figure - sample rows from bike sharing dataset the data seems to have loaded correctly nextwe need to check what data types pandas has inferred and if any of the attributes require type conversions the following snippet helps us check the data types of all attributes in [ ]hour_df dtypes out[ ]instant int dteday object season int yr int mnth int hr int holiday int weekday int workingday int weathersit int temp float atemp float hum float windspeed float casual int registered int cnt int dtypeobject as mentioned in the documentation for the datasetthere are bike sharing as well as weather attributes available the attribute dteday would require type conversion from object (or string typeto timestamp attributes like seasonholidayweekdayand so on are inferred as integers by pandasand they would require conversion to categoricals for proper understanding before jumping into type casting attributesthe following snippet cleans up the attribute names to make them more understandable and pythonic in [ ]hour_df rename(columns={'instant':'rec_id''dteday':'datetime''holiday':'is_holiday''workingday':'is_workingday''weathersit':'weather_condition''hum':'humidity''mnth':'month''cnt':'total_count''hr':'hour''yr':'year'},inplace=true