python-excel
excel 中python用法
一、介绍Excel是一款广泛使用的电子表格软件，Python是一种流行的编程语言。
结合Excel和Python的使用可以提高数据处理的效率和灵活性。
本文将介绍在Excel中使用Python的方法和技巧。
二、Python插件安装1. 打开Excel并进入“文件”菜单。
2. 选择“选项”。
3. 在选项对话框中，选择“加载项”。
4. 点击“Excel加载项”下的“转到”按钮。
5. 在“添加-Ins”对话框中，点击“浏览”。
6. 找到并选择Python插件的安装文件，点击“打开”。
7. 完成安装并重启Excel。
三、使用Python进行数据处理1. 在Excel中新建一个工作表。
2. 在需要进行数据处理的单元格输入Python函数，例如“=Py.COUNTIF(A1:A10,">5")”。
3. 按下Enter键，Excel会调用Python插件执行该函数，并在单元格中显示结果。
四、Python函数示例1. 使用Python的COUNTIF函数统计大于5的数据个数。
2. 使用Python的SUM函数计算数据的总和。
3. 使用Python的AVERAGE函数计算数据的平均值。
4. 使用Python的IF函数进行条件判断。
5. 使用Python的VLOOKUP函数进行数据查找。
五、Python脚本执行1. 在Excel中打开一个工作表。
2. 点击“开发人员”选项卡。
3. 选择“插入”下的“ActiveX 控件”。
4. 在工作表中插入一个按钮控件，右键点击该按钮并选择“属性”。
5. 在“单击”事件中绑定Python脚本文件。
6. 点击按钮执行Python脚本，实现自定义的数据处理逻辑。
六、Python图表生成1. 在Excel中选择需要生成图表的数据范围。
2. 点击“插入”选项卡中的“插入统计图表”按钮。
3. 在弹出的对话框中选择“Python图表”。
4. 根据需要选择图表类型和样式，点击确定生成图表。
python excel 单元格格式
Python是一种功能强大的编程语言，其在处理Excel文件方面有着很高的适用性。
本文将介绍Python在处理Excel单元格格式方面的用法和技巧。
一、使用openpyxl库处理单元格格式1.安装openpyxl库使用pip命令可以很方便地安装openpyxl库。
```pythonpip install openpyxl```2.导入openpyxl库在Python代码中使用import语句导入openpyxl库。
```pythonimport openpyxl```3.打开Excel文件使用openpyxl.load_workbook()函数可以打开一个Excel文件，并返回一个workbook对象，以供后续操作。
```pythonworkbook = openpyxl.load_workbook('example.xlsx')```4.选择工作表通过workbook对象的get_sheet_by_name()方法或者active属性可以选择一个工作表。
```pythonsheet = workbook.active```5.设置单元格格式通过使用openpyxl库中的各种属性和方法，可以对单元格的格式进行修改。
比如设置字体样式、颜色、大小，设置边框样式和颜色，设置单元格的对齐方式等。
二、使用xlrd和xlwt库处理单元格格式1.安装xlrd和xlwt库同样使用pip命令可以安装xlrd和xlwt库。
```pythonpip install xlrdpip install xlwt```2.导入xlrd和xlwt库在Python代码中使用import语句导入xlrd和xlwt库。
```pythonimport xlrdimport xlwt```3.读取Excel文件使用xlrd库中的open_workbook()函数可以打开一个Excel文件，并返回一个workbook对象，以供后续操作。
使用python操作excel
使⽤python操作excel使⽤python操作excelpython操作excel主要⽤到xlrd和xlwt这两个库，即xlrd是读excel，xlwt是写excel的库。
安装xlrd模块#pip install xlrd使⽤介绍常⽤单元格中的数据类型 empty（空的） string（text） number date boolean error blank（空⽩表格） empty为0，string为1，number为2，date为3，boolean为4， error为5（左边为类型，右边为类型对应的值）导⼊模块import xlrd打开Excel⽂件读取数据data = xlrd.open_workbook(filename[, logfile, file_contents, ...])#⽂件名以及路径，如果路径或者⽂件名有中⽂给前⾯加⼀个r标识原⽣字符。
#filename：需操作的⽂件名（包括⽂件路径和⽂件名称）；若filename不存在，则报错FileNotFoundError；若filename存在，则返回值为xlrd.book.Book对象。
常⽤的函数 excel中最重要的⽅法就是book和sheet的操作# （1）获取book中⼀个⼯作表names = data.sheet_names()#返回book中所有⼯作表的名字table = data.sheets()[0]#获取所有sheet的对象，以列表形式显⽰。
可以通过索引顺序获取，table = data.sheet_by_index(sheet_indx))#通过索引顺序获取，若sheetx超出索引范围，则报错IndexError；若sheetx在索引范围内，则返回值为xlrd.sheet.Sheet对象table = data.sheet_by_name(sheet_name)#通过名称获取，若sheet_name不存在，则报错xlrd.biffh.XLRDError；若sheet_name存在，则返回值为xlrd.sheet.Sheet对象以上三个函数都会返回⼀个xlrd.sheet.Sheet()对象data.sheet_loaded(sheet_name or indx)# 检查某个sheet是否导⼊完毕，返回值为bool类型，若返回值为True表⽰已导⼊；若返回值为False表⽰未导⼊# （2）⾏的操作nrows = table.nrows#获取该sheet中的有效⾏数table.row(rowx)#获取sheet中第rowx+1⾏单元，返回值为列表；列表每个值内容为：单元类型:单元数据table.row_slice(rowx[, start_colx=0, end_colx=None])#以切⽚⽅式获取sheet中第rowx+1⾏从start_colx列到end_colx列的单元，返回值为列表；列表每个值内容为：单元类型:单元数据table.row_types(rowx, start_colx=0, end_colx=None)#获取sheet中第rowx+1⾏从start_colx列到end_colx列的单元类型，返回值为array.array类型。
Python模块之pyexcel_xls
Python模块之pyexcel_xls⼀、适⽤场景在很多数据统计或者数据分析的场景中，我们都会使⽤到excel；在⼀些系统中我们也会使⽤excel作为数据导⼊和导出的⽅式，那么如何使⽤python加以辅助我们快速进⾏excel数据做更多复杂和精确的处理，下⾯通过pyexcel_xls模块进⾏。
⼆、模块概述pyexcel-xls 以 OrderedDict 结构处理数据，将整个excel⽂件转化为⼀个OrderedDict (有序字典)结构：每个key就是⼀个⼦表（Sheet）；每个⼦表（Sheet），转化为⼀个列表结构：很像⼆维数组，第⼀层列表为⾏（Row），⾏的下标为列（Column），对应的值为单元格的值；编码为 unicode，如果有中⽂必须进⾏转换。
三、读excel数据（xls,xlsx）3.1 先创建⼀个excle⽂件，readfile.xls，⾥⾯有如下数据：3.2 下⾯看如何读取这个⽂件：#!/usr/bin/env python# -*- coding:utf-8 -*-___Author___ = "Alfred Xue"___Date_____ = "2017/11/8 上午10:08"# pyexcel_xls 以 OrderedDict 结构处理数据from collections import OrderedDictfrom pyexcel_xls import save_datafrom pyexcel_xls import get_datadef read_xls_file():data = get_data(r"data/readfile.xls")print("数据格式：" type(data))for sheet_n in data.keys():print(sheet_n, ":", data[sheet_n])if__name__ == "__main__":read_xls_file()输出结构：数据格式： <class'collections.OrderedDict'>Sheet1 : [['ID', '⽤户名', '密码', '⾓⾊'], ['00001', 'Alfred', 'adfaoiqjofj', '管理员'], ['00002', 'Jack', ';kndfiqoe', '⽤户'], [], [], [], [], [], [], [], []]Process finished with exit code 0可以看到：整个excel⽂件，转化为⼀个OrderedDict (有序字典)结构：每个key就是⼀个⼦表（Sheet）。
python excel分列 制定分隔符 案例
一、引言随着信息技术的发展，数据处理已经成为各行各业中不可或缺的一部分。
在日常工作中，我们经常会遇到需要将数据进行分列分隔的情况，而Excel作为一款常用的数据处理工具，也提供了多种方法来实现这一目的。
本文将主要介绍如何利用Python来对Excel中的数据进行分列，并制定分隔符的方法，并结合实际案例进行说明。
二、Python处理Excel分列的方法1. 使用pandas库Pandas是一款功能强大的数据分析工具，在处理Excel数据时十分实用。
通过pandas库，我们可以很容易地对Excel中的数据进行分列和制定分隔符。
我们需要利用pandas的read_excel方法将Excel文件中的数据读取为DataFrame格式。
接下来，可以使用DataFrame的str.split方法将数据按照指定的分隔符进行分列。
再将处理后的数据保存到新的Excel文件中。
2. 使用openpyxl库Openpyxl是一款专门用于读写Excel文件的Python库，通过它，我们也可以很方便地对Excel数据进行分列。
我们需要使用openpyxl的load_workbook方法打开Excel文件，并定位到我们需要进行操作的工作表。
可以通过遍历工作表中的每一行数据，使用split方法按照指定的分隔符进行分列处理。
再将处理后的数据保存到新的Excel文件中。
三、案例分析为了更好地理解Python处理Excel分列并制定分隔符的方法，我们将以一份包含学生成绩信息的Excel文件为例进行说明。
该Excel文件中包含学生尊称和各科成绩，而每个学生的成绩都是用逗号分隔的。
我们希望将每个学生的成绩分列开，并且重新使用冒号作为分隔符。
1. 使用pandas库我们使用pandas库的read_excel方法将Excel文件中的数据读取为DataFrame格式。
```pythonimport pandas as pddf = pd.read_excel('学生成绩.xlsx')```可以使用DataFrame的str.split方法将数据按照逗号进行分列。
python excel解析
python excel解析Python是一门强大的编程语言，它可以与多种文件格式交互，包括Microsoft Excel。
利用Python语言，我们可以读取、处理和创建Excel文件，以及从Excel文件中提取有用的信息。
在Python中，我们可以使用第三方库——openpyxl来操作Excel文件。
openpyxl可以读取和写入Excel文件中的数据、格式和图表，也可以创建新的Excel文件。
下面是一些openpyxl库所支持的操作：1. 读取Excel文件要读取Excel文件，我们需要使用openpyxl库中的load_workbook 函数。
load_workbook函数将Excel文件作为输入，并返回一个Workbook对象，该对象包含Excel文件中的所有工作表。
2. 读取工作表一旦我们加载了Excel文件，我们就可以通过名字或索引访问其中的工作表。
我们可以使用Worksheet对象中的cell函数读取单元格中的数据，或使用iter_rows函数读取整个工作表中的行。
3. 写入Excel文件要写入Excel文件，我们需要使用Workbook对象的create_sheet函数创建新的工作表。
我们可以使用Worksheet对象中的cell函数写入单元格中的数据，或使用append函数向工作表中添加新行。
4. 格式化Excel文件我们可以使用openpyxl库中的各种函数和属性来格式化Excel文件。
例如，我们可以设置列宽、行高、单元格字体、颜色和边框等。
5. 创建图表使用openpyxl库，我们可以创建各种类型的图表，例如线图、柱状图、饼图等。
我们可以使用Chart对象中的各种函数和属性来设置图表的大小、数据系列、颜色等。
总之，利用Python和openpyxl库可以轻松地操作Excel文件。
无论是读取数据、处理数据还是创建新的Excel文件，Python都可以成为您的得力助手。
python处理excel实例
python处理excel实例Python是一种强大的编程语言，可以用于各种各样的任务，包括数据处理。
Excel是一个广泛使用的电子表格应用程序，用于处理和管理数据。
Python可以与Excel相结合，提供更高效和灵活的数据处理方式。
下面是一些Python处理Excel的实例：1.读取Excel文件: Python可以使用pandas包中的read_excel 函数读取Excel文件。
下面是一个简单的读取Excel文件的代码示例： import pandas as pd#读取Excel文件data = pd.read_excel('file.xlsx')print(data)2.写入Excel文件: Python也可以使用pandas包中的to_excel 函数将数据写入Excel文件。
下面是一个简单的写入Excel文件的代码示例：import pandas as pd#创建数据data = {'姓名': ['张三', '李四', '王五'], '年龄': [20, 25, 30]}#将数据转换为DataFrame格式df = pd.DataFrame(data)#将DataFrame写入Excel文件df.to_excel('file.xlsx', index=False)3.修改Excel文件: Python可以使用openpyxl包中的load_workbook函数打开Excel文件，并使用它的方法修改文件。
下面是一个简单的修改Excel文件的代码示例：from openpyxl import load_workbook#加载Excel文件wb = load_workbook('file.xlsx')#获取工作表ws = wb.active#修改单元格ws['A1'] = '姓名'ws['B1'] = '年龄'#保存文件wb.save('file.xlsx')这些实例只是Python处理Excel的基础知识，还有很多其他的功能和技巧可以使用。
python excel的读写
python excel的读写Python是一种功能强大的编程语言，可以用于处理各种类型的数据。
在数据处理中，Excel是一种常用的工具，因此，Python提供了许多库和模块，用于读写Excel文件。
本文将介绍如何使用Python 进行Excel的读写操作。
我们需要安装一个Python库，用于处理Excel文件。
最常用的库是`openpyxl`，它提供了许多功能，包括读取和写入Excel文件。
要安装`openpyxl`库，可以使用以下命令：```pip install openpyxl```安装完成后，我们就可以开始读取和写入Excel文件了。
我们来看看如何读取Excel文件。
假设我们有一个名为`data.xlsx`的Excel文件，其中包含了一些数据。
我们可以使用以下代码来读取该文件：```pythonimport openpyxl# 打开Excel文件workbook = openpyxl.load_workbook('data.xlsx')# 选择第一个工作表sheet = workbook.active# 遍历工作表中的每一行for row in sheet.iter_rows():# 遍历每一行中的每一列for cell in row:# 输出单元格的值print(cell.value)```上述代码中，我们首先使用`load_workbook()`函数打开Excel文件。
然后，我们选择第一个工作表，并使用`iter_rows()`方法遍历工作表中的每一行。
在内部循环中，我们遍历每一行中的每一列，并输出单元格的值。
接下来，我们来看看如何写入Excel文件。
假设我们有一些数据，我们想要将其写入到一个名为`output.xlsx`的Excel文件中。
我们可以使用以下代码来实现：```pythonimport openpyxl# 创建一个新的工作簿workbook = openpyxl.Workbook()# 创建一个新的工作表sheet = workbook.active# 将数据写入工作表data = [['姓名', '年龄', '性别'],['张三', 18, '男'],['李四', 20, '女'],['王五', 22, '男']]for row in data:sheet.append(row)# 保存工作簿workbook.save('output.xlsx')```上述代码中，我们首先创建一个新的工作簿，并使用`active`属性选择第一个工作表。
python处理excel实例
python处理excel实例Python是一种功能强大的编程语言，可以用来处理各种数据类型，包括Excel文件。
Python处理Excel文件的能力极强，可以进行数据提取、数据处理、数据分析等多方面操作。
下面是一个Python处理Excel文件的实例：1. 导入所需的库```pythonimport openpyxl```2. 读取Excel文件```pythonwb = openpyxl.load_workbook('example.xlsx')```这个代码块会打开名为example.xlsx的Excel文件，并将其存储在变量wb中。
3. 选择工作表```pythonsheet = wb['Sheet1']```这个代码块会选择名为Sheet1的工作表，并将其存储在变量sheet中。
4. 读取单元格数据cell_value = sheet['A1'].value```这个代码块会读取A1单元格的数据，并将其存储在变量cell_value中。
5. 读取行数据```pythonrow_values = []for row in sheet.iter_rows(min_row=2, max_col=3):row_values.append([cell.value for cell in row])```这个代码块会读取工作表中第2行到最后一行、第1列到第3列的数据，并将其存储在列表row_values中。
6. 读取列数据```pythoncolumn_values = []for column in sheet.iter_cols(min_row=2, max_row=4):column_values.append([cell.value for cell in column]) ```这个代码块会读取工作表中第2列到第4列、第1行到最后一行的数据，并将其存储在列表column_values中。
python操作excel----python打开及读取excel表格
python操作excel----python打开及读取excel表格from openpyxl import load_workbook# 只能打开已经存在的表格，不能⽤该⽅法创建⼀个新的表格workbook = load_workbook(filename='score.xlsx')# 获取表格⽂件内的所有sheet名称 ['Sheet1', 'Sheet2', 'Sheet3']print(workbook.sheetnames)# 通过sheet名称获取表格# sheet = workbook[workbook.sheetnames[0]]# 如果只有⼀张表，可以直接打开sheet = workbook.active# 获取表格的尺⼨⼤⼩print(sheet.dimensions) # A1:T25# 读取某⼀个格⼦ sheet['B2'] ; 获取⼀系列格⼦ sheet['B'] sheet['B2:B5'] sheet['A:C'] ; sheet[2] 第⼆⾏,按⾏获取cell = sheet['B2']print(cell.value)# 指定⾏列的范围，按⾏获取for row in sheet.iter_rows(min_row=2, max_row=3, min_col=1, max_col=2):print(row)# 指定⾏列的范围，按列获取for col in sheet.iter_cols(min_row=2, max_row=3, min_col=1, max_col=2):print(col)# 迭代整个表格的所有⾏for row in sheet.rows:print(row)# 迭代整个表格的所有列for col in sheet.cols:print(col)# 获取某个格⼦的⾏数、列数、坐标print(cell.row, cell.column, cell.coordinate)# ⽤⾏数和列数定位某⼀个格⼦cell = sheet.cell(row=1, column=1)from openpyxl import load_workbook# 只能打开已经存在的表格，不能⽤该⽅法创建⼀个新的表格workbook = load_workbook filename='score.xlsx'# 获取表格⽂件内的所有sheet名称 ['Sheet1', 'Sheet2', 'Sheet3']print workbook.sheetnames# 通过sheet名称获取表格# sheet = workbook[workbook.sheetnames[0]]# 如果只有⼀张表，可以直接打开sheet = workbook.active# 获取表格的尺⼨⼤⼩print sheet.dimensions# A1:T25# 读取某⼀个格⼦ sheet['B2'] ; 获取⼀系列格⼦ sheet['B'] sheet['B2:B5'] sheet['A:C'] ; sheet[2] 第⼆⾏,按⾏获取cell = sheet'B2'print cell.value# 指定⾏列的范围，按⾏获取for row in sheet.iter_rows min_row=2, max_row=3, min_col=1, max_col=2:print row# 指定⾏列的范围，按列获取for col in sheet.iter_cols min_row=2, max_row=3, min_col=1, max_col=2:print col# 迭代整个表格的所有⾏for row in sheet.rows:print row# 迭代整个表格的所有列for col in sheet.cols:print col# 获取某个格⼦的⾏数、列数、坐标print cell.row, cell.column, cell.coordinate # ⽤⾏数和列数定位某⼀个格⼦cell = sheet.cell row=1, column=1。
python对excel文件的处理
python对excel⽂件的处理python处理excel⽂件有很多⽅法，最开始接触的是xlrd、xlsxwriter模块，分别⽤于excel⽂件的读、写。
后来⼜学习了openpyxl模块，可以同时完成excel⽂件的读、写。
再后来，接触了⼤⽜pandas，这是python中专门⽤于数据分析的模块，有更加强⼤的功能。
本⽂尝试梳理⼀下这⼏个⽅法，以实际案例来对⽐各种⽅法的优劣。
1. xlrd、xlsxwriter模块1import xlrd #读取excel⽂件2import xlsxwriter #写⼊excel⽂件3 file_name = r'C:/2020/python-exer/excel_doc/time_fmt.xls' #存在⼀个excel⽂件，⽤于读4 file_name1 = r'C:/2020/python-exer/excel_doc/time_fmt_output.xls' #新建⼀个excel⽂件，⽤于写5# 读取excel⽂件，按⾏读取数据，每⾏数据对应⼀个列表元素6def excel_lines():7 wb = xlrd.open_workbook(file_name)8# 打开Excel⽂件9 sheet1 = wb.sheet_by_name('Sheet1') # 通过excel表格sheet名称获取⼯作表10 dat = [] # 创建空list11 Max_lines = sheet1.nrows # sheet1数据最⼤⾏数,即便每列元素不同。
12print(Max_lines)13for a in range(Max_lines):14 cells = sheet1.row_values(a) # 每⾏数据赋值给cells15 dat.append(cells)16return datView Code#>>>[['序号', '时间格式定义'], [1.0, '%a Locale’s abbreviated weekday name. '],[2.0, '%A Locale’s full weekday name. '],……从输出内容看出，得到的是⼀个嵌套list，每⾏数据对应着⼀个list元素。
python excel合并单元格填充方案
Python是一种高级编程语言，它在数据处理和分析领域有着广泛的应用。
而在日常办公中，Excel也是一种被广泛使用的办公软件，它的数据处理和展示功能在各行各业都得到了充分的利用。
