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pierjoe
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execcomp-ai

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Tags:
finance
sec
executive-compensation
def14a
proxy-statements
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Dask
Polars
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README.md CHANGED
@@ -27,64 +27,43 @@ dataset_info:
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  dtype: float64
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  splits:
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  - name: train
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- num_bytes: 6435443575
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- num_examples: 55446
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  - name: year_2005
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- num_bytes: 51501082
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  num_examples: 468
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  - name: year_2006
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- num_bytes: 55950632
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  num_examples: 492
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  - name: year_2007
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- num_bytes: 43420175
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  num_examples: 512
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  - name: year_2008
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- num_bytes: 47601529
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  num_examples: 486
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  - name: year_2009
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- num_bytes: 56480988
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  num_examples: 472
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  - name: year_2010
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- num_bytes: 50617002
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  num_examples: 429
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  - name: year_2011
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- num_bytes: 50137863
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  num_examples: 434
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  - name: year_2012
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- num_bytes: 668521206
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- num_examples: 5598
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  - name: year_2013
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- num_bytes: 646243770
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- num_examples: 5379
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  - name: year_2014
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- num_bytes: 630480994
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- num_examples: 5356
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  - name: year_2015
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- num_bytes: 629630120
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- num_examples: 5374
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  - name: year_2016
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- num_bytes: 620157461
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- num_examples: 5239
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  - name: year_2017
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- num_bytes: 594022160
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- num_examples: 5039
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  - name: year_2018
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- num_bytes: 568246306
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- num_examples: 4852
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  - name: year_2019
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- num_bytes: 565281285
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- num_examples: 4944
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  - name: year_2020
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- num_bytes: 553589124
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  num_examples: 4867
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  - name: year_2021
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- num_bytes: 562745567
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- num_examples: 5119
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  - name: year_2022
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- num_bytes: 40797943
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  num_examples: 386
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- download_size: 11668656218
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- dataset_size: 12870868782
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  configs:
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  - config_name: default
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  data_files:
@@ -161,6 +140,12 @@ size_categories:
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  Structured executive compensation data extracted from SEC DEF 14A proxy statements using AI.
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  ```python
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  from datasets import load_dataset
 
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  dtype: float64
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  splits:
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  - name: train
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+ num_examples: 12022
 
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  - name: year_2005
 
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  num_examples: 468
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  - name: year_2006
 
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  num_examples: 492
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  - name: year_2007
 
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  num_examples: 512
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  - name: year_2008
 
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  num_examples: 486
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  - name: year_2009
 
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  num_examples: 472
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  - name: year_2010
 
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  num_examples: 429
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  - name: year_2011
 
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  num_examples: 434
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  - name: year_2012
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+ num_examples: 391
 
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  - name: year_2013
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+ num_examples: 384
 
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  - name: year_2014
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+ num_examples: 430
 
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  - name: year_2015
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+ num_examples: 434
 
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  - name: year_2016
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+ num_examples: 357
 
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  - name: year_2017
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+ num_examples: 369
 
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  - name: year_2018
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+ num_examples: 374
 
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  - name: year_2019
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+ num_examples: 344
 
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  - name: year_2020
 
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  num_examples: 4867
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  - name: year_2021
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+ num_examples: 393
 
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  - name: year_2022
 
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  num_examples: 386
 
 
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  configs:
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  - config_name: default
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  data_files:
 
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  Structured executive compensation data extracted from SEC DEF 14A proxy statements using AI.
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+ ## Available Splits
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+
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+ | Split | Records | Description |
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+ |-------|---------|-------------|
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+ | `train` | 12,022 | All records combined |
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+ | `year_2005` - `year_2022` | varies | Records filtered by filing year |
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  ```python
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  from datasets import load_dataset