Update parquet files

.gitattributes

@@ -1,27 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bin.* filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zstandard filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,178 +0,0 @@
----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- en
-license:
-- other
-multilinguality:
-- monolingual
-size_categories:
-- 100K<n<1M
-source_datasets:
-- original
-task_categories:
-- text-classification
-task_ids:
-- intent-classification
-paperswithcode_id: null
-pretty_name: BingCoronavirusQuerySet
-dataset_info:
-  features:
-  - name: id
-    dtype: int32
-  - name: Date
-    dtype: string
-  - name: Query
-    dtype: string
-  - name: IsImplicitIntent
-    dtype: string
-  - name: Country
-    dtype: string
-  - name: PopularityScore
-    dtype: int32
-  config_name: country_2020-09-01_2020-09-30
-  splits:
-  - name: train
-    num_bytes: 22052706
-    num_examples: 317856
-  download_size: 16351450
-  dataset_size: 22052706
----
-
-# Dataset Card for BingCoronavirusQuerySet
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** None
-- **Repository:** https://github.com/microsoft/BingCoronavirusQuerySet
-- **Paper:** Nonewww
-- **Leaderboard:** [More Information Needed]
-- **Point of Contact:** [More Information Needed]
-
-### Dataset Summary
-
-Please note that you can specify the start and end date of the data. You can get start and end dates from here: https://github.com/microsoft/BingCoronavirusQuerySet/tree/master/data/2020
-
-example:
-
-```
-load_dataset("bing_coronavirus_query_set", queries_by="state", start_date="2020-09-01", end_date="2020-09-30")
-```
-
-You can also load the data by country by using `queries_by="country"`.
-
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed]
-
-### Languages
-
-[More Information Needed]
-
-## Dataset Structure
-
-### Data Instances
-
-[More Information Needed]
-
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-[More Information Needed]
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-[More Information Needed]
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
-
-### Licensing Information
-
-[More Information Needed]
-
-### Citation Information
-
-[More Information Needed]
-
-### Contributions
-
-Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.

bing_coronavirus_query_set.py

@@ -1,131 +0,0 @@
-# coding=utf-8
-# Copyright 2020 HuggingFace Datasets Authors.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# Lint as: python3
-
-import datasets
-
-
-_DESCRIPTION = """\
-This dataset was curated from the Bing search logs (desktop users only) over the period of Jan 1st, 2020 – (Current Month - 1). Only searches that were issued many times by multiple users were included. The dataset includes queries from all over the world that had an intent related to the Coronavirus or Covid-19. In some cases this intent is explicit in the query itself (e.g., “Coronavirus updates Seattle”), in other cases it is implicit , e.g. “Shelter in place”. The implicit intent of search queries (e.g., “Toilet paper”) was extracted using random walks on the click graph as outlined in this paper by Microsoft Research. All personal data were removed.
-"""
-_HOMEPAGE_URL = "https://github.com/microsoft/BingCoronavirusQuerySet"
-_CITATION = None
-
-_VERSION = "1.0.0"
-_BASE_URL = "https://raw.githubusercontent.com/microsoft/BingCoronavirusQuerySet/master/data/2020/{}_{}_{}.tsv"
-
-
-class BingCoronavirusQuerySetConfig(datasets.BuilderConfig):
-    def __init__(self, *args, queries_by=None, start_date=None, end_date=None, **kwargs):
-        super().__init__(
-            *args,
-            name=f"{queries_by}_{start_date}_{end_date}",
-            **kwargs,
-        )
-        self.queries_by = queries_by
-        self.start_date = start_date
-        self.end_date = end_date
-
-
-class BingCoronavirusQuerySet(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        BingCoronavirusQuerySetConfig(
-            queries_by="country",
-            start_date="2020-09-01",
-            end_date="2020-09-30",
-            description="Query by: country, start_date: 2020-09-01, end_date: 2020-09-30",
-            version=datasets.Version(_VERSION),
-        )
-    ]
-    BUILDER_CONFIG_CLASS = BingCoronavirusQuerySetConfig
-
-    def _info(self):
-        if self.config.queries_by == "country":
-            features = datasets.Features(
-                {
-                    "id": datasets.Value("int32"),
-                    "Date": datasets.Value("string"),
-                    "Query": datasets.Value("string"),
-                    "IsImplicitIntent": datasets.Value("string"),
-                    "Country": datasets.Value("string"),
-                    "PopularityScore": datasets.Value("int32"),
-                },
-            )
-        elif self.config.queries_by == "state":
-            features = datasets.Features(
-                {
-                    "id": datasets.Value("int32"),
-                    "Date": datasets.Value("string"),
-                    "Query": datasets.Value("string"),
-                    "IsImplicitIntent": datasets.Value("string"),
-                    "State": datasets.Value("string"),
-                    "Country": datasets.Value("string"),
-                    "PopularityScore": datasets.Value("int32"),
-                },
-            )
-        else:
-            raise Exception("Unknown queries_by. Choose one of: country or state")
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE_URL,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        def _base_url(queries_by, start_date, end_date):
-            if queries_by == "country":
-                queries_by = "QueriesByCountry"
-            else:
-                queries_by = "QueriesByState"
-            return _BASE_URL.format(queries_by, start_date, end_date)
-
-        download_url = _base_url(self.config.queries_by, self.config.start_date, self.config.end_date)
-        path = dl_manager.download_and_extract(download_url)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"datapath": path},
-            )
-        ]
-
-    def _generate_examples(self, datapath):
-        with open(datapath, encoding="utf-8") as f:
-            for sentence_counter, row in enumerate(f):
-                if sentence_counter == 0:
-                    continue
-                row = row.strip().split("\t")
-                if self.config.queries_by == "country":
-                    resp = {
-                        "id": sentence_counter,
-                        "Date": row[0],
-                        "Query": row[1],
-                        "IsImplicitIntent": row[2],
-                        "Country": row[3],
-                        "PopularityScore": row[4],
-                    }
-                else:
-                    resp = {
-                        "id": sentence_counter,
-                        "Date": row[0],
-                        "Query": row[1],
-                        "IsImplicitIntent": row[2],
-                        "State": row[3],
-                        "Country": row[4],
-                        "PopularityScore": int(row[5]),
-                    }
-                yield sentence_counter, resp

