[Tut] 7 Best Ways to Convert Dict to CSV in Python

[xSicKxBot]

7 Best Ways to Convert Dict to CSV in Python

5/5 – (1 vote)

Question: How to convert a dictionary to a CSV in Python?

In Python, convert a dictionary to a CSV file using the

Code:

DictWriter()

method from the

Code:

csv

module. The

Code:

csv.DictWriter()

method allows you to insert a dictionary-formatted row (keys=column names; values=row elements) into the CSV file using its

Code:

DictWriter.writerow()

method.

Learn More: If you want to learn about converting a list of dictionaries to a CSV, check out this Finxter tutorial.

Method 1: Python Dict to CSV in Pandas

First, convert a list of dictionaries to aPandas DataFrame that provides you with powerful capabilities such as the

Second, convert the Pandas DataFrame to a CSV file using the DataFrame’s

Code:

to_csv()

method with the filename as argument.

Code:

salary = [{'Name':'Alice', 'Job':'Data Scientist', 'Salary':122000}, {'Name':'Bob', 'Job':'Engineer', 'Salary':77000}, {'Name':'Carl', 'Job':'Manager', 'Salary':119000}] # Method 1 import pandas as pd df = pd.DataFrame(salary) df.to_csv('my_file.csv', index=False, header=True)

Output:

Code:

Name,Job,Salary Alice,Data Scientist,122000 Bob,Engineer,77000 Carl,Manager,119000

You create a Pandas DataFrame—which is Python’s default representation of tabular data. Think of it as an Excel spreadsheet within your code (with rows and columns).

The DataFrame is a very powerful data structure that allows you to perform various methods. One of those is the

Code:

to_csv()

method that allows you to write its contents into a CSV file.

• You set the
  Code:

  index
  argument of the
  Code:

  to_csv()
  method to
  Code:

  False
  because Pandas, per default, adds integer row and column indices 0, 1, 2, …. Again, think of them as the row and column indices in your Excel spreadsheet. You don’t want them to appear in the CSV file so you set the arguments to
  Code:

  False
  .
  
  
• You set the and
  Code:

  header
  argument to
  Code:

  True
  because you want the dict keys to be used as headers of the CSV.
  

If you want to customize the CSV output, you’ve got a lot of special arguments to play with. Check out this Finxter Tutorial for a comprehensive list of all arguments.

Related article:Pandas Cheat Sheets to Pin to Your Wall

Method 2: Dict to CSV File

In Python, convert a dictionary to a CSV file using the

Code:

DictWriter()

method from the

Code:

csv

module. The

Code:

csv.DictWriter()

method allows you to insert data into the CSV file using its

Code:

DictWriter.writerow()

method.

The following example writes the dictionary to a CSV using the keys as column names and the values as row values.

Code:

import csv data = {'A':'X1', 'B':'X2', 'C':'X3'} with open('my_file.csv', 'w', newline='') as f: writer = csv.DictWriter(f, fieldnames=data.keys()) writer.writeheader() writer.writerow(data)

The resulting file

Code:

'my_file.csv'

looks like this:



The

Code:

csv

library may not yet installed on your machine. To check if it is installed, follow these instructions. If it is not installed, fix it by running

Code:

pip install csv

in your shell or terminal.

Method 3: Dict to CSV String (in Memory)

To convert a list of dicts to a CSV string in memory, i.e., returning a CSV string instead of writing in a CSV file, use the

Code:

pandas.DataFrame.to_csv()

function without file path argument. The return value is a CSV string representation of the dictionary.

Here’s an example:

Code:

import pandas as pd data = [{'A':'X1', 'B':'X2', 'C':'X3'}, {'A':'Y1', 'B':'Y2', 'C':'Y3'}] df = pd.DataFrame(data) my_csv_string = df.to_csv(index=False) print(my_csv_string) ''' A,B,C X1,X2,X3 Y1,Y2,Y3 '''

We pass

Code:

index=False

because we don’t want an index 0, 1, 2 in front of each row.

Method 4: Dict to CSV Append Line

To append a dictionary to an existing CSV, you can open the file object in append mode using

Code:

open('my_file.csv', 'a', newline='')

and using the

Code:

csv.DictWriter()

to append a dict row using

Code:

DictWriter.writerow(my_dict)

.

