QuestionFor the problems in this homework, write your code in files… For the problems in this homework, write your code in filespokemon.py,covid.py, andtfidf.pyrespectively.Each of these files should be executable, which means that when we run your program, it should do an end-to-end run of the tasks in each problem, and produce results as required. For instance: > python pokemon.pyshould execute the tasks in Problem 1 and produce the required output files.Zip all of these Python files into a single file namedhw2.zipand submit this to Canvas. Do not include any input or output files, we only need your Python code.Problem 1: Pokemon Box Dataset (45 points)Given a CSV data file as represented by the sample filepokemonTrain.csvDownload pokemonTrain.csvperform the following operations on it.[7 pts]Find out what percentage of “fire” type pokemons are at or above the “level” 40.Your program should print the value as follows (replace … with value): Percentage of fire type Pokemons at or above level 40 = …The value should be rounded off (not ceiling) using theround()function. So, for instance, if the value is 12.3 (less than or equal to 12.5) you would print 12, but if it was 12.615 (more than 12.5), you would print 13.Print the value to a file named “pokemon1.txt”[10 pts]Fill in the missing “type” column values (given by NaN) by mapping them from the corresponding “weakness” values. You will see that usually, a given pokemon weakness has a fixed “type”, but there do exist some exceptions. Hence, fill in the “type” column with the most common “type” corresponding to the pokemon’s “weakness” value.For example, most of the pokemons having the weakness “electric” are “water” type pokemons but there are other types too that have “electric” as their weakness (exceptions in that “type”). But since “water” is the most common type for weakness “electric”, it should be filled in.In case of a tie, use the type that appears first in alphabetical order.[13 pts]Fill in the missing values in the Attack (“atk”), Defense (“def”) and Hit Points (“hp”) columns as follows:Set the pokemon level threshold to 40.For a Pokemon having level above the threshold (i.e. > 40), fill in the missing value for atk/def/hp with the average values of atk/def/hp of Pokemons with level > 40. So, for instance, you would substitute the missing “atk” value for Magmar (level 44), with the average “atk” value for Pokemons with level > 40. Round the average to one decimal place.For a Pokemon having level equal to or below the threshold (i.e. <= 40), fill in the missing value for atk/def/hp with the average values of atk/def/hp of Pokemons with level <= 40. Round the average to one decimal place.[10 pts]Create a dictionary that maps pokemon types to their personalities. This dictionary would map a string to a list of strings. For example: {"fire": ["docile", "modest", ...], "normal": ["mild", "relaxed", ...], ...