@MaxU 的解决方案不适用于更新版本的 python 和相关包。它引发了错误：
“zipfile.BadZipFile：文件不是 zip 文件”
我生成了一个新版本的函数，它可以与更新版本的 python 和相关包一起正常工作并用 python 测试：3.9 | openpyxl：3.0.6 |熊猫：1.2.3
此外，我还为辅助函数添加了更多功能：
- 现在它会根据单元格内容宽度调整所有列的大小，并且所有变量都将可见（参见“resizeColumns”）
- 您可以处理 NaN，如果您希望 NaN 显示为 NaN 或空单元格（参见“na_rep”）
- 添加“startcol”，你可以决定从特定列开始写入，否则将从 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()
示例用法：
# 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