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Showing content from http://pandas.pydata.org/pandas-docs/version/0.20/generated/pandas.get_dummies.html below:

pandas.get_dummies — pandas 0.20.3 documentation

data : array-like, Series, or DataFrame

prefix : string, list of strings, or dict of strings, default None

String to append DataFrame column names Pass a list with length equal to the number of columns when calling get_dummies on a DataFrame. Alternativly, prefix can be a dictionary mapping column names to prefixes.

prefix_sep : string, default ‘_’

If appending prefix, separator/delimiter to use. Or pass a list or dictionary as with prefix.

dummy_na : bool, default False

Add a column to indicate NaNs, if False NaNs are ignored.

columns : list-like, default None

Column names in the DataFrame to be encoded. If columns is None then all the columns with object or category dtype will be converted.

sparse : bool, default False

Whether the dummy columns should be sparse or not. Returns SparseDataFrame if data is a Series or if all columns are included. Otherwise returns a DataFrame with some SparseBlocks.

New in version 0.16.1.

drop_first : bool, default False

Whether to get k-1 dummies out of k categorical levels by removing the first level.

New in version 0.18.0.

Returns

——-

dummies : DataFrame or SparseDataFrame


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