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Summary of several methods of accessing xls/xlsx files in Python
Summary of several methods of accessing xls/xlsx files in Python
这篇文章主要介绍了关于Python学习_几种存取xls/xlsx文件的方法总结，有着一定的参考价值，现在分享给大家，有需要的朋友可以参考一下
想在深度学习程序运行时动态存下来一些参数。
存成Excel文件查看方便，就查了几种方法，做个测试。因为我平常也不怎么用 Excel，简单的存取数据就够了。
xlwt/xlrd库 存Excel文件：（如果存储数据中有字符，那么写法还有点小小的变化）
import xlwt workbook = xlwt.Workbook(encoding='utf-8') booksheet = workbook.add_sheet('Sheet 1', cell_overwrite_ok=True) #存第一行cell(1,1)和cell(1,2) booksheet.write(0,0,34) booksheet.write(0,1,38) #存第二行cell(2,1)和cell(2,2) booksheet.write(1,0,36) booksheet.write(1,1,39) #存一行数据 rowdata = [43,56] for i in range(len(rowdata)): booksheet.write(2,i,rowdata[i]) workbook.save('test_xlwt.xls')
读Excel文件：（同样是对于数值类型数据）
import xlrd workbook = xlrd.open_workbook('D:\\Py_exercise\\test_xlwt.xls') print(workbook.sheet_names()) #查看所有sheet booksheet = workbook.sheet_by_index(0) #用索引取第一个sheet booksheet = workbook.sheet_by_name('Sheet 1') #或用名称取sheet #读单元格数据 cell_11 = booksheet.cell_value(0,0) cell_21 = booksheet.cell_value(1,0) #读一行数据 row_3 = booksheet.row_values(2) print(cell_11, cell_21, row_3) >>>34.0 36.0 [43.0, 56.0]
openpyxl 库 存Excel文件：
from openpyxl import Workbook
workbook = Workbook()
booksheet = workbook.active #获取当前活跃的sheet,默认是第一个sheet
#存第一行单元格cell(1,1)
booksheet.cell(1,1).value = 6 #这个方法索引从1开始
booksheet.cell("B1").value = 7
#存一行数据
booksheet.append([11,87])
workbook.save("test_openpyxl.xlsx")
读Excel文件：
from openpyxl import load_workbook workbook = load_workbook('D:\\Py_exercise\\test_openpyxl.xlsx') #booksheet = workbook.active #获取当前活跃的sheet,默认是第一个sheet sheets = workbook.get_sheet_names() #从名称获取sheet booksheet = workbook.get_sheet_by_name(sheets[0]) rows = booksheet.rows columns = booksheet.columns #迭代所有的行 for row in rows: line = [col.value for col in row] #通过坐标读取值 cell_11 = booksheet.cell('A1').value cell_11 = booksheet.cell(row=1, column=1).value
原理上其实都一样，就写法上有些差别。
其实如果对存储格式没有要求的话，我觉得存成 csv文件 也挺好的：
import pandas as pd
csv_mat = np.empty((0,2),float)
csv_mat = np.append(csv_mat, [[43,55]], axis=0)
csv_mat = np.append(csv_mat, [[65,67]], axis=0)
csv_pd = pd.DataFrame(csv_mat)
csv_pd.to_csv("test_pd.csv", sep=',', header=False, index=False)因为它读起来非常简单：
import pandas as pd filename = "D:\\Py_exercise\\test_pd.csv" csv_data = pd.read_csv(filename, header=None) csv_data = np.array(csv_data, dtype=float)
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