替换Excel偶数行为上下平均值

169个直接转换上下两行转换实现代码
import openpyxl# 打开Excel文件
input_file = '(10s)result03-1.xlsx'
output_file = 'new-34.xlsx'
wb = openpyxl.load_workbook(input_file)
output_wb = openpyxl.Workbook()# 处理每个工作表
for sheet_name in wb.sheetnames:sheet = wb[sheet_name]# 新建一个工作表,用于存储处理后的数据output_sheet = output_wb.create_sheet(title=sheet_name)# 将前两行复制到新表格for row in range(1, 3):row_values = []for col in range(1, sheet.max_column+1):row_values.append(sheet.cell(row=row, column=col).value)output_sheet.append(row_values)# 处理数据for row in range(3, sheet.max_row+1):if row % 2 == 0:# 计算上下两行的平均值avg_values = []for col in range(1, sheet.max_column+1):value1 = sheet.cell(row=row-1, column=col).valuevalue2 = sheet.cell(row=row+1, column=col).valueif value1 is None or value2 is None:avg_values.append(None)else:avg_value = (value1 + value2) / 2avg_values.append(avg_value)# 将平均值写入新行output_sheet.append(avg_values)else:# 直接将原数据写入新行row_values = []for col in range(1, sheet.max_column+1):row_values.append(sheet.cell(row=row, column=col).value)output_sheet.append(row_values)# 判断总数行是否为偶数行if (sheet.max_row - 1) % 2 == 0:# 复制最后一行-1到总数行-1的位置last_row_values = []for col in range(1, sheet.max_column+1):last_row_values.append(sheet.cell(row=sheet.max_row-1, column=col).value)output_sheet.insert_rows(sheet.max_row, amount=1)for col in range(1, sheet.max_column+1):output_sheet.cell(row=sheet.max_row-1, column=col, value=last_row_values[col-1])# 保存新Excel文件
output_wb.save(output_file)# 输出导入的Excel文件的内容到控制台
print('导入的Excel文件内容:')
for sheet_name in wb.sheetnames:sheet = wb[sheet_name]print(f"Sheet Name: {sheet_name}")for row in sheet.iter_rows():row_values = []for cell in row:row_values.append(cell.value)print(row_values)print()# 输出导出的Excel文件的内容到控制台
print('导出的Excel文件内容:')
for sheet_name in output_wb.sheetnames:sheet = output_wb[sheet_name]print(f"Sheet Name: {sheet_name}")for row in sheet.iter_rows():row_values = []for cell in row:row_values.append(cell.value)print(row_values)print()

注:

如果原Excel表格中的行数为奇数,那么输出的新旧Excel文件的最后一行都会是None。而如果原Excel表格中的行数是偶数行,那么新Excel文件的最后一行就可以显示出来(是我们把最后一行给复制来的)。

转换前后数据(169-169)[结果]
xyzxyz
0.000.004879.00004879
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262.18806.924811.77214.79654.454828.515
691.60502.484848.21691.6502.484848.21
839.760.004762.53681.777.1454779.275
671.94-488.194710.34671.94-488.194710.34
263.15-809.894829.50204.37-649.1254770.41
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1916.97-1916.974695.591670.745-1758.324347.88
1966.74-1135.503933.491966.74-1135.53933.49
1966.14-526.833525.591955.87-567.753651.165
1945.000.003368.84194503368.84
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617.751069.972139.95617.751069.972139.95
268.011000.221793.54308.8751038.2351941.63
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303.95935.481514.64329.555961.1351599.345
558.80967.871720.95558.8967.871720.95
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1973.79419.543107.271973.79419.543107.27
1887.170.002905.991913.8612.743012.92
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1960.85-873.033305.201839.935-860.343197.01
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1869.91-2076.754303.221655.72-1949.84025.2
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1764.52-3056.244683.201616.65-2873.384442.41
2016.21-2402.824162.492016.21-2402.824162.49
1980.53-1661.863430.941917.835-1726.653475.265
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1908.07-694.482694.601855.635-692.0252668.64
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1277.481071.932213.021288.84984.4052183.07
782.19932.181614.84782.19932.181614.84
541.63938.141437.54567.185949.8951490.655
352.18967.611366.47352.18967.611366.47
169.09958.941292.19176.09924.9351268.635
0.00882.261170.800882.261170.8
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-1571.90907.542408.68-1571.9907.542408.68
-1941.43706.622741.72-1941.43706.622741.72

87个点转换成169个点实现代码.

