关于使用 python 将字符串导出为日期的 xlsxWriter 问题

Question

I have a list that includes dates in the following format: 11/01/2019. This date i convert to string.When I export this list to Excel, The Excel sheet recognizes these string as date.Is there a way to make these dates recognizable by Excel as string using pyhton?thank a lot.

DateTable
11/01/2019
12/01/2019
13/01/2019

data.insert(0, {'Date':datetime.strptime(str(DateTable)[j]),'%d/%m/%Y').strftime('%d/%m/%Y')})
self.date.to_excel('date.xlsx', sheet_name = 'Sheet1', index=False, engine='xlsxwriter') 

Answer 1

To understand what's at stake read The Spanish family wrongly accused of child pornography due to a mistake reading a date .

From the comments it looks like the real question is how to generate an Excel file that gets imported into another appplication. Don't convert dates to strings, especially in this case .

If you want to display dates in a certain way, specify the date display format when creating the ExcelWriter object:

writer = pd.ExcelWriter("pandas_datetime.xlsx",
                        engine='xlsxwriter',
                        datetime_format='dd/mm/yyyy hh:mm:ss',
                        date_format='dd/mm/yyyy')

Excel files aren't text, and all libraries that can import Excel files can handle date values, or know to read the formatted text value of a number or date.

Applications can import Excel dates without problems. That's the one advantage Excel has over CSV files - numbers and dates are binary values, they don't need parsing and aren't affected by localization settings.

If an application has to work with text though, it's always possible that the wrong format will be used, eg because the machine's locale settings changed, because whoever generated the Excel sheet made a mistake, because the application has to import files from multiple other systems that use different formats.

Explanation

Dates in Python (and C#, Java, JavaScript, MySQL, PostgreSQL,....) have no format. They're binary types. Formats apply only when parsing strings into dates or formatting dates as strings for export or display.

Excel has a date type as well. Dates and numbers aren't stored as strings, they're stored as binary values. How they are displayed depends on the cell's number format. Dates are stored as an OADate decimal whose integer part is an offset from 1899-12-30 and fractional part is the time in a 24 hour period.

If you want to display dates in a specific format, specify it in the cell style.

The XlsxWriter docs explain how to do that in Working with dates and time . The examples actually use the format you want:

workbook = xlsxwriter.Workbook('date_examples.xlsx')
worksheet = workbook.add_worksheet()

# Widen column A for extra visibility.
worksheet.set_column('A:A', 30)

# A number to convert to a date.
number = 41333.5

# Write it as a number without formatting.
worksheet.write('A1', number)                # 41333.5

format2 = workbook.add_format({'num_format': 'dd/mm/yy'})
worksheet.write('A2', number, format2)       # 28/02/13

format3 = workbook.add_format({'num_format': 'mm/dd/yy'})
worksheet.write('A3', number, format3)       # 02/28/13

You don't have to convert the date to an OADate decimal though. You can store dates directly. XlsxWriter:

... supports datetime objects of type datetime.datetime, datetime.date, datetime.time and datetime.timedelta.

The XlsxWriter docs show how to work with dates in Pandas as well . It's even easier - just pass the desired format as a parameter:

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='dd/mm/yyyy hh:mm:ss',
                        date_format='dd/mm/yyyy')

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

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

Answer 2

You need to set number format of the cell to "Plain Text", which is {'num_format': '@'}

workbook = Workbook("output.xlsx")
cell_format = workbook.add_format({'num_format': '@'})
worksheet = workbook.add_worksheet()
worksheet.write(0, 0, "15/12/2021", cell_format)
workbook.close()

And with pandas:

writer = pd.ExcelWriter("output.xlsx")
df.to_excel(writer, 'Sheet1')
workbook = writer.book
worksheet = writer.sheets['Sheet1']
cell_format = workbook.add_format({"num_format": "@"})
worksheet.set_column('A', 1, cell_format)
writer.save()