for any (x,y) if NAN you can impute to average of surrounding pixels as: if((x==0 & y==0): return (x+1)+(y+1))/2 else if(x==x_max & y==y_max): return (x-1)+(y-1))/2 else if(x==0 & y=...

As per business statement it is a exceptional scenario when minimum subsidy will be provided. So for displaying common behavior of data you can drop these exceptional values from table. You can use ...

you can develop simple predictive model like Linear regression to predict price of house given other features value, also analyse the features weight/coefficient and optimize your linear regression ...

Let your data frame be df. First get the numeric columns: num_col = df.select_dtypes('number').columns Then get the remaining columns. non_num_col = set(df.columns) - set(df.select_dtypes('number')....

you have 99 leaf species and 594 test records. Also the output is (594,). Here each value represents corresponding leaf species columns index. check the species data you would have received after One-...

Read about PCA("Principal Component Analysis") and while implementing must standardize data on similar scale.