Question

所以总体任务如下：使用提供的climate_data_Dec2017.csv文件，您的任务是找出12月26日我们记录的气象站每个风向的读数。

该文件包含超过此特定日期的数据，因此您必须使用过滤语句以确保仅包含26日的读数。

汇总字典中的读数。如果没有特定风向的任何记录，它仍应出现在字典中并且值为零。

因此实际数据集包括：

Collection {#475 ▼
#items: array:3 [▼
2 => "sara"
1 => "reza"
0 => "ali"
]
}

我所做的是：

Date,State,City,Station Code,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 (%)
2017-12-25,VIC,Melbourne,086338,15.1,21.4,0,8.2,10.4,S,44,17.2,57,20.7,54
2017-12-25,VIC,Bendigo,081123,11.3,26.3,0,,,ESE,46,17.2,53,25.5,25
2017-12-25,QLD,Gold Coast,040764,22.3,35.7,0,,,SE,59,29.2,53,27.7,67
2017-12-25,SA,Adelaide,023034,13.9,29.5,0,10.8,12.4,SE,43,18.6,42,27.7,17
2017-12-25,QLD,Brisbane,040913,22.5,36.2,0,11.0,10.0,WSW,61,29.5,53,32.3,53
2017-12-25,QLD,Townsville,032040,24.8,32.5,0,,,NNE,41,29.1,55,31.1,48
2017-12-25,QLD,Cairns,031011,20.3,33.3,0,,,E,41,29.2,59,32.4,45
2017-12-25,NSW,Wollongong,068228,15.9,21.3,7.6,,,SSW,48,18.5,80,19.5,70
2017-12-25,NSW,Newcastle,061055,19.8,21.6,0.6,,,S,48,20.2,83,20.9,74
2017-12-25,VIC,Ballarat,089002,8.5,21.4,0,,,SSE,54,13.3,62,21.1,40
2017-12-25,QLD,Sunshine C,040861,20.2,31.5,0,,,NNE,43,28.9,62,28.8,61
2017-12-25,NSW,Canberra,070351,13.4,23.0,0,,,ESE,39,15.0,66,21.9,47
2017-12-25,NSW,Albury,072160,14.7,29.1,0,,,SSE,37,18.7,42,26.6,32
2017-12-25,QLD,Toowoomba,041529,19.5,32.0,0,,,E,61,24.4,68,31.2,39
2017-12-25,VIC,Geelong,087184,14.1,21.6,0,,,S,41,16.7,58,19.9,53
2017-12-25,NT,Darwin,014015,24.0,27.6,20.0,6.6,0.0,NNE,46,25.4,91,27.3,81
2017-12-25,WA,Perth,009021,19.7,33.1,0,11.0,13.3,SW,39,27.8,34,31.1,29
2017-12-26,VIC,Ballarat,089002,10.8,29.1,0,,,SE,56,17.3,59,27.1,30
2017-12-26,NSW,Canberra,070351,10.8,22.4,0,,,E,39,18.3,57,21.8,48
2017-12-26,QLD,Brisbane,040913,19.0,29.7,54.8,12.4,7.5,E,26,25.2,77,28.8,56
2017-12-26,NSW,Newcastle,061055,18.5,22.5,3.8,,,SE,43,21.1,76,21.7,79
2017-12-26,SA,Adelaide,023034,18.0,33.3,0,11.4,12.7,E,43,25.7,23,28.6,28
2017-12-26,QLD,Toowoomba,041529,16.4,28.4,0,,,E,74,23.9,65,22.7,79
2017-12-26,WA,Perth,009021,15.4,27.4,0,9.0,13.2,SW,41,22.3,59,25.7,45
2017-12-26,VIC,Bendigo,081123,12.8,31.3,0,,,SE,41,20.5,50,30.3,27
2017-12-26,QLD,Gold Coast,040764,20.4,27.9,11.6,,,SSE,52,24.7,87,25.8,81
2017-12-26,VIC,Geelong,087184,12.5,26.6,0,,,SSE,31,18.9,69,23.8,50
2017-12-26,VIC,Melbourne,086338,12.5,30.5,0,8.0,12.9,SSE,37,17.4,66,27.0,43
2017-12-26,QLD,Cairns,031011,22.0,33.0,0,,,ENE,33,29.2,61,31.1,56
2017-12-26,NSW,Wollongong,068228,17.8,24.1,0,,,ENE,41,21.3,59,23.9,55
2017-12-26,QLD,Sunshine C,040861,19.9,28.6,7.4,,,ESE,33,28.4,67,27.6,68
2017-12-26,QLD,Townsville,032040,23.4,32.4,0,,,NE,37,29.9,52,30.4,50
2017-12-26,NSW,Albury,072160,14.0,30.7,0,,,NNE,31,21.6,46,29.2,26
2017-12-26,NT,Darwin,014015,24.6,31.6,8.0,4.6,1.4,NNW,56,26.7,90,30.3,72
2017-12-27,WA,Perth,009021,14.5,26.5,0,11.8,12.3,SSW,54,21.4,49,25.5,34
2017-12-27,NSW,Wollongong,068228,18.8,25.1,0,,,NE,43,21.8,77,23.3,72
