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Question

python find the maximum amount of rainfall on days where the maximum temperature was above 35...

python

find the maximum amount of rainfall on days where the maximum temperature was above 35 degrees Celsius. This time, should incoporate pandas in program. Provided dataset is a file called climate_data_2017.csv. The maximum temperature record is in the third column (index 2) and the rainfall is in the fourth column (index 3).

Result: Maximum amount of rainfall on hot days: 3.8 mm

data file:

Date,Minimum temperature (C),Maximum temperature (C),Rainfall (mm),Evaporation (mm),Sunshine (hours),Direction of maximum wind gust,Speed of maximum wind gust (km/h),9am Temperature (C),9am relative humidity (%),3pm Temperature (C),3pm relative humidity (%
2017-01-13,23,30.5,0,8.6,8.9,SSW,52,24.6,68,29,57
2017-01-14,24.6,32.5,0,10.6,7.1,ESE,35,28.7,59,29.2,52
2017-01-15,22.8,27,0,8,6.9,ESE,33,25.6,56,25.5,57
2017-01-16,21.7,27.2,0,7.2,12.1,NE,52,26.2,55,26.3,57
2017-01-17,20.8,36.6,0,10.4,11.9,NNE,50,25.3,64,32.6,44
2017-01-18,25.1,38.1,0,13.8,11.1,SSE,59,36.5,26,30.1,52
2017-01-19,20.1,24.5,0,12.6,0,ENE,41,21.5,61,22.7,53
2017-01-20,19,29.2,0,5.8,2.6,SSW,65,24.1,62,28.3,68
2017-01-21,20.8,27.4,7.8,6.2,9.7,SSE,48,22.2,49,26.6,42
2017-01-22,20.4,26.5,0,9.1,10.7,ENE,39,23.8,50,26,50
2017-01-23,21.5,32.6,0,9.6,12.1,NE,56,25.5,60,28.6,51
2017-01-24,24.5,37,0,12,2.6,SSW,69,32.6,34,35,33
2017-01-29,22.3,30.2,0,11.4,6.8,S,31,24.5,74,28.9,56
2017-01-30,23.1,34.3,0,6,12,NNE,56,27.9,67,30.3,54
2017-02-05,25.8,34.9,0,9.6,7,NW,41,29.5,50,34.1,41
2017-02-06,26.2,34.7,0,11.8,10.9,S,48,29.6,55,33.9,44
2017-02-07,22.1,24.9,6.4,8.2,1.3,,,22.2,88,21,89
2017-02-12,24.5,31.9,0,10.4,7.8,SSE,59,28.1,67,28.1,59
2017-02-13,17.8,27.3,0,7,12.8,SW,37,21.9,29,26.9,32
2017-02-14,21.6,24,0,9,1.9,SSE,44,22.3,68,21.2,73
2017-02-15,18,26.1,25.6,1.2,10.1,ENE,37,21.3,66,26.1,52
2017-02-16,19.5,30,0,8,11.1,NNE,54,23.4,63,28.8,51
2017-02-17,22.6,29.9,0,11.2,6.6,N,70,26.6,66,26.8,59
2017-02-18,21.8,29.4,8,5.4,7,SE,41,22.9,79,28.8,58
2017-02-19,18.6,26.1,3.2,6.4,7.9,S,48,19.7,69,25,48
