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updated matplotlib notebooks and tweaks to all the numpy ones.
1 parent 7d12201 commit b7bcfad

10 files changed

Lines changed: 1470 additions & 361 deletions

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‎Examples/matplotlib/matplotlib-instructor.ipynb‎

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‎Examples/matplotlib/matplotlib-learner.ipynb‎

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‎Examples/nosql/test_address_book_model.py‎

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@@ -6,13 +6,14 @@
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$ mongod --dbpath=mongo_data/
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"""
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#import address_book_model as model
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#import address_book_zodb as model
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# import address_book_model as model
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# import address_book_zodb as model
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import address_book_mongo as model
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a_book = model.create_sample()
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def test_name_search():
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"""find a single person by first name"""
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@@ -22,6 +23,7 @@ def test_name_search():
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assert people[0].first_name == 'Chris'
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assert people[0].last_name == 'Barker'
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def test_name_search2():
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people = a_book.find_people('barKer')
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first_names = [p.first_name for p in people]
@@ -30,17 +32,17 @@ def test_name_search2():
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assert 'Emma' in first_names
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assert 'Donna' in first_names
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def test_zip_search():
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locations = a_book.find_zip_codes(98105)
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assert len(locations) == 1
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assert locations[0].name == 'Python Certification Program'
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def test_state_search():
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locations = a_book.find_state('WA')
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names = [l.name for l in locations]
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assert "The Barkers" in names
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assert "Python Certification Program" in names
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‎Examples/numpy/broadcasting.ipynb‎

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@@ -32,7 +32,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1000 loops, best of 3: 872 µs per loop\n"
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"1000 loops, best of 3: 871 µs per loop\n"
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]
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}
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],
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The slowest run took 35.82 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
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"100000 loops, best of 3: 7.24 µs per loop\n"
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"The slowest run took 24.07 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
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"100000 loops, best of 3: 6.85 µs per loop\n"
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]
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}
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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": 10,
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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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"array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
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]
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},
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"execution_count": 10,
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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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": 13,
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"execution_count": 14,
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"metadata": {
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"collapsed": false
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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": 14,
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"execution_count": 15,
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"metadata": {
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"collapsed": false
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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": 15,
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"execution_count": 16,
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"metadata": {
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"collapsed": false
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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": 16,
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"execution_count": 17,
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"metadata": {
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"collapsed": false
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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": 17,
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"execution_count": 18,
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"metadata": {
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"collapsed": false
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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": 21,
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"execution_count": 19,
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"metadata": {
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"collapsed": false
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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": 23,
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"execution_count": 20,
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"metadata": {
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"collapsed": true
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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": 24,
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"execution_count": 21,
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"metadata": {
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"collapsed": false
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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": 22,
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"metadata": {
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"collapsed": false
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},
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"(3, 4)"
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]
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},
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"execution_count": 25,
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"execution_count": 22,
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"metadata": {},
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"output_type": "execute_result"
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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": 23,
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"metadata": {
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"collapsed": false
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},
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"(4,)"
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]
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},
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"execution_count": 26,
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"execution_count": 23,
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"metadata": {},
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"output_type": "execute_result"
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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": 28,
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"execution_count": 24,
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"metadata": {
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"collapsed": false
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},
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" [ 800, 1800, 3000, 4400]])"
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]
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},
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"execution_count": 28,
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}

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