我有一个csv文件，如下所示：
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我想从此文件中提取几列，并将这些列写入其他文件中。如何通过使用python 2.7.5？
指定列名来从CSV中提取列我写了以下内容，但是写得不正确？
################################################################################
#...................Program to create reduced feature vector ...................
################################################################################
import ast
import csv
import os
import sys
from string import *
from BST import Node
import ast
import sys,time
sys.setrecursionlimit(20100)
def File_Write(filename,write_ist):
filewrite=open(filename,"w")
filewrite.writerows(str(write_ist))
filewrite.close()
def read_file_list(feature_vector_file,selected_features) :
f = open("Dataset/Cross/Ensemble_FVT.csv")
reader = csv.reader(f)
headers = None
results = []
for row in reader:
if not headers:
headers = []
for i, col in enumerate(row):
## print i,col
if col in selected_features:
## print col
# Store the index of the cols of interest
headers.append(i)
else:
## print headers
results.append(list([row[i] for i in headers]))
## print results
return results
##################################################################################
#.................................MAIN PROGRAM....................................
##################################################################################
feature_list = ""
root_flag = 'false'
sent_number = 1
fvt_length = 0
line=[]
result=[]
##Reading the class and feature_vector_length from command line .......................
gender = sys.argv[1]
max_fvt_length = sys.argv[2]
##Setting the path for input and output files .......................
file_path = "/home/user/Mini_Project/Dataset/Cross/Sorted_Features.csv" ;##Input file..............
feature_vector_file = "/home/user/Mini_Project/Dataset/Cross/"+str(max_fvt_length+gender)+".csv" ;##Output file..............
##Creating the output directory if not existing .......................
d = os.path.dirname(feature_vector_file)
if not os.path.exists(d) :
os.makedirs(d)
####Opening the output file in write mode ...................
with open( feature_vector_file, "w" ) as fout :
fp_feature = csv.writer( fout )
fp_mi=csv.reader(open(file_path,"r"),delimiter=',')
for row in fp_mi :
## First field contains the feature and second field contains the feature_rank ..................
feature = row[0]
## Taking the top features only ...................
if int(fvt_length) < int(max_fvt_length) :
## print fvt_length
## Checking for root node in the BST ...................
if root_flag == 'false' :
root = Node( feature )
root_flag = 'true'
else :
root.insert( feature )
feature_list = feature_list + "\n" + feature
fvt_length += 1
feature_list1 = feature_list.strip()
line = feature_list1.split('\n')
## print "Number of features ",fvt_length
## line.sort()
line.append('Gender')
root.print_tree()
fp_feature.writerow(line)
#### Read files in separate classes and find the count of features in each class ...................
result=read_file_list(feature_vector_file,line)
fp_feature.writerows(result)
print "Extracted",fvt_length,"Features ranked using Mutual Information"
答案 0 :(得分：1)
f = open("Dataset/Cross/Ensemble_FVT.csv", "r")
reader = csv.reader(f)
现在您可以遍历reader。
for row in reader:
# here you'll get individual item of a particular row and column
print row["print_desired_column_number"]
如果在循环中使用row[0]，则会打印出第一列。
并且要在新的csv文件中编写所需的列，您可以使用所需的行列项在循环中填充列表，并使用_csv.writer对象writerow方法将列表作为行写入。
让我们说你要写第1,3和5栏。然后，
data = open("output.csv", "w")
w = csv.writer(data)
for row in reader:
my_row = []
my_row.append(row[0])
my_row.append(row[2])
my_row.append(row[4])
w.writerow(my_row)
现在，您将获得新的csv文件作为output.csv。