如何将 Pandas DataFrames 写入多个 Excel 工作表？

在本文中，我们将了解如何使用Python将不同的 DataFrame 导出到不同的 Excel 工作表。

为此， Pandas提供了一个名为xlsxwriter的函数。 ExcelWriter() 是一个允许您将 DataFrame 对象写入 Microsoft Excel 工作表的类。文本、数字、字符串和公式都可以使用 ExcelWriter() 编写。它也可以用于多个工作表。

Syntax:

pandas.ExcelWriter(path, date_format=None, mode=’w’)

Parameter:

• path: (str) Path to xls or xlsx or ods file.
• date_format: Format string for dates written into Excel files (e.g. ‘YYYY-MM-DD’).  str, default None
• mode: {‘w’, ‘a’}, default ‘w’. File mode to use (write or append). Append does not work with fsspec URLs.

to_excel() 方法用于将 DataFrame 导出到 excel 文件。要将单个对象写入 excel 文件，我们必须指定目标文件名。如果我们要写入多个工作表，我们需要创建一个具有目标文件名的 ExcelWriter 对象，还需要在我们必须写入的文件中指定工作表。也可以通过指定唯一的 sheet_name 来写入多个工作表。有必要保存写入文件的所有数据的更改。

Syntax:

DataFrame.to_excel(excel_writer, sheet_name=’Sheet1′,index=True)

Parameter:

• excel_writer: path-like, file-like, or ExcelWriter object (new or existing)
• sheet_name: (str, default ‘Sheet1’). Name of the sheet which will contain DataFrame.
• index: (bool, default True). Write row names (index).

使用pandas.DataFrame函数创建一些示例数据框。现在，在 pandas excelwriter函数中创建一个writer 变量并指定您希望存储 excel 文件的路径和文件名。

示例：将 Pandas 数据框写入多个 Excel 工作表

Python3

# import the python pandas package
import pandas as pd
 
# create  data_frame1 by creating a dictionary
# in which values are stored as list
data_frame1 = pd.DataFrame({'Fruits': ['Appple', 'Banana', 'Mango',
                                       'Dragon Fruit', 'Musk melon', 'grapes'],
                            'Sales in kg': [20, 30, 15, 10, 50, 40]})
 
# create  data_frame2 by creating a dictionary
# in which values are stored as list
data_frame2 = pd.DataFrame({'Vegetables': ['tomato', 'Onion', 'ladies finger',
                                           'beans', 'bedroot', 'carrot'],
                            'Sales in kg': [200, 310, 115, 110, 55, 45]})
 
# create  data_frame3 by creating a dictionary
# in which values are stored as list
data_frame3 = pd.DataFrame({'Baked Items': ['Cakes', 'biscuits', 'muffins',
                                            'Rusk', 'puffs', 'cupcakes'],
                            'Sales in kg': [120, 130, 159, 310, 150, 140]})
 
print(data_frame1)
print(data_frame2)
print(data_frame3)
 
# create a excel writer object
with pd.ExcelWriter("path to file\filename.xlsx") as writer:
   
    # use to_excel function and specify the sheet_name and index
    # to store the dataframe in specified sheet
    data_frame1.to_excel(writer, sheet_name="Fruits", index=False)
    data_frame2.to_excel(writer, sheet_name="Vegetables", index=False)
    data_frame3.to_excel(writer, sheet_name="Baked Items", index=False)

输出：

显示具有不同工作表的 excel 文件的输出保存在指定位置。

示例 2：另一种使用excelwriter将数据框存储在现有 excel 文件中的方法如下所示，

创建数据框并将它们附加到上面显示的现有 excel 文件中，使用 excelwriter函数中的mode= 'a' （意思是append ）。使用模式“a”会将新工作表添加为现有 Excel 文件中的最后一个工作表。

Python3

# import the python pandas package
import pandas as pd
 
# create  data_frame1 by creating a dictionary
# in which values are stored as list
data_frame1 = pd.DataFrame({'Fruits': ['Appple', 'Banana', 'Mango',
                                       'Dragon Fruit', 'Musk melon', 'grapes'],
                            'Sales in kg': [20, 30, 15, 10, 50, 40]})
 
