Hello guys, welcome to this YouTube video. In this video, I will be talking about data analysis using ChatGPT. Nowadays, using large language models such as ChatGPT for natural language processing tasks has become a ubiquitous trend. In today’s video, I will focus on analyzing a sales dataset using ChatGPT4 and show you how you can do that.
But before we delve into the video, I just want to remind you that it takes a lot of time and effort to put these materials together. So, I do appreciate it if you like, share, and subscribe if you find any of the contents of this video useful for your downstream work.
Now, let’s get into the video. As you can see, I’m already on the web page of ChatGPT. Right now, I’m going to change to ChatGPT4 and enable the features we’re going to be using today, such as the code interpreter.
To analyze the sales dataset, I will import the data set just as I would if I were using a pandas data frame. Once the data set is imported, I will provide a prompt to analyze the data set and ChatGPT will give us a summary of what the data set contains. We can see the columns and some basic statistics for the numerical columns.
Interestingly, the product price of $14.95 appears most frequently, about 2201 times. There are also some missing values in the data set, with about 1559 missing values in each column.
Next, I will clean the data set by removing the rows with missing values and converting the quantity ordered and price each columns to numeric data types. Now that the data set is clean, we can perform specific analysis on it.
Let’s find out which products had the best sales of the year. According to the analysis, the MacBook Pro laptop had the most sales, followed by the iPhone and ThinkPad.
Now, let’s find out which month had the most sales. The analysis shows that April had the most sales, with total sales amounting to approximately $3.4 million.
We can also find out which products were commonly sold together. The analysis reveals that the iPhone and the lightning charging cable were commonly sold together, with about 94 orders.
To determine which product sold the most, we can calculate the total quantity sold for each product. The analysis shows that the AAA Battery (full pack) was the product that sold the most, with 2936 units sold.
Now, let’s move on to a more complicated question. What is the probability that a laptop will be ordered next? ChatGPT explains that we can estimate the probability by calculating the proportion of all laptop orders relative to the total number of orders. Based on historical data, there is a fairly low chance that a laptop will be ordered next.
In addition to analyzing the data, ChatGPT also allows us to visualize the data set. We can visualize the sales distribution by hour, which shows that sales start to pick up early in the morning, peak in the late morning to early afternoon, and then see a steady increase again in the evening.
In conclusion, ChatGPT is a powerful tool for data analysis. It allows us to import and clean data sets, perform statistical analysis, answer complex questions, and visualize data. It provides valuable insights into sales data and helps us make informed decisions based on the data.
If you would like to see more videos related to ChatGPT and data analysis, let me know in the comments. Thank you for watching!
