在 Aspose.Cells for Python via .NET 中管理数据透视表的值字段

Adding a Field to the Data Region

Adding a base field to the data (value) region is the first step in shaping how a pivot table aggregates your source data. Aspose.Cells exposes PivotTable.add_field_to_area(PivotFieldType, str), an overload that accepts the constant PivotFieldType.DATA and the source-column name. Once a field is added to the data region, the API exposes it through the PivotTable.data_fields collection, in the order in which the fields were added. By default, a numeric source column is summarised with ConsolidationFunction.SUM, while a non-numeric column defaults to Count.

import aspose.cells as ac
from aspose.cells.pivot import PivotFieldType, ConsolidationFunction
workbook = ac.Workbook()
worksheet = workbook.worksheets[0]
worksheet.name = "Data"
headers = ["Category", "Item", "Year", "Amount"]
for j, h in enumerate(headers):
    worksheet.cells.get(0, j).put_value(h)
data = [
    ["Fruit",     "Apple",  2020, 100],
    ["Fruit",     "Apple",  2021, 150],
    ["Fruit",     "Banana", 2020,  80],
    ["Fruit",     "Banana", 2021,  90],
    ["Vegetable", "Carrot", 2020,  50],
    ["Vegetable", "Carrot", 2021,  60],
    ["Vegetable", "Daikon", 2020,  40],
    ["Vegetable", "Daikon", 2021,  45],
]
for i, row in enumerate(data):
    for j, val in enumerate(row):
        worksheet.cells.get(i + 1, j).put_value(val)
pivot_index = worksheet.pivot_tables.add("A1:D9", "F3", "PivotTable1", True, False)
pivot_table = worksheet.pivot_tables[pivot_index]
pivot_table.add_field_to_area(PivotFieldType.ROW, "Category")
pivot_table.add_field_to_area(PivotFieldType.ROW, "Item")
pivot_table.add_field_to_area(PivotFieldType.COLUMN, "Year")
pivot_table.add_field_to_area(PivotFieldType.DATA, "Amount")
pivot_table.add_field_to_area(PivotFieldType.DATA, "Amount")
pivot_table.data_fields[1].function = ConsolidationFunction.COUNT
pivot_table.add_field_to_area(PivotFieldType.COLUMN, pivot_table.values_field)
pivot_table.calculate_data()
workbook.save("output_plot.xlsx")

Changing the Summary Function

Changing function only affects the aggregate, the source column does not change.

import aspose.cells as ac
from aspose.cells.pivot import PivotFieldType, ConsolidationFunction
workbook = ac.Workbook()
worksheet = workbook.worksheets[0]
worksheet.name = "Data"
headers = ["Category", "Item", "Year", "Amount"]
for j, h in enumerate(headers):
    worksheet.cells.get(0, j).put_value(h)
data = [
    ["Fruit",     "Apple",  2020, 100],
    ["Fruit",     "Apple",  2021, 150],
    ["Fruit",     "Banana", 2020,  80],
    ["Fruit",     "Banana", 2021,  90],
    ["Vegetable", "Carrot", 2020,  50],
    ["Vegetable", "Carrot", 2021,  60],
    ["Vegetable", "Daikon", 2020,  40],
    ["Vegetable", "Daikon", 2021,  45],
]
for i, row in enumerate(data):
    for j, val in enumerate(row):
        worksheet.cells.get(i + 1, j).put_value(val)
pivot_index = worksheet.pivot_tables.add("A1:D9", "F3", "PivotTable1", True, False)
pivot_table = worksheet.pivot_tables[pivot_index]
pivot_table.add_field_to_area(PivotFieldType.ROW, "Category")
pivot_table.add_field_to_area(PivotFieldType.ROW, "Item")
pivot_table.add_field_to_area(PivotFieldType.COLUMN, "Year")
pivot_table.add_field_to_area(PivotFieldType.DATA, "Amount")
pivot_table.add_field_to_area(PivotFieldType.DATA, "Amount")
pivot_table.data_fields[1].function = ConsolidationFunction.COUNT
pivot_table.calculate_data()
workbook.save("output_function.xlsx")

Plotting Value Fields to Row or Column Axis

When a pivot table contains two or more data fields, Aspose.Cells exposes an additional virtual field called PivotTable.values_field. This virtual field represents the aggregate of every data field that lives in the data region. You can drag it into the Row or Column region as a base pivot field, which is useful for laying out multiple measures side by side.

PivotTable.values_field does not work if there is no or only one value field.

import aspose.cells as ac
from aspose.cells.pivot import PivotFieldType
workbook = ac.Workbook()
worksheet = workbook.worksheets[0]
worksheet.name = "Data"
headers = ["Category", "Item", "Year", "Amount"]
for j, h in enumerate(headers):
    worksheet.cells.get(0, j).put_value(h)
data = [
    ["Fruit",     "Apple",  2020, 100],
    ["Fruit",     "Apple",  2021, 150],
    ["Fruit",     "Banana", 2020,  80],
    ["Fruit",     "Banana", 2021,  90],
    ["Vegetable", "Carrot", 2020,  50],
    ["Vegetable", "Carrot", 2021,  60],
    ["Vegetable", "Daikon", 2020,  40],
    ["Vegetable", "Daikon", 2021,  45],
]
for i, row in enumerate(data):
    for j, val in enumerate(row):
        worksheet.cells.get(i + 1, j).put_value(val)
pivot_index = worksheet.pivot_tables.add("A1:D9", "F3", "PivotTable1", True, False)
pivot_table = worksheet.pivot_tables[pivot_index]
pivot_table.add_field_to_area(PivotFieldType.ROW, "Category")
pivot_table.add_field_to_area(PivotFieldType.ROW, "Item")
pivot_table.add_field_to_area(PivotFieldType.COLUMN, "Year")
pivot_table.add_field_to_area(PivotFieldType.DATA, "Amount")
pivot_table.calculate_data()
workbook.save("output_drag.xlsx")