There are many ways to read and write excel in python, and different modules have slightly different ways of reading and writing. Here I will mainly introduce a few commonly used methods.
- Use xlrd and xlwt to read and write excel;
- Use openpyxl to read and write excel;
- Use pandas to read and write excel;
reference:
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https://www.python-excel.org/
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html#pandas.read_excel
https: //www.jianshu.com/p/19219542bf23
2 | 0 data preparation
In order to facilitate the demonstration, I created a new data.xls and data.xlsx file here, the content of the first worksheet sheet1 area "A1:E5" is as follows, used to test the code for reading and writing excel:
3 | 0 xlrd and xlwt
xlrd is a library for reading data and formatting information from Excel files in .xls format xlwt is a library for
writing data and formatting information to older Excel files (for example: .xls).
3 | 1 example
pip install xlrd
pip install xlwt
We start to read the contents of the file
import xlrd
import os
file_path = os.path.dirname(os.path.abspath(__file__))
base_path = os.path.join(file_path, 'data.xlsx')
book = xlrd.open_workbook(base_path)
sheet1 = book.sheets()[0]
nrows = sheet1.nrows
print('表格总行数', nrows)
ncols = sheet1.ncols
print('表格总列数', ncols)
row3_values = sheet1.row_values(2)
print('第3行值', row3_values)
col3_values = sheet1.col_values(2)
print('第3列值', col3_values)
cell_3_3 = sheet1.cell(2, 2).value
print('第3行第3列的单元格的值：', cell_3_3)
Next, let's write. There are too many operations that can be performed. I only list the commonly used operations here.
import xlwt
import datetime
# 创建一个workbook 设置编码
workbook = xlwt.Workbook(encoding='utf-8')
# 创建一个worksheet
worksheet = workbook.add_sheet('Worksheet')
# 写入excel参数对应 行, 列, 值
worksheet.write(0, 0, label='测试')
# 设置单元格宽度
worksheet.col(0).width = 3333
# 设置单元格高度
tall_style = xlwt.easyxf('font:height 520;')
worksheet.row(0).set_style(tall_style)
# 设置对齐方式
alignment = xlwt.Alignment() # Create Alignment
# May be: HORZ_GENERAL, HORZ_LEFT, HORZ_CENTER, HORZ_RIGHT, HORZ_FILLED, HORZ_JUSTIFIED, HORZ_CENTER_ACROSS_SEL, HORZ_DISTRIBUTED
alignment.horz = xlwt.Alignment.HORZ_CENTER
# May be: VERT_TOP, VERT_CENTER, VERT_BOTTOM, VERT_JUSTIFIED, VERT_DISTRIBUTED
alignment.vert = xlwt.Alignment.VERT_CENTER
style = xlwt.XFStyle() # Create Style
style.alignment = alignment # Add Alignment to Style
worksheet.write(2, 0, '居中', style)
# 写入带颜色背景的数据
pattern = xlwt.Pattern() # Create the Pattern
# May be: NO_PATTERN, SOLID_PATTERN, or 0x00 through 0x12
pattern.pattern = xlwt.Pattern.SOLID_PATTERN
pattern.pattern_fore_colour = 5 # May be: 8 through 63. 0 = Black, 1 = White, 2 = Red, 3 = Green, 4 = Blue, 5 = Yellow, 6 = Magenta, 7 = Cyan, 16 = Maroon, 17 = Dark Green, 18 = Dark Blue, 19 = Dark Yellow , almost brown), 20 = Dark Magenta, 21 = Teal, 22 = Light Gray, 23 = Dark Gray, the list goes on...
style = xlwt.XFStyle() # Create the Pattern
style.pattern = pattern # Add Pattern to Style
worksheet.write(0, 1, '颜色', style)
# 写入日期
style = xlwt.XFStyle()
# Other options: D-MMM-YY, D-MMM, MMM-YY, h:mm, h:mm:ss, h:mm, h:mm:ss, M/D/YY h:mm, mm:ss, [h]:mm:ss, mm:ss.0
style.num_format_str = 'M/D/YY'
worksheet.write(0, 2, datetime.datetime.now(), style)
# 写入公式
worksheet.write(0, 3, 5) # Outputs 5
worksheet.write(0, 4, 2) # Outputs 2
# Should output "10" (A1[5] * A2[2])
worksheet.write(1, 3, xlwt.Formula('D1*E1'))
# Should output "7" (A1[5] + A2[2])
worksheet.write(1, 4, xlwt.Formula('SUM(D1,E1)'))
# 写入超链接
worksheet.write(1, 0, xlwt.Formula('HYPERLINK("http://www.baidu.com";"百度一下")'))
# 保存
workbook.save('Excel_test.xls')
It should be noted that it is best to execute through the command line in the current path, otherwise the file cannot be generated.
