I want to replace the header row of a cvs file text.csv.
header_list = ['column_1', 'column_2', 'column_3']
The header will look like this;
column_1, column_2, column_3
Here is my code;
import csv
with open('text.csv', 'w') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(header_list)
The header of the csv file was replaced correctly. However, the rest of the rows in the csv file were deleted. How do I replace only the header leaving the other rows intact?
I am using python v3.6
Here is a proper way to do it using csv module.
csv.DictReader reads the content of csv file into a list of dicts. It takes an optional fieldnames argument which if set applies a custom header and ignores an original header and treats it as a data row. So, all you need to do is read your csv
file with csv.DictReader and write data with csv.DictWriter. You will have to drop the first row in the reader because it contains the old header and write the new header. It does make sense to write the new data to a separate file though.
import csv
header = ["column_1", "column_2", "column_3"]
with open('text.csv', 'r') as fp:
reader = csv.DictReader(fp, fieldnames=header)
# use newline='' to avoid adding new CR at end of line
with open('output.csv', 'w', newline='') as fh:
writer = csv.DictWriter(fh, fieldnames=reader.fieldnames)
writer.writeheader()
header_mapping = next(reader)
writer.writerows(reader)
Use this:
import csv
header_list = ['column_1', 'column_2', 'column_3']
mystring = ",".join(header_list)
def line_prepender(filename, line):
with open(filename, 'r+') as csvfile:
content = csvfile.read()
csvfile.seek(0, 0)
csvfile.write(line.rstrip('\r\n') + '\n' + content)
line_prepender("text.csv", mystring)
Related
I want to append a column from 'b.csv' file and put it into 'a.csv' file but it only add a letter and not the whole string. I tried searching in google but there's no answer. I want to put the column under the headline "number". This is my code:
f = open('b.csv')
default_text = f.read()
with open('a.csv', 'r') as read_obj, \
open('output_1.csv', 'w', newline='') as write_obj:
csv_reader = reader(read_obj)
csv_writer = writer(write_obj)
for row in csv_reader:
row.append(default_text[8])
csv_writer.writerow(row)
This is the info in 'a.csv'
name,age,course,school,number
Leo,18,BSIT,STI
Rommel,23,BSIT,STI
Gaby,33,BSIT,STI
Ranel,31,BSIT,STI
This is the info in 'b.csv'
1212121
1094534
1345684
1093245
You can just concat rows read from both CSV file and pass it immediately to writer:
import csv
from operator import concat
with open(r'a.csv') as f1, \
open(r'b.csv') as f2, \
open(r'output_1.csv', 'w', newline='') as out:
f1_reader = csv.reader(f1)
f2_reader = csv.reader(f2)
writer = csv.writer(out)
writer.writerow(next(f1_reader)) # write column names
writer.writerows(map(concat, f1_reader, f2_reader))
So we initialize csv.reader() for both CSV files and csv.writer() for output. As first file (a.csv) contains column names, we read it using next() and pass to .writerow() to write them into output without any modifications. Then using map() we can iterate over both readers simultaneously applying operator.concat() which concatenate rows returned from both reader. We can pass it directly to .writerows() and let it consume generator returned by map().
If only pandas cannot be used, then it's convenient to use Table helper from convtools library (github).
from convtools.contrib.tables import Table
from convtools import conversion as c
(
Table.from_csv("tmp/1.csv", header=True)
# this step wouldn't be needed if your first file wouldn't have missing
# "number" column
.drop("number")
.zip(Table.from_csv("tmp/2.csv", header=["number"]))
.into_csv("tmp/results.csv")
)
I have a file "TAB.csv" with many columns. I would like to choose one column without header (index of that column is 3) from CSV file. Then create a new text file "NEW.txt" and write there that column (without header).
Below code reads that column but with the header. How to omit the header and save that column in a new text file?
import csv
with open('TAB.csv','rb') as f:
reader = csv.reader(f)
for row in reader:
print row[3]
This is the solution #tmrlvi was talking: it skips the first row (header) via next function:
import csv
with open('TAB.csv','rb') as input_file:
reader = csv.reader(input_file)
output_file = open('output.csv','w')
next(reader, None)
for row in reader:
row_str = row[3]
output_file.write(row_str + '\n')
output_file.close()
Try this:
import csv
with open('TAB.csv', 'rb') as f, open('out.txt', 'wb') as g:
reader = csv.reader(f)
next(reader) # skip header
g.writelines(row[3] + '\n' for row in reader)
enumerate is a nice function that returns a tuple. It enables to to view the index while running over an iterator.
import csv
with open('NEW.txt','wb') as outfile:
with open('TAB.csv','rb') as f:
reader = csv.reader(f)
for index, row in enumerate(reader):
if index > 0:
outfile.write(row[3])
outfile.write("\n")
Another solution would be to read one line from the file (in order to skip the header).
It's an old question but I would like to add my answer about Pandas library, I would like to say. It's better to use Pandas library for such tasks instead of writing your own code. And the simple code with Pandas will be like :
import pandas as pd
reader = pd.read_csv('TAB.csv', header = None)
I have some data that needs to be written to a CSV file. The data is as follows
A ,B ,C
a1,a2 ,b1 ,c1
a2,a4 ,b3 ,ct
The first column has comma inside it. The entire data is in a list that I'd like to write to a CSV file, delimited by commas and without disturbing the data in column A. How can I do that? Mentioning delimiter = ',' splits it into four columns on the whole.
Just use the csv.writer from the csv module.
import csv
data = [['A','B','C']
['a1,a2','b1','c1']
['a2,a4','b3','ct']]
fname = "myfile.csv"
with open(fname,'wb') as f:
writer = csv.writer(f)
for row in data:
writer.writerow(row)
https://docs.python.org/library/csv.html#csv.writer
No need to use the csv module since the ',' in the first column is already part of your data, this will work:
with open('myfile.csv', 'w') as f:
for row in data:
f.write(', '.join(row))
f.write('\n')
You could try the below.
Code:
import csv
import re
with open('infile.csv', 'r') as f:
lst = []
for line in f:
lst.append(re.findall(r',?(\S+)', line))
with open('outfile.csv', 'w', newline='') as w:
writer = csv.writer(w)
for row in lst:
writer.writerow(row)
Output:
A,B,C
"a1,a2",b1,c1
"a2,a4",b3,ct
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.
I'm trying to parse a pipe-delimited file and pass the values into a list, so that later I can print selective values from the list.
The file looks like:
name|age|address|phone|||||||||||..etc
It has more than 100 columns.
Use the 'csv' library.
First, register your dialect:
import csv
csv.register_dialect('piper', delimiter='|', quoting=csv.QUOTE_NONE)
Then, use your dialect on the file:
with open(myfile, "rb") as csvfile:
for row in csv.DictReader(csvfile, dialect='piper'):
print row['name']
Use Pandas:
import pandas as pd
pd.read_csv(filename, sep="|")
This will store the file in a dataframe. For each column, you can apply conditions to select the required values to print. It takes a very short time to execute. I tried with 111,047 rows.
If you're parsing a very simple file that won't contain any | characters in the actual field values, you can use split:
fileHandle = open('file', 'r')
for line in fileHandle:
fields = line.split('|')
print(fields[0]) # prints the first fields value
print(fields[1]) # prints the second fields value
fileHandle.close()
A more robust way to parse tabular data would be to use the csv library as mentioned in Spencer Rathbun's answer.
In 2022, with Python 3.8 or above, you can simply do:
import csv
with open(file_path, "r") as csvfile:
reader = csv.reader(csvfile, delimiter='|')
for row in reader:
print(row[0], row[1])