Given the following file

Code:

'my_file.csv'

:



You can append a row (dict) to the CSV file via this code snippet:

Code:

import csv row = {'A':'Y1', 'B':'Y2', 'C':'Y3'} with open('my_file.csv', 'a', newline='') as f: writer = csv.DictWriter(f, fieldnames=row.keys()) writer.writerow(row)

After running the code in the same folder as your original

Code:

'my_file.csv'

, you’ll see the following result:



Method 5: Dict to CSV Columns

To write a Python dictionary in a CSV file as a column, i.e., a single (key, value) pair per row, use the following three steps:

• Open the file in writing mode and using the
  Code:

  newline=''
  argument to prevent blank lines.
  
  
• Create a CSV writer object.
  
  
• Iterate over the (key, value) pairs of the dictionary using the
  Code:

  dict.items()
  method.
  
  
• Write one
  Code:

  (key, value)
  tuple at a time by passing it in the
  Code:

  writer.writerow()
  method.
  

Here’s the code example:

Code:

import csv data = {'A':42, 'B':41, 'C':40} with open('my_file.csv', 'w', newline='') as f: writer = csv.writer(f) for row in data.items(): writer.writerow(row)

Your output CSV file (column dict) looks like this:



Method 6: Dict to CSV with Header

Convert a Python dictionary to a CSV file with header using the

Code:

csv.DictWriter(fileobject, fieldnames)

method to create a writer object used for writing the header via

Code:

writer.writeheader()

without argument. This writes the list of column names passed as

Code:

fieldnames

, e.g., the dictionary keys obtained via

Code:

dict.keys()

.

To write the rows, you can then call the

Code:

DictWriter.writerow()

method.

The following example writes the dictionary to a CSV using the keys as column names and the values as row values.

Code:

import csv data = {'A':'X1', 'B':'X2', 'C':'X3'} with open('my_file.csv', 'w', newline='') as f: writer = csv.DictWriter(f, fieldnames=data.keys()) writer.writeheader() writer.writerow(data)

The resulting file

Code:

'my_file.csv'

looks like this:



Where to Go From Here

If you haven’t found your solution, yet, you may want to check out my in-depth guide on how to write a list of dicts to a CSV:

Guide: Write List of Dicts to CSV in Python

Bonus Method 7: Vanilla Python

If you don’t want to import any library and still convert a list of dicts into a CSV file, you can use standard Python implementation as well: it’s not complicated and very efficient.

Finxter Recommended: Join the Finxter community and download your 8+ Python cheat sheets to refresh your code understanding.

This method is best if you won’t or cannot use external dependencies.

• Open the file
  Code:

  f
  in writing mode using the standard
  Code:

  open()
  function.
  
  
• Write the first dictionary’s keys in the file using the one-liner expression
  Code:

  f.write(','.join(salary[0].keys()))
  .
  
  
• Iterate over the list of dicts and write the values in the CSV using the expression
  Code:

  f.write(','.join(str(x) for x in row.values()))
  .
  

Here’s the concrete code example:

Code:

salary = [{'Name':'Alice', 'Job':'Data Scientist', 'Salary':122000}, {'Name':'Bob', 'Job':'Engineer', 'Salary':77000}, {'Name':'Carl', 'Job':'Manager', 'Salary':119000}] # Method 3 with open('my_file.csv','w') as f: f.write(','.join(salary[0].keys())) f.write('n') for row in salary: f.write(','.join(str(x) for x in row.values())) f.write('n')

Output:

Code:

Name,Job,Salary Alice,Data Scientist,122000 Bob,Engineer,77000 Carl,Manager,119000

In the code, you first open the file object

Code:

f

. Then you iterate over each row and each element in the row and write the element to the file—one by one. After each element, you place the comma to generate the CSV file format. After each row, you place the newline character

Code:

'n'

.

Note: to get rid of the trailing comma, you can check if the element

Code:

x

is the last element in the row within the loop body and skip writing the comma if it is.

Related Tutorial: How to Convert a List to a CSV File in Python [5 Ways]

Programming Humor – Python

[i]“I wrote 20 short programs in Python yesterday. It was wonderful. Perl, I’m leaving you.” — xkcd[/i]

Where to Go From Here?

Enough theory. Let’s get some practice!

Coders get paid six figures and more because they can solve problems more effectively using machine intelligence and automation.

To become more successful in coding, solve more real problems for real people. That’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?

You build high-value coding skills by working on practical coding projects!

Do you want to stop learning with toy projects and focus on practical code projects that earn you money and solve real problems for people?

If your answer is YES!, consider becoming a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

If you just want to learn about the freelancing opportunity, feel free to watch my free webinar “How to Build Your High-Income Skill Python” and learn how I grew my coding business online and how you can, too—from the comfort of your own home.

Join the free webinar now!