4|0openpyxl
openpyxl is a Python library for reading/writing Excel 2010 xlsx/xlsm/xltx/xltm files.
Installation package
pip install openpyx
After installation, you can start reading data
import openpyxl
import os
file_path = os.path.dirname(os.path.abspath(__file__))
base_path = os.path.join(file_path, 'data.xlsx')
workbook = openpyxl.load_workbook(base_path)
worksheet = workbook.get_sheet_by_name('Sheet1')
row3=[item.value for item in list(worksheet.rows)[2]]
print('第3行值',row3)
col3=[item.value for item in list(worksheet.columns)[2]]
print('第3行值',col3)
cell_2_3=worksheet.cell(row=2,column=3).value
print('第2行第3列值',cell_2_3)
max_row=worksheet.max_row
print('最大行',max_row)
Now let's start writing data
import zipfile
# 创建文件句柄
file = zipfile.ZipFile("测试.zip", 'r')
# 提取压缩文件中的内容，注意密码必须是bytes格式，path表示提取到哪
file.extractall(path='.', pwd='123'.encode('utf-8')) 
5 | 0 pandas
pandas supports xls, xlsx, xlsm, xlsb, odf, ods and odt file extensions to read from the local file system or URL. Support the option of reading a single worksheet or a list of worksheets.
The first is still the installation package
pip install pandas
语法：
pd.read_excel(io, sheet_name=0, header=0, names=None, index_col=None, usecols=None, squeeze=False,dtype=None, engine=None, converters=None, true_values=None, false_values=None, skiprows=None, nrows=None, na_values=None, parse_dates=False, date_parser=None, thousands=None, comment=None, skipfooter=0, convert_float=True, **kwds)
- io, the storage path of Excel
- sheet_name, the name of the worksheet to be read
- header, which row to use as column name
- names, customize the final column name
- index_col, the column used as an index
- usecols, which columns need to be read
- squeeze, when the data contains only one column
- converters, mandatory column data type
- skiprows, skip specific rows
- nrows, the number of rows to be read
- skipfooter, skip the last n lines
import pandas as pd
import os
file_path = os.path.dirname(os.path.abspath(__file__))
base_path = os.path.join(file_path, 'data.xlsx')
df = pd.read_excel(base_path)
print(df)
写入数据
语法：
DataFrame.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)
参数说明：
- excel_writer: file path or existing ExcelWriter
- sheet_name: The name of the worksheet that will contain the data file
- na_rep: missing data representation
- float_format: Format a string of floating point numbers. For example, float_format = "%. 2f" has a format of 0.1234 to 0.12.
- columns: columns
- header: write out the column name. If a list of strings is given, it is assumed to be an alias for the column name.
- index: write row name (index)
- index_label: If required, the column label of the index column. If not specified, and the header and index are true, the index name is used. If the DataFrame uses multiple indexes, a sequence should be given.
- startrow: The cell row in the upper left corner dumps the data frame.
- startcol: Dump the data frame in the upper left cell column.
- engine: Write the engine "openpyxl" or "xlsxwriter" to be used. You can also set it through the options io.excel.xlsx.writer, io.excel.xls.writer and io.excel.xlsm.writer.
- merge_cells: Write multiple index and hierarchy rows into merged cells.
- encoding: Encode the generated excel file. Only necessary for xlwt, other writers support unicode.
- inf_rep: Represents infinity.
- verbose: Display more information in the error log.
- freeze_panes: Specify the bottom row and the right column to be frozen
from pandas import DataFrame
data = {'name': ['张三', '李四', '王五'],'age': [11, 12, 13],'sex': ['男', '女', '男']}
df = DataFrame(data)
df.to_excel('file.xlsx')
