diff --git a/Pipfile b/Pipfile
index 577c372..80a13ba 100644
--- a/Pipfile
+++ b/Pipfile
@@ -4,13 +4,16 @@ verify_ssl = true
 name = "pypi"
 
 [packages]
+"boto3" = "*"
 "fastparquet" = "*"
+"kaleido" = "*"
+"matplotlib" = "*"
 "pandas" = "*"
 "plotly" = "*"
 "pyarrow" = "*"
-"scipy" = "*"
+"requests" = "*"
 "s3fs" = "*"
-"kaleido" = "*"
+"scipy" = "*"
 
 [dev-packages]
 "black" = "*"
diff --git a/Pipfile.lock b/Pipfile.lock
index 7a1936e..f5a5769 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "f509498febe61f97f5b9257362c7cae8b434ae9b2d7f913016f09d7752123268"
+            "sha256": "1a63bafcd23ea0f8d388b5e5207c27bc2e330c8a7ca9ccc6f085fd0e4cffe3ac"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -16,322 +16,239 @@
         ]
     },
     "default": {
-        "aiobotocore": {
+        "boto3": {
             "hashes": [
-                "sha256:6c25381d31b712652bc2f6008683949351c240c56d24b1d8ae252c1034a50f63",
-                "sha256:f9fe0698cc497861bdb54cd16161c804031f758ada9480c35540f20c0c078385"
+                "sha256:8bd5fdd528260c4da3e070c00468cfd4a50ad75570e81a409970c4490fdee458"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==2.4.0"
-        },
-        "aiohttp": {
-            "hashes": [
-                "sha256:02f9a2c72fc95d59b881cf38a4b2be9381b9527f9d328771e90f72ac76f31ad8",
-                "sha256:059a91e88f2c00fe40aed9031b3606c3f311414f86a90d696dd982e7aec48142",
-                "sha256:05a3c31c6d7cd08c149e50dc7aa2568317f5844acd745621983380597f027a18",
-                "sha256:08c78317e950e0762c2983f4dd58dc5e6c9ff75c8a0efeae299d363d439c8e34",
-                "sha256:09e28f572b21642128ef31f4e8372adb6888846f32fecb288c8b0457597ba61a",
-                "sha256:0d2c6d8c6872df4a6ec37d2ede71eff62395b9e337b4e18efd2177de883a5033",
-                "sha256:16c121ba0b1ec2b44b73e3a8a171c4f999b33929cd2397124a8c7fcfc8cd9e06",
-                "sha256:1d90043c1882067f1bd26196d5d2db9aa6d268def3293ed5fb317e13c9413ea4",
-                "sha256:1e56b9cafcd6531bab5d9b2e890bb4937f4165109fe98e2b98ef0dcfcb06ee9d",
-                "sha256:20acae4f268317bb975671e375493dbdbc67cddb5f6c71eebdb85b34444ac46b",
-                "sha256:21b30885a63c3f4ff5b77a5d6caf008b037cb521a5f33eab445dc566f6d092cc",
-                "sha256:21d69797eb951f155026651f7e9362877334508d39c2fc37bd04ff55b2007091",
-                "sha256:256deb4b29fe5e47893fa32e1de2d73c3afe7407738bd3c63829874661d4822d",
-                "sha256:25892c92bee6d9449ffac82c2fe257f3a6f297792cdb18ad784737d61e7a9a85",
-                "sha256:2ca9af5f8f5812d475c5259393f52d712f6d5f0d7fdad9acdb1107dd9e3cb7eb",
-                "sha256:2d252771fc85e0cf8da0b823157962d70639e63cb9b578b1dec9868dd1f4f937",
-                "sha256:2dea10edfa1a54098703cb7acaa665c07b4e7568472a47f4e64e6319d3821ccf",
-                "sha256:2df5f139233060578d8c2c975128fb231a89ca0a462b35d4b5fcf7c501ebdbe1",
-                "sha256:2feebbb6074cdbd1ac276dbd737b40e890a1361b3cc30b74ac2f5e24aab41f7b",
-                "sha256:309aa21c1d54b8ef0723181d430347d7452daaff93e8e2363db8e75c72c2fb2d",
-                "sha256:3828fb41b7203176b82fe5d699e0d845435f2374750a44b480ea6b930f6be269",
-                "sha256:398701865e7a9565d49189f6c90868efaca21be65c725fc87fc305906be915da",
-                "sha256:43046a319664a04b146f81b40e1545d4c8ac7b7dd04c47e40bf09f65f2437346",
-                "sha256:437399385f2abcd634865705bdc180c8314124b98299d54fe1d4c8990f2f9494",
-                "sha256:45d88b016c849d74ebc6f2b6e8bc17cabf26e7e40c0661ddd8fae4c00f015697",
-                "sha256:47841407cc89a4b80b0c52276f3cc8138bbbfba4b179ee3acbd7d77ae33f7ac4",
-                "sha256:4a4fbc769ea9b6bd97f4ad0b430a6807f92f0e5eb020f1e42ece59f3ecfc4585",
-                "sha256:4ab94426ddb1ecc6a0b601d832d5d9d421820989b8caa929114811369673235c",
-                "sha256:4b0f30372cef3fdc262f33d06e7b411cd59058ce9174ef159ad938c4a34a89da",
-                "sha256:4e3a23ec214e95c9fe85a58470b660efe6534b83e6cbe38b3ed52b053d7cb6ad",
-                "sha256:512bd5ab136b8dc0ffe3fdf2dfb0c4b4f49c8577f6cae55dca862cd37a4564e2",
-                "sha256:527b3b87b24844ea7865284aabfab08eb0faf599b385b03c2aa91fc6edd6e4b6",
-                "sha256:54d107c89a3ebcd13228278d68f1436d3f33f2dd2af5415e3feaeb1156e1a62c",
