如何在不覆盖数据的情况下(使用熊猫)写入现有的excel文件?

问题:如何在不覆盖数据的情况下(使用熊猫)写入现有的excel文件?

我使用熊猫以以下方式写入excel文件:

import pandas

writer = pandas.ExcelWriter('Masterfile.xlsx') 

data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])

writer.save()

Masterfile.xlsx已经包含许多不同的选项卡。但是,它尚未包含“ Main”。

熊猫正确地写入了“主要”表,不幸的是,它也删除了所有其他标签。

I use pandas to write to excel file in the following fashion:

import pandas

writer = pandas.ExcelWriter('Masterfile.xlsx') 

data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])

writer.save()

Masterfile.xlsx already consists of number of different tabs. However, it does not yet contain “Main”.

Pandas correctly writes to “Main” sheet, unfortunately it also deletes all other tabs.


回答 0

熊猫文档说,它对xlsx文件使用openpyxl。快速浏览一下其中的代码ExcelWriter可以提示可能会发生以下情况:

import pandas
from openpyxl import load_workbook

book = load_workbook('Masterfile.xlsx')
writer = pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl') 
writer.book = book

## ExcelWriter for some reason uses writer.sheets to access the sheet.
## If you leave it empty it will not know that sheet Main is already there
## and will create a new sheet.

writer.sheets = dict((ws.title, ws) for ws in book.worksheets)

data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])

writer.save()

Pandas docs says it uses openpyxl for xlsx files. Quick look through the code in ExcelWriter gives a clue that something like this might work out:

import pandas
from openpyxl import load_workbook

book = load_workbook('Masterfile.xlsx')
writer = pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl') 
writer.book = book

## ExcelWriter for some reason uses writer.sheets to access the sheet.
## If you leave it empty it will not know that sheet Main is already there
## and will create a new sheet.

writer.sheets = dict((ws.title, ws) for ws in book.worksheets)

data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])

writer.save()

回答 1

这是一个辅助函数:

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None,
                       truncate_sheet=False, 
                       **to_excel_kwargs):
    """
    Append a DataFrame [df] to existing Excel file [filename]
    into [sheet_name] Sheet.
    If [filename] doesn't exist, then this function will create it.

    Parameters:
      filename : File path or existing ExcelWriter
                 (Example: '/path/to/file.xlsx')
      df : dataframe to save to workbook
      sheet_name : Name of sheet which will contain DataFrame.
                   (default: 'Sheet1')
      startrow : upper left cell row to dump data frame.
                 Per default (startrow=None) calculate the last row
                 in the existing DF and write to the next row...
      truncate_sheet : truncate (remove and recreate) [sheet_name]
                       before writing DataFrame to Excel file
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]

    Returns: None
    """
    from openpyxl import load_workbook

    # ignore [engine] parameter if it was passed
    if 'engine' in to_excel_kwargs:
        to_excel_kwargs.pop('engine')

    writer = pd.ExcelWriter(filename, engine='openpyxl')

    # Python 2.x: define [FileNotFoundError] exception if it doesn't exist 
    try:
        FileNotFoundError
    except NameError:
        FileNotFoundError = IOError


    try:
        # try to open an existing workbook
        writer.book = load_workbook(filename)

        # get the last row in the existing Excel sheet
        # if it was not specified explicitly
        if startrow is None and sheet_name in writer.book.sheetnames:
            startrow = writer.book[sheet_name].max_row

        # truncate sheet
        if truncate_sheet and sheet_name in writer.book.sheetnames:
            # index of [sheet_name] sheet
            idx = writer.book.sheetnames.index(sheet_name)
            # remove [sheet_name]
            writer.book.remove(writer.book.worksheets[idx])
            # create an empty sheet [sheet_name] using old index
            writer.book.create_sheet(sheet_name, idx)

