如何把数据导入(出)mysql
导出
  • sql语句
        select * from 表名 into outfile "详细路径" fields terminated by "," enclosed by "";
  • 命令行
        mysqldump
  • 客户端

导入

  • sql语句

load data infile "详细路径" into table 表名 fields terminated by "," enclosed by "";

  • 命令行

mysqlimport

  • 客户端
如何把数据导入pandas
导入
data=pd.read.csv(imputfile) #读取数据
df=DataFrame(data) #把数据转换为DataFrame格式
验证
 

实验数据-在/tmp目录下有文件stud_info.csv

统计文件行数:cat stud_info.csv|wc -w

查看文件前5行内容:head -5 stud_info.csv

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAA/kAAACuCAIAAADiRFqJAAAgAElEQVR4nO2dV5bkOJamQZoWNJpwrd3MXIZreoSHyszq6u4z06dO74CL4VIqkz3dlVVZ1b0Jvk9mZdYOfB0zDzQBkFBU5mbu/3fiIdxAqAuA/AFeAuT8n4/G3+7tPawNTlut3WqpbxgdYrRIpdH45bd/HD48jj58Pvvy3eV3//off/2f0dUdieP6z8/Pz77LCZoGB55DCCHE8QL+lbwA12d+cbxgnpAqbpZ8lXEloZEyh7aJp+94wTO/MmEYE8PxAu6l0bzmkfm14l2vVSq6vknj0sEcO3uzCJzmlYWG+c1SdP3neLiqzKJSZYmr0+sEtipqHCmvkNdX3kZZbEUFxtIIf53iu44XUJe4fjSC6/PSZ3tuZGQJbyjiUumF5t83wq4RGsJ1ebkqBzc3irLlCGt3upST7JgLqL7CXJvcVgAAAPLj7PeHwy87O3eD/kmruVMt9w2T1vr3j6MPn04/f3f57b/8x0//M7q6jSXAPpRnMPf22aMqflfnRGcfzswTP0HcLPkq4spDqSDhM070/NNSTlRG4tmR43lLofUVdqaDRVMinUaIhru+VEBIS5UlbqRY/GS4tipyHMUujM1HZR1D1gpZbSWyBnFcn+nArE6PyVTOwIkXLTaLlsj9dFq/qL7huHyFzyRMJ+i6avWcWuszEVmt74tsksJWAAAAcmL03d7h09bWTa87bjW3OVp/ONf6/83T+iAFsWVooq3z6UdkVAhy5QMlLxTJ80qlS5a4uaMzOSkiboIsYCs6EXUqEeXOEYq+N9fD7NWyEcBft1aVqrgW1EqZXU4QIUiFjqxeT4/Yh/OeMtoU3LWPZentAADwJhl+3dl/v7F51e2OplrfJuZE6/92eO8M30+0vv/Tf4/eQevngcCzJwmOE13WzPwePEupcqjRmwG2oinAGnx/Hs6bLlkSslIV14JL3DdSOtsscY0AAOCtMPyyffi0tXXT741brd1qdWCUOVr/24tv/hlaPy8SeeosjCylWs4aLSewFc1yWkNequLKvJzWyMLrqxEAAKweh0+bh09bWzeD/rjd3qtW14yybZjtidY/CLX+J2h9AAAAAAAAVo3t+96us75x1euP2+39Gk/rf4TWBwAAAAAAYPVYv7a3b/vrl3Zv3Grt16rrZimm9U+g9QEAAAAAAFg5Nm+7mze9wUXHprS+0SaVRuNnjta/eenyAgAAAAAAAPTYuuuvXdm9s3Zn1GzuVSvrhklr/btQ639z/vX30PoAAAAAAACsEtsPa/1Lq3PSah8367uVckzrHz9+PPmop/V5J6m8ddLsVJftKEnlcT1LB/bqAAAAAAAohu2Htf5lp3PSbh816zuV8tqKaf3ijj7KJ+VFa/0FHAWVO9D6AAAAAADFsHXX37jp9846rNY3kml95uzEha4mv0atvzrZ5QO0PgAAAABAMWze9rfv1tcue51hq7Fbq6yXTNs0E2n9mb6crOsnXd6nJwqxmMxx8LSI5Z4Tn0DlChNWpBydAnCmBPMEAs9NJL4l/jeTfOi0oyfnys3BXJFUWsvaSGxJzsyDN4OKa32R+o/8Lu05adDMFwAAAABgRdi+W9u529i8Whuc9azDVnWzUuoKtP5f+Fp/LujS+PBEjlB3PJ/V0ZRS5J62nm71PS7Y42kIUlZpfUbfTmRwHj48bFKOF3BLJ1rXj1yf7OB6WRvJLRkrDteoHCXt+rzyxW0r6jlp0cgXAAAAAGB12LwZbN2ubbxbW78YdI7a1c1KyTaNVkzrfxFq/bl+S671kyl1nuRKpfW1IqXT+pE/w5Xn3LQ+LW258lPwc7wu+naTXqlMhhXP/Ms5Wp9fDyqxgny3lPkCAAAAAKwS/Qu7f9Htn3V7Y7u93yyvlUzbIM3Yt7lffu//5W8Cf/25K0VC9aV2jYi7puSh9SepyuVbKq0fq1Fu3+Zq+A4Js9MW04LCiA2stiStkwUm5WUx/20eibquMKcaRb4AAAAAACuFfdK2Ty173LFHndZ+o7JWMm3DaLLr+k/fnH/5J/8vfxteSvbhoWS5rjBSCPWoo0pu6/okOongadVUWj8WaSm0Pu9a3bVqpYFVlpxnJEqKq6Wn0cLkJ++N8lvWF7r6y/MFAAAAAFgpOpTWbx+06lvVSr9sts251nc+jp++amj9qQ+PyJWcg3rNWKmbs/tyhI7wOn4v3J/f9rp+rIgSDxhhU/GzcP3nwHMcLwg81wsmnyVPEy9wqV2aLwAAAADASmGfWvap1Rl37KHVPmg1tquVfrnEaP2n8dPXs8/aWj+pOtT2Bef6vufht81PQ8/hJDqzKdRfP63WL85fX+vaUCyL0+F3GMcLngPfDybzx8D36auK22tVni8AAAAAwCrRv7C7p1Zn2G4ftRq7tep6qWSbcx+e24dj52n84evZ59/5f+ZrfccLJlIo1PrJVJhqjxdmJZezbJzgLQKTaWR/H9GWNoKFfWY7nMXtw5Na6+vtwyN7wyFoIy1LznblFLSTYHIYxpo7z0fKVsg+PBr5AgAAAACsDhvXg/65bY8t66jV2KlW1kyzYxgNEtX6n4Ran0RdtpMqb8ku6XSQ74odVGR+93zoTeFFBRalzOxxn+P++tyN/