummies`(data, prefix=None, prefix_sep='_', dummy_na=False)

  Convert categorical variable into dummy/indicator variables

  Parameters : | data : array-like or Series prefix : string, default None String to append DataFrame column names prefix_sep : string, default ‘_’ If appending prefix, separator/delimiter to use dummy_na : bool, default False Add a column to indicate NaNs, if False NaNs are ignored.
  Returns : | dummies : DataFrame

  Examples

      >>> import pandas as pd
      >>> s = pd.Series(list('abca'))

      >>> get_dummies(s)
         a  b  c
      0  1  0  0
      1  0  1  0
      2  0  0  1
      3  1  0  0

      >>> s1 = ['a', 'b', np.nan]

      >>> get_dummies(s1)
         a  b
      0  1  0
      1  0  1
      2  0  0

      >>> get_dummies(s1, dummy_na=True)
         a  b  NaN
      0  1  0    0
      1  0  1    0
      2  0  0    1

  See also `Series.str.get_dummies`.

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