@@ -1209,20 +1209,68 @@ def from_records(cls, data, index=None, exclude=None, columns=None,
12091209
12101210 def to_records (self , index = True , convert_datetime64 = True ):
12111211 """
1212- Convert DataFrame to record array. Index will be put in the
1213- 'index' field of the record array if requested
1212+ Convert DataFrame to a NumPy record array.
1213+
1214+ Index will be put in the 'index' field of the record array if
1215+ requested.
12141216
12151217 Parameters
12161218 ----------
12171219 index : boolean, default True
1218- Include index in resulting record array, stored in 'index' field
1220+ Include index in resulting record array, stored in 'index' field.
12191221 convert_datetime64 : boolean, default True
12201222 Whether to convert the index to datetime.datetime if it is a
1221- DatetimeIndex
1223+ DatetimeIndex.
12221224
12231225 Returns
12241226 -------
1225- y : recarray
1227+ y : numpy.recarray
1228+
1229+ See Also
1230+ --------
1231+ DataFrame.from_records: convert structured or record ndarray
1232+ to DataFrame.
1233+ numpy.recarray: ndarray that allows field access using
1234+ attributes, analogous to typed columns in a
1235+ spreadsheet.
1236+
1237+ Examples
1238+ --------
1239+ >>> df = pd.DataFrame({'A': [1, 2], 'B': [0.5, 0.75]},
1240+ ... index=['a', 'b'])
1241+ >>> df
1242+ A B
1243+ a 1 0.50
1244+ b 2 0.75
1245+ >>> df.to_records()
1246+ rec.array([('a', 1, 0.5 ), ('b', 2, 0.75)],
1247+ dtype=[('index', 'O'), ('A', '<i8'), ('B', '<f8')])
1248+
1249+ The index can be excluded from the record array:
1250+
1251+ >>> df.to_records(index=False)
1252+ rec.array([(1, 0.5 ), (2, 0.75)],
1253+ dtype=[('A', '<i8'), ('B', '<f8')])
1254+
1255+ By default, timestamps are converted to `datetime.datetime`:
1256+
1257+ >>> df.index = pd.date_range('2018-01-01 09:00', periods=2, freq='min')
1258+ >>> df
1259+ A B
1260+ 2018-01-01 09:00:00 1 0.50
1261+ 2018-01-01 09:01:00 2 0.75
1262+ >>> df.to_records()
1263+ rec.array([(datetime.datetime(2018, 1, 1, 9, 0), 1, 0.5 ),
1264+ (datetime.datetime(2018, 1, 1, 9, 1), 2, 0.75)],
1265+ dtype=[('index', 'O'), ('A', '<i8'), ('B', '<f8')])
1266+
1267+ The timestamp conversion can be disabled so NumPy's datetime64
1268+ data type is used instead:
1269+
1270+ >>> df.to_records(convert_datetime64=False)
1271+ rec.array([('2018-01-01T09:00:00.000000000', 1, 0.5 ),
1272+ ('2018-01-01T09:01:00.000000000', 2, 0.75)],
1273+ dtype=[('index', '<M8[ns]'), ('A', '<i8'), ('B', '<f8')])
12261274 """
12271275 if index :
12281276 if is_datetime64_any_dtype (self .index ) and convert_datetime64 :
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