}Note: You can create an empty default dictionary of list withdefaultdict(list)Your dictionary should have the keys ordered alphabetically, and also items ordered alphabetically in the values list, as shown in the example.Print the dictionary in the following format: Pokemon type to personality mapping: normal: mild, relaxed, ... fire: docile, modest, ... ...Print the dictionary to a file named "pokemon4.txt"[5 pts]Find out the average Hit Points ("hp") for pokemons of stage 3.0.Your program should print the value as follows (replace ... with value): Average hit point for Pokemons of stage 3.0 = ...You should round off the value, like in #1 above.Print the value to a file named "pokemon5.txt"Problem 2: Covid-19 Dataset (35 points)Given a Covid-19 data CSV file with 12 feature columns, perform the tasks given below. Use the sample filecovidTrain.csvDownload covidTrain.csvto test your code.[5 pts]In the age column, wherever there is a range of values, replace it by the rounded off average value. E.g., for 10-14 substitute 12. (Rounding should be done like in 1.1). You might want to use regular expressions here, but it is not required.[6 pts]Change the date format for the date columns - date_onset_symptoms, date_admission_hospital and date_confirmation from dd.mm.yyyy to mm.dd.yyyy. Again, you can use regexps here, but it is not required.[7 pts]Fill in the missing (NaN) "latitude" and "longitude" values by the average of the latitude and longitude values for the province where the case was recorded. Round the average to 2 decimal places.[7 pts]Fill in the missing "city" values by the most occurring city value in that province. In case of a tie, use the city that appears first in alphabetical order.[10 pts]Fill in the missing "symptom" values by the single most frequent symptom in the province where the case was recorded. In case of a tie, use the symptom that appears first in alphabetical order.Note: While iterating through records, if you come across multiple symptoms for a single record, you need to consider them individually for frequency counts.Very Important!: Some symptoms could be separated by a ';' , i.e., semicolon plus space and some by ';' , i.e., just a semicolon, even within the same record. For example: "fever; sore throat;cough;weak; expectoration;muscular soreness"After performing all these tasks, write the whole data back to another CSV file named "covidResult.csv"id,name,level,personality,type,weakness,atk,def,hp,stage53.0,Persian,40.0,mild,normal,fighting,104.0,116.0,NaN,2.0126.0,Magmar,44.0,docile,NaN,water,96.0,83.0,153.0,1.057.0,Primeape,9.0,lonely,fighting,flying,NaN,66.0,43.0,2.03.0,Venusaur,44.0,sassy,grass,fire,136.0,195.0,92.0,3.011.0,Metapod,4.0,naive,grass,fire,NaN,114.0,NaN,2.0126.0,Magmar,96.0,modest,fire,water,62.0,114.0,NaN,1.0137.0,Porygon,96.0,relaxed,NaN,fighting,68.0,50.0,127.0,1.069.0,Bellsprout,84.0,lonely,grass,fire,NaN,NaN,NaN,1.010.0,Caterpie,3.0,serious,NaN,flying,NaN,NaN,15.0,1.012.0,Butterfree,12.0,hasty,NaN,flying,20.0,NaN,NaN,3.035.0,Clefairy,18.0,impish,fairy,poison,33.0,NaN,NaN,1.059.0,Arcanine,35.0,gentle,fire,water,45.0,60.0,80.0,2.0111.0,Rhyhorn,31.0,naughty,rock,water,40.0,NaN,175.0,1.0136.0,Flareon,75.0,bold,NaN,water,NaN,143.0,NaN,2.051.0,Dugtrio,82.0,gentle,ground,water,152.0,161.0,168.0,2.038.0,Ninetales,5.0,brave,fire,water,NaN,179.0,173.0,2.0102.0,Exeggcute,88.0,rash,NaN,fire,NaN,124.0,NaN,1.095.0,Onix,46.0,mild,rock,water,NaN,NaN,191