image
imagewidth (px)
89
1.2k
label
class label
2 classes
id
stringlengths
32
32
0charts
c952835c631f003fa2e43a8a97e7339e
0charts
5c9b221cea01fafd6a5098da9b63ee42
0charts
8b3c962949bce78e75e15f7df6e7d3dd
0charts
471387b0bdda87f65e4f049ecc0235e7
0charts
9e13a64481502db3610cb717880910f3
0charts
9ea949458baac0c3bbad840c1ac9d573
0charts
47c243972640d122b85f8ce8886e3de0
0charts
d9605b548af1c6ab8b01b2fc58cc8104
0charts
191b5fa97e7492ec103eae097715aa69
0charts
5642bbb3cd256746452cf40b3b14d5e3
0charts
3053137df3cc0bbd791fd969a889f3f4
0charts
53e1d99a3e52a6e13d0813c772a42278
0charts
1357ac6ae6bfa05c344bd0f10b0b43e0
0charts
248c0b6e2e2cac80ad2d3ab0ca09f576
0charts
60afe85d19352fb80d63a78dfe5c733a
0charts
843b1e38177f80d5eb426e7025bb24a2
0charts
928f6ebfccf896bd2a2b178273db1f2b
0charts
3a84259998570ef51b199ed1ffb20539
0charts
ff0a2d8594b53791fd6ff8253508ea0d
0charts
28ca0f634a20058b04d3afedc599b62c
0charts
4817aa2df0891e3fd93aba396fc0696d
0charts
7124a25c9f5a4ac46162e4e9c1a02d63
0charts
4a5493288137f984a492a3550840c924
0charts
462f23de0e6e5fb2c29a1e1a05926a7e
0charts
7f80b6bb1728503e90df3fb6b3833dc7
0charts
2da52d797dbde8888b1b835525bd1328
0charts
feb70af46f02530d59f7fcd9d92f49d9
0charts
483bc657599e9ad85f6c01e2ddee7504
0charts
0c506cb2495b622376592df85bc11c7c
0charts
d38a68f186a6ace6b43e089a194cfb28
0charts
0b310821842899233bbb138e3e949053
0charts
84533762343e89e3a1e9df6c36f1c333
0charts
68d4c6032e5464fa70413c08eca38558
0charts
f6d5ea362f576c5560dc97ae8c63ebac
0charts
0767bd22652cbe2442d7d5ad12bd63bd
0charts
81e9b9e262a1db3bd2527117c5954fb4
0charts
a1fc254a614741b5cc281ed6fdcee04a
0charts
04b46f253bd6e064e75609600ad11afb
0charts
ae893e2910177711bc75f7c42fc2d182
0charts
b4c91075ca271d9fca83e2fe4155c912
0charts
b9985bebfae543c90d02f4ab7aa8aa22
0charts
2054e7aa357a21bac7136aa2824fd4f9
0charts
19ef705ab0db850ecdd1feb98531a8af
0charts
e5da6bc5db0829e15c10a1f2fc3933e2
0charts
b13b197e249c7b46f39fad3030b8bb19
0charts
7949afd953ab4d7b904e3fa30a970a4c
0charts
72d06bb4ddaa3ba50f3311795d237c9d
0charts
8a54cd057bb8d12e7fa5df8cd180e33f
0charts
ca3dcb35138bb886321dfa5a6cca13b7
0charts
d5594aa2cd1a5f6f8fcaa7c394a72b37
0charts
c720e8602179c9005b59b161a0bd69cb
0charts
afdf4c738c33502cb258a24066037a9b
0charts
50b0b93a4acea03bc84bfb6d86843705
0charts
7ef4d728e6ada11ddf1948769968c9ae
0charts
51b844a6b7ca6fa1c6b87260869679b5
0charts
55c9c102280a736540b0f5a85e011948
0charts
6424d7c602af5e1508a4856fa0424933
0charts
87518d0ea46475f70a03045af5a8f880
0charts
ee67d4fc2423d510ec19381cfa762989
0charts
b78f51b2b8d2ad9ec11363c79a9cb057
0charts
2b7aeb82de24c7e4fcec8a39a6df13d5
0charts
2648bb3539ba7d43ca57b3b042a0b454
0charts
c3ba69980f705b35f3c0c6fed1d47c16
0charts
7809e8876bafa7efa874a4df46de5f7f
0charts
d288c2565ace2699e68514b2d115f358
0charts
4ce21120283ddd0d8ffba306791dc1f0
0charts
797628624628b5f4ccbfb471564bc9fb
0charts
bc277dfccdea47e219bff5a0e3675a84
0charts
827808545f327fbf33d55a48cab799dd
0charts
4f49d909c357e2f6e2273e50b088e9a9
0charts
e0dc638540c930d89db2fdd09bd75525
0charts
640587dfb5e944d5374e2ada9c66b324
0charts
8650a526cb216646ba584a05dba61663
0charts
7e15945e6b556569f161c85a6b37f88e
0charts
3ee992cb5ff867ad37b2bd5e36120bc9
0charts
e9e5f1e3b3b6a593207e1c246fa94e6d
0charts
90eaa098ae8b900f94fecad07b54cdf3
0charts
c2aa223e75f5d4949d870970c655837c
0charts
10f934dfae617d5eec0b5b2d64cd3d54
0charts
4559729f35bef0d8b6e6d992063265f9
0charts
f8035368b40e63fa7ebab7cfc97008d8
0charts
a86dfac3e1180d2f29d9b523a704927f
0charts
fe2c8b53aef7ddf7027f7eea8c54cb03
0charts
7eda5ea3e9716ee90a8953361866a397
0charts
272f08d5e2d4d525b451cb53a7bff09d
0charts
054b2b0936b4b23776ce448904e4d68b
0charts
70680efc5419eaef66a62e0dd02b7503
0charts
83f7aabbeb806b23556be383981b8b5d
0charts
93811e77f3eda0dfd06d64d400a767d6
0charts
56424fcaac5ec41dd684efc718fe3d62
0charts
68f9adf9545ad67447c6772d476c3863
0charts
e449c5a7684b4732219e96b9d113cced
0charts
dda07b57d9dfb3caea0488eadb1be903
0charts
45dbc943471490542b4e3ac2e71f6f99
0charts
6b47b4b3505804fe9a38f2a379112c38
0charts
86ee3944e62c5e1e563d998cd139320a
0charts
94094e34e9c2f36ce838c289484859a4
0charts
2173974de2b69b1ac42e6e8a988d9e0e
0charts
faf1cf5ea5a63a1a72c73b5134d6d2dd
0charts
fdc9c2f6b5e6c3fe7549c7f0c74ea04f

