How to add a new column to a CSV file?

import csv
with open('input.csv','r') as csvinput:
with open('output.csv', 'w') as csvoutput:
writer = csv.writer(csvoutput)


for row in csv.reader(csvinput):
if row[0] == "Name":
writer.writerow(row+["Berry"])
else:
writer.writerow(row+[row[0]])

Maybe something like that is what you intended?

Also, csv stands for comma separated values. So, you kind of need commas to separate your values like this I think:

Name,Code
blackberry,1
wineberry,2
rasberry,1
blueberry,1
mulberry,2

This should give you an idea of what to do:

>>> v = open('C:/test/test.csv')
>>> r = csv.reader(v)
>>> row0 = r.next()
>>> row0.append('berry')
>>> print row0
['Name', 'Code', 'berry']
>>> for item in r:
...     item.append(item[0])
...     print item
...
['blackberry', '1', 'blackberry']
['wineberry', '2', 'wineberry']
['rasberry', '1', 'rasberry']
['blueberry', '1', 'blueberry']
['mulberry', '2', 'mulberry']
>>>

Edit, note in py3k you must use next(r)

Thanks for accepting the answer. Here you have a bonus (your working script):

import csv


with open('C:/test/test.csv','r') as csvinput:
with open('C:/test/output.csv', 'w') as csvoutput:
writer = csv.writer(csvoutput, lineterminator='\n')
reader = csv.reader(csvinput)


all = []
row = next(reader)
row.append('Berry')
all.append(row)


for row in reader:
row.append(row[0])
all.append(row)


writer.writerows(all)

Please note

1. the lineterminator parameter in csv.writer. By default it is set to '\r\n' and this is why you have double spacing.
2. the use of a list to append all the lines and to write them in one shot with writerows. If your file is very, very big this probably is not a good idea (RAM) but for normal files I think it is faster because there is less I/O.

3. As indicated in the comments to this post, note that instead of nesting the two with statements, you can do it in the same line:

   with open('C:/test/test.csv','r') as csvinput, open('C:/test/output.csv', 'w') as csvoutput:

I don't see where you're adding the new column, but try this:

    import csv
i = 0
Berry = open("newcolumn.csv","r").readlines()
with open(input.csv,'r') as csvinput:
with open(output.csv, 'w') as csvoutput:
writer = csv.writer(csvoutput)
for row in csv.reader(csvinput):
writer.writerow(row+","+Berry[i])
i++

I'm surprised no one suggested Pandas. Although using a set of dependencies like Pandas might seem more heavy-handed than is necessary for such an easy task, it produces a very short script and Pandas is a great library for doing all sorts of CSV (and really all data types) data manipulation. Can't argue with 4 lines of code:

import pandas as pd
csv_input = pd.read_csv('input.csv')
csv_input['Berries'] = csv_input['Name']
csv_input.to_csv('output.csv', index=False)

Check out Pandas Website for more information!

Contents of output.csv:

Name,Code,Berries
blackberry,1,blackberry
wineberry,2,wineberry
rasberry,1,rasberry
blueberry,1,blueberry
mulberry,2,mulberry

I used pandas and it worked well... While I was using it, I had to open a file and add some random columns to it and then save back to same file only.

This code adds multiple column entries, you may edit as much you need.

import pandas as pd


csv_input = pd.read_csv('testcase.csv')         #reading my csv file
csv_input['Phone1'] = csv_input['Name']         #this would also copy the cell value
csv_input['Phone2'] = csv_input['Name']
csv_input['Phone3'] = csv_input['Name']
csv_input['Phone4'] = csv_input['Name']
csv_input['Phone5'] = csv_input['Name']
csv_input['Country'] = csv_input['Name']
csv_input['Website'] = csv_input['Name']
csv_input.to_csv('testcase.csv', index=False)   #this writes back to your file

If you want that cell value doesn't gets copy, so first of all create a empty Column in your csv file manually, like you named it as Hours then, Now for this you can add this line in above code,

csv_input['New Value'] = csv_input['Hours']

or simply we can, without adding the manual column, we can

csv_input['New Value'] = ''    #simple and easy

I Hope it helps.

