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chapter05 fix for issue#34 #35

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chapter05 fix for issue#34 #35

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9d5750e
fix TfidfVectorizer(stop_words=list(stopwords))
bmerkle Jan 4, 2025
1d660b9
Update TfidfVectorizer to use list of stopwords
bmerkle Jan 4, 2025
cef1092
Add files to .gitignore for chapter 04
bmerkle Jan 4, 2025
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5 changes: 5 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -127,3 +127,8 @@ dmypy.json

# Pyre type checker
.pyre/

# files created by notebook instructions
ch04/lid.176.ftz
ch04/reddit_dataframe.pkl
ch04/reddit-selfposts.db
30 changes: 14 additions & 16 deletions ch05/Feature_Engineering_Similarity.ipynb
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Expand Up @@ -451,7 +451,7 @@
"source": [
"from spacy.lang.en.stop_words import STOP_WORDS as stopwords\n",
"print(len(stopwords))\n",
"tfidf = TfidfVectorizer(stop_words=stopwords)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords))\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"dt"
]
Expand All @@ -469,7 +469,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords, min_df=2)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), min_df=2)\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"dt"
]
Expand All @@ -480,7 +480,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords, min_df=.0001)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), min_df=.0001)\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"dt"
]
Expand All @@ -498,7 +498,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords, max_df=0.1)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), max_df=0.1)\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"dt"
]
Expand Down Expand Up @@ -527,11 +527,11 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords, ngram_range=(1,2), min_df=2)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), ngram_range=(1,2), min_df=2)\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"print(dt.shape)\n",
"print(dt.data.nbytes)\n",
"tfidf = TfidfVectorizer(stop_words=stopwords, ngram_range=(1,3), min_df=2)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), ngram_range=(1,3), min_df=2)\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])\n",
"print(dt.shape)\n",
"print(dt.data.nbytes)"
Expand Down Expand Up @@ -575,7 +575,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords))\n",
"dt = tfidf.fit_transform(headlines[\"lemmas\"].map(str))\n",
"dt"
]
Expand All @@ -586,7 +586,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords))\n",
"dt = tfidf.fit_transform(headlines[\"nav\"].map(str))\n",
"dt"
]
Expand Down Expand Up @@ -634,7 +634,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf = TfidfVectorizer(stop_words=stopwords, min_df=2)\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), min_df=2)\n",
"dt = tfidf.fit_transform(headlines[\"lemmas\"].map(str))\n",
"dt"
]
Expand Down Expand Up @@ -690,7 +690,7 @@
"source": [
"# there are \"test\" headlines in the corpus\n",
"stopwords.add(\"test\")\n",
"tfidf = TfidfVectorizer(stop_words=stopwords, ngram_range=(1,2), min_df=2, norm='l2')\n",
"tfidf = TfidfVectorizer(stop_words=list(stopwords), ngram_range=(1,2), min_df=2, norm='l2')\n",
"dt = tfidf.fit_transform(headlines[\"headline_text\"])"
]
},
Expand Down Expand Up @@ -764,9 +764,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"metadata": {},
"outputs": [],
"source": [
"%%time\n",
Expand Down Expand Up @@ -841,7 +839,7 @@
"metadata": {},
"outputs": [],
"source": [
"tfidf_word = TfidfVectorizer(stop_words=stopwords, min_df=1000)\n",
"tfidf_word = TfidfVectorizer(stop_words=list(stopwords), min_df=1000)\n",
"dt_word = tfidf_word.fit_transform(headlines[\"headline_text\"])"
]
},
Expand Down Expand Up @@ -880,7 +878,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "blueprints",
"language": "python",
"name": "python3"
},
Expand All @@ -894,7 +892,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
"version": "3.12.8"
},
"toc": {
"base_numbering": 1,
Expand Down