Stock Charts

This dataset is a collection of a sample of images from tweets that I scraped using my Discord bot that keeps track of financial influencers on Twitter. The data consists of images that were part of tweets that mentioned a stock. This dataset can be used for a wide variety of tasks, such as image classification or feature extraction.

FinTwit Charts Collection

This dataset is part of a larger collection of datasets, scraped from Twitter and labeled by a human (me). Below is the list of related datasets.

  • Crypto Charts: Images of financial charts of cryptocurrencies
  • Stock Charts: Images of financial charts of stocks
  • FinTwit Images: Images that had no clear description, this contains a lot of non-chart images

Dataset Structure

Each images in the dataset is structured as follows:

  • Image: The image of the tweet, this can be of varying dimensions.
  • Label: A numerical label indicating the category of the image, with '1' for charts, and '0' for non-charts.

Dataset Size

The dataset comprises 5,203 images in total, categorized into:

  • 4,607 chart images
  • 596 non-chart images

Usage

I used this dataset for training my chart-recognizer model for classifying if an image is a chart or not.

Acknowledgments

We extend our heartfelt gratitude to all the authors of the original tweets.

License

This dataset is made available under the MIT license, adhering to the licensing terms of the original datasets.

Downloads last month
51
Edit dataset card

Models trained or fine-tuned on StephanAkkerman/stock-charts