In this post, we take a look at How to Import an CSV File in IBM SPSS Statistics. Previously I made a post on How to Import Excel File in IBM SPSS. It was pretty easy tutorial for you to follow and there were plenty of the Excel sample templates that you could use.
So what are we doing in this tutorial? We are going to first find a CSV file which has some sample data. You can find one in the kaggle website. You can also make use of the same with the sample CSV data in the github website. It can be easy to setup and work with as well.
Make sure to download the IBM SPSS and start your trial. You would have 30 or so days enough for you to learn the software and also get your work easily done as well. First thing download and register your IBM ID and then use that at the time of the setup of the software and then get the keys started with the work there.
Check the below video if you prefer the visual instructions for the Importing CSV data to SPSS.
Let's get started with the CSV data in the sample file. You can check out the same in the data science dojo repository of the gitlab. You would find that it has plenty of the data science sample files that you can try.
You can check the repository here. Here you can also find the sample datasets like say titanic. You can check the CSV file here. Just say for the sake of the testing the SPSS we are going to be making use of the CSV file say titanic.
Let's take a look at the steps that you can use for the adding the CSV data into the software.
That's it. Now you would find that SPSS spreadsheet view where you can have the CSV data exactly as you can see in any other spreadsheet. You would also find the same in the excel file format which I already covered and linked to in the earlier tutorial so you have something to read and explore there.
Check out my channel through the video that is linked above. You would find variety of the tutorials that you can make use of for the data science, tools and the cloud too. I am going to be posting entire 2024 in the cloud related content. And I am hoping that this would be a good start for the content to explore those who are working in data science.
I'll see you later in next week and hopefully you would find the value in the tutorial. :)