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USANDO IRONXL PARA PYTHON

Cómo Ver un Archivo de Excel en Python

In this tutorial, we will explore how to use Python for viewing Excel files effectively. Excel files, commonly used for data storage such as storing tabular data, are well-supported by several Python libraries that facilitate reading and manipulation. We will focus on the popular and best library "IronXL" for this purpose.

How to View an Excel File in Python

  1. Install the IronXL Library.
  2. Load the Excel Workbook.
  3. Specify the Excel Worksheet.
  4. Select a Specific Range of Data.
  5. Print the Selected Data Range on the Screen.
  6. Read Cell Value.
  7. Read Complete Row from Excel File.
  8. Read the Complete Column from the Excel file.

Introduction to Python Excel Viewer

Before diving into the code, let's discuss the benefits of using Python to view Excel files. Python is well known for its simplicity and versatility, making it a powerful and robust programming language. By leveraging Python libraries, we can automate tasks related to data analysis, manipulation, and visualization, including handling Excel files.

Why Python for Excel?

Automation: Python enables the automation of repetitive tasks associated with Excel, such as data extraction, transformation, and analysis.

Integration: Python seamlessly integrates with other data science libraries like NumPy, pandas, and Matplotlib, enabling comprehensive data analysis workflows.

Cross-platform: Python, in its latest Python version, runs on multiple platforms, making it suitable for users across different operating systems.

Customization: Python provides flexibility to customize Excel workflows according to specific requirements, unlike conventional Excel macros.

Before proceeding further, let's understand what IronXL is, what features it provides, and how it is better than others.

Why IronXL?

IronXL is a Python library developed and maintained by Iron Software that allows software engineers to work with Excel and other spreadsheet files in Python applications and websites. Below are some of its notable key features:

Importing Data: IronXL can read data from XLS, XLSX, CSV, and TSV files.

Export Work Sheets: You can export data to XLS, XLSX, CSV, TSV, and JSON formats.

Encryption and Decryption: IronXL supports encrypting and decrypting XLSX, XLSM, and XLTX files with passwords.

Excel Formulas: Every time a sheet is edited, the formulas are recalculated.

Intuitive Ranges Setting: You can specify ranges using a syntax like "A1:B10".

Sorting: Ranges, columns, and rows can be sorted.

Cell Styling: Customize font, size, background pattern, border, and alignment.

Cross-Platform Support: IronXL is compatible with Python 3.7+ on Windows, macOS, Linux, Docker, Azure, and AWS.

Reading Excel File using IronXL

Let's begin step by step to read an Excel file.

Step 1: Installing IronXL Library

Before working with Excel files in Python, we need to ensure that the IronXL Library is installed. Install it with the following command.

pip install IronXL
pip install IronXL
SHELL

This command installs the IronXL Library in our project.

Step 2: Load Excel file

The next step involves loading an Excel workbook into our project. I will be using the following Excel spreadsheet throughout this tutorial.

How to View an Excel File in Python: Figure 1 - Microsoft Excel example worksheet

The following code will load the existing Excel file in the memory stream.

from ironxl import *     
# Supported for XLSX files, XLS, XLSM, XLTX, CSV, and TSV
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-ABC.TRIAL.EXPIRES.27.MAY.2024"
workbook = WorkBook.Load("test_excel.xlsx")  # Load existing Excel files
from ironxl import *     
# Supported for XLSX files, XLS, XLSM, XLTX, CSV, and TSV
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-ABC.TRIAL.EXPIRES.27.MAY.2024"
workbook = WorkBook.Load("test_excel.xlsx")  # Load existing Excel files
PYTHON

The above code demonstrates how to use the IronXL library in Python to load an Excel workbook named "test_excel.xlsx" and access its contents. By setting the LicenseKey attribute with a valid license key, the library enables support for various Excel file formats including XLSX, XLS, XLSM, XLTX, CSV, and TSV. You can get your free license key from here.

Step 3: Select Excel Spreadsheet

The next step is to select an Excel spreadsheet to work on. Excel files consist of multiple sheets; therefore, it is necessary to select an active spreadsheet. The following code will specify the spreadsheet.

# Select worksheet at index 0
worksheet = workbook.WorkSheets[0]
# Select worksheet at index 0
worksheet = workbook.WorkSheets[0]
PYTHON

The above line of code selects the first worksheet with zero-indexed from the loaded Excel workbook, enabling access to the data and properties of that specific sheet for further manipulation or analysis.

Step 4: Viewing Data

As we have loaded the workbook and selected the spreadsheet, let's write code to read an Excel file and print its data.

# Read from ranges of cells elegantly.
for cell in worksheet["A1:H10"]:
    print("Cell {} has value '{}'".format(cell.AddressString, cell.Text))
# Read from ranges of cells elegantly.
for cell in worksheet["A1:H10"]:
    print("Cell {} has value '{}'".format(cell.AddressString, cell.Text))
PYTHON

This code snippet demonstrates a sophisticated method for reading from cell ranges in an Excel worksheet using the IronXL library. It iterates over the specified range of cells (from A1 to H10 in this case) and prints out each cell's address and value. This provides a concise and effective method for accessing and processing data within the specified range of cells.

How to View an Excel File in Python: Figure 2 - Example output from the code snippet above iterating all the values for the specified range of cell using IronXL

Step 5: Read Cell Value

IronXL provides simpler methods to read cell values. We can efficiently read specific cell values from large datasets. The following code reads the cell value and prints it on the screen.

