What is csv package in python?
Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Reading and Writing CSV Files Show
Let’s face it: you need to get information into and out of your programs through more than just the keyboard and console. Exchanging information through text files is a common way to share info between programs. One of the most popular formats for exchanging data is the CSV format. But how do you use it? Let’s get one thing clear: you don’t have to (and you won’t) build your own CSV parser from scratch. There are several perfectly acceptable libraries you can use. The Python In this article, you’ll learn how to read, process, and parse CSV from text files using Python. You’ll see how CSV files work, learn the all-important So let’s get started! What Is a CSV File?A CSV file (Comma Separated Values file) is a type of plain text file that uses specific structuring to arrange tabular data. Because it’s a plain text file, it can contain only actual text data—in other words, printable ASCII or Unicode characters. The structure of a CSV file is given away by its name. Normally, CSV files use a comma to separate each specific data value. Here’s what that structure looks like:
Notice how each piece of data is separated by a comma. Normally, the first line identifies each piece of data—in other words, the name of a data column. Every subsequent line after that is actual data and is limited only by file size constraints. In general, the separator character is called a delimiter, and the comma is not the only one used. Other popular delimiters include the tab ( Where Do CSV Files Come From?CSV files are normally created by programs that handle large amounts of data. They are a convenient way to export data from spreadsheets and databases as well as import or use it in other programs. For example, you might export the results of a data mining program to a CSV file and then import that into a spreadsheet to analyze the data, generate graphs for a presentation, or prepare a report for publication. CSV files are very easy to work with programmatically. Any language that supports text file input and string manipulation (like Python) can work with CSV files directly. Parsing CSV Files With Python’s Built-in CSV LibraryThe Reading CSV Files With csvReading from a CSV file is done using the Here’s the
Here’s code to read it:
This results in the following output:
Each row returned by the Reading CSV Files Into a Dictionary With csvRather than deal with a list of individual Again, our input file,
Here’s the code to read it in as a dictionary this time:
This results in the same output as before:
Where did the dictionary keys come from? The first line of the CSV file is assumed to contain the keys to use to build the dictionary. If you don’t have these in your CSV file, you should specify your own keys by setting the Optional Python CSV reader ParametersThe
These parameters deserve some more explanation. Suppose you’re working with the following
This CSV file contains three fields: There are three different ways to handle this situation:
Writing CSV Files With csvYou can also write to a CSV file using a
The
Reading the file back in plain text shows that the file is created as follows:
Writing CSV File From a Dictionary With csvSince you can read our data into a dictionary, it’s only fair that you should be able to write it out from a dictionary as well:
Unlike The code above generates the following output file:
Parsing CSV Files With the pandas LibraryOf course, the Python CSV library isn’t
the only game in town. Reading CSV files is possible in
Installing As is using We won’t delve into
the specifics of how Reading CSV Files With pandasTo show some of the power of
Reading the CSV into a
That’s it: three lines of code, and only one of them is doing the actual work.
Here are a few points worth noting:
Let’s tackle these issues one at a time. To use a different column as the
Now the
Next, let’s fix the data type of the
Notice the difference in the output:
The date is now formatted properly, which is easily confirmed in interactive mode: >>>
If your CSV files doesn’t have column names in the first line, you can use the
Notice that, since the column names changed, the columns specified in the
Writing CSV Files With pandasOf course, if you can’t get your data out of
The only difference between this code and the reading code above is that the
ConclusionIf you understand the basics of reading CSV files, then you won’t ever be caught flat footed when you need to deal with importing data. Most CSV reading, processing, and writing tasks can be easily handled by the basic Are there other
ways to parse text files? Of course! Libraries like ANTLR, PLY, and PlyPlus can all handle heavy-duty parsing, and if simple But those are topics for other articles… Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Reading and Writing CSV Files What is CSV package?Package csv reads and writes comma-separated values (CSV) files. There are many kinds of CSV files; this package supports the format described in RFC 4180. A csv file contains zero or more records of one or more fields per record. Each record is separated by the newline character.
What is CSV used for in Python?A CSV file (Comma Separated Values file) is a type of plain text file that uses specific structuring to arrange tabular data. Because it's a plain text file, it can contain only actual text data—in other words, printable ASCII or Unicode characters. The structure of a CSV file is given away by its name.
Which library is used for CSV files in Python?To write to a CSV file in Python, we can use the csv. writer() function. The csv. writer() function returns a writer object that converts the user's data into a delimited string.
How do I run a CSV file in Python?Steps to read a CSV file:. Import the csv library. import csv.. Open the CSV file. The .open() method in python is used to open files and return a file object. ... . Use the csv.reader object to read the CSV file. csvreader = csv.reader(file). Extract the field names. ... . Extract the rows/records. ... . Close the file.. |