Hi in this video clip, let me explain how to use drawing functions provided by Matt Platt Lee for Panda State of Fame. You can use plotting functions agent method for presenting data frame valuables. It is very easy. So that's the strength of using Pandas data frame. But as I'm going to explain soon, it is better to use sns see bone instead of a map plot left. If you want to show data graphically from Pandas. So here's a line graph. I'm using irish data set, in order to add greed, greed equal true. And PST show is quite simple, right? And what do you see, yes. Wow is that simple. Wow, you don't need to specify what is legend. Then this plot method naturally take variable lame and you see it as a legend and attach it. It such is a good place and place. And definitely you can control the location of the legend and the size of the fund. But initially, if your purpose is to see the patterns from the data, then you simply use this function as a method and you are adding that method to data set. That simply you get the whole picture of the data. So what the top most one line is disciple length and the orange one is simple width. And the green one is pedal length and the bottom line is pedal rest. As you see here there's a pattern among three kinds. The 1st 50s Sentosa, Postcola and Veronica. From this one what do you see, the flower size of Veronika overall is larger than the size of Sentosa and Postcola. And also if you want to separate iris flour into civic groups. What variable you need to use because if you use green and orange, what happens? There's overlapping areas. So not easy to separate or kind from the other. But what about if you use not overlapping data in that case it is Egypt classify or iris flour into one of three groups. You can apply histogram and so kind you are using plot. The function is always plot. You specify what kind of plan hissed in the previous case. Here, you didn't specify kind because you are choosing a line graph. It is default, that's why you are now specifying kind. But you specify kind here histogram. Choosing histogram then and beans number is 40 then what you see is this one. So four kinds of variable information yes, presented and or at this time not overlapping. If overlapping it is added, not hiding behind another variable. So it is easy to read how the overlapping happens. So this is a kind of fancy and very informative presentation of data variables. Another box plot simply box and seem BO means that you want to see eliars also if there are eliars and also we use the show means true. That's why I mean values are presented and this is what we have seen already. And wow, it's so easy to see through figures from data frame. Another you simplify scatter, use scatter parameter to specify kind. And at this time scatter plot, you need to choose a variable paddle lens and paddle west. And you draw then this is what we have seen. But at this time because you are not allocating different colors for different kinds. So all three kinds have the same color. But as we already know this is the Sentosa and Veronika. No Postcola and top right Veronika. The other case at this time we are creating student. This is what we already have used. And at this time we are sorting before drawing. So sorting values. So depending on these values, the list labors will be sorted and we are applying bar chart, horizontal bar chart. And then what happens this way? Nicely sorted. So depending on the value, it is sorted, that's why the index is not sequential. So the fourth year, third year, first year, second year, what about you want to sort following index. In that case you simply change sort on the bar and then index instead of values. Then what happens first year, second year, third year, fourth year. It simply follows index. Index zero, one, two, three. That's why following index number, it is sorted and this presentation is what we have done already. So you can apply at the function before plotting. Now you can also drop I chat and let's show you the outcome first. Then this is the pie chart applied to the above data set and kind is pi student data set. This is here. Pandas data series and Platt function is applied to the cities and kindness pie and other parameter values. Our Children here, I already explained those parliament values. That's why I'm not explaining. But here PLTY label long because if you make it don't want what happens is that, none? This one, wide label is not provided which is printed here. That's why in order to remove that unnecessary information you and pierre de that wide label long, then it disappears. So if you use Platt function as your method in order to quickly and easily present data frame very worse you can do so. So this is a kind of well, strengths or python programming language. Before clothing let me give you leave your question through all for us, it is easy to find various graphical parents from data frame variables by applying Platt function. This is what I just explained, the sound answer is true.
