I want to write the rows of a csv file to another csv file. I want to change the content of each row as well in a way that if the row is empty, it remains empty and if it is not, any spaces at the beginning and end of the string are omitted. The original csv file has one column and 65422771 rows.
I have written the following to write the rows of the original csv file to the new one:
import csv
csvfile = open('data.csv', 'r')
with open('data 2.csv', "w+") as csv_file1:
writer = csv.writer(csv_file1)
count = 0
for row in csvfile:
row = row.replace('"', '')
count+= 1
print(count)
if row.strip() == '':
writer.writerow('\n')
else:
writer.writerow(row)
However, when the new csv file is made, it is shown that it has 130845543 rows (= count)! The size of the new csv file is also 2 times the size of the original one. How can I create the new csv file with exactly the same number of rows but with the mentioned changes made to them?
Try this:
import csv
with open('data.csv', 'r') as file:
rows = [[row[0].strip()] for row in csv.reader(file)]
with open('data_out.csv', "w", newline = "") as file:
writer = csv.writer(file)
writer.writerows(rows)
Also, as #tripleee mentioned, your file is quite large so you may want to read / write it in chunks. You can use pandas for that.
import pandas as pd
chunksize = 10_000
for chunk in pd.read_csv('data.csv', chunksize = chunksize, header = None):
chunk[0] = chunk[0].str.strip()
chunk.to_csv("data_out.csv", mode="a", header = False, index = False)
Related
Hi I'm writing a simple script to copy a set of rows from a csv file and paste them for N number of times in other file.
I'm not able to write the result into other file.
Please find the code below:
import csv
for i in range(2):
with open('C:\\Python\\CopyPaste\\result2.csv', 'r') as fp:
data = fp.readlines()
fp.close()
with open('C:\\Python\\CopyPaste\\mydata.csv', 'w') as mycsvfile:
thedatawriter = csv.writer(mycsvfile)
for row in data:
thedatawriter.writerow(row)
Assuming that the format of the input and output CSV files is the same, just read the input file into a string and then write it to an output file N times:
N = 3
with open('C:\\Python\\CopyPaste\\result2.csv', 'r') as infile,\
open('C:\\Python\\CopyPaste\\mydata.csv', 'w') as outfile:
data = fp.read() # read entire contents of input file into data
for i in range(N):
outfile.write(data)
The above answers the question literally, however, it will replicate the header row N times, probably not what you want. You can do this instead:
import csv
N = 3
with open('C:\\Python\\CopyPaste\\result2.csv', 'r') as infile,\
open('C:\\Python\\CopyPaste\\mydata.csv', 'w') as outfile:
reader = csv.reader(infile)
writer = csv.writer(outfile)
writer.writerow(next(reader)) # reads header line and writes it to output file
data = [row for row in reader] # reads the rest of the input file
for i in range(N):
writer.writerows(data)
This code reads the first row from the input file as the header, and writes it once to the output CSV file. Then the remaining rows are read from the input file into the data list, and replicated N times in the output file.
I guess your question is : read a .csv file and then write the data to another .csv file for N times?
If my recognition is right, my suggestion would be using pandas library, that's very convenient.
Something like:
import pandas as pd
df = pd.read_csv('origin.csv')
df.to_csv('output.csv')
I have a code to read csv file by row
import csv
with open('example.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
for row in readCSV:
print(row)
print(row[0])
But i want only selected columns what is the technique could anyone give me a script?
import csv
with open('example.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
column_one = [row[0] for row in readCSV ]
Will give you list of values from the first column. That being said - you'll have to read the entire file anyway.
You can't do that, because files are written byte-by-byte to your filesystem. To know where one line ends, you will have to read all the line to detect the presence of a line-break character. There's no way around this in a CSV.
So you'll have to read all the file -- but you can choose which parts of each row you want to keep.
I would definitely use pandas for that.
However, in plain python this one of the way to do it.
In this example I am extracting the content of row 3, column 4.
import csv
target_row = 3
target_col = 4
with open('yourfile.csv', 'rb') as csvfile:
reader = csv.reader(csvfile)
n = 0
for row in reader:
if row == target_row:
data = row.split()[target_col]
break
print data
read_csv in pandas module can load a subset of columns.
Assume you only want to load columns 1 and 3 in your .csv file.
import pandas as pd
usecols = [1, 3]
df = pd.read_csv('example.csv',usecols=usecols, sep=',')
Here is Doc for read_csv.
In addition, if your file is big, you can read the file piece by piece by specifying chucksize in read_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)
So I have a text file that looks like this:
1,989785345,"something 1",,234.34,254.123
2,234823423,"something 2",,224.4,254.123
3,732847233,"something 3",,266.2,254.123
4,876234234,"something 4",,34.4,254.123
...
I'm running this code right here:
file = open("file.txt", 'r')
readFile = file.readline()
lineID = readFile.split(",")
print lineID[1]
This lets me break up the content in my text file by "," but what I want to do is separate it into columns because I have a massive number of IDs and other things in each line. How would I go about splitting the text file into columns and call each individual row in the column one by one?
You have a CSV file, use the csv module to read it:
import csv
with open('file.txt', 'rb') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
This still gives you data by row, but with the zip() function you can transpose this to columns instead:
import csv
with open('file.txt', 'rb') as csvfile:
reader = csv.reader(csvfile)
for column in zip(*reader):
Do be careful with the latter; the whole file will be read into memory in one go, and a large CSV file could eat up all your available memory in the process.
I have a csv which contains 38 colums of data, all I want to find our how to do is, divide column 11 by column by column 38 and append this data tot he end of each row. Missing out the title row of the csv (row 1.)
If I am able to get a snippet of code that can do this, I will be able to manipulate the same code to perform lots of similar functions.
My attempt involved editing some code that was designed for something else.
See below:
from collections import defaultdict
class_col = 11
data_col = 38
# Read in the data
with open('test.csv', 'r') as f:
# if you have a header on the file
# header = f.readline().strip().split(',')
data = [line.strip().split(',') for line in f]
# Append the relevant sum to the end of each row
for row in xrange(len(data)):
data[row].append(int(class_col)/int(data_col))
# Write the results to a new csv file
with open('testMODIFIED2.csv', 'w') as nf:
nf.write('\n'.join(','.join(row) for row in data))
Any help will be greatly appreciated. Thanks SMNALLY
import csv
with open('test.csv', 'rb') as old_csv:
csv_reader = csv.reader(old_csv)
with open('testMODIFIED2.csv', 'wb') as new_csv:
csv_writer = csv.writer(new_csv)
for i, row in enumerate(csv_reader):
if i != 0:
row.append(float(row[10]) / float(row[37]))
csv_writer.writerow(row)
Use pandas:
import pandas
df = pandas.read_csv('test.csv') #assumes header row exists
df['FRACTION'] = 1.0*df['CLASS']/df['DATA'] #by default new columns are appended to the end
df.to_csv('out.csv')