Datasets:
Formats:
parquet
Size:
10K - 100K
File size: 1,649 Bytes
d52e51d 8112051 d52e51d 9625516 ede32af 9625516 3a4cc91 9625516 a08f663 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
dataset_info:
features:
- name: Text
dtype: string
- name: Cluster
dtype: int32
- name: Polarity
dtype: float64
- name: count_word
dtype: int64
splits:
- name: Cluster_1
num_bytes: 11487341
num_examples: 4797
- name: Cluster_2
num_bytes: 8423711
num_examples: 4025
- name: Cluster_3
num_bytes: 16002250
num_examples: 5026
download_size: 18951480
dataset_size: 35913302
configs:
- config_name: default
data_files:
- split: Cluster_1
path: data/Cluster_1-*
- split: Cluster_2
path: data/Cluster_2-*
- split: Cluster_3
path: data/Cluster_3-*
language:
- en
- es
- ru
- zh
- de
- fr
- th
- ca
- it
- ja
- pl
- eo
- eu
- vi
- fi
- hu
- ar
- nl
- da
- tr
- ko
- he
- id
- cs
- bn
- sv
---
- max count_word cluster_1: 1722
- min count_word cluster_1: 11
- max count_word cluster_2: 2624
- min count_word cluster_2: 21
- max count_word cluster_3: 2370
- min count_word cluster_3: 31
```Python
DatasetDict({
Cluster_1: Dataset({
features: ['Text', 'Cluster', 'Polarity', 'count_word'],
num_rows: 4797
})
Cluster_2: Dataset({
features: ['Text', 'Cluster', 'Polarity', 'count_word'],
num_rows: 4025
})
Cluster_3: Dataset({
features: ['Text', 'Cluster', 'Polarity', 'count_word'],
num_rows: 5026
})
})
```
|