.0,1.0134.0,Vaporeon,65.0,bashful,grass,fire,103.0,NaN,129.0,3.0114.0,Tangela,52.0,quiet,NaN,fire,151.0,166.0,84.0,1.053.0,Persian,42.0,quiet,normal,fighting,169.0,152.0,27.0,2.078.0,Rapidash,60.0,brave,fire,water,NaN,NaN,62.0,2.028.0,Sandslash,12.0,quiet,ground,water,103.0,50.0,128.0,2.071.0,Victreebel,100.0,gentle,grass,fire,NaN,190.0,NaN,3.02.0,Ivysaur,80.0,docile,grass,fire,42.0,131.0,165.0,2.0108.0,Lickitung,68.0,calm,NaN,fighting,124.0,169.0,125.0,1.0134.0,Vaporeon,65.0,bold,NaN,fire,34.0,67.0,60.0,3.052.0,Meowth,27.0,naughty,normal,fighting,170.0,169.0,143.0,1.014.0,Kakuna,92.0,impish,NaN,fire,72.0,NaN,48.0,2.05.0,Charmeleon,27.0,rash,fire,water,72.0,26.0,51.0,2.0140.0,Kabuto,88.0,bashful,rock,grass,NaN,167.0,NaN,1.051.0,Dugtrio,57.0,hardy,ground,water,139.0,155.0,NaN,2.0133.0,Eevee,97.0,lax,NaN,fighting,NaN,154.0,184.0,1.0132.0,Ditto,10.0,brave,normal,fighting,160.0,167.0,NaN,1.0114.0,Tangela,5.0,bold,grass,fire,NaN,59.0,NaN,1.049.0,Venomoth,99.0,careful,bug,fire,NaN,188.0,NaN,2.078.0,Rapidash,73.0,naughty,NaN,water,137.0,46.0,93.0,2.069.0,Bellsprout,73.0,quiet,grass,fire,97.0,NaN,NaN,1.08.0,Wartortle,29.0,hardy,water,grass,98.0,NaN,33.0,2.011.0,Metapod,80.0,quiet,grass,fire,66.0,116.0,28.0,2.095.0,Onix,85.0,docile,rock,water,88.0,NaN,174.0,1.051.0,Dugtrio,43.0,impish,NaN,water,NaN,72.0,196.0,2.035.0,Clefairy,67.0,sassy,fairy,poison,92.0,NaN,137.0,1.0113.0,Chansey,78.0,brave,normal,fighting,37.0,99.0,167.0,1.075.0,Graveler,22.0,impish,rock,water,80.0,146.0,200.0,2.012.0,Butterfree,8.0,impish,flying,fire,44.0,114.0,135.0,3.06.0,Charizard,55.0,timid,fire,water,NaN,NaN,71.0,3.0125.0,Electabuzz,37.0,hardy,electric,ground,NaN,NaN,158.0,1.057.0,Primeape,51.0,adamant,fighting,flying,200.0,NaN,123.0,2.0146.0,Moltres,62.0,naughty,fire,rock,65.0,155.0,NaN,1.059.0,Arcanine,59.0,bashful,NaN,water,NaN,54.0,NaN,2.0102.0,Exeggcute,98.0,calm,grass,fire,51.0,177.0,103.0,1.039.0,Jigglypuff,95.0,naughty,fairy,poison,104.0,79.0,NaN,1.0102.0,Exeggcute,9.0,adamant,grass,fire,123.0,NaN,50.0,1.058.0,Growlithe,28.0,impish,fire,water,183.0,172.0,144.0,1.074.0,Geodude,31.0,impish,NaN,water,117.0,138.0,100.0,1.0106.0,Hitmonlee,29.0,careful,fighting,flying,79.0,126.0,NaN,1.059.0,Arcanine,5.0,hardy,fire,water,NaN,173.0,74.0,2.051.0,Dugtrio,10.0,bashful,ground,water,142.0,176.0,120.0,2.019.0,Rattata,25.0,serious,NaN,fighting,NaN,84.0,183.0,1.03.0,Venusaur,67.0,naive,NaN,fire,145.0,NaN,35.0,3.053.0,Persian,87.0,jolly,normal,fighting,74.0,NaN,172.0,2.059.0,Arcanine,69.0,jolly,NaN,water,35.0,NaN,20.0,2.011.0,Metapod,17.0,mild,NaN,fire,191.0,127.0,NaN,2.076.0,Golem,78.0,hardy,NaN,water,65.0,145.0,137.0,3.06.0,Charizard,89.0,lax,fire,water,165.0,100.0,108.0,3.0ID,age,sex,city,province,country,latitude,longitude,date_onset_symptoms,date_admission_hospital,date_confirmation,symptoms11816.0,40-49,female,NaN,Aichi Prefecture,Japan,35.18333,136.9,19.02.2020,21.02.2020,22.02.2020,fever11814.0,60-69,male,Nagoya City,Aichi Prefecture,Japan,35.18333,136.9,19.02.2020,21.02.2020,22.02.2020,fever11813.0,60-69,male,Nagoya City,Aichi Prefecture,Japan,35.18333,136.9,19.02.2020,21.02.2020,22.02.2020,fever8504.0,60-69,male,NaN,Aichi