# create  data_frame2 by creating a dictionary
# in which values are stored as list
data_frame2 = pd.DataFrame({'Vegetables': ['tomato', 'Onion', 'ladies finger',
                                           'beans', 'bedroot', 'carrot'],
                            'Sales in kg': [200, 310, 115, 110, 55, 45]})
 
# create  data_frame3 by creating a dictionary
# in which values are stored as list
data_frame3 = pd.DataFrame({'Baked Items': ['Cakes', 'biscuits', 'muffins',
                                            'Rusk', 'puffs', 'cupcakes'],
                            'Sales in kg': [120, 130, 159, 310, 150, 140]})
 
 
# create  data_frame3 by creating a dictionary
# in which values are stored as list
data_frame4 = pd.DataFrame({'Cool drinks': ['Pepsi', 'Coca-cola', 'Fanta',
                                            'Miranda', '7up', 'Sprite'],
                            'Sales in count': [1209, 1230, 1359, 3310, 2150, 1402]})
 
# create a excel writer object as shown using
# Excelwriter function
with pd.ExcelWriter("path_to_file.xlsx", mode="a", engine="openpyxl") as writer:
     
    # use to_excel function and specify the sheet_name and index to
    # store the dataframe in specified sheet
    data_frame4.to_excel(writer, sheet_name="Cool drinks")

输出：

以压缩格式将大型 Pandas DataFrame 写入 excel 文件。

如果输出数据框很大，您还可以将 excel 文件存储为压缩文件。让我们保存我们为此示例创建的数据框。作为excel并将其存储为zip文件。 ZIP 文件格式是一种常见的存档和压缩标准。

Syntax:

ZipFile(file, mode=’r’)

Parameter:

• file: the file can be a path to a file (a string), a file-like object, or a path-like object.
• mode: The mode parameter should be ‘r’ to read an existing file, ‘w’ to truncate and write a new file, ‘a’ to append to an existing file, or ‘x’ to exclusively create and write a new file.

导入zipfile包并创建示例数据框。现在，指定 zip 文件必须存储的路径，这将在指定路径中创建一个zip 文件。创建一个必须存储 excel 文件的文件名。使用to_excel()函数并指定工作表名称和索引以将数据框存储在多个工作表中

示例：以 ZIP 格式编写大型数据帧

Python3

# import zipfile package
import zipfile
 
# import the python pandas package
import pandas as pd
 
# create  data_frame1 by creating a dictionary
# in which values are stored as list
data_frame1 = pd.DataFrame({'Fruits': ['Appple', 'Banana', 'Mango',
                                       'Dragon Fruit', 'Musk melon', 'grapes'],
                            'Sales in kg': [20, 30, 15, 10, 50, 40]})
 
# create  data_frame2 by creating a dictionary
# in which values are stored as list
data_frame2 = pd.DataFrame({'Vegetables': ['tomato', 'Onion', 'ladies finger',
                                           'beans', 'bedroot', 'carrot'],
                            'Sales in kg': [200, 310, 115, 110, 55, 45]})
 
# create  data_frame3 by creating a dictionary
# in which values are stored as list
data_frame3 = pd.DataFrame({'Baked Items': ['Cakes', 'biscuits', 'muffins',
                                            'Rusk', 'puffs', 'cupcakes'],
                            'Sales in kg': [120, 130, 159, 310, 150, 140]})
 
 
# create  data_frame3 by creating a dictionary
# in which values are stored as list
data_frame4 = pd.DataFrame({'Cool drinks': ['Pepsi', 'Coca-cola', 'Fanta',
                                            'Miranda', '7up', 'Sprite'],
                            'Sales in count': [1209, 1230, 1359, 3310, 2150, 1402]})
 
# specify the path in which the zip file has to be stored
with zipfile.ZipFile("path_to_file.zip", "w") as zf:
   
    # in open function specify the name in which
    # the excel file has to be stored
    with zf.open("filename.xlsx", "w") as buffer:
        with pd.ExcelWriter(buffer) as writer:
           
            # use to_excel function and specify the sheet_name and
            # index to store the dataframe in specified sheet
            data_frame1.to_excel(writer, sheet_name="Fruits", index=False)
            data_frame2.to_excel(writer, sheet_name="Vegetables", index=False)
            data_frame3.to_excel(writer, sheet_name="Baked Items", index=False)
            data_frame4.to_excel(writer, sheet_name="Cool Drinks", index=False)

输出：

压缩的 excel 文件的示例输出