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@@ -16,7 +16,8 @@ This repo contains the data for the first [UNFCCC Global Stocktake](https://unfc
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  The files in this dataset are as follows:
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  - `metadata.csv`: a CSV containing document metadata for each document we have collected. **This metadata may not be the same as what's stored in the source databases** – we have cleaned and added metadata where it's corrupted or missing.
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- - `full_text.jsonl`: a jsonlines file containing the full text of each document we have parsed. Each row is a text block (paragraph) with all the associated text block and document metadata.
 
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  A research tool you can use to view this data and the results of some classifiers run on it is at [gst1.org](https://gst1.org).
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@@ -78,7 +79,7 @@ metadata = pd.read_csv("metadata.csv")
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  ### Loading text block data
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- **The parquet file is recommended** as it stores the data much more (10x) more efficiently, meaning lower load on your system's memory requirements.
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  ``` py
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  # Reading from parquet
 
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  The files in this dataset are as follows:
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  - `metadata.csv`: a CSV containing document metadata for each document we have collected. **This metadata may not be the same as what's stored in the source databases** – we have cleaned and added metadata where it's corrupted or missing.
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+ - `full_text.parquet`: a parquet file containing the full text of each document we have parsed. Each row is a text block (paragraph) with all the associated text block and document metadata.
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+ - `full_text.jsonl`: a JSON file containing the same data as the parquet file. **It's recommended to use the parquet file as it stores the data 10x more efficiently.**
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  A research tool you can use to view this data and the results of some classifiers run on it is at [gst1.org](https://gst1.org).
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  ### Loading text block data
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+ As mentioned at the top of this README **the parquet file is recommended over JSON** as it stores the data much more (10x) more efficiently, meaning lower load on your system's memory requirements.
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  ``` py
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  # Reading from parquet