From c8c63f3bc3209897da45f3ef7a95edd7f3d64322 Mon Sep 17 00:00:00 2001
From: msyamkumar <msyamkumar@wisc.edu>
Date: Wed, 19 Oct 2022 15:43:11 -0500
Subject: [PATCH] Updating lecture 18 completed notebook file
---
.../lec-18/lec18_dictionaries2.ipynb | 11064 +---------------
1 file changed, 79 insertions(+), 10985 deletions(-)
diff --git a/f22/meena_lec_notes/lec-18/lec18_dictionaries2.ipynb b/f22/meena_lec_notes/lec-18/lec18_dictionaries2.ipynb
index 4e0ce2a..6e84b70 100644
--- a/f22/meena_lec_notes/lec-18/lec18_dictionaries2.ipynb
+++ b/f22/meena_lec_notes/lec-18/lec18_dictionaries2.ipynb
@@ -30,8 +30,8 @@
"outputs": [],
"source": [
"# Keys can be what type? : Any type that is ____immutable____________\n",
- "# Values can be what type? : any type (including other dictionaries)\n",
- "# Indexing? .... yes/no No\n",
+ "# Values can be what type? : Any type (including other dictionaries & lists)\n",
+ "# Indexing? .... yes/no No (lookup is not the same as indexing)\n",
"# Slicing? ..... yes/no No\n",
"# Mutable?......yes/no Yes"
]
@@ -315,13 +315,13 @@
"\n",
"major_freq = {} # KEY: unique major; VALUE: count of unique major\n",
"\n",
- "for row in cs220_data:\n",
- " major = row[cs220_header.index(\"Major\")]\n",
- " if major in major_freq:\n",
- " major_freq[major] += 1\n",
- " else:\n",
+ "for row_idx in range(len(cs220_data)):\n",
+ " major = cell(cs220_data, cs220_header, row_idx, \"Major\")\n",
+ " if major not in major_freq:\n",
" major_freq[major] = 1\n",
- " \n",
+ " else:\n",
+ " major_freq[major] += 1\n",
+ " \n",
"major_freq"
]
},
@@ -394,7 +394,7 @@
"suffix.get(1)\n",
"\n",
"# TODO: what happens when you try to get a key that is not there? Try it.\n",
- "print(suffix.get(10)) # Returns None\n",
+ "print(suffix.get(4))\n",
"\n",
"# TODO: what happens whey you try to pop a key that is not there? Try it.\n",
"# suffix.pop(10) # KeyError"
@@ -555,20 +555,20 @@
"outputs": [],
"source": [
"# Let's bucketize the data\n",
- "buckets = dict() # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
"\n",
"def bucketize(bucket_column):\n",
- " \"\"\"\n",
- " generates and returns bucketized data based on bucket_column\n",
- " \"\"\"\n",
- " # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
- " buckets = dict()\n",
+ " buckets = dict() # Key: unique bucketize column value; \\\n",
+ " # Value: list of lists (rows having that unique column value)\n",
+ "\n",
" for row_idx in range(len(cs220_data)):\n",
- " col_value = cell(cs220_data, cs220_header, row_idx, bucket_column)\n",
- " if col_value not in buckets:\n",
- " buckets[col_value] = []\n",
- " buckets[col_value].append(cs220_data[row_idx])\n",
- " \n",
+ " row = cs220_data[row_idx]\n",
+ " col_val = cell(cs220_data, cs220_header, row_idx, bucket_column)\n",
+ " if col_val not in buckets:\n",
+ " # no existing bucket\n",
+ " buckets[col_val] = []\n",
+ " # must append row in both cases (new bucket and existing bucket)\n",
+ " buckets[col_val].append(row)\n",
+ "\n",
" return buckets"
]
},
@@ -576,10932 +576,20 @@
"cell_type": "code",
"execution_count": 13,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'LEC001': [['LEC001',\n",
- " '22',\n",
- " 'Engineering: Biomedical',\n",
- " '53703',\n",
- " '43.073051',\n",
- " '-89.40123',\n",
- " 'none (just cheese)',\n",
- " 'neither',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '',\n",
- " 'Mathematics/AMEP',\n",
- " '53706',\n",
- " '31.230391',\n",
- " '121.473701',\n",
- " 'basil/spinach',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Economics (Mathematical Emphasis)',\n",
- " '53703',\n",
- " '48.86',\n",
- " '2.3522',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'early bird',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '19',\n",
- " 'Engineering: Mechanical',\n",
- " '53703',\n",
- " '24.7',\n",
- " '46.7',\n",
- " 'mushroom',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '23',\n",
- " 'Computer Science',\n",
- " '53711',\n",
- " '43.073929',\n",
- " '-89.385239',\n",