本文将讨论如何使用Python对Excel中的单元格进行合并和填充操作，使得数据处理更加高效和便捷。
1. 背景介绍在实际工作中，我们经常会遇到需要对Excel表格中的单元格进行合并和填充操作的情况。
当我们需要将多个单元格的数据合并成一个单元格，并且需要对合并后的单元格进行填充颜色或者文字格式设置时，手动操作显然效率太低，且容易出错。
而使用Python可以很好地解决这个问题，通过编写简单的代码即可实现对Excel表格的自动化处理。
2. Python库介绍在Python中，有几个强大的库可以用来处理Excel表格，比如pandas、openpyxl和xlrd/xlwt等。
在本文中，我们将以openpyxl 库为例来介绍如何实现对Excel中单元格的合并和填充操作。
3. 安装和导入openpyxl库在进行任何Python代码编写之前，我们首先需要安装openpyxl库。
我们可以使用pip命令来安装该库，具体命令如下：```pythonpip install openpyxl```在安装完成后，我们需要在Python代码中导入openpyxl库，具体代码如下：```pythonimport openpyxl```4. 打开Excel表格在进行任何对Excel表格的操作之前，我们首先需要打开Excel表格并定位到我们要操作的工作表。
这可以通过openpyxl库中的load_workbook方法来实现，具体代码如下：```pythonwb = openpyxl.load_workbook('example.xlsx')sheet = wb['Sheet1']```在上面的代码中，我们使用load_workbook方法打开了一个名为'example.xlsx'的Excel表格，并且定位到了该表格中的'Sheet1'工作表。
python保存excel的5种方法
python保存excel的5种方法Python 是一种功能强大的编程语言，广泛应用于数据分析、数据可视化等领域。
在处理数据时，我们常常需要将数据保存为Excel 格式。
本文将介绍使用Python 保存Excel 文件的五种方法。
### 1.使用pandas 库`pandas` 是一个专门用于数据分析和数据处理的Python 库。
它提供了非常简单易用的方法来保存DataFrame 到Excel 文件。
```pythonimport pandas as pd# 创建一个简单的DataFramedf = pd.DataFrame({"A": [1, 2, 3],"B": [4, 5, 6]})# 保存DataFrame到Excel文件df.to_excel("output.xlsx", index=False)```### 2.使用openpyxl 库`openpyxl` 是一个用于处理`.xlsx` 文件的Python 库。
它允许你手动创建和修改Excel 文件。
```pythonfrom openpyxl import Workbook# 创建一个工作簿和工作表wb = Workbook()ws = wb.active# 添加数据ws["A1"] = "Hello"ws["B1"] = "World"# 保存文件wb.save("output_openpyxl.xlsx")```### 3.使用xlsxwriter 库`xlsxwriter` 是一个用于创建`.xlsx` 文件的Python 库。
它支持更复杂的格式设置和功能，如添加图表和格式化单元格。
```pythonimport xlsxwriter# 创建一个工作簿和工作表wb = xlsxwriter.Workbook("output_xlsxwriter.xlsx")ws = wb.add_worksheet()# 添加数据ws.write("A1", "Hello")ws.write("B1", "World")# 关闭工作簿wb.close()```### 4.使用xlwt 库`xlwt` 是一个用于创建`.xls` 文件的Python 库（注意：不是`.xlsx`）。
python excel模糊匹配 -回复
python excel模糊匹配-回复Python中有许多强大的库可以处理Excel文件，其中一个常用的库是pandas。
在本文中，我们将使用pandas库通过模糊匹配的方式在Excel文件中查找相应的数据。
首先，我们需要安装pandas库。
可以使用以下命令在终端或命令提示符中安装pandas：pip install pandas安装完成后，我们可以导入pandas库，并读取我们的Excel文件。
假设我们的Excel文件名为“data.xlsx”，其中包含一个名为“Sheet1”的工作表。
可以使用以下代码读取该文件：pythonimport pandas as pd# 读取Excel文件data = pd.read_excel('data.xlsx', sheet_name='Sheet1')接下来，我们需要定义一个模糊匹配函数。
此函数将接受一个主题作为输入，并返回与该主题相关的所有行。
pythondef fuzzy_match(theme):# 创建一个空的DataFrame来存储匹配结果result = pd.DataFrame(columns=data.columns)# 使用模糊匹配查找相关行for index, row in data.iterrows():if theme in row['主题']:result = result.append(row, ignore_index=True) return result在此函数中，我们遍历了Excel文件中的每一行，检查主题列是否包含我们输入的主题。
如果找到了匹配的行，将其添加到结果DataFrame中。
现在，我们可以使用模糊匹配函数来查找与指定主题相关的行。
假设我们要查找与主题“Python”相关的数据，可以使用以下代码：pythontheme = 'Python'matched_data = fuzzy_match(theme)在上述代码中，我们定义了一个名为“theme”的变量，并将其设为“Python”。
python excel条件格式
python excel条件格式摘要：1.Python 与Excel 条件格式的基础知识2.条件格式的种类和应用场景3.使用Python 实现Excel 条件格式的方法和示例4.常见问题和解决方法正文：一、Python 与Excel 条件格式的基础知识Python 是一种广泛应用于数据处理和自动化的编程语言，而Excel 是办公软件中常用的电子表格软件。
Python 可以与Excel 进行交互，实现对Excel 文件的操作。
条件格式是Excel 中的一种功能，可以根据设定的条件来自动改变单元格的格式，如字体颜色、背景颜色等。
二、条件格式的种类和应用场景1.种类：Excel 提供了多种条件格式，如基于单元格数值的条件格式、基于单元格内容的条件格式、基于公式的结果的条件格式等。
2.应用场景：条件格式在实际应用中可以提高工作效率，例如在数据分析时，可以根据数据大小或者特定条件来高亮显示关键数据，便于用户快速识别和分析。
三、使用Python 实现Excel 条件格式的方法和示例Python 中有多种库可以实现与Excel 的交互，其中较为常用的是`openpyxl`库。
使用Python 实现Excel 条件格式的方法如下：1.首先，需要安装`openpyxl`库，可以使用以下命令进行安装：```pip install openpyxl```2.导入库，并创建一个新的Excel 工作簿：```pythonimport openpyxlworkbook = openpyxl.Workbook()```3.选择活动工作表，并创建一个新的条件格式规则：```pythonworksheet = workbook.active# 创建一个基于单元格数值的条件格式规则rule = openpyxl.ConditionalFormatRule(type="format",formula1="=A1<50", # 当A1 单元格的数值小于50 时，应用条件格式format_value="0000FF", # 设置字体颜色为红色operator="B", # 应用条件格式的优先级)```4.将条件格式规则应用于指定的单元格范围：```pythonworksheet["A1:A10"].conditionally_format(rule)```5.将工作簿保存为Excel 文件：```pythonworkbook.save("conditional_format_example.xlsx")```四、常见问题和解决方法在使用Python 实现Excel 条件格式时，可能会遇到一些问题，如条件格式不生效、格式与预期不符等。
python excel 单元格注释
Python Excel 单元格注释随着信息化时代的到来，Excel表格在各行业的应用越来越广泛。
作为一种强大的办公软件，Excel表格不仅可以帮助用户进行数据处理和分析，还可以实现数据的可视化和报表的生成。
在Excel表格中，单元格注释是一种非常重要的功能，它可以让用户在特定的单元格内添加说明性文字，以便于他人更好地理解和使用该表格。
而在Python中，我们也可以通过一些库实现对Excel表格的操作，包括单元格注释的添加和编辑。
本篇文章将详细介绍Python中如何对Excel表格的单元格进行注释的操作。
一、使用openpyxl库对Excel表格进行单元格注释1.安装openpyxl库在Python中，我们可以使用openpyxl库来对Excel表格进行操作。
如果你还没有安装openpyxl库，可以通过以下命令进行安装：```pythonpip install openpyxl```2.导入openpyxl库在使用openpyxl库对Excel表格进行操作之前，我们需要先导入该库：```pythonimport openpyxl```3.打开Excel表格在对Excel表格进行操作之前，我们需要先打开该表格。
可以通过openpyxl库中的load_workbook()函数来实现：```pythonworkbook = openpyxl.load_workbook('example.xlsx')```其中'example.xlsx'是你要操作的Excel表格文件名。
4.选择工作表在打开Excel表格后，我们还需要选择具体的工作表进行操作。
可以通过以下命令选择第一个工作表：```pythonsheet = workbook.active```如果你要选择其他的工作表，可以通过以下命令实现：```pythonsheet = workbook['Sheet1']```5.添加单元格注释在打开Excel表格并选择了具体的工作表之后，我们就可以对单元格添加注释了。
利用python对excel中的特定数据提取并写入新表的方法
利用python对excel中的特定数据提取并写入新表的方法一、引言在实际工作中，我们常常需要利用Python对Excel文件中的特定数据进行提取，并将其写入新的表格。
本文将详细介绍如何利用Python实现这一目的，从而提高数据处理的效率。
二、Python提取Excel数据库方法1.安装库要处理Excel文件，我们需要安装python-openpyxl库。
在命令行中输入以下命令进行安装：```pip install openpyxl```2.读取Excel文件首先，我们需要导入openpyxl库，并使用openpyxl.load_workbook()函数读取Excel文件。
```pythonimport openpyxl# 读取Excel文件workbook = openpyxl.load_workbook("example.xlsx")```3.提取特定数据接下来，我们需要根据需求提取Excel文件中的特定数据。
以下是一个简单的示例，提取A1单元格的值：```python# 提取A1单元格数据cell_value = workbook["Sheet1"].cell(1, 1).value```三、将提取的数据写入新表1.创建新表结构首先，我们需要创建一个新的Excel文件，并设置新表的结构。
以下代码示例创建了一个包含3列的新表：```python# 创建新表ew_workbook = workbook.copy(title="New Sheet")# 获取新表ew_sheet = new_workbook["New Sheet"]# 设置新表列宽for col in range(1, 4):new_sheet["A" + str(col)].column_width = 10```2.写入数据接下来，我们将提取的特定数据写入新表。
python 读取excel 表格方法
这段代码会输出第一行第一列单元格中的数据。将row和column参数设置为要读取的单元格的行号和列号即可。如果要获取整行或整列的数据，可以使用iter_rows或iter_cols方法。
六、遍历整个工作表
如果需要遍历整个工作表的数据，可以使用iter_rows方法，代码如下：
```python
```
现在，可以开始使用openpyxl库来读取Excel表格了。
三、打开Excel文件
要读取Excel表格，首先需要打开Excel文件。使用openpyxl库的load_workbook函数可以打开一个Excel文件，代码如下：
```python