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-                "sha256:d1fde0f44029e02d02d3993ad55ce93ead9bb9b15c6b7ccd580f90bd7e3de476",
-                "sha256:d24b8bb40d5c61ef2d9b6a8f4528c2f17f1c5d2d31fed62ec860f6006142e83e",
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-                "sha256:da22885266bbfb3f78218dc40205fed2671909fbd0720aedba39b4515c038091",
-                "sha256:da37dcfbf4b7f45d80ee386a5f81122501ec75672f475da34784196690762f4b",
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-                "sha256:db4c979b0b3e0fa7e9e69ecd11b2b3174c6963cebadeecfb7ad24532ffcdd11a",
-                "sha256:e164e0a98e92d06da343d17d4e9c4da4654f4a4588a20d6c73548a29f176abe2",
-                "sha256:e168a7560b7c61342ae0412997b069753f27ac4862ec7867eff74f0fe4ea2ad9",
-                "sha256:e381581b37db1db7597b62a2e6b8b57c3deec95d93b6d6407c5b61ddc98aca6d",
-                "sha256:e65bc19919c910127c06759a63747ebe14f386cda573d95bcc62b427ca1afc73",
-                "sha256:e7b8813be97cab8cb52b1375f41f8e6804f6507fe4660152e8ca5c48f0436017",
-                "sha256:e8a78079d9a39ca9ca99a8b0ac2fdc0c4d25fc80c8a8a82e5c8211509c523363",
-                "sha256:ebf909ea0a3fc9596e40d55d8000702a85e27fd578ff41a5500f68f20fd32e6c",
-                "sha256:ec40170327d4a404b0d91855d41bfe1fe4b699222b2b93e3d833a27330a87a6d",
-                "sha256:f178d2aadf0166be4df834c4953da2d7eef24719e8aec9a65289483eeea9d618",
-                "sha256:f88df3a83cf9df566f171adba39d5bd52814ac0b94778d2448652fc77f9eb491",
-                "sha256:f973157ffeab5459eefe7b97a804987876dd0a55570b8fa56b4e1954bf11329b",
-                "sha256:ff25f48fc8e623d95eca0670b8cc1469a83783c924a602e0fbd47363bb54aaca"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==3.8.3"
+            "index": "pypi",
+            "version": "==1.26.36"
         },
-        "aioitertools": {
+        "botocore": {
             "hashes": [
-                "sha256:04b95e3dab25b449def24d7df809411c10e62aab0cbe31a50ca4e68748c43394",
-                "sha256:42c68b8dd3a69c2bf7f2233bf7df4bb58b557bca5252ac02ed5187bbc67d6831"
+                "sha256:5cb1fb381c427fe12274eb866f2ff739169e0e1f33c2481a474ba2ff8ca43f75",
+                "sha256:927dd5c6b155f30d122c1d34f96aba8502e2e02f2d7a170351804d3de81f0c5e"
             ],
-            "markers": "python_version >= '3.6'",
-            "version": "==0.11.0"
+            "markers": "python_version >= '3.7'",
+            "version": "==1.29.36"
         },
-        "aiosignal": {
+        "certifi": {
             "hashes": [
-                "sha256:26e62109036cd181df6e6ad646f91f0dcfd05fe16d0cb924138ff2ab75d64e3a",
-                "sha256:78ed67db6c7b7ced4f98e495e572106d5c432a93e1ddd1bf475e1dc05f5b7df2"
+                "sha256:35824b4c3a97115964b408844d64aa14db1cc518f6562e8d7261699d1350a9e3",
+                "sha256:4ad3232f5e926d6718ec31cfc1fcadfde020920e278684144551c91769c7bc18"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==1.2.0"
+            "version": "==2022.12.7"
         },
-        "async-timeout": {
+        "charset-normalizer": {
             "hashes": [
-                "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15",
-                "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"
+                "sha256:5a3d016c7c547f69d6f81fb0db9449ce888b418b5b9952cc5e6e66843e9dd845",
+                "sha256:83e9a75d1911279afd89352c68b45348559d1fc0506b054b346651b5e7fee29f"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==4.0.2"
+            "version": "==2.1.1"
         },
-        "attrs": {
-            "hashes": [
-                "sha256:29adc2665447e5191d0e7c568fde78b21f9672d344281d0c6e1ab085429b22b6",
-                "sha256:86efa402f67bf2df34f51a335487cf46b1ec130d02b8d39fd248abfd30da551c"
+        "contourpy": {
+            "hashes": [
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+                "sha256:b3b1bd7577c530eaf9d2bc52d1a93fef50ac516a8b1062c3d1b9bcec9ebe329b",
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@@ -361,145 +278,268 @@
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@@ -511,31 +551,34 @@
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@@ -555,18 +598,34 @@
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@@ -804,23 +728,31 @@
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@@ -834,35 +766,26 @@