adpZ9P6kdrwqyzS+kTaRjqWpOUzP3HhFIFy0I8VLff99TXzBQAAAABYEbZv1zevB4OLXm9sWwfN+ma13C2ZTaPSaPwSav2Hp/GHL2efvvvhz38dXlzL0kqzvz4A2OcGAAAAAKAYdu43d+42Nq8Ga+c9+6jd2K5Xp/76U63/Yfz+y+lHaH1QEND6AAAAAADFsPewvfewtX2zvnbe6x5brd1GbVApWyVW638+/fjtDz+qtD4AaYDWBwAAAAAohj1ne/d+a/t6bf2i3xt22ruN2lpU64/efz59+vaHH386vrh66fKuLlxv/OQfGrxCoPUBAAAAAIphz9nevB5sXPYnWn+nXu2XS625v/7R/YfR4+fTp29++PGn43NofQAAAAAAAFaEvcftrevB5uVg42LQH3as3Xq1VzaatNZ/P3r8dAKtDwAAAAAAwGpx8H7n0NnZu93aere2NrLtvWatX5lr/Zv7idb/8M330PoAAAAAAACsEEcfdoZPh4fOzs71+vpJr7vforX+/lzrf4XWBwAAAAAAYJU4+rAzfDo4dHZ2r9fXT3ud/WY1pvWHjkLrs5+dyk48wjeYAAAAAAAALIjjDzvDp/0DZ3vnen3ttGtNtX6Vr/XfxVNwfUbCO14Q+TN62uvb3nQGAAAAAACABTF82hk+7e3fb229GwzGtnXQrK1VzNZE6x/c3h/dvx8+SrW+F1mqd7xArOelgQAAAAAAAIDcGD3tHD/t7d1trl/0eiPLOmjW1iul9kzrPyi1fhzXh9YHAAAAAADgpRk97R1/2Nu53Ric2faobR006+uVkmVWI3tuJtD6ri90yw9d9yH1AQAAAAAAKJ7R0/7xh72dm43Bacceta2DVmOjWp5o/X8c3D4cPSTT+jyP/Pm3u5D5AAAAAAAALIjRx6nWP7O7I6tz2GpsViud0kTr3z0cP3zQ1/qqdXus6wMAAAAAALAoRp8Ojp/2dm83187t3rhjH7Wam7WZ1j+Man3p/vpam+xIPHwAAAAAAAAA+TH+cnT8dLB/t7Vx2Ruc2t3j9kTrN5u//PaPwzvn+OHD6P2nkyfVubm6u2ni41wAAAAAAAAWwsnX4+HHw4OH7a2r/tqZ3Rtaza1a1S5Vm81f/vGPwzvn2Pkwev9ZofUje+zLwLo+AAAAAAAAC+Hs29Ho09GBM9f6LVrr32to/fDLW/5SveuzAThLCwAAAAAAgAVx/rvR+PPxweNc67e36tUurfWfpFo//Nw2xnzpfr4Jz7P24j8AAAAAAAAgK5e/Pz395vjgcXv9wh6cdHpDq71dr/XKtNYfK314AAAAAAAAAMvG9b9enH87OnjcHpxZ/bHVG1rtnUZ9rvUfofUBAAAAAABYSe7+99XlP50ePG53x63uqD3R+v0KrfXV3+YCAAAAAAAAlg3nDzcXvzvde9iyx0172Ooeh1q/qu2vDwAAAAAAAFhKnD/cjb8eb9+uh+v63WOrtV2v9SrQ+gAAAAAAAKw2D3+4O/y4t3k96J1YvZHVPbZaW/VatzzfX//hw+jx88kHaH0AAAAAAABWirs/3Ox92Nm4GgzO7N7Y7h5b7a1GrVthzs19/HTy4ev3P/50fP7upcsLAAAAAAAA0OPqf11uPWysvesPzu3+CaX1G9D6AAAAAAAArDLHXw8GN/3+pT04twcndvfYalFa/yCR1nf9hCdluf7CDtdyvCCnA3s5h4ct4QFhaeqbzUbUmWk4GBkAAAAAYCnY/7jTv+r2LjqD8+7gxO4eWc3NRtWuVBuNX377x8Htw9H9h6Hz6eT91+//BK2fb0p88jHKorX+ApsSAAAAAABocvpPo43b/uCyOzjv9ka2ddBqrNcqVpnS+u+HzqexXOsza936ahFan8PLaf3VyQ4AAAAAAOhw/W8XW/drg3e9wUWvO7Lb+63aWq1slSqNxi+//bZ/c390937ofBy///L9n3464mr9mc6brOvrL+9PZO3c+4MTUTqNoPxGOFKTTtddFq0vLjITErsiOgXgTAnS11fif6NoI45HUyQN5oqkkxg6cjSu2JKcJsJ7BwAAAAC8Re7+cLV+2+9f2qHWb+01q4NqqV2qNBo///bb/s394d3j8CHU+n/hav25sErlwzPXaY4XRPWY60flLiXhXJ/Wc5FAVu+xGWUjqm6TJBoX7HGLCVSpSuvnUF/uLEbZRuKo8eujjSQncrXj+fOM5ZaMFQdSHwAAAABvkod/v1677fUuO4OLvj20m7vNar9itsyJ1r++P7x7PH74OH4Uav25jkqn9Wkxxyq0uECTSTY2duTKUKDnpfWjU4yE7zFSXaTQ+nnUV6z1xW0k/zlZC6riJknG9SPTQkh9AAAAALxBHv79euO2P3jXHVwM7KHd2GlWehWzOdH6e9d3h7ePxw9PMq1PrXRn/DaX/dvxAq7fRkR4chfZY3GLcyhPkPKkvPKLU2n9XOor1PoK3yFhdpwW1C4Xr/UjyUgTonsKpD4AAAAA3ijX/3Yx1/rHdn27Ue5VjKYx0fpXd4e3zvH9VOufSfbhoYR32nVu9m+u/7rYnSTmxJJJ+8ocxXmX6ibNTk94sVJp/cz1FcbJovV517KzNTFKfa6y5DwjSH0AAAAAvFUOPu8Mru3+pd0/71lHVnWzXrLLpEEq9cbPv/62d3V7cBNq/c8qrT/14RG5dHMjJF3XnyNfyV7gun7apMOpjI7fC/fnt72uHyuiYKYRfjIOqQ8AAACAN8r6fS/U+r2zbnu/XVmrmh2T1Cdaf/fdROuPHG2tn0ClafigC2Uh99vURfjrR0k/i+CLUIE0jVg1OqMq1F8/rdYvzl9f69qw/0DqAwAAAODtsvU42LjrD9717HGnsdso98uGZcS1/lis9R0vmEipUOsn0FZKHRnbt8X1ZxcwYVOHDsFHpDnuw8Pu/pPkLQZv5yDRljaChX3Gf2lx+/Ck1vp6+/DI3nAI9uHRsuTMCwxSHwAAAABvlO33a1sP64N3fXvcqe/UzV7JaBukRir1+s+//rZ7eXtw7RzfybQ+ibpO6ysrHR0pSZsO8t243Cxmf/3oF8HJEqU/QpDuKMRJndnjPsf99bkfRtBTqvRaP1IbfpVFWj8SWVhbsSXDayD1AQAAAPBW2XT6m/fra+8G3XG3sdMwu6bRCtf1Q61