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test_excel.py
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test_excel.py
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# pylint: disable=E1101
import os
import warnings
from datetime import datetime, date, time, timedelta
from distutils.version import LooseVersion
from functools import partial
from warnings import catch_warnings
from collections import OrderedDict
import numpy as np
import pytest
from numpy import nan
import pandas as pd
import pandas.util.testing as tm
import pandas.util._test_decorators as td
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import u, range, map, BytesIO, iteritems, PY36
from pandas.core.config import set_option, get_option
from pandas.io.common import URLError
from pandas.io.excel import (
ExcelFile, ExcelWriter, read_excel, _XlwtWriter, _OpenpyxlWriter,
register_writer, _XlsxWriter
)
from pandas.io.formats.excel import ExcelFormatter
from pandas.io.parsers import read_csv
from pandas.util.testing import ensure_clean, makeCustomDataframe as mkdf
_seriesd = tm.getSeriesData()
_tsd = tm.getTimeSeriesData()
_frame = DataFrame(_seriesd)[:10]
_frame2 = DataFrame(_seriesd, columns=['D', 'C', 'B', 'A'])[:10]
_tsframe = tm.makeTimeDataFrame()[:5]
_mixed_frame = _frame.copy()
_mixed_frame['foo'] = 'bar'
@td.skip_if_no('xlrd', '0.9')
class SharedItems(object):
@pytest.fixture(autouse=True)
def setup_method(self, datapath):
self.dirpath = datapath("io", "data")
self.frame = _frame.copy()
self.frame2 = _frame2.copy()
self.tsframe = _tsframe.copy()
self.mixed_frame = _mixed_frame.copy()
def get_csv_refdf(self, basename):
"""
Obtain the reference data from read_csv with the Python engine.
Parameters
----------
basename : str
File base name, excluding file extension.
Returns
-------
dfref : DataFrame
"""
pref = os.path.join(self.dirpath, basename + '.csv')
dfref = read_csv(pref, index_col=0, parse_dates=True, engine='python')
return dfref
def get_excelfile(self, basename, ext):
"""
Return test data ExcelFile instance.
Parameters
----------
basename : str
File base name, excluding file extension.
Returns
-------
excel : io.excel.ExcelFile
"""
return ExcelFile(os.path.join(self.dirpath, basename + ext))
def get_exceldf(self, basename, ext, *args, **kwds):
"""
Return test data DataFrame.
Parameters
----------
basename : str
File base name, excluding file extension.
Returns
-------
df : DataFrame
"""
pth = os.path.join(self.dirpath, basename + ext)
return read_excel(pth, *args, **kwds)
class ReadingTestsBase(SharedItems):
# This is based on ExcelWriterBase
def test_usecols_int(self, ext):
dfref = self.get_csv_refdf('test1')
dfref = dfref.reindex(columns=['A', 'B', 'C'])
df1 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0, usecols=3)
df2 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, usecols=3)
with tm.assert_produces_warning(FutureWarning):
df3 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, parse_cols=3)
# TODO add index to xls file)
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
tm.assert_frame_equal(df3, dfref, check_names=False)
def test_usecols_list(self, ext):
dfref = self.get_csv_refdf('test1')
dfref = dfref.reindex(columns=['B', 'C'])
df1 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0,
usecols=[0, 2, 3])
df2 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, usecols=[0, 2, 3])
with tm.assert_produces_warning(FutureWarning):
df3 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, parse_cols=[0, 2, 3])
# TODO add index to xls file)
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
tm.assert_frame_equal(df3, dfref, check_names=False)
def test_usecols_str(self, ext):
dfref = self.get_csv_refdf('test1')
df1 = dfref.reindex(columns=['A', 'B', 'C'])
df2 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0,
usecols='A:D')
df3 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, usecols='A:D')
with tm.assert_produces_warning(FutureWarning):
df4 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, parse_cols='A:D')
