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

7 Best Ways to Convert Dict to CSV in Python

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

In Python, convert a dictionary to a CSV file using the DictWriter() method from the csv module. The csv.DictWriter() method allows you to insert a dictionary-formatted row (keys=column names; values=row elements) into the CSV file using its 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 a Pandas DataFrame that provides you with powerful capabilities such as the

Second, convert the Pandas DataFrame to a CSV file using the DataFrame’s to_csv() method with the filename as argument.

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:

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

• You set the index argument of the to_csv() method to 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 False.
• You set the and header argument to 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 DictWriter() method from the csv module. The csv.DictWriter() method allows you to insert data into the CSV file using its DictWriter.writerow() method.

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

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 'my_file.csv' looks like this:

The 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 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 pandas.DataFrame.to_csv() function without file path argument. The return value is a CSV string representation of the dictionary.

Here’s an example:

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 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 open('my_file.csv', 'a', newline='') and using the csv.DictWriter() to append a dict row using DictWriter.writerow(my_dict).

Given the following file 'my_file.csv':

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

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 '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 newline='' argument to prevent blank lines.
• Create a CSV writer object.
• Iterate over the (key, value) pairs of the dictionary using the dict.items() method.
• Write one (key, value) tuple at a time by passing it in the writer.writerow() method.

Here’s the code example:

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 csv.DictWriter(fileobject, fieldnames) method to create a writer object used for writing the header via writer.writeheader() without argument. This writes the list of column names passed as fieldnames, e.g., the dictionary keys obtained via dict.keys().

To write the rows, you can then call the DictWriter.writerow() method.

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

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 '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 f in writing mode using the standard open() function.
• Write the first dictionary’s keys in the file using the one-liner expression f.write(','.join(salary[0].keys())).
• Iterate over the list of dicts and write the values in the CSV using the expression f.write(','.join(str(x) for x in row.values())).

Here’s the concrete code example:

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:

Name,Job,Salary

Alice,Data Scientist,122000

Bob,Engineer,77000

Carl,Manager,119000

In the code, you first open the file object 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 'n'.

Note: to get rid of the trailing comma, you can check if the element 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 wrote 20 short programs in Python yesterday. It was wonderful. Perl, I’m leaving you.” — xkcd

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