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100 lines
3.0 KiB
100 lines
3.0 KiB
{
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"metadata": {
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": 3
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},
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"orig_nbformat": 4,
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"coopTranslator": {
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"original_hash": "27de2abc0235ebd22080fc8f1107454d",
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"translation_date": "2025-09-06T15:41:53+00:00",
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"source_file": "6-NLP/3-Translation-Sentiment/solution/notebook.ipynb",
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"language_code": "en"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2,
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from textblob import TextBlob\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# You should download the book text, clean it, and import it here\n",
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"with open(\"pride.txt\", encoding=\"utf8\") as f:\n",
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" file_contents = f.read()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"book_pride = TextBlob(file_contents)\n",
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"positive_sentiment_sentences = []\n",
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"negative_sentiment_sentences = []"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"for sentence in book_pride.sentences:\n",
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" if sentence.sentiment.polarity == 1:\n",
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" positive_sentiment_sentences.append(sentence)\n",
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" if sentence.sentiment.polarity == -1:\n",
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" negative_sentiment_sentences.append(sentence)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"The \" + str(len(positive_sentiment_sentences)) + \" most positive sentences:\")\n",
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"for sentence in positive_sentiment_sentences:\n",
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" print(\"+ \" + str(sentence.replace(\"\\n\", \"\").replace(\" \", \" \")))\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"The \" + str(len(negative_sentiment_sentences)) + \" most negative sentences:\")\n",
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"for sentence in negative_sentiment_sentences:\n",
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" print(\"- \" + str(sentence.replace(\"\\n\", \"\").replace(\" \", \" \")))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n---\n\n**Disclaimer**: \nThis document has been translated using the AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). While we strive for accuracy, please note that automated translations may contain errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is recommended. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.\n"
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]
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}
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]
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} |