workbook = openpyxl.load_workbook('example.xlsx')
```python
pip install openpyxl
```
安装完成后，就可以使用openpyxl库来操作Excel表格了。
二、导入openpyxl库
在使用openpyxl库之前，需要先导入它。可以使用以下代码将openpyxl库导入到Python脚本中：
```python
import openpyxl
十、处理大批量Excel文件
在实际工作中，可能需要处理大批量的Excel文件。openpyxl库可以很方便地处理这种情况，可以使用Python的文件操作功能和循环结合openpyxl库来实现批量处理。比如可以遍历文件夹中的所有Excel文件，对其进行读取、修改或合并等操作。
十一、与其他库结合使用
除了openpyxl库外，Python还有许多其他强大的数据处理和可视化库，比如pandas、numpy和matplotlib等。可以将openpyxl库与这些库结合使用，实现更复杂的数据处理和分析。比如可以使用pandas库读取Excel数据并进行分析，然后将分析结果再写回Excel文件中。
python操作Excel的5种方式
python操作Excel的5种⽅式Python对Excel的读写主要有xlrd、xlwt、xlutils、openpyxl、xlsxwriter⼏种。
1.xlrd主要是⽤来读取excel⽂件import xlrddata = xlrd.open_workbook('abcd.xls') # 打开xls⽂件table = data.sheets()[0] # 打开第⼀张表nrows = table.nrows # 获取表的⾏数for i in range(nrows): # 循环逐⾏打印if i == 0:# 跳过第⼀⾏continueprint (table.row_values(i)[:13]) # 取前⼗三列⽰例：#coding=utf-8########################################################filename:test_xlrd.py#author:defias#date:xxxx-xx-xx#function：读excel⽂件中的数据#######################################################import xlrd#打开⼀个workbookworkbook = xlrd.open_workbook('E:\\Code\\Python\\testdata.xls')#抓取所有sheet页的名称worksheets = workbook.sheet_names()print('worksheets is %s' %worksheets)#定位到sheet1worksheet1 = workbook.sheet_by_name(u'Sheet1')"""#通过索引顺序获取worksheet1 = workbook.sheets()[0]#或worksheet1 = workbook.sheet_by_index(0)""""""#遍历所有sheet对象for worksheet_name in worksheets:worksheet = workbook.sheet_by_name(worksheet_name)"""#遍历sheet1中所有⾏rownum_rows = worksheet1.nrowsfor curr_row in range(num_rows):row = worksheet1.row_values(curr_row)print('row%s is %s' %(curr_row,row))#遍历sheet1中所有列colnum_cols = worksheet1.ncolsfor curr_col in range(num_cols):col = worksheet1.col_values(curr_col)print('col%s is %s' %(curr_col,col))#遍历sheet1中所有单元格cellfor rown in range(num_rows):for coln in range(num_cols):cell = worksheet1.cell_value(rown,coln)print cell"""#其他写法：cell = worksheet1.cell(rown,coln).valueprint cell#或cell = worksheet1.row(rown)[coln].valueprint cell#或cell = worksheet1.col(coln)[rown].valueprint cell#获取单元格中值的类型，类型 0 empty,1 string, 2 number, 3 date, 4 boolean, 5 errorcell_type = worksheet1.cell_type(rown,coln)print cell_type"""2.xlwt主要是⽤来写excel⽂件#Python学习交流群：778463939import xlwtwbk = xlwt.Workbook()sheet = wbk.add_sheet('sheet 1')sheet.write(0,1,'test text')#第0⾏第⼀列写⼊内容wbk.save('test.xls')3.xlutils结合xlrd可以达到修改excel⽂件⽬的import xlrdfrom xlutils.copy import copyworkbook = xlrd.open_workbook(u'有趣装逼每⽇数据及趋势.xls')workbooknew = copy(workbook)ws = workbooknew.get_sheet(0)ws.write(3, 0, 'changed!')workbooknew.save(u'有趣装逼每⽇数据及趋势copy.xls')4.openpyxl可以对excel⽂件进⾏读写操作from openpyxl import Workbookfrom openpyxl import load_workbookfrom openpyxl.writer.excel import ExcelWriterworkbook_ = load_workbook(u"新歌检索失败1477881109469.xlsx") sheetnames =workbook_.get_sheet_names() #获得表单名字print sheetnamessheet = workbook_.get_sheet_by_name(sheetnames[0])print sheet.cell(row=3,column=3).valuesheet['A1'] = '47'workbook_.save(u"新歌检索失败1477881109469_new.xlsx")wb = Workbook()ws = wb.activews['A1'] = 4wb.save("新歌检索失败.xlsx")⽰例：import openpyxl# 新建⽂件workbook = openpyxl.Workbook()# 写⼊⽂件sheet = workbook.activesheet['A1']='A1'# 保存⽂件workbook.save('test.xlsx')5.xlsxwriter可以写excel⽂件并加上图表import xlsxwriterdef get_chart(series):chart = workbook.add_chart({'type': 'line'})for ses in series:name = ses["name"]values = ses["values"]chart.add_series({'name': name,'categories': 'A2:A10','values':values})chart.set_size({'width': 700, 'height': 350})return chartif __name__ == '__main__':workbook = xlsxwriter.Workbook(u'H5应⽤中⼼关键数据及趋势.xlsx') worksheet = workbook.add_worksheet(u"每⽇PV,UV")headings = ['⽇期', '平均值']worksheet.write_row('A1', headings)index=0for row in range(1,10):for com in [0,1]:worksheet.write(row,com,index)index+=1series = [{"name":"平均值","values":"B2:B10"}]chart = get_chart(series)chart.set_title ({'name': '每⽇页⾯分享数据'})worksheet.insert_chart('H7', chart)workbook.close()openpyxl⽰例：import xlsxwriter as xw#新建excelworkbook = xw.Workbook('myexcel.xlsx')#新建⼯作薄worksheet = workbook.add_worksheet()#写⼊数据worksheet.wirte('A1',1)#关闭保存workbook.close()合并表格实例：#coding:utf-8import xlsxwriterimport xlrd#新建excelworkbook = xlsxwriter.Workbook('⼴东.xlsx')#新建⼯作薄worksheet = workbook.add_worksheet()count = 1worksheet.write("A%s"%count,"公司名称")worksheet.write("B%s"%count,"法⼈")worksheet.write("C%s"%count,"电话")worksheet.write("D%s"%count,"注册资⾦")worksheet.write("E%s"%count,"注册时间")count+=1for i in range(1,153):data = xlrd.open_workbook('ah (%s).xls'%i) # 打开xls⽂件 table = data.sheets()[0] # 打开第⼀张表nrows = table.nrows # 获取表的⾏数for i in range(nrows): # 循环逐⾏打印if i == 0:# 跳过第⼀⾏continue# print (table.row_values(i)[:5]) # 取前⼗三列print(count,table.row_values(i)[:5][0])#写⼊数据#设定第⼀列（A）宽度为20像素 A:E表⽰从A到Eworksheet.set_column('A:A',30)worksheet.set_column('B:E',20)worksheet.write("A%s"%count,table.row_values(i)[:5][0]) worksheet.write("B%s"%count,table.row_values(i)[:5][1]) worksheet.write("C%s"%count,table.row_values(i)[:5][2]) worksheet.write("D%s"%count,table.row_values(i)[:5][3]) worksheet.write("E%s"%count,table.row_values(i)[:5][4]) count+=1#关闭保存workbook.close()。
python--Excel模块xlwings
python--Excel模块xlwings 安装：pip install xlwings基本操作：xlwings的特⾊:xlwings能够⾮常⽅便的读写Excel⽂件中的数据，并且能够进⾏单元格格式的修改可以和matplotlib以及pandas⽆缝连接可以调⽤Excel⽂件中VBA写好的程序，也可以让VBA调⽤⽤Python写的程序。