2017-12-27,VIC,Geelong,087184,14.9,37.2,0,,,N,41,26.4,46,35.9,20
2017-12-27,QLD,Sunshine C,040861,21.5,28.8,1.4,,,SE,33,26.5,73,27.6,66
2017-12-27,NSW,Albury,072160,15.0,32.5,0,,,E,30,23.6,54,30.9,29
2017-12-27,VIC,Ballarat,089002,15.3,32.9,0,,,N,56,22.2,55,30.9,30
2017-12-27,QLD,Toowoomba,041529,16.7,26.9,29.4,,,E,57,20.4,80,26.1,57
2017-12-27,QLD,Gold Coast,040764,20.3,29.4,0.2,,,S,41,26.4,72,27.5,71
2017-12-27,NSW,Canberra,070351,15.8,29.1,0,,,NE,33,18.9,68,26.4,37
2017-12-27,SA,Adelaide,023034,20.6,36.0,0,8.8,3.8,WSW,48,32.9,9,28.9,34
2017-12-27,VIC,Melbourne,086338,17.3,34.5,0,11.8,10.4,NW,46,25.3,45,32.9,32
2017-12-27,VIC,Bendigo,081123,16.3,35.6,0,,,N,46,22.7,54,32.9,30
2017-12-27,QLD,Cairns,031011,22.4,32.6,0,,,NE,35,29.1,59,31.3,55
2017-12-27,QLD,Townsville,032040,23.2,32.8,0,,,NE,37,30.3,52,30.0,59
2017-12-27,QLD,Brisbane,040913,20.7,29.6,3.0,5.6,10.0,E,30,27.3,60,28.2,56
2017-12-27,NSW,Newcastle,061055,20.5,23.5,0,,,E,39,22.1,80,22.9,79
2017-12-27,NT,Darwin,014015,23.5,31.3,8.8,3.0,0.0,NW,15,28.7,77,29.5,73
2017-12-28,NSW,Newcastle,061055,19.8,24.3,0,,,E,41,22.6,76,23.6,81
2017-12-28,QLD,Toowoomba,041529,16.6,27.9,0,,,E,43,21.3,73,27.4,52
2017-12-28,SA,Adelaide,023034,21.1,25.0,0,10.2,1.0,SSE,26,22.1,82,23.8,74
2017-12-28,QLD,Sunshine C,040861,20.4,28.8,24.0,,,E,31,26.0,69,27.6,63
2017-12-28,VIC,Ballarat,089002,20.1,30.4,0,,,NW,31,25.1,42,29.3,31
2017-12-28,NSW,Wollongong,068228,19.8,25.3,0,,,NE,39,23.2,73,23.8,75
2017-12-28,NSW,Canberra,070351,12.9,32.4,0,,,NW,37,20.1,70,32.4,31
2017-12-28,VIC,Bendigo,081123,22.6,34.4,0,,,NNE,24,26.2,43,32.6,29
2017-12-28,QLD,Townsville,032040,26.9,32.6,0,,,ENE,39,30.2,57,31.0,54
2017-12-28,WA,Perth,009021,15.7,28.8,0,11.2,13.2,SSW,52,22.1,44,25.6,40
2017-12-28,VIC,Melbourne,086338,24.0,32.8,0,14.0,4.1,SSW,31,26.4,46,23.9,73
2017-12-28,QLD,Brisbane,040913,20.6,29.4,0.6,7.8,12.5,ESE,24,27.5,60,28.8,57
2017-12-28,QLD,Gold Coast,040764,20.7,28.9,0,,,SSE,35,26.5,75,28.1,64
2017-12-28,NSW,Albury,072160,17.4,32.8,0,,,ENE,35,22.3,63,31.9,39
2017-12-28,VIC,Geelong,087184,22.9,28.0,0,,,S,39,25.7,54,20.7,85
2017-12-28,NT,Darwin,014015,25.6,34.5,1.0,0.8,9.8,WNW,31,31.0,72,33.1,62
2017-12-28,QLD,Cairns,031011,22.6,34.2,0,,,E,39,30.2,58,32.8,46
2017-12-29,NSW,Wollongong,068228,19.4,25.8,0,,,SW,22,22.7,85,23.2,84
2017-12-29,VIC,Bendigo,081123,20.6,30.6,0.8,,,SW,39,23.6,76,29.6,47
2017-12-29,NSW,Newcastle,061055,20.8,26.3,0,,,ENE,41,24.2,78,25.7,68
2017-12-29,SA,Adelaide,023034,18.2,22.7,2.4,2.8,1.9,WSW,33,20.3,70,21.5,64
2017-12-29,QLD,Toowoomba,041529,18.9,28.9,0,,,NNE,39,22.5,81,27.8,48
2017-12-29,NT,Darwin,014015,26.1,33.7,0,5.2,7.4,S,31,30.8,68,32.4,66
2017-12-29,VIC,Ballarat,089002,15.6,26.6,0,,,NNW,44,21.4,83,18.9,99
2017-12-29,QLD,Townsville,032040,26.0,33.2,0,,,NE,35,30.8,55,31.5,49
