请上传宽度大于 1200px,高度大于 164px 的封面图片
    调整图片尺寸与位置
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  • 两条折线图,分别取自不同的数据集,以形成对比,分类轴是一样的,X轴Y轴都是一样的。怎么实现呢?效果如图:
  • 如何把值轴中的刻度改成间隔为5呢?是修改“坐标轴-->值轴-->对数刻度:底数"?我修改了没有用。我需要让图中的值轴显示成:60,65,70,75,80,85……这样子
  • 插入了一张组合图,主次坐标轴用的都是柱形图,怎么在柱子上显示对应的值呢?单纯柱形图的话是有一个"标签"样式的。组合图中找到的"标签"样式只能设置坐标轴Y轴的值。。。
  • 1、根据"部署集成-->嵌入式部署-->2.2部分复制"的方式将数据决策系统部署到已有的系统中, 2、检测部署:http:/ip:服务器端口号/项目所在目录/ReportServer,能成功进入页面, 3、但是之前写好的文件和功能并没有展示出来。只出现了管理系统功能;如图: 4、如何把报表和图表再集成到只有"管理系统"的数据决策系统中呢?
  • 在做数据钻取的时候,怎么让钻取的报表也以“数据分析”的形式进行预览和查看呢?
  • 给表中的一行设置了背景色,请问如何取消,回到一开始的状态。
  • 新建表单制作了一张图表,居然没有打印和输出等功能,是本来就木有么?还是要通过调用打开打印和输出等功能?
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RRHzMKzCLbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDZkGwCyIdsAkA3ZBoBsLJzt+jOPG2csGPoeAHC9JbPdONHg0Cl/O2c8BACu9LCd5GVRn6u4nmMf9jvdBoCbPSjb55n1Md61zj8BgGssn+3WaYI7nTbdBoA7PGon+Wm6PTXbfv/+fdnw7t27zwC4w4cPHx70xM4aLJjtzlT6sC/2hytf2y5Lc3EAGLXwkeT1oeL112VxxZHksg0ACY9633bjTdpXvG9btgEgYV2fkibbAJAg2wCQDdkGgGzINgBkQ7YBIBuyDQDZkG0AyIZsA0A2ZBsAsiHbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDZkGwCyIdsAkA3ZBoBsyDYAZEO2ASAbsg0A2ZBtAMiGbANANmQbALIh2wCQDdkGtuxffvb3s1ii7yeyIdvAloX3WLZZlmwDWxbeY9lmWQtn+7DfvR3t9of+N5vfHSLbwLLCeyzbLGvRbJdF3eXDflcnuizeink5lm1gWeE9lm2WtWS2y6I5ma7/Nb/asg0sLLzHss2yHvba9mG/O8a6sYt8st6yDSwrvMeyzbIelO062k2NfegjZBtYVniPZZtlPSLbzde129q70auqev/+fdn2GcBywns8c1lwyB8+fHjAEztrsXy2Wy9ltws+OAdvXddsG1hUeI/NtlnWwtnuH352+c5hv5t6dVu2gWWF91i2WdaC2W4ce9Y6BK0s5r1pu5JtYGnhPZZtluVT0oAtC++xbLMs2Qa2LLzHss2yZBvYsvAeyzbLkm1gy8J7LNssS7aBLQvvsWyzLNkGtiy8x7LNsmQb2LLwHss2y5JtYMvCeyzbLEu2gS0L77FssyzZBrYsvMeyzbJkG9iy8B7LNsuSbWDLwnss2yxLtoEtC++xbLMs2Qa2LLzHss2yZBvYsvAeyzbLkm1gy8J7LNssS7aBLQvvsWyzLNkGtiy8x7LNsmQb2LLwHss2y5JtYMvCeyzbLEu2gS0L77FssyzZBrYsvMeyzbJkG9iy8B7LNsuSbWDLwnss2yxLtoEtC++xbLMs2Qa2LLzHss2yZBvYsvAeyzbLkm1gy8J7LNssS7aBLQvvsWyzLNkGtiy8x7LNshbO9mG/ezva7Q+n75VF71tjZBtYVniPZZtlLZrtsqjTfNjvdvvDseNFef7W+cvRG5BtYFHhPZZtlrVktsuiOZ8ui93+cK730WG/S3dbtoFlhfd4ndn+td/5Ys7Su97lOb0s3oqyOux3EztSL/tgh57+y2L4+4x72Gvbx0S3S979Z49sA8sK7/Gmst2YiR2zffqqsZ/1raPzpD9wiQ4Vn/CgbJ/n1Z1O96bb79+/L9s+A1hOeI9nLgsO+cOHD5PP0bdlu/kUPjULazV+TFnMOeqJlkdku/X/Y2bbQKDwHm9otl0Wb0U5Nl3e7Q+XA5BHnC5zmaUfv6qn6zNCzwOyfdkmVXcjeG0beLLwHm8m24f9rrkHuyx2+3LkOf2w37297Ypit9uXAyUui7eibCT+eIHGvnZSFs52q9md7ziSHHi68B5vJNunSXb9HH7Y74qyMxXrvNu3+YaizuvW9RXLYrc/lMXx4DbVnmXBbPd3ndT7PwaPTBgg28Cywnu8kWyXRVE25mXHyA7tQR3aid49xumyS73e6X46Kt2Ee5pPSQO2LLzHG8l2VXV2nu72h8YLn52AN/7ZmUX3puD1zPx0GLMjyafINrBl4T3eYLbrVzzHst2I7+Ul7OEc6/TVZBvYsvAeby7b7c++rI8Kr6fUg5+gcr7k9Nu27SafItvAloX3eGPZ3rf2eV/m0rv94fTPVrKnJttm29eTbWDLwnu8oWyzCrINbFl4j2WbZck2sGXhPV5ntsmXbANbFt5j2WZZsg1sWXiPZZtlyTawZeE9lm2WJdvAloX3eJ3Z/vj3f33O0rve5TPPLm/iTr/R+vJO7aE3eg2+yTt1I97nLdvApoX3eFPZbp2WuXECzvM3B/Laqer0560MVbz1CanNt3q/4glIZBvYsvAebynbzY8wbXwu2ogZSS2LebNls+0G2Qa2LLzHG8p2WVzO2DVYz8Y5tFOXuczS69NEtk/12WO23SDbwJaF93gz2T7sd8092GWx25cDJ+6sL7orit1uXw50tSzeirKR+OMFGvvah2/QbPtItuFef/Obv5nFEn0/xQjv8UayfTktdv3vouycrrMucXvu3Ghu42ye54n2bn8oi+PBbeMBnjcNfxGyDfcK77FsJ4T3eCPZLouibOydPubyMDDbHpoYt8p6nIqfdqnXO91PR6VfZt6d0DfX5OVC3SbbcK/wHst2QniPN5Ltqmq+qHya5I6db7v5z858uDcFr2fmRVlVwycEmzj6/NUqLttwr/Aey3ZCeI83mO36jNtj2W7Ed+rMndeeuLN3+debfMs23Cu8x7KdEN7jzWW7jnYz1o14Dn6CyvmS02/bnjgurfvTof30GyfbcK/wHst2QniPN5btfWuf92UuvdsfTv9sVXRqsj1rtn26kcbvbdT/1ebasg33C++xbCeE93hD2WYVZBvuFd5j2U4I77FssyzZhnuF91i2E8J7vM5sky/ZhnuF91i2E8J7LNssS7bhXuE9lu2E8B7LNsuSbbhXeI9lOyG8x7LNsmQb7hXeY9lOCO/xOrP915/8xpyld73LZ55d3sSdfgvW5b1aQ2/0GnyT98Stvdr7tLtkG+4V3mPZTgjv8aay3fik0tYJOM/fHPg0lU7Upz9vJVVl1a6Wz3ZZJDfTxBvjZZschfdYthPCe7ylbDc/kmz6Q0VnnJ2rLK76vJRXPN9X38LZPhwO/Y05/zNnZZschfdYthPCe7yhbJfF5Yxdg59J2jiHduoyl1n6+eydnVN99n7tlJeK+QN2knezfcUnxcs2OQrvsWwnhPd4M9