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如何使用 python 将 Excel 文件导入数据库表

In today's data-driven world, efficient handling and processing of data are essential tasks for any organization or individual. Python, with its rich ecosystem of libraries, offers powerful tools for data manipulation and management such as the pandas library. One common scenario is the need to extract or import data from Excel spreadsheets and store or insert data in a database for further analysis or integration with other systems. In this tutorial, we'll explore how to create a Python script that automates this process, allowing you to seamlessly read data from Excel sheet files and insert it into a database. By the end of this tutorial, you'll be ready to handle data migration tasks efficiently. Let's begin!

How to Import an Excel File into a Database Table Using Python

  1. Begin by installing the IronXL library.
  2. Load your Excel file into memory using IronXL.
  3. Load the specific spreadsheet you wish to work with.
  4. Select the precise data range that you intend to import.
  5. Establish a connection with any database such as SQLite or MySQL connection database using Python.
  6. Create a new table within your SQLite database to accommodate the imported data.
  7. Insert the selected rows from the Excel file into the newly created SQLite table.
  8. Retrieve and select data from the created SQLite table for further analysis or processing.

In this tutorial, we will use IronXL, a Python library renowned for its efficiency in handling Excel files. By integrating IronXL into our script, we ensure seamless extraction of data from Excel spreadsheets, enabling smooth insertion into databases for further analysis and processing.

What is IronXL?

IronXL is a Python library developed by Iron Software, offering robust functionality for reading, generating, and editing Excel files directly within Python applications. Notably, IronXL stands out for its independence from Microsoft Excel installation, simplifying deployment across different environments. With IronXL, developers benefit from:

Cross-Platform Support: Enjoy seamless operation on Windows, macOS, Linux, Docker, Azure, and AWS platforms, ensuring adaptability to diverse development setups.

Data Import and Export: Easily handle data import from XLS, XLSX, CSV, and TSV files, with the flexibility to export worksheets to these formats and even to JSON for enhanced interoperability.

Encryption Features: Ensure data security by leveraging IronXL's encryption capabilities, allowing for the protection of XLSX, XLSM, and XLTX files with passwords.

Formulas and Recalculation: Work effortlessly with Excel formulas, with the added benefit of automatic recalculation every time a sheet is edited, ensuring accuracy and reliability in data manipulation.

Cell Styling: Customize the appearance of individual cells by adjusting font styles, sizes, background patterns, borders, and alignment, enhancing the visual presentation of your Excel documents.

Wide Range of Document Formats: With support for various formats including XLS, XLSX, XLST, XLSM, CSV, and TSV, IronXL empowers developers to handle data in a multitude of scenarios with ease and efficiency.

Now, let's begin by installing IronXL.

Step 1: Install IronXL Library

The very first step is to install the IronXL library. Run the following command to install IronXL in the command prompt.

pip install IronXL
pip install IronXL
SHELL

Step 2: Load Excel Workbook

The next step is to load the Excel file. We will be using the following Excel file for this tutorial.

How to Import an Excel File into a Database Table Using python: Figure 1 - Sample Excel File Input

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

from ironxl import *  # Supported for XLSX, XLS, XLSM, XLTX, CSV, and TSV

# Assign a license key (retrieved from IronXL website)
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-DEPLOYMENT.TRIAL-5X63V4.TRIAL.EXPIRES.27.MAY.2024"

# Load the Excel workbook into memory
workbook = WorkBook.Load("sample_excel.xlsx")
from ironxl import *  # Supported for XLSX, XLS, XLSM, XLTX, CSV, and TSV

# Assign a license key (retrieved from IronXL website)
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-DEPLOYMENT.TRIAL-5X63V4.TRIAL.EXPIRES.27.MAY.2024"

# Load the Excel workbook into memory
workbook = WorkBook.Load("sample_excel.xlsx")
PYTHON

The above Python code snippet demonstrates loading an Excel workbook named "sample_excel.xlsx" using the IronXL library. Firstly, the necessary Python module is imported from IronXL. Then, a license key is assigned to validate the library usage. You can get your free license key from the IronXL Website. Finally, the Load method is employed to open and load the specified Excel workbook into memory. This enables subsequent manipulation of its contents programmatically, such as reading data, modifying cell values, or applying formatting.

