Question

我有3个不同的数据集，我想在同一个excel文件下的3个不同的表格中存储。我尝试如下。有没有紧凑的方法来降低编程复杂性？

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Answer 1

您可以使用pandas（python数据分析库）完成此任务。

通过pip install pandas安装。

import pandas as pd
datasets = [dataset, column_sum, row_sum]
sheet_names = ['img_reshape', 'column_sum', 'row_sum']
excel_filename = 'abcd.xlsx'
with pd.ExcelWriter(excel_filename) as writer:
    for data, sheet in zip(datasets, sheet_names):
        df = pd.DataFrame(data)
        df.to_excel(writer, sheet_name=sheet, header=None)

Answer 2

有一种更简单的方法。 xlsxwriter文档中提供了一个示例（链接here）我在下面发布了一个相当简单的例子。我还添加了三个示例数据帧，以便任何人都可以复制此示例。此外，还有一些可选的参数可以与您感兴趣的dataframe.to_excel一起使用，这些参数在Pandas文档中有概述。（链接here）。

import pandas as pd

df_1 = pd.DataFrame({'Data_1': [10, 20, 30, ]})
df_2 = pd.DataFrame({'Data_2': [20, 30, 40]})
df_3 = pd.DataFrame({'Data_3': [30, 40, 50]})

# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('abcd.xlsx', engine='xlsxwriter')

# Convert the dataframe to an XlsxWriter Excel object.
df_1.to_excel(writer, sheet_name='img_reshape')
df_2.to_excel(writer, sheet_name='column_sum')
df_3.to_excel(writer, sheet_name='row_sum')


writer.save()

Answer 3

我也推荐Pandas，但如果你只想用XlsxWriter做，那么你可以这样做：

import xlsxwriter

# Some sample data.
dataset = [[11, 12, 13, 14],
           [21, 22, 23, 24],
           [31, 32, 33, 34]]

column_sum = dataset
row_sum = dataset

xbook = xlsxwriter.Workbook('abcd.xlsx')
xsheet1 = xbook.add_worksheet('img_reshape')
xsheet2 = xbook.add_worksheet('column_sum')
xsheet3 = xbook.add_worksheet('row_sum')

mappings = [(dataset, xsheet1),
            (column_sum, xsheet2),
            (row_sum, xsheet3)]

for dataset, worksheet in mappings:
    for row_num, row_data in enumerate(dataset):
        for col_num, cell_data in enumerate(row_data):
            worksheet.write(row_num, col_num, cell_data)

xbook.close()

或者对于内循环，你可以这样做：

# Write the data.
for dataset, worksheet in mappings:
    for row_num, row_data in enumerate(dataset):
        worksheet.write_row(row_num, 0, row_data)

将3个不同的数据集保存到同一个excel文件下的3个不同的表中

3 个答案: