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I have below code to write my nested list into a csv file. The nested list looks like this
[['19181011', '13041519', '22121605', '11142007', '23000114'],
['1523141612', '2403051513', '0806022324', '1614012422', '0516121805'],
['23201621', '24171811', '08231524', '16011022', '17131220'],
['2317241822', '2220112421', '1124052211', '1010192318', '2108231524'],
['11220215', '24240507', '19180423', '07081422', '21201224']]
with open('MLpredictions.csv', 'w') as f:
writer = csv.writer(f, delimiter=';', lineterminator='\n')
writer.writerows(high5_pred)
But when i execute this code, i get like below in the csv file:
19181011;13041519;22121605;11142007;23000114
1523141612;2403051513;0806022324;1614012422;0516121805....
i changed the delimiter to ',' but then I get 5 different columns.
I want each list to be 1 row separated by ',' and not ';'.
Expected o/p, a single column:
19181011,13041519,22121605,11142007,23000114
1523141612,2403051513,0806022324,1614012422,0516121805
Any ideas how to do this?
Assuming that there is a specific reason why you want the data all in one column:
The reason you're getting seperate columns is because you're using the csv format, and your data is not escaped. Your raw file looks like this:
19181011,13041519,22121605,11142007,23000114
1523141612,2403051513,0806022324,1614012422,0516121805
but you need it to look like this:
"19181011,13041519,22121605,11142007,23000114"
"1523141612,2403051513,0806022324,1614012422,0516121805"
You're probably best to create a string object for each "row" of your output file. I'd do the following:
with open('MLpredictions.csv', 'w') as f:
writer = csv.writer(f, delimiter=';', lineterminator='\n')
rows = [','.join([str(number) for number in row]) for row in high5_pred]
writer.writerows(rows)
Note: unless you have a good reason why you don't want these numbers in different columns, I'd leave your code as is. It will be a lot easier to deal with the native csv format
So I have a CSV file like this,
how can I separate them into different columns like this,
using python without using the pandas lib.
Implementation that should work in python 3.6+.
import csv
with open("input.csv", newline="") as inputfile:
with open("output.csv", "w", newline="") as outputfile:
reader = csv.DictReader(inputfile) # reader
fieldnames = reader.fieldnames
writer = csv.DictWriter(outputfile, fieldnames=fieldnames) # writer
# make header
writer.writeheader()
# loop over each row in input CSV
for row in reader:
# get first column
column: str = str(row[fieldnames[0]])
numbers: list = column.split(",")
if len(numbers) != len(fieldnames):
print("Error: Lengths not equal")
# write row in output CSV
writer.writerow({field: num for field, num in zip(fieldnames, numbers)})
Explanation of the code:
The above code takes two file names input.csv and output.csv. The names being verbose don't need any further explanation.
It reads each row from input.csv and writes corresponding row in output.csv.
The last line is a "dictionary comprehension" combined with zip (similar to "list comprehensions" for lists). It's a nice way to do a lot of stuff in a single line but same code in expanded form looks like:
row = {}
for field, num in zip(fieldnames, numbers):
row[field] = num
writer.writerow(row)
It is already separated into different columns by , as separator, but the european version of excel usually uses ; as separator. You can specify the separator, when you import the csv:
https://support.microsoft.com/en-us/office/import-or-export-text-txt-or-csv-files-5250ac4c-663c-47ce-937b-339e391393ba
If you really want to change the file content with python use the replace function and replace , with ;: How to search and replace text in a file?
I have a CSV file with one column that has a person's first and last name. I am trying to use a CSV to split each name into two columns, first and last. The code below splits all of the first names into one row and all of the last names into one row instead of having a first name into a row and the last name in the next column next the the first name. Thanks for your time.
Code:
import csv
with open('fullnames.csv','r') as f:
reader = csv.reader(f)
newcsvdict = {"first name": [], "last name": []}
for row in reader:
first = row[0].split()[0]
last = row[0].split()[1]
newcsvdict["first name"].append(first)
newcsvdict["last name"].append(last)
with open('new.csv','w') as f:
w = csv.DictWriter(f, newcsvdict.keys())
w.writeheader()
w.writerow(newcsvdict)
Output:
In this simple case there is little benefit in using a csv.DictWriter, just use csv.writer:
import csv
header = ['first name', 'last name']
with open('fullnames.csv', 'r') as infile, open('new.csv', 'w') as outfile:
writer = csv.writer(outfile)
writer.writerow(header)
writer.writerows(row[0].split() for row in csv.reader(infile))
This works fine provided that the name column in the input CSV always consists of exactly one first name and one surname separated by whitespace. However, if there can be double-barrelled surnames, e.g. Helena Bonham Carter, you need to be more careful about splitting the name. This might work:
row[0].split(' ', 1)
but it assumes that the separator is exactly one space.
You can use pandas to write your csv (you could actually use pandas for the whole problem), this will automatically transpose you data from a dict of columns to a list of rows:
import pandas as pd
df = pd.DataFrame(newcsvdict)
df.to_csv('new.csv', index=False)
You're creating a single list associated with key. Either use Pandas, as #maxymoo suggested, or write each line separately.
import csv
with open(r'~/Documents/names.csv', 'r') as fh:
reader = csv.reader(fh)
with open(r'~/Documents/output.csv', 'w+') as o:
writer = csv.writer(o)
for row in reader:
output = row[0].split(' ', 1)
writer.writerow(output)
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 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.