Python 如何在不覆盖数据的情况下写入现有excel文件（使用pandas）？

我使用pandas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已经由许多不同的选项卡组成。但是，它还不包含“Main”

---

Pandas正确地写入“主”工作表，不幸的是，它还删除了所有其他选项卡。

Pandas文档称它使用openpyxl处理xlsx文件。快速浏览

ExcelWriter

中的代码，可以得出这样的结论：

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()

---

这工作得非常好，唯一的问题是主文件（我们添加新工作表的文件）的格式丢失。

使用

openpyxl

版本

2.4.0

和

pandas

版本

0.19.2

，@ski的过程变得简单了一些：

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!

---

老问题，但我猜有些人仍然在寻找这个-所以

我觉得这个方法很好，因为所有工作表都被加载到一个表名和数据帧对的字典中，由pandas使用sheetname=None选项创建。在将电子表格读入dict格式和从dict中写回工作表之间，添加、删除或修改工作表非常简单。对于我来说，xlsxwriter在速度和格式方面都比openpyxl更好

注：pandas（0.21.0+）的未来版本将“sheetname”参数更改为“sheet_name”

关于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)

---

我知道这是一个较旧的线程，但这是搜索时找到的第一项，如果您需要在已创建的工作簿中保留图表，则上述解决方案不起作用。在这种情况下，xlwings是一个更好的选择-它允许您写入excel手册并保留图表/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()

---

“keep_date_col”希望能帮助您这里有一个帮助函数：

import os
from openpyxl import load_workbook


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.

    @param filename: File path or existing ExcelWriter
                     (Example: '/path/to/file.xlsx')
    @param df: DataFrame to save to workbook
    @param sheet_name: Name of sheet which will contain DataFrame.
                       (default: 'Sheet1')
    @param 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...
    @param truncate_sheet: truncate (remove and recreate) [sheet_name]
                           before writing DataFrame to Excel file
    @param to_excel_kwargs: arguments which will be passed to `DataFrame.to_excel()`
                            [can be a dictionary]
    @return: None

    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)

    (c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)
    """
    # Excel file doesn't exist - saving and exiting
    if not os.path.isfile(filename):
        df.to_excel(
            filename,
            sheet_name=sheet_name, 
            startrow=startrow if startrow is not None else 0, 
            **to_excel_kwargs)
        return
    
    # ignore [engine] parameter if it was passed
    if 'engine' in to_excel_kwargs:
        to_excel_kwargs.pop('engine')

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

    # 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}

    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()

使用以下版本进行测试：

• 熊猫1.2.3
• Openpyxl 3.0.5

---

从pandas 0.24开始，您可以使用

ExcelWriter

的

模式

关键字参数简化此操作：

将熊猫作为pd导入
使用pd.ExcelWriter（'the_file.xlsx'，engine='openpyxl'，mode='a'）作为编写器：
数据过滤到excel（编写器）

熊猫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：

之后：

现在就升级你的熊猫吧：

pip install --upgrade pandas

方法：

• 如果不存在，则可以创建文件
• 根据图纸名称追加到现有excel

将熊猫作为pd导入
从openpyxl导入加载工作簿
def写入excel（df，文件）：
尝试：
book=加载工作簿（文件）
writer=pd.ExcelWriter（文件，engine='openpyxl'）
writer.book=书
writer.sheets=dict（（ws.title，ws）表示book.worksheets中的ws）
df.to_excel（编写器，**kwds）
writer.save（）
除FileNotFoundError为e外：
df.to_excel（文件，**kwds）

用法：

df_a=pd.DataFrame（范围（10），列=[“a”]）
df_b=pd.DataFrame（范围（10,20），列=[“b”]）
写入excel（df_a，“test.xlsx”，sheet_name=“sheet a”，columns=['a']，index=False）
写入excel（df_b，“test.xlsx”，sheet_name=“sheet b”，columns=['b']）

由@MaxU提供的解决方案非常有效。我只有一个建议：

如果指定truncate_sheet=True，则不应从现有图纸中保留“startrow”。我建议：

        if startrow is None and sheet_name in writer.book.sheetnames:
            if not truncate_sheet: # truncate_sheet would use startrow if provided (or zero below)
                startrow = writer.book[sheet_name].max_row

---

我使用了描述的答案

---

@MaxU的解决方案不适用于更新版本的python和相关软件包。它引发了一个错误： “zipfile.BadZipFile:文件不是zip文件”

我生成了一个新版本的函数，该函数与更新版本的python和相关软件包配合使用，并使用python:3.9 | openpyxl:3.0.6 | pandas:1.2.3进行了测试

此外，我还为helper函数添加了更多功能：

import pandas as pd

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None, startcol=None,
    truncate_sheet=False, resizeColumns=True, na_rep = 'NA', **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

      resizeColumns: default = True . It resize all columns based on cell content width
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]
      na_rep: default = 'NA'. If, instead of NaN, you want blank cells, just edit as follows: na_rep=''


    Returns: None

    *******************

    CONTRIBUTION:
    Current helper function generated by [Baggio]: https://stackoverflow.com/users/14302009/baggio?tab=profile
    Contributions to the current helper function: https://stackoverflow.com/users/4046632/buran?tab=profile
    Original helper function: (c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)


    Features of the new helper function:
    1) Now it works with python 3.9 and latest versions of pandas and openpxl
    ---> Fixed the error: "zipfile.BadZipFile: File is not a zip file".
    2) Now It resize all columns based on cell content width AND all variables will be visible (SEE "resizeColumns")
    3) You can handle NaN,  if you want that NaN are displayed as NaN or as empty cells (SEE "na_rep")
    4) Added "startcol", you can decide to start to write from specific column, oterwise will start from col = 0

    *******************



    """
    from openpyxl import load_workbook
    from string import ascii_uppercase
    from openpyxl.utils import get_column_letter
    from openpyxl import Workbook

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

    try:
        f = open(filename)
        # Do something with the file
    except IOError:
        # print("File not accessible")
        wb = Workbook()
        ws = wb.active
        ws.title = sheet_name
        wb.save(filename)

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


    # 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 = -1
        startrow = 0

    if startcol is None:
        startcol = 0

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


    if resizeColumns:

        ws = writer.book[sheet_name]

        def auto_format_cell_width(ws):
            for letter in range(1,ws.max_column):
                maximum_value = 0
                for cell in ws[get_column_letter(letter)]:
                    val_to_check = len(str(cell.value))
                    if val_to_check > maximum_value:
                        maximum_value = val_to_check
                ws.column_dimensions[get_column_letter(letter)].width = maximum_value + 2

        auto_format_cell_width(ws)

    # save the workbook
    writer.save()

# Create a sample dataframe
df = pd.DataFrame({'numbers': [1, 2, 3],
                    'colors': ['red', 'white', 'blue'],
                    'colorsTwo': ['yellow', 'white', 'blue'],
                    'NaNcheck': [float('NaN'), 1, float('NaN')],
                    })

# EDIT YOUR PATH FOR THE EXPORT 
filename = r"C:\DataScience\df.xlsx"   

# RUN ONE BY ONE IN ROW THE FOLLOWING LINES, TO SEE THE DIFFERENT UPDATES TO THE EXCELFILE 
  
append_df_to_excel(filename, df, index=False, startrow=0) # Basic Export of df in default sheet (Sheet1)
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0) # Append the sheet "Cool" where "df" is written
append_df_to_excel(filename, df, sheet_name="Cool", index=False) # Append another "df" to the sheet "Cool", just below the other "df" instance
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0, startcol=5) # Append another "df" to the sheet "Cool" starting from col 5
append_df_to_excel(filename, df, index=False, truncate_sheet=True, startrow=10, na_rep = '') # Override (truncate) the "Sheet1", writing the df from row 10, and showing blank cells instead of NaN

现在它根据单元格内容宽度调整所有列的大小，所有变量都将可见（请参见“resizeColumns”）

如果希望NaN显示为NaN或空单元格，则可以处理NaN（请参见“na_rep”）

添加了“startcol”，您可以决定从特定列开始写入，oterwise将从col=0开始

这里是函数：

import pandas as pd

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None, startcol=None,
    truncate_sheet=False, resizeColumns=True, na_rep = 'NA', **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

      resizeColumns: default = True . It resize all columns based on cell content width
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]
      na_rep: default = 'NA'. If, instead of NaN, you want blank cells, just edit as follows: na_rep=''


    Returns: None

    *******************

    CONTRIBUTION:
    Current helper function generated by [Baggio]: https://stackoverflow.com/users/14302009/baggio?tab=profile
    Contributions to the current helper function: https://stackoverflow.com/users/4046632/buran?tab=profile
    Original helper function: (c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)


