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We have introduced many chatgpt plug-ins before, interested students can read our historical articles. We also sorted out 45 dry articles in detail in our member group . Today we will introduce an artifact, which can help you analyze excel data in minutes, and perform visual display and data mining . You only need to know how to click the mouse!
1. Install the plugin
Find a plug-in called nodeable in the chatgpt4 plug-in market, and install it directly in the plug-in market.
If you are an expert student or a student who plays data analysis, you will know the introduction of this plug-in. In fact, its underlying principle is to use jupyter notebook to use python to analyze and process data and visualize it. In the past, data analysts with a monthly salary of 10,000 to 20,000 were do this.
2. After clicking Install, you need to synchronize your google account or github account
3. After linking the account, log in to the Noteable website
Everyone is very curious, I use gpt4 to analyze data, why is it so easy to log in to this website ? Because gpt4 cannot upload files, it cannot upload datasets. There used to be a code interpreter that could upload files, but it has been taken off the shelves now! So now only the Noteable plugin can be used!
Here we use the most common Titanic data set for demonstration analysis, and we need to upload this data set to this website. Titanic data set, if you are playing data mining, machine learning students are very familiar with it, it can be regarded as an entry-level helloworld.
It looks like this:
The following are the specific meanings of the fields:
PassengerId: user id
Survival: whether to survive, 0-no, 1-yes
pclass: class, 1-first class, 2-second class, 3-third class
name: name
sex: gender
Age: age
sibsp: Number of siblings/spouses on board
parch: number of parents/children on board
ticket: ticket number
fare: fare
cabin: Cabin number; cabin number
embarked: Embarked location
Generally speaking, we need to explore the relationship between these 10 or so factors, dig out the correlation of these variables, and conduct statistical analysis on the data. This is a job with a high threshold in 3-5 years. Now with gpt4 Xiaobai It can be done, as long as you can type, click the mouse and ask questions.
Upload the dataset to this website:
Click upload to upload your data set, and you will see your data after uploading. The URL in the picture below is very important, because it will be relied on in gpt4 analysis later.
4. Go back to gpt4 and start preparing the analysis data
Open the Noteable you have installed, then paste the URL of your dataset, and start the analysis. For example, enter:
Help me analyze this dataset https://app.noteable.io/p/3ee93768-238a-4138-xxx-daadf5e7d318/My-First-Project
Then gpt4 starts a preliminary analysis, it will tell you a general situation of the data set, and then display the first 5 rows, and tell you some basic statistical information of the data set, such as missing values, dimensions and so on.
5. Start mining data
Analyzing time, the most difficult thing is to mine the data and find the correlation of each dimension, such as the relationship between two variables and three variables. This requires a certain amount of statistical knowledge. Now that you have gpt4, you can be the boss and direct It works.
Next, I'll create some graphs to better understand the data. I'll start by creating the following graph:
age distribution chart
Gender distribution map
Relationship between age and fare
The relationship between age and survival rate
For example, using a histogram to generate an age relationship is a matter of minutes
Then analyze the relationship between age and fare, this is a scatter plot
Or to be more difficult, analyze the relationship between the three variables, and help me analyze the relationship between survivors, cabins, and fares with charts
Due to space limitations, I will not expand them one by one. In fact, you can see the underlying principles clearly when you open this plug-in.
Students who understand Python can tell at a glance that this is data analysis using the pandas library + matplot, but now it is done by fully automatic AI. No wonder some time ago I saw a foreign data analyst with an annual salary of 500,000 was replaced by GPT4 with an annual salary of 20 dollars. The cost difference is really too big! The cost of the machine is one-thousandth of the labor, which is too tempting for the boss.
Maybe it really proves that sentence. In the future, it is not AI that will replace you, but someone who understands AI tools. Interested students can learn it. I hope today’s sharing can help you. We will continue to share useful tools in our member group!
Finally, I would like to recommend our member group. Currently, there are venture capital angel investors, headhunters HR, Douyin big V, emotional bloggers, lawyers, psychological counselors, medical sales, real estate, insurance, piano teachers, operators, business consulting, Students from cross-border e-commerce, construction, data analysts in the Internet industry, back-end development, python testing and other industries will join.
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