# 批量合并多个Excel文件
import pandas as pd
import os
def merge_excel_files(directory, output_file):
# 获取目录下所有Excel文件的路径
excel_files = [f for f in os.listdir(directory) if f.endswith('.xlsx')]
# 创建一个空的DataFrame用于存储合并的数据
all_data = pd.DataFrame()
# 遍历每个Excel文件并读取数据
for file_name in excel_files:
print(f"正在处理: {file_name}")
file_path = os.path.join(directory, file_name)
df = pd.read_excel(file_path)
all_data = pd.concat([all_data, df], ignore_index=True)
# 将合并后的数据保存到新的Excel文件中
all_data.to_excel(output_file, index=False)
print(f"合并完成，结果已保存至: {output_file}")
# 使用方法
merge_excel_files('input_directory', 'merged_output.xlsx')
# 在Excel中查找并替换内容
from openpyxl import load_workbook
def find_and_replace_in_excel(file_path, search_text, replace_text):
wb = load_workbook(file_path)
for sheet in wb.worksheets:
print(f"正在处理工作表: {sheet.title}")
for row in sheet.iter_rows():
for cell in row:
if cell.value and search_text in str(cell.value):
old_value = cell.value
new_value = old_value.replace(search_text, replace_text)
cell.value = new_value
print(f"在单元格 {cell.coordinate} 中找到 '{search_text}'，已替换为 '{replace_text}'")
# 保存更改
wb.save('replaced_' + os.path.basename(file_path))
print("查找和替换操作已完成")
# 使用方法
find_and_replace_in_excel('example.xlsx', '旧文本', '新文本')
# 根据条件筛选数据并保存到新文件
import pandas as pd
def filter_excel_data(input_file, output_file, column_name, threshold):
df = pd.read_excel(input_file)
# 筛选出满足条件的数据
filtered_df = df[df[column_name] > threshold]
# 将筛选后的数据保存到新文件
filtered_df.to_excel(output_file, index=False)
print(f"筛选完成，符合条件的数据已保存至: {output_file}")
# 使用方法
filter_excel_data('data.xlsx', 'filtered_data.xlsx', 'Age', 30)
# 向Excel添加公式
from openpyxl import load_workbook
def add_formula_to_excel(file_path, formula, target_cell):
wb = load_workxl(file_path)
ws = wb.active
# 添加公式到指定单元格
ws[target_cell] = formula
print(f"公式 '{formula}' 已添加到单元格 {target_cell}")
wb.save('formulated_' + os.path.basename(file_path))
# 使用方法
add_formula_to_excel('example.xlsx', '=SUM(A1:A10)', 'B1')
# 批量调整Excel格式
from openpyxl import load_workbook
from openpyxl.styles import Font, Color, Alignment
def format_excel_file(file_path):
wb = load_workbook(file_path)
ws = wb.active
# 设置字体、颜色和对齐方式
for row in ws.iter_rows():
for cell in row:
cell.font = Font(name='Arial', size=12, bold=True, color='FF0000')
cell.alignment = Alignment(horizontal='center', vertical='center')
wb.save('formatted_' + os.path.basename(file_path))
print("格式调整完成")
# 使用方法
format_excel_file('example.xlsx')
# 批量重命名工作表
from openpyxl import load_workbook
def rename_sheets(file_path, prefix):
wb = load_workbook(file_path)
for sheet in wb.worksheets:
old_name = sheet.title
new_name = f"{prefix}_{old_name}"
sheet.title = new_name
print(f"工作表 '{old_name}' 已重命名为: {new_name}")
# 保存更改
wb.save('renamed_' + os.path.basename(file_path))
print("所有工作表重命名完成")
# 使用方法
rename_sheets('example.xlsx', 'New')
# 从多个Excel文件中提取特定列的数据
import pandas as pd
import os
def extract_columns_from_multiple_files(directory, columns_to_extract, output_file):
all_data = pd.DataFrame()
# 遍历目录中的所有Excel文件
for filename in os.listdir(directory):
if filename.endswith('.xlsx'):
file_path = os.path.join(directory, filename)
df = pd.read_excel(file_path)
# 提取指定的列
extracted_df = df[columns_to_extract]
all_data = pd.concat([all_data, extracted_df], ignore_index=True)
# 将结果保存到新的Excel文件
all_data.to_excel(output_file, index=False)
print(f"数据提取完成，结果已保存至: {output_file}")
# 使用方法
extract_columns_from_multiple_files('input_directory', ['Name', 'Age'], 'extracted_output.xlsx')
# 在Excel中插入新行或列
from openpyxl import load_workbook
def insert_row_or_column(file_path, location, dimension='row'):
wb = load_workbook(file_path)
ws = wb.active
if dimension == 'row':
ws.insert_rows(location)
print(f"在第{location}行之前插入了一行")
elif dimension == 'column':
ws.insert_cols(location)
