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<speak> Now, we will check the correlations for the new data frame.<break strength="x-strong"/> We have created a new data frame diabetes_df_copy.<break strength="x-strong"/> Now let's check the correlation for the newly created data frame diabetes _df,<break strength="x-strong"/> and we are using dot correlation method to plot this heat map,<break strength="x-strong"/> Let's run the cell.<break strength="x-strong"/> Yes, maximum like all these columns have an acceptable correlation with the outcome. <break strength="x-strong"/>It is improved because we have replaced all the N A N values with the means and medians.<break strength="x-strong"/> After cleaning data, correlations improved.<break strength="x-strong"/> So, here we have replaced glucose with the mean. <break strength="x-strong"/> The glucose and the outcome are highly correlated.<break strength="x-strong"/> Now, the correlation is 0.49.<break strength="x-strong"/> Previously correlation is 0.47.<break strength="x-strong"/> Here also, the outcome is well correlated with BMI. <break strength="x-strong"/>Now, The correlation is 0.31. <break strength="x-strong"/>Previously correlation is 0.29.<break strength="x-strong"/> Here also we can see that age the same <break strength="strong"/>because we have not modified anything over there.<break strength="x-strong"/> So after modifying the data frame, <break strength="strong"/>we have a good correlation with them. <break strength="x-strong"/> After modifying the data, <break strength="strong"/>the outcome is well correlated with Blood Pressure. <break strength="x-strong"/> Let's do one thing.<break strength="x-strong"/> Let's check our data frame.<break strength="x-strong"/> Use the head method to see the first five data points.<break strength="x-strong"/> So here, we have glucose, blood pressure, and skin thickness. <break strength="x-strong"/>So these are in 35, these are in 148. <break strength="x-strong"/>All these values are in different ranges. <break strength="x-strong"/>We can observe here. <break strength="x-strong"/> </speak>