country_2020-09-01_2020-09-30/bing_coronavirus_query_set-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a46fc363e489e5e37ab6a2988977605bd3d7906183f88ed4e0c318a1cf5049fc
+size 6768101

dataset_infos.json

@@ -1 +0,0 @@
-{"country_2020-09-01_2020-09-30": {"description": "This dataset was curated from the Bing search logs (desktop users only) over the period of Jan 1st, 2020 \u2013 (Current Month - 1). Only searches that were issued many times by multiple users were included. The dataset includes queries from all over the world that had an intent related to the Coronavirus or Covid-19. In some cases this intent is explicit in the query itself (e.g., \u201cCoronavirus updates Seattle\u201d), in other cases it is implicit , e.g. \u201cShelter in place\u201d. The implicit intent of search queries (e.g., \u201cToilet paper\u201d) was extracted using random walks on the click graph as outlined in this paper by Microsoft Research. All personal data were removed.\n", "citation": "", "homepage": "https://github.com/microsoft/BingCoronavirusQuerySet", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "Date": {"dtype": "string", "id": null, "_type": "Value"}, "Query": {"dtype": "string", "id": null, "_type": "Value"}, "IsImplicitIntent": {"dtype": "string", "id": null, "_type": "Value"}, "Country": {"dtype": "string", "id": null, "_type": "Value"}, "PopularityScore": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "bing_coronavirus_query_set", "config_name": "country_2020-09-01_2020-09-30", "version": "0.0.0", "splits": {"train": {"name": "train", "num_bytes": 22052706, "num_examples": 317856, "dataset_name": "bing_coronavirus_query_set"}}, "download_checksums": {"https://raw.githubusercontent.com/microsoft/BingCoronavirusQuerySet/master/data/2020/QueriesByCountry_2020-09-01_2020-09-30.tsv": {"num_bytes": 16351450, "checksum": "ff0eac0790cd4a276cb83c74200d692b0b38b6dc36cfc93b513415aed3dc724b"}}, "download_size": 16351450, "post_processing_size": null, "dataset_size": 22052706, "size_in_bytes": 38404156}}