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.
Related
I am trying to combine multiple rows in a csv file together. I could easily do it in Excel but I want to do this for hundreds of files so I need it to be as a code. I have tried to store rows in arrays but it doesn't seem to work. I am using Python to do it.
So lets say I have a csv file;
1,2,3
4,5,6
7,8,9
All I want to do is to have a csv file as this;
1,2,3,4,5,6,7,8,9
The code I have tried is this;
fin = open("C:\\1.csv", 'r+')
fout = open("C:\\2.csv",'w')
for line in fin.xreadlines():
new = line.replace(',', ' ', 1)
fout.write (new)
fin.close()
fout.close()
Could you please help?
You should be using the csv module for this as splitting CSV manually on commas is very error-prone (single columns can contain strings with commas, but you would incorrectly end up splitting this into multiple columns). The CSV module uses lists of values to represent single rows.
import csv
def return_contents(file_name):
with open(file_name) as infile:
reader = csv.reader(infile)
return list(reader)
data1 = return_contents('csv1.csv')
data2 = return_contents('csv2.csv')
print(data1)
print(data2)
combined = []
for row in data1:
combined.extend(row)
for row in data2:
combined.extend(row)
with open('csv_out.csv', 'w', newline='') as outfile:
writer = csv.writer(outfile)
writer.writerow(combined)
That code gives you the basis of the approach but it would be ugly to extend this for hundreds of files. Instead, you probably want os.listdir to pull all the files in a single directory, one by one, and add them to your output. This is the reason that I packed the reading code into the return_contents function; we can repeat the same process millions of times on different files with only one set of code to do the actual reading. Something like this:
import csv
import os
def return_contents(file_name):
with open(file_name) as infile:
reader = csv.reader(infile)
return list(reader)
all_files = os.listdir('my_csvs')
combined_output = []
for file in all_files:
data = return_contents('my_csvs/{}'.format(file))
for row in data:
combined_output.extend(row)
with open('csv_out.csv', 'w', newline='') as outfile:
writer = csv.writer(outfile)
writer.writerow(combined_output)
If you are specially dealing with csv file format. I recommend you to use csv package for the file operations. If you also use with...as statement, you don't need to worry about closing the file etc. You just need to define the PATH then program will iterate all .csv files
Here is what you can do:
PATH = "your folder path"
def order_list():
data_list = []
for filename in os.listdir(PATH):
if filename.endswith(".csv"):
with open("data.csv") as csvfile:
read_csv = csv.reader(csvfile, delimiter=',', quoting=csv.QUOTE_NONNUMERIC)
for row in read_csv:
data_list.extend(row)
print(data_list)
if __name__ == '__main__':
order_list()
Store your data in pandas df
import pandas as pd
df = pd.read_csv('file.csv')
Store the modified dataframe into new one
df_2 = df.groupby('Column_Name').agg(lambda x: ' '.join(x)).reset_index() ## Write Name of your column
Write the df to new csv
df2.to_csv("file_modified.csv")
You could do it also like this:
fIn = open("test.csv", "r")
fOut = open("output.csv", "w")
fOut.write(",".join([line for line in fIn]).replace("\n",""))
fIn.close()
fOut.close()
I've you want now to run it on multiple file you can run it as script with arguments:
import sys
fIn = open(sys.argv[1], "r")
fOut = open(sys.argv[2], "w")
fOut.write(",".join([line for line in fIn]).replace("\n",""))
fIn.close()
fOut.close()
So now expect you use some Linux System and the script is called csvOnliner.py you could call it with:
for i in *.csv; do python csvOnliner.py $i changed_$i; done
With windows you could do it in a way like this:
FOR %i IN (*.csv) DO csvOnliner.py %i changed_%i
I am working on implementation of a data mining algorithm in python. I have a large csv file which I am using as the input file to get the itemsets. I want to split the csv file into rows through program. Can someone tell how to make it possible?
import pandas as pd
pd.read_csv(file_name,sep='rows separator')
see http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html for details.
I assume the rows are delimited by new-lines and that columns are delimited by commas. In which case just python already knows how to read it line by line which in your case means row by row. Then each row can be split where there are commas.
item_sets=[] #Will put the data in here
with open(filename, "r") as file: # open the file
for data_row in file: #get data one row at a time
# split up the row into columns, stripping whitespace from each one
# and store it in item_sets
item_sets.append( [x.strip() for x in data_row.split(",")] )
import csv
with open('eggs.csv', 'rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
for row in spamreader:
print row
will printout all rows of a csv file as lists
I assume pandas impelmentation of read_csv is more efficient, but the csv module is built into python so if you don't want any dependencies, you can use it.
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 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 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.