YAML datasets (YAMLd) is a tiny subset of YAML designed specifically for representing tabular data (such as CSV). It is particularly useful for datasets with numerous features or lengthy sequences that are hard to read.

• The file ends with a top-level key data or dataset that contains the list of entries in the dataset.
• Everything before is considered meta-data. If you are using pandas, it will be loaded in the attrs property of the dataframe.

features_description:
  name: 'embloyee name'
  age: 'age'
  city: 'closest city to adress'

extra: 3.4

dataset:
  - name: 'John Doe'
    age: 30
    city: 'New York'
  - name: 'Jane Smith'
    age: 25
    city: 'San Francisco'
  - name: 'Bob Johnson'
    age: 35
    city: 'Chicago'

Using a 'mini' version of this, you can remove the feature names from each line as follows.

data:
  - name: 'John Doe'
    age: 30
    city: 'New York'
  - - 'Jane Smith'
    - 25
    - 'San Francisco'
  - - 'Bob Johnson'
    - 35
    - 'Chicago'

You can also remove feature names completly.

Note: This library is still experimental, use it with caution.

A simple example:

import yamld

#Read dataframe
dataframe = yamld.read_dataframe('your_yamld_file.yaml')

#Print meta-data
print(dataframe.attrs)

#Write dataframe to a file
yamld.write_dataframe('new_yamld_file.yaml', dataframe)

#Read yamld as a generator of `dict` values
dataset_gen = yamld.read_generator('your_yamld_file.yaml')

Note: this API is subject to change.

csv2yamld <your-csv-file>

yamld2csv <your-yamld-file>

For more details use csv2yamld -h or yamld2csv -h.

Reading CSV can be annoying, here is a simple solution:

csv2yamld <your-csv-file> --stdout | nvim -c 'set filetype=yaml' -

Of course, you can edit it, save it, and convert it back to CSV using yamld2csv.

pip install -U yamld

To install without virtual environments, you can use pipx.

The main goal is to edit and view your data files with nothing but your text editor. Consequently, a lot of YAML features are not parsed after the top-level key-word data or dataset, as their inclusion could either introduce clutter or hinder the parsing efficiency for dataset. For example, YAML explicit types markings and comments are not supported.

• Dataset data types:
  • List: surrounded with []
  • String: surrounded with "" or ''
  • Number

• No meta, only dataset: This can be done by providing only a list using the dash charachter. Example:

- - 30
  - 'New York'
- - 25
  - 'San Francisco'

• Meta data only: A YAML file with no top-level dataset or data key and it is not only a list of dash charachters is read exactly as any YAML file.

meta_val: "some_value"
another_meta_val: "another_value"