Prefecture,Japan,35.2188941,136.9996761,17.02.2020,18.02.2020,18.02.2020,NaN8501.0,60-60,female,Nagoya City,Aichi Prefecture,Japan,35.18333,136.9,13.02.2020,14.02.2020,15.02.2020,fever; headache11815.0,60-69,female,Nagoya City,Aichi Prefecture,Japan,35.18333,136.9,19.02.2020,21.02.2020,22.02.2020,fever889.0,46,female,NaN,Anhui,China,NaN,118.35600000000001,19.01.2020,22.01.2020,26.01.2020,fever888.0,47,female,Ma’anshan City,Anhui,China,31.62885,118.35600000000001,22.01.2020,24.01.2020,26.01.2020,NaN887.0,55,male,NaN,Anhui,China,31.62885,NaN,18.01.2020,24.01.2020,26.01.2020,fever886.0,47,male,Ma’anshan City,Anhui,China,31.62885,NaN,22.01.2020,23.01.2020,25.01.2020,fever885.0,54,female,Ma’anshan City,Anhui,China,NaN,NaN,18.01.2020,22.01.2020,25.01.2020,fever884.0,48,female,Ma’anshan City,Anhui,China,NaN,118.35600000000001,19.01.2020,23.01.2020,25.01.2020,fever479.0,25,female,Bozhou City,Anhui,China,33.43671,116.1808,21.01.2020,23.01.2020,25.01.2020,fever; pharyngalgia478.0,35,male,Bozhou City,Anhui,China,33.43671,116.1808,19.01.2020,22.01.2020,25.01.2020,fever477.0,60,male,Bozhou City,Anhui,China,33.43671,NaN,18.01.2020,22.01.2020,25.01.2020,NaN476.0,59,male,Bozhou City,Anhui,China,33.43671,116.1808,19.01.2020,21.01.2020,25.01.2020,cough; fever474.0,51,male,Bozhou City,Anhui,China,NaN,NaN,18.01.2020,21.01.2020,25.01.2020,NaN472.0,22,male,Fuyang City,Anhui,China,NaN,115.7036,21.01.2020,23.01.2020,25.01.2020,fever; sore throat471.0,43,male,Fuyang City,Anhui,China,32.9188,115.7036,23.01.2020,23.01.2020,25.01.2020,fever466.0,25,female,NaN,Anhui,China,32.9188,115.7036,22.01.2020,22.01.2020,24.01.2020,fever883.0,43,male,NaN,Anhui,China,NaN,118.35600000000001,22.01.2020,22.01.2020,25.01.2020,fever1296.0,44,female,Bengbu City,Anhui,China,33.10901,117.32600000000001,24.01.2020,24.01.2020,27.01.2020,fever7.0,42,female,NaN,Anhui,China,NaN,NaN,21.01.2020,21.01.2020,22.01.2020,fever6749.0,36,male,Luyang District Hefei City,Anhui,China,NaN,117.1894,26.01.2020,01.02.2020,05.02.2020,cough; fever4155.0,35,male,Hefei City,Anhui,China,31.79444,117.3428,30.01.2020,30.01.2020,31.01.2020,physical discomfort4154.0,32,male,Hefei City,Anhui,China,31.79444,117.3428,24.01.2020,28.01.2020,31.01.2020,NaN4153.0,27,female,NaN,Anhui,China,32.2842,NaN,28.01.2020,29.01.2020,31.01.2020,cough; fever4152.0,45,female,Feidong County Hefei City,Anhui,China,32.00123,117.5681,25.01.2020,30.01.2020,31.01.2020,NaN4151.0,51,female,Lujiang County Hefei City,Anhui,China,31.269679999999997,117.32,24.01.2020,29.01.2020,31.01.2020,chills; headache; fever4150.0,37,male,Yaohai District Hefei City,Anhui,China,NaN,NaN,20.01.2020,23.01.2020,31.01.2020,fever; pharyngeal discomfort6739.0,55,female,NaN,Anhui,China,31.72762,117.0201,03.02.2020,05.02.2020,05.02.2020,chest tightness; fever1297.0,53,male,Bengbu City,Anhui,China,NaN,117.32600000000001,14.01.2020,19.01.2020,27.01.2020,fever6740.0,48,female,Yaohai District Hefei City,Anhui,China,31.89544,117.3384,30.01.2020,03.02.2020,05.02.2020,fever; joint pain; muscle soreness6742.0,35,male,Shushan District Hefei City,Anhui,China,NaN,117.2001,29.01.2020,03.02.2020,05.02.2020,fever6743.0,29,male,Shushan District Hefei City,Anhui,China,31.82562,117.2001,01.02.2020,04.02.2020,05.02.2020,NaN6744.0,51,male,Lujiang