        # copy existing sheets
        writer.sheets = {ws.title:ws for ws in writer.book.worksheets}
    except FileNotFoundError:
        # file does not exist yet, we will create it
        pass

    if startrow is None:
        startrow = 0

    # write out the new sheet
    df.to_excel(writer, sheet_name, startrow=startrow, **to_excel_kwargs)

    # save the workbook
    writer.save()

注意:对于<0.21.0的熊猫,请替换sheet_namesheetname

用法示例:

append_df_to_excel('d:/temp/test.xlsx', df)

append_df_to_excel('d:/temp/test.xlsx', df, header=None, index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False, startrow=25)

Here is a helper function:

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None,
                       truncate_sheet=False, 
                       **to_excel_kwargs):
    """
    Append a DataFrame [df] to existing Excel file [filename]
    into [sheet_name] Sheet.
    If [filename] doesn't exist, then this function will create it.

    Parameters:
      filename : File path or existing ExcelWriter
                 (Example: '/path/to/file.xlsx')
      df : dataframe to save to workbook
      sheet_name : Name of sheet which will contain DataFrame.
                   (default: 'Sheet1')
      startrow : upper left cell row to dump data frame.
                 Per default (startrow=None) calculate the last row
                 in the existing DF and write to the next row...
      truncate_sheet : truncate (remove and recreate) [sheet_name]
                       before writing DataFrame to Excel file
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]

    Returns: None

    (c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)
    """
    from openpyxl import load_workbook

    # ignore [engine] parameter if it was passed
    if 'engine' in to_excel_kwargs:
        to_excel_kwargs.pop('engine')

    writer = pd.ExcelWriter(filename, engine='openpyxl')

    # Python 2.x: define [FileNotFoundError] exception if it doesn't exist 
    try:
        FileNotFoundError
    except NameError:
        FileNotFoundError = IOError


    try:
        # try to open an existing workbook
        writer.book = load_workbook(filename)
        
        # get the last row in the existing Excel sheet
        # if it was not specified explicitly
        if startrow is None and sheet_name in writer.book.sheetnames:
            startrow = writer.book[sheet_name].max_row

        # truncate sheet
        if truncate_sheet and sheet_name in writer.book.sheetnames:
            # index of [sheet_name] sheet
            idx = writer.book.sheetnames.index(sheet_name)
            # remove [sheet_name]
            writer.book.remove(writer.book.worksheets[idx])
            # create an empty sheet [sheet_name] using old index
            writer.book.create_sheet(sheet_name, idx)
        
        # copy existing sheets
        writer.sheets = {ws.title:ws for ws in writer.book.worksheets}
    except FileNotFoundError:
        # file does not exist yet, we will create it
        pass

    if startrow is None:
        startrow = 0

    # write out the new sheet
    df.to_excel(writer, sheet_name, startrow=startrow, **to_excel_kwargs)

    # save the workbook
    writer.save()
            

NOTE: for Pandas < 0.21.0, replace sheet_name with sheetname!

Usage examples:

append_df_to_excel('d:/temp/test.xlsx', df)

append_df_to_excel('d:/temp/test.xlsx', df, header=None, index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False, startrow=25)

回答 2

使用openpyxlversion 2.4.0pandasversion 0.19.2,@ ski提出的过程变得更加简单:

import pandas
from openpyxl import load_workbook

with pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl') as writer:
    writer.book = load_workbook('Masterfile.xlsx')
    data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])
#That's it!

With openpyxlversion 2.4.0 and pandasversion 0.19.2, the process @ski came up with gets a bit simpler:

import pandas
from openpyxl import load_workbook

with pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl') as writer:
    writer.book = load_workbook('Masterfile.xlsx')
    data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])
#That's it!

