YAML to CSV Converter Online – Convert YAML Lists to CSV

How to use the YAML to CSV Converter

Paste YAML into the input editor, upload a .yaml file, use Load URL, or click Sample.

Pick a Delimiter and decide on Include header row, Flatten nested objects and Quote all fields.

Click Convert to CSV; the status bar shows how many records were written.

Copy the CSV or Download it and open it in your spreadsheet app.

Convert YAML to CSV rows and columns

YAML is often used for data that is really a table: a team roster, a product catalog, a list of test cases or feature flags. This YAML to CSV converter turns such a list of records into CSV so you can sort it in a spreadsheet, import it into a database or share it with someone who does not work with YAML. Each record becomes a row and each field becomes a column.

Example

team: platform
members:
  - name: Priya
    role: lead
    skills: [go, k8s]
    address: {city: Austin, zip: "73301"}
  - name: Liam
    role: dev
    skills: [js]

With the default options:

name,role,skills.0,skills.1,address.city,address.zip
Priya,lead,go,k8s,Austin,73301
Liam,dev,js,,,

How the converter finds the table

CSV is flat, so the converter first looks for the list of records inside your document. If the top level is a list, that list is used. If it is a mapping with exactly one list of records next to plain values, as with members above, the converter uses that list, and the scalar siblings such as team: platform are not part of the table. A mapping with no list at all becomes a single row, one column per key.

Columns are the union of all keys across records, in the order they first appear. A record that lacks a field simply gets an empty cell, which is why Liam's address columns are blank.

Flattening nested data

With Flatten nested objects on (the default), nested mappings become dot-notation columns such as address.city, and lists are expanded by position into skills.0, skills.1 and so on. This is the most spreadsheet-friendly layout and the one most import tools expect.

Turn flattening off to keep one column per top-level field. Nested values are then written as JSON text inside the cell:

name,role,skills,address
Priya,lead,"[""go"",""k8s""]","{""city"":""Austin"",""zip"":""73301""}"
Liam,dev,"[""js""]",

That form is useful when the CSV will be read by a program that parses the JSON column again, or when lists vary a lot in length.

Delimiter and quoting

Delimiter – comma, semicolon, pipe or tab. Semicolons suit spreadsheet apps in locales that use a comma as the decimal separator.
Quote all fields – wraps every value in double quotes. Without it, only values that contain the delimiter, quotes or line breaks are quoted, and embedded quotes are doubled (say "hi" becomes "say ""hi""").
Include header row – untick it when you append rows to an existing file.

Things to watch for

Values keep the types YAML gave them. Unquoted 007 is already the number 7 before it reaches the CSV, so quote codes and IDs in the YAML if leading zeros matter.
Spreadsheet apps may reformat values such as long numbers or date-like strings when they open a CSV. If you need exact control over the sheet, use YAML to Excel instead.
Invalid YAML is reported with its line and column instead of producing a partial file.

Going the other way? CSV to YAML rebuilds YAML records from a CSV, and CSV viewer lets you check the output as a table.

Privacy

The conversion runs in your browser; the YAML is not uploaded. Only Load URL and Save & Share involve our server.

Convert YAML to CSV in Python

Load the YAML with PyYAML, then write the records with csv.DictWriter from the standard library. The step people miss is the column list: DictWriter raises ValueError when a record has a key that is not in fieldnames, so collect the keys of every record first. Records that lack a column get an empty cell. When you write to a file instead of sys.stdout, open it with newline="", because the csv module writes its own \r\n line endings.

# pip install pyyaml
import csv
import sys
import yaml

text = """
- name: Priya
  role: lead
  city: Austin
- name: Liam
  role: dev
"""

rows = yaml.safe_load(text)
columns = list(dict.fromkeys(key for row in rows for key in row))

writer = csv.DictWriter(sys.stdout, fieldnames=columns)
writer.writeheader()
writer.writerows(rows)

The converter above returns the same three lines for this input, and it also flattens nested mappings and lists into dot-notation columns, which DictWriter does not do.

Frequently asked questions

Why is a top-level key missing from my CSV?

When the YAML is a mapping that contains one list of records plus plain values, the list becomes the table and the plain values are left out, since they do not belong to any row. Move them into each record if you need them as columns.

How are nested YAML objects converted?

With Flatten nested objects on, each nested key becomes its own column named with dots, for example address.city. With it off, the nested object is written as JSON text in a single cell.

Can I create a semicolon-separated file?

Yes. Choose Semicolon in the Delimiter option. Values containing semicolons are then quoted, while commas inside values no longer need quotes.

Does the converter handle multi-document YAML?

Yes. Documents separated by --- form a list, and each document becomes one row.