Step 3: Selecting Worksheet

To select a worksheet in an Excel workbook using IronXL, you can specify the worksheet index or name.

# Select the first worksheet in the loaded Excel workbook
worksheet = workbook.WorkSheets[0]
# Select the first worksheet in the loaded Excel workbook
worksheet = workbook.WorkSheets[0]
PYTHON

This line selects the first worksheet in the loaded Excel workbook and assigns it to the variable worksheet, allowing subsequent operations to be performed on that specific worksheet within the workbook. This will load Excel data from an Excel sheet to a worksheet variable.

Step 4: Open the Database connection

In this tutorial, we're utilizing an SQLite database instead of a MySQL database server. To initiate database operations, we start by establishing a connection to the database.

import sqlite3

# Connect to SQLite database (or create it if it doesn't exist)
conn = sqlite3.connect('data.db')
import sqlite3

# Connect to SQLite database (or create it if it doesn't exist)
conn = sqlite3.connect('data.db')
PYTHON

The above line establishes a connection to an SQLite database named 'data.db'. If the specified database doesn't exist, it will be created automatically. This connection enables subsequent interaction with the SQLite database, such as executing queries and performing data manipulation operations.

Step 5: Create a table

The next step is to create a database table in the database, where we will import data from an Excel file. To create a table in the SQLite database, you can execute an SQL statement using the connection object.

# Create a cursor object for database operations
cursor = conn.cursor()

# Define and execute SQL to create a table if it doesn't exist
cursor.execute('''
CREATE TABLE IF NOT EXISTS customer (
    id INTEGER,
    FirstName TEXT,
    LastName TEXT,
    Gender TEXT,
    Country TEXT,
    Age INTEGER
)
''')
# Create a cursor object for database operations
cursor = conn.cursor()

# Define and execute SQL to create a table if it doesn't exist
cursor.execute('''
CREATE TABLE IF NOT EXISTS customer (
    id INTEGER,
    FirstName TEXT,
    LastName TEXT,
    Gender TEXT,
    Country TEXT,
    Age INTEGER
)
''')
PYTHON

The above code snippet initializes a cursor object to execute SQL commands within the SQLite database connection. It creates a table named 'customer' with columns 'id', 'FirstName', 'LastName', 'Gender', 'Country', and 'Age'. The table is created if it doesn't already exist, adhering to the specified column data types.

Step 6: Importing data into the Database using Python

Now, we will insert data into our newly created table. We will import an Excel file and insert its data into the SQLite database.

# Iteratively insert data from Excel worksheet into SQLite database
for i in range(2, 11):
    # Extracting values from columns A to F in Excel worksheet
    values_tuple = (
        worksheet[f"A{i}"].StringValue,
        worksheet[f"B{i}"].StringValue,
        worksheet[f"C{i}"].StringValue,
        worksheet[f"D{i}"].StringValue,
        worksheet[f"E{i}"].StringValue,
        worksheet[f"F{i}"].StringValue
    )
    # Executing SQL INSERT command
    cursor.execute("INSERT INTO customer VALUES (?, ?, ?, ?, ?, ?)", values_tuple)

# Commit data insertion to the database
conn.commit()
# Iteratively insert data from Excel worksheet into SQLite database
for i in range(2, 11):
    # Extracting values from columns A to F in Excel worksheet
    values_tuple = (
        worksheet[f"A{i}"].StringValue,
        worksheet[f"B{i}"].StringValue,
        worksheet[f"C{i}"].StringValue,
        worksheet[f"D{i}"].StringValue,
        worksheet[f"E{i}"].StringValue,
        worksheet[f"F{i}"].StringValue
    )
    # Executing SQL INSERT command
    cursor.execute("INSERT INTO customer VALUES (?, ?, ?, ?, ?, ?)", values_tuple)

# Commit data insertion to the database
conn.commit()
PYTHON

The above code iterates over rows 2 to 10 in the Excel worksheet, extracting values from columns A to F for each row. These values are stored in a tuple, representing the data to be inserted into the 'customer' table. The cursor then executes an SQL INSERT command, incorporating the values tuple into the table. This process repeats for each row, effectively importing data from the Excel file into the SQLite database. Finally, conn.commit() commits the transaction, ensuring the changes are saved and persisted in the database.