County Hefei City,Anhui,China,31.269679999999997,117.32,02.02.2020,03.02.2020,05.02.2020,NaN6745.0,35,male,Luyang District Hefei City,Anhui,China,31.92046,117.1894,24.01.2020,03.02.2020,05.02.2020,chills; fever6746.0,28,female,NaN,Anhui,China,31.8947345,117.3260293,29.01.2020,02.02.2020,05.02.2020,cough; fever6747.0,78,female,Xinzhan District Hefei City,Anhui,China,31.8947345,NaN,22.01.2020,30.01.2020,05.02.2020,chest pain; nasal congestion6748.0,38,female,Xinzhan District Hefei City,Anhui,China,NaN,117.3260293,30.01.2020,03.02.2020,05.02.2020,cough; muscle soreness; sweating6741.0,43,female,Xinzhan District Hefei City,Anhui,China,31.8947345,117.3260293,03.02.2020,04.02.2020,05.02.2020,fever1511.0,28,male,Huainan City,Anhui,China,32.75738,116.734,22.01.2020,25.01.2020,26.01.2020,dry cough475.0,38,male,NaN,Anhui,China,NaN,116.1808,20.01.2020,22.01.2020,25.01.2020,NaN15.0,45,male,Bengbu City,Anhui,China,33.10901,117.32600000000001,21.01.2020,21.01.2020,27.01.2020,fever14.0,38,female,Chizhou City,Anhui,China,30.28525,117.3658,22.01.2020,22.01.2020,23.01.2020,cough9.0,59,female,NaN,Anhui,China,NaN,116.734,19.01.2020,24.01.2020,26.01.2020,fever23.0,32,female,Haidian District,Beijing,China,40.02186,NaN,17.01.2020,20.01.2020,21.01.2020,respiratory symptoms24.0,45,male,Shijingshan District,Beijing,China,39.92715,116.1737,19.01.2020,21.01.2020,22.01.2020,NaN25.0,45,male,Shijingshan District,Beijing,China,NaN,116.1737,19.01.2020,21.01.2020,23.01.2020,fever26.0,18,female,Tongzhou District,Beijing,China,39.80292,116.7363,19.01.2020,20.01.2020,21.01.2020,fever; respiratory symptoms27.0,56,female,NaN,Beijing,China,39.91093,116.3591,16.01.2020,20.01.2020,21.01.2020,fever; respiratory symptoms28.0,42,male,NaN,Beijing,China,39.91093,NaN,20.01.2020,20.01.2020,22.01.2020,fever22.0,39,male,Haidian District,Beijing,China,40.02186,116.2285,09.01.2020,14.01.2020,21.01.2020,fever21.0,37,male,NaN,Beijing,China,39.8306,116.2499,14.01.2020,20.01.2020,21.01.2020,fever89.0,43,male,Lanzhou City,Gansu,China,36.351259999999996,103.6554,18.01.2020,21.01.2020,23.01.2020,discomfort; fever90.0,24,male,Baiyin City,Gansu,China,36.61864,104.6208,16.01.2020,22.01.2020,23.01.2020,cough; fever; headache; muscular soreness; weak8904.0,42,female,Longxi County Dingxi City,Gansu,China,35.10665,NaN,28.01.2020,04.02.2020,05.02.2020,NaN8905.0,26,female,Longxi County Dingxi City,Gansu,China,35.10665,104.6236,01.02.2020,04.02.2020,05.02.2020,fever; cough8906.0,37,male,Baiyin District Baiyin City,Gansu,China,36.56493,NaN,24.01.2020,29.01.2020,05.02.2020,NaN8907.0,24,male,Ningxian County Qingyang City,Gansu,China,NaN,108.1031,01.02.2020,01.02.2020,05.02.2020,fever; runny nose8915.0,29,female,Longxi County Dingxi City,Gansu,China,NaN,NaN,24.01.2020,04.02.2020,07.02.2020,headache; dry mouth8914.0,54,female,Longxi County Dingxi City,Gansu,China,35.10665,104.6236,21.01.2020,04.02.2020,07.02.2020,dry throat; sore throat; fatigue4280.0,31,male,Chengguan District Lanzhou City,Gansu,China,NaN,103.8756,19.01.2020,30.01.2020,01.02.2020,discomfort4281.0,66,female,Chengguan District Lanzhou City,Gansu,China,NaN,103.8756,24.01.2020,28.01.2020,01.02.2020,NaN4283.0,32,male,NaN,Gansu,China,35.13411,NaN,24.01.2020,28.01.2020,01.02.2020,fever4284.0,60,male,Gannan Prefecture,Gansu,China,34.33256,102.7657,28.01.2020,30.01.2020,01.02.2020,fever; cough5120.0,26,male,Chengguan District Lanzhou City,Gansu,China,36.07809,103.8756,26.01.2020,30.01.2020,02.02.2020,NaN5121.0,73,female,Xigu District Lanzhou City,Gansu,China,36.12968,103.51899999999999,28.01.2020,31.01.2020,02.02.2020,NaN5122.0,44,male,Xigu District Lanzhou City,Gansu,China,36.12968,103.51899999999999,23.01.2020,26.01.2020,02.02.2020,cough; fever; sputum5123.0,36,male,Ningxian County Qingyang City,Gansu,China,35.565909999999995,108.1031,24.01.2020,28.01.2020,02.02.2020,cough; fever5124.0,38,female,Linxia City Linxia Prefecture,Gansu,China,35.58106,103.1937,27.01.2020,01.02.2020,02.02.2020,cough; fever5126.0,64,female,Maiji District Tianshui City,Gansu,China,34.415,NaN,23.01.2020,30.01.2020,02.02.2020,cough; sputum5127.0,59,male,Maiji District Tianshui City,Gansu,China,34.415,NaN,24.01.2020,30.01.2020,02.02.2020,NaN5128.0,39,female,Maiji District Tianshui City,Gansu,China,NaN,106.1453,30.01.2020,30.01.2020,02.02.2020,fever5129.0,46,female,Qinzhou District Tianshui City,Gansu,China,34.40163,NaN,28.01.2020,30.01.2020,02.02.2020,chills; fatigue8916.0,38,female,Longxi County Dingxi City,Gansu,China,35.10665,NaN,21.01.2020,04.02.2020,07.02.2020,fever; dry mouth; throat discomfort8922.0,55,female,Maiji District Tianshui City,Gansu,China,34.415,106.1453,29.01.2020,31.01.2020,08.02.2020,pharyngeal discomfort6442.0,69,male,Chengguan District Lanzhou City,Gansu,China,36.07809,NaN,28.01.2020,28.01.2020,04.02.2020,fatigue8927.0,33,female,Huating County Pingliang City,Gansu,China,35.20198,NaN,29.01.2020,07.02.2020,09.02.2020,NaN8933.0,53,female,Gannan Prefecture,Gansu,China,34.33256,NaN,04.02.2020,11.02.2020,12.02.2020,dry throat; dry cough8934.0,34,female,Huating County Pingliang City,Gansu,China,NaN,106.5993,10.02.2020,11.02.2020,13.02.2020,NaN8937.0,57,male,Chengguan District Lanzhou City,Gansu,China,36.07809,103.8756,07.02.2020,14.02.2020,16.02.2020,cough; fever8929.0,27,female,NaN,Gansu,China,36.04074,107.6714,03.02.2020,06.02.2020,09.02.2020,fever8925.0,46,female,NaN,Gansu,China,36.12968,103.51899999999999,05.02.2020,07.02.2020,08.02.2020,NaN8924.0,1,female,Huating County Pingliang City,Gansu,China,35.20198,106.5993,30.01.2020,07.02.2020,08.02.2020,diarrhea8923.0,27,female,Huating County Pingliang City,Gansu,China,NaN,106.5993,01.02.2020,04.02.2020,08.02.2020,fever8928.0,23,male,Zhuanglang County Pingliang City,Gansu,China,35.25054,NaN,06.02.2020,08.02.2020,09.02.2020,cough; sputum; fever12037.0,52,female,Qilihe District Lanzhou City,Gansu,China,35.96467,NaN,25.01.2020,27.01.2020,30.01.2020,dry cough12034.0,57,male,NaN,Gansu,China,36.07809,103.8756,07.02.2020,14.02.2020,16.02.2020,NaN12038.0,41,male,Chengguan District Lanzhou City,Gansu,China,36.07809,103.8756,16.01.2020,27.01.2020,30.01.2020,cough; sore body; cold100.0,65,female,Shenzhen City,Guangdong,China,22.65389,114.1291,03.01.2020,10.01.2020,21.01.2020,cough; fever; weakness122.0,66,female,NaN,Guangdong,China,22.16925,113.361,13.01.2020,19.01.2020,21.01.2020,cough104.0,37,female,Shenzhen