Could someone help me with 4.3 please? I don't really understand this one. Thank you!

Below we load tables each containing over 100,000 weekday Uber rides in the Atlanta and Los Angeles metropolitan areas from the Uber Movement project. The sourceid and dstid columns contain codes corresponding to start and end locations of each ride. The hod column contains codes corresponding to the hour of the day the ride took place. The ride time column contains the length of the ride, in minutes. at lanta = Table.read_table("at lanta.csv") los_angeles = Table.read_table("los_angeles.csv") print("At lanta Table") at lanta.show(4) print("Los Angeles_Table") los_angeles.show(4) ... (1048571 rows omitted) Los Angeles Table Question 4.1. Produce a histogram of all ride times in Atlanta using the given bins. equal_bins = np.arange (0,81,2.5) atlanta.hist('ride time', unit = 'minutes', bins = equal_bins) \# Don't delete the following line! plots.ylim( 0,0.046); los_angeles.hist('ride time', unit = 'minutes', bins = equal_bins) \# Don't delete the following line! plots.ylim( 0,0.046); Question 4.3. Assign at lanta_10to15 and los_angeles_10to15 to the percentage of rides that are 1015 minutes long (including 10 but not including 15) in the respective metropolitan areas. Use the height variables provided below in order to compute the percentages. Your solution should only use height variables (heights of the bars of the histograms), numbers, and mathematical operations. You should not access the tables atlanta and os_angeles in any way. at lanta_10to12_half_height =0.02642 los_angeles_10to12_half_height =0.03772 at lanta_12_half_to_15_height =0.03393 los_angeles_12_half_to_15_height =0.04160 at lanta_10to15 = los_angeles_10to15 = round(at lanta_10to15, 2), round ( los_angeles_10to15, 2) Question 4.4. What are difference betweens the two histograms. What might be causing this? Hint: Try thinking about external factors that may be causing the difference