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python csv file add to field based off another field

I have a csv file looks like this:
I have a column called “Inventory”, within that column I pulled data from another source and it put it in a dictionary format as you see.
What I need to do is iterate through the 1000+ lines, if it sees the keywords: comforter, sheets and pillow exist than write “bedding” to the “Location” column for that row, else write “home-fashions” if the if statement is not true.
I have been able to just get it to the if statement to tell me if it goes into bedding or “home-fashions” I just do not know how I tell it to write the corresponding results to the “Location” field for that line.
In my script, im printing just to see my results but in the end I just want to write to the same CSV file.
from csv import DictReader
with open('test.csv', 'r') as read_obj:
csv_dict_reader = DictReader(read_obj)
for line in csv_dict_reader:
if 'comforter' in line['Inventory'] and 'sheets' in line['Inventory'] and 'pillow' in line['Inventory']:
print('Bedding')
print(line['Inventory'])
else:
print('home-fashions')
print(line['Inventory'])

The last column of your csv contains commas. You cannot read it using DictReader.
import re
data = []
with open('test.csv', 'r') as f:
# Get the header row
header = next(f).strip().split(',')
for line in f:
# Parse 4 columns
row = re.findall('([^,]*),([^,]*),([^,]*),(.*)', line)[0]
# Create a dictionary of one row
item = {header[0]: row[0], header[1]: row[1], header[2]: row[2],
header[3]: row[3]}
# Add each row to the list
data.append(item)
After preparing your data, you can check with your conditions.
for item in data:
if all([x in item['Inventory'] for x in ['comforter', 'sheets', 'pillow']]):
item['Location'] = 'Bedding'
else:
item['Location'] = 'home-fashions'
Write output to a file.
import csv
with open('output.csv', 'w') as f:
dict_writer = csv.DictWriter(f, data[0].keys())
dict_writer.writeheader()
dict_writer.writerows(data)

csv.DictReader returns a dict, so just assign the new value to the column:
if 'comforter' in line['Inventory'] and ...:
line['Location'] = 'Bedding'
else:
line['Location'] = 'home-fashions'
print(line['Inventory'])

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])

Making Python ignore CSV separator instruction [duplicate]

I am asking Python to print the minimum number from a column of CSV data, but the top row is the column number, and I don't want Python to take the top row into account. How can I make sure Python ignores the first line?
This is the code so far:
import csv
with open('all16.csv', 'rb') as inf:
incsv = csv.reader(inf)
column = 1
datatype = float
data = (datatype(column) for row in incsv)
least_value = min(data)
print least_value
Could you also explain what you are doing, not just give the code? I am very very new to Python and would like to make sure I understand everything.

You could use an instance of the csv module's Sniffer class to deduce the format of a CSV file and detect whether a header row is present along with the built-in next() function to skip over the first row only when necessary:
import csv
with open('all16.csv', 'r', newline='') as file:
has_header = csv.Sniffer().has_header(file.read(1024))
file.seek(0) # Rewind.
reader = csv.reader(file)
if has_header:
next(reader) # Skip header row.
column = 1
datatype = float
data = (datatype(row[column]) for row in reader)
least_value = min(data)
print(least_value)
Since datatype and column are hardcoded in your example, it would be slightly faster to process the row like this:
data = (float(row[1]) for row in reader)
Note: the code above is for Python 3.x. For Python 2.x use the following line to open the file instead of what is shown:
with open('all16.csv', 'rb') as file:

To skip the first line just call:
next(inf)
Files in Python are iterators over lines.

Borrowed from python cookbook,
A more concise template code might look like this:
import csv
with open('stocks.csv') as f:
f_csv = csv.reader(f)
headers = next(f_csv)
for row in f_csv:
# Process row ...

In a similar use case I had to skip annoying lines before the line with my actual column names. This solution worked nicely. Read the file first, then pass the list to csv.DictReader.
with open('all16.csv') as tmp:
# Skip first line (if any)
next(tmp, None)
# {line_num: row}
data = dict(enumerate(csv.DictReader(tmp)))

You would normally use next(incsv) which advances the iterator one row, so you skip the header. The other (say you wanted to skip 30 rows) would be:
from itertools import islice
for row in islice(incsv, 30, None):
# process

use csv.DictReader instead of csv.Reader.
If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as field names. you would then be able to access field values using row["1"] etc

Python 2.x
csvreader.next()
Return the next row of the reader’s iterable object as a list, parsed
according to the current dialect.
csv_data = csv.reader(open('sample.csv'))
csv_data.next() # skip first row
for row in csv_data:
print(row) # should print second row
Python 3.x
csvreader.__next__()
Return the next row of the reader’s iterable object as a list (if the
object was returned from reader()) or a dict (if it is a DictReader
instance), parsed according to the current dialect. Usually you should
call this as next(reader).
csv_data = csv.reader(open('sample.csv'))
csv_data.__next__() # skip first row
for row in csv_data:
print(row) # should print second row

The documentation for the Python 3 CSV module provides this example:
with open('example.csv', newline='') as csvfile:
dialect = csv.Sniffer().sniff(csvfile.read(1024))
csvfile.seek(0)
reader = csv.reader(csvfile, dialect)
# ... process CSV file contents here ...
The Sniffer will try to auto-detect many things about the CSV file. You need to explicitly call its has_header() method to determine whether the file has a header line. If it does, then skip the first row when iterating the CSV rows. You can do it like this:
if sniffer.has_header():
for header_row in reader:
break
for data_row in reader:
# do something with the row

this might be a very old question but with pandas we have a very easy solution
import pandas as pd
data=pd.read_csv('all16.csv',skiprows=1)
data['column'].min()
with skiprows=1 we can skip the first row then we can find the least value using data['column'].min()

The new 'pandas' package might be more relevant than 'csv'. The code below will read a CSV file, by default interpreting the first line as the column header and find the minimum across columns.
import pandas as pd
data = pd.read_csv('all16.csv')
data.min()

Because this is related to something I was doing, I'll share here.
What if we're not sure if there's a header and you also don't feel like importing sniffer and other things?
If your task is basic, such as printing or appending to a list or array, you could just use an if statement:
# Let's say there's 4 columns
with open('file.csv') as csvfile:
csvreader = csv.reader(csvfile)
# read first line
first_line = next(csvreader)
# My headers were just text. You can use any suitable conditional here
if len(first_line) == 4:
array.append(first_line)
# Now we'll just iterate over everything else as usual:
for row in csvreader:
array.append(row)

Well, my mini wrapper library would do the job as well.
>>> import pyexcel as pe
>>> data = pe.load('all16.csv', name_columns_by_row=0)
>>> min(data.column[1])
Meanwhile, if you know what header column index one is, for example "Column 1", you can do this instead:
>>> min(data.column["Column 1"])

For me the easiest way to go is to use range.
import csv
with open('files/filename.csv') as I:
reader = csv.reader(I)
fulllist = list(reader)
# Starting with data skipping header
for item in range(1, len(fulllist)):
# Print each row using "item" as the index value
print (fulllist[item])

I would convert csvreader to list, then pop the first element
import csv
with open(fileName, 'r') as csvfile:
csvreader = csv.reader(csvfile)
data = list(csvreader) # Convert to list
data.pop(0) # Removes the first row
for row in data:
print(row)

I would use tail to get rid of the unwanted first line:
tail -n +2 $INFIL | whatever_script.py

just add [1:]
example below:
data = pd.read_csv("/Users/xyz/Desktop/xyxData/xyz.csv", sep=',', header=None)**[1:]**
that works for me in iPython

Python 3.X
Handles UTF8 BOM + HEADER
It was quite frustrating that the csv module could not easily get the header, there is also a bug with the UTF-8 BOM (first char in file).
This works for me using only the csv module:
import csv
def read_csv(self, csv_path, delimiter):
with open(csv_path, newline='', encoding='utf-8') as f:
# https://bugs.python.org/issue7185
# Remove UTF8 BOM.
txt = f.read()[1:]
# Remove header line.
header = txt.splitlines()[:1]
lines = txt.splitlines()[1:]
# Convert to list.
csv_rows = list(csv.reader(lines, delimiter=delimiter))
for row in csv_rows:
value = row[INDEX_HERE]

Simple Solution is to use csv.DictReader()
import csv
def read_csv(file): with open(file, 'r') as file:
reader = csv.DictReader(file)
for row in reader:
print(row["column_name"]) # Replace the name of column header.

Add rows to a csvfile without creating an intermediate copy

How can I add rows to a csvfile by editing in place? I want to avoid the pattern of writing to a temp file and then replacing the original, (pseudocode):
add_records_to_csv(newdata, infile, tmpfile)
delete(infile)
rename(tmpfile, infile)
Here's the actual function. The lines "# <--" are what I want to get rid of and/or condense into something more straightforward:
def add_records_to_csv(dic, csvfile):
""" Append a dictionary to a CSV file.
Adapted from http://pymotw.com/2/csv/
"""
f_old = open(csvfile, 'rb') # <--
csv_old = csv.DictReader(f_old) # <--
fpath, fname = os.path.split(csvfile) # <--
csvfile_new = os.path.join(fpath, 'new_' + fname ) # <--
print(csvfile_new) # <--
f = open(csvfile_new, 'wb') # <--
try:
fieldnames = sorted(set(dic.keys() + csv_old.fieldnames))
writer = csv.DictWriter(f, fieldnames=fieldnames)
headers = dict( (n,n) for n in fieldnames )
writer.writerow(headers)
for row in csv_old:
writer.writerow(row)
writer.writerow(dic)
finally:
f_old.close()
f.close()
return csvfile_new

This is not going to be possible in general. Here is the reason, from your code:
fieldnames = sorted(set(dic.keys() + csv_old.fieldnames))
To me, this says that at least in some cases your new row contains columns that were not in the previous rows. When you add a row like this, you will have to update the header of the file (the first line), in addition to appending new rows at the end. If you need to have the column names in alphabetized order, then you may have to rearrange the fields in all the other rows in order to retain the ordering of the columns.
Because you may need to edit the first line of the file, in addition to appending new lines at the end and possibly editing all the lines in-between, there isn't a reasonable way to make this work in-place.
My suggestion is to try and figure out, ahead of time, all the fields/columns that you may need to include so that you guarantee your program will never have to edit the header and can simply add new rows.

If your new row has the same structure as the existing records the following will work:
import csv
def append_record_to_csv(dic, csvfile):
with open(csvfile, 'rb') as f:
# discover order of field names in header row
fieldnames = next(csv.reader(f))
with open(csvfile, 'ab') as f:
# assumes that dic contains only fieldnames in csv file
dwriter = csv.DictWriter(f, fieldnames=fieldnames)
dwriter.writerow(dic)
On the other hand, if your new row as a different structure than the existing rows a csv file is probably the wrong file format. In order to add a new column to a csv file every row needs to be edited. The performance of this approach is very bad and will be quite noticeable with a large csv file.

add a new column to an existing csv file

I have a csv file with 5 columns and I want to add data in a 6th column. The data I have is in an array.
Right now, the code that I have will insert the data I would want in the 6th column only AFTER all the data that already exists in the csv file.
For instance I have:
wind, site, date, time, value
10, 01, 01-01-2013, 00:00, 5.1
89.6 ---> this is the value I want to add in a 6th column but it puts it after all the data from the csv file
Here is the code I am using:
csvfile = 'filename'
with open(csvfile, 'a') as output:
writer = csv.writer(output, lineterminator='\n')
for val in data:
writer.writerow([val])
I thought using 'a' would append the data in a new column, but instead it just puts it after ('under') all the other data... I don't know what to do!

Appending writes data to the end of a file, not to the end of each row.
Instead, create a new file and append the new value to each row.
csvfile = 'filename'
with open(csvfile, 'r') as fin, open('new_'+csvfile, 'w') as fout:
reader = csv.reader(fin, newline='', lineterminator='\n')
writer = csv.writer(fout, newline='', lineterminator='\n')
if you_have_headers:
writer.writerow(next(reader) + [new_heading])
for row, val in zip(reader, data)
writer.writerow(row + [data])
On Python 2.x, remove the newline='' arguments and change the filemodes from 'r' and 'w' to 'rb' and 'wb', respectively.
Once you are sure this is working correctly, you can replace the original file with the new one:
import os
os.remove(csvfile) # not needed on unix
os.rename('new_'+csvfile, csvfile)

csv module does not support writing or appending column. So the only thing you can do is: read from one file, append 6th column data, and write to another file. This shows as below:
with open('in.txt') as fin, open('out.txt', 'w') as fout:
index = 0
for line in fin:
fout.write(line.replace('\n', ', ' + str(data[index]) + '\n'))
index += 1
data is a int list.
I test these codes in python, it runs fine.

We have a CSV file i.e. data.csv and its contents are:
#data.csv
1,Joi,Python
2,Mark,Laravel
3,Elon,Wordpress
4,Emily,PHP
5,Sam,HTML
Now we want to add a column in this csv file and all the entries in this column should contain the same value i.e. Something text.
Example
from csv import writer
from csv import reader
new_column_text = 'Something text'
with open('data.csv', 'r') as read_object, \
open('data_output.csv', 'w', newline='') as write_object:
csv_reader = reader(read_object)
csv_writer = writer(write_object)
for row in csv_reader:
row.append(new_column_text)
csv_writer.writerow(row)
Output
#data_output.csv
1,Joi,Python,Something text
2,Mark,Laravel,Something text
3,Elon,Wordpress,Something text
4,Emily,PHP,Something text
5,Sam,HTML,Something text

The append mode of opening files is meant to add data to the end of a file. what you need to do is provide random access to your file writing. you need to use the seek() method
you can see and example here:
http://www.tutorialspoint.com/python/file_seek.htm
or read the python docs on it here: https://docs.python.org/2.4/lib/bltin-file-objects.html which isn't terribly useful
if you want to add to the end of a column you may want to open the file read a line to figure out it's length then seek to the end.