k+7HfNPdhlsduXIx8Ifvz08KLY7fblQInL4q0oGzGuT9Y5+Sp5Ny4vleuzx2d74Azp41eVbTIU3mPZTgjv8UayfTktdv3vouycx6MucXvuPBCB+oplsdsfyuJ4cFs6wgPn/nrN17mfMNtu/MBr22xReI9lOyG8xxvJdlkUZaOTx8gOnX5raCd6fyp33qVe73Q/HZV+mXn3Q9/ux+u+zv3MbA/86P3792XbZ5Cb8B7PXKLvpxjhPZ65LDjkDx8+TD5P3/7adlVVdTPHzrfd/Gcnr70peD0zL8oqMYM+HA7Hls/co75hD852e4NNnhjVbJschffYbDshvMcbmW1X1aWp9duwxrLdiO/UmTuv3tN96v3LRvsJs+3W/55NbR7ZJkfhPZbthPAeby7bjafyS6wbz/uDn6ByvuT027YTQT79L0Dzhl6x3s85knzuIfqyTY7CeyzbCeE93li2961dqJe59G5/OP2zleypyfac2XZ9GwMXbLwe/jJ8ShrcK7zHsp0Q3uMNZZtVkG24V3iPZTshvMeyzbJkG+4V3mPZTgjv8TqzTb5kG+4V3mPZTgjvsWyzLNmGe4X3WLYTwnss2yxLtuFe4T2W7YTwHss2y5JtuFd4j2U7IbzH68z2nY+Z8Q8pu7wDeODEXf13cA2+yZsk2YZ7hfdYthPCe7ydbCc+KqV9hpGB33fY79665xWZui2GyTbcK7zHsp0Q3uNNZXtwin3+xJTW9Hroc8gHr/pqH5ZyP9mGe4X3WLYTwnu8qWxPzZAvZwQZOzVF42PR6q/qXe6ve1ava8h2Hj7+/V/PYom+n2KE91i2E8J7vKlsJ2fbVZ3r1q7y/tXK4q0oG3NzJ/W6imznIbzHsp0Q3mPZTgjv8aayPTHbPk+yy2JXFEMXPne57npZ7PaHsjieoUS1Z5HtPIT3WLYTwnss2wnhPd5Utk9h7Zww6nxOsPMF2qcH6fa4PvvH8Sjy0/8MnE4tZsI9TbbzEN5j2U4I77FsJ4T3eIvZboT7fNKvw+FwukzneLROts//qqfu9ava58PaHEk+QbbzEN5j2U4I77FsJ4T3eJvZrrvbi+zxNevEbLt3cZ2+jmznIbzHsp0Q3mPZTgjv8fayfXnXVu/82udPT2keXtbK9vTbtu0mn7LZbP/a73yRxTJzOOE9lu2E8B7LdkJ4jzeT7bq4ndnx+ZDwYt+dVp9/kgqx2fbVZFu2Zfte4T2W7YTwHm8m26yEbMu2bN8rvMeeghPCeyzbLEu2ZVu27xXeY0/BCeE9Xme2yZdsy7Zs3yu8x7KdEN5j2WZZsi3bsn2v8B7LdkJ4j2WbZcm2bMv2vcJ7LNsJ4T2WbZYl27IdkO2//uQ3slhmDie8x7KdEN7jdWb77/3hF3OWsauPn/bj8rmnrfN4Dr51rLq80XtC6u3eL/c+b9mWbdmW7S0L7/F2sj3jxJ3tc391rtv+UNNRQ9dvfWRL863er3gCEtmWbdmW7S0L7/Gmsp08cWdret285HhbLx+4lma23SDbsi3bsr1l4T3eVLanZsiXM4K0Ps+0WdbLXLn+qt7lPtp3s+0G2ZZt2ZbtLQvv8aaynZxtV3WuW7vK+1cri7eibMzN6w84Hy2w2XaDbMu2bMv2loX3eFPZnphtnyfZZbEriqELnxNbd70sdvtDWRzPtj0e4HnT8BexdLbLovc/P/X/U03fubI9JrzHsp0Q3mPZTgjv8aayXZ9ku3tG7beibJ0iLHHizsN+d8zB8SjyywlA6x80XyYfOvj85ULdtnC2D4dD+z49b872l2Nke0x4j2U7IbzHsp0Q3uMtZrvRzvO5Ow+Hw+ky3Tla7