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how to select a specific column of a csv file in python

I am a beginner of Python and would like to have your opinion..
I wrote this code that reads the only column in a file on my pc and puts it in a list.
I have difficulties understanding how I could modify the same code with a file that has multiple columns and select only the column of my interest.
Can you help me?
list = []
with open(r'C:\Users\Desktop\mydoc.csv') as file:
for line in file:
item = int(line)
list.append(item)
results = []
for i in range(0,1086):
a = list[i-1]
b = list[i]
c = list[i+1]
results.append(b)
print(results)

You can use pandas.read_csv() method very simply like this:
import pandas as pd
my_data_frame = pd.read_csv('path/to/your/data')
results = my_data_frame['name_of_your_wanted_column'].values.tolist()

A useful module for the kind of work you are doing is the imaginatively named csv module.
Many csv files have a "header" at the top, this by convention is a useful way of labeling the columns of your file. Assuming you can insert a line at the top of your csv file with comma delimited fieldnames, then you could replace your program with something like:
import csv
with open(r'C:\Users\Desktop\mydoc.csv') as myfile:
csv_reader = csv.DictReader(myfile)
for row in csv_reader:
print ( row['column_name_of_interest'])
The above will print to the terminal all the values that match your specific 'column_name_of_interest' after you edit it to match your particular file.
It's normal to work with lots of columns at once, so that dictionary method of packing a whole row into a single object, addressable by column-name can be very convenient later on.

To a pure python implementation, you should use the package csv.
data.csv
Project1,folder1/file1,data
Project1,folder1/file2,data
Project1,folder1/file3,data
Project1,folder1/file4,data
Project1,folder2/file11,data
Project1,folder2/file42a,data
Project1,folder2/file42b,data
Project1,folder2/file42c,data
Project1,folder2/file42d,data
Project1,folder3/filec,data
Project1,folder3/fileb,data
Project1,folder3/filea,data
Your python program should read it by line
import csv
a = []
with open('data.csv') as csv_file:
reader = csv.reader(csv_file, delimiter=',')
for row in reader:
print(row)
# ['Project1', 'folder1/file1', 'data']
If you print the row element you will see it is a list like that
['Project1', 'folder1/file1', 'data']
If I would like to put in my list all elements in column 1, I need to put that element in my list, doing:
a.append(row[1])
Now in list a I will have a list like:
['folder1/file1', 'folder1/file2', 'folder1/file3', 'folder1/file4', 'folder2/file11', 'folder2/file42a', 'folder2/file42b', 'folder2/file42c', 'folder2/file42d', 'folder3/filec', 'folder3/fileb', 'folder3/filea']
Here is the complete code:
import csv
a = []
with open('data.csv') as csv_file:
reader = csv.reader(csv_file, delimiter=',')
for row in reader:
a.append(row[1])

how to edit a csv in python and add one row after the 2nd row that will have the same values in all columns except 1

I'm new in Python language and i'm facing a small challenge in which i havent been able to figure it out so far.
I receive a csv file with around 30-40 columns and 5-50 rows with various details in each cell. The 1st row of the csv has the title for each column and by the 2nd row i have item values.
What i want to do is to create a python script which will read the csv file and every time to do the following:
Add a row after the actual 1st item row, (literally after the 2nd row, cause the 1st row is titles), and in that new 3rd row to contain the same information like the above one with one difference only. in the column "item_subtotal" i want to add the value from the column "discount total".
all the bellow rows should remain as they are, and save this modified csv as a new file with the word "edited" added in the file name.
I could really use some help because so far i've only managed to open the csv file with a python script im developing, but im not able so far to add the contents of the above row to that newly created row and replace that specific value.
Looking forward any help.
Thank you
Here Im attaching the CSV with some values changed for privacy reasons.
order_id,order_number,date,status,shipping_total,shipping_tax_total,fee_total,fee_tax_total,tax_total,discount_total,order_total,refunded_total,order_currency,payment_method,shipping_method,customer_id,billing_first_name,billing_last_name,billing_company,billing_email,billing_phone,billing_address_1,billing_address_2,billing_postcode,billing_city,billing_state,billing_country,shipping_first_name,shipping_last_name,shipping_address_1,shipping_address_2,shipping_postcode,shipping_city,shipping_state,shipping_country,shipping_company,customer_note,item_id,item_product_id,item_name,item_sku,item_quantity,item_subtotal,item_subtotal_tax,item_total,item_total_tax,item_refunded,item_refunded_qty,item_meta,shipping_items,fee_items,tax_items,coupon_items,order_notes,download_permissions_granted,admin_custom_order_field:customer_type_5
15001_TEST_2,,"2017-10-09 18:53:12",processing,0,0.00,0.00,0.00,5.36,7.06,33.60,0.00,EUR,PayoneCw_PayPal,"0,00",0,name,surname,,name.surname#gmail.com,0123456789,"address 1",,41541_TEST,location,,DE,name,surname,address,01245212,14521,location,,DE,,,1328,302,"product title",103,1,35.29,6.71,28.24,5.36,0.00,0,,"id:1329|method_id:free_shipping:3|method_title:0,00|total:0.00",,id:1330|rate_id:1|code:DE-MWST-1|title:MwSt|total:5.36|compound:,"id:1331|code:#getgreengent|amount:7.06|description:Launchcoupon for friends","text string",1,

