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wsds
V2EX  ›  Python

Python 菜鸡请教

  •  1
     
  •   wsds · 2018-06-15 10:12:53 +08:00 · 4392 次点击
    这是一个创建于 2114 天前的主题,其中的信息可能已经有所发展或是发生改变。

    有这么一堆数据:

    #test.log
    a, 1.324171
    b, 0.000126
    c, 1.970941
    a, 1.469649
    b, 0.000124
    c, 0.512929
    a, 1.290920
    b, 0.000118
    c, 0.259524
    a, 0.495958
    b, 0.000123
    c, 0.910949
    a, 1.268038
    b, 0.000118
    c, 1.016419
    a, 1.856081
    b, 0.000120
    c, 1.400075
    a, 1.314131
    b, 0.000140
    

    想要用 python 把左边的 key 一样的合并,但 value 要取它所有的和,还有平均值

    搞了半天,发现搞不定,也是尴尬,以下还是个半成品,搞不下去了,报错,求大神指点一些简单方法

    def two(file):
    
    	arr = []
    	with open(file, "r", encoding="utf-8") as f:
    		for i in f.readlines():
    			a = i.replace("\n", '').strip()
    			if a.split(",")[0] not in arr:
    				arr.append(a.split(",")[0])
    	ser = -1
    	while True:
    		ser += 1
    		try:
    			if a.split(",")[ser] == arr[ser]:
    				print(a.split(",")[ser])
    		except IndexError:
    			print("end!")
    			break
    
    
    two("test.log")
    
    
    47 条回复    2020-09-06 22:09:24 +08:00
    linxzh1989
        1
    linxzh1989  
       2018-06-15 10:16:56 +08:00
    pandas groupby sum?
    aborigine
        2
    aborigine  
       2018-06-15 10:18:07 +08:00 via iPhone
    了解一下 pandas ?导入生成个 dataframe 就行了
    wsds
        3
    wsds  
    OP
       2018-06-15 10:20:14 +08:00
    @aborigine 要用纯 python 处理,该怎么弄?
    wsds
        4
    wsds  
    OP
       2018-06-15 10:20:26 +08:00
    @aborigine 我的意思是,不要用这种一步到位的库
    deepreader
        5
    deepreader  
       2018-06-15 10:21:27 +08:00
    Dictionary 会用么?
    wsds
        6
    wsds  
    OP
       2018-06-15 10:23:12 +08:00
    @deepreader 抱歉,字典我知道,但以我的水平真心实现不了
    mentalkiller
        7
    mentalkiller  
       2018-06-15 10:25:19 +08:00
    @wsds #6 dict 是 python 内置的数据结构啊,不需要你自己实现
    wsds
        8
    wsds  
    OP
       2018-06-15 10:26:08 +08:00
    @mentalkiller 我的意思不是实现字典的功能,我的意思是用字典,我实现不了我的需求
    lixm
        10
    lixm  
       2018-06-15 10:30:15 +08:00   ❤️ 1
    ybping
        11
    ybping  
       2018-06-15 10:30:23 +08:00 via iPhone
    dict 了解一下
    scriptB0y
        12
    scriptB0y  
       2018-06-15 10:30:33 +08:00   ❤️ 1
    In [18]: data = """
    ...: a, 1.324171
    ...: b, 0.000126
    ...: c, 1.970941
    ...: a, 1.469649
    ...: b, 0.000124
    ...: c, 0.512929
    ...: a, 1.290920
    ...: b, 0.000118
    ...: c, 0.259524
    ...: a, 0.495958
    ...: b, 0.000123
    ...: c, 0.910949
    ...: a, 1.268038
    ...: b, 0.000118
    ...: c, 1.016419
    ...: a, 1.856081
    ...: b, 0.000120
    ...: c, 1.400075
    ...: a, 1.314131
    ...: b, 0.000140
    ...: """

    In [19]: result = {}
    ...: for line in data.splitlines():
    ...: if not line: continue
    ...: key, value = line.split(",")
    ...: result.setdefault(key, []).append(float(value))
    ...:

    In [20]: for key, values in result.items():
    ...: print(f"{key}: avg: {sum(values) / len(values)}, sum: {sum(values)}")
    ...:
    a: avg: 1.2884211428571428, sum: 9.018948
    b: avg: 0.00012414285714285714, sum: 0.000869
    c: avg: 1.0118061666666667, sum: 6.070837

    https://gist.github.com/laixintao/f4a186cea6c28fcf3dc696100458c410
    wsds
        13
    wsds  
    OP
       2018-06-15 10:33:08 +08:00
    @hahastudio
    @lixm
    @scriptB0y
    非常感谢各位!学习了
    wplct
        14
    wplct  
       2018-06-15 10:35:15 +08:00
    def two(file):
    data = {}
    with open(file, "r") as f:
    while True:
    s = f.readline()
    if s is None or not s:
    break
    print(s.split(', '))
    k, v = s.split(', ')
    v = float(v)
    if k not in data:
    data[k] = {
    'num': 1,
    'sum': v,
    'avg': v
    }
    else:
    data[k]['num'] += 1
    data[k]['sum'] += v
    data[k]['avg'] = data[k]['sum'] / data[k]['num']
    print(data)
    two('test.txt')
    wsds
        15
    wsds  
    OP
       2018-06-15 10:40:48 +08:00
    @wplct 感谢
    araraloren
        16
    araraloren  
       2018-06-15 10:43:41 +08:00   ❤️ 3
    一行脚本拯救你

    perl -nE 'state %z; my @z = split(", "); $z{@z[0]} += @z[1]; END { say for %z; } ' < test.log
    a
    9.018948
    b
    0.000869
    c
    6.070837

    perl6 -ne 'state %z; given .split(", ") { %z{.[0]} += .[1].Rat; }; END { say %z; }' < test.log
    {a => 9.018948, b => 0.000869, c => 6.070837}
    bufpay
        17
    bufpay  
       2018-06-15 10:51:56 +08:00
    其实一个 for 循环就可以了
    E1n
        18
    E1n  
       2018-06-15 11:03:54 +08:00 via Android
    @araraloren perl 好用,用 awk 能实现吗。。
    araraloren
        19
    araraloren  
       2018-06-15 11:05:43 +08:00
    @E1n awk 肯定能实现,不过我只懂基本的 awk 脚本
    imagechans
        20
    imagechans  
       2018-06-15 11:22:38 +08:00
    def stand(file):
    datas = [str(line).replace("\n","").strip().split(',')[1] for line in open(file)]
    s = sum([float(d) for d in datas])
    m = s / len(datas)
    print(s,m)


    stand("test.log")
    imagechans
        21
    imagechans  
       2018-06-15 11:24:19 +08:00
    @imagechans 这是按照我自己的习惯写的
    billgreen1
        22
    billgreen1  
       2018-06-15 11:43:25 +08:00   ❤️ 1
    < test.log | awk -F"," '{total[$1]+=$2; occurence[$1]+=1}END{for (key in total) printf("%s\t %s \t %s\n", key, total[key], total[key]/occurence[key])}'
    slimbloody
        23
    slimbloody  
       2018-06-15 12:09:58 +08:00
    default_dict
    arthasgxy
        24
    arthasgxy  
       2018-06-15 12:18:33 +08:00
    @lixm
    http://chuantu.biz/t6/328/1529036276x-1404792211.jpg

    求助,不知道为什么我这里运行会这样
    arthasgxy
        25
    arthasgxy  
       2018-06-15 12:36:07 +08:00
    https://gist.github.com/arthasgxy/9d1f8aae0c1e90dde5ec5e44032be4f5

    字典用的少,感觉只能写出来这种又蠢又长的
    wsds
        26
    wsds  
    OP
       2018-06-15 13:31:58 +08:00
    @bufpay 发现越是看上去简单的功能,实现起来越是困难
    xpresslink
        27
    xpresslink  
       2018-06-15 13:59:48 +08:00
    >>> data = """a, 1.324171
    b, 0.000126
    c, 1.970941
    a, 1.469649
    b, 0.000124
    c, 0.512929
    a, 1.290920
    b, 0.000118
    c, 0.259524
    a, 0.495958
    b, 0.000123
    c, 0.910949
    a, 1.268038
    b, 0.000118
    c, 1.016419
    a, 1.856081
    b, 0.000120
    c, 1.400075
    a, 1.314131
    b, 0.000140"""
    >>> import csv
    >>> from itertools import groupby
    >>> from operator import itemgetter as ig
    >>> {k:sum(map(lambda x:float(ig(1)(x)), v)) for k, v in groupby(sorted(csv.reader(iter(data.splitlines())), key=ig(0)), key=ig(0))}
    {'a': 9.018948, 'b': 0.000869, 'c': 6.070837}
    >>>
    Xiaobaixiao
        28
    Xiaobaixiao  
       2018-06-15 15:14:39 +08:00
    from collections import defaultdict

    logData='''a, 1.324171
    b, 0.000126
    c, 1.970941
    a, 1.469649
    b, 0.000124
    c, 0.512929
    a, 1.290920
    b, 0.000118
    c, 0.259524
    a, 0.495958
    b, 0.000123
    c, 0.910949
    a, 1.268038
    b, 0.000118
    c, 1.016419
    a, 1.856081
    b, 0.000120
    c, 1.400075
    a, 1.314131
    b, 0.000140'''

    def solve(logData):
    logList=[]
    logDict=defaultdict(int)
    for line in logData.splitlines():
    newList = line.split(',')
    k=newList[0]
    v=float(newList[1])
    logList.append(k)
    logDict[k]+=v
    for k,v in logDict.items():
    avg = v/logList.count(k)
    print("{0} 总和:{1} , 平均值:{2}".format(k,v,avg))