# TODO add index to xls, read xls ignores index name ?
tm.assert_frame_equal(df2, df1, check_names=False)
tm.assert_frame_equal(df3, df1, check_names=False)
tm.assert_frame_equal(df4, df1, check_names=False)
df1 = dfref.reindex(columns=['B', 'C'])
df2 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0,
usecols='A,C,D')
df3 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, usecols='A,C,D')
# TODO add index to xls file
tm.assert_frame_equal(df2, df1, check_names=False)
tm.assert_frame_equal(df3, df1, check_names=False)
df1 = dfref.reindex(columns=['B', 'C'])
df2 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0,
usecols='A,C:D')
df3 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0, usecols='A,C:D')
tm.assert_frame_equal(df2, df1, check_names=False)
tm.assert_frame_equal(df3, df1, check_names=False)
def test_excel_stop_iterator(self, ext):
parsed = self.get_exceldf('test2', ext, 'Sheet1')
expected = DataFrame([['aaaa', 'bbbbb']], columns=['Test', 'Test1'])
tm.assert_frame_equal(parsed, expected)
def test_excel_cell_error_na(self, ext):
parsed = self.get_exceldf('test3', ext, 'Sheet1')
expected = DataFrame([[np.nan]], columns=['Test'])
tm.assert_frame_equal(parsed, expected)
def test_excel_passes_na(self, ext):
excel = self.get_excelfile('test4', ext)
parsed = read_excel(excel, 'Sheet1', keep_default_na=False,
na_values=['apple'])
expected = DataFrame([['NA'], [1], ['NA'], [np.nan], ['rabbit']],
columns=['Test'])
tm.assert_frame_equal(parsed, expected)
parsed = read_excel(excel, 'Sheet1', keep_default_na=True,
na_values=['apple'])
expected = DataFrame([[np.nan], [1], [np.nan], [np.nan], ['rabbit']],
columns=['Test'])
tm.assert_frame_equal(parsed, expected)
# 13967
excel = self.get_excelfile('test5', ext)
parsed = read_excel(excel, 'Sheet1', keep_default_na=False,
na_values=['apple'])
expected = DataFrame([['1.#QNAN'], [1], ['nan'], [np.nan], ['rabbit']],
columns=['Test'])
tm.assert_frame_equal(parsed, expected)
parsed = read_excel(excel, 'Sheet1', keep_default_na=True,
na_values=['apple'])
expected = DataFrame([[np.nan], [1], [np.nan], [np.nan], ['rabbit']],
columns=['Test'])
tm.assert_frame_equal(parsed, expected)
def test_excel_table_sheet_by_index(self, ext):
excel = self.get_excelfile('test1', ext)
dfref = self.get_csv_refdf('test1')
df1 = read_excel(excel, 0, index_col=0)
df2 = read_excel(excel, 1, skiprows=[1], index_col=0)
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
df1 = excel.parse(0, index_col=0)
df2 = excel.parse(1, skiprows=[1], index_col=0)
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
df3 = read_excel(excel, 0, index_col=0, skipfooter=1)
tm.assert_frame_equal(df3, df1.iloc[:-1])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
df4 = read_excel(excel, 0, index_col=0, skip_footer=1)
tm.assert_frame_equal(df3, df4)
df3 = excel.parse(0, index_col=0, skipfooter=1)
tm.assert_frame_equal(df3, df1.iloc[:-1])
import xlrd
with pytest.raises(xlrd.XLRDError):
read_excel(excel, 'asdf')
def test_excel_table(self, ext):
dfref = self.get_csv_refdf('test1')
df1 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0)
df2 = self.get_exceldf('test1', ext, 'Sheet2', skiprows=[1],
index_col=0)
# TODO add index to file
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
df3 = self.get_exceldf('test1', ext, 'Sheet1', index_col=0,
skipfooter=1)
tm.assert_frame_equal(df3, df1.iloc[:-1])
def test_reader_special_dtypes(self, ext):
expected = DataFrame.from_dict(OrderedDict([
("IntCol", [1, 2, -3, 4, 0]),
("FloatCol", [1.25, 2.25, 1.83, 1.92, 0.0000000005]),
("BoolCol", [True, False, True, True, False]),
("StrCol", [1, 2, 3, 4, 5]),
# GH5394 - this is why convert_float isn't vectorized
("Str2Col", ["a", 3, "c", "d", "e"]),
("DateCol", [datetime(2013, 10, 30), datetime(2013, 10, 31),
datetime(1905, 1, 1), datetime(2013, 12, 14),