- " 'sausage',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '22',\n",
- " 'Engineering: Mechanical',\n",
- " '53719',\n",
- " '43.073051',\n",
- " '-89.40123',\n",
- " 'none (just cheese)',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '18',\n",
- " 'Computer Science',\n",
- " '53706',\n",
- " '26.2992',\n",
- " '87.2625',\n",
- " 'mushroom',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '24',\n",
- " 'Business: Information Systems',\n",
- " '53703',\n",
- " '43.073051',\n",
- " '-89.40123',\n",
- " 'macaroni/pasta',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '',\n",
- " 'Computer Science',\n",
- " '53715',\n",
- " '34.052235',\n",
- " '-118.243683',\n",
- " 'green pepper',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '26',\n",
- " 'Engineering: Mechanical',\n",
- " '53703',\n",
- " '41.902782',\n",
- " '12.496365',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '25',\n",
- " 'Economics',\n",
- " '53703',\n",
- " '40.712776',\n",
- " '-74.005974',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '19',\n",
- " 'Computer Science',\n",
- " '53706',\n",
- " '48.855709',\n",
- " '2.29889',\n",
- " 'pepperoni',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '21',\n",
- " 'Computer Science',\n",
- " '53715',\n",
- " '16.306652',\n",
- " '80.436539',\n",
- " 'Other',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '18',\n",
- " 'Engineering: Industrial',\n",
- " '53715',\n",
- " '30.733315',\n",
- " '76.779419',\n",
- " 'green pepper',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Economics (Mathematical Emphasis)',\n",
- " '53703',\n",
- " '43.073929',\n",
- " '-89.385239',\n",
- " 'macaroni/pasta',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '21',\n",
- " 'Business: Finance',\n",
- " '53711',\n",
- " '43.073929',\n",
- " '-89.385239',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '19',\n",
- " 'Computer Science',\n",
- " '53703',\n",
- " '51.507351',\n",
- " '-0.127758',\n",
- " 'sausage',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'no preference',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '21',\n",
- " 'Science: Biology/Life',\n",
- " '53703',\n",
- " '36',\n",
- " '117',\n",
- " 'macaroni/pasta',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '18',\n",
- " 'Engineering: Other',\n",
- " '53706',\n",
- " '41.902782',\n",
- " '12.496365',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
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- " ['LEC001',\n",
- " '18',\n",
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- " 'pepperoni',\n",
- " 'dog',\n",
- " 'Yes',\n",
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- " ['LEC001',\n",
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- " '-106.038353',\n",
- " 'macaroni/pasta',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'night owl',\n",
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- " ['LEC001',\n",
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- " 'Business: Other|Business: Accounting',\n",
- " '53703',\n",
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- " '121.473701',\n",
- " 'pepperoni',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'no preference',\n",
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- " '53706',\n",
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- " 'green pepper',\n",
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- " 'Yes',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '',\n",
- " 'Engineering: Mechanical',\n",
- " '53715',\n",
- " '19.8968',\n",
- " '155.5828',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
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- " ['LEC001',\n",
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- " 'Computer Science',\n",
- " '53703',\n",
- " '43.21518',\n",
- " '-87.94241',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'no preference',\n",
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- " ['LEC001',\n",
- " '22',\n",
