How to use Code Interpreter: A Detailed Guide
This time, we will explain in detail how to use the new ChatGPT function “Code Interpreter”. This function is a mechanism that allows Python code to be executed on ChatGPT, and there are various ways to use it, such as data analysis and file upload/download. Now let’s take a closer look.
1. What is Code Interpreter?
Code Interpreter is a new feature that allows you to run Python code on ChatGPT. As a result, ChatGPT can perform more advanced operations such as code generation, execution, file upload/download, etc. from a simple conversation tool.
Python is a programming language used in a wide range of applications, including data analysis, machine learning, and web development. So, allowing ChatGPT to run Python code greatly expands its scope of use.
2. Setting up Code Interpreter
Code Interpreter is set up in the following three steps.
1. Billing for ChatGPT Plus: First, in order to use Code Interpreter, you need to pay for ChatGPT Plus. ChatGPT Plus is a paid version of ChatGPT with more advanced features.
2. Set the Setting Beta: Next, set the Setting Beta. You can do this from ChatGPT’s settings screen. Beta is a test version for testing new features. Since Code Interpreter is still a new feature, it is offered as a Beta version.
3. Enable Code Interpreter: Finally, enable Code Interpreter. This can also be done from the ChatGPT settings screen. Once enabled, you will be able to run Python code on ChatGPT.
3. How to use Code Interpreter
Code Interpreter can be used in a variety of ways, such as generating and executing Python code and uploading and downloading files. Specific use cases include data analysis, graph creation, and natural language processing (analysis and generation of text files).
3.1 Data analysis
Python has a rich set of libraries for data analysis. Libraries such as pandas and numpy can be used to aggregate and analyze data. Code Interpreter allows you to perform data analysis directly on ChatGPT.
3.2 Graphing
In order to visually understand the results of data analysis, it is effective to create a graph. Libraries such as matplotlib and seaborn in Python can be used to create many different types of graphs. With Code Interpreter, you can create graphs directly on ChatGPT.
3.3 Natural language processing
Python also has a rich set of libraries for natural language processing. Libraries such as nltk and spaCy can be used to parse and generate text data. With Code Interpreter, you can do natural language processing directly on ChatGPT.
4. Code Interpreter fee
For Code Interpreter fees, please refer to the ChatGPT official website and various resources. Some functions can be used for free, but you need to purchase a paid plan to use all functions.
This is the basic usage of Code Interpreter. Leveraging this greatly expands the possibilities of ChatGPT. Please, try it.
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