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‎.ipynb_checkpoints/Arrays & Lists-checkpoint.ipynb

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{
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"cells": [
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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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"## Array Sum"
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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": 1,
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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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"5\n",
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"1 2 5 9 6\n",
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"23\n"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=list(map(int,input().split()))\n",
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"sum=0\n",
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"for i in list1:\n",
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" sum=sum+i\n",
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"print(sum)"
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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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"## Swap Alternate"
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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": 2,
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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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"6\n",
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"9 3 6 12 4 32\n",
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"3 9 12 6 32 4 "
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"for i in range(0,n-1,2):\n",
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" list1[i],list1[i+1]=list1[i+1],list1[i]\n",
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"for i in list1:\n",
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" print(i,end=\" \")"
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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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"## Find Unique"
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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": 3,
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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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"7\n",
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"2 3 1 6 3 6 2\n",
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"1\n"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"list2=[]\n",
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"for i in list1:\n",
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" if i not in list2:\n",
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" list2.append(i)\n",
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" else:\n",
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" list2.remove(i)\n",
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"for i in list2:\n",
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" print(i)\n",
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" "
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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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"## Find Duplicate"
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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": 5,
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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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"5\n",
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"7 4 5 3 7\n",
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"7\n"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"list2=[]\n",
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"for i in list1:\n",
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" if i in list2:\n",
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" print(i)\n",
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" else:\n",
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" list2.append(i)"
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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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"## Array Intersection (error)"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n",
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"1 0 2 5 6\n",
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"4\n",
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"4 5 3 2\n",
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"5\n",
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"2\n"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"m=int(input())\n",
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"list2=[x for x in input().split()]\n",
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"list3=list(set(list1) & set(list2))\n",
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"for i in list3:\n",
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" print(i)"
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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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"## Pair Sum (missing)"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n",
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"4 2 5 6 5\n",
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"2\n",
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" 1 2\n",
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"2\n"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"m=int(input())\n",
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"list2=[x for x in input().split()]\n",
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"list3=list(set(list1) & set(list2))\n",
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"for i in list3:\n",
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" print(i)"
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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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"## Triplet Sum (error)"
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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": 9,
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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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"7\n",
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"1 2 3 4 5 6 7 \n",
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"12\n",
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"1 4 7\n"
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]
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},
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{
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"ename": "TypeError",
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"evalue": "'int' object is not callable",
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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<ipython-input-9-0d2766509cc3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 8\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m!=\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m!=\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m!=\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m==\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[0mmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 11\u001b[0m \u001b[0mmax\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[0mmid\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mTypeError\u001b[0m: 'int' object is not callable"
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[int(x) for x in input().split()]\n",
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"size=int(input())\n",
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"list3=[]\n",
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"for i in range(n):\n",
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" for j in range(i+1,n):\n",
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" for k in range(j+1,n):\n",
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" if list1[i]!=list1[j] and list1[j]!=list1[k] and list1[k]!=list1[i]:\n",
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" if list1[i]+list1[j]+list1[k]==size:\n",
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" min=min(list1[i],list1[j],list1[k])\n",
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" max=max(list1[i],list1[j],list1[k])\n",
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" mid=(list1[i]+list1[j]+list1[k])-max-min\n",
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" print(min,mid,max)"
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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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"## Sort 0 1"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n",
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"1 0 1 0 1\n",
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"0 0 1 1 1 "
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]
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}
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],
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"source": [
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"n=int(input())\n",
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"list1=[x for x in input().split()]\n",
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"list1.sort()\n",
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"for i in list1:\n",
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" print(i,end=\" \")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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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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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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