2017-02-20,17.5,28.3,0.6,8,12.5,WSW,63,19.9,32,27.5,18
2017-02-21,16.9,27.6,0,10.4,11.7,NNE,33,19.4,41,26.3,36
2017-02-22,19.3,27.7,0,7,12.2,NE,48,25.8,50,26.2,47
2017-02-23,21.6,28.1,0,11.6,11.5,NNE,46,25.4,55,27.3,52
2017-02-24,21.8,28,0,10.6,5.7,S,31,24.5,69,27.3,56
2017-02-25,18.6,20.8,7.8,4.4,0,SSW,44,18.7,89,19,87
2017-02-26,18.3,25.5,28.6,5.8,5.3,S,48,20.7,67,24.3,54
2017-02-27,18.7,26.6,26.4,7.6,7.5,ESE,44,23.3,60,25.6,47
2017-02-28,20.7,26.7,2.6,5.6,9.2,ESE,48,25.1,63,26.4,61
2017-03-01,20.6,27.2,26.4,7.2,2.2,E,43,21.4,87,25,67
2017-03-02,20.5,26.3,3.2,3.6,7.6,E,26,23,81,25,69
2017-03-03,20.7,24.8,37.8,5.2,1.4,SE,63,21.7,89,22.2,85
2017-03-04,19.9,23.3,27.6,4,0.2,SSE,54,21.5,87,20.9,86
2017-03-05,20.1,23,7.6,2.4,0,SW,56,20.4,78,22.1,76
2017-03-06,19.6,25.7,2.4,4,7.7,SSW,65,20.5,63,25.5,49
2017-03-07,18.8,23.2,0,9.4,3.6,SSE,54,19.3,73,21.7,62
2017-03-08,16.9,23.5,5,8.8,1.4,SE,46,19.9,67,22,56
2017-03-09,17.9,25.1,1,5.4,2.7,SSE,43,20.3,69,23.3,54
2017-03-10,17.3,25.8,0.6,5.4,7.4,SSE,44,19.3,73,25.1,51
2017-03-11,16.9,26.1,0.2,5,10.7,SSE,31,20.1,61,25.5,47
2017-03-12,17.4,26.4,0,7.2,10.6,NNE,46,22.3,62,26,50
2017-03-13,22.2,27.4,0,7.2,6.2,E,56,23.7,68,27,63
2017-03-14,22.6,25.9,0.4,7.6,0.5,E,44,23.9,71,21.4,67
2017-03-15,19.8,25.9,38,,5.5,E,54,22.9,76,24.8,67
2017-03-16,21.9,24.9,2.6,7.6,1,ENE,56,23.1,84,24.5,85
2017-03-17,20,22.7,20,3,1.3,S,59,20.3,83,20.5,81
2017-03-18,19.3,25.8,45.8,2.8,3.6,SSE,65,21.8,88,24.1,79
2017-03-19,21.6,26.2,4.2,,5.5,ESE,57,23.7,86,25.3,76
2017-03-20,23.7,27.9,0.2,8.4,4.4,NNE,39,25.8,74,26.9,66
2017-03-21,23.3,27.1,0,5.2,1.5,NNE,30,24.5,77,26,72
2017-03-22,22.3,31.9,25.6,6,4.4,WSW,63,23.9,82,29.8,57
2017-03-29,21.4,28.8,0,2.4,8.4,E,30,22.5,84,27,71
2017-03-30,22.5,26,2.4,7.4,0,SSW,69,25.2,70,19.2,88
2017-03-31,15.3,22.6,42.4,,9.9,SW,54,16.9,56,21.6,53
2017-04-01,14.5,25.6,0,,10.7,SSE,35,17.1,63,22.5,48
2017-04-02,17,22,0,,5.8,SSE,50,19.8,66,20.1,59
2017-04-03,14.8,22,33.8,4.2,1.5,SSE,50,15.7,90,21.8,49
2017-04-04,14.9,22.8,7.8,0.4,6.4,SE,41,17.9,78,20.7,60
2017-04-05,14.1,23.3,0.4,5.4,10.2,ESE,37,18.1,72,22.9,45
2017-04-06,13.2,23.4,0.2,6,8.7,ESE,24,17.1,69,23.2,42
