文件中年月数据的平均温度 python

Question

我有一个数据文件，其中包含某种特定格式的数据，并且在处理时有一些额外的行要忽略。我需要处理数据并根据数据计算出一个值。

示例数据：

Average monthly temperatures in Dubuque, Iowa, 
January 1964 through december 1975, n=144

24.7    25.7    30.6    47.5    62.9    68.5    73.7    67.9    61.1    48.5    39.6    20.0
16.1    19.1    24.2    45.4    61.3    66.5    72.1    68.4    60.2    50.9    37.4    31.1
10.4    21.6    37.4    44.7    53.2    68.0    73.7    68.2    60.7    50.2    37.2    24.6
21.5    14.7    35.0    48.3    54.0    68.2    69.6    65.7    60.8    49.1    33.2    26.0
19.1    20.6    40.2    50.0    55.3    67.7    70.7    70.3    60.6    50.7    35.8    20.7
14.0    24.1    29.4    46.6    58.6    62.2    72.1    71.7    61.9    47.6    34.2    20.4
8.4     19.0    31.4    48.7    61.6    68.1    72.2    70.6    62.5    52.7    36.7    23.8
11.2    20.0    29.6    47.7    55.8    73.2    68.0    67.1    64.9    57.1    37.6    27.7
13.4    17.2    30.8    43.7    62.3    66.4    70.2    71.6    62.1    46.0    32.7    17.3
22.5    25.7    42.3    45.2    55.5    68.9    72.3    72.3    62.5    55.6    38.0    20.4
17.6    20.5    34.2    49.2    54.8    63.8    74.0    67.1    57.7    50.8    36.8    25.5
20.4    19.6    24.6    41.3    61.8    68.5    72.0    71.1    57.3    52.5    40.6    26.2

样本文件来源：http://robjhyndman.com/tsdldata/data/cryer2.dat

注意：此处，行代表年份，列代表月份。

我正在尝试编写一个函数，其中 returns 从给定的 url 开始的任何一个月的平均温度。

我试过如下：

def avg_temp_march(f):

   march_temps = []

    # read each line of the file and store the values
    # as floats in a list
    for line in f:
        line = str(line, 'ascii') # now line is a string
        temps = line.split()
    # check that it is not empty.
        if temps != []:
            march_temps.append(float(temps[2]))

    # calculate the average and return it
    return sum(march_temps) / len(march_temps)

avg_temp_march("data5.txt")

但是我得到了错误 line = str(line, 'ascii')

TypeError: decoding str is not supported

Answer 1

我认为不需要将字符串转换为字符串。

我尝试通过一些修改来修复您的代码：

def avg_temp_march(f):
    # f is a string read from file

    march_temps = []

    for line in f.split("\n"):
        if line == "":  continue
        temps = line.split(" ")
        temps = [t for t in temps if t != ""]

        # check that it is not empty.
        month_index = 2
        if len(temps) > month_index:

            try:
                march_temps.append(float(temps[month_index]))
            except Exception, e:
                print temps
                print "Skipping line:", e
    # calculate the average and return it
    return sum(march_temps) / len(march_temps)

输出：

['Average', 'monthly', 'temperatures', 'in', 'Dubuque,', 'Iowa,']
Skipping line: could not convert string to float: temperatures
['January', '1964', 'through', 'december', '1975,', 'n=144']
Skipping line: could not convert string to float: through
32.475

根据你原来的问题（最新编辑之前），我认为你可以通过这种方式解决你的问题。

# from urllib2 import urlopen 
from urllib.request import urlopen #python3

def avg_temp_march(url):
  f = urlopen(url).read()
  data = f.split("\n")[3:] #ingore the first 3 lines
  data = [line.split() for line in data if line!=''] #ignore the empty lines
  data = [map(float, line) for line in data] #Convert all numbers to float
  month_index = 2 # 2 for march
  monthly_sum = sum([line[month_index] for line in data])
  monthly_avg = monthly_sum/len(data)
  return monthly_avg

print avg_temp_march("http://robjhyndman.com/tsdldata/data/cryer2.dat")

Answer 2

使用pandas，代码变得更短：

import calendar
import pandas a spd
df = pd.read_csv('data5.txt', delim_whitespace=True, skiprows=2,
                 names=calendar.month_abbr[1:])

现在三月份：

>>> df.Mar.mean()
32.475000000000001

所有月份：

>>> df.mean()
Jan    16.608333
Feb    20.650000
Mar    32.475000
Apr    46.525000
May    58.091667
Jun    67.500000
Jul    71.716667
Aug    69.333333
Sep    61.025000
Oct    50.975000
Nov    36.650000
Dec    23.641667
dtype: float64

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