开源免费，⼀直在更新【能读出公式计算的值】新建⼯作簿：import xlwings as xwapp = xw.App(visible=True,add_book=False) #创建应⽤#visible=True 显⽰Excel⼯作簿；False 不显⽰⼯作簿#add_book=False 不再新建⼀个⼯作簿;True 另外再新建⼀个⼯作簿wb = app.books.add() #新建⼯作簿sh1=xw.books.active #引⽤活动⼯作薄wb.activate() #激活为当前⼯作簿打开已有⼯作簿：⽅式⼀：import xlwings as xwapp = xw.App(visible=True,add_book=False)wb = app.books.open('D:\sample.xlsx') #读⼊已有⼯作簿⽅式⼆：import xlwings as xwwb = xw.Book('D:\sample.xlsx') #读⼊已有⼯作簿#⼯作簿不显⽰保存⼯作簿：import xlwings as xwwb = xw.Book('D:\sample.xlsx')wb.save('D:\samplelm.xlsx') #保存⼯作簿参数可以省略：⼯作簿的原路径或脚本所在的路径退出和关闭：import xlwings as xwapp = xw.App(visible=True,add_book=False)wb = app.books.open('D:\sample.xlsx')wb.close() #关闭⼯作簿(程序不能编辑了)----显⽰的⽂件不关闭app.quit() #退出应⽤---显⽰的⽂件也关闭⼯作表操作：import xlwings as xwapp = xw.App(visible=True,add_book=False)wb = app.books.open('D:\sample.xlsx')sht = wb.sheets[0] #引⽤⼯作表#参数：⼯作表序号sht1 = wb.sheets['物理'] #引⽤⼯作表#参数：⼯作表名称sht=xw.sheets.active #引⽤活动sheetprint(sht)print(sht1)wb.close()app.quit()sht.clear() # 清除sheet的内容和格式a= #返回表格名称sht.delete # 删除sheet----[没有删除啊]单元格操作：import xlwings as xwapp = xw.App(visible=True,add_book=False)wb = app.books.open('D:\sample.xlsx')sht = wb.sheets[0]rng = sht.range('a1') #引⽤单元格---⽅式⼀#<Range [sample.xlsx]Sheet!$A$1>#参数：可以⼤写，可以⼩写rng = sht['b1'] #引⽤单元格---⽅式⼆rng = sht[0,0] #引⽤单元格---⽅式三--第⼀⾏的第⼀列即a1rng=xw.Range('c1') #引⽤活动sheet上的单元格#注意Range⾸字母⼤写print(rng)wb.close()app.quit()rng = sht.range('a1:a5') #引⽤区域---⽅式⼀#<Range [sample.xlsx]Sheet!$A$1:$A$5>rng = sht['a1:b5'] #引⽤区域---⽅式⼆#<Range [sample.xlsx]Sheet!$A$1:$B$5>#rng = sht[:5,0] #引⽤区域---⽅式三---rng = sht.range('a1')rng.value=10 #单元格赋值rng = sht.range('b1')rng.value='abcd' #单元格赋值sht.range('c1').value = [1,2,3,4] #按⾏插⼊#从单元格c1开始，按⾏依次插⼊数据sht.range('a1:d4').value = [10,20,30,40] #指定区域插⼊数据---按⾏sht.range('a2').options(transpose=True).value = [5, 6, 7, 8] #按列插⼊#从单元格a2开始，按列依次插⼊数据#既然默认的是按⾏写⼊，我们就把它倒过来嘛（transpose），单词要打对，如果你打错单词，它不会报错，⽽会按默认的⾏来写⼊sht.range('a6').expand('table').value = [['a','b','c'],['d','e','f'],['g','h','i']] #区域赋值#从单元格a6开始赋值#['a','b','c'] 是⼀⾏；['d','e','f']是⼀⾏L=sht.range('a1:d4').value #读取A1:D4区域的值原表格数据：返回值：返回值是列表，每⼀⾏是⼀个列表返回的数值默认是浮点数rng=sht['d2']a=rng.value #返回指定单元格的值rng = sht.range('a1')rng.add_hyperlink(r'','百度','提⽰：点击即链接到百度') # 指定单元格加⼊超链接a=rng.hyperlink #获得range的超链接#/rng = sht.range('b6')rng.formula='=SUM(B1:B5)' #输⼊公式a=rng.formula #获取公式#=SUM(B1:B5)a=rng.get_address(row_absolute=True, column_absolute=True,include_sheetname=False, external=False) # 获得单元格的绝对地址# $B$6其它操作：a=wb.fullname #返回⼯作簿的绝对路径#D:\sample.xlsxa= #返回⼯作簿的名称#sample.xlsxsht.activate() # 激活sheet为活动⼯作表sht = wb.sheets[0]rng = sht.range('a1')a=rng.address #取得当前range的地址--$A$1rng = sht.range('a1:c1')a=rng.address #取得当前range的地址--$A$1:$C$1a=rng.get_address() #与rng.address相同rng.clear_contents() # 清除range的内容rng.clear() # 清除格式和内容sht = wb.sheets[0]rng = sht.range('a1')rng.color=(255,0,0) # 设置range的背景颜⾊rng = sht.range('b1')rng.color=(0,0,255)a = rng.color # 取得range的背景⾊,以元组形式返回RGB值#(255, 0, 0)rng.color=None # 清除range的背景⾊sht = wb.sheets[0]rng = sht.range('c2:g4')a=rng.column #获得range的第⼀列列标#从A列是1a=rng.count #返回range中单元格的格数a=rng.row # 返回range的第⼀⾏⾏标rng = sht.range('b2:g4')a=st_cell #获得range中右下⾓最后⼀个单元格#<Range [sample.xlsx]Sheet!$G$4>rng = sht.range('b6:c1')a=rng.width # 返回range的总宽度rng = sht.range('b6')a=rng.column_width # 获得列宽sht = wb.sheets[0]rng = sht.range('b2:g4')a=rng.row_height # ⾏的⾼度，所有⾏⼀样⾼返回⾏⾼，不⼀样返回None a=rng.height # 返回range的总⾼度a=rng.shape # 返回range的⾏数和列数---(3, 6)a=rng.sheet # 返回range所在的sheet#<Sheet [sample.xlsx]Sheet>a=rng.rows #返回range的所有⾏for i in a:print(i)#<Range [sample.xlsx]Sheet!$B$2:$G$2>#<Range [sample.xlsx]Sheet!$B$3:$G$3>#<Range [sample.xlsx]Sheet!$B$4:$G$4>a=rng.rows[0] # range的第⼀⾏#<Range [sample.xlsx]Sheet!$B$2:$G$2>a=rng.rows.count # range的总⾏数a=rng.columns # 返回range的所有列for i in a:print(i)#<Range [sample.xlsx]Sheet!$C$2:$C$4>#<Range [sample.xlsx]Sheet!$D$2:$D$4>#<Range [sample.xlsx]Sheet!$E$2:$E$4>#<Range [sample.xlsx]Sheet!$F$2:$F$4>#<Range [sample.xlsx]Sheet!$G$2:$G$4>rng = sht.range('b2:g4')a=rng.columns[0] # 返回range的第⼀列#<Range [sample.xlsx]Sheet!$B$2:$B$4>a=rng.columns.count # 返回range的列数rng.autofit() # 所有range的⼤⼩⾃适应rng.columns.autofit() # 所有列宽度⾃适应rng.rows.autofit() # 所有⾏⾼⾃适应。
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Working with Excel filesin PythonChris Withers with help from John MachinEuroPython 2009, BirminghamThe Tutorial MaterialsThese can be obtained by CD, USB drive or downloaded from here:•/presentations/europython2009excel.zipThe WebsiteThe best place to start when working with Excel files in Python is the website:•© Simplistix Ltd 2009LicenseTHE WORK (AS DEFINED BELOW) IS PROVIDED UNDER THE TERMS OF THIS CREATIVE COMMONS PUBLIC LICENCE ("CCPL" OR "LICENCE"). THE WORK IS PROTECTED BY COPYRIGHT AND/OR OTHER APPLICABLE LAW. ANY USE OF THE WORK OTHER THAN AS AUTHORIZED UNDER THIS LICENCE OR COPYRIGHT LAW IS PROHIBITED. BY EXERCISING ANY RIGHTS TO THE WORK PROVIDED HERE, YOU ACCEPT AND AGREE TO BE BOUND BY THE TERMS OF THIS LICENCE. 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USE OF THIS LICENCE MEANS THAT YOU AND THE LICENSOR EACH ACCEPTS THESE CONDITIONS IN SECTION 7.1, 7.2, 7.3, 7.4 AND EACH ACKNOWLEDGES CREATIVE COMMONS CORPORATION'S VERY LIMITED ROLE AS A FACILITATOR OF THE LICENCE FROM THE LICENSOR TO YOU.IntroductionThis tutorial covers the following libraries:xlrd•/pypi/xlrd•reading data and formatting from .xls files•this tutorial covers version 0.7.1•API documentation can be found at:◦https:///svn/xlrd/trunk/xlrd/doc/xlrd.html xlwt•/pypi/xlwt•writing data and formatting to .xls files•this tutorial covers version 0.7.2•incomplete API documentation can be found at:◦https:///svn/xlwt/trunk/xlwt/doc/xlwt.html •fairly complete examples can be found at◦https:///svn/xlwt/trunk/xlwt/examples/ xlutils•/pypi/xlutils• a collection of utilities using both xlrd and xlwt:◦copying data from a source to a target spreadsheet◦filtering data from a source to a target spreadsheet•this tutorial covers version 1.3.0 and above.