Python读取文本文件中的数据，然后从字符串列表中提取子字符串

Question

我有一个天气数据文件，其中有高温，低温，降雨等，我需要打开该文件，并返回数据的基础上从用户输入的年范围。用户输入开始日期和结束日期，然后我将这些数据放入一个列表中，用户可以在年度范围的数据子列表中搜索最高（高温）或最低温度（低温）或最高降雨量（PRCP）。目前我可以搜索字符串，但不知道如何识别高温，例如，在子列表中收集高温，然后找到最高的，然后返回数据。低温和降雨也一样

到目前为止，我掌握的情况如下：

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)

    '''

测试数据：

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

很难从复制粘贴的数据示例中分辨出来，但看起来您的文件使用的是“固定宽度”的行格式—行中的每一列从给定位置开始，到给定位置结束。这是一个相当常见的类型的“格式”的日子

因此，您需要在这里写下每个列的名称、开始和结束位置，这样您就可以轻松地将行解析为字段，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()}

现在，您可以将文件解析为一系列字段dicts：

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))

您还可以对列值进行筛选、排序等，构建panda数据帧等

请注意，在解析过程中，您可以（也可能希望）将数据转换为正确的类型。有了以上的出发点，你应该可以很容易地做到这一点