Kiran Gadhave  23:55  
Okay. Okay. Okay, so we have a few questions. So Well, firstly, you know, like very general, what you wrote, what were your first thoughts on the interactive? Analysis security?

M4  24:10  
I thought it was a, it made it a lot easier for sure. Like, yeah, it was a lot easier to like, make categories and just just edit the table in general. Sometimes it was like a little bit like, slow, which was a little bit annoying, but overall, it was really good.

Kiran Gadhave  24:35  
And so you, basically, so I did a small tutorial, you tried it out, like for one take for writing it categories. And then you essentially just did the entire notebook. So how was the learning curve between the you know, you'll never having seen this before, but using it for the tasks?

M4  24:55  
Yeah, I didn't really I didn't have that much struggle, like picking up on it like Just a short tutorial.

Kiran Gadhave  25:01  
And anything that was confusing, hard to understand or you know, an intuitive like, this is not usually what you expect.

M4  25:13  
Oh, no, nothing that I can really think of that was all very intuitive. Okay.

Kiran Gadhave  25:21  
So now basically, I have a few questions, we'll go over, like the top level tasks. And I want you to think about what was your experience during that particular task in both notebooks. And, you know, think about in terms of what felt efficient or felt intuitive. So for like, the first type of tasks we did for manipulating the columns, or renaming, deleting, or changing the data types. So just, you know, what do you think about doing these talks in big bold notebooks different ways?

M4  25:57  
Okay. So let's see, with the persist module is definitely a lot easier, like, you know, just like, click on the column name, and just like change it, you know, get rid of the call, which is a lot easier than with pandas. Like typing it all out, and like, you know, getting the syntax all perfect.

Kiran Gadhave  26:28  
And how about when you had to, you know, change some values, like find some, some, you know, find some data that there was extra something or remove it, for example, in the first one, you had to find the like, with P and for this, you think hard numbers, which are like inches. So, hello, those two tasks.

M4  26:50  
Yeah. So, with persist? It's definitely really easy. You just like, search for it, and find it. Yeah, just like came right up. And I could just click on it and edit it. And then, yeah, with pandas, it was a lot. A lot more tricky. I definitely have to, like, look some stuff up on how to do it. And yeah.

Kiran Gadhave  27:13  
So next is, you know, tasks where you had to basically remove parts of the data. So you know, remove, liquid insert, arrange or remove, like old data. Yeah.

M4  27:28  
Yeah, once again, a lot a lot more tricky with pandas. I was like, looking stuff up to figure out how to do that. But with persist, it was really easy to just like, select it, and then just remove it. I remember, I couldn't remember what button it was, but like, it only took me like one second to find it. Yeah.

Kiran Gadhave  27:50  
Okay. And I think the last toss was, I mean, the last was we're just looking at the chart. But before that was the assigning categories, one, so get to create new categories. And I think for the first one, you have to create land for second one as you get another season. So how was God like? Well, support the first tool book, you didn't complete that task. Skip it. So where did you get started?

M4  28:21  
Um, yeah, I was just having a hard time. Just like creating the column, it just kept giving me errors. I don't know, I was probably doing something a little bit wrong. But and

Kiran Gadhave  28:37  
you know, house in general, your experience? Well, so since you say you say you are learning pandas and Python, as a hobby. And at this point, I'm presuming like, at some point, you will, you know, maybe go in data science or machine learning and maybe use it professionalism. What's your gripe or what? So what sort of problems to face searching through documentation for like pandas?

M4  29:04  
Yeah. It's definitely tricky, because like, there's like a lot of information that you can look through. But sometimes it's hard to find like, specifically what you're trying to do, you know, have

Kiran Gadhave  29:18  
you tried using tools like Chad ship ETL stuff to basically just ask it to give you code for this? Um,

M4  29:25  
yeah, but I'm like, there's like the generative AI on Google. And that can be helpful, but sometimes it doesn't get it quite right. Yeah.

Kiran Gadhave  29:33  
Yep. Yeah, that's definitely true. Okay. So again, the back to talking about the tool. So, have you been interactive analysis before? Like, using something like Tableau?

M4  29:49  
Yeah, like, I do stuff on Excel.

Kiran Gadhave  29:52  
So how was your so how's your experience, you know, for example, if you have to Do something with Excel and then you find, you know that you realize I can't do a particular thing in Excel and you need to read some Python code. So what's your workflow? Like? How do you go from Excel to like a notebook?

M4  30:21  
Don't know that I do that too much. But,

Kiran Gadhave  30:23  
but I mean, I mean, hypothetically how to going

M4  30:27  
from Excel to know it? Well, I guess all you'd have to you could like load the Excel file onto. Yeah, yeah.

Kiran Gadhave  30:35  
So what are your thoughts on something that persist? Where you can like, interact your analysis in the notebook? And you can create a data frame and just write Python code right there? Instead of having to go through a

M4  30:51  
file? Right? Yeah, no, that's a lot more convenient than having to, like, load the file on, and then make changes. And then you know, like, get the file, like, a lot more steps than just having the interactive thing, or it's basically like Excel, but it's like, embedded in and you can, you know, code and you can do the interactive things. Yeah. You

Kiran Gadhave  31:12  
use the extension for your work. Will you use the extension? Your Future? Oh, yeah. Yeah,

M4  31:21  
I think it's definitely really convenient.

Kiran Gadhave  31:24  
And so. So my last question is, so you work with Excel, but you haven't worked with Tableau. Right. So how was so did you find this interactive table and interactive charts in general, useful for the analysis? Yeah. Compared to, you know, usually with pandas, as you print static charts, look at it and go to something. So compared to that experience,

M4  31:52  
yeah, compared to that, yeah, it's definitely a lot more, a lot more useful.