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@@ -949,29 +872,37 @@
             "markers": "python_version >= '3.7'",
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@@ -994,7 +925,7 @@
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@@ -1011,6 +942,13 @@
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@@ -1021,19 +959,19 @@
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@@ -1044,19 +982,26 @@
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@@ -1066,13 +1011,20 @@
             "markers": "python_version >= '3.7'",
             "version": "==3.1.2"
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@@ -1085,11 +1037,11 @@
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@@ -1101,19 +1053,35 @@
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@@ -1125,11 +1093,11 @@
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@@ -1208,35 +1176,35 @@
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@@ -1256,19 +1224,19 @@
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@@ -1283,16 +1251,16 @@
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@@ -1311,69 +1279,47 @@
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@@ -1448,6 +1386,60 @@
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+                "sha256:48c346915c114f5fdb3ead70312bd042a953a8ce5c7106d5bfb1a5254e47da92",
+                "sha256:50602afada6d6cbfad699b0c7bb50d5ccffa7e46a3d738092afddc1f9758427f",
+                "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2",
+                "sha256:77f396e6ef4c73fdc33a9157446466f1cff553d979bd00ecb64385760c6babdc",
+                "sha256:81957921f441d50af23654aa6c5e5eaf9b06aba7f0a19c18a538dc7ef291c5a1",
+                "sha256:819b3830a1543db06c4d4b865e70ded25be52a2e0631ccd2f6a47a2822f2fd7c",
+                "sha256:897b80890765f037df3403d22bab41627ca8811ae55e9a722fd0392850ec4d86",
+                "sha256:98c4d36e99714e55cfbaaee6dd5badbc9a1ec339ebfc3b1f52e293aee6bb71a4",
+                "sha256:9df7ed3b3d2e0ecfe09e14741b857df43adb5a3ddadc919a2d94fbdf78fea53c",
+                "sha256:9fa600030013c4de8165339db93d182b9431076eb98eb40ee068700c9c813e34",
+                "sha256:a80a78046a72361de73f8f395f1f1e49f956c6be882eed58505a15f3e430962b",
+                "sha256:afa17f5bc4d1b10afd4466fd3a44dc0e245382deca5b3c353d8b757f9e3ecb8d",
+                "sha256:b3d267842bf12586ba6c734f89d1f5b871df0273157918b0ccefa29deb05c21c",
+                "sha256:b5b9eccad747aabaaffbc6064800670f0c297e52c12754eb1d976c57e4f74dcb",
+                "sha256:bfaef573a63ba8923503d27530362590ff4f576c626d86a9fed95822a8255fd7",
+                "sha256:c5687b8d43cf58545ade1fe3e055f70eac7a5a1a0bf42824308d868289a95737",
+                "sha256:cba8c411ef271aa037d7357a2bc8f9ee8b58b9965831d9e51baf703280dc73d3",
+                "sha256:d15a181d1ecd0d4270dc32edb46f7cb7733c7c508857278d3d378d14d606db2d",
+                "sha256:d4b0ba9512519522b118090257be113b9468d804b19d63c71dbcf4a48fa32358",
+                "sha256:d4db7c7aef085872ef65a8fd7d6d09a14ae91f691dec3e87ee5ee0539d516f53",
+                "sha256:d4eccecf9adf6fbcc6861a38015c2a64f38b9d94838ac1810a9023a0609e1b78",
+                "sha256:d67d839ede4ed1b28a4e8909735fc992a923cdb84e618544973d7dfc71540803",
+                "sha256:daf496c58a8c52083df09b80c860005194014c3698698d1a57cbcfa182142a3a",
+                "sha256:dbad0e9d368bb989f4515da330b88a057617d16b6a8245084f1b05400f24609f",
+                "sha256:e61ceaab6f49fb8bdfaa0f92c4b57bcfbea54c09277b1b4f7ac376bfb7a7c174",
+                "sha256:f84fbc98b019fef2ee9a1cb3ce93e3187a6df0b2538a651bfb890254ba9f90b5"
+            ],
+            "markers": "python_full_version >= '3.6.0'",
+            "version": "==6.0"
+        },
         "pyzmq": {
             "hashes": [
                 "sha256:0108358dab8c6b27ff6b985c2af4b12665c1bc659648284153ee501000f5c107",
@@ -1525,24 +1517,38 @@
                 "sha256:f0d945a85b70da97ae86113faf9f1b9294efe66bd4a5d6f82f2676d567338b66",
                 "sha256:fa0ae3275ef706c0309556061185dd0e4c4cd3b7d6f67ae617e4e677c7a41e2e"
             ],
-            "markers": "python_version >= '3.6'",
+            "markers": "python_full_version >= '3.6.0'",
             "version": "==24.0.1"
         },
         "qtconsole": {
             "hashes": [
-                "sha256:8eadf012e83ab018295803c247c6ab7eacd3d5ab1e1d88a0f37fdcfdab9295a3",
