Use df.columns to get the column name of the Pandas DataFrame and return an Index object; 2. Use list(df.columns) or df.columns.tolist() to convert it into a Python list; 3. You can directly traverse df.columns to output each column name; In addition, you can use slices or list comprehensions to filter, such as df.columns[:2] to get the first two columns, and [col for col in df.columns if col.startswith('A')] to filter column names starting with A. These methods are implemented based on df.columns, which can meet most needs for obtaining and processing column names.
There are several common methods to get the column name of a Pandas DataFrame. Here is a simple and clear example showing how to get column names.
1. Use the .columns attribute
This is the most commonly used method, returning an Index object with all column names.
import pandas as pd
# Create a sample DataFrame
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 35],
'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)
# Get column name column_names = df.columns
print(column_names)Output:
Index(['Name', 'Age', 'City'], dtype='object')
2. Convert to Python list
If you want a normal Python list, you can use list() or .tolist() :
# Method 1: Use list() col_list = list(df.columns) print(col_list) # Output: ['Name', 'Age', 'City'] # Method 2: Use tolist() col_list = df.columns.tolist() print(col_list) # Output: ['Name', 'Age', 'City']
3. Traverse column names
You can also iterate over the column names like you would with a list:
for col in df.columns:
print(col)Output:
Name Age City
Tips
-
.columnsis read-only, but you can reassign values to rename all columns . - If you only want to view the first few columns or do conditional filtering, you can use it in combination with slices or list comprehensions.
For example, look at the first two columns:
print(df.columns[:2]) # Index(['Name', 'Age'], ...)
Or filter column names starting with a specific character:
print([col for col in df.columns if col.startswith('A')]) # As in ['Age']
Basically that's it. df.columns is the most core method, and it can basically meet most needs with tolist() .
The above is the detailed content of python pandas get column names example. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undress AI Tool
Undress images for free
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
How to use PHP combined with AI to achieve text error correction PHP syntax detection and optimization
Jul 25, 2025 pm 08:57 PM
To realize text error correction and syntax optimization with AI, you need to follow the following steps: 1. Select a suitable AI model or API, such as Baidu, Tencent API or open source NLP library; 2. Call the API through PHP's curl or Guzzle and process the return results; 3. Display error correction information in the application and allow users to choose whether to adopt it; 4. Use php-l and PHP_CodeSniffer for syntax detection and code optimization; 5. Continuously collect feedback and update the model or rules to improve the effect. When choosing AIAPI, focus on evaluating accuracy, response speed, price and support for PHP. Code optimization should follow PSR specifications, use cache reasonably, avoid circular queries, review code regularly, and use X
PHP calls AI intelligent voice assistant PHP voice interaction system construction
Jul 25, 2025 pm 08:45 PM
User voice input is captured and sent to the PHP backend through the MediaRecorder API of the front-end JavaScript; 2. PHP saves the audio as a temporary file and calls STTAPI (such as Google or Baidu voice recognition) to convert it into text; 3. PHP sends the text to an AI service (such as OpenAIGPT) to obtain intelligent reply; 4. PHP then calls TTSAPI (such as Baidu or Google voice synthesis) to convert the reply to a voice file; 5. PHP streams the voice file back to the front-end to play, completing interaction. The entire process is dominated by PHP to ensure seamless connection between all links.