datetime(2015, 3, 14)])
]))
basename = 'test_types'
# should read in correctly and infer types
actual = self.get_exceldf(basename, ext, 'Sheet1')
tm.assert_frame_equal(actual, expected)
# if not coercing number, then int comes in as float
float_expected = expected.copy()
float_expected["IntCol"] = float_expected["IntCol"].astype(float)
float_expected.loc[float_expected.index[1], "Str2Col"] = 3.0
actual = self.get_exceldf(basename, ext, 'Sheet1', convert_float=False)
tm.assert_frame_equal(actual, float_expected)
# check setting Index (assuming xls and xlsx are the same here)
for icol, name in enumerate(expected.columns):
actual = self.get_exceldf(basename, ext, 'Sheet1', index_col=icol)
exp = expected.set_index(name)
tm.assert_frame_equal(actual, exp)
# convert_float and converters should be different but both accepted
expected["StrCol"] = expected["StrCol"].apply(str)
actual = self.get_exceldf(
basename, ext, 'Sheet1', converters={"StrCol": str})
tm.assert_frame_equal(actual, expected)
no_convert_float = float_expected.copy()
no_convert_float["StrCol"] = no_convert_float["StrCol"].apply(str)
actual = self.get_exceldf(basename, ext, 'Sheet1', convert_float=False,
converters={"StrCol": str})
tm.assert_frame_equal(actual, no_convert_float)
# GH8212 - support for converters and missing values
def test_reader_converters(self, ext):
basename = 'test_converters'
expected = DataFrame.from_dict(OrderedDict([
("IntCol", [1, 2, -3, -1000, 0]),
("FloatCol", [12.5, np.nan, 18.3, 19.2, 0.000000005]),
("BoolCol", ['Found', 'Found', 'Found', 'Not found', 'Found']),
("StrCol", ['1', np.nan, '3', '4', '5']),
]))
converters = {'IntCol': lambda x: int(x) if x != '' else -1000,
'FloatCol': lambda x: 10 * x if x else np.nan,
2: lambda x: 'Found' if x != '' else 'Not found',
3: lambda x: str(x) if x else '',
}
# should read in correctly and set types of single cells (not array
# dtypes)
actual = self.get_exceldf(basename, ext, 'Sheet1',
converters=converters)
tm.assert_frame_equal(actual, expected)
def test_reader_dtype(self, ext):
# GH 8212
basename = 'testdtype'
actual = self.get_exceldf(basename, ext)
expected = DataFrame({
'a': [1, 2, 3, 4],
'b': [2.5, 3.5, 4.5, 5.5],
'c': [1, 2, 3, 4],
'd': [1.0, 2.0, np.nan, 4.0]}).reindex(
columns=['a', 'b', 'c', 'd'])
tm.assert_frame_equal(actual, expected)
actual = self.get_exceldf(basename, ext,
dtype={'a': 'float64',
'b': 'float32',
'c': str})
expected['a'] = expected['a'].astype('float64')
expected['b'] = expected['b'].astype('float32')
expected['c'] = ['001', '002', '003', '004']
tm.assert_frame_equal(actual, expected)
with pytest.raises(ValueError):
actual = self.get_exceldf(basename, ext, dtype={'d': 'int64'})
def test_reading_all_sheets(self, ext):
# Test reading all sheetnames by setting sheetname to None,
# Ensure a dict is returned.
# See PR #9450
basename = 'test_multisheet'
dfs = self.get_exceldf(basename, ext, sheet_name=None)
# ensure this is not alphabetical to test order preservation
expected_keys = ['Charlie', 'Alpha', 'Beta']
tm.assert_contains_all(expected_keys, dfs.keys())
# Issue 9930
# Ensure sheet order is preserved
assert expected_keys == list(dfs.keys())
def test_reading_multiple_specific_sheets(self, ext):
# Test reading specific sheetnames by specifying a mixed list
# of integers and strings, and confirm that duplicated sheet
# references (positions/names) are removed properly.
# Ensure a dict is returned
# See PR #9450
basename = 'test_multisheet'
# Explicitly request duplicates. Only the set should be returned.
expected_keys = [2, 'Charlie', 'Charlie']
dfs = self.get_exceldf(basename, ext, sheet_name=expected_keys)
expected_keys = list(set(expected_keys))
tm.assert_contains_all(expected_keys, dfs.keys())
assert len(expected_keys) == len(dfs.keys())
def test_reading_all_sheets_with_blank(self, ext):
