TheGreatRambler/mm2_level_comments

Mario Maker 2 level comments

Part of the Mario Maker 2 Dataset Collection

Dataset Description

The Mario Maker 2 level comment dataset consists of 31.9 million level comments from Nintendo's online service totaling around 20GB of data. The dataset was created using the self-hosted Mario Maker 2 api over the course of 1 month in February 2022.

How to use it

The Mario Maker 2 level comment dataset is a very large dataset so for most use cases it is recommended to make use of the streaming API of datasets. You can load and iterate through the dataset with the following code:

from datasets import load_dataset

ds = load_dataset("TheGreatRambler/mm2_level_comments", streaming=True, split="train")
print(next(iter(ds)))

#OUTPUT:
{
 'data_id': 3000006,
 'comment_id': '20200430072710528979_302de3722145c7a2_2dc6c6',
 'type': 2,
 'pid': '3471680967096518562',
 'posted': 1561652887,
 'clear_required': 0,
 'text': '',
 'reaction_image_id': 10,
 'custom_image': [some binary data],
 'has_beaten': 0,
 'x': 557,
 'y': 64,
 'reaction_face': 0,
 'unk8': 0,
 'unk10': 0,
 'unk12': 0,
 'unk14': [some binary data],
 'unk17': 0
}

Comments can be one of three types: text, reaction image or custom image. type can be used with the enum below to identify different kinds of comments. Custom images are binary PNGs.

You can also download the full dataset. Note that this will download ~20GB:

ds = load_dataset("TheGreatRambler/mm2_level_comments", split="train")

Data Structure

Data Instances

{
 'data_id': 3000006,
 'comment_id': '20200430072710528979_302de3722145c7a2_2dc6c6',
 'type': 2,
 'pid': '3471680967096518562',
 'posted': 1561652887,
 'clear_required': 0,
 'text': '',
 'reaction_image_id': 10,
 'custom_image': [some binary data],
 'has_beaten': 0,
 'x': 557,
 'y': 64,
 'reaction_face': 0,
 'unk8': 0,
 'unk10': 0,
 'unk12': 0,
 'unk14': [some binary data],
 'unk17': 0
}

Data Fields

Field	Type	Description
data_id	int	The data ID of the level this comment appears on
comment_id	string	Comment ID
type	int	Type of comment, enum below
pid	string	Player ID of the comment creator
posted	int	UTC timestamp of when this comment was created
clear_required	bool	Whether this comment requires a clear to view
text	string	If the comment type is text, the text of the comment
reaction_image_id	int	If this comment is a reaction image, the id of the reaction image, enum below
custom_image	bytes	If this comment is a custom drawing, the custom drawing as a PNG binary
has_beaten	int	Whether the user had beaten the level when they created the comment
x	int	The X position of the comment in game
y	int	The Y position of the comment in game
reaction_face	int	The reaction face of the mii of this user, enum below
unk8	int	Unknown
unk10	int	Unknown
unk12	int	Unknown
unk14	bytes	Unknown
unk17	int	Unknown

Data Splits

The dataset only contains a train split.

Enums

The dataset contains some enum integer fields. This can be used to convert back to their string equivalents:

CommentType = {
    0: "Custom Image",
    1: "Text",
    2: "Reaction Image"
}

CommentReactionImage = {
    0: "Nice!",
    1: "Good stuff!",
    2: "So tough...",
    3: "EASY",
    4: "Seriously?!",
    5: "Wow!",
    6: "Cool idea!",
    7: "SPEEDRUN!",
    8: "How?!",
    9: "Be careful!",
    10: "So close!",
    11: "Beat it!"
}

CommentReactionFace = {
    0: "Normal",
    16: "Wink",
    1: "Happy",
    4: "Surprised",
    18: "Scared",
    3: "Confused"
}

Dataset Creation

The dataset was created over a little more than a month in Febuary 2022 using the self hosted Mario Maker 2 api. As requests made to Nintendo's servers require authentication the process had to be done with upmost care and limiting download speed as to not overload the API and risk a ban. There are no intentions to create an updated release of this dataset.

Considerations for Using the Data

The dataset consists of comments from many different Mario Maker 2 players globally and as such their text could contain harmful language. Harmful depictions could also be present in the custom images.