print(f"在第{location}列之前插入了一列")
wb.save('inserted_' + os.path.basename(file_path))
# 使用方法
insert_row_or_column('example.xlsx', 5, 'row') # 在第5行之前插入一行
insert_row_or_column('example.xlsx', 3, 'column') # 在第3列之前插入一列
# 删除重复数据
import pandas as pd
def remove_duplicates(input_file, output_file, subset=None):
df = pd.read_excel(input_file)
# 删除重复项
df.drop_duplicates(subset=subset, inplace=True)
# 保存处理后的数据
df.to_excel(output_file, index=False)
print(f"重复数据删除完成，结果已保存至: {output_file}")
# 使用方法
remove_duplicates('data_with_duplicates.xlsx', 'cleaned_data.xlsx', subset=['Name', 'Email'])
# 跨文件复制工作表
from openpyxl import load_workbook
def copy_sheet(source_file, target_file, sheet_name):
source_wb = load_workbook(source_file)
target_wb = load_workbook(target_file)
if sheet_name in source_wb.sheetnames:
source_ws = source_wb[sheet_name]
# 创建新的工作表
target_ws = target_wb.create_sheet(title=sheet_name)
# 复制单元格内容
for row in source_ws.iter_rows():
for cell in row:
target_ws[cell.coordinate].value = cell.value
# 保存目标文件
target_wb.save(target_file)
print(f"工作表 '{sheet_name}' 已从 {source_file} 复制到 {target_file}")
else:
print(f"源文件中不存在名为 '{sheet_name}' 的工作表")
# 使用方法
copy_sheet('source.xlsx', 'target.xlsx', 'Sheet1')
# 批量调整列宽
from openpyxl import load_workbook
def adjust_column_width(file_path):
wb = load_workbook(file_path)
ws = wb.active
for column in ws.columns:
max_length = 0
column_letter = column[0].column_letter # 获取列字母
for cell in column:
try:
if len(str(cell.value)) > max_length:
max_length = len(str(cell.value))
except:
pass
adjusted_width = (max_length + 2)
ws.column_dimensions[column_letter].width = adjusted_width
wb.save('adjusted_' + os.path.basename(file_path))
print("所有列宽调整完成")
# 使用方法
adjust_column_width('example.xlsx')
# 数据透视表创建
import pandas as pd
def create_pivot_table(input_file, output_file, index_columns, values_columns):
df = pd.read_excel(input_file)
pivot_table = pd.pivot_table(df, values=values_columns, index=index_columns, aggfunc='sum')
# 将透视表保存到新的Excel文件
pivot_table.to_excel(output_file)
print(f"数据透视表已生成并保存至: {output_file}")
# 使用方法
create_pivot_table('sales_data.xlsx', 'pivot_output.xlsx', ['Region'], ['Sales'])
# 批量添加图表
from openpyxl import load_workbook
from openpyxl.chart import BarChart, Reference
def add_chart_to_excel(file_path, sheet_name, chart_title, x_axis_title, y_axis_title, data_range):
wb = load_workbook(file_path)
ws = wb[sheet_name]
chart = BarChart()
chart.title = chart_title
chart.x_axis.title = x_axis_title
chart.y_axis.title = y_axis_title
data = Reference(ws, min_col=data_range['min_col'], min_row=data_range['min_row'],
max_col=data_range['max_col'], max_row=data_range['max_row'])
categories = Reference(ws, min_col=data_range['category_col'], min_row=data_range['category_min_row'],
max_row=data_range['category_max_row'])
chart.add_data(data, titles_from_data=True)
chart.set_categories(categories)
ws.add_chart(chart, "E5") # 在单元格E5处添加图表
wb.save('chart_added_' + os.path.basename(file_path))
print("图表添加完成")
# 使用方法
add_chart_to_excel('example.xlsx', 'Sheet1', '销售统计', '产品', '销售额',
{'min_col': 1, 'min_row': 2, 'max_col': 2, 'max_row': 7,
'category_col': 1, 'category_min_row': 2, 'category_max_row': 7})
# 合并相同内容的单元格
from openpyxl import load_workbook
from openpyxl.utils import get_column_letter
def merge_cells_with_same_content(file_path):
wb = load_workbook(file_path)
ws = wb.active
for col in range(1, ws.max_column + 1):
start = None
for row in range(1, ws.max_row + 1):
current_cell = ws[f"{get_column_letter(col)}{row}"]
next_cell = ws[f"{get_column_letter(col)}{row + 1}"] if row < ws.max_row else None
if start is None and current_cell.value == next_cell.value:
start = current_cell.coordinate
elif start is not None and current_cell.value != next_cell.value:
end = current_cell.coordinate
ws.merge_cells(f"{start}:{end}")