# Test reading all sheetnames by setting sheetname to None,
# In the case where some sheets are blank.
# Issue #11711
basename = 'blank_with_header'
dfs = self.get_exceldf(basename, ext, sheet_name=None)
expected_keys = ['Sheet1', 'Sheet2', 'Sheet3']
tm.assert_contains_all(expected_keys, dfs.keys())
# GH6403
def test_read_excel_blank(self, ext):
actual = self.get_exceldf('blank', ext, 'Sheet1')
tm.assert_frame_equal(actual, DataFrame())
def test_read_excel_blank_with_header(self, ext):
expected = DataFrame(columns=['col_1', 'col_2'])
actual = self.get_exceldf('blank_with_header', ext, 'Sheet1')
tm.assert_frame_equal(actual, expected)
@td.skip_if_no('openpyxl')
@td.skip_if_no('xlwt')
# GH 12292 : error when read one empty column from excel file
def test_read_one_empty_col_no_header(self, ext):
df = pd.DataFrame(
[["", 1, 100],
["", 2, 200],
["", 3, 300],
["", 4, 400]]
)
with ensure_clean(ext) as path:
df.to_excel(path, 'no_header', index=False, header=False)
actual_header_none = read_excel(
path,
'no_header',
usecols=[0],
header=None
)
actual_header_zero = read_excel(
path,
'no_header',
usecols=[0],
header=0
)
expected = DataFrame()
tm.assert_frame_equal(actual_header_none, expected)
tm.assert_frame_equal(actual_header_zero, expected)
@td.skip_if_no('openpyxl')
@td.skip_if_no('xlwt')
def test_read_one_empty_col_with_header(self, ext):
df = pd.DataFrame(
[["", 1, 100],
["", 2, 200],
["", 3, 300],
["", 4, 400]]
)
with ensure_clean(ext) as path:
df.to_excel(path, 'with_header', index=False, header=True)
actual_header_none = read_excel(
path,
'with_header',
usecols=[0],
header=None
)
actual_header_zero = read_excel(
path,
'with_header',
usecols=[0],
header=0
)
expected_header_none = DataFrame(pd.Series([0], dtype='int64'))
tm.assert_frame_equal(actual_header_none, expected_header_none)
expected_header_zero = DataFrame(columns=[0])
tm.assert_frame_equal(actual_header_zero, expected_header_zero)
@td.skip_if_no('openpyxl')
@td.skip_if_no('xlwt')
def test_set_column_names_in_parameter(self, ext):
# GH 12870 : pass down column names associated with
# keyword argument names
refdf = pd.DataFrame([[1, 'foo'], [2, 'bar'],
[3, 'baz']], columns=['a', 'b'])
with ensure_clean(ext) as pth:
with ExcelWriter(pth) as writer:
refdf.to_excel(writer, 'Data_no_head',
header=False, index=False)
refdf.to_excel(writer, 'Data_with_head', index=False)
refdf.columns = ['A', 'B']
with ExcelFile(pth) as reader:
xlsdf_no_head = read_excel(reader, 'Data_no_head',
header=None, names=['A', 'B'])
xlsdf_with_head = read_excel(reader, 'Data_with_head',
index_col=None, names=['A', 'B'])
tm.assert_frame_equal(xlsdf_no_head, refdf)
tm.assert_frame_equal(xlsdf_with_head, refdf)
def test_date_conversion_overflow(self, ext):
# GH 10001 : pandas.ExcelFile ignore parse_dates=False
expected = pd.DataFrame([[pd.Timestamp('2016-03-12'), 'Marc Johnson'],
[pd.Timestamp('2016-03-16'), 'Jack Black'],
[1e+20, 'Timothy Brown']],
columns=['DateColWithBigInt', 'StringCol'])
result = self.get_exceldf('testdateoverflow', ext)
tm.assert_frame_equal(result, expected)
def test_sheet_name_and_sheetname(self, ext):
# GH10559: Minor improvement: Change "sheet_name" to "sheetname"
# GH10969: DOC: Consistent var names (sheetname vs sheet_name)
# GH12604: CLN GH10559 Rename sheetname variable to sheet_name
# GH20920: ExcelFile.parse() and pd.read_xlsx() have different
# behavior for "sheetname" argument
dfref = self.get_csv_refdf('test1')
df1 = self.get_exceldf('test1', ext,
sheet_name='Sheet1') # doc
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
df2 = self.get_exceldf('test1', ext,
sheetname='Sheet1') # bkwrd compat
excel = self.get_excelfile('test1', ext)
df1_parse = excel.parse(sheet_name='Sheet1') # doc
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
df2_parse = excel.parse(sheetname='Sheet1') # bkwrd compat
