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added new exercise #29

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25552a5
added new exercise
SamarjitDebnath Sep 7, 2024
b0e7fc0
added solution for pos exercise (4)
SamarjitDebnath Sep 7, 2024
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61 changes: 40 additions & 21 deletions 7_pos/Exercise/pos_exercise_solution.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -19,24 +19,24 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 2,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"'Inflation rose again in April, continuing a climb that has pushed consumers to the brink and is threatening the economic expansion, the Bureau of Labor Statistics reported Wednesday.\\n\\nThe consumer price index, a broad-based measure of prices for goods and services, increased 8.3% from a year ago, higher than the Dow Jones estimate for an 8.1% gain. That represented a slight ease from March’s peak but was still close to the highest level since the summer of 1982.\\n\\nRemoving volatile food and ene'"
"'Inflation rose again in April, continuing a climb that has pushed consumers to the brink and is threatening the economic expansion, the Bureau of Labor Statistics reported Wednesday.\\n\\nThe consumer price index, a broad-based measure of prices for goods and services, increased 8.3% from a year ago, higher than the Dow Jones estimate for an 8.1% gain. That represented a slight ease from March’s peak but was still close to the highest level since the summer of 1982.\\n\\nRemoving volatile food and energ'"
]
},
"execution_count": 3,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with open(\"news_story.txt\",\"r\") as f:\n",
"with open(\"../news_story.txt\",\"r\") as f:\n",
" news_text = f.read()\n",
" \n",
"news_text[:500]"
Expand All @@ -51,7 +51,7 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -69,7 +69,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 4,
"metadata": {
"scrolled": true
},
Expand All @@ -80,7 +80,7 @@
"[8.3, 8.1, 1982, 6.2, 6, 0.3, 0.2, 0.6, 0.4, 0.1]"
]
},
"execution_count": 10,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -91,7 +91,7 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 5,
"metadata": {
"scrolled": true
},
Expand All @@ -111,7 +111,7 @@
" prices]"
]
},
"execution_count": 17,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -129,18 +129,18 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{92: 96,\n",
" 100: 29,\n",
" 100: 27,\n",
" 86: 15,\n",
" 85: 39,\n",
" 96: 17,\n",
" 97: 33,\n",
" 96: 16,\n",
" 97: 32,\n",
" 90: 34,\n",
" 95: 4,\n",
" 87: 13,\n",
Expand All @@ -153,7 +153,7 @@
" 101: 1}"
]
},
"execution_count": 12,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -165,19 +165,19 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"NOUN | 96\n",
"VERB | 29\n",
"VERB | 27\n",
"ADV | 15\n",
"ADP | 39\n",
"PROPN | 17\n",
"PUNCT | 33\n",
"PROPN | 16\n",
"PUNCT | 32\n",
"DET | 34\n",
"PRON | 4\n",
"AUX | 13\n",
Expand All @@ -195,11 +195,30 @@
"for k,v in count.items():\n",
" print(doc.vocab[k].text, \"|\",v)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['rise', 'continue', 'push', 'threaten', 'report', 'base', 'increase', 'represent', 'remove', 'call', 'rise', 'cloud', 'peak', 'mean', 'continue', 'lose', 'adjust', 'decrease', 'drop', 'begin', 'see', 'rise', 'spread', 'respond', 'come', 'show', 'have']\n"
]
}
],
"source": [
"# Print all the root/base (consider lemma) forms of verbs (VERB POS type) in a python list.\n",
"lemmVerbTokens = [token.lemma_ for token in doc if token.pos_ == 'VERB']\n",
"print(lemmVerbTokens)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -213,7 +232,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
"version": "3.11.1"
}
},
"nbformat": 4,
Expand Down
1 change: 1 addition & 0 deletions 7_pos/pos_exercise.md
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@ Exercise for Spacy POS tutorial,
1) Extract all NOUN tokens from this story. You will have to read the file in python first to collect all the text and then extract NOUNs in a python list
2) Extract all numbers (NUM POS type) in a python list
3) Print a count of all POS tags in this story
4) Print all the root/base (consider lemma) forms of verbs (VERB POS type) in a python list.

[Solution](https://github.com/codebasics/nlp-tutorials/blob/main/7_pos/Exercise/pos_exercise_solution.ipynb)