逻辑:

在排除前两行的87个数据点后,我们需要在每隔一行添加一个空白行进行计算。这些空白行的值应该是其上下两行数据点的平均值。

import openpyxl# 打开 Excel 文件
workbook = openpyxl.load_workbook('10s.xlsx')# 新建一个工作表,用于存储处理后的数据
output_wb = openpyxl.Workbook()# 处理每个工作表
for sheet_name in workbook.sheetnames:sheet = workbook[sheet_name]# 新建一个工作表,用于存储处理后的数据output_sheet = output_wb.create_sheet(title=sheet_name)# 添加空白行for row in range(sheet.max_row, 0, -1):if row > 2:sheet.insert_rows(row + 1)# 处理数据for row in range(1, sheet.max_row + 1):if row > 2:if row % 2 == 0:# 计算上下两行的平均值avg_values = []for col in range(1, sheet.max_column + 1):value1 = sheet.cell(row=row - 1, column=col).valuevalue2 = sheet.cell(row=row + 1, column=col).valueif value1 is None:value1 = 0if value2 is None:value2 = 0avg_value = (value1 + value2) / 2avg_values.append(avg_value)# 将平均值写入新行output_sheet.append(avg_values)else:# 直接将原数据写入新行row_values = []for col in range(1, sheet.max_column + 1):row_values.append(sheet.cell(row=row, column=col).value)output_sheet.append(row_values)else:# 如果是前两行则直接将原数据写入新行row_values = []for col in range(1, sheet.max_column + 1):row_values.append(sheet.cell(row=row, column=col).value)output_sheet.append(row_values)# 处理完前两行后,将计数器重置为 0row = 0# 保存新Excel文件
output_wb.save('10s-1-2-new3.xlsx')

转换前后 (87个点-->169个点)

xyzxyz
0.000.004897.00004897
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344.09-250.004861.43-41.05-1254866.41
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-270.75959.4551787.475
-541.5937.911875.81
-1277.071049.9552950.55
-2012.6411624025.29
-2063.371051.633794.4
-2114.1941.263563.51
-1484.53945.3952765.515
-854.96949.531967.52
-583.16953.91759.53
-311.36958.271551.54
-105.695954.711512.125
99.97951.151472.71
322.575947.721575.865
545.18944.291679.02
1080.251058.9452376.795
1615.321173.63074.57
1777.51792.953064.085
1939.7412.33053.6
1895.2159.462983.57
1850.73-393.382913.54
1833.265-856.323184.85
1815.8-1319.263456.16
1656.505-1956.264033.585
1497.21-2593.254611.01
910.63-2838.184692.36
324.05-3083.14773.71
-318.73-3021.174782.515
-961.51-2959.234791.32
-1412.98-2514.964540.98
-1864.45-2070.684290.64
-1958.68-1492.353875.495
-2052.9-914.013460.35
-2004.08-457.0053235.59
-1955.2503010.83
-2064.202947.35
-2173.1502883.87
-2092.36-366.0752862.31
-2011.56-732.152840.75
-1889.78-1107.842951.76
-1768-1483.533062.77
-1680.96-2122.133646.57
-1593.91-2760.734230.37
-1102.16-3111.274447.6
-610.41-3461.84664.83
0.785-3466.254670.82
611.98-3470.694676.81
1190.51-3267.384685.995
1769.04-3064.064695.18
1861.645-2351.944040.3
1954.25-1639.813385.42
1901.185-1156.242997.68
1848.12-672.662609.94
1880.045-336.332573.605
1911.9702537.27
1839.895321.7152516.9
1767.82643.432496.53
1512.275848.9752336.805
1256.731054.522177.08
894.065987.471793.735
531.4920.421410.39
352.645953.3151369.66
173.89986.211328.93
8.62937.3151263.04
-156.65888.421197.15
-318.9860.91237.085
-481.15833.381277.02
-658.025766.9751361.675
-834.9700.571446.33
-1393.54705.5552101.61
-1952.18710.542756.89

 

 

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