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DOC/TST: doctests leaving extraneous files #23858

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Merged
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Nov 23, 2018
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DOC/TST: doctests leaving extraneous files #23858

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dc59f1f
DOC/TST: doctests leaving extraneous files
Nov 22, 2018
9d1b415
fixed PEP8 issues
Nov 22, 2018
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8 changes: 5 additions & 3 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2028,8 +2028,9 @@ def to_parquet(self, fname, engine='auto', compression='snappy',
Examples
--------
>>> df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})
>>> df.to_parquet('df.parquet.gzip', compression='gzip')
>>> pd.read_parquet('df.parquet.gzip')
>>> df.to_parquet('df.parquet.gzip',
... compression='gzip') # doctest: +SKIP
>>> pd.read_parquet('df.parquet.gzip') # doctest: +SKIP
col1 col2
0 1 3
1 2 4
Expand Down Expand Up @@ -2243,7 +2244,8 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
>>> buffer = io.StringIO()
>>> df.info(buf=buffer)
>>> s = buffer.getvalue()
>>> with open("df_info.txt", "w", encoding="utf-8") as f:
>>> with open("df_info.txt", "w",
... encoding="utf-8") as f: # doctest: +SKIP
... f.write(s)
260

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9 changes: 5 additions & 4 deletions pandas/core/generic.py
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Expand Up @@ -2069,25 +2069,26 @@ def _repr_latex_(self):
>>> df1 = pd.DataFrame([['a', 'b'], ['c', 'd']],
... index=['row 1', 'row 2'],
... columns=['col 1', 'col 2'])
>>> df1.to_excel("output.xlsx")
>>> df1.to_excel("output.xlsx") # doctest: +SKIP

To specify the sheet name:

>>> df1.to_excel("output.xlsx", sheet_name='Sheet_name_1')
>>> df1.to_excel("output.xlsx",
... sheet_name='Sheet_name_1') # doctest: +SKIP

If you wish to write to more than one sheet in the workbook, it is
necessary to specify an ExcelWriter object:

>>> df2 = df1.copy()
>>> with pd.ExcelWriter('output.xlsx') as writer:
>>> with pd.ExcelWriter('output.xlsx') as writer: # doctest: +SKIP
... df1.to_excel(writer, sheet_name='Sheet_name_1')
... df2.to_excel(writer, sheet_name='Sheet_name_2')

To set the library that is used to write the Excel file,
you can pass the `engine` keyword (the default engine is
automatically chosen depending on the file extension):

>>> df1.to_excel('output1.xlsx', engine='xlsxwriter')
>>> df1.to_excel('output1.xlsx', engine='xlsxwriter') # doctest: +SKIP
"""

def to_json(self, path_or_buf=None, orient=None, date_format=None,
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