obtenir la valeur maximale de chaque colonne du fichier csv

Question

Quelqu'un pourrait-il m'aider à résoudre le problème suivant. Je l'ai essayé moi-même et j'ai joint la solution aussi. J'ai utilisé la liste 2-d, mais je veux une solution différente sans liste 2-d, ce qui devrait être plus pythonique.

pl suggérer moi l'un de vous avez une autre façon de le faire.

Q) Envisager les prix des actions d'un nombre N de sociétés donné pour chaque mois depuis 1990 dans un fichier CSV. Le format du fichier est comme ci-dessous avec la première ligne comme en-tête.

Année, Mois, Société A, Société B, C Company, ............. Société N

1990, Jan, 10, 15, 20, ... ......., 50

1990, février, 10, 15, 20, .........., 50

.

.

.

.

2013, sept 50, 10, 15 ............ 500

La solution doit être dans ce format. a) Liste pour chaque année et mois de société où le cours de l'action était le plus élevé.

Voici ma réponse en utilisant la liste 2-d.

def generate_list(file_path): 
    ''' 
     return list of list's containing file data.''' 

    data_list=None #local variable  
    try: 
     file_obj = open(file_path,'r') 
     try: 
      gen = (line.split(',') for line in file_obj) #generator, to generate one line each time until EOF (End of File) 
      for j,line in enumerate(gen): 
       if not data_list: 
        #if dl is None then create list containing n empty lists, where n will be number of columns. 
        data_list = [[] for i in range(len(line))] 
        if line[-1].find('\n'): 
         line[-1] = line[-1][:-1] #to remove last list element's '\n' character 

       #loop to convert numbers from string to float, and leave others as strings only 
       for i,l in enumerate(line): 
        if i >=2 and j >= 1: 
         data_list[i].append(float(l)) 
        else:    
         data_list[i].append(l) 
     except IOError, io_except: 
      print io_except 
     finally: 
      file_obj.close() 
    except IOError, io_exception: 
     print io_exception 

    return data_list 

def generate_result(file_path): 
    ''' 
     return list of tuples containing (max price, year, month, 
company name). 
    ''' 
    data_list = generate_list(file_path) 
    re=[] #list to store results in tuple formet as follow [(max_price, year, month, company_name), ....] 
    if data_list: 
     for i,d in enumerate(data_list): 
      if i >= 2: 
       m = max(data_list[i][1:])  #max_price for the company 
       idx = data_list[i].index(m) #getting index of max_price in the list 
       yr = data_list[0][idx]   #getting year by using index of max_price in list 
       mon = data_list[1][idx]  #getting month by using index of max_price in list 
       com = data_list[i][0]   #getting company_name 
       re.append((m,yr,mon,com)) 
     return re 


if __name__ == '__main__': 
    file_path = 'C:/Document and Settings/RajeshT/Desktop/nothing/imp/New Folder/tst.csv' 
    re = generate_result(file_path) 
    print 'result ', re 

I have tried to solve it with generator also, but in that case it was giving result for only one company i.e. only one column.

p = 'filepath.csv' 

f = open(p,'r') 
head = f.readline() 
gen = ((float(line.split(',')[n]), line.split(',',2)[0:2], head.split(',')[n]) for n in range(2,len(head.split(','))) for i,line in enumerate(f)) 
x = max((i for i in gen),key=lambda x:x[0]) 
print x 

vous pouvez prendre les données d'entrée fournies ci-dessous qui est au format csv ..

year,month,company 1,company 2,company 3,company 4,company 5 
1990,jan,201,245,243,179,133 
1990,feb,228,123,124,121,180 
1990,march,63,13,158,88,79 
1990,april,234,68,187,67,135 
1990,may,109,128,46,185,236 
1990,june,53,36,202,73,210 
1990,july,194,38,48,207,72 
1990,august,147,116,149,93,114 
1990,september,51,215,15,38,46 
1990,october,16,200,115,205,118 
1990,november,241,86,58,183,100 
1990,december,175,97,143,77,84 
1991,jan,190,68,236,202,19 
1991,feb,39,209,133,221,161 
1991,march,246,81,38,100,122 
1991,april,37,137,106,138,26 
1991,may,147,48,182,235,47 
1991,june,57,20,156,38,245 
1991,july,165,153,145,70,157 
1991,august,154,16,162,32,21 
1991,september,64,160,55,220,138 
1991,october,162,72,162,222,179 
1991,november,215,207,37,176,30 
1991,december,106,153,31,247,69 

résultat attendu suit.

[(246.0, '1991', 'march', 'company 1'), 
(245.0, '1990', 'jan', 'company 2'), 
(243.0, '1990', 'jan', 'company 3'), 
(247.0, '1991', 'december', 'company 4'), 
(245.0, '1991', 'june', 'company 5')] 

Merci à l'avance ...