-                "sha256:c29d24464f57cdbaa17d6f6060be6e6d5e29126e7feb57eebc1747433382b3d1"
+                "sha256:57748ea2fd26320a0b77adba20131cfbb13818c7c96d83fafcb110ff55f58b35",
+                "sha256:be13560c19bdb3b54ed9741a915aa701a68d424519e8341ac479a91209e694b2"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==5.3.2"
+            "version": "==5.4.0"
         },
         "qtpy": {
             "hashes": [
-                "sha256:268cf5328f41353be1b127e04a81bc74ec9a9b54c9ac75dd8fe0ff48d8ad6ead",
-                "sha256:7d5231133b772e40b4ee514b6673aca558331e4b88ca038b26c9e16c5c95524f"
+                "sha256:0603c9c83ccc035a4717a12908bf6bc6cb22509827ea2ec0e94c2da7c9ed57c5",
+                "sha256:8d6d544fc20facd27360ea189592e6135c614785f0dec0b4f083289de6beb408"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==2.2.1"
+            "version": "==2.3.0"
+        },
+        "rfc3339-validator": {
+            "hashes": [
+                "sha256:138a2abdf93304ad60530167e51d2dfb9549521a836871b88d7f4695d0022f6b",
+                "sha256:24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa"
+            ],
+            "version": "==0.1.4"
+        },
+        "rfc3986-validator": {
+            "hashes": [
+                "sha256:2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9",
+                "sha256:3d44bde7921b3b9ec3ae4e3adca370438eccebc676456449b145d533b240d055"
+            ],
+            "version": "==0.1.1"
         },
         "send2trash": {
             "hashes": [
@@ -1572,23 +1578,23 @@
                 "sha256:3b2503d3c7084a42b1ebd08116e5f81aadfaea95863628c80a3b774a11b7c759",
                 "sha256:fc53893b3da2c33de295667a0e19f078c14bf86544af307354de5fcf12a3f30d"
             ],
-            "markers": "python_version >= '3.6'",
+            "markers": "python_full_version >= '3.6.0'",
             "version": "==2.3.2.post1"
         },
         "stack-data": {
             "hashes": [
-                "sha256:8e515439f818efaa251036af72d89e4026e2b03993f3453c000b200fb4f2d6aa",
-                "sha256:b92d206ef355a367d14316b786ab41cb99eb453a21f2cb216a4204625ff7bc07"
+                "sha256:32d2dd0376772d01b6cb9fc996f3c8b57a357089dec328ed4b6553d037eaf815",
+                "sha256:cbb2a53eb64e5785878201a97ed7c7b94883f48b87bfb0bbe8b623c74679e4a8"
             ],
-            "version": "==0.6.0"
+            "version": "==0.6.2"
         },
         "terminado": {
             "hashes": [
-                "sha256:520feaa3aeab8ad64a69ca779be54be9234edb2d0d6567e76c93c2c9a4e6e43f",
-                "sha256:bf6fe52accd06d0661d7611cc73202121ec6ee51e46d8185d489ac074ca457c2"
+                "sha256:6ccbbcd3a4f8a25a5ec04991f39a0b8db52dfcd487ea0e578d977e6752380333",
+                "sha256:8650d44334eba354dd591129ca3124a6ba42c3d5b70df5051b6921d506fdaeae"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==0.17.0"
+            "version": "==0.17.1"
         },
         "tinycss2": {
             "hashes": [
@@ -1625,11 +1631,18 @@
         },
         "traitlets": {
             "hashes": [
-                "sha256:1201b2c9f76097195989cdf7f65db9897593b0dfd69e4ac96016661bb6f0d30f",
-                "sha256:b122f9ff2f2f6c1709dab289a05555be011c87828e911c0cf4074b85cb780a79"
+                "sha256:6cc57d6dc28c85d5365961726ffd19b538739347749e13ebe34e03323a0e8f84",
+                "sha256:c864831efa0ba6576d09b44884b34e41defc18c0d7e720b4a2d6698c842cab3e"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==5.5.0"
+            "version": "==5.8.0"
+        },
+        "uri-template": {
+            "hashes": [
+                "sha256:934e4d09d108b70eb8a24410af8615294d09d279ce0e7cbcdaef1bd21f932b06",
+                "sha256:f1699c77b73b925cf4937eae31ab282a86dc885c333f2e942513f08f691fc7db"
+            ],
+            "version": "==1.2.0"
         },
         "wcwidth": {
             "hashes": [
@@ -1638,6 +1651,13 @@
             ],
             "version": "==0.2.5"
         },
+        "webcolors": {
+            "hashes": [
+                "sha256:16d043d3a08fd6a1b1b7e3e9e62640d09790dce80d2bdd4792a175b35fe794a9",
+                "sha256:d98743d81d498a2d3eaf165196e65481f0d2ea85281463d856b1e51b09f62dce"
+            ],
+            "version": "==1.12"
+        },
         "webencodings": {
             "hashes": [
                 "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78",
@@ -1647,19 +1667,19 @@
         },
         "websocket-client": {
             "hashes": [
-                "sha256:398909eb7e261f44b8f4bd474785b6ec5f5b499d4953342fe9755e01ef624090",
-                "sha256:f9611eb65c8241a67fb373bef040b3cf8ad377a9f6546a12b620b6511e8ea9ef"
+                "sha256:d6b06432f184438d99ac1f456eaf22fe1ade524c3dd16e661142dc54e9cba574",
+                "sha256:d6e8f90ca8e2dd4e8027c4561adeb9456b54044312dba655e7cae652ceb9ae59"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.4.1"
+            "version": "==1.4.2"
         },
         "widgetsnbextension": {
             "hashes": [
-                "sha256:34824864c062b0b3030ad78210db5ae6a3960dfb61d5b27562d6631774de0286",
-                "sha256:7f3b0de8fda692d31ef03743b598620e31c2668b835edbd3962d080ccecf31eb"
+                "sha256:003f716d930d385be3fd9de42dd9bf008e30053f73bddde235d14fbeaeff19af",
+                "sha256:eaaaf434fb9b08bd197b2a14ffe45ddb5ac3897593d43c69287091e5f3147bf7"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==4.0.3"
+            "version": "==4.0.5"
         }
     }
 }
diff --git a/metadata/plate.csv.gz b/metadata/plate.csv.gz
index 22377e7..d8882fb 100644
Binary files a/metadata/plate.csv.gz and b/metadata/plate.csv.gz differ
diff --git a/metadata/well.csv.gz b/metadata/well.csv.gz
index 6426a13..050b8bd 100644
Binary files a/metadata/well.csv.gz and b/metadata/well.csv.gz differ
diff --git a/sample_notebook.ipynb b/sample_notebook.ipynb
index 6f60c59..fee0890 100644
--- a/sample_notebook.ipynb
+++ b/sample_notebook.ipynb
@@ -40,9 +40,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "formatter = ('s3://cellpainting-gallery/cpg0016-jump/'\n",
-    "             '{Metadata_Source}/workspace/profiles/'\n",
-    "             '{Metadata_Batch}/{Metadata_Plate}/{Metadata_Plate}.parquet')"
+    "profile_formatter = (\n",
+    "    \"s3://cellpainting-gallery/cpg0016-jump/\"\n",
+    "    \"{Metadata_Source}/workspace/profiles/\"\n",
+    "    \"{Metadata_Batch}/{Metadata_Plate}/{Metadata_Plate}.parquet\"\n",
+    ")\n",
+    "\n",
+    "loaddata_formatter = (\n",
+    "    \"s3://cellpainting-gallery/cpg0016-jump/\"\n",
+    "    \"{Metadata_Source}/workspace/load_data_csv/\"\n",
+    "    \"{Metadata_Batch}/{Metadata_Plate}/load_data_with_illum.parquet\"\n",
+    ")\n"
    ]
   },
   {
@@ -63,18 +71,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plates = pd.read_csv('metadata/plate.csv.gz')\n",
-    "wells = pd.read_csv('metadata/well.csv.gz')\n",
-    "compound = pd.read_csv('metadata/compound.csv.gz')"
+    "plates = pd.read_csv(\"metadata/plate.csv.gz\")\n",
+    "wells = pd.read_csv(\"metadata/well.csv.gz\")\n",
+    "compound = pd.read_csv(\"metadata/compound.csv.gz\")\n",
+    "orf = pd.read_csv(\"metadata/orf.csv.gz\")\n"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "id": "850df1c5",
    "metadata": {},
    "source": [
     "## Sample plates\n",
-    "Let's sample two plates of a certain type (encoded in `Metadata_PlateType`) from each data-generating center (`Metadata_Source`). Note that only 6 out of the 12 sources are currently available. "
+    "Let's sample two plates of a certain type (encoded in `Metadata_PlateType`) from each data-generating center (`Metadata_Source`). Note that only 8 out of the 12 sources are currently available. "
    ]
   },
   {
@@ -126,73 +136,101 @@
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>413</th>\n",
-       "      <td>source_3</td>\n",
-       "      <td>CP_31_all_Phenix1</td>\n",
-       "      <td>JCPQC028</td>\n",
+       "      <th>400</th>\n",
+       "      <td>source_11</td>\n",
+       "      <td>Batch5</td>\n",
+       "      <td>LM71-102_1</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>414</th>\n",
+       "      <th>288</th>\n",
+       "      <td>source_11</td>\n",
+       "      <td>Batch2</td>\n",
+       "      <td>LM37-70_1</td>\n",
+       "      <td>TARGET2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>418</th>\n",
+       "      <td>source_2</td>\n",
+       "      <td>20210614_Batch_1</td>\n",
+       "      <td>1053600674</td>\n",
+       "      <td>TARGET2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>544</th>\n",