2017-12-29,NSW,Canberra,070351,18.3,33.4,0,,,NW,46,24.7,56,31.3,33
2017-12-29,QLD,Cairns,031011,24.9,34.3,0,,,E,39,29.8,61,32.6,47
2017-12-29,WA,Perth,009021,15.6,30.0,0,8.8,13.1,WSW,41,22.9,43,27.5,38
2017-12-29,VIC,Melbourne,086338,18.6,24.4,0.2,5.8,1.0,SSW,35,19.5,78,20.0,85
2017-12-29,QLD,Gold Coast,040764,22.4,28.8,10.2,,,NNE,26,26.0,91,27.3,74
2017-12-29,NSW,Albury,072160,21.0,27.3,1.4,,,SSE,33,23.0,82,25.9,66
2017-12-29,VIC,Geelong,087184,17.2,22.6,0,,,SSW,26,19.3,79,18.7,93
2017-12-29,QLD,Sunshine C,040861,21.9,29.9,0,,,NE,26,27.5,65,28.5,62
2017-12-30,NSW,Wollongong,068228,21.6,29.7,0.6,,,SE,46,25.2,73,26.8,69
2017-12-30,QLD,Townsville,032040,25.8,33.6,0.2,,,N,35,30.2,60,31.7,49
2017-12-30,QLD,Brisbane,040913,23.3,32.2,0,8.6,7.8,NE,24,28.9,55,30.4,65
2017-12-30,VIC,Melbourne,086338,15.6,21.3,8.4,4.2,8.1,SSW,65,19.0,60,19.6,71
2017-12-30,VIC,Bendigo,081123,13.6,25.3,0.4,,,SW,43,17.8,60,22.2,47
2017-12-30,QLD,Cairns,031011,22.0,33.9,0,,,ENE,46,29.0,61,31.2,62
2017-12-30,QLD,Sunshine C,040861,21.0,31.3,0,,,NNE,43,29.0,54,28.1,72
2017-12-30,VIC,Geelong,087184,13.6,22.8,4.6,,,W,56,17.9,78,21.9,41
2017-12-30,NSW,Canberra,070351,18.6,28.3,16.4,,,WNW,50,22.8,70,27.8,33
2017-12-30,QLD,Gold Coast,040764,23.4,31.5,0,,,NW,41,27.2,61,28.0,74
2017-12-30,NSW,Albury,072160,20.3,27.7,13.8,,,W,44,23.0,65,26.2,36
2017-12-30,VIC,Ballarat,089002,8.2,18.6,1.4,,,WSW,50,14.7,81,16.6,70
2017-12-30,SA,Adelaide,023034,17.4,22.7,0.2,4.8,10.2,SW,41,19.1,72,22.0,51
2017-12-30,NT,Darwin,014015,24.2,34.8,1.2,4.4,11.2,NW,28,29.9,71,33.6,61
2017-12-30,NSW,Newcastle,061055,23.2,34.1,2.0,,,NW,52,24.6,81,31.2,50
2017-12-30,QLD,Toowoomba,041529,19.1,30.2,0,,,N,31,23.6,70,30.2,49
2017-12-31,QLD,Toowoomba,041529,21.1,30.2,1.4,,,E,54,24.7,75,23.6,66
2017-12-31,NSW,Canberra,070351,14.9,27.9,0,,,NNW,37,19.7,65,26.2,37
2017-12-31,VIC,Bendigo,081123,8.9,29.0,0,,,WNW,33,17.3,54,26.7,28
2017-12-31,NSW,Newcastle,061055,21.3,25.3,0.2,,,SSE,46,22.5,78,22.4,82
2017-12-31,NSW,Wollongong,068228,18.9,23.4,19.6,,,NNE,48,19.2,93,21.1,84
2017-12-31,QLD,Sunshine C,040861,24.1,32.5,0,,,SSW,65,30.3,62,27.1,78
2017-12-31,QLD,Gold Coast,040764,22.4,29.1,14.8,,,SE,56,27.1,84,25.6,97
2017-12-31,VIC,Geelong,087184,9.8,25.9,0,,,SSE,33,16.4,70,23.9,48
2017-12-31,QLD,Brisbane,040913,24.7,33.6,0,8.0,6.6,E,31,30.0,63,27.1,76
2017-12-31,VIC,Melbourne,086338,12.0,25.7,0.2,4.0,13.5,S,33,17.3,60,22.5,48
2017-12-31,WA,Perth,009021,19.7,33.6,0,12.4,13.2,WSW,41,26.0,45,30.6,36
2017-12-31,VIC,Ballarat,089002,5.7,25.2,2.0,,,W,39,12.8,77,23.5,35
2017-12-31,QLD,Townsville,032040,26.7,33.3,0,,,NNE,33,30.8,55,33.0,44
2017-12-31,NT,Darwin,014015,27.4,34.1,0,6.0,8.6,N,26,30.8,73,32.8,59
2017-12-31,QLD,Cairns,031011,21.6,33.1,0,,,NNE,28,29.9,61,31.2,54
2017-12-31,NSW,Albury,072160,12.7,29.5,0,,,WNW,33,19.9,67,27.7,30
2017-12-31,SA,Adelaide,023034,13.7,22.3,0,8.0,9.7,SW,35,17.7,59,21.4,53