Answer 1

En utilisant collections.OrderedDict et collections.namedtuple:

import csv 
from collections import OrderedDict, namedtuple 

with open('abc1') as f: 
    reader = csv.reader(f) 
    tup = namedtuple('tup', ['price', 'year', 'month']) 
    d = OrderedDict() 
    names = next(reader)[2:] 
    for name in names: 
     #initialize the dict 
     d[name] = tup(0, 'year', 'month') 
    for row in reader: 
     year, month = row[:2]   # Use year, month, *prices = row in py3.x 
     for name, price in zip(names, map(int, row[2:])): # map(int, prices) py3.x 
      if d[name].price < price: 
       d[name] = tup(price, year, month) 
print d   

Sortie:

OrderedDict([ 
('company 1', tup(price=246, year='1991', month='march')), 
('company 2', tup(price=245, year='1990', month='jan')), 
('company 3', tup(price=243, year='1990', month='jan')), 
('company 4', tup(price=247, year='1991', month='december')), 
('company 5', tup(price=245, year='1991', month='june'))]) 

Answer 2

je n'étais pas tout à fait sûr de savoir comment vous vouliez sortie donc pour l'instant je viens de le faire imprimer la sortie à l'écran.

import os 
import csv 
import codecs 


## Import data !!!!!!!!!!!! CHANGE TO APPROPRIATE PATH !!!!!!!!!!!!!!!!! 
filename= os.path.expanduser("~/Documents/PYTHON/StackTest/tailor_raj/Workbook1.csv") 

## Get useable data 
data = [row for row in csv.reader(codecs.open(filename, 'rb', encoding="utf_8"))] 

## Find Number of rows 
row_count= (sum(1 for row in data)) -1 

## Find Number of columns 
    ## Since this cannot be explicitly done, I set it to run through the columns on one row until it fails. 
    ## Failure is caught by try/except so the program does not crash 
columns_found = False 
column_try =1 
while columns_found == False: 
    column_try +=1 
    try: 
     identify_column = data[0][column_try] 
    except: 
     columns_found=True 
## Set column count to discoverd column count (1 before it failed) 
column_count=column_try-1 

## Set which company we are checking (start with the first company listed. Since it starts at 0 the first company is at 2 not 3) 
companyIndex = 2 

#This will keep all the company bests as single rows of text. I was not sure how you wanted to output them. 
companyBest=[] 

## Set loop to go through each company 
while companyIndex <= (column_count): 

    ## For each new company reset the rowIndex and highestShare 
    rowIndex=1 
    highestShare=rowIndex 

    ## Set loop to go through each row 
    while rowIndex <=row_count: 
     ## Test if data point is above or equal to current max 
     ## Currently set to use the most recent high point 
     if int(data[highestShare][companyIndex]) <= int(data[rowIndex][companyIndex]): 
      highestShare=rowIndex 

     ## Move on to next row 
     rowIndex+=1 

    ## Company best = Company Name + year + month + value 
    companyBest.append(str(data[0][companyIndex])+": "+str(data[highestShare][0]) +", "+str(data[highestShare][1])+", "+str(data[highestShare][companyIndex])) 

    ## Move on to next company 
    companyIndex +=1 

for item in companyBest: 
    print item 

Assurez-vous de changer le chemin de votre nom de fichier un plus approprié.

La sortie est affichée comme ceci:

Company A: 1990, nov 1985

Société B: 1990, mai 52873

Société C: 1990, mai 3658

Company D: 1990, nov 156498

Company E: 1990, juil 987

Answer 3

Aucun générateur, malheureusement, mais petite taille de code, en particulier en Python 3:

from operator import itemgetter 
from csv import reader 

with open('test.csv') as f: 
    year, month, *data = zip(*reader(f)) 

for pricelist in data: 
    name = pricelist[0] 
    prices = map(int, pricelist[1:]) 
    i, price = max(enumerate(prices), key=itemgetter(1)) 
    print(name, price, year[i+1], month[i+1]) 

En Python 2.X vous pouvez faire la même chose, mais un peu plus maladroit, en utilisant les éléments suivants (et les différents déclaration d'impression):

with open('test.csv') as f: 
    columns = zip(*reader(f)) 
    year, month = columns[:2] 
    data = columns[2:] 

---

Ok je suis venu avec des générateurs macabres! il est également l'utilisation de comparaison de tuple lexicographique et reduce pour comparer les lignes consécutives:

from functools import reduce # only in Python 3 
import csv 

def group(year, month, *prices): 
    return ((int(p), year, month) for p in prices) 

def compare(a, b): 
    return map(max, zip(a, group(*b))) 

def run(fname): 
    with open(fname) as f: 
     r = csv.reader(f) 
     names = next(r)[2:] 
     return zip(names, reduce(compare, r, group(*next(r)))) 

list(run('test.csv'))