##############################################################################
#
# An example of converting a Pandas dataframe with datetimes to an xlsx file
# with a default datetime and date format using Pandas and XlsxWriter.
#
# Copyright 2013-2016, John McNamara, jmcnamara@cpan.org
#

import pandas as pd
from datetime import datetime, date

# Create a Pandas dataframe from some datetime data.
df = pd.DataFrame({'Date and time': [datetime(2015, 1, 1, 11, 30, 55),
                                     datetime(2015, 1, 2, 1,  20, 33),
                                     datetime(2015, 1, 3, 11, 10    ),
                                     datetime(2015, 1, 4, 16, 45, 35),
                                     datetime(2015, 1, 5, 12, 10, 15)],
                   'Dates only':    [date(2015, 2, 1),
                                     date(2015, 2, 2),
                                     date(2015, 2, 3),
                                     date(2015, 2, 4),
                                     date(2015, 2, 5)],
                   })

# Create a Pandas Excel writer using XlsxWriter as the engine.
# Also set the default datetime and date formats.
writer = pd.ExcelWriter("pandas_datetime.xlsx",
                        engine='xlsxwriter',
                        datetime_format='mmm d yyyy hh:mm:ss',
                        date_format='mmmm dd yyyy')

# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')

# Get the xlsxwriter workbook and worksheet objects in order to set the column
# widths, to make the dates clearer.
workbook  = writer.book
worksheet = writer.sheets['Sheet1']

worksheet.set_column('B:C', 20)

# Close the Pandas Excel writer and output the Excel file.
writer.save()
