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<speak> So now, let's create a plot to check null values. <break strength="x-strong"/> Here we can see that <break strength="weak"/>we don't have any null values in any of the columns. <break strength="x-strong"/> Now<break strength="weak"/> let's create a plot to check our outcome. <break strength="x-strong"/> The outcome column gives<break strength="weak"/> information about patients having diabetes or not.<break strength="x-strong"/> Let's create a color wheel. <break strength="x-strong"/> Here, we are taking diabetes_df data frame. <break strength="x-strong"/>This data frame is our old data frame.<break strength="x-strong"/> We are taking the outcome column. <break strength="x-strong"/> We are mapping with this color wheel.<break strength="x-strong"/> We are taking value counts of this outcome.<break strength="x-strong"/> What is the value_counts function?<break strength="x-strong"/> values_count function returns object containing counts of unique values.<break strength="x-strong"/> We are drawing the plot of value count.<break strength="x-strong"/> Let's run the cell.<break strength="x-strong"/> So here, we can say that around 268 people have one.<break strength="x-strong"/> So 268 people have diabetes.<break strength="x-strong"/> Five hundred people don't have diabetes. <break strength="x-strong"/> </speak>