2017-04-07,14.1,23.8,0,3.4,10.6,ENE,28,18.7,69,23.7,41
2017-04-08,14.9,24.9,0,5,9.8,ENE,37,18.4,68,23.1,49
2017-04-09,15.5,28.7,0,7,9.6,WNW,67,20.1,62,27.9,35
2017-04-10,11.7,17.9,8.8,7.8,6.1,W,54,13.9,51,15.7,56
2017-04-11,13.8,23,0,3.6,2.1,SSW,54,17.9,56,22.2,48
2017-04-21,14.4,23.9,0,4,7.2,ENE,26,17.9,68,22.4,58
2017-04-22,17.7,24.1,0,4.2,3.5,N,19,19.9,68,22.5,60
2017-04-23,15.9,26.7,0,3.6,9.5,E,22,18.5,74,23.6,58
2017-04-24,15.7,23.9,0,3,10,NNE,24,18.2,74,22.7,61
2017-04-25,18.2,26.7,0,4.4,3,NW,39,20.6,69,21.9,65
2017-04-26,16.9,24.8,1.8,4.6,7.9,WSW,67,20.2,55,18.1,43
2017-04-27,12.1,20,0.4,7,8.2,S,46,13.1,46,18.5,45
2017-04-28,10.2,21.8,0,5,10.4,SW,44,13.5,51,20.1,39
2017-04-29,10.8,22.7,0,3.6,10.5,W,31,14,60,21.2,51
2017-04-30,14,22.6,0,3,7.8,SSE,28,17.2,66,20.5,59
2017-05-01,13.2,25.6,0,4,9.5,NNW,30,15.9,78,24.2,40
2017-05-02,14.6,23.9,0,5,8.4,SSW,39,17.2,65,23.2,33
2017-05-03,14.9,18.4,1.4,5,3.4,S,43,16.9,61,16.3,67
2017-05-04,11.8,20,3.8,3.8,3.3,W,24,14.7,78,19.5,45
2017-05-05,12.7,21.6,0.4,2.4,8.5,E,26,15.1,74,20.5,54
2017-05-06,12.7,26.2,0,4,8.4,NNW,43,14.8,77,25.2,39
2017-05-07,14.6,22.2,0.2,4,10,W,50,17.2,47,21.1,25
2017-05-08,10.2,20.1,0,,9.9,SSW,33,12.2,49,18.9,41
2017-05-09,10.7,21,0,9.6,7.5,SSE,31,13.3,67,19.8,45
2017-05-10,10.5,21.7,0,3.4,10,W,37,13.3,70,20.3,52
2017-05-11,10.9,22.1,0,2,8.5,W,30,13.4,73,19.7,56
2017-05-12,12.5,19.6,0.4,2.6,1.7,WNW,26,14.1,78,18.5,71
2017-05-13,14,21.3,3.2,0.6,7.3,ENE,28,15.8,86,20.1,67
2017-05-14,14.7,18.7,0,4,0.3,ESE,26,16.3,89,18.1,74
2017-05-15,13.1,20.8,5.2,1.6,5.5,SSW,43,14.6,75,20.2,49
2017-05-16,11.1,21.9,0,3,9.9,W,33,14.4,59,20.3,39
2017-05-17,9.8,20.2,0,3.4,9.5,W,28,12.7,72,19.6,52
2017-05-18,12.6,21.5,0,3.6,6.4,E,33,14.8,79,20.2,62
2017-05-19,14.8,20.4,0,1.4,0.5,NNE,43,19.5,78,20.2,72
2017-05-20,16.7,23.2,14.6,1,5.4,NE,35,17.5,86,22.8,58
2017-05-21,13.8,23.5,0,4,9.2,W,30,15.7,69,21.9,49
2017-05-22,13,21,0,1,6.9,W,22,14.7,84,20.1,65
2017-05-23,14.7,22.6,0,2.4,8.8,ENE,24,16.6,82,22.4,65
2017-05-24,14.8,22.7,0.8,3.4,9,WSW,54,16.7,77,22.5,31
2017-05-25,11.6,21.4,0,5.6,9.6,WSW,33,14,60,19.7,43
2017-05-26,10.6,20.8,0,1.8,9.8,W,30,14,58,19.6,56