Step 7: Reading data from the Database

To verify if the data was inserted correctly, you can read data from the 'customer' table in the SQLite database using a SELECT query. For example:

# Execute a SELECT query to retrieve all data from the 'customer' table
cursor.execute("SELECT * FROM customer")

# Fetch all rows from the result set
rows = cursor.fetchall()

# Print each row to verify inserted data
for row in rows:
    print(row)

# Close the database connection to release resources
conn.close()
# Execute a SELECT query to retrieve all data from the 'customer' table
cursor.execute("SELECT * FROM customer")

# Fetch all rows from the result set
rows = cursor.fetchall()

# Print each row to verify inserted data
for row in rows:
    print(row)

# Close the database connection to release resources
conn.close()
PYTHON

The above code executes a SELECT query on the 'customer' table in the SQLite database, retrieving all rows. The fetched rows are stored in the 'rows' variable using the fetchall() method. Then, each row is printed iteratively, displaying the data inserted into the 'customer' table. Finally, the database connection is closed using the close() method to release resources.

How to Import an Excel File into a Database Table Using python: Figure 2 - Read from Database Output

The Complete Code is as follows:

import sqlite3
from ironxl import *  # Supported for XLSX, XLS, XLSM, XLTX, CSV, and TSV

# Assign a license key (retrieved from IronXL website)
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-DEPLOYMENT.TRIAL-5X63V4.TRIAL.EXPIRES.27.MAY.2024"

# Load the Excel workbook into memory
workbook = WorkBook.Load("sample_excel.xlsx")

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

# Connect to SQLite database (or create it if it doesn't exist)
conn = sqlite3.connect('data.db')

# Create a cursor object for database operations
cursor = conn.cursor()

# Define and execute SQL to create a table if it doesn't exist
cursor.execute('''
CREATE TABLE IF NOT EXISTS customer (
    id INTEGER,
    FirstName TEXT,
    LastName TEXT,
    Gender TEXT,
    Country TEXT,
    Age INTEGER
)
''')

# Clear any existing data from the table
cursor.execute("DELETE FROM customer")

# Iteratively insert data from Excel worksheet into SQLite database
for i in range(2, 11):
    # Extracting values from columns A to F in Excel worksheet
    values_tuple = (
        worksheet[f"A{i}"].StringValue,
        worksheet[f"B{i}"].StringValue,
        worksheet[f"C{i}"].StringValue,
        worksheet[f"D{i}"].StringValue,
        worksheet[f"E{i}"].StringValue,
        worksheet[f"F{i}"].StringValue
    )
    # Executing SQL INSERT command
    cursor.execute("INSERT INTO customer VALUES (?, ?, ?, ?, ?, ?)", values_tuple)

# Commit data insertion to the database
conn.commit()

# Execute a SELECT query to retrieve all data from the 'customer' table
cursor.execute("SELECT * FROM customer")

# Fetch all rows from the result set
rows = cursor.fetchall()

# Print each row to verify inserted data
for row in rows:
    print(row)

# Close the database connection to release resources
conn.close()
import sqlite3
from ironxl import *  # Supported for XLSX, XLS, XLSM, XLTX, CSV, and TSV

# Assign a license key (retrieved from IronXL website)
License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-DEPLOYMENT.TRIAL-5X63V4.TRIAL.EXPIRES.27.MAY.2024"

# Load the Excel workbook into memory
workbook = WorkBook.Load("sample_excel.xlsx")

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

# Connect to SQLite database (or create it if it doesn't exist)
conn = sqlite3.connect('data.db')

# Create a cursor object for database operations
cursor = conn.cursor()

# Define and execute SQL to create a table if it doesn't exist
cursor.execute('''
CREATE TABLE IF NOT EXISTS customer (
    id INTEGER,
    FirstName TEXT,
    LastName TEXT,
    Gender TEXT,
    Country TEXT,
    Age INTEGER
)
''')