How to develop AI intelligent form system with PHP PHP intelligent form design and analysis
Jul 25, 2025 pm 05:54 PM
When choosing a suitable PHP framework, you need to consider comprehensively according to project needs: Laravel is suitable for rapid development and provides EloquentORM and Blade template engines, which are convenient for database operation and dynamic form rendering; Symfony is more flexible and suitable for complex systems; CodeIgniter is lightweight and suitable for simple applications with high performance requirements. 2. To ensure the accuracy of AI models, we need to start with high-quality data training, reasonable selection of evaluation indicators (such as accuracy, recall, F1 value), regular performance evaluation and model tuning, and ensure code quality through unit testing and integration testing, while continuously monitoring the input data to prevent data drift. 3. Many measures are required to protect user privacy: encrypt and store sensitive data (such as AES
python seaborn jointplot example
Jul 26, 2025 am 08:11 AM
Use Seaborn's jointplot to quickly visualize the relationship and distribution between two variables; 2. The basic scatter plot is implemented by sns.jointplot(data=tips,x="total_bill",y="tip",kind="scatter"), the center is a scatter plot, and the histogram is displayed on the upper and lower and right sides; 3. Add regression lines and density information to a kind="reg", and combine marginal_kws to set the edge plot style; 4. When the data volume is large, it is recommended to use "hex"
How to use PHP combined with AI to analyze video content PHP intelligent video tag generation
Jul 25, 2025 pm 06:15 PM
The core idea of PHP combining AI for video content analysis is to let PHP serve as the backend "glue", first upload video to cloud storage, and then call AI services (such as Google CloudVideoAI, etc.) for asynchronous analysis; 2. PHP parses the JSON results, extract people, objects, scenes, voice and other information to generate intelligent tags and store them in the database; 3. The advantage is to use PHP's mature web ecosystem to quickly integrate AI capabilities, which is suitable for projects with existing PHP systems to efficiently implement; 4. Common challenges include large file processing (directly transmitted to cloud storage with pre-signed URLs), asynchronous tasks (introducing message queues), cost control (on-demand analysis, budget monitoring) and result optimization (label standardization); 5. Smart tags significantly improve visual
How to develop AI-based text summary with PHP Quick Refining Technology
Jul 25, 2025 pm 05:57 PM
The core of PHP's development of AI text summary is to call external AI service APIs (such as OpenAI, HuggingFace) as a coordinator to realize text preprocessing, API requests, response analysis and result display; 2. The limitation is that the computing performance is weak and the AI ecosystem is weak. The response strategy is to leverage APIs, service decoupling and asynchronous processing; 3. Model selection needs to weigh summary quality, cost, delay, concurrency, data privacy, and abstract models such as GPT or BART/T5 are recommended; 4. Performance optimization includes cache, asynchronous queues, batch processing and nearby area selection. Error processing needs to cover current limit retry, network timeout, key security, input verification and logging to ensure the stable and efficient operation of the system.
PHP integrated AI emotional computing technology PHP user feedback intelligent analysis
Jul 25, 2025 pm 06:54 PM
To integrate AI sentiment computing technology into PHP applications, the core is to use cloud services AIAPI (such as Google, AWS, and Azure) for sentiment analysis, send text through HTTP requests and parse returned JSON results, and store emotional data into the database, thereby realizing automated processing and data insights of user feedback. The specific steps include: 1. Select a suitable AI sentiment analysis API, considering accuracy, cost, language support and integration complexity; 2. Use Guzzle or curl to send requests, store sentiment scores, labels, and intensity information; 3. Build a visual dashboard to support priority sorting, trend analysis, product iteration direction and user segmentation; 4. Respond to technical challenges, such as API call restrictions and numbers
PHP integrated AI intelligent image processing PHP image beautification and automatic editing
Jul 23, 2025 pm 07:12 PM
PHP integrated AI image processing requires the help of a third-party API or local model, which cannot be directly implemented; 2. Use ready-made services such as Google CloudVision API to quickly realize facial recognition, object detection and other functions. The advantages are fast development and strong functions. The disadvantages are that they need to pay, rely on the network and have data security risks; 3. Deploy local AI models through PHP image library such as Imagick or GD combined with TensorFlowLite or ONNXRuntime. It can be customized, the data is safer, and the cost is low, but the development is difficult and requires AI knowledge; 4. Mixed solutions can combine the advantages of API and local model, such as using API for detection and beautification of local models; 5. Selecting AI image processing API should be comprehensive
