Update README.md

README.md

@@ -17,7 +17,6 @@ The files in this dataset are as follows:
 
 - `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.
 - `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.
-- `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.**
 
 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). 
 
@@ -79,12 +78,12 @@ metadata = pd.read_csv("metadata.csv")
 
 ### Loading text block data
 
-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.
+Once loaded into a Huggingface Dataset or Pandas DataFrame object the parquet file can be converted to other formats, e.g. Excel, CSV or JSON.
 
 ``` py
-# Reading from parquet
-text_blocks = pd.read_parquet("full_text.parquet")
+# Using huggingface (easiest)
+dataset = load_dataset("ClimatePolicyRadar/global-stocktake-documents")
 
-# Reading from jsonl
-text_blocks = pd.read_json("full_text.jsonl", lines=True)
+# Using pandas
+text_blocks = pd.read_parquet("full_text.parquet")
 ```