# Clear any existing data from the table
cursor.execute("DELETE FROM customer")

# Iteratively insert data from Excel worksheet into SQLite database
for i in range(2, 11):
    # Extracting values from columns A to F in Excel worksheet
    values_tuple = (
        worksheet[f"A{i}"].StringValue,
        worksheet[f"B{i}"].StringValue,
        worksheet[f"C{i}"].StringValue,
        worksheet[f"D{i}"].StringValue,
        worksheet[f"E{i}"].StringValue,
        worksheet[f"F{i}"].StringValue
    )
    # Executing SQL INSERT command
    cursor.execute("INSERT INTO customer VALUES (?, ?, ?, ?, ?, ?)", values_tuple)

# Commit data insertion to the database
conn.commit()

# Execute a SELECT query to retrieve all data from the 'customer' table
cursor.execute("SELECT * FROM customer")

# Fetch all rows from the result set
rows = cursor.fetchall()

# Print each row to verify inserted data
for row in rows:
    print(row)

# Close the database connection to release resources
conn.close()
PYTHON

Conclusion

In conclusion, this tutorial has demonstrated an automated approach to data manipulation, specifically extracting and inserting Excel data into a database. This process not only enhances the efficiency of data management but also unlocks its full potential for data handling endeavors. Embrace the power of Python and IronXL to optimize your data workflows and propel your projects forward with confidence.

常见问题解答

如何使用Python将数据从Excel文件导入数据库?

你可以使用IronXL库从Excel文件导入数据到数据库,首先通过`WorkBook.Load()`加载Excel文件,然后选择工作表并与SQLite建立数据库连接以插入数据。

使用IronXL处理Excel文件在Python中有什么好处?

IronXL允许你处理Excel文件而无需安装Microsoft Excel,支持跨平台操作,提供像加密和公式重新计算等强大功能,并有效管理数据提取和插入过程。

如何为Python项目安装IronXL?

要为Python项目安装IronXL,你可以使用命令:`pip install IronXL`。这会将IronXL添加到你的Python环境中,从而让你有效地处理Excel文件。

在未安装Microsoft Excel的情况下,是否可以在Python中处理Excel文件?

是的,使用IronXL,你可以在未安装Microsoft Excel的情况下处理Excel文件。IronXL提供了所有读取、编辑和写入Excel文件所需的功能。

在Python中创建一个数据库表以存储Excel数据的过程是什么?

要在Python中创建数据库表,你可以使用SQLite的`sqlite3`模块。在使用`connect()`建立连接后,通过cursor对象执行SQL的`CREATE TABLE`语句。

如何验证Excel数据是否成功插入到SQLite数据库中?

你可以通过在表上执行`SELECT`查询,并使用`fetchall()`方法检索并打印结果集中的所有行来验证插入。

在使用Python将数据从Excel迁移到数据库时需要遵循哪些步骤?

步骤包括安装IronXL、加载Excel文件、选择工作表、连接到数据库、创建表,并迭代Excel行以使用SQL `INSERT`命令插入数据。

IronXL是否能处理Excel公式并在Python中重新计算它们?

是的,IronXL支持Excel公式并能重新计算它们,为Python应用中的Excel文件操作提供全面的解决方案。

IronXL是否支持Excel文件操作的跨平台操作?

是的,IronXL支持跨平台操作,包括像Windows、macOS、Linux、Docker、Azure和AWS等环境,使其成为各种开发设置的多功能选择。

IronXL如何增强Python应用中的数据工作流程?

IronXL通过提供高效的数据提取、操作和插入能力来增强数据工作流程,这优化了数据管理过程并提高了数据驱动应用程序的性能。

Curtis Chau
技术作家

Curtis Chau 拥有卡尔顿大学的计算机科学学士学位,专注于前端开发,精通 Node.js、TypeScript、JavaScript 和 React。他热衷于打造直观且美观的用户界面,喜欢使用现代框架并创建结构良好、视觉吸引力强的手册。

除了开发之外,Curtis 对物联网 (IoT) 有浓厚的兴趣,探索将硬件和软件集成的新方法。在空闲时间,他喜欢玩游戏和构建 Discord 机器人,将他对技术的热爱与创造力相结合。