Change column type in Artifact.csv file

README.md

@@ -10,18 +10,18 @@ size_categories:
 dataset_info:
   - config_name: ChAFF
     features:
-      - name: Type
-        dtype: string
-      - name: DatasetName
-        dtype: string
-      - name: AID
-        dtype: int64
-      - name: ID
-        dtype: string
-      - name: IDType
-        dtype: string
-      - name: SMILES
-        dtype: string
+    - name: Type
+      dtype: string
+    - name: DatasetName
+      dtype: string
+    - name: AID
+      dtype: int64
+    - name: ID
+      dtype: string
+    - name: IDType
+      dtype: string
+    - name: SMILES
+      dtype: string
 ---
 
 # ChAFF datasets
@@ -59,7 +59,6 @@ A summary file is uploaded, which lists:
 - Type
 - DatasetName
 - AID
-- AID_confirmatory
 - NumActiveCompounds
 - PaperTitle
 - Reference
@@ -67,7 +66,7 @@ A summary file is uploaded, which lists:
 - AssayName
 - Description
 
-Dataset summary file can be found: ChAFF_dataset_summary.csv
+Dataset summary file can be found: ChAFF_dataset_summary.json
 
 
 # License
@@ -85,14 +84,23 @@ First, from the command line install the `datasets` library
 then, from within python load the datasets library.
 
     >>> import datasets
-
-Now load the 'ChAFF' datasets together,
-
-    >>> assays = datasets.load_dataset("maomlab/ChAFF", split="train")
-
-
-If you are interested in the summary file,
-
-    >>> summary = datasets.load_dataset("json", data_files="https://huggingface.co/datasets/maomlab/ChAFF/resolve/main/summary.json", split="train")
-
-The default split is "train", as we did not split the datasets.
+    >>> from datasets import load_dataset, Features, Value
+
+Specifiy column types to prevent pyarrow error.
+```python
+features = Features({
+    "Type": Value("string"),
+    "DatasetName": Value("string"),
+    "AID": Value("int64"),
+    "ID": Value("string"),
+    "IDType": Value("string"),
+    "SMILES": Value("string")
+})
+```
+
+Now load one of the 'ChAFF' datasets, e.g.,
+
+    >>> dataset = datasets.load_dataset("maomlab/ChAFF", name = "default", data_files = "data/Absorbance.csv", split = "train", features = features)
+
+You can modify "data/Absorbance.csv" based on your interest (e.g., "data/Reactivity.csv"). 
+The default is split = "train" as we did not split the datasets.