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Python utility packages

Project description

Utility Functions for python

pip install chitti

Pretty print

from chitti import pprint, pprint_nl
brands = ['apple', 'samsung', 'pixel', 'one plus']

pprint(brands)
OUT:
apple
samsung
pixel
one plus

pprint_nl(brands)
OUT:
apple

samsung

pixel

one plus

Color Words in text

from chitti import color_words_in_text
text = 'camera is awesome and battery is good'
words = ['camera', 'battery']
color_words_in_text(text, words, color='green', text_color='white')

Train and Validation split

Splits dataframe into train and val dataframes
Split each category into 80% train and 20% val

from chitti.train_test_split import train_val_split

path = 'data.csv'
df = pd.read_csv(path)

text_col='Article_clean'
target_col='NewsType'
train_df, val_df = train_val_split(df, text_col=text_col, target_col=target_col, size=0.8)

print(train_df[target_col].value_counts())
print(val_df[target_col].value_counts())

Download pretrained word vectors

Supported Vectors:

  • GloVe.6B.50d
  • GloVe.6B.100d
  • GloVe.6B.200d
  • GloVe.6B.300d
  • GloVe.42B.300d
  • GloVe.840B.300d
  • GloVe.Twitter.25d
  • GloVe.Twitter.50d
  • GloVe.Twitter.100d
  • GloVe.Twitter.200d

This will download specified vector and creates two files

  • word_index.pkl => word2index dictionary
  • embedding_matrix.npy => Numpy matrix of size (vocab_size, embedding_size)
from chitti.nlp import download_pretrained_vectors, download_pretrained_vectors_
download_pretrained_vectors('GloVe.6B.50d')
download_pretrained_vectors_('glove.6B.50d.txt')

Text cleaning Utils

from chitti.nlp import stem_words, lemmatize_words
from chitti.nlp import remove_punctuation, remove_stopwords, space_punctuation

text = 'i, love. you    ..... ,,, !!! ?? ?> >> '
print(remove_punctuation(text))
OUT:
'i love you'

Project details


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Files for chitti, version 0.2.7
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