correlations correlation helps us understand relationships between different attributes of the data since this focuses on forecastingcorrelations can help us understand and exploit relationships to build better models ##note it is important to understand that correlation does not imply causation we strongly encourage you to explore more on the same the following snippet first prepares correlational matrix using the pandas utility function corr(it then uses heat map to plot the correlation matrix in [ ]corrmatt hour_df[["temp","atemp""humidity","windspeed""casual","registered""total_count"]corr(mask np array(corrmattmask[np tril_indices_from(mask)false sn heatmap(corrmattmask=maskvmax square=true,annot=truefigure - shows the output correlational matrix (heat mapshowing values in the lower triangular form on blue to red gradient (negative to positive correlationfigure - correlational matrix