zTd7SPK61e1z4e19TMxcfT5q1X8ATvJx49FGHtrwOWqsj0ivMeynRDeY9lOCO/xNrNdt7T3nH6cKCdm272LX3Xizt7lX2/y/eBsd+7QqftXtseE91i2E8J7LNsJ4T3eXrYv79o6T7Vr509PaR5e1sr29Nu2J45L6/50cja4Pc/N9tQdLNtjwnss2wnhPZbthPAebybbdXE7z+Ln16GLfXdaff5Jaro2Z7Z9up3+VP8Vd5GHz7bfv39ftn22kPAez1xmDie8xzOXmcMJ7/HMZeZwwns8c5k5nI0J7/HMZcEhf/jwYfJ5+pbZNuvgtW2zbbNts+0tC+/xZmbbrMSDs93cA+JIctk+C++xbCfMfEIPX2YOJ7zH68w2+Xp4tr1vW7b7wnss2wnhPZZtSPApabIt27LdEt5j2YYE2ZZt2ZbtlvAeyzYkyLZsy7Zst4T3WLaf4M61Gj/tx+VV0tZ5PMc/qXT4BNtjZhwjtXmyLduyLdst4T2W7Se4Za1mnLhz9P1Ch/3urf2hpqNSVVbtSrbDl5nDCe+xbCeE91i2E8J7vKlsJ0/c2ZpeNy85/vGmlw9cm+UVz/fVJ9uyLduy3RLeY9l+ghuzPTVDvpwRZOzjOxpvCq6/qne5D2d5YG9710vFXLZlW7ZluyW8x7L9BDdmOznbrupct3aV969WFm9F2Yhx/QHn6fr2buj1ziJSVZVshy8zhxPeY9lOCO+xbCeE93hT2Z6YbZ87Wha7ohi68DmzddfLYrc/lMXxbNsTp5rqn/vrNV/nlm3Zlm3ZbgnvsWw/wY3Zrk+y3T1J1FtRtk4RljhxZ30ir+NR5JcTgDbO8HWZijd2v7er/rqvc8u2bMu2bLeE91i2n+C+bDfCfT535+FwOF2m+1Jz79QU7SPK61e1z4e1Dc+gD4fDseUz96hvmGzLtmzLdkt4j2X7Ce7Ndt3dXmSPcU3MtnsXv25P9+n3vmy0ZTt8mTmc8B7LdkJ4j2U7IbzH28v25V1b56l27fzpKc3JcCvb02/bTgT5tOu8KKuXrrdsy7Zsy3ZLeI9l+wluWKu6uJ3Z8fl16GLfP9J7+u1ZM2bb9QvdAxdsvB7+MmRbtmVbtlvCeyzbT7DOtWIO2ZZt2ZbtlvAey/YTrHOtmEO2ZVu2ZbslvMeyDQmyLduyLdst4T2WbUiQbdmWbdluCe+xbEOCbMu2bMt2S3iPZRsSZFu2ZVu2W8J7LNuQINuyLduy3clk3tkAAAX1SURBVBLeY9mGBNmWbdmW7ZbwHss2JMi2bMu2bLeE91i2IUG2ZVu2ZbslvMeyDQmyLduyLdst4T2WbUiQbdmWbdluCe+xbEOCbMu2bMt2S3iPZRsSZFu2ZVu2W8J7LNuQINuyLduy3RLeY9mGhGdkuz65+uTZzGV7THiPZTshvMeynRDeY9lmWc/Idlm8FfNyLNtjwnss2wnhPZbthPAeyzbLekK251dbtkeF91i2E8J7LNsJ4T2WbZb1+Gw3dpFP1lu2x4T3WLYTwnss2wnhPZZtlvXMQ9LKwmvbsl1VlWzLtmzLNrd67pHkZdHp9vv378u2zxYS3uOZy8zhhPd45jJzOOE9nrnMHE54j2cuM4cT3uOZy8zhhPd45jJzOHN8+PDhqU/sPNeDs33Y7xqhPux36f3kZttjwntstp0Q3mOz7YTwHptts6yHz7YvB6Qd9rupV7dle0x4j2U7IbzHsp0Q3mPZZlnPOZJ81pu2K9keF95j2U4I77FsJ4T3WLZZlk9Jk23Zlu2W8B7LNiTItmzLtmy3hPdYtiFBtmVbtmW7JbzHsg0Jsi3bsi3bLeE9lm1IkG3Zlm3