You can also use pandas to manipulate the data from the csv like this:
import pandas
import copy
Read the csv file into a pandas dataframe:
df = pandas.read_csv(filename)
Make a deepcopy of the first row of data and add the discount total to the item subtotal:
new_row = copy.deepcopy(df.loc[1])
new_row['item_subtotal'] += new_row['discount total']
Concatenate the first 2 rows with the new row and then everything after that:
df = pandas.concat([df.loc[:1], new_row, df.loc[2:]], ignore_index=True)
Change the filename and write the out the new csv file:
filename = filename.strip('.csv') + 'edited.csv'
df.to_csv(filename)
I hope this helps! Pandas is great for cleanly handling massive amounts of data, but may be overkill for what you are trying to do. Then again, maybe not. It would help to see an example data file.

The first step is to turn that .csv into something that is a little easier to work with. Fortunately, python has the 'csv' module which makes it easy to turn your .csv file into a much nicer list of lists. The below will give you a way to both turn your .csv into a list of lists and turn the modified data back into a .csv file.
import csv
import copy
def csv2list(ifile):
"""
ifile = the path of the csv to be converted into a list of lists
"""
f = open(ifile,'rb')
olist=[]
c = csv.reader(f, dialect='excel')
for line in c:
olist.append(line) #and update the outer array
f.close
return olist
#------------------------------------------------------------------------------
def list2csv(ilist,ofile):
"""
ilist = the list of lists to be converted
ofile = the output path for your csv file
"""
with open(ofile, 'wb') as csvfile:
csvwriter = csv.writer(csvfile, delimiter=',',
quotechar='|', quoting=csv.QUOTE_MINIMAL)
[csvwriter.writerow(x) for x in ilist]
Now, you can simply copy list[1] and change the appropriate element to reflect your summed value using:
listTemp = copy.deepcopy(ilist[1])
listTemp[n] = listTemp[n] + listTemp[n-x]
ilist.insert(2,listTemp)
As for how to change the file name, just use:
import os
newFileName = os.path.splitext(oldFileName)[0] + "edited" + os.path.splitext(oldFileName)[1]
Hopefully this will help you out!

Best way to reverse lines in a csv file python

I want to know the best way to reverse the lines of a big csv file (+50000 lines) in python 2.7 and rewrite it, avoiding the first line.
input:
A;B;C
1;2;3
4;5;6
output
A;B;C
4;5;6
1;2;3
I need to know how to do it in a efficient way in python 2.7.
Thank you guys,
menchopez

read the csv file using csv module and open the output also using csv module. Now you're working with lists as rows.
Use next to write the title line as-is. Now that the first line is consumed, convert the rest of the data into a list to read it fully and apply writerows on the reversed list:
import csv
with open("in.csv") as fr, open("out.csv","wb") as fw:
cr = csv.reader(fr,delimiter=";")
cw = csv.writer(fw,delimiter=";")
cw.writerow(next(cr)) # write title as-is
cw.writerows(reversed(list(cr)))
writerows is the fastest way of doing it, because it involves no python loops.
Python 3 users have to open the output file using open("out.csv","w",newline="") instead.

If you can use external libraries, the pandas library is good for large files:
import pandas as pd
# load the csv and user row 0 as headers
df = pd.read_csv("filepath.csv", header = 0)
# reverse the data
df.iloc[::-1]
If you cannot use external libraries:
import csv
with open("filepath.csv") as csvFile:
reader = csv.reader(csvFile)
# get data
data = [row for row in reader]
# get headers and remove from data
headers = data.pop(0)
# reverse the data
data_reversed = data[::-1]
# append the reversed data to the list of headers
output_data = headers.append(data_reversed)

Read as follows:
rows = []
first = True
for row in reader:
if first:
first = False
first_row = row
continue
rows.append(row)
write as follows:
rows.append(first_row)
writer.writerows(rows[::-1])

How can I read only the header column of a CSV file using Python?