City,Guangdong,China,NaN,114.1291,02.01.2020,11.01.2020,21.01.2020,diarrhea; fever; nasal congestion; pleuritic chest pain; sore throat103.0,63,female,Shenzhen City,Guangdong,China,NaN,114.1291,08.01.2020,15.01.2020,21.01.2020,anhelation; cough; fever; pleural effusion; weakness101.0,36,male,Shenzhen City,Guangdong,China,22.65389,114.1291,01.01.2020,11.01.2020,21.01.2020,cough; diarrhea; fever; rhinorrhoea; sneezing99.0,66,male,NaN,Guangdong,China,22.65389,114.1291,04.01.2020,10.01.2020,19.01.2020,NaN91.0,40,male,Foshan City,Guangdong,China,NaN,NaN,10.01.2020,20.01.2020,22.01.2020,cough; dizziness5199.0,47,male,NaN,Guangxi,China,21.88401,107.9967,26.01.2020,31.01.2020,02.02.2020,fever; dry cough; fatigue6512.0,62,male,NaN,Guangxi,China,21.88401,107.9967,29.01.2020,01.02.2020,04.02.2020,fever; fatigue11927.0,52,female,Fangchenggang City,Guangxi,China,21.88401,107.9967,16.01.2020,29.01.2020,03.02.2020,chest tightness; fatigue9152.0,60,male,Fangchenggang City,Guangxi,China,21.88401,107.9967,28.01.2020,04.02.2020,07.02.2020,NaN6513.0,60,female,Fangchenggang City,Guangxi,China,21.88401,107.9967,02.02.2020,03.02.2020,05.02.2020,fever; sore throat;fatigue;vomiting9181.0,38,female,NaN,Guangxi,China,21.88401,107.9967,28.01.2020,28.01.2020,30.01.2020,fever; fatigue6514.0,45,female,Fangchenggang City,Guangxi,China,21.88401,NaN,30.01.2020,03.02.2020,05.02.2020,cough11926.0,62,male,Fangchenggang City,Guangxi,China,21.88401,107.9967,25.01.2020,29.01.2020,03.02.2020,fever; fatigue11911.0,10,male,Fangchenggang City,Guangxi,China,21.88401,NaN,07.02.2020,08.02.2020,09.02.2020,fever9180.0,65,male,Fangchenggang City,Guangxi,China,21.88401,NaN,13.01.2020,28.01.2020,30.01.2020,NaN150.0,34,male,Guilin City,Guangxi,China,25.35865,110.5145,19.01.2020,22.01.2020,24.01.2020,cough; fever6511.0,54,female,Fangchenggang City,Guangxi,China,NaN,107.9967,30.01.2020,01.02.2020,04.02.2020,fever;sore throat; fatigue; diarrhea166.0,61,male,Yulin City,Guangxi,China,22.44296,110.182,21.01.2020,22.01.2020,24.01.2020,NaN148.0,46,male,NaN,Guangxi,China,23.481720000000003,NaN,20.01.2020,21.01.2020,22.01.2020,fever147.0,49,male,Liuzhou City,Guangxi,China,24.95009,NaN,21.01.2020,21.01.2020,22.01.2020,fever956.0,47,female,Fangchenggang City,Guangxi,China,21.88401,NaN,23.01.2020,25.01.2020,26.01.2020,fever; fatigue; dry cough152.0,72,female,Beihai City,Guangxi,China,21.676660000000002,109.32799999999999,19.01.2020,19.01.2020,24.01.2020,fever; weak153.0,20,female,Beihai City,Guangxi,China,21.676660000000002,NaN,22.01.2020,22.01.2020,24.01.2020,NaN154.0,54,male,NaN,Guangxi,China,21.676660000000002,109.32799999999999,22.01.2020,22.01.2020,24.01.2020,cough; fever146.0,62,female,Beihai City,Guangxi,China,NaN,109.32799999999999,09.01.2020,21.01.2020,22.01.2020,cough; fever145.0,63,male,NaN,Guangxi,China,21.676660000000002,NaN,14.01.2020,21.01.2020,22.01.2020,NaN11970.0,44,female,Fangchenggang City,Guangxi,China,21.88401,107.9967,22.01.2020,27.01.2020,28.01.2020,cough; fever155.0,33,female,NaN,Guangxi,China,NaN,106.2863,19.01.2020,21.01.2020,24.01.2020,fever156.0,49,female,Hechi City,Guangxi,China,24.64574,107.8409,21.01.2020,22.01.2020,24.01.2020,chest