回答 3

从pandas 0.24开始,您可以使用mode关键字参数简化此操作ExcelWriter

import pandas as pd

with pd.ExcelWriter('the_file.xlsx', engine='openpyxl', mode='a') as writer: 
     data_filtered.to_excel(writer) 

Starting in pandas 0.24 you can simplify this with the mode keyword argument of ExcelWriter:

import pandas as pd

with pd.ExcelWriter('the_file.xlsx', engine='openpyxl', mode='a') as writer: 
     data_filtered.to_excel(writer) 

回答 4

老问题了,但我猜有些人还在搜索这个-所以…

我发现此方法不错,因为所有工作表都加载到工作表名称和数据框对的字典中,该字典由熊猫使用sheetname = None选项创建。在将电子表格读取为dict格式并将其从dict写回之前,添加,删除或修改工作表很简单。对于我来说,就速度和格式而言,xlsxwriter在执行此特定任务方面比openpyxl更好。

注意:未来版本的熊猫(0.21.0+)将把“ sheetname”参数更改为“ sheet_name”。

# read a single or multi-sheet excel file
# (returns dict of sheetname(s), dataframe(s))
ws_dict = pd.read_excel(excel_file_path,
                        sheetname=None)

# all worksheets are accessible as dataframes.

# easy to change a worksheet as a dataframe:
mod_df = ws_dict['existing_worksheet']

# do work on mod_df...then reassign
ws_dict['existing_worksheet'] = mod_df

# add a dataframe to the workbook as a new worksheet with
# ws name, df as dict key, value:
ws_dict['new_worksheet'] = some_other_dataframe

# when done, write dictionary back to excel...
# xlsxwriter honors datetime and date formats
# (only included as example)...
with pd.ExcelWriter(excel_file_path,
                    engine='xlsxwriter',
                    datetime_format='yyyy-mm-dd',
                    date_format='yyyy-mm-dd') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

对于2013年问题中的示例:

ws_dict = pd.read_excel('Masterfile.xlsx',
                        sheetname=None)

ws_dict['Main'] = data_filtered[['Diff1', 'Diff2']]

with pd.ExcelWriter('Masterfile.xlsx',
                    engine='xlsxwriter') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

Old question, but I am guessing some people still search for this – so…

I find this method nice because all worksheets are loaded into a dictionary of sheet name and dataframe pairs, created by pandas with the sheetname=None option. It is simple to add, delete or modify worksheets between reading the spreadsheet into the dict format and writing it back from the dict. For me the xlsxwriter works better than openpyxl for this particular task in terms of speed and format.

Note: future versions of pandas (0.21.0+) will change the “sheetname” parameter to “sheet_name”.

# read a single or multi-sheet excel file
# (returns dict of sheetname(s), dataframe(s))
ws_dict = pd.read_excel(excel_file_path,
                        sheetname=None)

# all worksheets are accessible as dataframes.

# easy to change a worksheet as a dataframe:
mod_df = ws_dict['existing_worksheet']

# do work on mod_df...then reassign
ws_dict['existing_worksheet'] = mod_df

# add a dataframe to the workbook as a new worksheet with
# ws name, df as dict key, value:
ws_dict['new_worksheet'] = some_other_dataframe

# when done, write dictionary back to excel...
# xlsxwriter honors datetime and date formats
# (only included as example)...
with pd.ExcelWriter(excel_file_path,
                    engine='xlsxwriter',
                    datetime_format='yyyy-mm-dd',
                    date_format='yyyy-mm-dd') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

For the example in the 2013 question:

ws_dict = pd.read_excel('Masterfile.xlsx',
                        sheetname=None)

ws_dict['Main'] = data_filtered[['Diff1', 'Diff2']]

with pd.ExcelWriter('Masterfile.xlsx',
                    engine='xlsxwriter') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

回答 5

我知道这是一个较旧的线程,但这是您在搜索时发现的第一项,并且如果需要将图表保留在已创建的工作簿中,则上述解决方案将不起作用。在这种情况下,xlwings是一个更好的选择-它允许您写入Excel书并保留图表/图表数据。