    Features of the new helper function:
    1) Now it works with python 3.9 and latest versions of pandas and openpxl
    ---> Fixed the error: "zipfile.BadZipFile: File is not a zip file".
    2) Now It resize all columns based on cell content width AND all variables will be visible (SEE "resizeColumns")
    3) You can handle NaN,  if you want that NaN are displayed as NaN or as empty cells (SEE "na_rep")
    4) Added "startcol", you can decide to start to write from specific column, oterwise will start from col = 0

    *******************



    """
    from openpyxl import load_workbook
    from string import ascii_uppercase
    from openpyxl.utils import get_column_letter
    from openpyxl import Workbook

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

    try:
        f = open(filename)
        # Do something with the file
    except IOError:
        # print("File not accessible")
        wb = Workbook()
        ws = wb.active
        ws.title = sheet_name
        wb.save(filename)

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


    # 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 = -1
        startrow = 0

    if startcol is None:
        startcol = 0

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


    if resizeColumns:

        ws = writer.book[sheet_name]

        def auto_format_cell_width(ws):
            for letter in range(1,ws.max_column):
                maximum_value = 0
                for cell in ws[get_column_letter(letter)]:
                    val_to_check = len(str(cell.value))
                    if val_to_check > maximum_value:
                        maximum_value = val_to_check
                ws.column_dimensions[get_column_letter(letter)].width = maximum_value + 2

        auto_format_cell_width(ws)

    # save the workbook
    writer.save()

# Create a sample dataframe
df = pd.DataFrame({'numbers': [1, 2, 3],
                    'colors': ['red', 'white', 'blue'],
                    'colorsTwo': ['yellow', 'white', 'blue'],
                    'NaNcheck': [float('NaN'), 1, float('NaN')],
                    })

# EDIT YOUR PATH FOR THE EXPORT 
filename = r"C:\DataScience\df.xlsx"   

# RUN ONE BY ONE IN ROW THE FOLLOWING LINES, TO SEE THE DIFFERENT UPDATES TO THE EXCELFILE 
  
append_df_to_excel(filename, df, index=False, startrow=0) # Basic Export of df in default sheet (Sheet1)
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0) # Append the sheet "Cool" where "df" is written
append_df_to_excel(filename, df, sheet_name="Cool", index=False) # Append another "df" to the sheet "Cool", just below the other "df" instance
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0, startcol=5) # Append another "df" to the sheet "Cool" starting from col 5
append_df_to_excel(filename, df, index=False, truncate_sheet=True, startrow=10, na_rep = '') # Override (truncate) the "Sheet1", writing the df from row 10, and showing blank cells instead of NaN

用法示例：

import pandas as pd

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None, startcol=None,
    truncate_sheet=False, resizeColumns=True, na_rep = 'NA', **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

      resizeColumns: default = True . It resize all columns based on cell content width
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]
      na_rep: default = 'NA'. If, instead of NaN, you want blank cells, just edit as follows: na_rep=''


    Returns: None

    *******************

    CONTRIBUTION:
    Current helper function generated by [Baggio]: https://stackoverflow.com/users/14302009/baggio?tab=profile
    Contributions to the current helper function: https://stackoverflow.com/users/4046632/buran?tab=profile
    Original helper function: (c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)


    Features of the new helper function:
    1) Now it works with python 3.9 and latest versions of pandas and openpxl
    ---> Fixed the error: "zipfile.BadZipFile: File is not a zip file".
    2) Now It resize all columns based on cell content width AND all variables will be visible (SEE "resizeColumns")
    3) You can handle NaN,  if you want that NaN are displayed as NaN or as empty cells (SEE "na_rep")
    4) Added "startcol", you can decide to start to write from specific column, oterwise will start from col = 0

    *******************



    """
    from openpyxl import load_workbook
    from string import ascii_uppercase
    from openpyxl.utils import get_column_letter
    from openpyxl import Workbook

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

    try:
        f = open(filename)
        # Do something with the file
    except IOError:
        # print("File not accessible")
        wb = Workbook()
        ws = wb.active
        ws.title = sheet_name
        wb.save(filename)

