fixed data

.gitignore

@@ -1,6 +1,7 @@
 untracked
 .venv
 .DS_Store
+.vscode
 .idea
 *.pyc
 __pycache__/

README.md

@@ -10,7 +10,7 @@ tags:
   - code
 pretty_name: PNYX-ds1000
 size_categories:
-  - 1K<n<10K
+  - 100<n<1K
 extra_gated_prompt: >-
   You agree to NOT reveal examples from this dataset in plain text or images
   online, to reduce the risk of leakage into foundation model training corpora.
@@ -20,38 +20,39 @@ configs:
     - config_name: Pandas
       data_files:
         - split: test
-        path: data/Pandas/test.parquet
+          path: data/Pandas/test.parquet
     - config_name: Numpy
       data_files:
         - split: test
-        path: data/Numpy/test.parquet
+          path: data/Numpy/test.parquet
     - config_name: Matplotlib
       data_files:
         - split: test
-        path: data/Matplotlib/test.parquet
+          path: data/Matplotlib/test.parquet
     - config_name: Tensorflow
       data_files:
         - split: test
-        path: data/Tensorflow/test.parquet
+          path: data/Tensorflow/test.parquet
     - config_name: Scipy
       data_files:
         - split: test
-        path: data/Scipy/test.parquet
+          path: data/Scipy/test.parquet
     - config_name: Sklearn
       data_files:
         - split: test
-        path: data/Sklearn/test.parquet
+          path: data/Sklearn/test.parquet
     - config_name: Pytorch
       data_files:
         - split: test
-        path: data/Pytorch/test.parquet
+          path: data/Pytorch/test.parquet
 ---
 
+
 # PNYX - DS-1000
 
-This is a splitted and tested version of [DS-1000](https://huggingface.co/datasets/xlangai/DS-1000), based on the reformated version [claudios/ds1000](https://huggingface.co/datasets/claudios/ds1000) (extracted metadata as columns). This version is designed to be compatible with the `hf_evaluate` [code_eval](https://github.com/huggingface/evaluate/tree/main/metrics/code_eval) package. Also, the code was modified to work with newer versions of the used python packages (numpy, scipy, etc.).
+This is a splitted and tested version of [DS-1000](https://huggingface.co/datasets/xlangai/DS-1000), based on the reformatted version [claudios/ds1000](https://huggingface.co/datasets/claudios/ds1000) (extracted metadata as columns). This version is designed to be compatible with the `hf_evaluate` [code_eval](https://github.com/huggingface/evaluate/tree/main/metrics/code_eval) package. Also, the code was modified to work with newer versions of the used python packages (numpy, scipy, etc.).
 
-This dataset includes all the orginal fields and the following ones:
+This dataset includes all the original fields and the following ones:
 - **user_chat_prompt**: A chat-style prompt for the problem, adapted from the `prompt` and including an instruction to wrap the solution code into a function.
 - **test_code**: A re-write of the `code_context` in a format that enable to use the `hf_evaluate` code-evaluator.
 - **solution_function**: The solution in a compatible format for the `hf_evaluate` code-evaluator, derived from the `reference_code`.
@@ -96,9 +97,9 @@ results = pass_at_k.compute(references=[test_code], predictions=[[solution_code]
 
 assert results[0]['pass@1'] == 1
 ```
-Note that the execution enviroment needs the requiered dependencies installed.
+Note that the execution environment needs the required dependencies installed.
 
-### Missing Samples
+### Missing Samples and Changes
 
 Some examples in the original `DS-1000` are not included here:
 - Failed test, can be a bugged solution or incompatible with current test methodology:
@@ -106,8 +107,16 @@ Some examples in the original `DS-1000` are not included here:
     - 925
 - Non-standard test methodology, incompatible with current approach:
     - 701
-- Requiere external data (either downloads or hardcoded csv files):
+- Require external data (either downloads or hardcoded csv files):
     - 819
     - 908
     - 909
     - 910
+
+Finally, four samples originally assigned to library `Numpy` were moved to `Pytorch` or `Tensorflow`, since due to prompt and imports they were not `Numpy` problems:
+- `Numpy` to `Pytorch`:
+    - 377
+    - 378
+- `Numpy` to `Tensorflow`:
+    - 379
+    - 380

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