2017-05-27,12.6,20.6,0,2.8,7,W,24,14.2,77,19.4,65
2017-05-28,11.9,23.7,0,2.4,8.4,NNW,48,13.3,83,23.2,37
2017-07-19,10.6,17.5,0,6.6,9.1,WSW,57,12,53,16.9,33
2017-07-20,9.3,17.5,0,4.4,9.6,WSW,63,11.4,55,15.8,26
2017-07-21,7.5,18,0,4.2,9.2,W,46,9.6,53,17.4,37
2017-07-22,6,19.1,0,3.6,9.8,W,31,7.9,64,18.7,27
2017-07-23,6.5,22.1,0,3.6,9.9,NW,44,10.8,49,22.1,22
2017-07-24,10,21.3,0,7.2,9.6,WSW,31,12.7,51,20.9,24
2017-07-25,7.9,20.6,0,4.2,9.9,NW,30,11,63,19.7,32
2017-07-26,11,21.3,0,2.8,9.9,W,70,18,39,20.2,27
2017-07-27,9.1,17.5,0,4.8,9.7,W,31,11.2,61,17.1,44
2017-07-28,11.2,19.1,0,4.2,8.3,WSW,67,13.1,51,18.9,25
2017-07-29,8.2,21.2,0,4.6,9.9,W,31,10.7,52,20.9,23
2017-07-30,10.7,26.5,0,6,6.2,NNW,44,18.4,25,24.8,22
2017-07-31,15.6,16.5,0,4.4,0,WSW,56,15.7,72,11.8,85
2017-08-01,8.6,18.1,6,2.4,9.8,SW,39,11.6,57,16.9,39
2017-08-02,7.2,18.2,0,3.2,8.8,S,41,9.6,62,16.8,51
2017-08-03,8.9,17.4,3,2.8,5.5,NNE,37,10.3,85,16.4,70
2017-08-04,10.3,17.3,13.8,1.8,10.2,W,50,12.8,60,16.6,41
2017-08-05,9.6,19.9,0,5.6,10.1,WNW,48,14,46,19.3,22
2017-08-06,12.1,21.3,0,6.8,9.9,NW,54,15,46,20.9,26
2017-08-07,13.5,18.4,0,6.8,9.8,W,63,14.7,44,16.9,25
2017-08-08,9.7,19.3,0,7.2,10.3,WSW,54,12.1,45,18.5,24
2017-08-09,9.2,20.9,0,5,10.4,W,33,12,53,20,32
2017-08-10,9.2,24.2,0,4,9.4,NNW,31,11.8,64,23.5,24
2017-08-11,11.8,25.9,0,7.6,7.9,WSW,37,20.7,24,25.2,23
2017-08-12,9.6,21.4,0,6.2,6.9,WSW,44,13.5,43,20.7,27
2017-08-13,10.2,20.6,0,3.2,10.1,WSW,33,13.2,54,18.5,43
2017-08-14,8.5,23.1,0,3.8,10,W,24,10.9,71,23,24
2017-08-15,10.7,22.4,0,4.8,3,W,35,12.8,57,20.1,44
2017-08-16,12.8,21.8,0,6,9.6,W,74,20.5,42,20.5,28
2017-08-17,11.3,22.4,0,7.2,10.5,WNW,54,15.7,42,22,20
2017-08-18,11.4,16.9,0,8.4,10.6,W,93,13.6,41,16,28
2017-08-19,8.7,16.5,0,6.4,10.4,S,63,11.1,41,16.2,33
2017-08-20,6.4,16.2,0.2,5.4,9.1,W,41,9.8,44,15,53
2017-08-21,8.3,17.7,0,3.4,2,W,30,11.7,66,15.9,48
2017-08-22,8.7,20.2,0,1.4,10.6,W,22,11.8,61,18.2,37
2017-08-23,8.3,19.9,0,3.8,10.6,NNE,31,12.1,64,18.6,60
2017-08-24,11.2,18,0,4,7.8,SSW,54,13.6,46,17.1,49
2017-08-25,9.6,17.9,0,5.2,9.4,SSW,48,12.7,55,16.5,51
2017-08-26,7.7,20.4,0,3.8,10.3,W,30,11.1,66,17.3,44