/Q2v9Yy0fHgAAAAAAAMASsHbXXb8dDC4H3XG3vl03bIM0DVI3Ylr/C7Q+AAAAAAAAq0TvutN7Z9snnfZRu7pRJRYhTYPUuFr/p2P+/voAAAAAAACA5aN7ZXUvLGvcbuw1ymvlUOsbca3/CK2/ooiOKUjxsQEAAAAAAFgpuldW/9K2xu3abq20Vopq/YuI1r966fICAAAAAAAA9Ohdddauep1xu7pbLa2VjI5h0D48oda/fzp5/AqtDwAAAAAAwCqxdmNv3g7sk05tt15er0y0fpWU6/Wff/011PpDaH0AAAAAAABWjo3b3ubtoHti13YbodYnDRLT+h9PHr/+AK0PAAAAAADACrFx21u77nXGVnWnXgq/zQ21fo3V+u+//vDjS2t9yYFNrzLfLKximV+K5bRVglJpHlWdez0THJFdSP5cmG/RX7RVl7NfpeGlayLPP6/SoefkhdySy2Pn4liGFkQrAJr1m17/stMetgrV+glFgYC3ofVX21aL5TXbapm0viCDpdT6L5NbPiXIpz/nz0vbcjFav6j0FlGC5ew5i223ZWKZ6vZ2W2GxZBmDixi//Wu7e95uHTVVWv8baP3FsNq2Wiyv2Vb5a/30QOsvpgTLqdheHmh9FcvZc96uylymur3dVlgsy671u+869lm7ddQM/fXTaX3x6yDu5u6zK6IV5FR4nkDguUl7peMFz/PojjgwHqrIl4mc+Ka8XLaapETHjvY5YaFd//k5CIJpwPQ6JuPXZCuduKL6JrJzihZ05/lGo1Hm4qY4vd/PrpsWTcvO6WskbGDHC6KpJb0byp5hmca+lJT1lduZU+hkD2d5fYWtT9Q9Jx9b8VLXtSQvVFYjNVL1I2oFTqRkPXY5e06WZ2gmlSktc2FP5+XUDG+pFV6fGlGXWRE3U8+hsC+s7pnVPm7V9xqV9YphT/fhCbX+5c3BjULrx4UVv3U01gWjfzPdcGKURJ2Gutrx/GjK86xi10rzZa+OxFWWaelsxV4cV1mur1H5sDsGnhP+JrDOytsqS99Q2TmvFhRqDPFdPSxMEMwCHc+L3swEdk5fI1m/0pqvyRHWNtPY188yYX1nP/IrmX4cKepL1K0vtGUWW8mtIU9Zma+6RjLE40TWCrFYSXrscvacLM/QeLVipLNzcU/n5dQMb6wVXp8aecHxy2KfR7S+SWn93yZa/2Gm9a+5RVHe0dJpssifYQOmbBtVKP2LPF953AyFkl9UnK1kg5hDbJCH2c7/53jBtCivzlZZ+obCzllbMBpXIc3iIZLMZFo/rxrJYyeW+sLaZhn7crLVl182nTInKhXnF3Ul+bbMYit5DolGGSffTEVJ2XMisiJRj12VnpM05XQq84WezsupGd5aK7w+NSIvsyJulp4TxT63uqft9lGzvsOu69cnWv9QofUn7xfk99VUmoxqJSorvRt4LK4qlEpbni8vZfYmLy/V8tlKoYzn5aaIj655CXj/Y3NbXVtl6RuLa0FB91dofUleBdlZ3K8iqcWXd9RIJjxpx746wyz1JUI7Zx1H4vryy8lNJHZFFlvNLudaI+Eoi+ebsCS8gmn1HI68j98Z9TJciZ4jD03aDqnsXOzTeTk1w1tqhdenRuRllsfNUuYY3XPLPmm1Dhu17Xp5rWJ0DNIkHK3/4ZsffvxpyNH6sYrwipFKK3AVTFr1owwVa7L43JGHpvVXwFa8KXv0b9XoCi94/bZK0jcWXKoX1/qKGkn7FVuLVNJNECnL2JeTub5SO6cdR/L6ataRe0UWW+neVZKHJi6JoGz8nqNoBUlHkrE6PUceGlMhqVRmsrtofk/n5dQMb70VVl+NvNT4jdG76FijZuOgXtuulQdlYhHSJKQ20/q3hzePKq0fLZreA5bz86qu66diaWyVJWX56Hp9tsrSN7Cun3B1dvpTOuWmv16lPfbVGWarb5LVHV00Vv5Sav2XspVGvoVofZ1WmOqsRFJ/dXqOPDRpO6Syc3FP5+XUDG+tFV6fGnmp8Rujf9FpDxtzrd8mpElIPaL1P52GWv9CofVFZdarSXT+w5vS6d7Bk06H6V/k+aZ+haJZxoXbKtnqLJuyfHS9Pltl6RuKFYuMLahaOBD/LA3hFz2HGsn7Ff1jEKQTboLGyDL21Rlmq6/orpVlHMnrOytKcq2f5z2HM47ko0yebzatL+s5qkTDa5JJ/dXpOfJQzvXy7FPZubin83JqhjfWCq9PjbzY+I3SP7c6o1b7sNHcbVTWKuG6vlEnFY7W/ytP67uxb4wF4ktkhmn00ATih9DkdYZ2xem0CSGFfVMf/hCtXFib+JhbQltpKDZmxk6nrBhdr85WWfqGws56pRLZit8okqJrhlDh6ptbohpJ+xVbXeGzjmsNVaUyjX0pmesr6s8ZxpGqvtFiqyumWV85CmvIU1bmq1mjpD1HpxUmxUm4GrecPSfLM5RTL3mttcucw9NZxBJqhmyl4pQtxnK1witXI8WMXz16Z+3uuNU5arX2WtX1qmEZpEmMmqGt9cmspaW3uGkVo9Wcxw3CTVUFt87n5+XdX1/Y7qJxu1y2Uim2SHkSvDV7fbbixo0kLaqv0s46pRJqfcn++rQd+QbV1UaR1DPWSNKvonUT3Nqkio3JgL0m2dhPukKbpb6i/hwtdJJxpKqvuPXVPSe9rVTWkI8FeWhGrS/pOepWCEuW/Gm8nD0nyzM0eokw48R2TnkH1mEJNUO2UkUvWfJWeJVqpOjxq0f3pN0dtztH7dZeq7peMyyDNI2EWh/Ecf0srfK2WGVbSaVoQfmtqq3SILdv8dZYdPtm4aX7Bmy1qqyyNVap18lBKywDq9wKcuxRqztud46s9l67tl4z2gZpGARaPyPcV2mAy4rZij5FQ/zmrbDMV8pWWVGszxZijRdt3yy8QN+ArV4FK2aNle11ctAKy8CKtUIS+Fq/qu+vDzg48TdaQMDq2Ur6QrXwnFfLVqmZvjJVfEVQhDVern2z8DJ9A7ZafVbPGqvZ6+SgFZaB1WsFfSZa/7hj7Vuro/W5fqQCZ6e3DmylD2wFRKBv6ANb0cAaywBaYRlAK7wcvVG7P+50hx37wK5v1A2rRBpm3IfnZLm0PgAAAAAAAEBFb2QNxnZvaNuHdn2jaXTKRtOMf5sLrQ8AAAAAAMCK