- " 'Engineering: Mechanical',\n",
- " '53703',\n",
- " '47.497913',\n",
- " '19.040236',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Business andministration',\n",
- " '53703',\n",
- " '37.389091',\n",
- " '-5.984459',\n",
- " 'pineapple',\n",
- " 'dog',\n",
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- " 'sausage',\n",
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- " 'cat',\n",
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- " 'pineapple',\n",
- " 'dog',\n",
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- " 'dog',\n",
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- " 'pepperoni',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '22',\n",
- " 'consumer behavior and marketplace studies',\n",
- " '53715',\n",
- " '43.653225',\n",
- " '-79.383186',\n",
- " 'mushroom',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Computer Science',\n",
- " '53715',\n",
- " '41',\n",
- " '-87',\n",
- " 'Other',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '17',\n",
- " 'Statistics',\n",
- " '53715',\n",
- " '43.0722',\n",
- " '89.4008',\n",
- " 'pineapple',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'early bird',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Economics',\n",
- " '53715',\n",
- " '27.99942',\n",
- " '120.66682',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '19',\n",
- " 'Mathematics/AMEP',\n",
- " '53711',\n",
- " '45.85038',\n",
- " '-84.616989',\n",
- " 'pineapple',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '23',\n",
- " 'Economics',\n",
- " '53703',\n",
- " '43.07348',\n",
- " '-89.38089',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC001',\n",
- " '29',\n",
- " 'Business: Other|Technology Strategy/ Product Management',\n",
- " '53705',\n",
- " '37.386051',\n",
- " '-122.083855',\n",
- " 'Other',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '18',\n",
- " 'Engineering: Biomedical',\n",
- " '53715',\n",
- " '43.073051',\n",
- " '-89.40123',\n",
- " 'sausage',\n",
- " 'dog',\n",
- " 'No',\n",
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- " 'Yes'],\n",
- " ['LEC001',\n",
- " '18',\n",
- " 'Data Science',\n",
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- " '45.079163',\n",
- " 'mushroom',\n",
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- " 'Business: Other',\n",
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- " '-89.46498',\n",
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- " 'cat',\n",
- " 'No',\n",
- " 'early bird',\n",
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- " ['LEC001',\n",
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- " 'Business: Other|Consumer Behavior and Marketplace Studies',\n",
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- " '-111.891045',\n",
- " 'green pepper',\n",
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- " 'cat',\n",
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- " 'night owl',\n",
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- " ['LEC001',\n",
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- " '22',\n",
- " 'International Studies',\n",
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- " '11.58022',\n",
- " 'none (just cheese)',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
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- " ['LEC001',\n",
- " '19',\n",
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- " '38.331581',\n",
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- " 'dog',\n",
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- " 'No',\n",
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- " ['LEC001',\n",
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- " 'Economics',\n",
- " '53726',\n",
- " '42.92',\n",
- " '-87.96',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '19',\n",
- " 'Engineering: Mechanical',\n",
- " '53715',\n",
- " '29.424122',\n",
- " '-98.493629',\n",
- " 'mushroom',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Agricultural and Applied Economics',\n",
- " '53703',\n",
- " '-22.932924',\n",
- " '-47.073845',\n",
- " 'pineapple',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'Maybe'],\n",
- " ['LEC001',\n",
- " '25',\n",
- " 'Medicine',\n",
- " '53703',\n",
- " '48.38203',\n",
- " '-123.537827',\n",
- " 'basil/spinach',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'No'],\n",
- " ['LEC001',\n",
- " '20',\n",
- " 'Business: Other|Real Estate',\n",
- " '53703',\n",
- " '51.5',\n",
- " '0.128',\n",
- " 'mushroom',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
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- " 'Maybe'],\n",
- " ['LEC003',\n",
- " '19',\n",
- " 'Engineering: Mechanical',\n",
- " '53706',\n",
- " '43',\n",
- " '-88.27',\n",
- " 'Other',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '20',\n",
- " 'Business: Other|Accounting',\n",
- " '53726',\n",
- " '43',\n",
- " '-89',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '18',\n",
- " 'Data Science',\n",
- " '53562',\n",
- " '42.66544',\n",
- " '21.165319',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '18',\n",
- " 'Engineering: Mechanical',\n",
- " '53706',\n",
- " '33.748997',\n",
- " '-84.387985',\n",
- " 'mushroom',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '19',\n",
- " 'Business: Actuarial',\n",
- " '53706',\n",
- " '39.299236',\n",
- " '-76.609383',\n",
- " 'pineapple',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC003',\n",
- " '',\n",
- " 'Engineering: Mechanical',\n",
- " '53706',\n",
- " '45.87128',\n",
- " '-89.711632',\n",
- " 'pepperoni',\n",
- " 'neither',\n",
- " 'Yes',\n",
- " 'no preference',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '',\n",
- " 'Computer Science',\n",
- " '53703',\n",
- " '43.07',\n",
- " '-89.4',\n",
- " 'pepperoni',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'no preference',\n",
- " 'Maybe'],\n",
- " ['LEC003',\n",
- " '19',\n",
- " 'Engineering: Industrial',\n",
- " '53703',\n",
- " '40.712776',\n",
- " '-74.005974',\n",
- " 'basil/spinach',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'No'],\n",
- " ['LEC003',\n",
- " '18',\n",
- " 'Data Science',\n",
- " '53706',\n",
- " '40.712776',\n",
- " '-74.005974',\n",
- " 'Other',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'No'],\n",
- " ['LEC003',\n",
- " '20',\n",
- " 'Economics',\n",
- " '53703',\n",
- " '22.54',\n",
- " '114.05',\n",
- " 'pineapple',\n",
- " 'dog',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '18',\n",
- " 'Data Science',\n",
- " '53706',\n",
- " '36.974117',\n",
- " '-122.030792',\n",
- " 'pepperoni',\n",
- " 'cat',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '18',\n",
- " 'Mathematics/AMEP',\n",
- " '53706',\n",
- " '42.99571',\n",
- " '-90',\n",
- " 'sausage',\n",
- " 'dog',\n",
- " 'Yes',\n",
- " 'night owl',\n",
- " 'Yes'],\n",
- " ['LEC003',\n",
- " '19',\n",
- " 'Engineering: Industrial',\n",
- " '53715',\n",
- " '24.713552',\n",
- " '46.675297',\n",
- " 'basil/spinach',\n",
- " 'neither',\n",
- " 'Yes',\n",
- " 'early bird',\n",
- " 'Maybe'],\n",
- " ['LEC003',\n",
- " '19',\n",
- " 'Engineering: Mechanical',\n",
- " '53705',\n",
- " '46.589146',\n",
- " '-112.039108',\n",
- " 'none (just cheese)',\n",
- " 'cat',\n",
- " 'No',\n",
- " 'night owl',\n",
- " 'Yes']]}"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
- "sec_buckets = bucketize(\"Lecture\")\n",
- "sec_buckets"
+ "lec_buckets = bucketize(\"Lecture\")\n",
+ "# lec_buckets"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "major_buckets = bucketize(\"Major\")\n",
+ "# major_buckets"
]
},
{
@@ -11513,7 +601,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -11522,7 +610,7 @@
"19.61"
]
},
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -11539,18 +627,16 @@
" count = 0\n",
" for row_idx in range(len(data)):\n",
" col_data = cell(data, header, row_idx, col_name)\n",
+ " # handle bounds checking\n",
" if col_data != None:\n",
- " # handle bounds checking\n",
- " if col_data < min_bound or col_data > max_bound:\n",
- " continue\n",
- " total += col_data\n",
- " count += 1\n",
+ " if col_data > min_bound and col_data < max_bound:\n",
+ " total += col_data\n",
+ " count += 1\n",
+ " \n",
+ " if count == 0:\n",
+ " return 0 # or whatever is the expected return value\n",
+ " return round(total / count, 2) # implicit else\n",
" \n",
- " if count != 0:\n",
- " return round(total / count, 2)\n",
- " else:\n",
- " return 0\n",
- " \n",
"min_age = 0\n",
"max_age = 118\n",
"col_avg(cs220_data, cs220_header, \"Age\", min_age, max_age)"
@@ -11565,7 +651,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
@@ -11573,10 +659,10 @@
" \"\"\"\n",
" Computes and returns column average per bucket\n",
" \"\"\"\n",
- " averages = {} # Key: bucket column; Value: average for that bucket\n",
+ " averages = {} # Key: bucket name; Value: bucket average\n",
" for bucket_name in buckets:\n",
- " bucket_rows = buckets[bucket_name]\n",
- " averages[bucket_name] = col_avg(bucket_rows, cs220_header, avg_col_name, min_age, max_age)\n",
+ " averages[bucket_name] = col_avg(buckets[bucket_name], \\\n",
+ " cs220_header, avg_col_name, min_age, max_age)\n",
" return averages"
]
},
@@ -11591,7 +677,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -11605,13 +691,13 @@
" 'LEC003': 19.14}"
]
},
- "execution_count": 16,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "avg_per_bucket(sec_buckets, \"Age\")"
+ "avg_per_bucket(lec_buckets, \"Age\")"
]
},
{
@@ -11623,7 +709,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 18,
"metadata": {},
"outputs": [
{
@@ -11729,13 +815,12 @@
" 'Environmental Studies': 18.0}"
]
},
- "execution_count": 17,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "major_buckets = bucketize(\"Major\")\n",
"avg_per_bucket(major_buckets, \"Age\")"
]
},
@@ -11768,7 +853,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 19,
"metadata": {},
"outputs": [
{
@@ -11787,7 +872,7 @@
" 'Procrastinator']"
]
},
- "execution_count": 18,
+ "execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
@@ -11799,7 +884,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
@@ -11807,18 +892,27 @@
" \"\"\"\n",
" Transform data into a list of dictionaries\n",
" \"\"\"\n",
- " dict_list = [] #should be defined outside the for loop, because it stores the entire data\n",
+ " transformed_data = [] #should be defined outside the for loop, because it stores the entire data\n",
+ " for row in data:\n",
+ " #should be defined inside the for loop, because it represents one row as a dictionary\n",
+ " row_dict = {} # Key: header; Value: data\n",
+ " for idx in range(len(row)):\n",
+ " row_dict[header[idx]] = row[idx]\n",
+ " transformed_data.append(row_dict)\n",
+ " return transformed_data\n",
" \n",
- " for row in cs220_data:\n",
- " new_row = {} #should be defined inside the for loop, because it represents one row as a dictionary\n",
- " for i in range(len(cs220_header)):\n",
- " new_row[cs220_header[i]] = row[i]\n",
- " dict_list.append(new_row)\n",
- " return dict_list\n",
- " \n",
"transformed_data = transform(cs220_header, cs220_data)"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# transformed_data"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -11828,7 +922,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
@@ -11852,7 +946,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 23,
"metadata": {},
"outputs": [
{
@@ -11883,7 +977,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
@@ -11929,7 +1023,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 25,
"metadata": {},
"outputs": [
{
@@ -11938,7 +1032,7 @@
"'Tom Sawyer bamboozled the neighborhood boys into painting for him'"
]
},
- "execution_count": 23,
+ "execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
@@ -11956,7 +1050,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 26,
"metadata": {},
"outputs": [
{
@@ -11965,7 +1059,7 @@
"['bamboozle', 'gubbins']"
]
},
- "execution_count": 24,
+ "execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
--
GitLab