This code will suffice your request and I have tested on the sample code.

import csv


with open(in_path, 'r') as f_in, open(out_path, 'w') as f_out:
csv_reader = csv.reader(f_in, delimiter=';')
writer = csv.writer(f_out)


for row in csv_reader:
writer.writerow(row + [row[0]]

Yes Its a old question but it might help some

import csv
import uuid


# read and write csv files
with open('in_file','r') as r_csvfile:
with open('out_file','w',newline='') as w_csvfile:


dict_reader = csv.DictReader(r_csvfile,delimiter='|')
#add new column with existing
fieldnames = dict_reader.fieldnames + ['ADDITIONAL_COLUMN']
writer_csv = csv.DictWriter(w_csvfile,fieldnames,delimiter='|')
writer_csv.writeheader()




for row in dict_reader:
row['ADDITIONAL_COLUMN'] = str(uuid.uuid4().int >> 64) [0:6]
writer_csv.writerow(row)

Append new column in existing csv file using python without header name

  default_text = 'Some Text'
# Open the input_file in read mode and output_file in write mode
with open('problem-one-answer.csv', 'r') as read_obj, \
open('output_1.csv', 'w', newline='') as write_obj:
# Create a csv.reader object from the input file object
csv_reader = reader(read_obj)
# Create a csv.writer object from the output file object
csv_writer = csv.writer(write_obj)
# Read each row of the input csv file as list
for row in csv_reader:
# Append the default text in the row / list
row.append(default_text)
# Add the updated row / list to the output file
csv_writer.writerow(row)

Thankyou

In case of a large file you can use pandas.read_csv with the chunksize argument which allows to read the dataset per chunk:

import pandas as pd


INPUT_CSV = "input.csv"
OUTPUT_CSV = "output.csv"
CHUNKSIZE = 1_000 # Maximum number of rows in memory


header = True
mode = "w"
for chunk_df in pd.read_csv(INPUT_CSV, chunksize=CHUNKSIZE):
chunk_df["Berry"] = chunk_df["Name"]
# You apply any other transformation to the chunk
# ...
chunk_df.to_csv(OUTPUT_CSV, header=header, mode=mode)
header = False # Do not save the header for the other chunks
mode = "a" # 'a' stands for append mode, all the other chunks will be appended

If you want to update the file inplace, you can use a temporary file and erase it at the end

import pandas as pd


INPUT_CSV = "input.csv"
TMP_CSV = "tmp.csv"
CHUNKSIZE = 1_000 # Maximum number of rows in memory


header = True
mode = "w"
for chunk_df in pd.read_csv(INPUT_CSV, chunksize=CHUNKSIZE):
chunk_df["Berry"] = chunk_df["Name"]
# You apply any other transformation to the chunk
# ...
chunk_df.to_csv(TMP_CSV, header=header, mode=mode)
header = False # Do not save the header for the other chunks
mode = "a" # 'a' stands for append mode, all the other chunks will be appended


os.replace(TMP_CSV, INPUT_CSV)

For adding a new column to an existing CSV file(with headers), if the column to be added has small enough number of values, here is a convenient function (somewhat similar to @joaquin's solution). The function takes the

1. Existing CSV filename
2. Output CSV filename (which will have the updated content) and
3. List with header name&column values

def add_col_to_csv(csvfile,fileout,new_list):
with open(csvfile, 'r') as read_f, \
open(fileout, 'w', newline='') as write_f:
csv_reader = csv.reader(read_f)
csv_writer = csv.writer(write_f)
i = 0
for row in csv_reader:
row.append(new_list[i])
csv_writer.writerow(row)
i += 1

Example:

new_list1 = ['test_hdr',4,4,5,5,9,9,9]
add_col_to_csv('exists.csv','new-output.csv',new_list1)

Existing CSV file:

Output(updated) CSV file:

You may just write:

import pandas as pd
import csv
df = pd.read_csv('csv_name.csv')
df['Berry'] = df['Name']
df.to_csv("csv_name.csv",index=False)

Then you are done. To check it, you may run:

h = pd.read_csv('csv_name.csv')
print(h)

If you want to add a column with some arbitrary new elements(a,b,c), you may replace the 4th line of the code by:

df['Berry'] = ['a','b','c']