The dialect parameter skipinitialspace when it is True, whitespace immediately following the delimiter is ignored. The default is False.

DictReader ( ) gives OrderedDict by default in its output. An OrderedDict is a dictionary subclass which saves the order in which its contents are added. To remove the OrderedDict use dict ( ).

(i) To read a CSV file into a dictionary can be done by using DictReader class of csv module which works similar to the reader ( )class but creates an object which maps data to a dictionary.
(ii) The keys are given by the fieldnames as parameter.

A dialect is a class of csv module which helps to define parameters for reading and writing CSV. It allows to create, store, and re-use various formatting parameters for data.

Closing a file will free up the resources that were tied with the file and is done using Python close ( ) method.

Python, a file operation takes place in the following order
Step 1: Open a file
Step 2 : Perform Read or write operation
Step 3 : Close the file

If the fields of data in your CSV file contain commas, you can protect them by enclosing those data fields in double-quotes ("). The commas that are part of your data will then be kept separate from the commas which delimit the fields themselves.

To sort by more than one column you can use itemgetter with multiple indices:
operator.itemgetter 
Example:
sortedlist = sorted (data, key = operator. itemgetter(1))

The row heading is get sorted, to avoid the first row should be skipped. This is can be done by using the command "next( )".

A CSV file is a human readable text file where each line has a number of fields, separated by commas or some other delimiter.

Import csv
csvData = [['Student, 'Age'], [Dhanush', '17'], ['Kalyani', '18'], ['Ram', '15']]
with open('c:\\pyprg\\ch13\\Pupil.csv', 'w') as CF:
writer = csv.writer(CF) # CF is the file object
writer.writerows(csvData) # csvData is the List name
CF.close( )

(i) CSV file - data with default delimiter comma (,)
(ii) CSV file - data with Space at the beginning
(ill) CSV file - data with quotes
(iv) CSV file - data with quotes

#importing csv
import csv
#opening the csv file which is in different location with read mode
with open('c:\\pyprg\\ sample1.csv', 'r') as F:
#other way to open the file is f= ('c:\\pyprg\\ sample1.csv', 'r')
reader = csv.reader(F)
# printing each line of the Data row by row
print(row)
F.close ( )

'The syntax for csv.reader() is
csv.reader(fileobject,delimiter,fmtparams)
where
(i) file object: passes the path and the mode of the file.
(ii) delimiter: an optional parameter containing the standard dilects like , | etc can be omitted
(iii) fmtparams: optional parameter which help to override the default values of the dialects like skipinitialspace, quoting etc. Can be omitted.

To create a CSV file using Microsoft Excel, launch Excel and then open the file you want to save in CSV format. For example. below is the data contained in our sample Excel worksheet:

Once the data is entered in the worksheet, select File ⟶ Save As option, and for the "Save as type option" select CSV (Comma delimited) or type the file name along with extension .csv.

To create a CSV file in Notepad,
(i) First open a new file using
File ⟶New or ctrl +N.
(ii) Then enter the data separating each value with a comma and each row with a new line.
(iii) For example consider the following details
Topic1, Topic2, Topic3
one, two, three
Example1, Example2, Example3
(iv) Save this content in a file with the extension.csv.

The main difference between the csv.reader( ) and DictReader( ) is in simple terms csv.reader and csv.writer work with list/ tuple, while csv. DictReader and csv.DictWriter work with dictionary. csv. DictReader and csv. DictWriter take additional argument fieldnames that are used as dictionary keys.

Write mode:
Open a file for writing. Creates a new file if it does not exist or truncates the file if it exists.
Append mode:
Open for appending at the end of the file without truncating it. Creates a new file if it does not exist.

