如何在Python中从csv文件的特定列打​​印前366行

Question

我的csv文件有两列，第一列是日期，第二列是该日期的平均温度。我试图使我的代码仅从第二列（第1-366行）中打印第一年的数据，但是我很难找到一种方法来执行此操作。我希望代码能够打印前几年的行以及标题为“是第一年是2010年”的标题。

这是我使用的控制器：

import FunctionLibrary
ConfigData = FunctionLibrary.CSV_Read('CSV.csv')
#print(ConfigData)
Data = FunctionLibrary.CSV_Read('CSV.csv')
a=FunctionLibrary.MeanCalc([1:365])
print(a)

这是函数库：

import csv
from matplotlib import pyplot
import numpy as np
from os.path import isfile
import math
import statistics
from collections import defaultdict
from csv import reader

data=defaultdict(list)
with open ('CSV.csv') as f:
    rd = csv.DictReader(f)
    for i in rd:
         for j in i.keys():
             data[j].append(i[j])
#print({k:v for k,v in data.items()})
def col_extract(FileName):
    reader= csv.reader(FileName, delimiter=' ')
    included_cols=[1,2]
    for row in reader:
        content = list(row[1:366] for i in inculded_cols)
        return content
#print(col_extract('CSV.csv'))

def CSV_Read(FileName):
    with open(FileName) as csv_file:
        csv_reader = csv.reader(csv_file, delimiter=',')
        line_count = 0
        for row in csv_reader:
            if line_count==0:
                Header=row
                lstf=[[] for i in range(len(Header))]
            else:
                index=0
                for item in row:
                    lstf[index].append(item)
                    index+=1
            line_count += 1
    return [line_count-1, Header, lstf]

def Trend(Data, ColNum1, ColNum2):
    z=np.polyfit([float(item) for item in Data[ColNum1]],[float(item) for 
item in Data[ColNum2]],1)
    return z

def CSV_Write(FileName, Data, Header):
    new = not isfile(FileName) #checks if the file exists
    #Potential improvement: if the file exists use your CSV_Read function to 
ensure the number of columns in Data match number of columns in file
    with open(FileName, 'a',newline='') as csvfile:
        writer = csv.writer(csvfile)
        if new:    writer.writerow(Header)
        resortedData = [[Data[i][r] for i in range(len(Data))]for r in 
range(len(Data[0]))] #convert the elements of the list from columns to rows
        for r in resortedData:
            writer.writerow(r)

def MeanCalc(FileName, x):
    #from filename import meantemp as d
    a=statistics.mean(FileName/365)
    return a
print(MeanCalc('CSV.csv',[2][1:366]))

如您所见，我尝试了多种功能，但似乎没有一种对我有用。