CNAE-9

Donated on 8/2/2012

This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a subset of 9 categories

Dataset Characteristics

Multivariate, Text

Subject Area

Business

Associated Tasks

Classification

Feature Type

Integer

# Instances

1080

# Features

-

Dataset Information

Additional Information

This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a subset of 9 categories cataloged in a table called National Classification of Economic Activities (Classificação Nacional de Atividade Econômicas - CNAE). The original texts were pre-processed to obtain the current data set: initially, it was kept only letters and then it was removed prepositions of the texts. Next, the words were transformed to their canonical form. Finally, each document was represented as a vector, where the weight of each word is its frequency in the document. This data set is highly sparse (99.22% of the matrix is filled with zeros).

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
no
no
no
no
no
no
no
no
no
no

0 to 10 of 857

Additional Variable Information

In the data set there are 857 attributes, 1 attributes with the class of instance and 856 with word frequency: 1. category: range 1 - 9 (integer) 2 - 857. word frequency: (integer)

Dataset Files

FileSize
CNAE-9.data1.8 MB
CNAE-9.names2.2 KB

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Download (1.8 MB)
Install the ucimlrepo package 
pip install ucimlrepo
Import the dataset into your code 
from ucimlrepo import fetch_ucirepo 
  
# fetch dataset 
cnae_9 = fetch_ucirepo(id=233) 
  
# data (as pandas dataframes) 
X = cnae_9.data.features 
y = cnae_9.data.targets 
  
# metadata 
print(cnae_9.metadata) 
  
# variable information 
print(cnae_9.variables)
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Citation
Ciarelli, P. & Oliveira, E. (2009). CNAE-9 [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C51G7P.
Style:

Creators

Patrick Ciarelli

Elias Oliveira

DOI

License

This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.

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