start = None
wb.save('merged_' + os.path.basename(file_path))
print("相同内容的单元格合并完成")
# 使用方法
merge_cells_with_same_content('example.xlsx')
# 从Excel中导出图片
from openpyxl import load_workbook
from openpyxl.drawing.image import Image
def extract_images_from_excel(file_path, output_dir):
wb = load_workbook(file_path, keep_vba=True)
ws = wb.active
for img in ws._images:
image = Image(img.ref)
image_path = os.path.join(output_dir, f"image_{img.anchor._from.row}.png")
image.save(image_path)
print(f"图片已保存至: {image_path}")
# 使用方法
extract_images_from_excel('example_with_images.xlsx', 'output_images')
# 批量转换日期格式
import pandas as pd
def convert_date_format(input_file, output_file, date_column, current_format, target_format):
df = pd.read_excel(input_file)
# 转换日期格式
df[date_column] = pd.to_datetime(df[date_column], format=current_format).dt.strftime(target_format)
# 保存结果
df.to_excel(output_file, index=False)
print(f"日期格式转换完成，结果已保存至: {output_file}")
# 使用方法
convert_date_format('dates.xlsx', 'formatted_dates.xlsx', 'Date', '%Y-%m-%d', '%d/%m/%Y')
# 根据条件拆分Excel文件
import pandas as pd
def split_excel_by_condition(input_file, column_name, condition_value):
df = pd.read_excel(input_file)
# 根据条件筛选数据
matching_df = df[df[column_name] == condition_value]
non_matching_df = df[df[column_name] != condition_value]
# 保存结果
matching_df.to_excel(f'matching_{condition_value}.xlsx', index=False)
non_matching_df.to_excel('non_matching.xlsx', index=False)
print(f"符合条件的数据已保存至: matching_{condition_value}.xlsx")
print("不符合条件的数据已保存至: non_matching.xlsx")
# 使用方法
split_excel_by_condition('data.xlsx', 'Category', 'A')
# 在Excel中添加水印
from openpyxl import load_workbook
from openpyxl.drawing.text import TextBlock, Paragraph, ParagraphProperties, CharacterProperties, Font
from openpyxl.drawing.spreadsheet_drawing import OneCellAnchor, AnchorMarker
from openpyxl.utils.units import cm_to_EMU
def add_watermark(file_path, watermark_text):
wb = load_workbook(file_path)
ws = wb.active
drawing = TextBlock(
Paragraph(paragraphProperties=ParagraphProperties(defRPr=CharacterProperties(sz=400))),
[Paragraph(watermark_text, paragraphProperties=ParagraphProperties(defRPr=CharacterProperties(sz=400)))])
anchor = OneCellAnchor(anchorRow=5, anchorCol=5,
_from=AnchorMarker(x=cm_to_EMU(2), y=cm_to_EMU(2)),
ext=AnchorMarker(x=cm_to_EMU(10), y=cm_to_EMU(1)))
ws.add_drawing(drawing, anchor)
wb.save('watermarked_' + os.path.basename(file_path))
print("水印添加完成")
# 使用方法
add_watermark('example.xlsx', '机密')
# 批量加密Excel文件
from openpyxl import load_workbook
from openpyxl.workbook.protection import WorkbookProtection
def encrypt_excel_files(directory, password):
for filename in os.listdir(directory):
if filename.endswith('.xlsx'):
file_path = os.path.join(directory, filename)
wb = load_workbook(file_path)
# 设置工作簿保护密码
wb.security = WorkbookProtection(workbookPassword=password, lockStructure=True)
# 保存加密后的文件
encrypted_filename = f'encrypted_{filename}'
wb.save(os.path.join(directory, encrypted_filename))
print(f"{filename} 已加密并保存为 {encrypted_filename}")
# 使用方法
encrypt_excel_files('input_directory', 'your_password')
# 批量更新超链接
from openpyxl import load_workbook
def update_hyperlinks(file_path, old_url, new_url):
wb = load_workbook(file_path)
for sheet in wb.worksheets:
for row in sheet.iter_rows():
for cell in row:
if cell.hyperlink and cell.hyperlink.target.startswith(old_url):
new_link = cell.hyperlink.target.replace(old_url, new_url)
cell.hyperlink = Hyperlink(display=None, ref=cell.coordinate,
location=None, tooltip=None, target=new_link)
print(f"超链接在单元格 {cell.coordinate} 中已从 {old_url} 更新为 {new_url}")
wb.save('updated_links_' + os.path.basename(file_path))
# 使用方法
update_hyperlinks('example.xlsx', 'http://oldwebsite.com', 'http://newwebsite.com')
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