distress; cough; expectoration; muscular soreness162.0,33,male,Hechi City,Guangxi,China,24.64574,107.8409,19.01.2020,21.01.2020,24.01.2020,cough; headache163.0,2,female,Hechi City,Guangxi,China,NaN,107.8409,22.01.2020,23.01.2020,24.01.2020,fever; sneeze151.0,41,male,Guilin City,Guangxi,China,25.35865,110.5145,20.01.2020,23.01.2020,24.01.2020,fever164.0,29,male,NaN,Guangxi,China,21.88401,107.9967,23.01.2020,23.01.2020,24.01.2020,discomfort165.0,62,male,NaN,Guangxi,China,21.88401,107.9967,15.01.2020,23.01.2020,24.01.2020,NaN11971.0,55,female,NaN,Guangxi,China,NaN,107.9967,22.01.2020,26.01.2020,28.01.2020,fever; nasal congestion; runny nose; sore throat; cough167.0,20,male,NaN,Guizhou,China,26.43055,107.1928,18.01.2020,18.01.2020,22.01.2020,discomfort169.0,50,female,Tongren City,Guizhou,China,NaN,NaN,14.01.2020,21.01.2020,22.01.2020,NaN8489.0,68,male,Zunyi City,Guizhou,China,28.171429999999997,107.0848,31.01.2020,03.02.2020,07.02.2020,nausea; vomiting11550.0,0-10,male,NaN,Hokkaido,Japan,43.4115473,142.3833135,15.02.2020,19.02.2020,21.02.2020,fever 37.7 C11551.0,0-10,male,Nakafurano,Hokkaido,Japan,43.4115473,142.3833135,18.02.2020,19.02.2020,21.02.2020,fever 37.7 C12576.0,30-39,male,Okhotsk,Hokkaido,Japan,NaN,144.260889,17.02.2020,24.02.2020,27.02.2020,sore throat; fever (38-39 C)12554.0,70-79,female,Shinhidaka,Hokkaido,Japan,42.4384206,142.3325668,17.02.2020,24.02.2020,26.02.2020,fever (38-39 C); malaise4109.0,39,male,Hong Kong,Hong Kong,China,22.38074,114.1324,19.01.2020,30.01.2020,01.02.2020,cough; fever1085.0,64,male,NaN,Hong Kong,China,22.38074,114.1324,24.01.2020,25.01.2020,26.01.2020,fever9670.0,51,male,Tsing Yi,Hong Kong,China,NaN,NaN,03.02.2020,10.02.2020,12.02.2020,fever9672.0,67,female,Quarry Bay,Hong Kong,China,22.2859106,114.20686780000001,31.01.2020,12.02.2020,13.02.2020,chills; cough; fever9673.0,37,male,Wan Chai,Hong Kong,China,NaN,114.16524809999999,08.02.2020,12.02.2020,13.02.2020,fever7670.0,60,male,Lam Tin,Hong Kong,China,NaN,114.234404,22.01.2020,30.01.2020,04.02.2020,fever; myalgia; shortness of breath11865.0,96,female,NaN,Hong Kong,China,22.2826304,114.18812109999999,13.02.2020,22.02.2020,22.02.2020,fever; cough3052.0,72,male,NaN,Hong Kong,China,22.38074,114.1324,25.01.2020,29.01.2020,28.01.2020,fever1084.0,68,female,Hong Kong,Hong Kong,China,NaN,114.1324,21.01.2020,25.01.2020,26.01.2020,cough; fever3681.0,37,female,Hong Kong,Hong Kong,China,22.38074,NaN,28.01.2020,30.01.2020,31.01.2020,cough3682.0,75,male,Hong Kong,Hong Kong,China,22.38074,114.1324,22.01.2020,24.01.2020,31.01.2020,cough; dyspnea4903.0,80,male,New Territories,Hong Kong,China,22.406999999999996,114.12200000000001,19.01.2020,30.01.2020,01.02.2020,cough; fever5161.0,72,female,Block 1 Site 11 Whampao Garden,Hong Kong,China,22.304412699999997,114.1870613,01.02.2020,01.02.2020,02.02.2020,cough3053.0,73,female,Hong Kong,Hong Kong,China,22.38074,114.1324,25.01.2020,29.01.2020,28.01.2020,fever12545.0,60,Female,NaN,Hong Kong,China,22.38074,114.1324,12.02.2020,24.02.2020,24.02.2020,cough6353.0,64,female,Kowloon,Hong Kong,China,22.319751,114.18611999999999,23.01.2020,01.02.2020,04.02.2020,NaNComputer ScienceEngineering & TechnologyPython Programming COMPUTER S CS210
