Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
Hi guys, everything all right?
I have a large dataset with base64 images, and they are displaying in my table like this:
If you notice, the line size is too much big, my dataset images are all in 597x186 proportion, is there a way do make them smaller to reduce my line size? I see that theres much blank spaces in my table (when i decode and look directly in a file, i see that the blank space generated by application that encode the B64 image is alright as you can see below, but in PowerBI, theres a huge blank space)
Is there a way to better formatting that?
For tests, that a base64 example:
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlUAAAC6CAYAAACHi7jMAAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAACVaADAAQAAAABAAAAugAAAACi/hQ+AAAhfElEQVR4Ae2deew+V1WH6cYiCmU3FKRQNESNJhiMGEUSRdyiEfeFRBOiMVKjRnAJMSqYQIzRGCL+QSLELY2RGoM7WhCQRBZBUEqhrUAB0ba0hS4sLudjv5/2dDoz7519e25yf3fmzrnnnvPc+c49vzvLe5/7kCCwLQL/E+b+b2SVpPUQ0Jg4r8cqLIEABCAwI4FzZ+yLriAwBoFzxlCCDghAAAIQgMDYBAiqxiaKvrkIEFzNRZp+IAABCECgiABBVREmhFZCIN/y060mEgQgAAEIQGA1BAiqVjMUGFJAgNWpAkiIQAACEIDAMgQIqpbhTq8QgAAEIAABCOyMwPk780fuvDvy42r8+kylTrePqnUSUf2ntHGWLPdpV0R5ZeRvSftsTk9A40CCAAQgAAEIrJbAXm6n3ByEH7QA5Y8v1O8Cri7apZ6lqp6rCrJYaV10WO7ReQ56q2N1D0F2IAABCOyVwNYnJX+zaImASufE50TWZPIW7ZAmI8AkPRlaFEMAAhCAAATuJKCAJudbeoB5bdJxdWz/YuSLI59KV4VA7lu3BEnjE8iMpd37+U3A8XtFY1cCHheVJAhAAAIQ2CABX8j7BFN292Gx8bzI74psfSpfFfnbIp9Kt4WA2z37lDDHOxHwSqT4Oogya+93UojwZAQ8LipJEIAABCCwQQK+kA8JqrLbXx87fxDZelV+IrIeXL+mJVv+10KGNB4Bc1Xp5DqCKhNZR+lxyWO1DsuwAgIQgAAEigj4Qn5rkXS50KNC9PmR9Sah+ygpX1TeBZInCChoMvOXJVnXEVQlKCvY9LioJEEAAhA4JIGtPwDsC/gdMXoPmGgEnxN6v+yE7gvj+EMjXxpZz1qRhhG4MZo/5EyFxji/UOExr9YP65HWQwl4XKRn69eVoSxoDwEIQGCTBHQhV779zPqLz/a1iqE380jbJOBxzRO1PfExVqpMZB2lx6VuzNZhIVZAAAIQgEArAV/IP3kmpQ90uk7lk1tbc3CNBPJtv/+uMdDjS1BVA2fBKo+LShIEIAABCGyQgC/kDqq+InzIk7KO+9gG3TukyR7TpsnZxwmq1nV6eFyaxm1d1mINBCAAAQjci4Av5PlnZSRUDay0/wX3aj1+xXND5VPHV3sYjXncfrvBa485QVUDoIWqPS4EVQsNAN1CAAIQGErAF/L8u3zW+brY8HGXD/fBCcqvPuvvHybQfQSVutXncWoLmEpkjsBrbT56XFSSIAABCEBggwR8Ia/7YWS5c1Fky7jUqtZ5OjhyelboUx/Xjaz3KOo8PirbkuXaAq+29hybhsCHQq3G5g3TqEcrBCAAgfUTOH/9Jg6yUBd6fe7gY5H9mvcFsa2VrQdH1g8ij5Uecabo/mMpPJCeHEj9a6HfuU1hE8QmJKD/wOg/K4zLhJBRDQEIrJtA/v7Pui1tt84BU53UzVEpP1+TDkpeX2Ef8+1AB6guU3dsthDIK06akL+4RTYf8mc0ch3byxLQLdw8nstaQ+8QgAAEINCJgCZh5bpX7+sUKYhyG5djvR34yjPd+hApqYxAfo5K43Eq6datx+2ULMchAAEIQAACEOhAwBNsaVBl1frftNuq1P6QtwO/60yHdGlljFRGII9BSYs8biXyyEAAAhCAAAQgUEDgtpDxpFz9pEJB8/u8PrW3nj5vB+aASs9qPbakc2TuGjuxf0chD4KqQlCIQQACEIAABEoJ3BCCDoRUfmtpw4rc0LcDfyTZoYDq4op+dusJ5LFToFSacrvSNshBAAIQgAAEINBAQA+Z5xWLVzTIlVbrLcCsTxO39k/9duCPh4wneclfHJl0mkBmre0uKfPu0g5ZCEAAAhCAAAQaCOjVbU3I391wvE/130cjT9oum94OrAZUT+rT4QHbaDXPbFV2TW7bNRjr2g/yEIAABCAAgUMR0IrV2Knu7cDLKp38c+znyf0LK8fZbSZgbn0CKml1+64vJjRbxBEIQAACEIAABCYloJUQT+BeFXlT1OV6HSegKh8G81TZ97MT1jHmR1vLPUASAhCAAAQgAIFeBHIAlbc1sevbVk/spfWYjRwMqey7ysQ3qo557uA1BCAAAQjsgIAm/xwMaFvPBPV903AHSHq5kDl61a+PohzY9mlPGwhAAAIQgAAEFiDwzdFnnsQVUP3xAnbsocscmA7xZyw9Q2ygLQQgAAEIQAAChQQ+EnJ58vb2kBWWwq53K2aGWuUbkqyHsRhCkbYQgAAEIACBCQlcH7o9YTeVTOT9BiDf+uun4e5WHpu+z2TdrYktCEAAAhCAAARGI3BjaPIkXS0VQL3xrCdt+/hZFUUHAmanckj6RDS2riF6aAsBCEAAAhCAwAgE9Bq+J+a60oFU7mrMlZas9yjb5jx0pY/g9ihnDH5CAAIQgMAqCZwbVt0U2RN7Xfn2E5Y/MrW//IQsh+9NwMw/c+9DnWoIqjrhQhgCEIAABCAwDgEFU7dF9oReLa/s2I3bD11t6djt5sXHDIQYg82fDjgAAQhAAAJbIqBg6vbInoBz+d4BjmQ9A9QcrumY3KyLh9QPdxrhMAQgAAEIzEmgKZjSSsn3jGDImCsuI5izGRUOhIau8N0aHlvXZpzHUAhAAAIQgMCWCDQFU5qAv3dER3hYvR9MB0JDv09FUNuPP60gAAEIQAACJwnMFUzZkM+LDQcIf+pKylYCYwZCZq/yCMn+HsFXfIQABCAAgYUIKJhqegD9+ya2yRPd0FtZE5u5GvXmNUYgZF1HYW9/h74xuZqTAUMgAAEIQGA9BNpWpr5/JjM90Y0RJMxk8qLdmNcYgZB1HeUh9aP5u+iJSucQgAAEjkTgw+GsJ5lczhVMmfWYt7Osc8+lx2roassRH1I3u6MEkXv+O8A3CEAAAqsi4AnG5Q8uZJ2CA9uwkAmb6XbMB/uPGMz6PBsakG7mhMFQCEAAAhCYh8CXRzeaXMb4NMIQi58UjT3Z/dEQRQdoO2YgZOZj3EbcAvockOpnlUgQgAAEIACBXRI42gTfdxDNSeWQlAOMDw1RtKG2OSAlqNrQwGEqBCAAAQh0IzBWsNCt1+1Jm9PQ1SXrGRqcbYlg9pmgaksjh60QgAAEgoDerCOVETjS5F5G5N5SeUXpWfc+3KvmqNyP6nevk4RGEIAABCCwLQI8rH56vPLtq9PSzRJj6WnuYZ1H8krVLes08VBW/Ud4m8dE2zo3rzgUBZyFAAQgMAGBh4dOX2B/egL9e1BpPiqHJOsZegtxiA1zt83PkMl/gqq5R+Du/vJ/oHwu1pV3t2ALAhCAQBDg9l/5aXB9En1g2mbz3gQ0AfVNCi6cPuKNA5TnHMDHLbioc/e8QkMl+4FCWcQgAIEDEDj/AD7u3cWm1ZxPheP3X8j5HBh1NSEH+hd1bbxheYKq5Qev+rfUNCaS87HHxrb283m7vCdYAAEILEKAC8Ei2EftVBf3uny/qM+3LBRkTZlyIHXBCB0NWe0aoXtUHJCAAyWdy96uw6Dr5ivSAclyviYgbELgqAQIqo4z8gp0HGTpf9YvHtn1tkmotKu8UsC5WUoNuTEI3JGUlKzg/3DIV8/5TycdbEIAAgckwMS1n0G/KlzRRT7na2K/7n/QkvnZs2M5kImq3qk6wfRRZB11NvfRt+U2MJh39LSy2yf5nFVbBWMv6KOENhCAwD4IEFTtYxybvLgkDmiMdeFX9g9Ux+ZdSfVjTuB9deXbh0d6QF0D8Zd3jQYbSxPQm39dUw6sXti1MfIQgMB+CBBU7WcsS56Z0oPfDrKurbjeNxiqqOn9KYB8Lh7pAXXxe0YVIvubI6D/sDiN9bdkfZQQgAAEdklAF0vl61bknW16Z0+bPnnmk/X0UXNF0tGnvdq4/7FuR/a1Y4l28tn+u7x5CUMO3Ke5D3kuKo/jED0HHgZchwAEjkTAF941Tfy2acgkPDSwyh9L7HM+5MmoT/utt8n+jzGeW+exhP3mPjQYsh6VJAhA4GAE8i2Xg7k+yN38DMUgRSM2ftAAXXpIN08mXSeEoefRGnkOwNm56dH97wxsxQ0uX7FtmAYBCExMoOTV4YlN2JR6BRtrmwB1K/IxZxTfHOVTzra7FveNBnouy9+Y0urJ0GCpxIa3JqH8sHqqPszmmOfXm4Kax7IK8NTD2DqPLq02Yh8CEIAABCAwJgHdYtPE13UlZ0wb6nTZpjHsyrei6vqqqxvSf5/+6mzYcp35ZRZ9b+dmHdbbt9QPCh8lmZFuhQ9Jr4rG1jVED20hAIENEphjJWKDWBpNfnA68r60vfRmfnBeqwxDUv4h3x8YoqiwrVf+NBEdPQ1ZqXMwZZ5jsHxUKJFeEgQgAAEIQGASAv5faN1k87jo0bfiJum8RantGiM4sa46H+tM6CpvHbr157anbkm5zd7KyxID+WYepStVDqbcTmXpuKm/uvTBqMz6xtBZ18+a6uwvK1VrGhVsgQAEdk/AF9/qxKVVBh/T9hNnJpEnwvyTG33MsB8qS5Llq0xOtc0BwSnZvR5XMGl+8tHbp4Kqr0yybtOVv/prS3l83MdebwnaP4KqtjOCYxCAAARGJuCLr8qcclBlmblXX9yvyo9l4zpuXx3y1lUyUVtWDLokt1N51JQDFzEwk1NBVT7fSsZoCN9so+ybur8htvZta+4EVX0J0g4CEJjl7a69YW4KAM4LR6s/r6I6yd8e+RGRp075eZoLo7O+gdUl0dZ+SuffFRr+8UI5ifHWXwdYNaL5eci8XSM6uEr683N7Oid8fgxWjgIIQAACEDgugfy/9joKD4nKfEtHk4/zy+saTFDn/lT2DaxkVtbTZOYVSa5Jpq7+FMe6NnusqzL2/qmVKsupnDPlfufue0o/7RcrVVNSRjcEIACBCoEuwUC+ReOLttr3/ZZUxZTWXfensm9gpQnGemR3XcoBZN3xprpTepva7a2+ysH7N51w1HJN43Ki+aDD+W9AduwhmefQoErjZl174IIPEIAABCYlkCeUko4eH0K5jS+4qtMHN6dM7ktl38Aq66izNftWd7yujrf+7qZivuKo5P22oOonk9wv/H+r+f/J4y6bt57MfWhQlblsnQn2QwACEJicQN+Lpp5LyW19EVfdlG8Kuh+VV/ekYx11t6SyT6Xq+7Qp1b01ObMVEyXvtwVVeQX0zlbL/JvHUXZvOZn7bQOdsJ6t8xiIgeYQgAAEygjkiaSsxT2lnhy7WYcvwp5U7yk9zp77UHlRD5VuX2dj9qVUdZu+Uh1D5N4SjTV56sF6BYpaxfto5L+NPHcyCwVKSt5vC6r6ML9T+/j/Zltk+1aTuY8VVNX9rWyVDXZDAAIQmIxAnkSGdKKvVftCnktNrlO8KZj76Gp3W9uuPLJ8/hHnrjYNkc/+VLdfOkRxj7bu3yy83xZUWWYtE3ceU9m2xWSmYwVV+h1NEgQgAAEInCCQJ5AToicPPzQk/jOyL+i5HPoBz2rnV6Z+vCpSlWnab7vd1IWHAofsY1N/U9dnG6rbcwYqf5h42Gfbs6WgSrbn80A+bC2Z+1hB1Yu3BgB7IQCBZQk8YdnuF+s9Tx5jGpHfovMFXqUCmpzbJttT9uQ+3n9KuHLcNlWfq+rCwzpULplsRw6g9JuJrv+tmYzL4+EubUPbOFsm2+/2S5b5XJCNW0pmOiSouiEctp4t+Y6tEIDAwgT+OvrXxeONkZ8XecoHrUP9qlKeOMY2TG8K5lUhX6Dryr63F7Kuizo44HbVibyUh9ur9K2uDt2PKpptyYpdrzGYI9Wxsw1bDKrELPskX7aSzH1IUJV934rf2AkBCKyAgJa2b43sC5HKD0fW7Yy9r2DNceG8f3DM/WTOeVsyfVLWUdrebap9ZjubdLmtymr7pjZT1Wdb8lfd1d+1kX18qv6z3jp27n+rQZX8y37Jny0kcx8SVFnHVnzewrhgIwQOQ0A/wfKdkX8/sn6GJV9Q3hf7PxV5jylPGFP796XRwRdVOskf5DRz3UbqkvLzVaUTgPuqBkWneOTj1bZdbB5DNtvS9D0i+/m2MTo8oSPbY1H3v+WgSr5k3/Tc4NqTuY8RVC19nq+dNfZBAAInCCjA+s3I+gV7X5xU6gJ1eWTd1tpLypPFkj5lO8z8mg4G3RKybqfyVLJsdcLIdlR15FuZ1XZV2Tn27UObv7Z5jluAdfa4butBlcbTvrTxnmPcS/qwrX2Dqra/g5L+kYEABCBQS+AZUfuGyPkhXF+w9BzQ0yNvOa3p4imeZpvLawsB6ztNuV1bM8tVg6MmHmt5088+Ndnp4y71DSv76rqpSvej0sl1BFUmMk9p7n2DKrfPYzmP5fQCAQgchsCvh6fV1StddDTBXR/51ZG/JvKW0hovnjlgyPb9ewHY0sDKetVXTrnvXG95lWtIXeyxbNc3JLv66X4yU9ftIajS37j96cpmbnnb2SeoavobmNsH+oMABA5C4BvCz3+J3LSy4gtaSanvN/3ZgtzWfAHNtpllnrCbsJUEVk36cp/Wb1mVS7/pV7WphIcmVvvg9lOU7iPfanTdHoIqMbM/+mL9mpPtzGNRaq/bqiRBAAIQmJ3Ab0SPepi9eosoX5xKt/XA8a/M6EFdEDFj90VdZRvN8dTD7Dmwqgs8rKd6LPcl4yynsipbZPxEQrarxKYLkh/vmcgeqbVNH0h9uG5vQZX8WnPS99fMvoud1fO/S1tkIQABCIxO4PzQeOFZfkiUD0/5c2Pb+TWxXffmmy+EKhWkvTDylGlLF9Fsq/icCihuDBnzrMo21ec+qttTjkNX3ba/9PteXlU9FYx2tcPyWnG1Ta5T6TqCqkxl+u2vS+yv7NCdx0slCQIQgMBmCSjIyhe0um1NTE8Z2cMcOIysehJ1+rHgKpu2QKEpsLKOarCVeVhG5ZqSnu2zbf9UaNgVZ22q/hY2PynmtwyrrGznXoIq3fa3T/oEy5pTXjkvsTOf+yXyyEAAAhDYBIFLw8pTq1i6sOsiqICiLWuyq2a1c/YEoXJLKU8A9qHJ/rrAym2kJyex9DGX+fgatrPvpfZcceZX1d/S9qfkmmwyw70EVeJgn6ZieYp16fG8WvXugkb2SyUJAhCAwC4JPDe8yg8a5wvf2NtbA9hl1SoHVprgza5uYvQxlWq3tmT76mxvsvWyOOB239EkNKD+iEGVeK49la5W+dzYgk9rZ459EIDAhgg8P2xVkJUnsXxBHLK9IQz3MLWORd1bT3VsqoFJVdc9OlrBzkvDBvuhb1CVpgeHoH0Tm8eVNiyUs01Vnq7f00rVO4KJ/fraQj5LiZWsVtkXldXxW8pu+oUABCAAgQUJ3BB958khb+cAK9d7W2bfN7KDDtevcYLJNsruLumSELZvv9ylYYGs9VaZuX5PQZVw2K9rC9gsLdK2WmU/VFbHbmm76R8CEFiYwLkL90/3yxF4WHR9TuS6iUHnhScN/ZxNNT0iKvQMm9rnVN3Px5bY/rHo1DbJn67p6mjg25lz/37dXv82H9B1EBaQ/8bUZ362Kp9D2t7rGCX32YQABCAAgb4E8qqOJo0+uW/fU7TL/vTV/94zDs/sq6ChndnmVUGJur4u2LWqEhnLrqW0zfqFhS2k6mqV7VfZNjZb8A0bIQCBiQjwP62JwG5Urc4Hrey8toP9XxKymmjWmLxKNcQ2rVYpfeLOYvR/Pzy6xnUr3Mo1J69W5fNb21vxYd1nAtZBAAIQOBiBl4e/WknJKz6aVJzffMYjf1bhrGoVhe0csrKg26RjP1wtpratCsr1KpuSZYb41aR7qnrbXFfKD2e9VPKCqYzoqDevVsnuLfHu6CriEIAABCAwB4EcAHhCdF1+zsjH/mQOowr7sE1rmwxtl8pqkq0+Xj3mfR9fm1+2r660zVsu6/yiDgIQgMBdBFjGvgsFGxUCT4h9Tdr5HNGEqLf+3h9ZSasK1fTt1YqF9nPA0fYm3dzmaVXPSTyPlhSIfzRySfB4NDb4CwEIbJxAnjA37grmj0hAb7xdHTk/k3R97Ot80S0RPbytJBknBwi5jY/NXWrCznY8dG4DWvo7Lx2r+/u7Kh3f46Z+U1G/5ykO8l9ZY5XzA2NfgdcaVrXys3T5TcAwjwQBCEDgngT0Y8YkCJjAo2Pjusg5INHEVp38bz5r4FK7knFgVV3hOhOfpagGVNmXWQxo6UQBqZPsrEtPikpz1KrWEf9GtQKqwGstSeOmcdDYkCAAAQg0EqhOlo2CHDgEgQeElzkI0cT/yBrP33lW57IqknVUj025v+aASn7nACmvWDUx4e+zicy89flNwPfM2zW9QQACEIDAlgkoMNFKySUtTlwYx34+ct1tNbVVblqJiUOjp2tCo/t1OXonAxVqtcO26UH/tmQ5lXXJx+dkXGdHad1LQtA2f7C00crk7kg+rMw0zIEABCAAgb0ScFDWFBCM5bffQPRk7XKtgYbtK+FyiqF1rdXXPMZ6Jsn2qnxhPrixbfuhHyYnQQACEIAABGYh4Mlnqkk/Bx3uS+VU/Q2Flr/jdWqVSn1l/+r6ts9r9dc2Zz9k82t8YKPltWG32T9toz5gNgQgAAEIbIxAnkzHNt2Tmkv1VRKojG1HF322VWVJykFYnbz1yfc1pny7z7au0c4+Nvnczi8d9NFDGwhAAAIQgEAxAU+mY0781umy2JgFBW2ryi7Bn9u9r8Z2HxuTbU03varys0eyU59Q2FN6dThj/r+7J8fwBQIQgAAE1kvAE4/KMSb/rE/bW0jZ5q4M3LauXduxpbj8anRsu1xu/XZfE0uvJNaNTVMb6iEAAQhAAAKDCHhyddlXmSYv61C5hZTt7TP5un1d27ZjS7Cpe2lgCTvm6vM50ZHH4F1zdUo/EIAABCAAAU8+LrvcAjM9t1W5hZTtrQuKSnzIOqryPtZXd1Vf3/3/ioa2xWXTt8v69rHWdvmtxrXaiF0QgAAEILBDApr8Pemq7BIM5HZrRlP1saufVd+yvuoxM+nCsapjyP6LorFtcLm3Z6dK+Nh3PrFQQgsZCEAAAhAYjYB+N82TkMu6H2TOHeoDo5ZdKoDI9uTtv4idHPjYTpd9VuSy/nxLLddr233MzeRnUt+2QWXdR2Bl597TteGgOfzS3p3FPwhAAAIQWB+BukBEAURd9oSlcsl0QXT++ZH1gHKd/dnOajCldn2Sfg7FeqvtXT9XUPVvyRb3rfIot/qq/PN+Dn7/Jh9gGwIQgAAEIDAHgTwR5Um6afv2OYyq6eO+UXfKVgU2knl8TfunRZ18+r2aYyVV5qFgLifXTx1U3Rqduq9c3piNOfj2U8L/fI586OA8cB8CEIAABBYikCejPGnn7Tmf1XlMcHhdZAUr2Ybqto6XfPzxm870/HmUfZL7rQZPTfV9+qi2eV5UNI3LP1aF2b+LwMdjy+Oib3WRIAABCEAAAockUHJbT4HND0V+dAdCYwVVmqxz8uRdDbayTNftq6KB9eZSAdYzuyo7qPyViaHG5kcPygG3IQABCEDggATuFz5r8stBRN5WQHHeAC4/kXT3UZNty+1t45Cg6ndCYf4sgHW6vCl3yHYxgVeGpBmq5DmrYnQIQgACEIDA1gnkwEXbuq33hMhDgikzeWpsWH+f55DybTjrVOlJu0tQdSqIsk5u8WXS/ba/KprlsRPbn+unilYQgAAEIACBbRF44ITmXhq6HbC8qWM/egjabf8qtXVdW1D1spBvW4myDgWRb0262RyPQH7Oyrz1GZG3RybIGo8zmiAAAQhA4EAEFLRoUm0LgppweDLObV2nUsHWRyPrgX7J5GN12wqi3haZNA+By6IbBVJ1Y1Gt0/hpheuTDfmOqNctZRIEIAABCEDg0AR8O0gT53WVfEPs6xmmupwn3pIH6rO8tgmiAsJK0rPDjtdHviVydZxK9/UBVhIEIAABCEDg0ATeHN6XTpx95BS06XafPtT5ksik9RP4rDDxs1PWbWh9G60tx2ESBCCwVgLnrNUw7ILADglcHz5pIq2m86Oi6W9Rx5y06qTbfH4GTMHXuT5ICQEIQAACEIAABCDQTCA/j2Mpr2Tl56x8jBICEIAABCAAAQhAoIGAgyg9U6XkfYKqO3nwLwQgAIFVEODWwSqGASMgUESAv9ciTAhBAAIQWIYAF+lluNMrBCAAAQhAAAI7I0BQtbMBxZ1dEtDtPqWmh9nvPMq/EIAABCCwKAGCqkXx0zkEigg4qCoSRggCEIAABJYhQFC1DHd6hUAXAk9PwvnnalI1mxCAAAQgsDQBbicsPQL0D4EyAl6t0ht//s+Q6rxdpgUpCEAAAhCYjAAX5MnQohgCkxDgP0KTYEUpBCAAgeEECKqGM0QDBCAAAQhAAAIQ4NYB5wAENkaAlaqNDRjmQgACxyHAStVxxhpPIQABCEAAAhCYkABB1YRwUQ2BEQn4QfURVaIKAhCAAATGJEBQNSZNdEFgOgIEVdOxRTMEIACBUQgQVI2CESUQmJzATZP3QAcQgAAEIDCIAA+9DsJHYwjMSqC6WsV3qmbFT2cQgAAE2gmwUtXOh6MQgAAEIAABCECgiABBVREmhCAAAQhAAAIQgEA7AYKqdj4chQAEIAABCEAAAkUECKqKMCEEAQhAAAIQgAAE2gkQVLXz4SgE1kSg+qD6mmzDFghAAAKHJ0BQdfhTAAAQgAAEIAABCIxBgKBqDIrogAAEIAABCEDg8AQIqg5/CgBgQwS4/behwcJUCEDgeAQIqo435ni8XQLnbdd0LIcABCCwfwIEVfsfYzyEAAQgAAEIQGAGAgRVM0CmCwhAAAIQgAAE9k+AoGr/Y4yH+yLAc1X7Gk+8gQAEdkSAoGpHg4krhyBAUHWIYcZJCEBgiwQIqrY4ath8ZAI8rH7k0cd3CEBg1QQIqlY9PBgHgVYC57Qe5SAEIAABCMxKgKBqVtx0BgEIQAACEIDAXgkQVO11ZPHrCAR4vuoIo4yPEIAABCAAAQhMRkDBlPL9JusBxRCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQODSB/wP3u048NAz1xAAAAABJRU5ErkJggg=="
