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Dictionaries and Sets
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‎PythonFromScratch.ipynb

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"source": [
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"tp1.count(1)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Dictionaries and Sets"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"d1 = dict()\n",
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"d2 = {}\n",
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"d3 = {'nom':'Azdad','prenom':'Anas','age':22, 4:5}\n",
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"d4 = {'a':1, 'b':2, 'c':3}"
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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": 7,
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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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"5"
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]
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},
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"execution_count": 7,
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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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"d3[4]"
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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": 8,
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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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"4"
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]
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},
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"execution_count": 8,
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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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"len(d3)"
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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": 11,
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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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"'a'"
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]
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},
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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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"source": [
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"min(d4)"
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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": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"del(d4['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": 13,
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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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"{'b': 2, 'c': 3}"
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]
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},
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"execution_count": 13,
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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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"d4"
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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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"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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"{}"
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]
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},
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"execution_count": 14,
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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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"d4.clear()\n",
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"d4"
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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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"metadata": {},
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"outputs": [
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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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"nom Azdad\n",
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"prenom Anas\n",
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"age 22\n",
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"4 5\n"
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]
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}
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],
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"source": [
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"for indices, values in d3.items():\n",
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" print(indices, ' ', values)"
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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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"metadata": {},
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"outputs": [
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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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"nom\n",
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"prenom\n",
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"age\n",
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"4\n"
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]
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}
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],
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"source": [
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"for indices in d3.keys():\n",
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" print(indices)"
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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": 18,
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"metadata": {},
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"outputs": [
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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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"Azdad\n",
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"Anas\n",
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"22\n",
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"5\n"
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]
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}
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],
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"source": [
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"for values in d3.values():\n",
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" print(values)"
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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": 20,
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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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"5"
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]
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},
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"execution_count": 20,
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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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"d3.pop(4)"
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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": 27,
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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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"{0: 'a', 1: 'b', 2: 'c', 3: 'd', 4: 'e', 5: 'f'}"
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]
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},
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"execution_count": 27,
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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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"lt = ['a', 'b', 'c', 'd', 'e', 'f']\n",
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"lt_dt = {i:lt[i] for i in range(len(lt))}\n",
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"lt_dt"
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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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"outputs": [
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{
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"data": {
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"text/plain": [
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"{1, 2, 3, 4, 5, 7, 'anas'}"
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]
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},
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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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"source": [
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"lt = ['anas', 5, 7, 2, 3, 4, 5, 'anas', 1, 1]\n",
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"ens = set(lt)\n",
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"ens"
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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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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "'set' object is not subscriptable",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_30060/3208747743.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mens\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
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"\u001b[1;31mTypeError\u001b[0m: 'set' object is not subscriptable"
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]
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}
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],
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"source": [
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"ens[0]"
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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": 25,
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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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"set"
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]
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},
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"execution_count": 25,
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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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"ens1 = {'anas',1, 'anas'}\n",
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"type(ens1)"
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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": 26,
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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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"{1, 'anas'}"
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]
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},
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"execution_count": 26,
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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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"ens1"
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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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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "0bd0263b2349850895389e1032d04cbc5bd2ce95c132b2480249abf6cf466d9f"
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"hash": "ce2665c828cadf88826a7c4b72219d2463d2835c9122540076c4da858c580ad1"
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},
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"kernelspec": {
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"display_name": "Python 3.8.8 64-bit ('base': conda)",
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"display_name": "Python 3.9.7 ('base')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {

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