+       "      <td>source_2</td>\n",
+       "      <td>20210808_Batch_4</td>\n",
+       "      <td>1086292884</td>\n",
+       "      <td>TARGET2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>872</th>\n",
        "      <td>source_3</td>\n",
-       "      <td>CP_31_all_Phenix1</td>\n",
-       "      <td>JCPQC029</td>\n",
+       "      <td>CP_33_all_Phenix1</td>\n",
+       "      <td>JCPQC032</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>802</th>\n",
-       "      <td>source_4</td>\n",
-       "      <td>2021_08_30_Batch13</td>\n",
-       "      <td>BR00127146</td>\n",
+       "      <th>933</th>\n",
+       "      <td>source_3</td>\n",
+       "      <td>CP_36_all_Phenix1</td>\n",
+       "      <td>JCPQC038</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>724</th>\n",
+       "      <th>1133</th>\n",
        "      <td>source_4</td>\n",
        "      <td>2021_08_02_Batch10</td>\n",
        "      <td>BR00121423</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>987</th>\n",
+       "      <th>1111</th>\n",
+       "      <td>source_4</td>\n",
+       "      <td>2021_07_26_Batch9</td>\n",
+       "      <td>BR00121427</td>\n",
+       "      <td>TARGET2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1296</th>\n",
        "      <td>source_5</td>\n",
-       "      <td>JUMPCPE-20210902-Run26_20210903_010341</td>\n",
-       "      <td>ACPJUM141</td>\n",
+       "      <td>JUMPCPE-20210716-Run12_20210719_162047</td>\n",
+       "      <td>ACPJUM062</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>995</th>\n",
+       "      <th>1269</th>\n",
        "      <td>source_5</td>\n",
-       "      <td>JUMPCPE-20210903-Run27_20210904_215148</td>\n",
-       "      <td>ACPJUM142</td>\n",
+       "      <td>JUMPCPE-20210712-Run09_20210713_003159</td>\n",
+       "      <td>ACPJUM051</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1086</th>\n",
+       "      <th>1504</th>\n",
        "      <td>source_6</td>\n",
-       "      <td>p210831CPU2OS48hw384exp024JUMP</td>\n",
-       "      <td>110000294901</td>\n",
+       "      <td>p210906CPU2OS48hw384exp025JUMP</td>\n",
+       "      <td>110000294881</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1066</th>\n",
+       "      <th>1485</th>\n",
        "      <td>source_6</td>\n",
-       "      <td>p210824CPU2OS48hw384exp022JUMP</td>\n",
-       "      <td>110000293081</td>\n",
+       "      <td>p210830CPU2OS48hw384exp023JUMP</td>\n",
+       "      <td>110000293093</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1417</th>\n",
+       "      <th>1934</th>\n",
        "      <td>source_8</td>\n",
-       "      <td>J2</td>\n",
-       "      <td>A1170490</td>\n",
+       "      <td>J4</td>\n",
+       "      <td>A1166179</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1421</th>\n",
+       "      <th>1722</th>\n",
        "      <td>source_8</td>\n",
-       "      <td>J3</td>\n",
-       "      <td>A1166127</td>\n",
+       "      <td>J1</td>\n",
+       "      <td>A1170384</td>\n",
        "      <td>TARGET2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -203,30 +241,38 @@
        "     Metadata_Source                          Metadata_Batch  \\\n",
        "106        source_10             2021_08_03_U2OS_48_hr_run12   \n",
        "125        source_10             2021_08_09_U2OS_48_hr_run13   \n",
-       "413         source_3                       CP_31_all_Phenix1   \n",
-       "414         source_3                       CP_31_all_Phenix1   \n",
-       "802         source_4                      2021_08_30_Batch13   \n",
-       "724         source_4                      2021_08_02_Batch10   \n",
-       "987         source_5  JUMPCPE-20210902-Run26_20210903_010341   \n",
-       "995         source_5  JUMPCPE-20210903-Run27_20210904_215148   \n",
-       "1086        source_6          p210831CPU2OS48hw384exp024JUMP   \n",
-       "1066        source_6          p210824CPU2OS48hw384exp022JUMP   \n",
-       "1417        source_8                                      J2   \n",
-       "1421        source_8                                      J3   \n",
+       "400        source_11                                  Batch5   \n",
+       "288        source_11                                  Batch2   \n",
+       "418         source_2                        20210614_Batch_1   \n",
+       "544         source_2                        20210808_Batch_4   \n",
+       "872         source_3                       CP_33_all_Phenix1   \n",
+       "933         source_3                       CP_36_all_Phenix1   \n",
+       "1133        source_4                      2021_08_02_Batch10   \n",
+       "1111        source_4                       2021_07_26_Batch9   \n",
+       "1296        source_5  JUMPCPE-20210716-Run12_20210719_162047   \n",
+       "1269        source_5  JUMPCPE-20210712-Run09_20210713_003159   \n",
+       "1504        source_6          p210906CPU2OS48hw384exp025JUMP   \n",
+       "1485        source_6          p210830CPU2OS48hw384exp023JUMP   \n",
+       "1934        source_8                                      J4   \n",
+       "1722        source_8                                      J1   \n",
        "\n",
        "         Metadata_Plate Metadata_PlateType  \n",
        "106   Dest210726-160150            TARGET2  \n",
        "125   Dest210727-153003            TARGET2  \n",
-       "413            JCPQC028            TARGET2  \n",
-       "414            JCPQC029            TARGET2  \n",
-       "802          BR00127146            TARGET2  \n",
-       "724          BR00121423            TARGET2  \n",
-       "987           ACPJUM141            TARGET2  \n",
-       "995           ACPJUM142            TARGET2  \n",
-       "1086       110000294901            TARGET2  \n",
-       "1066       110000293081            TARGET2  \n",
-       "1417           A1170490            TARGET2  \n",
-       "1421           A1166127            TARGET2  "
+       "400          LM71-102_1            TARGET2  \n",
+       "288           LM37-70_1            TARGET2  \n",
+       "418          1053600674            TARGET2  \n",
+       "544          1086292884            TARGET2  \n",
+       "872            JCPQC032            TARGET2  \n",
+       "933            JCPQC038            TARGET2  \n",
+       "1133         BR00121423            TARGET2  \n",
+       "1111         BR00121427            TARGET2  \n",
+       "1296          ACPJUM062            TARGET2  \n",
+       "1269          ACPJUM051            TARGET2  \n",
+       "1504       110000294881            TARGET2  \n",
+       "1485       110000293093            TARGET2  \n",
+       "1934           A1166179            TARGET2  \n",
+       "1722           A1170384            TARGET2  "
       ]
      },
      "execution_count": 4,
@@ -235,8 +281,12 @@
     }
    ],
    "source": [
-    "sample = plates.query('Metadata_PlateType==\"TARGET2\"').groupby('Metadata_Source').sample(2, random_state=42)\n",
-    "sample"
+    "sample = (\n",
+    "    plates.query('Metadata_PlateType==\"TARGET2\"')\n",
+    "    .groupby(\"Metadata_Source\")\n",
+    "    .sample(2, random_state=42)\n",
+    ")\n",
+    "sample\n"
    ]
   },
   {
@@ -270,11 +320,19 @@
    "outputs": [],
    "source": [
     "dframes = []\n",
-    "columns = ['Metadata_Source', 'Metadata_Plate', 'Metadata_Well', 'Cells_AreaShape_Eccentricity', 'Nuclei_AreaShape_Area']\n",
+    "columns = [\n",
+    "    \"Metadata_Source\",\n",
+    "    \"Metadata_Plate\",\n",
+    "    \"Metadata_Well\",\n",
+    "    \"Cells_AreaShape_Eccentricity\",\n",
+    "    \"Nuclei_AreaShape_Area\",\n",
+    "]\n",
     "for _, row in sample.iterrows():\n",
-    "    s3_path = formatter.format(**row.to_dict())\n",
-    "    dframes.append(pd.read_parquet(s3_path, storage_options={\"anon\": True}, columns=columns))\n",
-    "dframes = pd.concat(dframes)"
+    "    s3_path = profile_formatter.format(**row.to_dict())\n",
+    "    dframes.append(\n",
+    "        pd.read_parquet(s3_path, storage_options={\"anon\": True}, columns=columns)\n",
+    "    )\n",
+    "dframes = pd.concat(dframes)\n"
    ]
   },
   {
@@ -304,8 +362,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "metadata = compound.merge(wells, on='Metadata_JCP2022')\n",
-    "ann_dframe = metadata.merge(dframes, on=['Metadata_Source', 'Metadata_Plate', 'Metadata_Well'])"
+    "metadata = compound.merge(wells, on=\"Metadata_JCP2022\")\n",
+    "ann_dframe = metadata.merge(\n",
+    "    dframes, on=[\"Metadata_Source\", \"Metadata_Plate\", \"Metadata_Well\"]\n",
+    ")\n"
    ]
   },
   {