    >>> solve(logData)
    a 总和:9.018948 , 平均值:1.2884211428571428
    b 总和:0.000869 , 平均值:0.00012414285714285714
    c 总和:6.070837 , 平均值:1.0118061666666667
    zhang0320
        29
    zhang0320  
       2018-06-15 15:20:00 +08:00
    with open('data.txt', 'r') as f:
    data = f.read()
    dict_data = {}
    for i in data.split('\n'):
    if i.split(',')[0] not in dict_data:
    dict_data[i.split(',')[0]]=float(i.split(',')[1])
    dict_data[i.split(',')[0]]=dict_data[i.split(',')[0]]+float(i.split(',')[1])

    print(dict_data)



    我是个新手菜鸟,不知道这种想法对不对。。。
    zhang0320
        30
    zhang0320  
       2018-06-15 15:24:06 +08:00
    with open('data.txt', 'r') as f:
    data = f.read()
    dict_data = {}
    for i in data.split('\n'):
    if i.split(',')[0] not in dict_data:
    dict_data[i.split(',')[0]] = float(i.split(',')[1])
    else:
    dict_data[i.split(',')[0]] = dict_data[i.split(',')[0]] + float(i.split(',')[1])

    print(dict_data)


    不好意思 忘了个 else:
    Alexhex
        31
    Alexhex  
       2018-06-15 15:26:18 +08:00
    拷到 Excel 里一个数据透视表搞定美滋滋。
    ful1v1dcker
        32
    ful1v1dcker  
       2018-06-15 15:31:59 +08:00
    什么鬼,V 站 markdown 失效了?全是代码坨啊。。。
    reself
        33
    reself  
       2018-06-15 15:33:22 +08:00 via Android
    @araraloren 哈哈 perl 自带代码混淆
    araraloren
        34
    araraloren  
       2018-06-15 15:37:12 +08:00
    @ful1v1dcker 本来就是这样,只支持楼主的。。不然还需要什么 chrome markdown 插件(外面那个帖子)
    JCZ2MkKb5S8ZX9pq
        35
    JCZ2MkKb5S8ZX9pq  
       2018-06-15 15:57:18 +08:00
    d = {}
    逐行
    k, v = (i.strip() for i in text.split(','))
    d.setdefault(k, []) # 建个列表
    d[k].append(float(v))

    这样直观一点,然后求值啥的慢慢折腾呗。
    lixm
        36
    lixm  
       2018-06-15 16:48:31 +08:00
    @arthasgxy 因为是 yield, 所以是一个生成器
    gnozix
        37
    gnozix  
       2018-06-15 17:58:27 +08:00
    我意思一下:
    ```python
    temp = {}
    for i, j in dict or tuple:
    if i in temp:
    temp[i] = float(j)
    else:
    temp[i] += float(j)
    ```
    ful1v1dcker
        38
    ful1v1dcker  
       2018-06-15 17:58:45 +08:00
    @araraloren 噢好吧,果然没用最垃圾只有更垃圾
    yaorc
        39
    yaorc  
       2018-06-15 18:26:46 +08:00
    def pivot_table():
    with open('data.txt', 'r') as f:
    all_data = f.readlines()[1:]
    keys = []
    result = {}
    count = {}

    for data in all_data:
    content = data.split(',')
    key = content[0]
    value = float(content[1].strip())

    # 添加键
    if key not in keys:
    keys.append(key)
    result[key] = value
    count[key] = 1
    else:
    result[key] += value
    count[key] += 1

    print('元素:', keys)
    print('元素个数:', count)
    print('和:', result)

    print('\n 统计信息(元素,和,平均值):')
    for k, v in result.items():
    avg = v / count[k]
    print(k, v, avg)


    ----------输出-----------
    元素: ['a', 'b', 'c']
    元素个数: {'a': 7, 'b': 7, 'c': 6}
    和: {'a': 9.018948, 'b': 0.000869, 'c': 6.070837}

    统计信息(元素,和,平均值):
    a 9.018948 1.2884211428571428
    b 0.000869 0.00012414285714285714
    c 6.070837 1.0118061666666667
    inter18099
        40
    inter18099  
       2018-06-15 20:53:16 +08:00
    def two(file):

    num_dict = {}
    with open(file, "r", encoding="utf-8") as f:
    for i in f.readlines():
    a = i.replace("\n", '').strip()
    line_list = a.split(",")
    if line_list[0] not in num_dict:
    num_dict[line_list[0]] = [line_list[1], 1]
    else:
    num_dict[line_list[0]] = [float(num_dict[line_list[0]][0]) + float(line_list[1]), int(num_dict[line_list[0]][1]) + 1]
    for x in num_dict:
    num_dict[x].append(num_dict[x][0] / num_dict[x][1])
    print(num_dict)


    two("/Users/yourname/program/test/test.log")
    UnluckyNinja
        41
    UnluckyNinja  
       2018-06-15 21:49:22 +08:00
    def text = '''a, 1.324171
    b, 0.000126
    c, 1.970941
    a, 1.469649
    b, 0.000124
    c, 0.512929
    a, 1.290920
    b, 0.000118
    c, 0.259524
    a, 0.495958
    b, 0.000123
    c, 0.910949
    a, 1.268038
    b, 0.000118
    c, 1.016419
    a, 1.856081
    b, 0.000120
    c, 1.400075
    a, 1.314131
    b, 0.000140
    '''

    // file.readLines().collect{
    text.readLines().collect{
    it.split(',')*.trim()
    }.groupBy{
    it[0]
    }.collectEntries{k, vList ->
    [(k): [sum: def sum = vList.sum{ it[1] as BigDecimal }, average: sum / vList.size()]]
    }

    /* result: [a:[sum:9.018948, average:1.2884211429], b:[sum:0.000869, average:0.0001241429], c:[sum:6.070837, average:1.0118061667]]

    groovy 写的,groovy 有的 python 肯定有,语法方法名啥的改一下应该就差不多了 */
    Binb
        42
    Binb  
       2018-06-16 10:16:44 +08:00
    #!/usr/bin/env python
    # -*- coding: utf-8 -*-

    a = {}
    with open('test.log','r') as f:
    for i in f:
    j = i.split(',')
    a.setdefault(j[0],[]).append(float(j[1]))

    result = {}
    for k,v in a.items():
    s = sum(v)
    result.setdefault(k,[]).append(s)
    result[k].append(s/len(v))

    print result
    # {'a': [9.018948, 1.2884211428571428], 'c': [6.070837, 1.0118061666666667], 'b': [0.000869, 0.00012414285714285714]}
    NICCEEEE
        43
    NICCEEEE  
       2018-06-16 17:21:39 +08:00
    import collections

    d = """a, 1.324171
    b, 0.000126
    c, 1.970941
    a, 1.469649
    b, 0.000124
    c, 0.512929
    a, 1.290920
    b, 0.000118
    c, 0.259524
    a, 0.495958
    b, 0.000123
    c, 0.910949
    a, 1.268038
    b, 0.000118
    c, 1.016419
    a, 1.856081
    b, 0.000120
    c, 1.400075
    a, 1.314131
    b, 0.000140"""

    L = [(i[0], i[3:]) for i in d.split('\n')]
    data_dict = collections.defaultdict(int)

    for i, j in L:
    data_dict[i] += float(j)

    print(data_dict)
    yangxiaoyong
        44
    yangxiaoyong  
       2018-06-16 20:33:05 +08:00 via Android
    讲下原理的东西,map reduce 可以了解一下,首先把数据分组归类
    map (lambda x: { value: x.key, key: x.key, count: 1})
    按上面的把数据按 key 分组放好
    然后执行归约函数,将数据集合归约为一个最终结果
    reduce(lambda acc, curr: merge(acc,curr), mapdata )

    merge 根据 key 将相同 key 的数值相加得到总合,count 相加得到次数,总和除以次数可以得平均值

    最后的结果应该是 {a: { value,count,avg}}

    手机码字,凑合看吧
    bugcoder
        45
    bugcoder  
       2018-06-17 08:24:41 +08:00
    没人贴 pandas 的,我就献个丑吧:
    ···
    import pandas as pd

    data_file = 'data.txt'
    data_df = pd.read_csv(data_file, comment='#', names=['key', 'value'])

    sums = data_df.groupby('key').sum()
    means = data_df.groupby('key').mean()
    ···
    mingyun
        46
    mingyun  
       2018-07-15 11:55:11 +08:00
    @bugcoder 这个简单
    biglazycat
        47
    biglazycat  
       2020-09-06 22:09:24 +08:00
    convert_list = {}
    for line in open('test.log'):
    k, v = line.split(',')
    convert_list.setdefault(k,[]).append(float(v.strip()))

    # print(convert_list)
    for k, v in convert_list.items():
    total_sum = sum(v)
    avg = total_sum / len(v)
    print(total_sum)
    print(avg)
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