0RtZ/ZHdO7btw15jowWtDwAAAAAAwCuhN2r3h53ukW0fhFq/Qpol+PC8HiKfy8MlDiwnkV3b1Fuka6f7Vvq84zAb33M2aU5qCdwwAADgNdAbtbvHln1o2we9+kbLsCqkUSLVuNb/VqL12Q8u+OfhiD+/mH3OLTg0k4Z/yJnos46U+WrEzRKaC+xBbiFhhSI/0xIqjX6KHQ2T7HxMorAz3XWkHYdzWE4c4Rf0se1/mS4rr0t862B5z1GlpVnhxD2WuUZaMqk1FHXK0xrRhAPfZQ5R8T1nPk31+W3LOyslVrdcd1bIct/QxvU8R9jNRamzW0O7fvRczyDgSPdoHvHGzWC9nPoGAACALFBav1vfaBpWmTRMUjUqNV2tHzl7ILbVqlxsTh5IXBWqkqayuFny1YmbNlSB9DP1yJOeXrHn5j79YVYAxwsSP7cnJWIURIKHt9TO7F62rDZRhfIykh5nJzzAW76jbqzk8p4jo7iRwpQ2COQlU1tDHDlvaySEf8wh+ytvzpCf0Mxy31Cly4xvzwsCz6UqR9VDUiW6ManSSEb+PGj2v5w2y0jfNwAAAORJb2x1hx37yLYPbInWP5VofY+31j69t/OEhehg4qRaP0ncLPmycbOEpsP1EyehIaSSiHXfp0WD7yd+ePPszJWzs4rKQ7npi0JVx27L+pmw/dKo28JGChWHezx75Bq5r4zEznlag5N24LlzNxRNjc7T+tHq5C80s9xzVAmzjaOr9V3XnUbhzUGY+ZkbeUU2O03ed2NFYK4UvFtRVglaHwAAXpLu2LJHnc5xxz7o1NcbRrtE6kYirR+HXhqMLRPy1w1z1/pZ8pXHzRKajhRan4nMX9dnvHul8Z99d5qKM1ltzEPr871Bpr/IQzWSF4dFExLHlqSbi4LJa6TMIgSeIy8Zd2Fe087FWiN8TTUvDqtIhSyR1s9j7Me0vuZMPelbEmZ1Igj9hTyXEEIc1+W2vedq3jE4VYLWBwCAl8QeW/bI6hxb1n6rtlYzWgapE1IlE61/kULrR19k6ygJsdZXr0SL1ozT5iuPmyU0JQm0fjy3PHx4fHeSTPh9X4qHd7FaP+nCPHu9ePk1iV9QGnIbKdPEpvOxBNbQt3PR1pimQyczFaA8wtck8wnO3HMl7KmTsi5M6+cy9tOt6+tnFHf8m+bBvHWKTR0Cz0v7jTO0PgAAvDD22LLHVue41d5v1tYqRovEtf4oidaPe/8Gk0fyczD73Cx25xdp/ahbMe+BJtWRKfKVx80SmhK11mdmRYy3cl5an7j+s++FSiwnrc93SZ/+Ig+NFTH5evNMzqTTr9nbNceRwiwhJ3tNoWvnYqyhtRwtqsvUXGH4dJRMf6A77kK0fqaxzzOEtr8+VVUZgedwXpbQPjyFSHJofQAAeGHsk5nWb9TWK0abGA3DqBnlVFo/1Jw8l9V0Ckbrolem9XXfxgvVXLgKnzYFXnFm2in8b05an6d2Y38LQ0WpxIIEHzCL8lHFlddIm3xHCrOuK13517MG30ekOGvQybDL+gL5OSvz/AqO+Gf/zpPctT6VcCofHhnTWZDIOyegu07gedKbR3JbQusDAMALY592OqO2ddRs7dVqa2XDIkbTMGtmuVb/+ddfk2l9jmjK7JmgcdUb9eHhes/GxBGjHbKs61Omyk3rE2ZmEzoHMQWUh86vEdRK1+Odl4TK1zqTgsl3pEQuFJVMUiOlnYuzBvPZaFSXTzqsRK7Hx8aL+esX4cNDjfEU9RDPj0U5uuzX8dMZi6BIekDrAwDAC2Ofdqxhq3VQr29XKn2TtOh1/V93L24Or/X89SWro9z3zSx5a/1M+crjZglNR0J//cjCqMD9N0HmarcPrXKpo8htxQ11vEAk9fX9zuOlU6u0LOo255EiWv1lKpDEpVs9D9EolRZM146v4s+CRelzevSLaf1cxr54iKbT+rxJG9v9HNZPiLmVTaf2mRYroPUBAOCFsU8sa9hq7Neqm2apa5AmIXViVBNqfaEvfexGL1iFzduHJ1O+8rhZQtORWutHn9JLroQ+7mwAAB68SURBVPXzlfrC1DTW9TVEWkoFs4CRoqdDpSWMKe4irBF1Y+Ir02m4qPljJno5rZ/H2Heme9oqYQynzSQW5bfvzLbWYnsmPc+i7m9cPyBVlaD1AQDgJZlo/b1aZd0wbUIahNQIqRJK6zsKrT935OZCP/GEt32B/2vUd1f729ws+SrjZgmlstXWAQm0PpU5J5ZC63NLpan1FTUS2dljJ0lsfHnotHBiQS/96JZ9FcNcq7UELlUwAmsUNVKUV8hrJLdzYdaIXcOdycmqypXxulpfXqqU/Tn12J/pdd8VyOl81vXj8G8KlOlZJ5/oGREkra0AAAAsis64rdb69x9P3n/zw49/HZ7Htb7AgUDsdq2MHlkkj61J6cXNkq8ibsZQoqd+mOT4cxw/ZmTfnVWNKzPEOxiKSpVR6yvsTAcL3thIDCmW+sqlaGYtNNEytrLnEIE1ihwpsQsT+ZLI7FyUNTTyUGTNPTc6Pj/IV+tnvG+IUnYcV7VgHqmHzvEDqbV+1LWKdugX2SSFrQAAACyEUOs39+vVTbPUM0iLkIZB+/AczLX+TzytD1LA9eQQuV0/+y43jN6ST+yZKyP+IiX10zhL3NzJ4jiVh9MVrBFLRJQKf2IiV8uTqzSXikVXytuouBbUSlnPLUfySbraglMiWp8zf47efHjTwaXp7QAAAGJYo1Zn1G4e1GtbpVLfIJM9N01o/QIRr0e/JFlKtZw1eilgDRqRNVJLRJVrT6ZS6YQWl++LkuUTlOWsEQAAAEIorT9Z15dq/WNo/TzQ3xJlkWQp1XLW6KWANWiW0xryUhVX5uW0RhZeX40AAOC10R61OiOruV+vbpil7syHB+v6AAAAAAAArDjtUdsaslq/Rgj89QEAAAAAAFh12iOrfdxu7jdqm5VS1yRNQmqEVCL78Hw6Fe7DAwAAAAAAAFhK2iOrddxq7jea27XKoGy0iFEjpEyYs7TuP52+/xZaHwAAAAAAgFXCGlmt41broNnea9bXK6W2YczX9X/bvbg9vH4cKc/NBfnieIFyYwuNb+Jy2TERgCUhywY8b34sOA5zjgPnfIykptW5SwEAAHh5rJFlDVvtg1Z7r1lfr