- What is a CSV file?
- Why would you want to open a CSV file in Python?
- How to open a CSV file in Python
- How to read data from a CSV file in Python
- How to write data to a CSV file in Python
- How to append data to a CSV file in Python
- How to delete data from a CSV file in Python
- How to close a CSV file in Python
This tutorial will show you how to open a CSV file in Python using the built-in csv module.
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In this article, we will show you how to open a CSV file in Python using the csv module.
A CSV (comma-separated values) file is a text file that stores data in a tabular format. Each row in the file contains one data record. Each record consists of one or more fields, separated by commas.
The csv module provides functionality to both read from and write to CSV files. It also comes with a number of features to make working with CSV files more efficient and pleasant.
What is a CSV file?
A CSV file is a comma-separated values file, which allows data to be stored in a tabular format. Python has a built-in module called csv that allows you to read and write CSV files.
In order to open a CSV file in Python, you must use the csv module, which is a part of the standard library. The csv module provides a number of functions and classes to read and write tabular data in CSV format.
The first step is to import the csv module:
Next, you need to create a Reader object:
csvreader = csv.reader(open(“filename.csv”, “rb”))
Why would you want to open a CSV file in Python?
There are many reasons why you would want to open a CSV file in Python. One reason is that you may want to perform some sort of data analysis on the data in the CSV file. For example, you may want to calculate the mean, median, or mode of the data in the CSV file. Another reason why you would want to open a CSV file in Python is if you wanted to modify the data in some way. For example, you may want to add or delete certain columns or rows of data.
How to open a CSV file in Python
There are a number of ways to open a CSV file in Python. One way is to use the built-in open() function. This function takes two arguments, the first being the name of the file to be opened and the second being the mode in which the file should be opened. The mode argument can take on one of three values: ‘r’ for reading, ‘w’ for writing, and ‘a’ for appending. For example, to open a CSV file for reading, you would use the following code:
with open(‘file.csv’, ‘r’) as f:
data = f.read()
How to read data from a CSV file in Python
There are a number of ways to read data from a CSV file in Python. CSV (comma separated values) files are a common format for storing structured data.
One common way to read CSV files in Python is to use the built-in open() function. This function takes two arguments, the first is the path to the CSV file and the second is a list of options.
The most common option for reading CSV files is the “r” option, which stands for “read”. This option tells Python that we want to open the file for reading purposes. We can also specify other options such as “w” for write or “a” for append.
Once we have opened the file, we can then use theCSV module’s reader() function to read the contents of the file. This function returns an iterator that can be used to loop over the rows of the CSV file.
Each row returned by the reader() function is itself a list of values, one value for each column in the CSV file. We can loop over this list and print out each value:
with open(‘some.csv’, ‘r’) as f:
reader = csv.reader(f)
for row in reader:
How to write data to a CSV file in Python
In Python, there is no need for importing external library for file handling. The csv module implements classes to read and write tabular data in CSV format. It contains the following classes:
Writing to a CSV File
To write data in a file, we must open the file in writing mode using open() function. To append data to an existing file, open the file in append mode using ‘a’ value as second argument to open(). For a complete list of possible modes, see the documentation of the built-in function open(). By default, the newline character ‘\n’ is used as line terminator. We can change this using newline parameter of open(). For example,
with open(‘eggs.csv’, ‘w’, newline=”) as csvfile:
spamwriter = csv.writer(csvfile, delimiter=’ ‘,
spamwriter.writerow([‘Spam’] * 5 + [‘Baked Beans’])
spamwriter.writerow([‘Spam’, ‘Lovely Spam’, ‘Wonderful Spam’])
This will write following data rows to eggs2.csv file:
Spam Spam Spam Spam Spam Baked Beans
Spam Lovely Spam Wonderful Spam
We use delimiter parameter to specify a different delimiter other than the default ‘,’ for separating row values (it defaults to ‘,’). In our example above ‘|’ is used as delimiter character. For escaped characters or non-printable characters, we use quotechar parameter along with quoting parameter (it defaults to QUOTE_MINIMAL). The valid values of quoting are given below −
QUOTE_MINIMAL – It instructs writer objects only to quote those fields which contain special characters like delimiter, quotechar or any of the characters in lineterminator . This is the least flexible quoting method . Unlike double quote method , it does not treat two consecutive delimiters as one each . But it does not protect row and field separators from accidental occurrence in data . So , for best results don’t add field or row separators inside quoted fields , like this – 1,”field1=”value1″,field2=”value2″,field3=”value3″ so that Python csv module correctly skips them and thus prevents their unintentionally appearing in correct places later during Pandas Dataframe reassembling from complete list of all rows stored earlier during writer object’s writerows method call , because if these separators did accidentally occur inside quoted field values then they would split up python’s internally remembered current row into two different python lists – each containing one part of split up row – and so if you had written 2 rows before this mishap then when you would now read these written 2 rows back through reader object then first list representing first completerow would be followed by second incomplete list consisting only value part corresponding to that one split column plus also a value corresponding very first field in next row i . e third written column (so this way 6 attempted column fields total) because that was from where actual split apart happened , so second dataframe constructed during subsequent reading step would have only 3 columns instead of 5 columns whereas you were expecting 5 and similarly heppens bit differently with QUOTE_ALL option where two consecative commas run also get considered as empty string possibility inside field value too i . e just like what happens when string quotes get missed out during csv input cell entered by user but here reading behaviour want quite same upfront during splitting stage itself ) ; but we will see more about it bit later here itself under – discussion item 12 , But just keep in mind here right now that such accidental situation can occur while typing input cell normally by users themselves while they omit out string quotes around text where they see fit or dont see fit ; but once you have finalised your pandas import command line syntax completely then such accidental omission mistakes shouldnt occur anymore ! So do take care or precaution anyway !
QUOTE_NONNUMERIC – It works same way like minimal mode option but it instructs writer objects only Quote those fields which are non-numeric ? i think what does it mean ? may be those fields which dont represent any numeric number ? So probably instead those format strings which are associated with numeric types could be said more precisely here ? Anyways lets see some examples bit later below on this itself simply how such numeric formatting strings look like suchlike eg : %Y %m %d %H:%M:%S etc
How to append data to a CSV file in Python
There are a number of ways to append data to a CSV file using the Python programming language. One common method is to use the built-in open() function to open the file in read mode, append desired content to the file, and then close it. Another popular method is to use the with keyword, which automatically closes the file after writing is complete.
How to delete data from a CSV file in Python
CSV files are very easy to work with in Python. We can use the CSV module to read in the contents of a CSV file, and then we can delete data from it using the delete method.
To start, we need to import the CSV module:
We also need to open our CSV file. We’ll do that with the open() function:
my_file = open(“my_csv_file.csv”, “r”)
Once we have our file object, we can use the reader() method to read in the contents of our CSV file:
reader = csv.reader(my_file)
We can then loop through our reader object to delete data from our CSV file:
for row in reader:
# if the row meets some condition
# delete the row
How to close a CSV file in Python
CSV files are a common type of file used for storing data. They store data in a tabular format, with each row representing a different record and each column representing a different field. CSV files are easy to read and write, and they can be used in many different programming languages.
To close a CSV file in Python, you can use the close() method. This method takes no arguments, and it will close the file that is currently open.
What is a CSV file?
A CSV (comma-separated values) file is a text file that stores information in a tabular format. Each row in the file represents a record, and each column represents a field. CSV files are commonly used to store data from spreadsheets and databases.
How do I open a CSV file in Python?
You can open a CSV file using the built-in open() function or the csv module.
How do I read data from a CSV file in Python?
You can read data from a CSV file using the csv module.