Related
Im attempting to simplify a python code that will print the first five rows (plus header) of a large csv file in a more condensed output if possible. I would prefer to use pandas, however in this case I would like to just to just use the import cv and import os (Mac user).
Code as follows:
import csv
filename = "/Users/xx/Desktop/xx.csv"
fields = []
rows = []
with open(filename, 'r') as csvfile:
csvreader = csv.reader(csvfile)
fields = next(csvreader)
for row in csvreader:
rows.append(row)
print("Total no. of rows:%d"%(csvreader.line_num))
print('Field names are:' + ', '.join(field for field in fields))
print('\nFirst 5 rows are:\n')
for row in rows[:5]:
for col in row:
print("%10s"%col,end=" "),
print('\n')
I have several CSV files that look like this:
Input
Name Code
blackberry 1
wineberry 2
rasberry 1
blueberry 1
mulberry 2
I would like to add a new column to all CSV files so that it would look like this:
Output
Name Code Berry
blackberry 1 blackberry
wineberry 2 wineberry
rasberry 1 rasberry
blueberry 1 blueberry
mulberry 2 mulberry
The script I have so far is this:
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):
writer.writerow(row+['Berry'])
(Python 3.2)
But in the output, the script skips every line and the new column has only Berry in it:
Output
Name Code Berry
blackberry 1 Berry
wineberry 2 Berry
rasberry 1 Berry
blueberry 1 Berry
mulberry 2 Berry
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
the lineterminator parameter in csv.writer. By default it is
set to '\r\n' and this is why you have double spacing.
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.
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'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
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
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.
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)
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++
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]]
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
Existing CSV filename
Output CSV filename (which will have the updated content) and
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:
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
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']
import csv
with open("somecities.csv") as f:
reader = csv.DictReader(f)
data = [r for r in reader]
Contents of somecities.csv:
Country,Capital,CountryPop,AreaSqKm
Canada,Ottawa,35151728,9984670
USA,Washington DC,323127513,9833520
Japan,Tokyo,126740000,377972
Luxembourg,Luxembourg City,576249,2586
New to python and I'm trying to read and append a csv file. I've spent some time experimenting with some responses to similar questions with no luck--which is why I believe the code above to be pretty useless.
What I am essentially trying to achieve is to store each row from the CSV in memory using a dictionary, with the country names as keys, and values being tuples containing the other information in the table in the sequence they are in within the CSV file.
And from there I am trying to add three more cities to the csv(Country, Capital, CountryPop, AreaSqKm) and view the updated csv. How should I go about doing all of this?
The desired additions to the updated csv are:
Brazil, Brasília, 211224219, 8358140
China, Beijing, 1403500365, 9388211
Belgium, Brussels, 11250000, 30528
EDIT:
Import csv
with open("somecities.csv", "r") as csvinput:
with open(" somecities_update.csv", "w") as csvresult:
writer = csv.writer(csvresult, lineterminator='\n')
reader = csv.reader(csvinput)
all = []
headers = next(reader)
for row in reader:
all.append(row)
# Now we write to the new file
writer.write(headers)
for record in all:
writer.write(record)
#row.append(Brazil, Brasília, 211224219, 8358140)
#row.append(China, Beijing, 1403500365, 9388211)
#row.append(Belgium, Brussels, 11250000, 30528)
So assuming you can use pandas for this I would go about it this way:
import pandas as pd
df1 = pd.read_csv('your_initial_file.csv', index_col='Country')
df2 = pd.read_csv('your_second_file.csv', index_col='Country')
dfs = [df1,df2]
final_df = pd.concat(dfs)
DictReader will only represent each row as a dictionary, eg:
{
"Country": "Canada",
...,
"AreaSqKm": "9984670"
}
If you want to store the whole CSV as a dictionary you'll have to create your own:
import csv
all_data = {}
with open("somecities.csv", "r") as f:
reader = csv.DictReader(f)
for row in reader:
# Key = country, values = tuple containing the rest of the data.
all_data[row["Country"]] = (row["Capital"], row["CountryPop"], row["AreaSqKm"])
# Add the new cities to the dictionary here...
# To write the data to a new CSV
with open("newcities.csv", "w") as f:
writer = csv.writer(f)
for key, values in all_data.items():
writer.writerow([key] + list(values))
As others have said, though, the pandas library could be a good choice. Check out its read_csv and to_csv functions.
Just another idea with creating and list and appending the new values through list construct as below, not tested:
import csv
with open("somecities.csv", "r") as csvinput:
with open("result.csv", "w") as csvresult:
writer = csv.writer(csvresult, lineterminator='\n')
reader = csv.reader(csvinput)
all = []
row = next(reader)
row.append(Brazil, Brasília, 211224219, 8358140)
row.append(China, Beijing, 1403500365, 9388211)
all.append(row)
for row in reader:
row.append(row[0])
all.append(row)
writer.writerows(all)
The simplest Form i see, tested in python 3.6
Opening a file with the 'a' parameter allows you to append to the end of the file instead of simply overwriting the existing content. Try that.
>>> with open("somecities.csv", "a") as fd:
... fd.write("Brazil, Brasília, 211224219, 8358140")
OR
#!/usr/bin/python3.6
import csv
fields=['Brazil', 'Brasília', '211224219','8358140']
with open(r'somecities.csv', 'a') as f:
writer = csv.writer(f)
writer.writerow(fields)
So I'm trying to combine two different csv files into a single one and I've done that. The two csv files are of students in school who are present in 1 and absent in another.
I need to put the date the file was created at the top of the new csv and have each grade of the present students on a new page or after 3 blank rows.
Also on each new page or after each 3 blanks i want to have the name or the teacher, the date on which the file was created and the grade.
import csv
with open('inschool.csv', encoding="cp437") as f:
reader = csv.reader(f)
in_school = list(reader)
with open('notinschool.csv', encoding="cp437") as f:
reader = csv.reader(f)
not_in_school = list(reader)
for grade, name, status, hr_teacher in not_in_school:
print(grade, name, status, hr_teacher)
for grade, name, status, hr_teacher in in_school:
print(grade, name, status, hr_teacher)
iFile = open('inschool.csv', encoding="cp437")
reader = csv.reader(iFile)
IFILE = open('notinschool.csv', encoding="cp437")
READER = csv.reader(IFILE)
oFile = open('combined.csv','wt',encoding="cp437")
writer = csv.writer(oFile, delimiter='|', quoting=csv.QUOTE_ALL)
for row in READER:
writer.writerow(row)
writer.writerow("[]")
for row in reader:
writer.writerow(row)
writer.writerow("[]")
The code which i tried for the 3 blank rows had this ending but it gave 3 blank rows/lines after each students name instead of after each grade.
iFile = open('Inschool.csv',)
reader = csv.reader(iFile)
IFILE = open('notinschool.csv')
READER = csv.reader(IFILE)
oFile = open('combined.csv','wb')
writer_a = csv.writer(oFile, delimiter='|', quoting=csv.QUOTE_ALL)
writer_b = csv.writer(oFile, delimiter='|', quoting=csv.QUOTE_ALL, lineterminator="\n\n\n\n")
for row in READER:
writer_a.writerow(row)
writer_b.writerow([])
for row in reader:
writer_b.writerow(row)
I would appreciate it if someone could help me. Thanks.
You can do it really easy in the terminal. Just cd to the directory and do the command cat inschool.csv notinschool.csv > combined.csv
If you want to do it in Python I would do:
in_file1 = open("inschool.csv","r").read().split("\n")
in_file2 = open("notinschool.csv","r").read().split("\n")
out_file = open("combined.csv","w")
for line in in_file1:
if line:
out_file.write(line + "\n")
for line in in_file2:
if line:
out_file.write(line + "\n")
reading files the way above isn't the most efficient, but if they are small it doesnt really matter and it's easier to visualize what's happening. you can use your input file method with this b/c the concept stays the same :)
I just got into using this module called pandas and it is for DataFrames. They are much easier to use, process, navigate through, and merge than parsing text files.
I have several CSV files that look like this:
Input
Name Code
blackberry 1
wineberry 2
rasberry 1
blueberry 1
mulberry 2
I would like to add a new column to all CSV files so that it would look like this:
Output
Name Code Berry
blackberry 1 blackberry
wineberry 2 wineberry
rasberry 1 rasberry
blueberry 1 blueberry
mulberry 2 mulberry
The script I have so far is this:
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):
writer.writerow(row+['Berry'])
(Python 3.2)
But in the output, the script skips every line and the new column has only Berry in it:
Output
Name Code Berry
blackberry 1 Berry
wineberry 2 Berry
rasberry 1 Berry
blueberry 1 Berry
mulberry 2 Berry
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
the lineterminator parameter in csv.writer. By default it is
set to '\r\n' and this is why you have double spacing.
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.
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'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
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
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.
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)
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++
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]]
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
Existing CSV filename
Output CSV filename (which will have the updated content) and
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']
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