简单的例子:

import xlwings as xw
import pandas as pd

#create DF
months = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
value1 = [x * 5+5 for x in range(len(months))]
df = pd.DataFrame(value1, index = months, columns = ['value1'])
df['value2'] = df['value1']+5
df['value3'] = df['value2']+5

#load workbook that has a chart in it
wb = xw.Book('C:\\data\\bookwithChart.xlsx')

ws = wb.sheets['chartData']

ws.range('A1').options(index=False).value = df

wb = xw.Book('C:\\data\\bookwithChart_updated.xlsx')

xw.apps[0].quit()

I know this is an older thread, but this is the first item you find when searching, and the above solutions don’t work if you need to retain charts in a workbook that you already have created. In that case, xlwings is a better option – it allows you to write to the excel book and keeps the charts/chart data.

simple example:

import xlwings as xw
import pandas as pd

#create DF
months = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
value1 = [x * 5+5 for x in range(len(months))]
df = pd.DataFrame(value1, index = months, columns = ['value1'])
df['value2'] = df['value1']+5
df['value3'] = df['value2']+5

#load workbook that has a chart in it
wb = xw.Book('C:\\data\\bookwithChart.xlsx')

ws = wb.sheets['chartData']

ws.range('A1').options(index=False).value = df

wb = xw.Book('C:\\data\\bookwithChart_updated.xlsx')

xw.apps[0].quit()

回答 6

在pandas 0.24中有一个更好的解决方案:

with pd.ExcelWriter(path, mode='a') as writer:
    s.to_excel(writer, sheet_name='another sheet', index=False)

之前:

后:

因此,立即升级您的熊猫:

pip install --upgrade pandas

There is a better solution in pandas 0.24:

with pd.ExcelWriter(path, mode='a') as writer:
    s.to_excel(writer, sheet_name='another sheet', index=False)

before:

after:

so upgrade your pandas now:

pip install --upgrade pandas

回答 7

def append_sheet_to_master(self, master_file_path, current_file_path, sheet_name):
    try:
        master_book = load_workbook(master_file_path)
        master_writer = pandas.ExcelWriter(master_file_path, engine='openpyxl')
        master_writer.book = master_book
        master_writer.sheets = dict((ws.title, ws) for ws in master_book.worksheets)
        current_frames = pandas.ExcelFile(current_file_path).parse(pandas.ExcelFile(current_file_path).sheet_names[0],
                                                               header=None,
                                                               index_col=None)
        current_frames.to_excel(master_writer, sheet_name, index=None, header=False)

        master_writer.save()
    except Exception as e:
        raise e

这非常完美,只有主文件(添加新工作表的文件)的格式丢失了。

def append_sheet_to_master(self, master_file_path, current_file_path, sheet_name):
    try:
        master_book = load_workbook(master_file_path)
        master_writer = pandas.ExcelWriter(master_file_path, engine='openpyxl')
        master_writer.book = master_book
        master_writer.sheets = dict((ws.title, ws) for ws in master_book.worksheets)
        current_frames = pandas.ExcelFile(current_file_path).parse(pandas.ExcelFile(current_file_path).sheet_names[0],
                                                               header=None,
                                                               index_col=None)
        current_frames.to_excel(master_writer, sheet_name, index=None, header=False)

        master_writer.save()
    except Exception as e:
        raise e

This works perfectly fine only thing is that formatting of the master file(file to which we add new sheet) is lost.


回答 8

writer = pd.ExcelWriter('prueba1.xlsx'engine='openpyxl',keep_date_col=True)

“ keep_date_col”希望对您有所帮助

writer = pd.ExcelWriter('prueba1.xlsx'engine='openpyxl',keep_date_col=True)

The “keep_date_col” hope help you


回答 9

book = load_workbook(xlsFilename)
writer = pd.ExcelWriter(self.xlsFilename)
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, sheet_name=sheetName, index=False)
writer.save()
book = load_workbook(xlsFilename)
writer = pd.ExcelWriter(self.xlsFilename)
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, sheet_name=sheetName, index=False)
writer.save()