Solved! Go to Solution.
Hi @Igarsaba ,
According to my knowledge, you can resize the image by adjusting the image height in the format, but the overall scale of the image will still be a square. PowerBI does not currently support resizing the cell where the image is located as a rectangle, you can only change the original scale of your image and adjust its length and width to be consistent.
If you would like to suggest some feature improvements. I have found users with similar needs to you here , you may vote the idea and comment to improve this feature. It is a place for customers provide feedback about Microsoft Office products . What’s more, if a feedback is high voted there by other customers, it will be promising that Microsoft Product Team will take it into consideration when designing the next version in the future.
Best Regards,
Jianbo Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Igarsaba ,
According to my knowledge, you can resize the image by adjusting the image height in the format, but the overall scale of the image will still be a square. PowerBI does not currently support resizing the cell where the image is located as a rectangle, you can only change the original scale of your image and adjust its length and width to be consistent.
If you would like to suggest some feature improvements. I have found users with similar needs to you here , you may vote the idea and comment to improve this feature. It is a place for customers provide feedback about Microsoft Office products . What’s more, if a feedback is high voted there by other customers, it will be promising that Microsoft Product Team will take it into consideration when designing the next version in the future.
Best Regards,
Jianbo Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
| User | Count |
|---|---|
| 38 | |
| 36 | |
| 33 | |
| 32 | |
| 29 |
| User | Count |
|---|---|
| 129 | |
| 88 | |
| 79 | |
| 68 | |
| 63 |