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May 12, 2020
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DOC: Examples for DataFrame.from_records #34058

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e25b01a
Added examples to DataFrame.from_records.
bdice May 7, 2020
015d0a7
Clarify allowable inputs to from_records.
bdice May 7, 2020
e54be87
Allow long type in flake8.
bdice May 7, 2020
30b8fce
Simplify wording.
bdice May 8, 2020
e2a86f5
Use "structured ndarray" as type description.
bdice May 8, 2020
6b22c25
Fix tabs/spaces from editor misconfiguration.
bdice May 8, 2020
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51 changes: 48 additions & 3 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1233,8 +1233,8 @@ def from_dict(cls, data, orient="columns", dtype=None, columns=None) -> "DataFra

See Also
--------
DataFrame.from_records : DataFrame from ndarray (structured
dtype), list of tuples, dict, or DataFrame.
DataFrame.from_records : DataFrame from structured ndarray, sequence
of tuples or dicts, or DataFrame.
DataFrame : DataFrame object creation using constructor.

Examples
Expand Down Expand Up @@ -1633,9 +1633,13 @@ def from_records(
"""
Convert structured or record ndarray to DataFrame.

Creates a DataFrame object from a structured ndarray, sequence of
tuples or dicts, or DataFrame.

Parameters
----------
data : ndarray (structured dtype), list of tuples, dict, or DataFrame
data : structured ndarray, sequence of tuples or dicts, or DataFrame
Structured input data.
index : str, list of fields, array-like
Field of array to use as the index, alternately a specific set of
input labels to use.
Expand All @@ -1656,6 +1660,47 @@ def from_records(
Returns
-------
DataFrame

See Also
--------
DataFrame.from_dict : DataFrame from dict of array-like or dicts.
DataFrame : DataFrame object creation using constructor.

Examples
--------
Data can be provided as a structured ndarray:

>>> data = np.array([(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')],
... dtype=[('col_1', 'i4'), ('col_2', 'U1')])
>>> pd.DataFrame.from_records(data)
col_1 col_2
0 3 a
1 2 b
2 1 c
3 0 d

Data can be provided as a list of dicts:

>>> data = [{'col_1': 3, 'col_2': 'a'},
... {'col_1': 2, 'col_2': 'b'},
... {'col_1': 1, 'col_2': 'c'},
... {'col_1': 0, 'col_2': 'd'}]
>>> pd.DataFrame.from_records(data)
col_1 col_2
0 3 a
1 2 b
2 1 c
3 0 d

Data can be provided as a list of tuples with corresponding columns:

>>> data = [(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')]
>>> pd.DataFrame.from_records(data, columns=['col_1', 'col_2'])
col_1 col_2
0 3 a
1 2 b
2 1 c
3 0 d
"""
# Make a copy of the input columns so we can modify it
if columns is not None:
Expand Down