Related
So far I have been trying to copy specific rows including headers from original csv file to a new one. However, once I run my code it was copying a total mess creating a huge document.
This is one of the options I have tried so far, which seems to be the closest to the solution:
import csv
with open('D:/test.csv', 'r') as f,open('D:/out.csv', 'w') as f_out:
reader = csv.DictReader(f)
writer = csv.writer(f_out)
for row in reader:
if row["ICLEVEL"] == "1":
writer.writerow(row)
The thing is that I have to copy only those rows where value of "ICLEVEL"(Header name) is equal to "1".
Note: test.csv is very huge file and I cannot hardcode all header names in the writer.
Any demostration of pythonic way of doing this is greatly appreciated. Thanks.
writer.writerow expects a sequence (a tuple or list). You can use DictWriter which expects a dict.
import csv
with open('D:/test.csv', 'r') as f, open('D:/out.csv', 'w') as f_out:
reader = csv.DictReader(f)
writer = csv.DictWriter(f_out, fieldnames=reader.fieldnames)
writer.writeheader() # For writing header
for row in reader:
if row['ICLEVEL'] == '1':
writer.writerow(row)
Your row is a dictionary. CSV writer cannot write dictionaries. Select the values from the dictionary and write just them:
writer.writerow(reader.fieldnames)
for row in reader:
if row["ICLEVEL"] == "1":
values = [row[field] for field in reader.fieldnames]
writer.writerow(values)
I would actually use Pandas, not a CSV reader:
import pandas as pd
df=pd.read_csv("D:/test.csv")
newdf = df[df["ICLEVEL"]==1]
newdf.to_csv("D:/out.csv",index=False)
The code is much more compact.
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.
I have been trying initially to create a program to go through one file and select certain columns that will then be moved to a new text file. So far I have
import os, sys, csv
os.chdir("C://Users//nelsonj//Desktop//Master_Project")
with open('CHS_2009_test.txt', "rb") as sitefile:
reader = csv.reader(sitefile, delimiter=',')
pref_cols = [0,1,2,4,6,8,10,12,14,18,20,22,24,26,30,34,36,40]
for row in reader:
new_cols = list(row[i] for i in pref_cols)
print new_cols
I have been trying to use the csv functions to write the new file but I am continuosly getting errors. I will eventually need to do this over a folder of files, but thought I would try to do it on one before tackling that.
Code I attempted to use to write this data to a new file
for row in reader:
with open("CHS_2009_edit.txt", 'w') as file:
new_cols = list(row[i] for i in pref_cols)
newfile = csv.writer(file)
newfile.writerows(new_cols)
This kind of works in that I get a new file, but in only prints the second row of values from my csv, i.e., not the header values and places commas in between each individual character, not just copying over the original columns as they were.
I am using PythonWin with Python 2.6(from ArcGIS)
Thanks for the help!
NEW UPDATED CODE
import os, sys, csv
path = ('C://Users//nelsonj//Desktop//Master_Project')
for filename in os.listdir(path):
pref_cols = [0,1,2,4,6,8,10,12,14,18,20,22,24,26,30,34,36,40]
with open(filename, "rb") as sitefile:
with open(filename.rsplit('.',1)[0] + "_Master.txt", 'w') as output_file:
reader = csv.reader(sitefile, delimiter=',')
writer = csv.writer(output_file)
for row in reader:
new_row = list(row[i] for i in pref_cols)
writer.writerow(new_row)
print new_row
Getting list index out of range for the new_row, but it seems to still be processing the file. Only thing I can't get it to do now is loop through all files in my directory. Here's a hyperlink to Screenshot of data text file
Try this:
new_header = list(row[i] for i in pref_cols if i in row)
That should avoid the error, but it may not avoid the underlying problem. Would you paste your CSV file somewhere that I can access, and I'll fix this for you?
For your purpose of filtering, you don't have to treat the header differently from the rest of the data. You can go ahead remove the following block:
headers = reader.next()
for row in headers:
new_header = list(row[i] for i in pref_cols)
print new_header
Your code did not work because you treated headers as a list of rows, but headers is just one row.