# Read Integer value
int_cell_value = worksheet["H2"].IntValue 
print(int_cell_value)
# Read String value
text_cell_value = worksheet["B2"].StringValue 
print(text_cell_value)
# Read Integer value
int_cell_value = worksheet["H2"].IntValue 
print(int_cell_value)
# Read String value
text_cell_value = worksheet["B2"].StringValue 
print(text_cell_value)
PYTHON

This code snippet demonstrates how to extract an integer value from cell H2 and a string value from cell B2 in an Excel worksheet using the IronXL library. It then prints out the extracted values, providing clear and organized output for further processing or display.

How to View an Excel File in Python: Figure 3 - Example output from the code snippet above obtaining both the integer and cell value using IronXL

Step 6: Select Complete Row

IronXL provides a method to select a specific row from an Excel file. The following code will read a specific row from the Excel file and print it on the screen.

# Get row from worksheet
row_1 = worksheet.GetRow(1)
print(row_1)
# Get row from worksheet
row_1 = worksheet.GetRow(1)
print(row_1)
PYTHON

This code snippet demonstrates how to retrieve a specific row from an Excel worksheet using the IronXL library. It selects the first row (row index 1) from the worksheet and then prints it out, allowing for further processing or analysis of the row's data. In this way, we can get all the rows from the Excel sheet.

How to View an Excel File in Python: Figure 4 - Example output from the code snippet above using IronXL to get the first row of data from the Excel worksheet

Step 7: Select Complete Column

IronXL provides a method to select a specific Column from an Excel file. The following code will read a specific Column from the Excel file and print it on the screen.

# Get Column from worksheet
column_a = worksheet.GetColumn(1)
print(column_a)
# Get Column from worksheet
column_a = worksheet.GetColumn(1)
print(column_a)
PYTHON

This code snippet illustrates how to extract a specific column from an Excel worksheet using the IronXL library. It retrieves the data from column A (column index 1) and prints it out, providing access to the column's contents for further manipulation or analysis.

How to View an Excel File in Python: Figure 5 - Example output from the code snippet above demonstrating how to extract a specific column using IronXL

Conclusion

In this tutorial, we explored how to use Python for Excel file viewing, focusing on the IronXL library. Python's versatility makes it ideal for automating Excel-related tasks, and IronXL enhances this capability by providing features like importing options for individual developers and organizations. With IronXL and Python, handling Excel files becomes more efficient, enabling developers to unlock the full potential of Excel data within their applications.

Preguntas Frecuentes

¿Cómo puedo ver archivos Excel usando Python?

Puede usar la biblioteca IronXL para ver archivos Excel en Python. Ofrece funciones para cargar libros de trabajo, seleccionar hojas de cálculo y leer rangos de datos específicos o valores de celdas.

¿Qué debo instalar para usar Python para ver archivos Excel?

Para usar Python para ver archivos Excel, necesita instalar la biblioteca IronXL, lo cual se puede hacer usando el comando pip: `pip install IronXL`.

¿Cómo cargo un libro de trabajo de Excel en Python?

Usando IronXL, puede cargar un libro de trabajo de Excel con el siguiente código: workbook = WorkBook.Load('test_excel.xlsx'), el cual carga el archivo de Excel especificado en la memoria.

¿Qué formatos de archivo soporta IronXL para operaciones de Excel?

IronXL admite varios formatos de archivo, incluidos XLSX, XLS, CSV y TSV, lo que lo hace versátil para diferentes operaciones de Excel.

¿Cómo puedo leer un valor de celda específico de un archivo Excel usando Python?

Para leer un valor de celda específico usando IronXL, puede usar worksheet['H2'].IntValue para enteros o worksheet['B2'].StringValue para valores de cadenas.

¿Puede IronXL manejar la encriptación y desencriptación de archivos Excel?

Sí, IronXL puede manejar la encriptación y desencriptación de archivos Excel, proporcionando una capa adicional de seguridad para sus datos.

¿Es IronXL compatible con diferentes sistemas operativos?

Sí, IronXL es compatible con Python 3.7+ y admite operaciones multiplataforma en Windows, macOS, Linux, Docker, Azure y AWS.

¿Cómo selecciono una hoja de cálculo específica de un libro de trabajo usando Python?

Para seleccionar una hoja de cálculo específica de un libro de trabajo usando IronXL, puede usar el código worksheet = workbook.WorkSheets[0] para seleccionar la primera hoja de cálculo.

¿Cuáles son los beneficios de usar IronXL para la manipulación de archivos Excel en Python?

IronXL ofrece facilidad de integración en aplicaciones Python, soporte robusto para varios formatos de archivo, capacidades avanzadas de manejo de datos y compatibilidad multiplataforma.

¿Cómo puedo automatizar tareas de Excel usando Python?

Python, con bibliotecas como IronXL, le permite automatizar tareas de Excel como análisis de datos, visualización y manipulación, mejorando la productividad y eficiencia.

Curtis Chau
Escritor Técnico

Curtis Chau tiene una licenciatura en Ciencias de la Computación (Carleton University) y se especializa en el desarrollo front-end con experiencia en Node.js, TypeScript, JavaScript y React. Apasionado por crear interfaces de usuario intuitivas y estéticamente agradables, disfruta trabajando con frameworks modernos y creando manuales bien ...

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