JARVIS-DFT 3D dataset (jdft_3d.json)

Dataset for 3D materials
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Websites: 
1) https://jarvis.nist.gov/jarvisdft  ,<br>
2) https://jarvis-tools.readthedocs.io/en/master/databases.html ,
3) https://jarvis-tools.readthedocs.io/en/master/publications.html
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Loading the dataset:
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unzip jdft_3d-12-12-2022.json.zip
import os, json
import pandas as pd
f = open(' jdft_3d-12-12-2022.json', 'r')
data3d=json.load(f)
f.close()
df=pd.DataFrame(data3d)
print (df)
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or
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pip install jarvis-tools
from jarvis.db.figshare import data
data2d = data('dft_3d')
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For more details about using the dataset, use the jupyter-notebooks:
https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks<br>

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本数据集为3D材料数据集。
相关网站如下：
1) https://jarvis.nist.gov/jarvisdft
2) https://jarvis-tools.readthedocs.io/en/master/databases.html
3) https://jarvis-tools.readthedocs.io/en/master/publications.html

数据集加载方式如下：
方式一：解压文件`jdft_3d-12-12-2022.json.zip`，随后通过以下代码加载数据：
python
import os, json
import pandas as pd
f = open(' jdft_3d-12-12-2022.json', 'r')
data3d=json.load(f)
f.close()
df=pd.DataFrame(data3d)
print (df)

方式二：先安装jarvis-tools库，再通过如下代码加载数据：
bash
pip install jarvis-tools

python
from jarvis.db.figshare import data
data2d = data('dft_3d')

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如需了解该数据集的更多使用细节，请参阅Jupyter Notebook示例仓库：https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks