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craigsdennis
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Explores ufuncs and broadcasting
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‎Introduction to NumPy.ipynb

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"orders.dot(prices)"
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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": 74,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(array([1, 2, 3, 4, 5]), array([ 6, 7, 8, 9, 10]))"
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]
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},
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"execution_count": 74,
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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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"source": [
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"a, b = np.split(np.arange(1, 11), 2)\n",
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"a, b"
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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": 75,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 7, 9, 11, 13, 15])"
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]
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},
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"execution_count": 75,
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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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"source": [
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"a + b"
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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": 76,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([-5, -5, -5, -5, -5])"
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]
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},
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"execution_count": 76,
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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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"source": [
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"a - b"
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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": 77,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([5, 5, 5, 5, 5])"
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]
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},
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"execution_count": 77,
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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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"source": [
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"b - a"
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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": 78,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 6, 14, 24, 36, 50])"
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]
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},
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"execution_count": 78,
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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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"source": [
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"a * b"
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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": 79,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([3, 4, 5, 6, 7])"
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]
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},
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"execution_count": 79,
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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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"source": [
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"a + 2"
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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": 81,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([3, 4, 5, 6, 7])"
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]
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},
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"execution_count": 81,
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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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"source": [
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"a + np.repeat(2, 5)"
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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": 82,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(array([[0., 1., 2.],\n",
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" [3., 4., 5.],\n",
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" [6., 7., 8.]]), array([0., 1., 2.]))"
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]
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},
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"execution_count": 82,
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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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"source": [
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">>> x1 = np.arange(9.0).reshape((3, 3))\n",
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">>> x2 = np.arange(3.0)\n",
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"x1, x2"
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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": 83,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([[ 0., 2., 4.],\n",
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" [ 3., 5., 7.],\n",
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" [ 6., 8., 10.]])"
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]
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},
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"execution_count": 83,
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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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"source": [
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">>> np.add(x1, x2)"
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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": 84,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([[ 2., 3., 4.],\n",
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" [ 5., 6., 7.],\n",
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" [ 8., 9., 10.]])"
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]
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},
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"execution_count": 84,
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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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"source": [
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"np.add(x1, 2)"
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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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