I am looking for a a way to read just the header row of a large number of large CSV files.
Using Pandas, I have this method available, for each csv file:
>>> df = pd.read_csv(PATH_TO_CSV)
>>> df.columns
I could do this with just the csv module:
>>> reader = csv.DictReader(open(PATH_TO_CSV))
>>> reader.fieldnames
The problem with these is that each CSV file is 500MB+ in size, and it seems to be a gigantic waste to read in the entire file of each just to pull the header lines.
My end goal of all of this is to pull out unique column names. I can do that once I have a list of column headers that are in each of these files.
How can I extract only the header row of a CSV file, quickly?

Expanding on the answer given by Jeff It is now possbile to use pandas without actually reading any rows.
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: pd.DataFrame(np.random.randn(10, 4), columns=list('abcd')).to_csv('test.csv', mode='w')
In [4]: pd.read_csv('test.csv', index_col=0, nrows=0).columns.tolist()
Out[4]: ['a', 'b', 'c', 'd']
pandas can have the advantage that it deals more gracefully with CSV encodings.

I might be a little late to the party but here's one way to do it using just the Python standard library. When dealing with text data, I prefer to use Python 3 because unicode. So this is very close to your original suggestion except I'm only reading in one row rather than the whole file.
import csv
with open(fpath, 'r') as infile:
reader = csv.DictReader(infile)
fieldnames = reader.fieldnames
Hopefully that helps!

I've used iglob as an example to search for the .csv files, but one way is to use a set, then adjust as necessary, eg:
import csv
from glob import iglob
unique_headers = set()
for filename in iglob('*.csv'):
with open(filename, 'rb') as fin:
csvin = csv.reader(fin)
unique_headers.update(next(csvin, []))

Here's one way. You get 1 row.
In [9]: DataFrame(np.random.randn(10,4),columns=list('abcd')).to_csv('test.csv',mode='w')
In [10]: read_csv('test.csv',index_col=0,nrows=1)
Out[10]:
a b c d
0 0.365453 0.633631 -1.917368 -1.996505

What about:
pandas.read_csv(PATH_TO_CSV, nrows=1).columns
That'll read the first row only and return the columns found.

you have missed nrows=1 param to read_csv
>>> df= pd.read_csv(PATH_TO_CSV, nrows=1)
>>> df.columns

it depends on what the header will be used for, if you needed the headers for comparison purposes only (my case) this code will be simple and super fast, it will read the whole header as one string. you can transform all the collected strings together according to your needs:
for filename in glob.glob(files_path+"\*.csv"):
with open(filename) as f:
first_line = f.readline()

it is easy you can use this:
df = pd.read_csv("path.csv", skiprows=0, nrows=2)
df.columns.to_list()
In this case you can only read really few row for get your header

if you are only interested in the headers and would like to use pandas, the only extra thing you need to pass in apart from the csv file name is "nrows=0":
headers = pd.read_csv("test.csv", nrows=0)

import pandas as pd
get_col = list(pd.read_csv("first_test_pipe.csv",sep="|",nrows=1).columns)
print(get_col)

Python - Printing individual cells from an Excel spreadsheet in CSV format

I have an excel spreadsheet saved as a CSV file, but cannot find a way to call individual values from cells into Python using the CSV module. Any help would be greatly appreciated

There is also a Python library capable of reading xls data. Have a look at python-xlrd.
For writing xls data, you can use python-xlwt.

The csv module provide readers that iterate over the rows of a csv file - the rows are lists of strings. One way to get access to individual cells would be to:
Read the entire file in as a list of lists
import csv
with open('test.csv', 'r') as f:
reader = csv.reader(f)
the_whole_file = list(reader)
Then access the individual cells by indexing into the_whole_file. The first index is the row and the second index is the column - both are zero based. To access the cell at the second row, fourth column:
row = 1
column = 3
cell_R1_C3 = the_whole_file[row][column]
print cell_R1_C3

If you have the excel file as a CSV, you can use csv.reader
import csv
myFilePath = "/Path/To/Your/File"
with open(myFilePath,'rb') as csvfile:
reader = csv.reader( csvfile, delimiter=',' )
for row in reader:
# 'row' has all the cells (thanks to wwii for the fix!). Get the first 4 columns
a, b, c, d = row[:4]