Update
This update deals with writing the CSV data to a new file. You should move the open statement above the for row...
with open("CHS_2009_edit.txt", 'w') as output_file:
writer = csv.writer(output_file)
for row in reader:
new_cols = list(row[i] for i in pref_cols)
writer.writerows(new_cols)
Update 2
This update deals with the header output problem. If you followed my suggestions, you should not have this problem. I don't know what your current code looks like, but it looks like you supplies a string where the code expects a list. Here is the code that I tried on my system (using my made-up data) and it seems to work:
pref_cols = [...] # <<=== Should be set before entering the loop
with open('CHS_2009_test.txt', "rb") as sitefile:
with open('CHS_2009_edit.txt', 'w') as output_file:
reader = csv.reader(sitefile, delimiter=',')
writer = csv.writer(output_file)
for row in reader:
new_row = list(row[i] for i in pref_cols)
writer.writerow(new_row)
One thing to notice: I use writerow() to write a single row, where you use writerows() -- that makes a difference.
I am using below referred code to edit a csv using Python. Functions called in the code form upper part of the code.
Problem: I want the below referred code to start editing the csv from 2nd row, I want it to exclude 1st row which contains headers. Right now it is applying the functions on 1st row only and my header row is getting changed.
in_file = open("tmob_notcleaned.csv", "rb")
reader = csv.reader(in_file)
out_file = open("tmob_cleaned.csv", "wb")
writer = csv.writer(out_file)
row = 1
for row in reader:
row[13] = handle_color(row[10])[1].replace(" - ","").strip()
row[10] = handle_color(row[10])[0].replace("-","").replace("(","").replace(")","").strip()
row[14] = handle_gb(row[10])[1].replace("-","").replace(" ","").replace("GB","").strip()
row[10] = handle_gb(row[10])[0].strip()
row[9] = handle_oem(row[10])[1].replace("Blackberry","RIM").replace("TMobile","T-Mobile").strip()
row[15] = handle_addon(row[10])[1].strip()
row[10] = handle_addon(row[10])[0].replace(" by","").replace("FREE","").strip()
writer.writerow(row)
in_file.close()
out_file.close()
I tried to solve this problem by initializing row variable to 1 but it didn't work.
Please help me in solving this issue.
Your reader variable is an iterable, by looping over it you retrieve the rows.
To make it skip one item before your loop, simply call next(reader, None) and ignore the return value.
You can also simplify your code a little; use the opened files as context managers to have them closed automatically:
with open("tmob_notcleaned.csv", "rb") as infile, open("tmob_cleaned.csv", "wb") as outfile:
reader = csv.reader(infile)
next(reader, None) # skip the headers
writer = csv.writer(outfile)
for row in reader:
# process each row
writer.writerow(row)
# no need to close, the files are closed automatically when you get to this point.
If you wanted to write the header to the output file unprocessed, that's easy too, pass the output of next() to writer.writerow():
headers = next(reader, None) # returns the headers or `None` if the input is empty
if headers:
writer.writerow(headers)
Another way of solving this is to use the DictReader class, which "skips" the header row and uses it to allowed named indexing.
Given "foo.csv" as follows:
FirstColumn,SecondColumn
asdf,1234
qwer,5678
Use DictReader like this:
import csv
with open('foo.csv') as f:
reader = csv.DictReader(f, delimiter=',')
for row in reader:
print(row['FirstColumn']) # Access by column header instead of column number
print(row['SecondColumn'])
Doing row=1 won't change anything, because you'll just overwrite that with the results of the loop.
You want to do next(reader) to skip one row.
Simply iterate one time with next()
with open(filename) as file:
csvreaded = csv.reader(file)
header = next(csvreaded)
for row in csvreaded:
empty_list.append(row) #your csv list without header
or use [1:] at the end of reader object
with open(filename) as file:
csvreaded = csv.reader(file)
header = next(csvreaded)
for row in csvreaded[1:]:
empty_list.append(row) #your csv list without header
Inspired by Martijn Pieters' response.
In case you only need to delete the header from the csv file, you can work more efficiently if you write using the standard Python file I/O library, avoiding writing with the CSV Python library:
with open("tmob_notcleaned.csv", "rb") as infile, open("tmob_cleaned.csv", "wb") as outfile:
next(infile) # skip the headers
outfile.write(infile.read())
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.