Free CSV to YAML formatter — upload or paste — no server

Convert CSV to YAML
Proper quoting,
any structure.

Q: How do I convert CSV to YAML?

Upload your CSV to CSVShift, choose sequence of mappings or keyed object mode, enable type coercion if your data has numbers, and click Convert. Copy the YAML to your clipboard or download the .yaml file.

Q: How do I convert CSV to YAML in Python?

import csv, yaml; rows = list(csv.DictReader(open('file.csv'))); print(yaml.dump(rows, default_flow_style=False)). Requires: pip install pyyaml. For type coercion, use yaml.safe_dump() which handles Python native types.

Q: What YAML structure is best for CSV data?

A sequence of mappings (list of dicts) is the most common and idiomatic YAML representation for tabular CSV data. Each CSV row becomes a YAML mapping block starting with - , with column headers as keys. This maps directly to a list of dicts in Python, Ruby, and most languages that parse YAML.

Free CSV to YAML converter. Sequence of mappings or keyed object. Correct YAML scalar quoting — strings that look like booleans, numbers or reserved words are quoted automatically. Type coercion, custom indent. Runs in your browser.

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Correct YAML string quoting

Sequence or keyed mapping

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YAML structure

Key column

Value types

Empty fields

Indentation

YAML generated

YAML structure modes

Two idiomatic ways to represent tabular data in YAML.

Sequence of mappings (default)

- name: Alice
  age: 32
  active: true
- name: Bob
  age: 28
  active: false

Each CSV row becomes a YAML mapping block starting with -. Maps directly to a list of dicts in Python, Ruby, Go and most YAML parsers. The most common structure for data files.

Keyed mapping

Alice:
  age: 32
  active: true
Bob:
  age: 28
  active: false

First column (or chosen key column) becomes the top-level key. Maps to a dict of dicts. Useful for lookup tables, configuration files and data indexed by a unique identifier.

YAML string quoting — why it matters

Values that look like YAML keywords must be quoted — or they parse as the wrong type.

CSV value	YAML output	Why
true	true	YAML boolean — no quotes needed (with type detection on)
yes	true	YAML treats yes/no/on/off as booleans in YAML 1.1
True	'True'	Capitalised — quoted to preserve as string if types off
null	null	YAML null — no quotes needed (with type detection on)
~	null	Tilde is YAML null shorthand
42	42	Integer — unquoted with type detection on
0755	'0755'	Octal-looking — quoted to preserve leading zero
Alice: Smith	'Alice: Smith'	Contains `: ` — would parse as a mapping key
New York, NY	New York, NY	Commas are safe in YAML values — no quoting needed

CSV to YAML in Python

Code examples for scripting workflows.

Python — csv + PyYAML

import csv, yaml with open('data.csv', newline='') as f: rows = list(csv.DictReader(f)) # Sequence of mappings (default): print(yaml.dump(rows, default_flow_style=False, allow_unicode=True)) # Keyed mapping (indexed by 'name' column): keyed = {row['name']: {k:v for k,v in row.items() if k != 'name'} for row in rows} print(yaml.dump(keyed, default_flow_style=False))

Requires: pip install pyyaml. yaml.dump() applies correct YAML quoting automatically — strings that look like booleans or numbers are quoted to prevent type misinterpretation.

Python — pandas + PyYAML

import pandas as pd, yaml df = pd.read_csv('data.csv') # Convert to list of dicts with Python-native types rows = df.to_dict(orient='records') print(yaml.dump(rows, default_flow_style=False))

df.to_dict(orient='records') preserves pandas type inference — integers stay as int, floats as float. yaml.dump() then serialises these native Python types as proper YAML scalars.

When do you need CSV to YAML?

Common developer workflows that require YAML from CSV data.

Configuration files

Application configuration and environment settings are often maintained in spreadsheets and need to be deployed as YAML config files. Converting the CSV to keyed YAML mapping produces a file that loads directly into any YAML-based config system (Kubernetes, Helm, Ansible).

Test fixtures and seed data

Test suites in Ruby on Rails, Django and many frameworks use YAML fixture files to seed databases. Converting a CSV dataset to YAML sequence-of-mappings produces fixture files ready to load with rails db:fixtures:load or Django's fixture framework.

Kubernetes and Helm values

Helm chart values files are YAML. Converting a CSV of environment-specific settings (hostnames, resource limits, feature flags) to keyed YAML produces a values file that overrides chart defaults per environment.

Ansible and infrastructure-as-code

Ansible inventory and variable files use YAML. Converting host lists or variable tables from CSV to YAML sequence-of-mappings produces files compatible with Ansible's group_vars and host_vars directory structure.

Related CSV tools

Other free converters on CSVShift you might need.

All data format converters

YAML generated
in your browser. Correctly.

Most CSV-to-YAML tools treat every value as a string and wrap it in quotes — producing valid but verbose YAML. CSVShift applies the correct YAML 1.2 scalar resolution rules: reserved words (true, false, null, yes, no, on, off) are detected and handled based on your type coercion setting. Strings that resemble reserved words but should stay as strings are quoted with the most appropriate quote style.

Correct YAML quoting

Reserved words, special characters, and values with colons or hash signs are quoted — not silently broken.

Block literal scalars

Multiline values in CSV cells are serialised as YAML literal block scalars using the | indicator.

Two structure modes

Sequence of mappings for lists of records; keyed mapping for lookup tables and config files.

Free, no conditions

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Frequently asked questions

Common questions about converting CSV to YAML format.

How do I convert CSV to YAML?

Upload your CSV or paste it into CSVShift, choose sequence of mappings or keyed object mode, enable type coercion if your data has numbers and booleans, and click Convert. Copy the YAML or download the .yaml file.

What YAML structure is best for CSV data?

A sequence of mappings (list of dicts) is the most idiomatic structure for tabular data — each row becomes a mapping block starting with -. Use a keyed mapping when the data has a natural unique identifier column and you need to look up records by that key.

How do I convert CSV to YAML in Python?

import csv, yaml; rows = list(csv.DictReader(open('f.csv'))); print(yaml.dump(rows, default_flow_style=False)). Requires pip install pyyaml. yaml.dump() applies correct YAML quoting — strings that resemble booleans or numbers are quoted automatically.

Why do some string values get quoted in YAML?

YAML parsers interpret unquoted values like true, yes, null, 42 as booleans, nulls and numbers respectively. If your CSV has a "status" column with the value yes that should stay as the string "yes", it must be quoted as 'yes' in YAML. With type coercion off, CSVShift quotes these values to preserve them as strings.

Is my data safe when converting CSV to YAML online?

Yes. CSVShift generates YAML entirely in your browser. Your CSV is never uploaded to any server. Open the Network inspector during conversion — zero outbound data requests are made.

Convert CSV to YAMLProper quoting,any structure.