tm.assert_frame_equal(df1, dfref, check_names=False)
tm.assert_frame_equal(df2, dfref, check_names=False)
tm.assert_frame_equal(df1_parse, dfref, check_names=False)
tm.assert_frame_equal(df2_parse, dfref, check_names=False)
def test_sheet_name_both_raises(self, ext):
with tm.assert_raises_regex(TypeError, "Cannot specify both"):
self.get_exceldf('test1', ext, sheetname='Sheet1',
sheet_name='Sheet1')
excel = self.get_excelfile('test1', ext)
with tm.assert_raises_regex(TypeError, "Cannot specify both"):
excel.parse(sheetname='Sheet1',
sheet_name='Sheet1')
@pytest.mark.parametrize("ext", ['.xls', '.xlsx', '.xlsm'])
class TestXlrdReader(ReadingTestsBase):
"""
This is the base class for the xlrd tests, and 3 different file formats
are supported: xls, xlsx, xlsm
"""
def test_excel_read_buffer(self, ext):
pth = os.path.join(self.dirpath, 'test1' + ext)
expected = read_excel(pth, 'Sheet1', index_col=0)
with open(pth, 'rb') as f:
actual = read_excel(f, 'Sheet1', index_col=0)
tm.assert_frame_equal(expected, actual)
with open(pth, 'rb') as f:
xls = ExcelFile(f)
actual = read_excel(xls, 'Sheet1', index_col=0)
tm.assert_frame_equal(expected, actual)
@td.skip_if_no('xlwt')
def test_read_xlrd_Book(self, ext):
import xlrd
df = self.frame
with ensure_clean('.xls') as pth:
df.to_excel(pth, "SheetA")
book = xlrd.open_workbook(pth)
with ExcelFile(book, engine="xlrd") as xl:
result = read_excel(xl, "SheetA")
tm.assert_frame_equal(df, result)
result = read_excel(book, sheet_name="SheetA", engine="xlrd")
tm.assert_frame_equal(df, result)
@tm.network
def test_read_from_http_url(self, ext):
url = ('https://raw.github.com/pandas-dev/pandas/master/'
'pandas/tests/io/data/test1' + ext)
url_table = read_excel(url)
local_table = self.get_exceldf('test1', ext)
tm.assert_frame_equal(url_table, local_table)
@td.skip_if_no('s3fs')
def test_read_from_s3_url(self, ext):
boto3 = pytest.importorskip('boto3')
moto = pytest.importorskip('moto')
with moto.mock_s3():
conn = boto3.resource("s3", region_name="us-east-1")
conn.create_bucket(Bucket="pandas-test")
file_name = os.path.join(self.dirpath, 'test1' + ext)
with open(file_name, 'rb') as f:
conn.Bucket("pandas-test").put_object(Key="test1" + ext,
Body=f)
url = ('s3://pandas-test/test1' + ext)
url_table = read_excel(url)
local_table = self.get_exceldf('test1', ext)
tm.assert_frame_equal(url_table, local_table)
@pytest.mark.slow
def test_read_from_file_url(self, ext):
# FILE
localtable = os.path.join(self.dirpath, 'test1' + ext)
local_table = read_excel(localtable)
try:
url_table = read_excel('file://localhost/' + localtable)
except URLError:
# fails on some systems
import platform
pytest.skip("failing on %s" %
' '.join(platform.uname()).strip())
tm.assert_frame_equal(url_table, local_table)
@td.skip_if_no('pathlib')
def test_read_from_pathlib_path(self, ext):
# GH12655
from pathlib import Path
str_path = os.path.join(self.dirpath, 'test1' + ext)
expected = read_excel(str_path, 'Sheet1', index_col=0)
path_obj = Path(self.dirpath, 'test1' + ext)
actual = read_excel(path_obj, 'Sheet1', index_col=0)
tm.assert_frame_equal(expected, actual)
@td.skip_if_no('py.path')
def test_read_from_py_localpath(self, ext):
# GH12655
from py.path import local as LocalPath
str_path = os.path.join(self.dirpath, 'test1' + ext)
expected = read_excel(str_path, 'Sheet1', index_col=0)
abs_dir = os.path.abspath(self.dirpath)
path_obj = LocalPath(abs_dir).join('test1' + ext)
actual = read_excel(path_obj, 'Sheet1', index_col=0)
tm.assert_frame_equal(expected, actual)
def test_reader_closes_file(self, ext):
pth = os.path.join(self.dirpath, 'test1' + ext)
f = open(pth, 'rb')
with ExcelFile(f) as xlsx:
# parses okay
read_excel(xlsx, 'Sheet1', index_col=0)
assert f.closed
@td.skip_if_no('openpyxl')
@td.skip_if_no('xlwt')
def test_creating_and_reading_multiple_sheets(self, ext):