Program: To read a csv file with comma (,)
#importing csv
import csv
#opening the csv file which is in different location with read mode
with open('c:\\Pyprg\ \sample1.csv', 'r') as F:
#other way to open the file is
f=('C:\\pyprg\\sample1.csv', 'r')
reader = csv.reader(F))
#printing each line of the Data row by row.
print (row)
F. close( )
Output:
['SNO','NAME', 'CITY']
['12101', 'RAM', 'CHENNAI']
['12102', 'LAVANYA' "TIRUCHY']
['12103', 'LAKSHMAN', 'MADURAI']

(i) Python has a built-in function open() to open a file. This function returns a file object also called a handle, as it is used to read or modify the file accordingly.
For Example:
>>>f = open ("sample.txt") #open file in current directory # f is file object
>>> f =  open ('c:\\Pyprg\ch13 sample5.csv') # specifying full path
(ii) The default is reading in text mode. In this mode, while reading from the file the data would be in the format of strings.
(iii) On the other hand, binary mode returns bytes and this is the mode to be used when dealing with non-text files like image or exe files.

import csv
with open ('c\\pyprg\\ch13\\ dynamicfile.csv', 'w') as f:
w = csv.writer(f)
ans= 'y'
while (ans=='y'):
name=input("Name?:")
date=input("Date of birth:")
Place=input ("Place:")
w.writerow([name, date, place])
ans=input("Do you want to enter more y/n?:")
F=open('c:\\pyprg\\ch13\\dynamicfile.csv",r')
reader=csv.reader(F)
for row in reader:
print (row)
F.close()

import csv
csv.register_dialect('myDialect', delimiter = '|', quoting=csv.QUOTE_ALL)
with open('c:\\pyprg\\ch13\\ grade.csv', 'w') as csvfile:
fieldnames = ['Name', 'Grade']
writer = csv.DictWriter(csvfile,
fieldnames=fieldnames. dialect ="myDialect")
writer.writeheader()
writer.writerows([{'Grade': 'B', 'Name': Anu'},
{'Grade': 'A', 'Name': 'Beena',},
{Grade': 'C', 'Name': 'Tarun'}])
print("writing completed")

import csv
Data = [['Fruit', 'Quantity'], ['Apple', '5'], ['Banana', '7']' ['Mango: '8']]
csv.register_dialect('mydialect; delimiter = '|', lineterminator = '\n')
with open('c:\\pyprg\\ch3\\line.csv', 'w') as f:
writer = csv.writer(f, dialect='myDialect')
writer.writerows(Data)
f.close ( )

To sort by more than one column you can use itemgetter with multiple indices: operator. itemgetter (1,2).

The following program do the task mentioned above using operator.itemgetter(col_no)
Example:
# Program to sort the entire row by using a specified column.
# declaring multiple header files
import csv, operator
#One more way to read the file
data = csv.reader(open('c:\\PYPRG\ \sample8.csv'))
next(data) #(to omit the header)
#using operator module for sorting multiple columns
sortedlist = sorted (data, key=operator.
itemgetter(1) # 1 specifies we want to sort
# according to second column for row in sortedlist:
print(row)
Output:
['Mouse', '20']
['Keyboard', '48']
['Monitor', '52']

# sort a selected column given by user leaving the header column
import csv
# other way of declaring the filename
inFile= 'c:\\pyprg\\sample6.csv'
# opening the csv file which is in the same location of this
python file
F=open(inFile', 'r')
# reading the File with the help of csv.reader()
reader = csv.reader(F)
# skipping the first row(heading)
next(reader)
# declaring a list
arrayValue = [ ]
a = int(input ("Enter the column number 1 to 3:-"))
# sorting a particular column-cost
for row in reader:
arrayValue.append(row[a])
arrayValue.sort ( )
for row in arrayValue:
print (row)
F.close ( )

Import csv
csv.register_dialect('myDialect', delimiter = '|')
with open ('c:\\pyprg\\sample4.csv', 'r') as f:
reader = csv,reader(f, dialect='myDialect')
for row in reader:
print(row)
f.close( )

import csv
csv.register_dialect('myDialect', delimiter = ',',skipinitialspace = True)
F=open('c:\\pyprg\\sample2.csv', 'r')
reader = csv.reader(F, dialect = 'myDialect')
for row in reader:
print(row)
F.close( )