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


    # 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 = -1
        startrow = 0

    if startcol is None:
        startcol = 0

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


    if resizeColumns:

        ws = writer.book[sheet_name]

        def auto_format_cell_width(ws):
            for letter in range(1,ws.max_column):
                maximum_value = 0
                for cell in ws[get_column_letter(letter)]:
                    val_to_check = len(str(cell.value))
                    if val_to_check > maximum_value:
                        maximum_value = val_to_check
                ws.column_dimensions[get_column_letter(letter)].width = maximum_value + 2

        auto_format_cell_width(ws)

    # save the workbook
    writer.save()

# Create a sample dataframe
df = pd.DataFrame({'numbers': [1, 2, 3],
                    'colors': ['red', 'white', 'blue'],
                    'colorsTwo': ['yellow', 'white', 'blue'],
                    'NaNcheck': [float('NaN'), 1, float('NaN')],
                    })

# EDIT YOUR PATH FOR THE EXPORT 
filename = r"C:\DataScience\df.xlsx"   

# RUN ONE BY ONE IN ROW THE FOLLOWING LINES, TO SEE THE DIFFERENT UPDATES TO THE EXCELFILE 
  
append_df_to_excel(filename, df, index=False, startrow=0) # Basic Export of df in default sheet (Sheet1)
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0) # Append the sheet "Cool" where "df" is written
append_df_to_excel(filename, df, sheet_name="Cool", index=False) # Append another "df" to the sheet "Cool", just below the other "df" instance
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0, startcol=5) # Append another "df" to the sheet "Cool" starting from col 5
append_df_to_excel(filename, df, index=False, truncate_sheet=True, startrow=10, na_rep = '') # Override (truncate) the "Sheet1", writing the df from row 10, and showing blank cells instead of NaN

---

你能举个例子吗？我在文档中没有发现类似的东西。我认为熊猫中没有像ExcelReader这样的东西。我使用read_excel从excel中读取数据。我认为这不会将数据保存到excel中。@nrathaus似乎没有一个

ExcelReader

请注意，在回答问题的确切内容时存在一些混淆。一些答案假设“Main”还不存在，OP只是在现有excel工作簿中添加一个新工作表。其他人认为“Main”已经存在，OP希望将新数据附加到“Main”的底部。您能解释writer.sheets的用途吗？ExcelWriter出于某种原因使用此变量访问工作表。如果您将其保留为空，它将不知道主工作表已经存在，并将创建一个新的工作表。此解决方案工作正常。但它有一个缺点。它会打断电子表格中的公式和连接。你知道如何改变这种行为吗？你到底是怎么被打破的。。？您可以将此作为一个单独的问题提问，并将其标记为

openpyxl

，并提供足够的详细信息：您有什么样的公式，数据是如何更新的，它是如何阻止公式的。现在我就是帮不上忙，太多我不知道的事情。它可以用于.xlsm文件吗？这对我不适用。如果已经有一个“主”工作表，它将创建一个名为“Main1”的新工作表，只包含新的数据，并且保持“主”工作表的内容不变。@Qululu我认为在这个问题上，两个不同的目标之间可能存在混淆。这允许您向现有工作簿添加其他工作表。其目的不是将其他数据附加到现有图纸中。

# Create a sample dataframe
df = pd.DataFrame({'numbers': [1, 2, 3],
                    'colors': ['red', 'white', 'blue'],
                    'colorsTwo': ['yellow', 'white', 'blue'],
                    'NaNcheck': [float('NaN'), 1, float('NaN')],
                    })

# EDIT YOUR PATH FOR THE EXPORT 
filename = r"C:\DataScience\df.xlsx"   

# RUN ONE BY ONE IN ROW THE FOLLOWING LINES, TO SEE THE DIFFERENT UPDATES TO THE EXCELFILE 
  
append_df_to_excel(filename, df, index=False, startrow=0) # Basic Export of df in default sheet (Sheet1)
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0) # Append the sheet "Cool" where "df" is written
append_df_to_excel(filename, df, sheet_name="Cool", index=False) # Append another "df" to the sheet "Cool", just below the other "df" instance
append_df_to_excel(filename, df, sheet_name="Cool", index=False, startrow=0, startcol=5) # Append another "df" to the sheet "Cool" starting from col 5
append_df_to_excel(filename, df, index=False, truncate_sheet=True, startrow=10, na_rep = '') # Override (truncate) the "Sheet1", writing the df from row 10, and showing blank cells instead of NaN