Question

我试图在不使用Panda的情况下获得此解决方案（右下方），基本上我想要做的是获得健康患者和患者的平均值在CSV文件中。该文件有303名患者，有14个类别（因此有13行）有些数据缺失，因此用？的第13行代替将患者与健康状况分开，大于0的患者生病，任何=或低于0的健康状况。我找到了分裂它们的方法，但我知道如何将这些线加起来分别得到健康患者和患者的平均值。关于如何进行的任何想法都很棒

 Please enter a training file name: train.csv
    Total Lines Processed: 303
    Total Healthy Count: 164
    Total Ill Count: 139
    Averages of Healthy Patients:
    [52.59, 0.56, 2.79, 129.25, 242.64, 0.14, 0.84, 158.38, 0.14, 0.59, 1.41, 0.27, 3.77, 0.00]
    Averages of Ill Patients:
    [56.63, 0.82, 3.59, 134.57, 251.47, 0.16, 1.17, 139.26, 0.55, 1.57, 1.83, 1.13, 5.80, 2.04]
    Seperation Values are:
    [54.61, 0.69, 3.19, 131.91, 247.06, 0.15, 1.00, 148.82, 0.34, 1.08, 1.62, 0.70, 4.79, 1.02]

我仍然有很长的路要走我的代码，我只是在寻找一种简单的方法来获得患者的平均值。我目前的方法只获得第13列，但我需要所有13个如上所述。任何有关我应该尝试解决这个问题的方法的帮助都会非常棒，非常感激。

import csv
#turn csv files into a list of lists
with open('train.csv') as csvfile:
     reader = csv.reader(csvfile, delimiter=',')
     csv_data = list(reader)

i_list = []
for row in csv_data:
    if (row and int(row[13]) > 0):
        i_list.append(int(row[13]))
H_list = []
for row in csv_data:
    if (row and int(row[13]) <= 0):
        H_list.append(int(row[13]))
for row in reader:

Icount = len(i_list)
IPavg = sum(i_list)/len(i_list)
Hcount = len(H_list)
HPavg = sum(H_list)/len(H_list)
file = open("train.csv")
numline = len(file.readlines())

print(numline)
print("Total amount of healthy patients " + str(Icount))
print("Total amount of ill patients " + str(Hcount))
print("Averages of healthy patients " + str(HPavg))
print("Averages of ill patients " + str(IPavg)

评论中提出的问题的例子

CVS File
A         B        C       D   N(so on to column 13) 
10        .50      ?       44   0
4         4.5      20      34   0
12         ?       33      23   3 (this one would be Ill patient)
11         3.2     32       33   0
[![CSVfile][1]][1]

屏幕截图

Answer 1

这是教程（评论）的完整内容。如果你想了解如何掌握python，请仔细阅读它们。

import csv

#turn csv files into a list of lists
with open('train.csv','rU') as csvfile:
     reader = csv.reader(csvfile)
     csv_data = list(reader)

# Create two lists to handle the patients
# And two more lists to collect the 'sum' of the columns
# The one that needs to hold the sum 'must' have 0 so we 
# can work with them more easily
iList = []
iList_sum = [0,0,0,0,0,0,0,0,0,0,0,0,0]

hList = []
hList_sum = [0,0,0,0,0,0,0,0,0,0,0,0,0]

# Only use one loop to make the process mega faster
for row in csv_data:
    # If row 13 is greater than 0, then place them as unhealthy
    if (row and int(row[13]) > 0):
        # This appends the whole 'line'/'row' for storing :)
        # That's what you want (instead of saving only one cell at a time)
        iList.append(row)

    # If it failed the initial condition (greater than 0), then row 13
    # is either less than or equal to 0. That's simply the logical outcome
    else:
        hList.append(row)

# Use these to verify the data and make sure we collected the right thing
# print iList
# [['67', '1', '4', '160', '286', '0', '2', '108', '1', '1.5', '2', '3', '3', '2'], ['67', '1', '4', '120', '229', '0', '2', '129', '1', '2.6', '2', '2', '7', '1']]
# print hList
# [['63', '1', '1', '145', '233', '1', '2', '150', '0', '2.3', '3', '0', '6', '0'], ['37', '1', '3', '130', '250', '0', '0', '187', '0', '3.5', '3', '0', '3', '0']]

# We can use list comprehension, but since this is a beginner task, let's go with basics:

# Loop through all the 'rows' of the ill patient 
for ill_data in iList:

    # Loop through the data within each row, and sum them up
    for i in range(0,len(ill_data) - 1):
        iList_sum[i] += float(ill_data[i])


# Now repeat the process for healthy patient
# Loop through all the 'rows' of the healthy patient 
for healthy_data in hList:

    # Loop through the data within each row, and sum them up
    for i in range(0,len(healthy_data) - 1):
        hList_sum[i] += float(ill_data[i])

# Using list comprehension, I basically go through each number
# In ill list (sum of all columns), and divide it by the lenght of iList that
# I found from the csv file. So, if there are 22 ill patients, then len(iList) will
# be 22. You can see that the whole thing is wrapped in brackets, so it would show
# as a python list

ill_avg = [ ill / len(iList) for ill in iList_sum]
hlt_avg = [ hlt / len(hList) for hlt in hList_sum]

# Do whatever....

CSV Python列/行平均值

1 个答案: