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# -*- coding: utf-8 -*-
from __future__ import division, print_function, absolute_import
import inspect
from petl.util.base import Table
def todataframe(table, index=None, exclude=None, columns=None,
coerce_float=False, nrows=None):
"""
Load data from the given `table` into a
`pandas <http://pandas.pydata.org/>`_ DataFrame. E.g.::
>>> import petl as etl
>>> table = [('foo', 'bar', 'baz'),
... ('apples', 1, 2.5),
... ('oranges', 3, 4.4),
... ('pears', 7, .1)]
>>> df = etl.todataframe(table)
>>> df
foo bar baz
0 apples 1 2.5
1 oranges 3 4.4
2 pears 7 0.1
"""
import pandas as pd
it = iter(table)
try:
header = next(it)
except StopIteration:
header = None # Will create an Empty DataFrame
if columns is None:
columns = header
return pd.DataFrame.from_records(it, index=index, exclude=exclude,
columns=columns, coerce_float=coerce_float,
nrows=nrows)
Table.todataframe = todataframe
Table.todf = todataframe
def fromdataframe(df, include_index=False):
"""
Extract a table from a `pandas <http://pandas.pydata.org/>`_ DataFrame.
E.g.::
>>> import petl as etl
>>> import pandas as pd
>>> records = [('apples', 1, 2.5), ('oranges', 3, 4.4), ('pears', 7, 0.1)]
>>> df = pd.DataFrame.from_records(records, columns=('foo', 'bar', 'baz'))
>>> table = etl.fromdataframe(df)
>>> table
+-----------+-----+-----+
| foo | bar | baz |
+===========+=====+=====+
| 'apples' | 1 | 2.5 |
+-----------+-----+-----+
| 'oranges' | 3 | 4.4 |
+-----------+-----+-----+
| 'pears' | 7 | 0.1 |
+-----------+-----+-----+
"""
return DataFrameView(df, include_index=include_index)
class DataFrameView(Table):
def __init__(self, df, include_index=False):
assert hasattr(df, 'columns') \
and hasattr(df, 'iterrows') \
and inspect.ismethod(df.iterrows), \
'bad argument, expected pandas.DataFrame, found %r' % df
self.df = df
self.include_index = include_index
def __iter__(self):
if self.include_index:
yield ('index',) + tuple(self.df.columns)
for i, row in self.df.iterrows():
yield (i,) + tuple(row)
else:
yield tuple(self.df.columns)
for _, row in self.df.iterrows():
yield tuple(row)
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