迭代 CSV 删除分析的数据

Question

您好，我正在尝试获取一个 CSV 文件并遍历每个客户数据。解释一下，每个客户都有 12 个月的数据。我想分析他们的年度数据，将这些数据的相关性保存到一个新列表中并循环，直到分析完所有客户。

例如，以下是客户数据的样子（简化情况）：

我已经能够让它工作以在一个客户数据的 CSV 中生成相关性。但是，我的数据表中有成千上万的客户。我想使用嵌套的 for 循环将每个客户的所有相关值放入列表/数组中。该列表将包含一行特定客户的相关性，然后下一行将是下一个客户。

这是我当前的代码：

import numpy
from numpy import genfromtxt
overalldata = genfromtxt('C:\Users\User V\Desktop\CUSTDATA.csv', delimiter=',')
emptylist = []
overalldatasubtract = overalldata[13::]
#This is where I try to use the four loop to go through all the customers. I     don't know if len will give me all the rows or the number of columns.
for x in range(0,len(overalldata),11):
    for x in range(0,13,1):
            cust_months = overalldata[0:x,1]
            cust_balancenormal = overalldata[0:x,16]
            cust_demo_one = overalldata[0:x,2]
            cust_demo_two = overalldata[0:x,3]
            num_acct_A = overalldata[0:x,4]
            num_acct_B = overalldata[0:x,5]
    #Correlation Calculations
            demo_one_corr_balance = numpy.corrcoef(cust_balancenormal, cust_demo_one)[1,0]
            demo_two_corr_balance = numpy.corrcoef(cust_balancenormal, cust_demo_two)[1,0]
            demo_one_corr_acct_a = numpy.corrcoef(num_acct_A, cust_demo_one)[1,0]
            demo_one_corr_acct_b = numpy.corrcoef(num_acct_B, cust_demo_one)[1,0]
            demo_two_corr_acct_a = numpy.corrcoef(num_acct_A, cust_demo_two)[1,0]
            demo_two_corr_acct_b = numpy.corrcoef(num_acct_B, cust_demo_two)[1,0]

            result_correlation = [demo_one_corr_balance, demo_two_corr_balance, demo_one_corr_acct_a, demo_one_corr_acct_b, demo_two_corr_acct_a, demo_two_corr_acct_b]

result_correlation_combined = emptylist.append(result_correlation)
#This is where I try to delete the rows I have already analyzed.
overalldata = overalldata[11**x::]

print result_correlation_combined
print overalldatasubtract

看起来我的减法方法是有效的，但是当我用更大的数据集尝试它时，我意识到我的方法完全错误。

你会以不同的方式来做这件事吗？我认为它可以工作，但我找不到我的错误。

Answer 1

您对两个循环使用相同的变量x。在第二个循环中，x 会从 0 变为 12，无论客户是谁，由于您仅使用 x 设置行号，因此您被困在第一个客户身上。

你的双循环应该是这样的：

# loop over the customers
for x_customer in range(0,len(overalldata),12):
    # loop over the months
    for x_month in range(0,12,1):
        # line number: x
        x = x_customer*12 + x_month
        ...

我更改了循环的边界和步骤，因为：

• 循环 1： 有 12 个月，因此每个客户 12 行 -> step = 12
• 循环 2： 有 12 个月，所以月份的范围是 0 到 11 -> range(0,12,1)

Answer 2

这就是我解决问题的方法：这是我的 for 循环放置的问题。一个简单的缩进问题。感谢您对以上海报的帮助。

对于范围内的 x_customer(0,len(overalldata),12)：

    for x in range(0,13,1):
            cust_months = overalldata[0:x,1]
            cust_balancenormal = overalldata[0:x,16]
            cust_demo_one = overalldata[0:x,2]
            cust_demo_two = overalldata[0:x,3]
            num_acct_A = overalldata[0:x,4]
            num_acct_B = overalldata[0:x,5]
#Correlation Calculations
            demo_one_corr_balance = numpy.corrcoef(cust_balancenormal, cust_demo_one)[1,0]
            demo_two_corr_balance = numpy.corrcoef(cust_balancenormal, cust_demo_two)[1,0]
            demo_one_corr_acct_a = numpy.corrcoef(num_acct_A, cust_demo_one)[1,0]
            demo_one_corr_acct_b = numpy.corrcoef(num_acct_B, cust_demo_one)[1,0]
            demo_two_corr_acct_a = numpy.corrcoef(num_acct_A, cust_demo_two)[1,0]
            demo_two_corr_acct_b = numpy.corrcoef(num_acct_B, cust_demo_two)[1,0]

            result_correlation = [(demo_one_corr_balance),(demo_two_corr_balance),(demo_one_corr_acct_a),(demo_one_corr_acct_b),(demo_two_corr_acct_a),(demo_two_corr_acct_b)]
            numpy.savetxt('correlationoutput.csv', (result_correlation))
    result_correlation_combined = emptylist.append([result_correlation])
    cust_delete_list = [0,(x_customer),1]
    overalldata = numpy.delete(overalldata, (cust_delete_list), axis=0)