I just want to know, what are your first thoughts on the interactive analysis that you did?

M13  1:53:24  
Yeah. So it was very, I mean, the first person? Yes, yeah. So it was very hard. I mean, easy and user friendly. And you don't have to remember the syntax and the code that we usually do. I mean, in pandas, and usually diamond racism. So the, and the main thing is, whenever you do some mistake, you can have that visibility to go back to the previous state. So yeah, so that was really helpful.

Kiran Gadhave  1:53:58  
And so, you know, this was first time seeing versus Yeah, I basically gave you a small tutorial, you tried like, one, one task? And then you did the actual task notebook? How was the learning curve?

M13  1:54:14  
Yeah, I mean, I don't think you have to put much effort while learning the process. So whenever it's basically just G UI, if you know, the tabs and everything, whether the start phase, then it's very easy to use it. And yeah, that's okay.

Kiran Gadhave  1:54:36  
And you know, for those staying on personal preserve anything that was confusing or hard to understand, or just an entity, you know, in gooeys, this is not how things usually are. So this was weird.

M13  1:54:49  
So I mean, whatever time I have spent so as of now, it's good, but I have to of course, like Cafe spend Over time, then I would get to know the things better.

Kiran Gadhave  1:55:05  
Okay, so now, you know, so far like this next segment will basically go over the high level tasks that did it in both. And I want you to think about for each task, cube use percentage that pandas? Well, first of all, were you thought you were efficient, like, in during the task? But also in general? Do you think that this task, even though if it was efficient with X, I would still prefer why? Because of some reasons. So you know, like, think about from both perspectives. So first of all, like the color manipulation tasks, or renaming, deleting changing categories, so for those kinds of tasks, do you think of both approaches? Yeah.

M13  1:55:45  
So I mean, everything per se was better. But here, you have to write the code and remember the syntax, but there, you can just have your mouse to edit and all. But one thing that I think would be would, the pandas would take over the process would be where you have multiple columns, and you have to edit the values, right? The one value towards everything, they are within a single line of code, you can do that easily. But here, you have to go everywhere, and then manually enter the right.

Kiran Gadhave  1:56:23  
So like, like search and replace all types of things. Yeah. Like, I think like in editors, you can do search and replace. But like it pandas, you can do something similar. Yeah, that is, that is a fair point. So how about the tasks where you had to remove subsets of point, you know, based on either like outliers or like, a range of years?

M13  1:56:47  
Yeah, that was, I mean, that that is very easy are doing in the persist? Because just you have to drag the area where you want to take that point into consideration. And just within two button, you can I didn't consider that or drop that that is easy. In persist.

Kiran Gadhave  1:57:08  
Yeah. And you know, like for those tasks, if you look at the pandas code, for those, it's also pretty much one liner, you just have to do less than or greater than you think about from that perspectives. Would you still use purses for those times? Yeah. Because

M13  1:57:27  
it's usually happen that greater than smaller than equals to that corner cases, you may do mistake while writing code and you have to re correct it, whenever you see the output. But here, you know, that if you select these things, and did it, that part would be omitted.

Kiran Gadhave  1:57:48  
Right? So basically, like, instead of extra step for output, delete, you have the output. Yeah, yeah. But yeah, that's it. Then the last, like the bigger task credit was assigning new categories, so like adding a column and, you know, points between these range of X point between the two in Java. So what about those tasks? Yeah,

M13  1:58:09  
so that is even easy in purses, because I was not able to do in the past. Because you have to I mean, there are multiple steps over here, you have to write first you have to insert quorum, then you have to write a code, I mean, individual code for inserting quorum, then you have to whatever the points you have, right, you have to make a condition. If this match point would be there, then you should choose this category, this match point. So that repeated steps and that the time consuming, but in process, you can you can make the whatever the table structure, column structure, and just then you have to grant the points area and choose whatever category you want to choose.

Kiran Gadhave  1:58:55  
Yeah, actually, so let's go back to so that's the part where that's the only touch just kept, right. Yeah. So for pandas, when you're adding categories, where did you get stuck? So what was like, you know, this is just not working?

M13  1:59:10  
I mean, you get over the road? Yeah, I was getting offers, I was getting the syntax error for adding the column.

Okay, click Close. And I will check. Yeah, so firstly, I was getting the syntax error. I have tried two different syntax to write but I wasn't getting that. And then what why what was my thought was, I have to write three conditions, if the range would be less than 20. They need to consider the range equals to whatever short everywhere and then receive the second condition and then the category would be that yeah, so that was my thought, but it was giving and syntax error. And it was I mean, time consuming, and I have to figure out the syntax while I was getting error, but that is not the case in persist. because, I mean, if you have done some mistake, you can just go back and repeat it, repeat it do from the start, or did you get output? So that's easy for the persist.

Kiran Gadhave  2:00:12  
Yeah. And you know, like, I basically, you know, wanted to know more about just for the coding part. When you so what are like, so I'm assuming, so you do data has read. So you quite frequently look up syntaxes? So where often do you get stuck when you're looking for syntax? Especially something like pandas? Yeah, what are the often, you know, like, you're debugging and then every time I record, you know, every time I have to look this up.

M13  2:00:41  
Yeah. So usually, when you don't be in this track for a long time, it's usually happen that you forget the syntax and everything. Because I in I mean, it's been more than six months, I have not working on these pandas library and everything. So I forget the syntax, right. So that's the way I mean, you have to be in touch. For the pandas, when you have hands on, then it's easy for you to remember the syntax and work on that. And it's usually that it may happen that you get some issues, and you have to search for the Stack Overflow and everything to figure out.

Kiran Gadhave  2:01:18  
And you know, Lorenzo, like, isn't like something, you remember you, when you get stuck like this, I always get stuck here, like the event Stack Overflow, even like, you know, every time I copy this code, it doesn't work, or something like that off top of your head, like what do you think about you know, like with pandas, you search for things, there are always like, five different ways to do that. Yeah. And so you're late. Does that trip you up? Like sometime?

M13  2:01:51  
I mean, it depends. I mean, if you are doing one thing with one way, it might happen, that it won't work. So you always have the alternate solution.

Kiran Gadhave  2:02:03  
So do you do that? Do you switch to the other way? Try to debug the first time. I didn't

M13  2:02:08  
know. I mean, rather than spending time on the debug here, I choose that another way.

Kiran Gadhave  2:02:13  
Okay. And that's where, right? Okay, so now, you know, coming back from comparison. So the one one part of persist was the extension, you can take a data frame, and you know, either make it a table or a chart, attractive one. And the output you get is also another data frame. So the so you know, you could imagine a workflow where you can move between code and interaction. So you know, you start with the table, as you said, you start like, you know, you fix some column names. And then you realize, I have to change this value, but it's there are like, 30 of those values. So you make it. So basically, you get a data frame out with like, your fixed column names, and you write code. Yeah. And then you again, make it into a chart and continue. So what do you think about workflow lighters?

M13  2:03:05  
Yeah, I mean, this is quite good, because I assume that there might be some drawbacks of using purses have not spent much time. Somewhere, this would be having a higher age and D writing the pandas code, but in the combination that would suit better. So, you

Kiran Gadhave  2:03:23  
know, like you basically you got, like, the one of the first big issues with the current version is, of course, if you have to edit like 50 rows. Yeah, you have to like, click 50 times. Yeah, that's obviously going to take probably, it will definitely take more than you are if you have to Google the sentence. Yeah. So yeah, that is said, there are definitely certain tasks, which are hard. Yeah. But you know, like, I think, maybe a search and replace will fix that. So. Yeah. So would you use persist? In general, the data is like, either for coursework or, you know, like, for research or whatever. Yeah, I

M13  2:03:59  
mean, I came to know about this today on the Okay. So, I mean, it's very easy. And I would encourage others, I will tell them that this is the new thing. Okay. And yeah, if, if I get a chance, I will definitely spend more time on this. Okay.

Kiran Gadhave  2:04:15  
Yeah. Then have you used interactive analysis before? Like Tableau or Excel? Yeah. I have used. So how valuable do you find interactive tables and charts compared to you know, standard, we have pandas, where you have to print like, you still get to see the data using charts, but they're not interactive. Yeah. I mean,

M13  2:04:38  
to the one who are not familiar with the CS background with a coding background for them, the way the GI comes, that is more helpful for them. And yeah, even in long term, when you don't remember the code and why because the background is even the code only. Tattoo is even made from some scripts and everything. So you It's easy for them who are not from the CS background. And that is where the UI take over the coding part. Okay. Yeah.

Kiran Gadhave  2:05:09  
Yeah, I think that's pretty much it, in terms of it. So let me turn off the recordings and. Okay.