5Yt05x/m/vb3kTrfz798J3/41+HFzfcRNjdoPnHSYr3e55t35zi9CBh3Cz5asTNkrIeam3i+s+BTx3AEzkOdrLpvutw0nB4P4rLwZRkUnX9qkmtId8LXBiqcy5VNCHRoVWqqkTjKnp7st3NhVFzHEfxa5THjOVlq3zGApuWjmIvZizol1FUX+VJW3qEp9cKD+Tgp87uccoeVOZ4wXMQcKR7NI8UZyqLybNvAAAAEGKN2p1Ru33QbO7U62uVslUqNU2zVppr/Zv3o4fPZx++83/8G1frR7bJdrwgLo3E58ZPHjncrZ1V+z3L4mbJVydu2pT14R566VCna/IOCaJ+kymBBM/XiTphNELC6EJrsDtzR49JlYfyMpIegsoKP+2UI3EVvT1ZmWMVKGYcMXUJAnm/zNFW+Y0FKj19aZn/WNDJMvVdRZUuU17PC+ij9JjKSo4ZoxuTKg3v6NwJ86DZ/6TnfOlbMu++AQAAQER71GoPW/XdWmW9VLJNo2EYNcOoGDOtf3TzfuR8OXv6nf/j30Zcre/x1tqZp2xEOnCeK6m0fpK4WfJl42ZJWV0PxVOUVoDCZ7rjug73MPs0uP7zs+/7tCzw/cSPZ541uIJ1Vmh5KDd9UWikhRKlHFvUl/X2ZGWO5lTYOGIK48r7ZZ620itVEhJp/TDrPMeCdqYZ7kiqhNnG0dX6rjvrobw5CDM/cyMv0MI8pjGF8wLH89MYGVofAAAKpzlstI4a1a2y2SdGm5A6IRVCyjOtf3d0834cav0/87V+HHrxL7YQyF8ZzF3rZ8lXHjdLysmZOyO4rit8vDPCwfU8x/V9V7z+lkRihLWb5uVM1hPz0Pp8f49ZLaShGskLwxKkrNOIVPMnKrOavMbRLELgOfIqFWSrxWr94saCLlnuSKqEoxMx8bpAJKskMCsbQegv5LmEsC8W6XJ5bkpfKGh9AAAonPphtb5frWyVzAExO8RoEKNmGBUzovXPQ61/qaP1o6+qdbSCWOtLnmCSuFnylcfNVKPERNMWaX0y10Gu5/vB5OV4GE4va0pe1/OZKJIwszDNFFUrVuvLChRPRz9lnaVXRlnmqvVzG0fTxOZvhhZsqzy1vq62LWIs6JLljqRKOMW6vn5G8Rcg0zyYt06xZgg8L/qxb4IqQesDAECxVPcrlZ1yedMsDQzTNowWMer0t7mJtX7cvzd8Vkz/w7+3i7R+1HGY98iS6sgU+crjZqqRGlYyxZb+JFp/GsWbC0+6GdSuueIC+W6YnBdKppy0Pt/pXOoPI9axCVaUdVPWXdSfX5OgzEpyHEdMPxLXqjhbFb6uz/qdzH/OeSzokuWOxIU3x9H216dGsIzAczhmpH14CpHk0PoAAFA4lb1yedssbVBav2aQ0F//7xN/fX2tP/c4mZCrMhZc9Kq0/ixq4Dmcx6tK68+dZgVCZhJJv3QzmRhKhWSR2SrFosT1bOxvYagolVgQxwpaKasX9WO9Xb/MCvIdR8y6rnTlvyBbLdaHZ55r3mNBl9y1PpVwKh8eGVObirxzArrrBJ4nnTGk7OrQ+gAAUCSV3VJpy5hr/fDc3PAsrb//untxe3T9fvyg56/PEV35erzo65vV9+GZCv7YrzKt73h+6E0frtQFIi0wUR381VAWjvNHblqfMIuNoXMQU2V56PwagQCUeEQrU1Z6U4umGDpllpPvOIpcKGqJIm31Ilq/gLGgy6J8eCgPef5LPilaM1EmR5f9dn46YxEUSQ9ofQAAKJzKXqm8bZZDrd8xJt/mlqZa//z28Drcc1O4D88EgfTJ/k2h8irur1nylcfNtUZCwjX9mI6Vav1IILOUS3lwJCsUp3Z5an1VXqpQ/pRoFqTrpqzW1vEYOiZQzhh0U07f60Srv9F+VZitXkTrFzIWdMlyR1IlLJ7WptD6vEkb2/0idmRug9OJfyZHKGh9AAAonMp+ubJTroT++pYRLuqzWv9xdC/bX58QiS997FYuWIXN24cnU77yuHnWSATrffvMlSr0RVM9F1t1m/6l8GaQF2VRWj9fqa8vpeJXqkuipzmTyrkFjCM9HSotYRJbaZZKEx2tX+BY0CXLHUmVcLjjrZJ5Rgo3fV4s6iWHM9t4i+2Zs5ZgrMj3A1JVCVofAACKpXZQqe9Xq1ul+bp+lfLhOb85vHoc3X86ff+t8NzcuSM3F/qZJryxCzxc6V+Esk6QaOp8lXGzpEwFSpajmXiidVPON3jUiqUGnD034r9qan1ZjQRRCKF39+A0rzx0Wji+keWLzfKUpXFVvV1ZZqGtihpHyisKs5VWqRQ9hy2L7rp+MWNBt8wZ7kj8lGd63XcFcjqfdf04/AkR+3aEcvKJnhFB0toKAABAfjSOqs3DWnW7ZA6I0SGkwfrrn98cXjmh1v/hx78Oz69jCQiepWK3a2X0yBL6c7q4WfJVxM2YMhE//xK58LqxPTe13oyIrylC6yusQQcL3tiIG0Ei9bU8yAUpy+Kqe7uqzERgqyLHUezCRL4kaW2lWao8tH50jbygsaAMzXhXEaXsOK5qwTx6M9D4/CC11mcislqfc2hZalsBAADIicZRpXlYrWyVjC4xLBL9Nvfs5uDKGd59PH38RqD1QQp4vhqaOp9+ROq6XNOv8SVZ6Pum5Bs3d9K4R+QRN0EWsBWdiGBZPYbv8kN8lxCH2qG36LFQXAtqpaznlqNhAPV6ekTrCz4bj7ZF4hoBAAAokPpRpXFYqWyVDJsYFjFahlEzKK1/ffDOGd59PHn85oc//QStnw+6X3ZKSHlKpYwspcqhRm8G2IpmOa0hL1VxZV5OaxBCUjvbLHGNAADgrVA/KNf3y9WtUqlvlGzDDLV+iZRrtZ///uvO2fXBu4fh7dOJ8/WHP/10fH710uV9DSTy1FkYWUq1nDVaTmArmuW0hrxUxZV5Oa2RhddXIwAAWD1qe6XaTqm6ZVYGZrlrmm2O1j++fTpxvkDrAwAAAAAAsEpUts3KllFZN8rhun7TMCb++rWf//7rzunVweX98e2H8cOX76H1AQAAAAAAWCHKW0Z5g5QHpNQlpkWMBjGqhFTmWn//8v745sP44fP3//XT8dm7ly4vAAAAAAAAQI/yllHeMMoDo2QTs02MOjGqzLr+/uX90c378cPn7//rL9D6AAAAAAAArAyVLbOyUaoMTLHWvzu6eT+6/wSt/3KkOCkHgNeN43lpjlYQ8bY3jGH29XJ9zukZSU1D74EKAADgJRFq/Wqo9d/tX9wdXU+0/pFA67P7PfMPjBTv6DzboDnF+UDCuFny1YgrC1VZQwhn2+zpofXKjczlx4Nm2AkjLBSVwKSU+vWS2lm+27dqL3AqXF7FuAGztL4sZVXry/NV5aRprMS9nblGWrKYJRPs157UVioE8jyNMhUeLSU4pzYlefU6KeHptbI7guiONjMAO2FyvOA5CDjSPZpHijOVxaQfKQAAABhCrV/uG6XOVOtX5lp/+yTU+o+ju09/FGj9yFkpjhfEH+jik+EnDxXu5s2qHZ1lcbPkqxNXFKqyhj60Yomu68cEuDSZmFBPUqCJ/mBUQIIHsNTOrFaLLsjKQ6OmdTxfukki74zhVK0vS1lnLIjzlVHcKGPqEgTyknG7u7iNZHFzGSmO53uOfJ4b0aF6F0fIR23m1us4MZnSel4QeC418Kn7h+QVId2YVGl4R+dOmAfN/ic950vfjulHCgAAgCjlLbO8YUa1fomUq7X/+/dft0/e7U20/sc//uefj055Wt/jrbVP7888ccB5cqTS+kniZsmXjSsPlVsjCUKtn8xJgXpSp1pnc/3nZ9/36Qe/7yeuEs8KXEk6K588NJEVhG9FsvQcbphm66fR+oWNMipO4LnykkXSVbWRLG5+I4VaeWecTxKPE8k0KM+T6zL3OknCbOPoan3XdadReHMQZpbsRubbYR7TmMJ5gWwqLq8StD4AAGSlvGmW181SzzAtYrYIqRMS1fq3h1ePQ7HWj0M/ZGMPXP4TOHetnyVfeVzNlHWDoxczYjf2gE7unkAtuKV6vxAWf1oAZ7JimIfW5/vVTH+RhyawqqQXZek58pTlkXNRMHmNslmEwHPkJeO+HtF020htK2FBppeyTjZUR5UPSk6zxwteyHcyGXudNOHoRExrdV26FM+BWfcIQn+h8NMJvsOT43luytkStD4AAOTAROt3DbNNzCZP65/fHl49Dm/1tX70ZbSOGhBrffUbYNGacdp85XF1U56SbIGOeewyS/m+m2apL7vX60RzhKonVFApHsB5a/3J/zUcnGVWy9Jz9FqWf00eCia3UTZNbCaRRSWL10Vf66e3leTqwHM4rwcmY0hu3rgQnjqMKJVxZrL1OnnCKdb19TOKrxZM82AaITZ1CDwvNrXSrxK0PgAAZKW0YZbWzFLXNNuG2TSya/24B2/4NJj+J4FXA/tKOeLfK4+bJV95XN2UedZQInoFzktG4i7BSzKdP/RcBrr+s++Fi6U5aX2+W/lsuVYa6kY+EBbZWV7UvHtOlHSl0iHHUcYsIYtLlrwFlflKaqRNVOpPsgplu7i7MwNN/IZkYev6ye4qEXjr8tr++tT4lhF4Duu+M63KzIenEEkOrQ8AADlgrpulgVjrjyNa/1KeGvNynZB8lZPooqXV+jFrqKCfmM7UMX62vBh5GoeiW5k68xQWzpfEzMTPfLk0J63PU6xi/c6GxpUhd1VYsVScoeeoF6ElrZ9RweQ7yph1XenKP6e+8haUx5XVSBdK6oeZM/kwC/XREHYJPMx7unI9lbWrofWphFP58MiYriiIvHMCuusEniedMSS3JbQ+AADkwETr98ySZZpNg9QNUjGiWv+do6X1OUtzmb0LNK5aUh+e5AuVjuu6DvW0DPzp83WqOeJuxmoi6/9J5QvHvSM3rU+Y5cRwNZaxpDCU3wo8BSUrZ/qeo/SmlrZ+JgWT7yiLXCgqmaS+8haUxxXWSA/H8+fqcvrCifmkQ5TsRKRO9PDMG2z6QsD3/dnLrIVo/SJ8eJz0g54I522SHF32y/rpjEVQJD2g9QEAIAdKG6XSWmmi9Vtmeq0veLJqfnOWt9bPlK88rlbKqeULnQLHl0BnJZ+TUgrfHSq22nVDiV4UuSqMtoJK66vVUtqeo0pZ1frpFUzuo0y0+htbH9d16c7bVtLMIgmzylLW7znOcuyAC98XLEzr67agKmFBhdNpfd6kjW0sh/UTYobndFkgw70HWh8AAHKhvFkpr5dLvVKpM9X65ZgPj1Lri31Dojdrwfv8vH14MuUrj6tOOYWnTIyYbKF9exImzZEN8S8aE0QuSusnkPpxB+FYM2iIpZQ9R13ONHMMNQsYZXo6VFpC9srMthJG48RkJa1S67tCL5fJFvXO4rS+ZguqEmbc/sQwqwjaTGJRfvuMGXnTLOZuleJYMmh9AADIgVDrl/ulUsc0mwapEVImxEyi9eeO3Fzop5bctT3ugUH/wr6gV8TNkq8yrjRUYQ0qW9VyJ/vkj+iAZM+/qHLgvx7glkpT6ytqJLKzx06hIppaHhp92RLrLUqtlKr1pSlrtb5cwQgsWdQoU14ht6S8jbLbStyv4lI+csPIsq4v+U1eKnVolvsVP+WZXvddgZzOZ10/Dn/hgZqHs04+nAWGdLYCAACQhPJmpbJRqQzKabW+wAlA7HatjB5ZQo+tK+nFzZKvIq4kVMcaRPmE4zvZ06/QJ/9PsPLHfLrIf5AXofUVdqaDBW9sxI3ALEomWU7O0vqylJWtr8yXCCxZ5CiLXZjIl0TWRplsJbHGNCBa/VgfyKj1Yy+PlKWShma854hSdhxXtWAenQXFd9ThRUmn9ZmIEYd+kU1S2AoAAIA25c3yXOtP/PXjPjyJ9tcHSkS+C/MnHEfFxdW17yV032eeoLxVzNRP1Dz8lnIjjQPES6fMZPEqLJmLrcTWoDUld1IhU6t8b/Spk4pwCqkulTo0C1op67nliD37FXWniWh9zrcXUc3Omw4uTW8HAIBXSnmzXN4ol/vlUqdktkyjbhjxb3OTnaUFVGT4HrFAspRqOWu0isCSNGprvIS95HkWV6Il7htZPkFZzhoBAMDrYa71LWj9BaG/rckiyVKq5azRKgJL0iynNeSlKq7My2mNLLy+GgEAwDJS3iiH+/CYbdNsmqRuGBXDKBuU1r87gtYHAAAAAABg5Sivl0p9s2QLtP7JROuP7j7+8T//Aq0PAAAAAADAylAamEaXGB3DbJlGwyA1ItD6n6D1AQAAAAAAWCXMvkFsYlhCrb8/1frfQ+sDAAAAAACwSnQN0mG0PqkQaP0Xhn/WVewazndtgo0GhTuFA7AKsLtq8nZqT5bC28NxmF18OedjJLWOzl0KAADAEmArtP6ehtZnd3TmHwkp3rN5tgVzihOAhHGz5KsRVxbKFDv1LhPq3cld/znw3dgm4c9B4InO/5mXlXnyaxRFc3tuHlI7y/fz1g9VCJW4NeWtnyWu8kQkaU6aFU7cn5lrlLtYig7pUtUoi52lOF4QBD69n37KHR45J7apTqJKRFF9g03G8xzhcWSi1Nmt7FlbOF7wHAQc6R7NI8G5yGpy6hsAAAAU8LT+fM9NDX/9yGkojhewTwT52e+TRw53e2bVns2yuFny1YkrClWfLqMLd4We1iXKgz5Vh+roPqWzHqgktDNrnagSSxoqtnMsd3nrZ4kr7zkyihtHTF2CQF6oaAryVpDHTWJnBey4kh/qqneYlFIbp6DQvkGX1vOCwHMpm1A3A859gUmHOjFsEp13/O2EedDsf1Lz6tsxv74BAABAgW0Q2xBq/fG7vfPbo6vH0a1wH55wjYmCuXvzpIPowNikWj9J3Cz5snE1U05Wh9mliqcorQA5z/T5T7NJATfVZMo9hwNQeWbgCtZZPvLQWJlkdhaWX6NxksVN1jciORU2jqg4gefK6xxJV9EK0riapdJDofVdN6NaTPKeS51Y3n2DSoNtHF2tP7UP1+2GdehhTTnLYxpTOC9wPD/NPQJaHwAAiscmxDaMjinR+knP0qIX/2ILgYL36Hlr/Sz5yuNqppysDkJCqe67k2ew4PE+F/RBMJP2gimBZBFPQEFan+/vMf1FHhrzHhDbWdICysZJGjdZ31CR1ziaRQg8R15n7sK8pttGFjurkWj9aefnT32kI7MgjVlY34hpfdm6QCSrJDDGDUJ/odAxkO/w5Hiem3K2BK0PAADFo6P13yXS+tFX1TpaQaz1JU8wSdws+crj6qZM1SCj1I9IWp7WjwZSl/EEwSvQ+pEUxUWUFV7HSSxJ3ER9Q0lu42ia2PzNkPYLEH2tn8XOoijCXjvV+jFHJ3UqTIpBqqVovcIX0TfSrevrZxT/5nmaB/PWKTZ1CDwv+rFvgipB6wMAQMF0COkQYhlGyzAaBqmz3+aOL/fObg/fOfpaP+7fGz4rpv/h39tFWj/qOCzaY0aoI1PkK4+rk/L8WZj4IcZKptjSn0zrU2ESl90UcFYFk6au7cMz+0UeGi1ZOpWZd6hur9Mhx3HE9KNkL0C0WkGaqjpUi9i6vtakVbZ2L/f5z0TufYO3Lq/trz9tfMXifuA5HE8o2oenEEkOrQ8AAMVjEWIR0iah1jfqxOBq/ZunP/7nn49OL+WJxdaxM2oUrYuWT+uL7aHFdLWS83iVaH2O1Fc/3bXKU9C6Pk/Pxv5OEsrXuKplX4kWTBo3N62f7ziKOT8JV/459ZW3gjyutFTJkPjwyGNJ23eBPjy59I20PjwyZu9IBN45Ad11As+T3lNSdnVofQAAKBSLkDYhLWK0DLNpmLTW/+XX7dHl3tmNrtbnCK7MvgcaVy2xDw9JL5T57glirc9K/cBzxGLGcVyPuy2ngMK0PmGmI74bs6QwlL/eHC2kSs6p/FmSxs3JhyffcRS5UFRnSX3lbSSPK80zAem1fr7SVLewC/HhoTzkU7zJE8zbJDm67Lfz0xmLoEh6QOsDAEDxdAixiNE2zJY50/oTf/2Z1r/U0PqSlVWNL9Ly1vqZ8pXHTfiNXYaVXd+NCVih1qeyoZ/I4pX9BEUqUuvHMhJfFP1UNa6cYj5NimLL/VlSxM3h+8vcx5FI70b7lbZLt3oeolGqpKTT+vFiLERVFtU3IlaIpJ5C6/MmbWz3i9xwmNug70qLpAe0PgAAFE+HkA4xLLPUMs2mYdSJUSbEpLT+6c3h5cPx9Yc//p8fhVpf6Esfu5ULdGPePjyZ8pXH1UxZM1gYiVa1rAeGyC9X5cac2ol/UVpfX+rrrOtrSCnp24Y0cRP2DW6+BY8jPR0qLSF7ZRY76xK1S1ymOqI3VeGYmMrSSSn4L81yo5C+MUkj8H35u4roVF7hyMeLRfntO5ON/KP3lVkLMFo/xbFk0PoAAFA8FrWu3zCMGqP1t0aXu6c3BzOtf8LT+tTTlAf9TBPe2AUerhF/dP1vc7Pkq4wrCeV9Fyeangie9LHVR9G6KU+7h5GF3vHK9/XcUumoElmNiNjOHjuFYuPLQiMe7TGRrLVQLZk8po2r0+sEtipqHCmvUDihSdsoi62owFga7NsI31Wt67vcfWDis3R2yVrxUXfK0Pz7xkyv+65ATuezrh+Hv2xPWZJ18omeEUHS2goAAECOTD7MJWbTMOuGUSVGmRgzrT+82D29ObiQaH2Bi4DY7VoZPbKEHlt10oubJV9FXHkou44m1vO8sEQuvNx1/ekvnHXOF9H6CjvTwaIpkU4jJFxslpYqS9xIsfjJcG1V5DiKXZjIl0TWClltJbIGcVyf6cCsTo/JVM7A4TsbcfybxO9REmv9ovqG46oWzCODW+dssdRa342cbkAPHZFNUtgKAABAXlBa35Bo/Svxuj5IDM9XQ1Pn04/IqBDkygdKXiiSF3uQqMkSN3eyOB3l4LCkkwVsRSeiTiWi3DlC0ffmepi9WjYCRO7m8lIV14JaKeu55Yg9+xXzDZqIfTjvKaNNwV37WJbeDgAAb5MOMSxitrla/+9bw4vd02tK61+8dHFfBQLPniSwG17k8tVhllLlUKM3A2xFU4A1+P48Qo9+fhKyUhXXgkvcN1I62yxxjQAA4M1gG4ZlmG3DbJp8rX8Sav330Pp5kchTZ2FkKdVy1mg5ga1oltMa8lIVV+bltEYWXl+NAABgBbENwzKNlmnItP49tD4AAAAAAACrhmWQtkFahtE0jRq0PgAAAAAAAK+GtkFahDQJaRikahiVBWr9/yf9BwAAAAAAAMhEROuXiVEixIDWBwAAAAAAYNWZaf26QSoCrX8OrQ8AAAAAAMDK0TZIixhNYnC1/nESrc87SUUGtD4AAAAAAAAFEmr9hmHWDQNaHwAAAAAAgNdDi5AmMeqGWTfMuL++ptZnzk7UPjgFWh8AAAAAAIACaRHSIEadmDWp1n8n1vqzAxUn6/ray/vQ+gAAAAAAABTG/wcYzbgRMNT/lwAAAABJRU5ErkJggg==" alt="" />