# Test reading multiple sheets, from a runtime created excel file
# with multiple sheets.
# See PR #9450
def tdf(sheetname):
d, i = [11, 22, 33], [1, 2, 3]
return DataFrame(d, i, columns=[sheetname])
sheets = ['AAA', 'BBB', 'CCC']
dfs = [tdf(s) for s in sheets]
dfs = dict(zip(sheets, dfs))
with ensure_clean(ext) as pth:
with ExcelWriter(pth) as ew:
for sheetname, df in iteritems(dfs):
df.to_excel(ew, sheetname)
dfs_returned = read_excel(pth, sheet_name=sheets)
for s in sheets:
tm.assert_frame_equal(dfs[s], dfs_returned[s])
def test_reader_seconds(self, ext):
import xlrd
# Test reading times with and without milliseconds. GH5945.
if LooseVersion(xlrd.__VERSION__) >= LooseVersion("0.9.3"):
# Xlrd >= 0.9.3 can handle Excel milliseconds.
expected = DataFrame.from_dict({"Time": [time(1, 2, 3),
time(2, 45, 56, 100000),
time(4, 29, 49, 200000),
time(6, 13, 42, 300000),
time(7, 57, 35, 400000),
time(9, 41, 28, 500000),
time(11, 25, 21, 600000),
time(13, 9, 14, 700000),
time(14, 53, 7, 800000),
time(16, 37, 0, 900000),
time(18, 20, 54)]})
else:
# Xlrd < 0.9.3 rounds Excel milliseconds.
expected = DataFrame.from_dict({"Time": [time(1, 2, 3),
time(2, 45, 56),
time(4, 29, 49),
time(6, 13, 42),
time(7, 57, 35),
time(9, 41, 29),
time(11, 25, 22),
time(13, 9, 15),
time(14, 53, 8),
time(16, 37, 1),
time(18, 20, 54)]})
actual = self.get_exceldf('times_1900', ext, 'Sheet1')
tm.assert_frame_equal(actual, expected)
actual = self.get_exceldf('times_1904', ext, 'Sheet1')
tm.assert_frame_equal(actual, expected)
def test_read_excel_multiindex(self, ext):
# GH 4679
mi = MultiIndex.from_product([['foo', 'bar'], ['a', 'b']])
mi_file = os.path.join(self.dirpath, 'testmultiindex' + ext)
expected = DataFrame([[1, 2.5, pd.Timestamp('2015-01-01'), True],
[2, 3.5, pd.Timestamp('2015-01-02'), False],
[3, 4.5, pd.Timestamp('2015-01-03'), False],
[4, 5.5, pd.Timestamp('2015-01-04'), True]],
columns=mi)
actual = read_excel(mi_file, 'mi_column', header=[0, 1])
tm.assert_frame_equal(actual, expected)
actual = read_excel(mi_file, 'mi_column', header=[0, 1], index_col=0)
tm.assert_frame_equal(actual, expected)
expected.columns = ['a', 'b', 'c', 'd']
expected.index = mi
actual = read_excel(mi_file, 'mi_index', index_col=[0, 1])
tm.assert_frame_equal(actual, expected, check_names=False)
expected.columns = mi
actual = read_excel(mi_file, 'both', index_col=[0, 1], header=[0, 1])
tm.assert_frame_equal(actual, expected, check_names=False)
expected.index = mi.set_names(['ilvl1', 'ilvl2'])
expected.columns = ['a', 'b', 'c', 'd']
actual = read_excel(mi_file, 'mi_index_name', index_col=[0, 1])
tm.assert_frame_equal(actual, expected)
expected.index = list(range(4))
expected.columns = mi.set_names(['c1', 'c2'])
actual = read_excel(mi_file, 'mi_column_name',
header=[0, 1], index_col=0)
tm.assert_frame_equal(actual, expected)
# Issue #11317
expected.columns = mi.set_levels(
[1, 2], level=1).set_names(['c1', 'c2'])
actual = read_excel(mi_file, 'name_with_int',
index_col=0, header=[0, 1])
tm.assert_frame_equal(actual, expected)
expected.columns = mi.set_names(['c1', 'c2'])
expected.index = mi.set_names(['ilvl1', 'ilvl2'])
actual = read_excel(mi_file, 'both_name',
index_col=[0, 1], header=[0, 1])
tm.assert_frame_equal(actual, expected)
actual = read_excel(mi_file, 'both_name',
index_col=[0, 1], header=[0, 1])