2017-08-27,8.6,19.5,0,4,8.4,SSW,57,12.8,44,19.3,27
2017-08-28,7.6,16.3,1.2,5.4,7.6,SW,59,10.9,54,15.3,43
2017-08-29,7.5,16.7,0,4,7,W,30,10.6,62,16,46
2017-08-30,8.4,19,0,3.8,10.6,SSW,48,11.9,44,17.7,35
2017-08-31,7.8,17.7,0,5.6,7.7,SSE,56,11.7,43,14.6,52
2017-09-01,8.2,19.2,0,3.4,9.8,W,33,12.2,52,17.7,44
2017-09-02,7.8,19.4,0,4.8,10.8,W,24,11.8,69,17.5,49
2017-09-03,10,27.2,0,5,7.3,NW,48,15.3,55,26.6,16
2017-09-04,12,22.2,0,7.6,10.7,WNW,56,16,35,21.7,22
2017-09-05,11.4,18.7,0,10.4,10.8,W,61,14.7,31,18.2,22
2017-09-06,11.5,19.9,0,8,10.6,WNW,59,14.6,31,19,21
2017-09-07,10,21.9,0,7,10.6,W,50,15.7,38,21.5,21
2017-09-08,11.1,20.4,0,5.6,10.8,W,65,16,39,19.9,22
2017-09-09,9.6,19.4,0,8,10.8,WSW,44,13.1,37,17.7,31
2017-09-10,8,19.1,0,5,10.8,W,24,13.5,52,17.3,51
2017-09-11,8.7,22.7,0,3.8,10.1,NE,24,14.4,60,22.5,29
2017-09-12,11.3,27.2,0,5.8,2.3,E,26,18.2,43,23.4,34
2017-09-13,18.2,33.8,0,6.2,9.6,NNW,70,24.9,19,32.5,10
2017-09-14,12,17.3,0.2,13,10.5,WSW,72,13.8,37,16.4,26
2017-09-15,10.5,22.8,0,7.8,10.6,W,52,16.6,37,22.2,24
2017-09-16,12.5,24.2,0,7,6.4,SSW,56,17.3,43,21.3,22
2017-09-17,8.1,18.6,0,4.6,10.8,ESE,28,13.6,48,16.4,37
2017-09-18,8.2,21,0,5.6,10.7,NE,39,14,55,20.2,55
2017-09-19,14,25.2,0,6.4,10.8,SSW,54,20.4,30,23.1,16
2017-09-20,10.7,19,0,9.2,7.7,WSW,33,14.6,44,17.7,56
2017-09-21,10.4,21.3,0,3.8,10.1,NE,30,15.6,65,21.2,49
2017-09-22,12.8,27.7,0,7.2,10.5,NNE,35,20.1,35,25.8,26
2017-09-23,15.5,32.2,0,8.6,5.7,NNE,50,23,25,29.1,25
2017-09-24,23,29.2,0,12,6.5,W,54,27.1,20,27.8,15
2017-09-25,16,26.7,0,10.8,10.8,WNW,57,22.3,21,23.3,19
2017-09-26,12.3,22.2,0,9.6,11,WSW,41,19.5,29,19,47
2017-09-27,15.4,22.7,0,6.6,8.2,ENE,50,18.1,58,21.1,62
2017-09-28,18,25.7,0,6.2,3.8,WNW,59,22.7,47,24.1,26
2017-09-29,13,26.9,0,6.8,11.1,W,39,20.4,36,26.8,20
2017-09-30,16.3,24.1,0,9.2,0.7,WSW,59,18.8,30,23.5,15
2017-10-01,11.2,23.1,0,6,10.6,W,31,15.4,65,19.3,36
2017-10-02,12,22.9,0,6.2,10.1,NE,44,16.7,55,21.3,60
2017-10-03,16.7,22.1,0,7,5.4,NNE,39,18.9,69,20.1,65
2017-10-04,15.6,23.8,0,3.6,8.7,SE,30,20.4,72,22.1,58
2017-10-05,16.5,23.4,0,5,9.6,NNE,41,19.5,73,22.6,64
2017-10-06,18,22.1,0,6.6,4.7,SSW,39,18.9,66,20.3,46
2017-10-07,13.7,22,0,6.2,8.7,SSW,43,16.2,52,21.1,46
2017-10-08,13,21.4,0,4.8,2.3,ENE,31,16.6,70,19.6,64
2017-10-09,16.6,30,0,2.6,8.3,S,48,20.1,74,27.5,45
2017-10-10,16.1,21.3,0,8,4.7,ENE,39,19,62,20.5,59
2017-10-11,18,23.2,0,5.6,3.8,NNE,48,19.3,86,22.6,75
2017-10-12,19.2,29.6,0,3.6,9.6,SW,46,23.2,61,27.3,30
2017-10-13,14.7,23.2,0,7.2,10.5,NE,46,18.4,69,22.7,55
2017-10-14,17.1,22.3,0,7.6,0,S,54,18.7,63,18.2,61
2017-10-15,16,22.4,0,3.8,2.4,ESE,28,22.3,52,20.1,58
2017-10-16,15.9,23.3,0,5,10.4,E,30,22.4,55,22.3,50
2017-10-17,16.9,23.5,0,7.6,9.9,ENE,39,21.2,57,22.9,47
2017-10-18,18.8,23.2,0,9,10.4,NNE,50,20.9,64,22.5,56
2017-10-19,17.1,25.3,0,10,11.4,NNE,52,22.1,52,24.6,47
2017-10-20,19,19.6,7.8,9.2,0,S,56,19.6,87,15.3,85
2017-10-21,13,20,16.4,4.4,11.3,SSW,50,16.8,52,18.9,53
2017-10-22,13.4,21.7,0.2,4.8,5.5,ESE,30,16,75,18.7,60
2017-10-23,12.7,23,3.4,3.6,12.1,S,31,18,60,22.1,43
2017-10-24,13.9,24.3,0,6.8,10.5,NE,39,19.9,57,22.6,55
2017-10-25,18,26.9,0,8,5,S,59,21,67,23.3,56
2017-10-26,17.2,24.6,0.4,7,6.5,WSW,63,19.7,73,22.6,63
2017-10-27,14.8,24.2,34.2,7.2,3.9,WSW,61,18.1,85,22.3,65
2017-10-28,17.5,25.1,0.2,3.2,7.7,ENE,35,21.6,66,22.3,65
2017-10-29,20.2,29.6,0.2,4.6,10.6,NNE,39,24.4,49,27.7,35
2017-10-30,20.3,35.4,0,11.4,9.3,SSW,69,28.5,37,34.9,13
2017-10-31,13,20.5,0,12,10.1,SSE,57,15.8,43,19.7,36
2017-11-01,13,22.2,0,9.6,4.2,SSW,54,15.4,39,21,32
2017-11-02,15.3,22.6,0,5.6,9.9,ESE,31,20.1,56,21.8,46
2017-11-03,16.9,26.9,0,6.6,5.9,SSW,57,20.6,58,25.7,48
2017-11-04,16.2,17.1,1.6,7.4,0,SSE,39,17,73,15.8,78
2017-11-05,14.1,19.5,31.8,2.6,0,ENE,39,14.9,85,17.7,59
2017-11-06,14.8,26.3,4.4,1.8,5.7,SSW,67,19.4,81,23.6,57
2017-11-24,18.2,25.9,0,10.8,9.3,NE,41,23.4,59,24.5,54
2017-11-25,18.9,26.4,0,8,12.6,ENE,35,23.8,59,24.3,62
2017-11-26,19.3,26.8,0,8.4,10.1,NE,48,24.4,65,24.8,64
2017-11-27,20.6,25.1,0,8.6,1.9,ENE,39,23.7,66,24.5,65
2017-11-28,19.3,27.7,0,5.8,11.1,SE,35,25.1,64,26.9,59
2017-11-29,20.6,26.4,0.8,,7.7,E,26,22.8,78,25.8,64
2017-11-30,20.2,26.7,1.8,10.8,10.9,ENE,48,24.4,66,25.9,62
2017-12-01,20.1,27.5,0.2,8.6,11.3,NE,59,25.4,62,26.6,57
2017-12-02,19.7,26.8,0,11,1.3,WNW,72,22.9,72,24.6,62
2017-12-03,16.9,29.2,10.8,0.6,13.5,E,37,22.1,45,23.7,50
