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<speak> So that we can know the difference like, <break strength="strong"/>what's the difference now? <break strength="x-strong"/> We have modified glucose, blood pressure.<break strength="x-strong"/> Let's see glucose, how it was before <break strength="weak"/>and how it is now. <break strength="x-strong"/> So, without filling values, we can see that <break strength="weak"/>the glucose 100 for around 210 people. <break strength="x-strong"/> Now, let's see the new plot.<break strength="x-strong"/> Here, we can see that this is the curve. <break strength="x-strong"/>OK, so here we have 160 people around this. <break strength="x-strong"/> In the old plot, <break strength="weak"/>we have 210 people.<break strength="x-strong"/> And in the new plot, <break strength="weak"/>we have 160 people.<break strength="x-strong"/> Before, we had 120 glucose for around 160 people.<break strength="x-strong"/> Here it is 120 for around 120 people.<break strength="x-strong"/> But now <break strength="weak"/>we have 160 people with the same glucose. <break strength="x-strong"/> As we have modified the data frame, <break strength="weak"/>the distribution has changed.<break strength="x-strong"/> We have modified the data set. <break strength="x-strong"/>We have removed all NAN values.<break strength="x-strong"/> All the plots have changed. <break strength="x-strong"/> We did not modify some columns. <break strength="x-strong"/>We did not change the pregnancies column.<break strength="x-strong"/> So no change in the pregnancies plot.<break strength="x-strong"/> The outcome column histogram is also the same. <break strength="x-strong"/> </speak>