定义:同一种类型数据的集合

通俗的讲就是,将多个同一种类型的数据按一定的内存顺序写在一起。

注意我的几个关键字“多个”,“同一种”,“一定的内存顺序”。如果理解了这几个关键词,说明你的数组已经掌握了。

我们分开了解这几个关键词:

多个:首先数组是为了存储多个数据而产生的,如果你只有一个数据那就没必要用数组了,当然你非要定义数组存储单个数据也是不会报错的。

//eg
#include<iostream>
using namespace std;

void main()
{
int a; //等效于 int a[1];
int num[10]; //一般用于定于多个,此处就表示,定义10个int类型的数据
     //注意数组是从零开始计数的
}

同一种:数组最重要的特点就是将相同类型的数据放在了一起,便于以后的各种迭代处理,直接看代码更容易理解

//eg
#include<iostream>
using namespace std;

void main()
{
   int a[10]; //假如你现在需要十个正整型数据 先赋值再求和
   int sun = 0; //定义sum的初始值为0
   for(int i = 0; i < 10; ++i)
  {
       a[i] = i;
  }
   for(int j = 0; j < 10; ++j)
  {
       sum += a[j];
  }
cout << sum << endl;
}

一定的内存顺序:这块是很重要的,即数组在内存中的相邻数据之间的间隔一定的(数据类型的长度),数组和指针可以相互使用,现在很好的理解数组的内存结构,在后面指针那里就很容易学懂了。

#include<iostream>
using namespace std;
void main()
{
int a[10] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 }; //我们可以先去打印a[0] 与 a[9]之间的内存差看看效果
cout << &a[0] <<" "<< &a[9]  << endl; //& 在这里是取地址符
cin.get();
}

用两个地址作差除去,size(int),看看是个什么结果。下面我将用图来解释:

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0oUK4/kzKZZrXEe0lez5QyF+fzRXUsACtDsGVNVBqDyV06m+f+J1xfj9YjaBI7GPGmHjuDj7vn2UKLcZQm3T62tpZLuvvOXiUAM3UL3eEodbqa46hzmC5o1zDi/FR0Nqq/buygd9waKc7hcLpTGjEZhMdw2NjwSTs5Y9kx+Wh5uthmvqtE0XGeFiQobXc7No2otVOc74Yw7VRUdvUo/zpbqHimtS06smiHq9AWPMymX0wKwuRZD3tX4a4o2LFjn3ToX8uduLZditLFpEe7IR1kEcr5t+VMF2LcC8d3d+H4/u/Yd3Jw07KG0gzKQZ14HpvP9fio7exr8mQjwMtax3Hea3AorU/yOqZ+cEXA5eQ6/Ff5dbXT1zSFqHF3kk6mEmUZb8OFTtNR7UHYeb3NA4FF+RovH0OVDKCkLu3ddHh8bZrX/Zm1PCwWaM3r0UEWkIoBqFjOn9M1duL1PJo6k5b/uQpnc3lO14l6yT5rvI7mzWz5Ui11e/dmufa/4X7UQZthPNDasgV02raqZ9RchP/2t6rrUzVlLs7cXlluHQvAahFsWROVxmB6l05u2LGDcV7PTomy0cDYkIiBmKPhyNhjttBi0svvP7bd7F9GSwmkGRy1xnFpRCdLwc+2oq02yLPGxGP/pZpNM1zgb3xEt7HT2EFrpGhk/dkpT8MK2ajm7mPaoI+jzjt/Zhs5K0bLs/eIP0/f4aRpu9u2jt5o44STvDH4J+wMxr+rekeyEuhJgwbZbjwn4S7tnM2XJTJjg3oJslHFRba1zUeqw1UY1DujpayhtvUf0k5APdMrDdTEOfpznIvYyRgGMpMO9l0cDV1OR2n77C4tt+M7ynRo4QyjkU6uwTzzpbVKiAGX5E1/ffJYG45+oWthNM2w9E6nWfksBwLTnXjaMlUqGUBZOew6+6ZqQubdjBYJtI7OVbxeRtP3srogrptRmzoTg9aLVk55ec4Cb6PPujqZLdmUwkr196lMv08o/c3vux9102YYD7S2TEUqvX4UoPkbfpWnMpeDb+WMvEXbK9/x3QLwZQRb1lK+6G0c6E1T6GsdrjQgMtopoDecelBkn5S2jy03WpMOS2wMD0d7TkK4K00jSjukvftw/Jg1/B+OJo96VjND3oedq+H6LktNhy8dQzmtOR1xq68rk486/5k+OpU1KgfD6QyVHRAebodZE0VDLd3NYM7R4fja3tvl2DzySiCs/pr8bw9O83LxmXTufGHPSZsrLEP6udMR7qYOX75VclNWSvGdNgVaqn8hPNzW1oXIswey7XQbMk6GmTF5OvmU40+vj3JnJL4+vdymLOSam7xmS11WbpuyZ9q1Ld44rpja8VldX4NfapFroTTNMP9FWl+ndUGtfMaA2VVScnuVurBhd6d6h7/Y1vvLp7jEQP48a1RNUT9X8XpJztFgWBeMX5PVbMtuyvNCmS317Yhb1mmaYdmz8DJhseTp04RbjAVpFjtX33c/WrzNkE23/BN2HosFbef4q3l7qWjfjIJyebtruMZT8jh6KGXqFb6+jgVghX2woh4/+qGf/O9HXDblI2kM5r/uf8Svrf9Yfu7g42ovfCQtxo9B5ddXH0kjMXl+9j6Nf6Uf0vcL/bZnlJ+793E1/APx+PLXTnsk753+ndrfGFztTX9t/TN9RuO5qyqOqfqc+FmLz56d6+L7qH6G9vM8+i4W/7yTz1fz3x5+v/P83XieZigPpSPLyt+s5aFWNorvZe+q+snHj73hM078ThvKaOmJ2fuXy/SUT1mc/+F7ZJ+7f5V/txPPWX4s5efEYy+d9/j+9XMweu2U46yXr6ZylD6neg6b6pbRY4Zzk77n7OdwkWsw/e/WF9TL3ngZGXt95XNOOfa5r4XsnFb/3LR6LP8M6Ytm+K4rLx19pzNf6xOuiZYPNKGO+sS1n7zPVb/lXjblXpH+c0fleab70KS6fYrKMWW/qX3HU+6lDee77dqof5bh313Ctb/s+9HVJ9oMV59oqzR80LxubTsnpTK7jDoWgLW2Ff8nAOTiSGac8rFKi+7Cd3AtAACwKMEWAAAAgA5ZswUAAACgQ4ItAAAAAB0SbAEAAADokGALAAAAQIcEWwAAAAA6JNgCAAAA0CHBFgAAAIAOCbYAAAAAdEiwBQAAAKBDgi0AAAAAHRJsAQAAAOiQYAsAAABAhwRbAAAAADok2AIAAADQIcEWAAAAgA4JtgAAAAB0SLAFAAAAoEOCLQAAAAAdEmwBAAAA6ND/ffcBbIKtra3vPgQAAIAf5ePj47sPAVoJtgAAALB2DGqvt58eLDONCAAAAKBDgi0AAAAAHRJsAQAAAOiQNVsAAABWyE9fy2Je1mZhHQm2fDMV6fdTeQPQxD16tbhfA3Xq6fWxiXW4YAtMoAJfrrZK13n/ept4AwQAWLqn0xD+JP//+Wb217w/hfD3IYTX1+y/d3dDOLoI4WB7KYfIcmx96NUs3aROjNP//Xw/30ewZXUItqw318znqIvWg+/pe0y7Pzj/n9d0jp3XqrW8/tOAyZ8Qbl+S/+gnBztLsOU9hNOT/DUN9vrzBW1WyCaWc5ktALT66TfBdSIgBgBroBJkmdNpL3ld/nMMrFweJT/8F8Kf+xBekvd7Sf5xfyeE57Muj5glkdnyBWROrDbfz/dZy1GKH2ojv4vYGBrkP/cOQljxzFx11fJsZPlfQ76n7yGzZfk2ccR/Xmtx/cd2xclhCI0xlhkyW+J0o8M80tJ/DOHmoPrvp1ujQMxj8rlr/7zqNrGcy2wBYAO9VxtEsdGy4sGWtVMOZrXqmX8ONBtbs+I4hIszdTUr7L9RuyLNSrlIfnUSwvksGS5Ju+RPEUnpjwdaopvHEG4Ps5//XCf3T9ktq06wBYDNc33SMvJEZ/4ejkbg2uxdaSwCNUmnc783XkfHKRS350k/NKk3btQbrKgiyFIMJPw34+ve/43K/NVFy5MO0jhMem99uU9eI/i46gRbAGaWNACfkpvhw9topC3shnB8FMLZmuVybrSnGUeZWFxyrRSXSNhL/6/R7hcdDrAmaoGWGFg5+hUqa1bEgEv41TzyD99p+yyE5wVfO3jLf0humL8nRFCO+sk1kEZbsuxRwZaVJtgCjLwnjZx/f0O4fx39Lk3b/Z1U5htemz9dh3B43vAP+WJl58nN8eouhLMNP0/r4PTwu49gs7gufqZYJ5YDz3Fb0p2jpJOw+usfscLKWYeVNSkOsiy46/0sWB6nUhyt35oV0Oq/0iDepDq0t1N6zbupuCtOsIXuLLKHPKujaMDUFaNIMd1/o1c+z0cc9vZCOL5MB9XSkbaH+3y1+eRx3kt+r/G30mI9lU5ticGxpEFzPm2eC4sZjDpMvzQEf5T36xBOzpuneKQX10BwjcW95QUrnWLY8O9ndyHc55kvOprdSgOo96OsRGvkfK23GTNut3+VXiO1ZdUJtvB59T3kWT/l1c3jXNM4LSbN2n1IGjW3WaPmJWlc74cNDrjshPA4qDXs8pG2i6SB0suzXixYtsKeRqv8x2yLX3+/93Bg3ZR3yoiGUzzC6H4BCytNPzz+3fKc7Wz6YWyX6Gh2Y1IANV0jp2FXHDpWKvt7OxOfyXoRbGFxn9lDntUTgyx3N9V2y0Fycz27COG0ly/Gldx0n842M3NjUgAlztHtn1uwbNUV04fiiGkceX/63sP50d6LFQH30g2H+AFih6wItMRr6O6s4X6xAZmtM+2yVbMGW8uvhlkCKaVO6Y7K5dPeS4NFsb7uH2cB1PJgW7r7jYALLEKwhflN3EOetbQzaWX/7epWcw9PWaOaqp24AqiLYmWVpw/dyTyC+bxnI9+p/gZnOCb+/Zl/ge0rU6tmViz+eZuc54uGINVwx5Ypi4gyg/J1nZzPwfPofNcH29q+D2Ci/333AXyN92we4v5+8tgKYSs+4s9J4/vp/bsPbg3V9pCPUyuu2raaYC2cTWs490a7ibzOuofdppqysBnfoDZ9yPfztf4l5/+peLjnrqWnv6VFSzcge2Wi3WztrmmPMusWze7gJp+RnhS43n61zohB8yILQ13+eeXruvF85oNtqeSJf6WDwrx+fmbLxB1EXrIGuLmI81t0D3n4kZLG4H3eYukffe+hUBO3Ea1NH2L5hltYxoWjG3Z/apq2yOp6KE0f2vTmUpwqNTWxp7R9cWxjbvo5m9dNnEJ0kk1TP6xPFbLzX2eGu9/0J5zPg2xANd0B6kF/aWlKU+he3iY/9b3U6TKVbuVtQGZLsYNIzMBIbniDQf54HI3Ux+kRgrWzS/eQv7EC/EYp7Syy+2viMzdOnFZXNKpjg0VDZLUMtxE1fejLTRrpj9ul97bce9fC02gBdfX/bIYZA3vZ1Avm8560OV7bpmolv7//l8az+KRZd7/5tZv/8Oq8L9POArMEZM2tvJ+f2dK4g0iU/PfzYwhb1qGAqa7/jH4+2uTrJGllnJZ2sHm9HQWh4q4cFzrzKyWmnBdrKzw+y6L4SnEqQGNVEa+hk9HC6of71XUCWD3lUdSi/i8WyK9sEfs7+R59kWkZ/5NHp/qXyva8ygu2FlnUxeD9v+T+e36bLdbfewvhY9OntH21l2xxaGV6OX4VqS1JGX9qu4eGUuaoBejXwc/PbIk7iLRmYByMdiq2DgU0iw2fosO68Snkg3zhvvwxDLQkFcnRbw2QVVLeOSUuTrnR5XaVxDUAnkvrfCUX0T9DpSttUEtpP91PGviHWcDs5WW0PWwvafWfSlWS1fIZT6VAy9Uoi3o7f8QpXB/FGiJJ/b5//W1H+iMMMymmZKwMpxuxVL3Sls8PE+rS4bTOY+3ONfDzgy2TvJdqlmnz42AT1bcE3PhpGL0ssDJ85A2VGHiJ88rjotv6javhpLRW13kvXxi99iiCMdFh6ff6i8t3djn6OU4JYA0k9d3DfhZkKaZmx8dVf/SUOC17owMuslo+5ekh/2FSe+MgKXd5mXu5d8/9jOH0oEmL35bWpGO5tn+Xlrh4aH5ObJcXTZfj319xVHzS5gRbYsrr6Wl1R6Jeb1Rggarr/WqgRap/yEblb0qP5Jx8fCQNv6vsn9N1KE6/9xBhLZQyS1ltw1HtlyzQEjPF0oyDg3x72HK2Qci2iN3UDrCsls+ZdcT+oFiIXmbcpxxcVNevvK6dy8qadCxfUujv8vZkkblV/kreS5lfExc1ZpX8/GBLjADG4Eqa8nqbp7zm/1ZfsA/Ib65bpalDfYGWaeJ0xWKkLd4g6w0Wvt7doLQgesvjsdTbfyz9Xh/pC7yP1vtgfcSddRob+KVsg43tAMtqYd2UO/dhlAVaDEzHvlO6o5bI+JeJm5AU02zTtYlq30cqDoBar2hd/OxgSzEFohhluMp3I4oj0fHx/GxkDcrSa+ZwFJCM18yz7VlnUh4hMi3i+21vT39UX9Dye5bDDmdrYzjVIEzeZvSgtO3922B5x7OqZLV0Z56tb/mc2Lkv79AaDQem97JMtoudlhezFGfP1cGgSqLAlQHQNfOzdyP6d5//YAoETBV3bhmuYeGaAZbIDmfryTaj7Sxa+XlH/SwLPc0QvWifJvG3NMX5t5P9adtJHfz8ka1lOSgCpb3RBiNPdr/5lBg8mXfJw7ijX9xtq/hO4tIXBoPW0g8OtpQWdGq98UljhlR555Z0B4BNXwh3ET9zpH4rphT/YB/5/3863AqHE5/JXOKONTuXSQOzHkipbf288TucrYHyDhn/vU/Y4XGDlRetvHT/XFiaIZrv9BentITHWh1S1B/5f5qu1a227M5i3SaBxK8n43bt/expRNMMUz5hw/0tb7WooThuhvUHyiP1k1LtYSMkN9fzw3yHp/1sznn6c68UaOmrb9ZBeYeMSdODylM7Nq0OHGZS9wUPPyXpVD6XprQUdchwc4teNVB742QvX2nw+gcNJMFX+cHBlqTCHu5odj6+YOXTdXXbz28SR41/wmO/WEw13IbTFTieeR4bz4jcdO//sg7jU1PQ5T3buem81AC0Qvza2Mofslo6tlNZAImvedgAAAPDSURBVCCbcz60N1oPijWQ1GfHxTb3E3Ya2tipHU+j+r9/NPmpzCBOaRkk57JUh5TXrBjWH9orX8JaRPApWx8fHx/Tn7amigVyh/ayaPlLqVO0e553NPvZ3Lgl2IQOfTytz/nPcePb7w9jMY/hVIrk8WfSE3PLTghbuWqprS4JL9WTEUfq79ZzQeFNqKd+spW7Zgr1NQB62yt5fSj/08XNnYuuVlIjhnKNGJdyLLegvvpsfmv5L6939vjxIzNbpl0fSz3/wzpkdeuPLjSd4++v15NW4VY+FBF3IvvmTKK2cvj954lZrWY5X66fHWyJYifp5Hy8d9iP6YdnIZxuCbZ0QLBlfZW/u1nFoMwyMwFWr1qqrTMxJo60Na1PsT42oZ76yVbvmlkvyv9sYpe33Nd9D+N93/2wWTO0tX9Yli+p12Omf+9s/EJOZwAUIdXl9ZHmIdiy/gRbfrJyZPyLF3fbhEacxsb6WsVgy6qL56yYpRiXjdukjgWw2coZLmVFZuSm1YdXYbTRyKYFmlh/5TZgMUOw3kuqZ7Ktmk3pyv4Egi0shWALAPCTFEHnTQ84F9k+saO6YcsC8wNMGnCLZfokbPb1zfL99FCEYMsX2IRgCwDApimvebbJGZ+sNxm7fJefHor4v+8+AAAAWDflPbf+a30WrL6XIMACyyCz5QvIbAEAAICRnx6KkNnyBX56IQIAAFgWg9esI8EWAAAAVpbBa9bR/777AAAAAAB+EsEWAAAAgA4JtgAAAAB0SLAFAAAAoEOCLQAAAAAdEmwBAAAA6JBgCwAAAECHBFsAAAAAOiTYAgAAANAhwRYAAACADgm2AAAAAHRIsAUAAACgQ4ItAAAAAB0SbAEAAADokGALAAAAQIcEWwAAAAA6JNgCAAAA0CHBFgAAAIAOCbYAAAAAdEiwBQAAAKBDgi0AAAAAHRJsAQAAAOiQYAsAAABAhwRbAAAAADok2AIAAADQIcEWAAAAgA4JtgAAAAB0SLAFAAAAoEOCLQAAAAAdEmwBAAAA6JBgCwAAAECHBFsAAAAAOiTYAgAAANAhwRYAAACADgm2AAAAAHRIsAUAAACgQ4ItAAAAAB0SbAEAAADokGALAAAAQIcEWwAAAAA6JNgCAAAA0CHBFgAAAIAOCbYAAAAAdEiwBQAAAKBDgi0AAAAAHRJsAQAAAOiQYAsAAABAhwRbAAAAADok2AIAAADQIcEWAAAAgA4JtgAAAAB0SLAFAAAAoEOCLQAAAAAdEmwBAAAA6JBgCwAAAECHBFsAAAAAOvT/Z71xvMKug+IAAAAASUVORK5CYII=" alt="" />

数组的初始化

数组的初始化有很多的种方法,这里我将写出最长见的几种:

#include<iostream>
using namespace std;
int main()
{
int a[10] = {0}; //这种方式将默认是个元素全部为零
   int b[10] = {0,1,2,3,4,5,6,7,8,9};//一一对应的方式。
   //也可以在后续的过程中给出自己的操作
   return 0;
}

这里还有二维数组未说明,后期继续,写得有问题的地方请指出,我改正,谢谢!

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