我觉得我有点接近，但我缺少0的值。

我的输出是：

wind_direction = {}
expected_date = "2017-12-26"
is_first_line = True

for row in open("climate_data_Dec2017.csv"):
  if is_first_line:
    is_first_line = False
  else:
    values = row.split(",")
    date = values[0]
    wind = values[9]
    if date == expected_date:
      if wind in wind_direction:
         wind_direction[wind] += 1
      else:
         wind_direction[wind] = 1


for key in sorted(wind_direction):
  print(key, ":", wind_direction[key])

我的问题是，我是如何获得字典中存在的剩余值，并将其归为0。

期望的答案是：

"E : 4
ENE : 2
ESE : 1
NE : 1
NNE : 1
NNW : 1
SE : 3
SSE : 3
SW : 1"

Answer 1

没关系，我是一个绝对的野兽。

wind_direction = {}
expected_date = "2017-12-26"
is_first_line = True

for row in open("climate_data_Dec2017.csv"):
  if is_first_line:
    is_first_line = False
  else:
    values = row.split(",")
    date = values[0]
    wind = values[9]
    if date == expected_date:
      if wind in wind_direction:
         wind_direction[wind] += 1
      else:
         wind_direction[wind] = 1
    if date not in wind_direction:
      if wind in wind_direction:
         wind_direction[wind] += 0
      else:
         wind_direction[wind] = 0

for key in sorted(wind_direction):
  print(key, ":", wind_direction[key])

输出将是：

E : 4
ENE : 2
ESE : 1
N : 0
NE : 1
NNE : 1
NNW : 1
NW : 0
S : 0
SE : 3
SSE : 3
SSW : 0
SW : 1
W : 0
WNW : 0
WSW : 0

Answer 2

if wind in wind_direction:
        if date == expected_date:
            wind_direction[wind] += 1
    else:
        if date == expected_date:
            wind_direction[wind] = 1
        else:
            wind_direction[wind] = 0

Answer 3

正如@sacul所建议的那样，熊猫可能最适合这个：

import pandas as pd
df=pd.read_csv("~/Desktop/datas.csv",header=0,sep=",")
df=df[df["Date"]=="2017-12-26"]

answ={}
winds=list(set(df[df.columns[9]]))
for i in winds:
    answ[i]=len(df[df[df.columns[9]]==str(i)])
print(answ)

切片数据和聚合计数

3 个答案: