Convert dataset to Parquet

README.md

@@ -17,8 +17,65 @@ task_categories:
 - other
 task_ids:
 - natural-language-inference
-paperswithcode_id: null
 pretty_name: test
+dataset_info:
+- config_name: customers
+  features:
+  - name: customer_id
+    dtype: int64
+  - name: name
+    dtype: string
+  - name: age
+    dtype: int64
+  splits:
+  - name: train
+    num_bytes: 2164
+    num_examples: 70
+  - name: validation
+    num_bytes: 465
+    num_examples: 15
+  - name: test
+    num_bytes: 463
+    num_examples: 15
+  download_size: 6030
+  dataset_size: 3092
+- config_name: products
+  features:
+  - name: product_id
+    dtype: int64
+  - name: name
+    dtype: string
+  - name: price
+    dtype: float64
+  splits:
+  - name: train
+    num_bytes: 1674
+    num_examples: 56
+  - name: validation
+    num_bytes: 359
+    num_examples: 12
+  - name: test
+    num_bytes: 358
+    num_examples: 12
+  download_size: 6172
+  dataset_size: 2391
+configs:
+- config_name: customers
+  data_files:
+  - split: train
+    path: customers/train-*
+  - split: validation
+    path: customers/validation-*
+  - split: test
+    path: customers/test-*
+- config_name: products
+  data_files:
+  - split: train
+    path: products/train-*
+  - split: validation
+    path: products/validation-*
+  - split: test
+    path: products/test-*
 ---
 
 # Dataset Card for test

dummy_data.zip → customers/test-00000-of-00001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:62ac49720a8a94b6f27b0c575a2004176ded5fa78399c2b03a4fa4cda119d9ea
-size 3631
+oid sha256:5594c80522f04f61c7e8fd71ec9592b60c51deef2a29dc340d9208bd979a6c4e
+size 1750

customers/test.csv

@@ -1,16 +0,0 @@
-,customer_id,name,age
-96,97,Customer_97,40
-4,5,Customer_5,26
-42,43,Customer_43,35
-77,78,Customer_78,32
-10,11,Customer_11,71
-0,1,Customer_1,55
-9,10,Customer_10,71
-69,70,Customer_70,54
-73,74,Customer_74,21
-83,84,Customer_84,22
-44,45,Customer_45,65
-76,77,Customer_77,40
-39,40,Customer_40,29
-33,34,Customer_34,31
-30,31,Customer_31,67

customers/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:879e13f830fe6a77be919acd4942c0048fbd87c0a4e52f2c88166ffba66a50af
+size 2530

customers/train.csv

@@ -1,71 +0,0 @@
-,customer_id,name,age
-11,12,Customer_12,52
-47,48,Customer_48,40
-85,86,Customer_86,24
-28,29,Customer_29,38
-93,94,Customer_94,66
-5,6,Customer_6,46
-66,67,Customer_67,31
-65,66,Customer_66,24
-35,36,Customer_36,62
-16,17,Customer_17,39
-49,50,Customer_50,69
-34,35,Customer_35,51
-7,8,Customer_8,70
-95,96,Customer_96,29
-27,28,Customer_28,79
-19,20,Customer_20,56
-81,82,Customer_82,69
-25,26,Customer_26,50
-62,63,Customer_63,68
-13,14,Customer_14,21
-24,25,Customer_25,57
-3,4,Customer_4,30
-17,18,Customer_18,23
-38,39,Customer_39,22
-8,9,Customer_9,71
-78,79,Customer_79,35
-6,7,Customer_7,53
-64,65,Customer_65,68
-36,37,Customer_37,68
-89,90,Customer_90,70
-56,57,Customer_57,28
-99,100,Customer_100,58
-54,55,Customer_55,53
-43,44,Customer_44,51
-50,51,Customer_51,45
-67,68,Customer_68,60
-46,47,Customer_47,46
-68,69,Customer_69,46
-61,62,Customer_62,52
-97,98,Customer_98,35
-79,80,Customer_80,30
-41,42,Customer_42,72
-58,59,Customer_59,64
-48,49,Customer_49,37
-98,99,Customer_99,46
-57,58,Customer_58,65
-75,76,Customer_76,27
-32,33,Customer_33,79
-94,95,Customer_95,49
-59,60,Customer_60,56
-63,64,Customer_64,59
-84,85,Customer_85,21
-37,38,Customer_38,69
-29,30,Customer_30,77
-1,2,Customer_2,56
-52,53,Customer_53,30
-21,22,Customer_22,52
-2,3,Customer_3,55
-23,24,Customer_24,71
-87,88,Customer_88,36
-91,92,Customer_92,76
-74,75,Customer_75,44
-86,87,Customer_87,30
-82,83,Customer_83,37
-20,21,Customer_21,51
-60,61,Customer_61,51
-71,72,Customer_72,49
-14,15,Customer_15,23
-92,93,Customer_93,24
-51,52,Customer_52,29

customers/val.csv

@@ -1,16 +0,0 @@
-,customer_id,name,age
-26,27,Customer_27,58
-53,54,Customer_54,43
-70,71,Customer_71,22
-15,16,Customer_16,49
-45,46,Customer_46,57
-88,89,Customer_89,73
-40,41,Customer_41,79
-12,13,Customer_13,69
-72,73,Customer_73,79
-55,56,Customer_56,43
-80,81,Customer_81,27
-18,19,Customer_19,58
-90,91,Customer_91,23
-31,32,Customer_32,33
-22,23,Customer_23,53

customers/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a051dec440d31820adb12a02d3170380378626d9b7343766c3e9ce76c23c7f98
+size 1750

dataset_infos.json

@@ -1,61 +0,0 @@
-{
-  "customers": {
-    "description": "This is the customer dataset. It contains information about customer interactions.",
-    "citation": "@inproceedings{author2024dataset,\n  title={A Dataset for Customer Interactions},\n  author={Author, A.},\n  booktitle={Conference on Data},\n  year={2024}\n}",
-    "homepage": "https://example.com/customers",
-    "license": "MIT License",
-    "features": {
-      "customer_id": {
-        "dtype": "int64",
-        "_type": "Value"
-      },
-      "name": {
-        "dtype": "string",
-        "_type": "Value"
-      },
-      "age": {
-        "dtype": "int64",
-        "_type": "Value"
-      }
-    },
-    "download_size": 12345678,
-    "dataset_size": 23456789,
-    "task_categories": [
-      "tabular"
-    ],
-    "task_ids": [
-      "regression"
-    ],
-    "version": "1.0.0"
-  },
-  "products": {
-    "description": "This is the product dataset. It includes details about various products.",
-    "citation": "@inproceedings{author2024dataset,\n  title={A Dataset for Product Analysis},\n  author={Author, B.},\n  booktitle={Product Analytics Conference},\n  year={2024}\n}",
-    "homepage": "https://example.com/products",
-    "license": "Apache License 2.0",
-    "features": {
-      "product_id": {
-        "dtype": "int64",
-        "_type": "Value"
-      },
-      "name": {
-        "dtype": "string",
-        "_type": "Value"
-      },
-      "price": {
-        "dtype": "double",
-        "_type": "Value"
-      }
-    },
-    "download_size": 7890123,
-    "dataset_size": 8901234,
-    "task_categories": [
-      "classification"
-    ],
-    "task_ids": [
-      "binary_classification"
-    ],
-    "version": "1.0.0"
-  }
-}
-

products/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ece099e826b10b8ac169357b631e70eb89fb60981d0ef4c2d2b2d23b799afa74
+size 1775

products/test.csv

@@ -1,13 +0,0 @@
-,product_id,name,price
-4,5,Product_5,269.37079112122996
-73,74,Product_74,685.4914088169825
-30,31,Product_31,455.75885589146424
-55,56,Product_56,417.2148362971622
-33,34,Product_34,535.8877036986996
-12,13,Product_13,850.2555800942548
-35,36,Product_36,884.8205869267379
-0,1,Product_1,781.976413555275
-64,65,Product_65,343.7487279386133
-28,29,Product_29,744.4778261439482
-22,23,Product_23,245.88954088766758
-67,68,Product_68,675.1697127782456

products/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a8bc2fe7220c23d10a87c4b8ec92bb4615b9a10a7b5b6d34880b47b4e021c90
+size 2620

products/train.csv

@@ -1,57 +0,0 @@
-,product_id,name,price
-34,35,Product_35,627.0339105804485
-62,63,Product_63,795.2203625971675
-42,43,Product_43,431.42174870634176
-54,55,Product_55,171.29278952097133
-16,17,Product_17,727.2072210972166
-39,40,Product_40,488.4934137670739
-56,57,Product_57,232.33327948040628
-79,80,Product_80,818.5325554700922
-7,8,Product_8,172.55514641687452
-50,51,Product_51,484.58955660187667
-53,54,Product_54,104.3223454128037
-19,20,Product_20,627.8929825553761
-66,67,Product_67,160.2453054361185
-25,26,Product_26,733.2758690991045
-44,45,Product_45,221.6231309201294
-13,14,Product_14,646.7432023479928
-76,77,Product_77,343.43198976410105
-3,4,Product_4,472.5873287639955
-17,18,Product_18,289.6892006326001
-38,39,Product_39,935.7701837570473
-8,9,Product_9,711.887311071343
-65,66,Product_66,580.6405432081264
-6,7,Product_7,267.3146277123249
-36,37,Product_37,30.57509848504054
-72,73,Product_73,893.1409905386581
-58,59,Product_59,691.6589417200158
-46,47,Product_47,136.55068856676792
-78,79,Product_79,853.188338930974
-15,16,Product_16,450.0831695158656
-27,28,Product_28,881.2456312569794
-41,42,Product_42,566.9732082525446
-26,27,Product_27,742.0870715920396
-48,49,Product_49,894.6951757165921
-24,25,Product_25,794.4546339940993
-43,44,Product_44,587.238548414977
-77,78,Product_78,524.5048062872403
-57,58,Product_58,590.7441471934189
-11,12,Product_12,290.99334081899434
-32,33,Product_33,10.535300745444836
-75,76,Product_76,965.8899199420919
-59,60,Product_60,821.4789406713716
-63,64,Product_64,703.1451760515428
-69,70,Product_70,878.63055771838
-37,38,Product_38,475.778730622188
-29,30,Product_30,911.5928884027744
-1,2,Product_2,607.9732982452558
-52,53,Product_53,669.7002011972322
-21,22,Product_22,170.68073655716717
-2,3,Product_3,521.0349099965142
-23,24,Product_24,704.275434148361
-74,75,Product_75,338.606477325675
-20,21,Product_21,89.88173740252655
-60,61,Product_61,666.7241424290982
-71,72,Product_72,798.0284175208953
-14,15,Product_15,646.53290939936
-51,52,Product_52,319.54741973678875

products/val.csv

@@ -1,13 +0,0 @@
-,product_id,name,price
-45,46,Product_46,238.7534646641605
-31,32,Product_32,272.12339271529373
-18,19,Product_19,702.6422504593837
-5,6,Product_6,286.3477557446952
-61,62,Product_62,876.9379619780921
-9,10,Product_10,507.5089689086898
-47,48,Product_48,457.126492113172
-70,71,Product_71,704.57755157279
-49,50,Product_50,622.5561531442168
-68,69,Product_69,809.4552429423823
-40,41,Product_41,553.2586258624842
-10,11,Product_11,347.22224358729665

products/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9fa184616b9dbb077bae17a8e908b80327902c221609616a4067648031b9f8cd
+size 1777

test.ipynb

@@ -1,81 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/xinzhao/anaconda3/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n",
-      "Using the latest cached version of the module from /Users/xinzhao/.cache/huggingface/modules/datasets_modules/datasets/iszhaoxin--test/ca8172e7372b0c39741729fdfe907438e4d8633843d1f170ac4d65686e2e2300 (last modified on Tue Nov 19 09:59:57 2024) since it couldn't be found locally at iszhaoxin/test, or remotely on the Hugging Face Hub.\n"
-     ]
-    }
-   ],
-   "source": [
-    "from datasets import load_dataset\n",
-    "dataset = load_dataset('iszhaoxin/test', name='customers')  # Replace 'customers' with the appropriate subset name\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from datasets import get_dataset_config_names"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['default']"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "get_dataset_config_names(\"iszhaoxin/test\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "base",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

test.py

@@ -1,87 +0,0 @@
-import os
-from pdb import set_trace
-
-import datasets
-import pandas as pd
-
-_CITATION = """\
-Put your dataset citation here.
-"""
-
-_DESCRIPTION = """\
-Description of your dataset goes here.
-"""
-
-_HOMEPAGE = "https://your-dataset-homepage.com"
-
-_LICENSE = "License information goes here."
-
-
-class Test(datasets.GeneratorBasedBuilder):
-    """Your dataset description"""
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="customers", 
-            version=datasets.Version("1.0.0"), 
-            description="This is subset A"),
-        datasets.BuilderConfig(
-            name="products", 
-            version=datasets.Version("1.0.0"), 
-            description="This is subset B"),
-    ]
-
-    def _info(self):
-        # set_trace()
-        if self.config.name == "customers":
-            features = datasets.Features(
-                {
-                    "customer_id": datasets.Value("int64"),
-                    "name": datasets.Value("string"),
-                    "age": datasets.Value("int64"),
-                }
-            )
-        elif self.config.name == "products":
-            features = datasets.Features(
-                {
-                    "product_id": datasets.Value("int64"),
-                    "name": datasets.Value("string"),
-                    "price": datasets.Value("double"),
-                }
-            )
-        else:
-            raise ValueError(f"Unknown subset: {self.config.name}")
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.manual_dir or "./"
-        data_dir = os.path.join(data_dir, self.config.name)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": os.path.join(data_dir, "train.csv")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepath": os.path.join(data_dir, "val.csv")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": os.path.join(data_dir, "test.csv")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        # set_trace()
-        with open(filepath, encoding="utf-8") as f:
-            df = pd.read_csv(filepath, index_col=0)
-            for id_, item in df.iterrows():
-                yield id_, item.to_dict()