tm.assert_frame_equal(actual, expected)
actual = read_excel(mi_file, 'both_name_skiprows', index_col=[0, 1],
header=[0, 1], skiprows=2)
tm.assert_frame_equal(actual, expected)
@td.skip_if_no('xlsxwriter')
def test_read_excel_multiindex_empty_level(self, ext):
# GH 12453
with ensure_clean('.xlsx') as path:
df = DataFrame({
('One', 'x'): {0: 1},
('Two', 'X'): {0: 3},
('Two', 'Y'): {0: 7},
('Zero', ''): {0: 0}
})
expected = DataFrame({
('One', u'x'): {0: 1},
('Two', u'X'): {0: 3},
('Two', u'Y'): {0: 7},
('Zero', 'Unnamed: 3_level_1'): {0: 0}
})
df.to_excel(path)
actual = pd.read_excel(path, header=[0, 1])
tm.assert_frame_equal(actual, expected)
df = pd.DataFrame({
('Beg', ''): {0: 0},
('Middle', 'x'): {0: 1},
('Tail', 'X'): {0: 3},
('Tail', 'Y'): {0: 7}
})
expected = pd.DataFrame({
('Beg', 'Unnamed: 0_level_1'): {0: 0},
('Middle', u'x'): {0: 1},
('Tail', u'X'): {0: 3},
('Tail', u'Y'): {0: 7}
})
df.to_excel(path)
actual = pd.read_excel(path, header=[0, 1])
tm.assert_frame_equal(actual, expected)
@td.skip_if_no('xlsxwriter')
def test_excel_multindex_roundtrip(self, ext):
# GH 4679
with ensure_clean('.xlsx') as pth:
for c_idx_names in [True, False]:
for r_idx_names in [True, False]:
for c_idx_levels in [1, 3]:
for r_idx_levels in [1, 3]:
# column index name can't be serialized unless
# MultiIndex
if (c_idx_levels == 1 and c_idx_names):
continue
# empty name case current read in as unnamed
# levels, not Nones
check_names = True
if not r_idx_names and r_idx_levels > 1:
check_names = False
df = mkdf(5, 5, c_idx_names,
r_idx_names, c_idx_levels,
r_idx_levels)
df.to_excel(pth)
act = pd.read_excel(
pth, index_col=list(range(r_idx_levels)),
header=list(range(c_idx_levels)))
tm.assert_frame_equal(
df, act, check_names=check_names)
df.iloc[0, :] = np.nan
df.to_excel(pth)
act = pd.read_excel(
pth, index_col=list(range(r_idx_levels)),
header=list(range(c_idx_levels)))
tm.assert_frame_equal(
df, act, check_names=check_names)
df.iloc[-1, :] = np.nan
df.to_excel(pth)
act = pd.read_excel(
pth, index_col=list(range(r_idx_levels)),
header=list(range(c_idx_levels)))
tm.assert_frame_equal(
df, act, check_names=check_names)
def test_excel_old_index_format(self, ext):
# see gh-4679
filename = 'test_index_name_pre17' + ext
in_file = os.path.join(self.dirpath, filename)
# We detect headers to determine if index names exist, so
# that "index" name in the "names" version of the data will
# now be interpreted as rows that include null data.
data = np.array([[None, None, None, None, None],
['R0C0', 'R0C1', 'R0C2', 'R0C3', 'R0C4'],
['R1C0', 'R1C1', 'R1C2', 'R1C3', 'R1C4'],
['R2C0', 'R2C1', 'R2C2', 'R2C3', 'R2C4'],
['R3C0', 'R3C1', 'R3C2', 'R3C3', 'R3C4'],
['R4C0', 'R4C1', 'R4C2', 'R4C3', 'R4C4']])
columns = ['C_l0_g0', 'C_l0_g1', 'C_l0_g2', 'C_l0_g3', 'C_l0_g4']
mi = MultiIndex(levels=[['R0', 'R_l0_g0', 'R_l0_g1',
'R_l0_g2', 'R_l0_g3', 'R_l0_g4'],
['R1', 'R_l1_g0', 'R_l1_g1',
'R_l1_g2', 'R_l1_g3', 'R_l1_g4']],
labels=[[0, 1, 2, 3, 4, 5], [0, 1, 2, 3, 4, 5]],
names=[None, None])
si = Index(['R0', 'R_l0_g0', 'R_l0_g1', 'R_l0_g2',
'R_l0_g3', 'R_l0_g4'], name=None)
expected = pd.DataFrame(data, index=si, columns=columns)
actual = pd.read_excel(in_file, 'single_names')
tm.assert_frame_equal(actual, expected)
expected.index = mi
actual = pd.read_excel(in_file, 'multi_names')
tm.assert_frame_equal(actual, expected)
