将Excel转换为NumPy

NumPy简介

NumPy（Numerical Python）是Python的开源数值计算扩展。该工具可用于存储和处理大型矩阵，比Python的嵌套列表结构效率更高（也可用于表示矩阵）。它支持大量的多维数组和矩阵操作，并为数组操作提供了大量的数学函数库。

NumPy的主要功能：

1. Ndarray，一个多维数组对象，是一个快速、灵活、节省空间的数据结构。
2. 线性代数操作，包括矩阵乘法、转置、求逆等。
3. 快速傅里叶变换，在数组上执行快速傅里叶变换。
4. 浮点数组的快速操作。
5. 将C语言代码集成到Python中，使其运行速度更快。

使用Aspose.Cells for Python via .NET API，您可以将Excel、TSV、CSV、Json等多种格式转换为Numpy ndarray。

将Excel工作簿转换为NumPy ndarray的方法

以下是一个示例代码片段，演示使用Aspose.Cells for Python via .NET将excel数据导出为NumPy数组的方法：

1. 加载样本文件。 1.遍历excel数据并使用Aspose.Cells for Python via .NET将数据导出为NumPy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# workbook to ndarray
excel_ndarray = np.array([], dtype= object)

sheet_count = book.worksheets.capacity - 1
excel_list = []
for sheet_index in range(0, sheet_count):
    sheet_list =[]
    sheet = book.worksheets.get(sheet_index)
    cells = sheet.cells
    rows = cells.rows
    max_column_index  = cells.max_column + 1

    row_count = rows.count
    index = -1
    for row_index in range(0, row_count):
        row = rows.get_row_by_index(row_index)    
        if row_index != row.index:        
            for blank_row_index in range(index+1, row.index):
                blank_row  =[]
                for blank_column_index in range(0,max_column_index):                
                    blank_row.append("")
                sheet_list.append(blank_row)
        
        data_row  =[]            
        for column_index in range(0,max_column_index):
            curr_cell = cells.check_cell(row.index, column_index)
            if curr_cell:
                data_row.append(curr_cell.value)
            else:
                data_row.append("")
        sheet_list.append(data_row)
        index = row.index

    excel_list.append(sheet_list)

excel_ndarray = np.asarray(excel_list)
print(excel_ndarray)

输出结果：

[[['City' 'Region' 'Store']    
  ['Chicago' 'Central' '3055'] 
  ['New York' 'East' '3036']   
  ['Detroit' 'Central' '3074']]

 [['City2' 'Region2' 'Store3']
  ['Seattle' 'West' '3000']
  ['philadelph' 'East' '3082']
  ['Detroit' 'Central' '3074']]

 [['City3' 'Region3' 'Store3']
  ['Seattle' 'West' '3166']
  ['New York' 'East' '3090']
  ['Chicago' 'Central' '3055']]]

将工作表转换为NumPy ndarray的方法

以下是一个示例代码片段，演示使用Aspose.Cells for Python via .NET将工作表数据导出为NumPy ndarray的方法：

1. 加载样本文件。
2. 获取第一个工作表。 1.使用Aspose.Cells for Python Excel库将工作表数据转换为Numpy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# Get the first worksheet
sheet1 = book.worksheets.get(0)
cells = sheet1.cells
rows = cells.rows
max_column_index  = sheet1.cells.max_column + 1

# worksheet to ndarray
worksheet_list =[]
row_count = rows.count
index = -1
for row_index in range(0, row_count):
    row = rows.get_row_by_index(row_index)    
    if row_index != row.index:        
        for blank_row_index in range(index+1, row.index):
            blank_row  =[]
            for blank_column_index in range(0,max_column_index):                
                blank_row.append("")
            worksheet_list.append(blank_row)
    
    data_row  =[]            
    for column_index in range(0,max_column_index):
        curr_cell = cells.check_cell(row.index, column_index)
        if curr_cell:
            data_row.append(curr_cell.value)
        else:
            data_row.append("")
    worksheet_list.append(data_row)
    index = row.index

worksheet_ndarray = np.asarray(worksheet_list)
print(worksheet_ndarray)

输出结果：

[['City' 'Region' 'Store']    
 ['Chicago' 'Central' '3055'] 
 ['New York' 'East' '3036']   
 ['Detroit' 'Central' '3074']]

如何将Excel的范围转换为NumPy ndarray

下面是一个示例代码片段，演示如何使用Aspose.Cells for Python via .NET将范围数据导出到NumPy ndarray中：

1. 加载样本文件。
2. 获取第一个工作表。
3. 创建范围。
4. 使用Aspose.Cells for Python Excel库将范围数据转换为NumPy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# Get the first worksheet
sheet1 = book.worksheets.get(0)

# range to ndarray
cells = sheet1.cells
range_obj = cells.create_range("B1", "C3")
range_list =[]
for row_index in range(range_obj.first_row , range_obj.first_row + range_obj.row_count ):
    row  =[]            
    for column_index in range(range_obj.first_column, range_obj.first_column + range_obj.column_count):
        curr_cell = cells.check_cell(row_index, column_index)
        if curr_cell:
            row.append(curr_cell.value)
        else:
            row.append("")
    range_list.append(row)

range_ndarray = np.asarray(range_list)
print(range_ndarray)

输出结果：

[['Region' 'Store']
 ['Central' '3055']
 ['East' '3036']]

如何将Excel的ListObject转换为NumPy ndarray

下面是一个示例代码片段，演示如何使用Aspose.Cells for Python via .NET将ListObject数据导出为NumPy ndarray：

1. 加载样本文件。
2. 获取第一个工作表。
3. 创建ListObject对象。
4. 使用Aspose.Cells for Python Excel库将ListObject数据转换为NumPy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# Get the first worksheet
sheet1 = book.worksheets.get(0)
cells = sheet1.cells

# listobject to ndarray
table_index = sheet1.list_objects.add("A1", "C4", True)
table = sheet1.list_objects[table_index]

table_list =[]
for row_index in range(table.start_row , table.end_row + 1):
    row  =[]            
    for column_index in range(table.start_column, table.end_column + 1):
        curr_cell = cells.check_cell(row_index, column_index)
        if curr_cell:
            row.append(curr_cell.value)
        else:
            row.append("")
    table_list.append(row)

table_ndarray = np.asarray(table_list)
print(table_ndarray)

输出结果：

[['City' 'Region' 'Store']
 ['Chicago' 'Central' '3055']
 ['New York' 'East' '3036']
 ['Detroit' 'Central' '3074']]

如何将Excel的行转换为NumPy ndarray

下面是一个示例代码片段，演示如何使用Aspose.Cells for Python via .NET将行数据导出为NumPy ndarray：

1. 加载样本文件。
2. 获取第一个工作表。
3. 通过行索引获取行对象。
4. 使用Aspose.Cells for Python Excel库将行数据转换为NumPy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# Get the first worksheet
sheet1 = book.worksheets.get(0)

cells = sheet1.cells
max_column_index  = cells.max_column + 1

# row to ndarray
row_index = cells.max_data_row
row_list = []
for column_index in range(0,max_column_index):
    curr_cell = cells.check_cell(row_index, column_index)
    if curr_cell:
        row_list.append(curr_cell.value)
    else:
        row_list.append("")

row_ndarray = np.asarray(row_list)
print(row_ndarray)

输出结果：

['Detroit' 'Central' '3074']

如何将Excel的列转换为NumPy ndarray

以下是一个示例代码片段，演示如何使用Aspose.Cells for Python将列数据导出为NumPy ndarray via .NET：

1. 加载样本文件。
2. 获取第一个工作表。
3. 通过列索引获取列对象。
4. 使用Aspose.Cells for Python Excel库将列数据转换为NumPy ndarray。

import numpy as np
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range

# Open the Excel workbook
book = Workbook("sample_data.xlsx")

# Get the first worksheet
sheet1 = book.worksheets.get(0)

cells = sheet1.cells
max_row_index  = cells.max_row + 1

# column to ndarray
column_index = cells.max_data_column
column_list = []
for row_index in range(0,max_row_index):
    curr_cell = sheet1.cells.check_cell(row_index, column_index)
    if curr_cell:
        column_list.append(curr_cell.value)
    else:
        column_list.append("")

column_ndarray = np.asarray(column_list)
print(column_ndarray)

输出结果：

['Store' '3055' '3036' '3074']