•documentation and examples can be found at:◦https:///svn/xlutils/trunk/xlutils/docs/There are still reasons why automating an Excel instance via COM is necessary:•manipulation of graphs•rich text cells•reading formulae in cells•working with macros and names•the more esoteric things found in .xls filesInstallationThere are several methods of installation available. While the following examples are for xlrd , the exact same steps can be used for any of the three libraries.Install from SourceOn Linux:NB: Make sure you use the python you intend to use for your project.On Windows, having used WinZip or similar to unpack xlrd-0.7.1.zip:NB: Make sure you use the python you intend to use for your project.Install using Windows InstallerOn Windows, you can download and run the xlrd-0.7.1.win32.exe installer.Beware that this will only install to Python installations that are in the Windows registry.Install using EasyInstallThis cross-platform method requires that you already have EasyInstall installed. For more information on this, please see:•/DevCenter/EasyInstallInstallation using BuildoutBuildout provides a cross-platform method of meeting the python package dependencies of a project without interfering with the system Python.Having created a directory called mybuildout , download the following file into it:•/*checkout*/zc.buildout/trunk/bootstrap/bootstrap.pyNow, create a file in mybuildout called buildout.cfg containing the following:NB: The versions section is optionalFinally, run the following:These lines:•initialise the buildout environment •run the buildout. This should be done each time dependencies change.Now you can do the following:Buildout lives at /pypi/zc.buildout [buildout]parts = pyversions = versions[versions]xlrd=0.7.1xlwt=0.7.2xlutils=1.3.2[py]recipe = zc.recipe.eggeggs =xlrdxlwtxlutilsinterpreter = pybuildout.cfgReading Excel FilesAll the examples shown below can be found in the xlrd directory of the course material.Opening WorkbooksWorkbooks can be loaded either from a file, an mmap.mmap object or from a string: from mmap import mmap,ACCESS_READfrom xlrd import open_workbookprint open_workbook('simple.xls')with open('simple.xls','rb') as f:print open_workbook(file_contents=mmap(f.fileno(),0,access=ACCESS_READ))aString = open('simple.xls','rb').read()print open_workbook(file_contents=aString)open.pyNavigating a WorkbookHere is a simple example of workbook navigation:from xlrd import open_workbookwb = open_workbook('simple.xls')for s in wb.sheets():print 'Sheet:',for row in range(s.nrows):values = []for col in range(s.ncols):values.append(s.cell(row,col).value)print ','.join(values)printsimple.pyThe next few sections will cover the navigation of workbooks in more detail.The xlrd.Book object returned by open_workbook contains all information to do with the workbook and can be used to retrieve individual sheets within the workbook.The nsheets attribute is an integer containing the number of sheets in the workbook. This attribute, in combination with the sheet_by_index method, is the most common way of retrieving individual sheets.The sheet_names method returns a list of unicodes containing the names of all sheets in the workbook. Individual sheets can be retrieved using these names by way of thesheet_by_name function.The results of the sheets method can be iterated over to retrieve each of the sheets in the workbook.The following example demonstrates these methods and attributes:from xlrd import open_workbookbook = open_workbook('simple.xls')print book.nsheetsfor sheet_index in range(book.nsheets):print book.sheet_by_index(sheet_index)print book.sheet_names()for sheet_name in book.sheet_names():print book.sheet_by_name(sheet_name)for sheet in book.sheets():print sheetintrospect_book.pyxlrd.Book objects have other attributes relating to the content of the workbook that are only rarely useful:•codepage•countries•user_nameIf you think you may need to use these attributes, please see the xlrd documentation.The xlrd.sheet.Sheet objects returned by any of the methods described above contain all the information to do with a worksheet and its contents.The name attribute is a unicode representing the name of the worksheet.The nrows and ncols attributes contain the number of rows and the number of columns, respectively, in the worksheet.The following example shows how these can be used to iterate over and display the contents of one worksheet:xlrd.sheet.Sheet objects have other attributes relating to the content of the worksheet that are only rarely useful:•col_label_ranges •row_label_ranges •visibilityIf you think you may need to use these attributes, please see the xlrd documentation.from xlrd import open_workbook,cellnamebook = open_workbook('odd.xls')sheet = book.sheet_by_index(0)print print sheet.nrowsprint sheet.ncolsfor row_index in range(sheet.nrows):for col_index in range(sheet.ncols):print cellname(row_index,col_index),'-',print sheet.cell(row_index,col_index).valueintrospect_sheet.pyGetting a particular CellAs already seen in previous examples, the cell method of a Sheet object can be used to return the contents of a particular cell.The cell method returns an xlrd.sheet.Cell object. These objects have very few attributes, of which value contains the actual value of the cell and ctype contains the type of the cell.In addition, Sheet objects have two methods for returning these two types of data. The cell_value method returns the value for a particular cell, while the cell_type method returns the type of a particular cell. These methods can be quicker to execute than retrieving the Cell object.Cell types are covered in more detail later. The following example shows the methods, attributes and classes in action:from xlrd import open_workbook,XL_CELL_TEXTbook = open_workbook('odd.xls')sheet = book.sheet_by_index(1)cell = sheet.cell(0,0)print cellprint cell.valueprint cell.ctype==XL_CELL_TEXTfor i in range(sheet.ncols):print sheet.cell_type(1,i),sheet.cell_value(1,i)cell_access.pyIterating over the contents of a SheetWe've already seen how to iterate over the contents of a worksheet and retrieve theresulting individual cells. However, there are methods to retrieve groups of cells more easily. There are a symmetrical set of methods that retrieve groups of cell informationeither by row or by column.The row and col methods return all the Cell objects for a whole row or column, respectively.The row_slice and col_slice methods return a list of Cell objects in a row or column, respectively, bounded by and start index and an optional end index.The row_types and col_types methods return a list of integers representing the cell types in a row or column, respectively, bounded by and start index and an optional end index.The row_values and col_values methods return a list of objects representing the cell values in a row or column, respectively, bounded by a start index and an optional end index.The following examples demonstrates all of the sheet iteration methods:from xlrd import open_workbookbook = open_workbook('odd.xls')sheet0 = book.sheet_by_index(0)sheet1 = book.sheet_by_index(1)print sheet0.row(0)print sheet0.col(0)printprint sheet0.row_slice(0,1)print sheet0.row_slice(0,1,2)print sheet0.row_values(0,1)print sheet0.row_values(0,1,2)print sheet0.row_types(0,1)print sheet0.row_types(0,1,2)printprint sheet1.col_slice(0,1)print sheet0.col_slice(0,1,2)print sheet1.col_values(0,1)print sheet0.col_values(0,1,2)print sheet1.col_types(0,1)print sheet0.col_types(0,1,2)sheet_iteration.pyUtility FunctionsWhen navigating around a workbook, it's often useful to be able to convert between row and column indexes and the Excel cell references that users may be used to seeing. The following functions are provided to help with this:The cellname function turns a row and column index into a relative Excel cell reference.The cellnameabs function turns a row and column index into an absolute Excel cell reference.The colname function turns a column index into an Excel column name.These three functions are demonstrated in the following example:UnicodeAll text attributes and values produced by xlrd will be either unicode objects or, in rare cases, ascii strings.Each piece of text in an Excel file written by Microsoft Excel is encoded into one of the following:•Latin1, if it fits •UTF_16_LE, if it doesn't fit into Latin1•In older files, by an encoding specified by an MS codepage. These are mapped toPython encodings by xlrd and still result in unicode objects.In rare cases, other software has been known to write no codepage or the wrong codepage into Excel files. In this case, the correct encoding may need to be specified toopen_workbook :Types of CellWe have already seen the cell type expressed as an integer. This integer corresponds to a set of constants in xlrd that identify the type of the cell. The full set of possible cell types is listed in the following sections.TextThese are represented by the xlrd.XL_CELL_TEXT constant.Cells of this type will have values that are unicode objects.NumberThese are represented by the xlrd.XL_CELL_NUMBER constant.Cells of this type will have values that are float objects.DateThese are represented by the xlrd.XL_CELL_DATE constant.NB: Dates don't really exist in Excel files, they are merely Numbers with a particular number formatting.xlrd will return xlrd.XL_CELL_DATE as the cell type if the number format string looks like a date.The xldate_as_tuple method is provided for turning the float in a Date cell into a tuple suitable for instantiating various date/time objects. This example shows how to use it:Caveats:•Excel files have two possible date modes, one for files originally created on Windowsand one for files originally created on an Apple machine. This is expressed as the datemode attribute of xlrd.Book objects and must be passed to xldate_as_tuple.•The Excel file format has various problems with dates before 3 Jan 1904 that can cause date ambiguities that can result in xldate_as_tuple raising anXLDateError.•The Excel formula function DATE()can return unexpected dates in certaincircumstances.from datetime import date,datetime,timefrom xlrd import open_workbook,xldate_as_tuplebook = open_workbook('types.xls')sheet = book.sheet_by_index(0)date_value =xldate_as_tuple(sheet.cell(3,2).value,book.datemode)print datetime(*date_value),date(*date_value[:3])datetime_value =xldate_as_tuple(sheet.cell(3,3).value,book.datemode)print datetime(*datetime_value)time_value =xldate_as_tuple(sheet.cell(3,4).value,book.datemode)print time(*time_value[3:])print datetime(*time_value)dates.pyBooleanThese are represented by the xlrd.XL_CELL_BOOLEAN constant.Cells of this type will have values that are bool objects.ErrorThese are represented by the xlrd.XL_CELL_ERROR constant.Cells of this type will have values that are integers representing specific error codes. The error_text_from_code function can be used to turn error codes into error messages:from xlrd import open_workbook,error_text_from_codebook = open_workbook('types.xls')sheet = book.sheet_by_index(0)print error_text_from_code[sheet.cell(5,2).value]print error_text_from_code[sheet.cell(5,3).value]errors.pyFor a simpler way of sensibly displaying all cell types, see xlutils.display.Empty / BlankExcel files only store cells that either have information in them or have formatting applied to them. However, xlrd presents sheets as rectangular grids of cells.Cells where no information is present in the Excel file are represented by thexlrd.XL_CELL_EMPTY constant. In addition, there is only one “empty cell”, whose value is an empty string, used by xlrd, so empty cells may be checked using a Python identity check.Cells where only formatting information is present in the Excel file are represented by the xlrd.XL_CELL_BLANK constant and their value will always be an empty string.from xlrd import