# The analogous versions of the "names" version data
# where there are explicitly no names for the indices.
data = np.array([['R0C0', 'R0C1', 'R0C2', 'R0C3', 'R0C4'],
['R1C0', 'R1C1', 'R1C2', 'R1C3', 'R1C4'],
['R2C0', 'R2C1', 'R2C2', 'R2C3', 'R2C4'],
['R3C0', 'R3C1', 'R3C2', 'R3C3', 'R3C4'],
['R4C0', 'R4C1', 'R4C2', 'R4C3', 'R4C4']])
columns = ['C_l0_g0', 'C_l0_g1', 'C_l0_g2', 'C_l0_g3', 'C_l0_g4']
mi = MultiIndex(levels=[['R_l0_g0', 'R_l0_g1', 'R_l0_g2',
'R_l0_g3', 'R_l0_g4'],
['R_l1_g0', 'R_l1_g1', 'R_l1_g2',
'R_l1_g3', 'R_l1_g4']],
labels=[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4]],
names=[None, None])
si = Index(['R_l0_g0', 'R_l0_g1', 'R_l0_g2',
'R_l0_g3', 'R_l0_g4'], name=None)
expected = pd.DataFrame(data, index=si, columns=columns)
actual = pd.read_excel(in_file, 'single_no_names')
tm.assert_frame_equal(actual, expected)
expected.index = mi
actual = pd.read_excel(in_file, 'multi_no_names', index_col=[0, 1])
tm.assert_frame_equal(actual, expected, check_names=False)
def test_read_excel_bool_header_arg(self, ext):
# GH 6114
for arg in [True, False]:
with pytest.raises(TypeError):
pd.read_excel(os.path.join(self.dirpath, 'test1' + ext),
header=arg)
def test_read_excel_chunksize(self, ext):
# GH 8011
with pytest.raises(NotImplementedError):
pd.read_excel(os.path.join(self.dirpath, 'test1' + ext),
chunksize=100)
@td.skip_if_no('openpyxl')
@td.skip_if_no('xlwt')
def test_read_excel_parse_dates(self, ext):
# GH 11544, 12051
df = DataFrame(
{'col': [1, 2, 3],
'date_strings': pd.date_range('2012-01-01', periods=3)})
df2 = df.copy()
df2['date_strings'] = df2['date_strings'].dt.strftime('%m/%d/%Y')
with ensure_clean(ext) as pth:
df2.to_excel(pth)
res = read_excel(pth)
tm.assert_frame_equal(df2, res)
# no index_col specified when parse_dates is True
with tm.assert_produces_warning():
res = read_excel(pth, parse_dates=True)
tm.assert_frame_equal(df2, res)
res = read_excel(pth, parse_dates=['date_strings'], index_col=0)
tm.assert_frame_equal(df, res)
dateparser = lambda x: pd.datetime.strptime(x, '%m/%d/%Y')
res = read_excel(pth, parse_dates=['date_strings'],
date_parser=dateparser, index_col=0)
tm.assert_frame_equal(df, res)
def test_read_excel_skiprows_list(self, ext):
# GH 4903
actual = pd.read_excel(os.path.join(self.dirpath,
'testskiprows' + ext),
'skiprows_list', skiprows=[0, 2])
expected = DataFrame([[1, 2.5, pd.Timestamp('2015-01-01'), True],
[2, 3.5, pd.Timestamp('2015-01-02'), False],
[3, 4.5, pd.Timestamp('2015-01-03'), False],
[4, 5.5, pd.Timestamp('2015-01-04'), True]],
columns=['a', 'b', 'c', 'd'])
tm.assert_frame_equal(actual, expected)
actual = pd.read_excel(os.path.join(self.dirpath,
'testskiprows' + ext),
'skiprows_list', skiprows=np.array([0, 2]))
tm.assert_frame_equal(actual, expected)
def test_read_excel_nrows(self, ext):
# GH 16645
num_rows_to_pull = 5
actual = pd.read_excel(os.path.join(self.dirpath, 'test1' + ext),
nrows=num_rows_to_pull)
expected = pd.read_excel(os.path.join(self.dirpath,
'test1' + ext))
expected = expected[:num_rows_to_pull]
tm.assert_frame_equal(actual, expected)
def test_read_excel_nrows_greater_than_nrows_in_file(self, ext):
# GH 16645
expected = pd.read_excel(os.path.join(self.dirpath,
'test1' + ext))
num_records_in_file = len(expected)
num_rows_to_pull = num_records_in_file + 10
actual = pd.read_excel(os.path.join(self.dirpath, 'test1' + ext),
nrows=num_rows_to_pull)
tm.assert_frame_equal(actual, expected)
def test_read_excel_nrows_non_integer_parameter(self, ext):
# GH 16645
msg = "'nrows' must be an integer >=0"
with tm.assert_raises_regex(ValueError, msg):
pd.read_excel(os.path.join(self.dirpath, 'test1' + ext),
nrows='5')