---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: ID
    dtype: string
  - name: DOCUMENT_LEVEL_SCORE
    dtype: float64
  - name: DOCUMENT_LEVEL_MAGNITUDE
    dtype: float64
  - name: SENTENCE
    dtype: string
  - name: SENTENCE_SCORE
    dtype: float64
  - name: SENTENCE_MAGNITUDE
    dtype: float64
  - name: LABEL
    dtype: int64
  - name: LENGTH
    dtype: int64
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 328225.8010973937
    num_examples: 1166
  - name: test
    num_bytes: 82197.19890260631
    num_examples: 292
  download_size: 172216
  dataset_size: 410423.0
---
# Dataset Card for "sentiment_data_google"

Dataset for sentiment analysis on sentence level
Here we used google API to get doc level and sentiment level Score

* id2label = {0: "NEGATIVE", 1: "POSITIVE",2:"NEUTRAL"}
* label2id = {"NEGATIVE": 0, "POSITIVE": 1,"NEUTRAL":2}

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)