{"id":125763,"date":"2022-06-17T09:05:29","date_gmt":"2022-06-17T09:05:29","guid":{"rendered":"https:\/\/blog.finxter.com\/?p=425456"},"modified":"2022-06-17T09:05:29","modified_gmt":"2022-06-17T09:05:29","slug":"convert-csv-to-dictionary-in-python","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2022\/06\/17\/convert-csv-to-dictionary-in-python\/","title":{"rendered":"Convert CSV to Dictionary in Python"},"content":{"rendered":"
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5\/5 – (1 vote) <\/div>\n<\/div>\n
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\"\"<\/figure>\n<\/div>\n

The best way to convert a CSV file to a Python dictionary is to create a CSV file object f<\/code> using open(\"my_file.csv\")<\/code> and pass it in the csv.DictReader(f)<\/code> method. The return value is an iterable of dictionaries, one per row in the CSV file, that maps the column header from the first row to the specific row value.<\/p>\n<\/p>\n

Let’s have a look at a simple example to demonstrate this solution next!<\/p>\n

Basic Solution: CSV to Dict Example<\/h2>\n

Here’s the content of an example CSV file \"my_file.csv\"<\/code> used in our code snippet below:<\/p>\n

Name,Job,Age,Income\nAlice,Programmer,23,110000\nBob,Executive,34,90000\nCarl,Sales,45,50000<\/code><\/pre>\n
If you visualize this CSV in table form, it looks like this:<\/p>\n
\n\n\n\n\n\n\n\n
Name<\/th>\nJob<\/th>\nAge<\/th>\nIncome<\/th>\n<\/tr>\n<\/thead>\n
Alice<\/td>\nProgrammer<\/td>\n23<\/td>\n110000<\/td>\n<\/tr>\n
Bob<\/td>\nExecutive<\/td>\n34<\/td>\n90000<\/td>\n<\/tr>\n
Carl<\/td>\nSales<\/td>\n45<\/td>\n50000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n
Here’s the code to convert that CSV file to multiple dictionaries, one dictionary<\/a> per row by using the csv.DictReader(file)<\/code> function:<\/p>\n
import csv csv_filename = 'my_file.csv' with open(csv_filename) as f: reader = csv.DictReader(f) for row in reader: print(row)<\/pre>\n
A dictionary<\/a> is a data structure that maps keys to values.<\/p>\n
The output of the previous code snippet shows how the first row of the CSV is used as a header to determine the keys of the dictionary that are mapped to the values defined in the individual rows of the CSV file: <\/p>\n
{'Name': 'Alice', 'Job': 'Programmer', 'Age': '23', 'Income': '110000'}\n{'Name': 'Bob', 'Job': 'Executive', 'Age': '34', 'Income': '90000'}\n{'Name': 'Carl', 'Job': 'Sales', 'Age': '45', 'Income': '50000'}<\/code><\/pre>\n<\/p>\n
The csv.DictReader(f)<\/code> method takes a file object f<\/code> as an input argument. So, you first need to open the file using the built-in Python open()<\/a><\/code> function.<\/p>\n
\"\ud83e\udeb2\" Note<\/strong>: A common error is to pass the filename as a string—but this doesn’t work! The csv.DictReader(f)<\/code> method expects a file object as a required argument.<\/p>\n
One-Liner Solution: CSV to Dict<\/h2>\n
I love Python one-liners. That’s why I have written a book<\/a> on those after all. \"\ud83d\ude42\"<\/p>\n
So, can we convert a CSV to a list of dictionaries in a single line of Python?<\/strong><\/p>\n
Of course, we can!<\/p>\n
Here’s the one-liner that accomplishes the same as the code discussed before:<\/p>\n
import csv; print(*csv.DictReader(open('my_file.csv')), sep='\\n')<\/pre>\n
\"\ud83d\udca1\" Explanation<\/strong>: We import the csv<\/code> module, use the semicolon<\/a> ;<\/code> to package two statements in one line, unpack<\/a> *<\/code> all rows from the csv.DictReader()<\/code> output in a print<\/code> statement, and use the newline character '\\n'<\/code> as a separator<\/a> between two dictionary rows.<\/p>\n
The output is the same as before:<\/p>\n
{'Name': 'Alice', 'Job': 'Programmer', 'Age': '23', 'Income': '110000'}\n{'Name': 'Bob', 'Job': 'Executive', 'Age': '34', 'Income': '90000'}\n{'Name': 'Carl', 'Job': 'Sales', 'Age': '45', 'Income': '50000'}<\/code><\/pre>\n
If you just want to store the CSV contents in a list of dictionaries rather than printing<\/a> them, you can use the following technique:<\/p>\n
import csv; lst=[*csv.DictReader(open('my_file.csv'))]; print(lst)<\/pre>\n
The output is a list of dictionaries<\/a>, one per (non-header) row of the original CSV:<\/p>\n
[{'Name': 'Alice', 'Job': 'Programmer', 'Age': '23', 'Income': '110000'}, {'Name': 'Bob', 'Job': 'Executive', 'Age': '34', 'Income': '90000'}, {'Name': 'Carl', 'Job': 'Sales', 'Age': '45', 'Income': '50000'}]<\/pre>\n
If you’re interested in learning one-liners<\/a> as well, feel free to check out my book:<\/p>\n
Python One-Liners Book: Master the Single Line First!<\/h2>\n
Python programmers will improve their computer science skills with these useful one-liners.<\/strong><\/p>\n
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\"Python<\/a><\/figure>\n<\/div>\n
Python One-Liners<\/em> <\/a>will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. <\/em><\/strong>You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.<\/p>\n
The book’s five chapters cover (1) tips and tricks, (2) regular expressions, (3) machine learning, (4) core data science topics, and (5) useful algorithms. <\/p>\n
Detailed explanations of one-liners introduce key computer science concepts <\/em><\/strong>and boost your coding and analytical skills<\/em><\/strong>. You’ll learn about advanced Python features such as list comprehension<\/strong><\/em>, slicing<\/em><\/strong>, lambda functions<\/em><\/strong>, regular expressions<\/em><\/strong>, map <\/em><\/strong>and reduce <\/em><\/strong>functions, and slice assignments<\/em><\/strong>. <\/p>\n
You’ll also learn how to:<\/p>\n