2017-12-04,16.1,18.6,3,10,0.4,SSW,52,16.8,79,17.1,81
2017-12-05,16,25.3,7.6,0.6,5.9,SSW,63,18.4,71,23.8,54
2017-12-06,18.2,26,0.2,10.2,5.7,SW,44,19.8,59,19.3,68
2017-12-07,17.5,31.3,5.8,6.4,12.6,NE,43,25.2,39,28.3,32
2017-12-08,21.4,27.7,0,12.8,8.9,SE,50,22.8,44,23.7,52
2017-12-09,18.1,24.1,0,8,7.9,SSE,35,21.4,52,22.6,46
2017-12-10,17.3,24.8,0,7.4,12.7,ENE,39,23,54,24.2,50
2017-12-11,18,26.5,0,10.4,13.1,ENE,43,24,49,25.8,47
2017-12-12,20.3,27,0,10.2,12.2,ENE,41,25.2,56,25.2,57
2017-12-13,19.3,28,0,10,13,NNE,56,24.7,59,28,52
2017-12-14,20.9,30.8,0,9.2,11.6,NNE,59,27.3,54,29.9,43
2017-12-15,20.7,26.6,0.2,13.4,0.1,SSW,54,21.9,73,26.3,61
2017-12-16,21.4,28.5,1.4,2.6,11.6,NE,48,25.3,67,25.9,61
2017-12-17,21.9,26.8,0.6,10,1.1,SE,39,23.1,82,24.5,71
2017-12-18,21.1,27.6,0.2,3.2,5.8,ENE,33,24.8,69,25.6,64
2017-12-19,22.3,35.3,0,6.4,5.2,NNE,57,25.4,69,30.1,50
2017-12-20,25.2,38.3,0,11.4,8.6,SSW,78,35.3,32,27.1,60
2017-12-21,21.2,24.5,3,,1.1,ESE,39,23.7,62,22.9,64
2017-12-22,21.2,26.1,0.2,13.6,7.9,ENE,35,23.9,63,25,59
2017-12-23,20.1,28.3,0,7.6,12.3,NE,41,24.8,61,26.7,56
2017-12-24,21,37.7,0,10,7.6,SSE,50,28.3,53,28.4,52
2017-12-25,18.5,21.7,1.2,10,0.2,SSE,46,20,64,21,62
2017-12-26,19.5,23.8,0,5.2,0,ENE,43,21.3,54,22.6,54
2017-12-27,18.8,26.2,3,4.6,10.9,E,43,23.7,60,24.9,62
2017-12-28,19.2,27.4,0,9.8,10.8,ENE,44,25,59,26.2,57
2017-12-29,21.3,28.8,0,8.2,8.4,NE,33,25.6,72,28.3,58
2017-12-30,22.4,36.2,3.8,8.4,8,WNW,44,23.6,82,34.8,27
2017-12-31,20.1,25.3,6,9.2,7.1,,,21.1,76,24.6,61

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Homework Answers

Answer #1

Code:

import pandas as pd #importing pandas pacakage

data=pd.read_csv("climate_data_2017.csv") #reading climate_Data csv file using pandas

df1=data.loc[data['Maximum temperature (C)']>35.00] #filtering the data where the maximum temparature is >35

print ('Maximum amount of rainfall on hot days: ' + str(df1['Rainfall (mm)'].max()))

#after that finding the maximum rain fall value among that filtered data

Code and Output Screenshots:

csv file screenshot for reference:

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