Python讀取數據的文本文件，然后從字符串列表中提取子字符串

Question

我有一個天氣數據文件，它有高溫、低溫、降雨等。我需要打開文件並根據用戶輸入的年份范圍返回數據。 用戶輸入開始日期和結束日期，然后我將該數據放入一個列表中，然后用戶可以在該年份范圍的數據子列表中搜索最高 (HIGHTEMP) 或最低溫度 (LOWTEMP) 或最高降雨量 (PRCP)。 目前我可以搜索字符串，但不確定如何識別高溫，例如，然后收集子列表中的高溫，然后找到最高的，然后返回該數據。 與低溫和降雨相同。

這是我到目前為止所擁有的：

def openFile():
    begin = input("Enter your starting year in this format YYYY ")
    end = input("Enter your ending year for weather data in this format YYYY ")

    lines = tuple(open('/Users/jasontt/test/spokaneweatherdata.txt', 'r'))
    #print(lines)
    print("")
    #print(lines[1])
    print("")

    result = [i for i in lines if str(begin) in i]
    #print("This is begining data ", result)

    resultTwo = [i for i in lines if str(end) in i]
    #print("This is end of data ", resultTwo)
    #Combined list based on years entered
    ultimateList = [result + resultTwo]
    #Combined list of weather data for years selected
    print(ultimateList)

    '''

測試數據：

STATION           STATION_NAME                                       ELEVATION  LATITUDE   LONGITUDE  DATE     PRCP     TEMPMAX     TEMPMIN
----------------- -------------------------------------------------- ---------- ---------- ---------- -------- -------- -------- --------
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490101 0.00     44       27
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490102 0.00     42       25
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490103 0.15     46       30
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490104 0.03     41       30
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490105 1.14     46       37
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490106 0.00     51       40
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490107 0.00     57       36
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490108 0.00     56       45
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490109 0.00     66       42
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490110 0.00     70       51
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490111 0.03     59       45
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490112 0.04     48       38
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490113 0.00     52       36
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490114 0.00     56       36
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490115 0.00     49       31
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490116 0.00     68       28
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490117 0.00     63       50
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490118 0.04     53       42
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490119 0.01     63       38
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490120 0.00     45       28
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490121 0.97     35       28
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490122 0.29     60       34
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490123 0.14     47       38
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490124 0.01     72       38
GHCND:USW00013741                     SPOKANE REGIONAL AIRPORT WA US      366.1   37.31667  -79.96667 19490125 0.05     66       49

Answer 1

很難從復制粘貼的數據樣本中分辨出來，但看起來您的文件正在使用“固定寬度”行格式 - 行中的每一列都從給定位置開始並在給定位置結束。 這在當時是一種非常常見的“格式”......

所以你在這里想要的是寫下每一列的名稱，開始和結束位置，這樣你就可以輕松地將行解析為字段，即：

FORMAT_MAP = {
    # fieldname : (start, end)
    "STATION": (0, 17),
    "STATION_NAME": (18, 68),
    "ELEVATION": (69, 79),
    # etc...
    }


def parse_line(line):
    return {name: line[start:end].strip() for name, (start, end) in FORMAT_MAP.items()}

現在您可以將文件解析為一系列字段字典：

def iter_parse_file(f, startyear, endyear):
   # skip the first two header lines
   next(f);  next(f)

   for line in f: 
      # we assume the lines are sorted on date, and that the
      # date format is YYYYMMDD. 
      row = parse_line(line)
      year = row["DATE"][:4]
      if year < startyear:
         continue
      elif year > endyear:
         break
      yield row


with open("your/file.ext") as f:
    rows = list(iter_parse_file(f, startyear, endyear))

for row in rows:
    print("{DATE} : {TEMPMIN} - {TEMPMAX}".format(**row))

您還可以對列值進行過濾、排序等，構建熊貓數據框等。

請注意，您可以（並且可能想要）在解析過程中將數據轉換為正確的類型。 有了上面的起點，你應該能夠很容易地做到這一點。