aspose-cells-python

Aspose.Cells for Python via .NET

Product Page <https://products.aspose.com/cells/python-net>_ | Docs <https://docs.aspose.com/cells/python-net/>_ | API Reference <https://reference.aspose.com/cells/python-net/>_ | Demos <https://products.aspose.app/cells/family/>_ | Blog <https://blog.aspose.com/category/cells/>_ | Code Samples <https://github.com/aspose-cells/Aspose.Cells-for-Python-via-.NET>_ | Free Support <https://forum.aspose.com/c/cells>_ | Temporary License <https://purchase.aspose.com/temporary-license>_ | EULA <https://company.aspose.com/legal/eula>_

Try our free online apps <https://products.aspose.app/cells/family>_ demonstrating some of the most popular Aspose.Cells functionality.

Overview

Aspose.Cells for Python via .NET is a powerful spreadsheet management library that allows developers to create, format, and manipulate Excel files programmatically without the need for Microsoft Excel. It supports features like:

• Creating Pivot Tables
• Advanced conditional formatting
• Conversion to PDF, HTML, JSON
• Charts, Smart Markers, OLE objects
• Filtering data

Aspose.Cells API Features

• Spreadsheet generation & manipulation via API
• High-quality file format conversion & rendering
• Print Microsoft Excel® files to physical or virtual printers
• Combine, modify, protect, or parse Excel® sheets
• Apply worksheet formatting and page setup
• Create & customize Excel® charts, Pivot Tables, conditional formatting, slicers, tables & spark-lines
• Convert Excel® charts to images & PDF
• Formula calculation engine supporting basic and advanced Excel functions

Supported Read & Write Formats

• Microsoft Excel®: XLS, XLSX, XLSB, XLSM, XLT, XLTX, XLTM, SpreadsheetML
• OpenOffice: ODS, SXC, FODS
• Text: JSON, TXT, CSV, TSV, Tab-Delimited
• Web: HTML, MHTML
• iWork®: Numbers

Save Excel® Files As

• Microsoft Word®: DOCX
• Microsoft PowerPoint®: PPTX
• Microsoft Excel®: XLAM
• Fixed Layout: PDF, XPS
• Text: JSON, TXT, CSV, TSV, Tab-Delimited, XML
• Image: TIFF, PNG, BMP, JPEG, GIF, SVG
• Metafile: EMF
• Markdown: MD

Examples

Create Excel file from scratch

.. code-block:: python

# import the python package
import aspose.cells
from aspose.cells import License, Workbook, FileFormatType

# Instantiating a Workbook object
workbook = Workbook()
# Get the first worksheet
worksheet = workbook.worksheets[0]
# Get the "A1" cell
cell = worksheet.cells.get("A1")
# Write "Hello World" to  "A1" in the first sheet
cell.put_value("Hello World!")
# Saving this workbook to XLSX
workbook.save("HelloWorld.xlsx")

Convert Excel XLSX file to PDF

.. code-block:: python

# import the python package
import aspose.cells
from aspose.cells import Workbook

# Instantiating a Workbook object
workbook = Workbook("HelloWorld.xlsx")
# Saving this workbook to PDF
workbook.save("HelloWorld.pdf")

Create a chart

.. code-block:: python

from aspose.cells import Workbook
from aspose.cells.charts import ChartType

# Instantiating a Workbook object
workbook = Workbook()
# Adding a new worksheet to the Excel object
sheetIndex = workbook.worksheets.add()
# Obtaining the reference of the newly added worksheet by passing its sheet index
worksheet = workbook.worksheets[sheetIndex]
# Adding sample values to cells
worksheet.cells.get("A1").put_value(50)
worksheet.cells.get("A2").put_value(100)
worksheet.cells.get("A3").put_value(170)
worksheet.cells.get("A4").put_value(300)
worksheet.cells.get("B1").put_value(160)
worksheet.cells.get("B2").put_value(32)
worksheet.cells.get("B3").put_value(50)
worksheet.cells.get("B4").put_value(40)
# Adding sample values to cells as category data
worksheet.cells.get("C1").put_value("Q1")
worksheet.cells.get("C2").put_value("Q2")
worksheet.cells.get("C3").put_value("Y1")
worksheet.cells.get("C4").put_value("Y2")
# Adding a chart to the worksheet
chartIndex = worksheet.charts.add(ChartType.COLUMN, 5, 0, 15, 5)
# Accessing the instance of the newly added chart
chart = worksheet.charts[chartIndex]
# Adding SeriesCollection (chart data source) to the chart ranging from "A1" cell to "B4"
chart.n_series.add("A1:B4", True)
# Setting the data source for the category data of SeriesCollection
chart.n_series.category_data = "C1:C4"
# Saving the Excel file
workbook.save("Chart.xlsx")

Convert Excel workbook to JSON

.. code-block:: python

from aspose.cells import Workbook

# Instantiating a Workbook object
workbook = Workbook()
# Obtaining the reference of the newly added worksheet
sheet = workbook.worksheets[0]
cells = sheet.cells
# Setting the value to the cells
cells.get("A1").put_value("First name")
cells.get("A2").put_value("Simon")
cells.get("A3").put_value("Kevin")
cells.get("A4").put_value("Leo")
cells.get("A5").put_value("Johnson")

cells.get("B1").put_value("Age")
cells.get("B2").put_value(32)
cells.get("B3").put_value(33)
cells.get("B4").put_value(34)
cells.get("B5").put_value(35)

cells.get("C1").put_value("Value")
cells.get("C2").put_value(123.546)
cells.get("C3").put_value(56.78)
cells.get("C4").put_value(34)
cells.get("C5").put_value(9)
# Saving the Excel file to json
workbook.save("Out.json")

Convert Excel to Pandas DataFrame

.. code-block:: python

import pandas as pd
from aspose.cells import Workbook

# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Get the first worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
# Add header and data values to specific cells
cells.get("A1").value = "Name"
cells.get("B1").value = "Age"
cells.get("C1").value = "City"
cells.get("A2").value = "Alice"
cells.get("B2").value = 25
cells.get("C2").value = "New York"
cells.get("A3").value = "Bob"
cells.get("B3").value = 30
cells.get("C3").value = "San Francisco"
cells.get("A4").value = "Charlie"
cells.get("B4").value = 35
cells.get("C4").value = "Los Angeles"

rowCount = cells.max_data_row
columnCount = cells.max_data_column

# Read the header row (row 0) and store column names
columnDatas = []
for c in range(columnCount + 1):
    columnDatas.append(cells.get_cell(0, c).value)

# Create an empty pandas DataFrame with column names from Excel
result = pd.DataFrame(columns=columnDatas, dtype=object)

# Read each data row (from row 1 onward) and add to the DataFrame
for i in range(1, rowCount + 1):
    rowarray = [cells.get_cell(i, j).value for j in range(columnCount + 1)]
    result.loc[i - 1] = rowarray

print(result)

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