ZbgnvsWxDgmzLtmzLdkt4j2UbEmRbtmVbtlvCeyzbkCDbsi3bst0S3mPZhgTZlm3Zlu2W8B7LNiTItmzLtmy3hPdYtiFBtmVbtmW7JbzHsg0Jsi3bsi3bLeE9lm1IkG3Zlm3ZbgnvsWxDgmzLtmzLdkt4j2UbEmRbtmVbtlvCeyzbkCDbsi3bst0S3mPZhgTZlm3Zlu2W8B7LNiTItmzLtmy3hPdYtiFBtmVbtmW7JbzHsg0Jsi3bsi3bLeE9lm1IkG3Zlm3ZbgnvsWxDgmzLtmzLdkt4j2UbEmRbtmVbtlvCeyzbkCDbsi3bst0S3mPZhgTZlm3Zlu2W8B7LNiTItmzLtmy3hPdYtiFBtmVbtmW7JbzHsg0Jsi3bsi3bLeE9lm1IkG3Zlm3ZbgnvsWxDwhOyXRZvR7v9Yeqisj0ivMeynRDeY9lOCO+xbLOsR2f7sN+9FWX3yzGyPSa8x7KdEN5j2U4I77Fss6wHZ/uw3zXm2If9Lt1t2R4T3mPZTgjvsWwnhPdYtlnWg7NdFq09451/9i8u2yPCeyzbCeE9lu2E8B7LNst6branptsLZvt3f/CXWSwzh/Pv/+x3s1hmDudv/uTbWSwzh/Or3/u9LJaZw/lXP/7LLJaZw/mvH/51FsvM4cC6Ztvv3r0rAbjDu3fvHvvETqh1vbYNwJ3K5XZbskIPfwNYWVxxJDkAd5LtbVvX+7YBuJNsb9u6PiUNgDvJ9rbJNsCmvH//PnoVeCDZBoBsyDYAZEO2ASAbss0r+rtf/e3f/epvf/SnX8xf/vO7/zR/+fH//j+JJXr0QMZkmxdyrHW9RGVbxYGbyTavotNs2QZyJNu8hH6zZRvIkWyzfYPNlm0gR7LNxo01W7aBHMk2GyfbwJbINluWaLZsAzmSbbZMtoGNkW22TLaBjZFttky2gY2RbbZMtoGNkW22TLaBjZFtNk62gS2RbTZOtoEtkW0AyIZsA0A2ZBsAsiHbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDZkGwCyIdsAkA3ZBoBsyDYAZEO2ASAbsg0A2ZBtAMiGbANANmQbALIh2wCQDdkGgGzINgBkQ7YBIBuyDQDZkG0AyIZsA0A2ZBsAsiHbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDZkGwCyIdsAkA3ZBoBsyDYAZEO2ASAbsg0A2ZBtAMiGbANANmQbALIh2wCQDdkGgGzINgBkQ7YBIBuyDQDZkG0AyIZsA0A2ZBsAsiHbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDZkGwCyIdsAkA3ZBoBsyDYAZEO2ASAbsg0A2ZBtAMiGbANANmQbALIh2wCQDdkGgGzINgBkQ7YBIBuyDQDZkG0AyIZsA0A2ZBsAsiHbAJAN2QaAbMg2AGRDtgEgG7INANmQbQDIhmwDQDb+P89OZeCaGC51AAAAAElFTkSuQmCC 如上,我想把优秀率的3个柱形图放在一起进行对比(图中的前3个,现在是分开的),良好率的3个柱形图放在一起对比,优秀率与良好率是分开的
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 设置的单元格图表在网页中只占到网页的二分之一不到,怎么修改图表的大小使之自适应浏览器的大小呢?求高手指点。。。
  • 数据决策系统中的例子是怎么做出来的?有每个例子的视频教程么?特别是系统中有一个“图表热点链接”的例子,现在正需要做一个类似的图表,怎么进行学习呢?

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