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我正在从 netCDF 文件中读取数据并将其缩减为向量，然后将向量写入 csv 文件。数据重新格式化工作正常，但是当我尝试将数据写入 csv 时，它不会写入整个文件。事实上，它甚至不写一个 csv 文件，而是写一个通用的“文件”类型。

import numpy as np
import netCDF4
import os
import csv

'''
I'm importing the lists I need to automate file extraction from a seperate file
to reduce clutter
'''
from gmLists import files #Stores the different paths I need
from gmLists import variableNames #Stores names of variables
from gmLists import years #Years I have data for
from gmLists import urlPrefix #Used to get files
from gmLists import yearlyDataList #Used to store numpy arrays
#Used to store the names of the csv files to be created
from gmLists import csvFileNames 


for i in range(10):
    os.chdir(files[0]) #Read from here

    for j in range(16):
        #Name of specific file in directory
        url = urlPrefix[0] + str(years[j]) + ".nc" 
        temp = netCDF4.Dataset(url).variables[variableNames[i]][:,::] 


        dataYear = temp[:,179:408,10:235] 

        # do monthly mean here
        if(years[j]%4 != 0):
            January = np.mean(dataYear[0:31,::], axis=0)      
            February = np.mean(dataYear[31:59,::], axis=0)     
            March = np.mean(dataYear[59:90,::], axis=0)     
            April = np.mean(dataYear[90:120,::], axis=0)
            May = np.mean(dataYear[120:151,::], axis=0)
            June = np.mean(dataYear[151:181,::], axis=0)
            July = np.mean(dataYear[181:212,::], axis=0)
            August = np.mean(dataYear[212:243,::], axis=0)
            September = np.mean(dataYear[243:273,::], axis=0)
            October = np.mean(dataYear[273:304,::], axis=0)
            November = np.mean(dataYear[304:334,::], axis=0)
            December = np.mean(dataYear[334:365,::], axis=0)
        else:
           # for leap year
           January = np.mean(dataYear[0:31,::], axis=0)     
           February = np.mean(dataYear[31:60,::], axis=0)     
           March = np.mean(dataYear[60:91,::], axis=0)     
           April = np.mean(dataYear[91:121,::], axis=0)
           May = np.mean(dataYear[121:152,::], axis=0)
           June = np.mean(dataYear[152:182,::], axis=0)
           July = np.mean(dataYear[182:213,::], axis=0)
           August = np.mean(dataYear[213:244,::], axis=0)
           September = np.mean(dataYear[244:274,::], axis=0)
           October = np.mean(dataYear[274:305,::], axis=0)
           November = np.mean(dataYear[305:335,::], axis=0)
           December = np.mean(dataYear[335:366,::], axis=0)

    monthlyData = np.stack([January, February, March, April, May, June, July, 
                            August, September, October, November, December], 
                            axis=0)

    yearlyDataList.append(monthlyData)


totalMonthlyData = np.vstack([yearlyDataList[0], yearlyDataList[1], 
yearlyDataList[2], yearlyDataList[3], yearlyDataList[4], yearlyDataList[5],
yearlyDataList[6], yearlyDataList[7], yearlyDataList[8], yearlyDataList[9],
yearlyDataList[10], yearlyDataList[11], yearlyDataList[12], 
yearlyDataList[13], yearlyDataList[14], yearlyDataList[15]]) 

# flatten the array to vector
flattenedMonthlyData = np.reshape(totalMonthlyData, (np.product(totalMonthlyData.shape),))

#The below code is where I think the problem is
os.chdir('saveDirectory') # your save destination

csvfile = csvFileNames[0]

with open(csvfile, "w") as output:
    writer = csv.writer(output, lineterminator='\n')
    for val in flattenedMonthlyData:
        writer.writerow([val])

我希望我没有包含太多代码。我知道读取 netCDF 文件并重新格式化它的代码是正确的。我包含了该代码，以防有一些交互弄脏了我没有看到的东西。

在我添加循环机制之前，我成功地生成了一个 csv 文件，但是从那时起，当我运行代码时，生成的文件比我的一个好的 csv 文件小 5000 KB，它们甚至不是 csv 文件。它们是一些通用文件类型。即使我尝试倒退并删除循环，我也无法重现我之前的成功。任何帮助将不胜感激。

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