导入数据
将/tmp/目录下的stud_info.csv导入表stud_info中,忽略第一行
mysql> load data infile '/tmp/stud_info.csv' into table stud_info fields terminated by "," ignore 1 lines; 
注释:terminated by ","表示这个文件的列是按逗号来分隔的; ignore 1 lines表示导入表中的时候忽略第一行表头

aaarticlea/png;base64,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" alt="" />

导出数据

mysql> select * from stud_info into outfile '/tmp/stud_info_wu1.txt' fields terminated by "," enclosed by "";

注释:terminated by ","表示导出来的文件列与列之间用逗号分隔;enclosed by ""表示导出来的每一列不加任何东西

aaarticlea/png;base64,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" alt="" />

aaarticlea/png;base64,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" alt="" />

将数据导入pandas
In []: import numpy as np

In []: import pandas as pd

In []: from pandas import DataFrame

In []: inputfile1='/tmp/stud_info.csv'

In []: data = pd.read_csv(inputfile1)

In []: df = DataFrame(data)

In [7]: df.count()

aaarticlea/png;base64,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" alt="" />

In [8]: df.columns
In [9]: df.head(2)
In [10]: df.tail(2)
aaarticlea/png;base64,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" alt="" />

wc命令

格式:wc -【参数】file

wc -l file # 显示文件行数

wc -w file #打印单词数

练习:

编写一个shell脚本把stud_info.csv导入表(表各自定义);把stud_info.csv导入pandas;验证导入数据的正确性。

 #!/bin/bash
#文件名称:import_mysql
#文件功能:将stud_info.csv导入stud_info表中
#创建作者:邬家栋
#创建时间:-- rows_file=`cat /tmp/stud_info.csv|wc -l` #注意这里是反引号
echo "stud_info.csv一共有${rows_file}行" #要先连接数据库
mysql -u feigu_mysql -p testdb << EOF
drop table if exists wu_stud_info;
create table wu_stud_info(
stud_code varchar() not null,
stud_name varchar() not null,
stud_gend varchar() not null default "M",
birthday date null,
log_date date null,
orig_addr varchar() null,
lev_date date null,
colledge_code varchar() null,
colledge_name varchar() null,
state varchar() null,
primary key(stud_code)
); load data infile '/tmp/stud_info.csv' into table wu_stud_info fields terminated by ',' ignore lines; EOF if [ $? -eq ] ; then
echo "操作成功"
else
echo "操作失败" fi 注释:在写默认值的时候,默认值需要用引号引起来。
注意:if语句一定不要忘记写fi结尾。if后面中括号需留空格
 #!/bin/bash
#文件名称:pandas_import.sh
#文件功能:将stud_info.csv 导入到padans中
#创建时间:--
#创建者:邬家栋 ipython << EOF import numpy as np
import pandas as pd
from pandas import DataFrame
inputfile1 = '/tmp/stud_info.csv'
data= pd.read_csv(inputfile1)
df=DataFrame(data) EOF if [ $? -eq ] ;then
echo "操作成功"
else
echo "操作失败"
fi

mysql基础(4)-数据导入的更多相关文章

  1. sqoop用法之mysql与hive数据导入导出

    目录 一. Sqoop介绍 二. Mysql 数据导入到 Hive 三. Hive数据导入到Mysql 四. mysql数据增量导入hive 1. 基于递增列Append导入 1). 创建hive表 ...

  2. MySQL Shell import_table数据导入

    目录 1. import_table介绍 2. Load Data 与 import table功能示例 2.1 用Load Data方式导入数据 2.2 用import_table方式导入数据 3. ...

  3. docker中mysql数据库的数据导入和导出

    导出数据 查看下 mysql 运行名称 docker ps 结果:  执行导出(备份)数据库命令: 由第一步的结果可知,我们的 mysql 运行在一个叫 mysql_server 的 docker ...

  4. mysql恢复和数据导入的问题(ERROR 2006 (HY000) at line 1016: MySQL server has gone away)

    今天在上班过程中需要将一个1.3G的数据库sql文件导入到mysql数据库中去,在执行过程遇到了一些问题,执行到一半时报错,错误如下 ERROR 2006 (HY000) at line 1016: ...

  5. MySQL 5.6数据导入报 GTID 相关错误

    从阿里云备份数据后还原到本地,用命令行 mysql -uroot -p --default-character-set=<character> -f <dbname> < ...

  6. mysql5.x升级到mysql5.7后导入之前数据库date出错的快速解决方法【mysql低版本数据导入到高版本出错的解决方法】

    mysql5.x升级至mysql5.7后导入之前数据库date出错,这是由于MySQL的sql_mode的影响,解决方法如下所示: [具体参考:mysql的sql_mode详解]修改mysql5.7的 ...

  7. 利用python将mysql中的数据导入excel

    Python对Excel的读写主要有xlrd.xlwt.xlutils.openpyxl.xlsxwriter几种. 如下分别利用xlwt和openpyxl将mysql数据库中查询的数据保存到exce ...

  8. mysql的csv数据导入与导出

    # 需要station_realtime存在 load data infile 'd:/xxxx/station_realtime2013_01.csv' into table `station_re ...

  9. Mysql学习_02_mysql数据导入导出

    二.参考资料 1.MySQL 数据导出

  10. Mysql提升大数据导入速度的绝妙方法

    一.对于Myisam类型的表,可以通过以下方式快速的导入大量的数据.      ALTER TABLE tblname DISABLE KEYS;     loading the data     A ...

随机推荐

  1. EasyGBS国标流媒体视频平台接入海康、大华、宇视的摄像机、硬盘录像机NVR、国标下级平台的方案

    在上一篇<EasyNVR和EasyDSS云平台联手都不能解决的事情,只有国标GB28181能解决了>我们大致介绍了国标GB/T28181的使用场景,而且初步介绍了EasyGBS国标视频平台 ...

  2. Jquery来对form表单提交(mvc方案)

    来自:http://www.cnblogs.com/lmfeng/archive/2011/06/18/2084325.html 我先说明一下,这是asp.net mvc 里面的用法, Jquery来 ...

  3. delphi 中配置文件的使用(*.ini)和TIniFile 用法

    一.配置文件 .ini 文件是基于文本类型的格式文件,用于存储程序初始化和配置数据. .ini文件是有段(Sections)和键(key)组成的,每个文件可以有 n个段(每个段有方括号括起来),每个段 ...

  4. undefined let 作用域

    const o = {uid:123,pid:'wwww'}const wxPayNotifyUrlBizInfo = (o) => { // TODO json let s = '' for ...

  5. do not use numbers as enumeration values

    w 字段类型设置错误 有限元的判断,勿用枚举行. MySQL :: MySQL 5.7 Reference Manual :: 12.4.4 The ENUM Typehttps://dev.mysq ...

  6. 洛谷 P4768 [NOI2018]归程

    洛谷 361行代码的由来 数据分治大发好啊- NOI的签到题,可怜我在家打了一下午才搞了80分. 正解应该是kruskal重构树或排序+可持久化并查集. 我就分点来讲暴力80分做法吧(毕竟正解我也没太 ...

  7. CentOS 7.4 下安装Epel源和Nginx

    EPEL (Extra Packages for Enterprise Linux)是基于Fedora的一个项目,为“红帽系”的操作系统提供额外的软件包,适用于RHEL.CentOS和Scientif ...

  8. 《Python 机器学习》笔记(四)

    数据预处理--构建好的训练数据集 机器学习算法最终学习结果的优劣取决于两个主要因素:数据的质量和数据中蕴含的有用信息的数量. 缺失数据的处理 在实际应用过程中,样本由于各种原因缺少一个或多个值得情况并 ...

  9. 20170520 BADI增强学习

    一.要求:Tcode:FF_5 导入数据运行时,产生财务凭证之前修改某些字段值.Exmp:FEBRE-VWEZWBKPF-XBLNRFEBEP-CHECTBSEG-ZUONR there is a b ...

  10. MySQL安装后的设定及其变量(参数)的设置

    1.为所有root用户设定密码:mysql> SET PASSWORDmysql> update mysql.user SET password=PASSWORD("your_p ...