open_workbook,empty_cellprint empty_cell.valuebook = open_workbook('types.xls')sheet = book.sheet_by_index(0)empty = sheet.cell(6,2)blank = sheet.cell(7,2)print empty is blank, empty is empty_cell, blank is empty_cell book = open_workbook('types.xls',formatting_info=True)sheet = book.sheet_by_index(0)empty = sheet.cell(6,2)blank = sheet.cell(7,2)print empty.ctype,repr(empty.value)print blank.ctype,repr(blank.value)emptyblank.pyThe following example brings all of the above cell types together and shows examples of their use:NamesThese are an infrequently used but powerful way of abstracting commonly usedinformation found within Excel files.They have many uses, and xlrd can extract information from many of them. A notable exception are names that refer to sheet and VBA macros, which are extracted but should be ignored.Names are created in Excel by navigating to Insert > Name > Define . If you plan to use xlrd to extract information from Names, familiarity with the definition and use of names in your chosen spreadsheet application is a good idea.from xlrd import open_workbookdef cell_contents(sheet,row_x):result = []for col_x in range(2,sheet.ncols):cell = sheet.cell(row_x,col_x)result.append((cell.ctype,cell,cell.value))return resultsheet = open_workbook('types.xls').sheet_by_index(0)print 'XL_CELL_TEXT',cell_contents(sheet,1)print 'XL_CELL_NUMBER',cell_contents(sheet,2)print 'XL_CELL_DATE',cell_contents(sheet,3)print 'XL_CELL_BOOLEAN',cell_contents(sheet,4)print 'XL_CELL_ERROR',cell_contents(sheet,5)print 'XL_CELL_BLANK',cell_contents(sheet,6)print 'XL_CELL_EMPTY',cell_contents(sheet,7)printsheet = open_workbook('types.xls',formatting_info=True).sheet_by_index(0)print 'XL_CELL_TEXT',cell_contents(sheet,1)print 'XL_CELL_NUMBER',cell_contents(sheet,2)print 'XL_CELL_DATE',cell_contents(sheet,3)print 'XL_CELL_BOOLEAN',cell_contents(sheet,4)print 'XL_CELL_ERROR',cell_contents(sheet,5)print 'XL_CELL_BLANK',cell_contents(sheet,6)print 'XL_CELL_EMPTY',cell_contents(sheet,7)cell_types.pyTypesA Name can refer to:• A constant◦CurrentInterestRate = 0.015◦NameOfPHB = “Attila T. Hun”•An absolute (i.e. not relative) cell reference◦CurrentInterestRate = Sheet1!$B$4•Absolute reference to a 1D, 2D, or 3D block of cells◦MonthlySalesByRegion = Sheet2:Sheet5!$A$2:$M$100• A list of absolute references◦Print_Titles = [row_header_ref, col_header_ref])Constants can be extracted.The coordinates of an absolute reference can be extracted so that you can then extract the corresponding data from the relevant sheet(s).A relative reference is useful only if you have external knowledge of what cells can be used as the origin. Many formulas found in Excel files include function calls and multiple references and are not useful, and can be too hard to evaluate.A full calculation engine is not included in xlrd.ScopeThe scope of a Name can be global, or it may be specific to a particular sheet. A Name's identifier may be re-used in different scopes. When there are multiple Names with the same identifier, the most appropriate one is used based on scope. A good example of this is the built-in name Print_Area; each worksheet may have one of these.Examples:name=rate, scope=Sheet1, formula=0.015name=rate, scope=Sheet2, formula=0.023name=rate, scope=global, formula=0.040A cell formula (1+rate)^20 is equivalent to 1.015^20 if it appears in Sheet1 but equivalent to 1.023^20 if it appears in Sheet2, and 1.040^20 if it appears in any other sheet.UsageCommon reasons for using names include:•Assigning textual names to values that may occur in many places within a workbook ◦eg: RATE = 0.015•Assigning textual names to complex formulae that may be easily mis-copied ◦eg: SALES_RESULTS = $A$10:$M$999Here's an example real-world use case: reporting to head office. A company's head office makes up a template workbook. Each department gets a copy to fill in. The various rangesof data to be provided all have defined names. When the files come back, a script is used to validate that the department hasn't trashed the workbook and the names are used to extract the data for further processing. Using names decouples any artistic repositioning of the ranges, by either head office template-designing user or by departmental users who are filling in the template, from the script which only has to know what the names of the ranges are.In the examples directory of the xlrd distribution you will find namesdemo.xls which has examples of most of the non-macro varieties of defined names. There is also xlrdnamesAPIdemo.py which shows how to use the name lookup dictionaries, and how to extract constants and references and the data that references point to.FormattingWe've already seen that open_workbook has a parameter to load formatting information from Excel files. When this is done, all the formatting information is available, but the details of how it is presented are beyond the scope of this tutorial.If you wish to copy existing formatted data to a new Excel file, see xlutils.copy and xlutils.filter.If you do wish to inspect formatting information, you'll need to consult the following attributes of the following classes:xlrd.Bookcolour_map font_list format_list format_map palette_record style_name_map xf_listxlrd.sheet.Sheetcell_xf_indexrowinfo_mapcolinfo_mapcomputed_column_widthdefault_additional_space_above default_additional_space_below default_row_height default_row_height_mismatch default_row_hidden defcolwidthgcwmerged_cellsstandard_widthxlrd.sheet.Cellxf_indexOther ClassesIn addition, the following classes are solely used to represent formatting information:xlrd.sheet.Rowinfo xlrd.sheet.Colinfo xlrd.formatting.Font xlrd.formatting.Format xlrd.formatting.XFxlrd.formatting.XFAlignment xlrd.formatting.XFBackground xlrd.formatting.XFBorder。