@@ -355,26 +415,26 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1512</th>\n",
-       "      <td>JCP2022_033924</td>\n",
-       "      <td>IAZDPXIOMUYVGZ-UHFFFAOYSA-N</td>\n",
-       "      <td>InChI=1S/C2H6OS/c1-4(2)3/h1-2H3</td>\n",
-       "      <td>source_6</td>\n",
-       "      <td>110000293081</td>\n",
-       "      <td>E13</td>\n",
-       "      <td>0.76608</td>\n",
-       "      <td>794.30</td>\n",
+       "      <th>5878</th>\n",
+       "      <td>JCP2022_109917</td>\n",
+       "      <td>YPHMISFOHDHNIV-UHFFFAOYSA-N</td>\n",
+       "      <td>InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...</td>\n",
+       "      <td>source_5</td>\n",
+       "      <td>ACPJUM062</td>\n",
+       "      <td>K08</td>\n",
+       "      <td>0.85995</td>\n",
+       "      <td>716.30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4535</th>\n",
-       "      <td>JCP2022_115049</td>\n",
-       "      <td>ZQPXNYLXYNRFNP-UHFFFAOYSA-N</td>\n",
-       "      <td>InChI=1S/C16H12N6O5/c23-21(24)9-1-3-11-13(5-9)...</td>\n",
-       "      <td>source_8</td>\n",
-       "      <td>A1170490</td>\n",
-       "      <td>C14</td>\n",
-       "      <td>0.78057</td>\n",
-       "      <td>711.22</td>\n",
+       "      <th>5357</th>\n",
+       "      <td>JCP2022_097564</td>\n",
+       "      <td>WATNXVHKRRTUFK-UHFFFAOYSA-N</td>\n",
+       "      <td>InChI=1S/C23H29N3O2/c1-4-8-18(9-5-2)23(27)24-1...</td>\n",
+       "      <td>source_11</td>\n",
+       "      <td>LM37-70_1</td>\n",
+       "      <td>M06</td>\n",
+       "      <td>0.74290</td>\n",
+       "      <td>877.81</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -382,20 +442,20 @@
       ],
       "text/plain": [
        "     Metadata_JCP2022            Metadata_InChIKey  \\\n",
-       "1512   JCP2022_033924  IAZDPXIOMUYVGZ-UHFFFAOYSA-N   \n",
-       "4535   JCP2022_115049  ZQPXNYLXYNRFNP-UHFFFAOYSA-N   \n",
+       "5878   JCP2022_109917  YPHMISFOHDHNIV-UHFFFAOYSA-N   \n",
+       "5357   JCP2022_097564  WATNXVHKRRTUFK-UHFFFAOYSA-N   \n",
        "\n",
        "                                         Metadata_InChI Metadata_Source  \\\n",
-       "1512                    InChI=1S/C2H6OS/c1-4(2)3/h1-2H3        source_6   \n",
-       "4535  InChI=1S/C16H12N6O5/c23-21(24)9-1-3-11-13(5-9)...        source_8   \n",
+       "5878  InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...        source_5   \n",
+       "5357  InChI=1S/C23H29N3O2/c1-4-8-18(9-5-2)23(27)24-1...       source_11   \n",
        "\n",
        "     Metadata_Plate Metadata_Well  Cells_AreaShape_Eccentricity  \\\n",
-       "1512   110000293081           E13                       0.76608   \n",
-       "4535       A1170490           C14                       0.78057   \n",
+       "5878      ACPJUM062           K08                       0.85995   \n",
+       "5357      LM37-70_1           M06                       0.74290   \n",
        "\n",
        "      Nuclei_AreaShape_Area  \n",
-       "1512                 794.30  \n",
-       "4535                 711.22  "
+       "5878                 716.30  \n",
+       "5357                 877.81  "
       ]
      },
      "execution_count": 7,
@@ -404,7 +464,7 @@
     }
    ],
    "source": [
-    "ann_dframe.sample(2, random_state=42)"
+    "ann_dframe.sample(2, random_state=42)\n"
    ]
   },
   {
@@ -441,7 +501,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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"
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -456,17 +516,820 @@
     "    y=\"Nuclei_AreaShape_Area\",\n",
     "    color=\"Metadata_Source\",\n",
     "    hover_name=\"Metadata_JCP2022\",\n",
-    "    hover_data=[\"Metadata_InChIKey\"]\n",
+    "    hover_data=[\"Metadata_InChIKey\"],\n",
     ")\n"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "id": "4bfb1c6b",
    "metadata": {},
    "source": [
-    "So that's just a couple of (raw) measurements from the sentinel plates for ~50% of the sources, for the principal dataset alone. \n",
+    "So that's just a couple of (raw) measurements from the sentinel plates for ~66% of the sources, for the principal dataset alone. "
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "5642a156",
+   "metadata": {},
+   "source": [
+    "## Load images\n",
+    "\n",
+    "[LoadData](https://cellprofiler-manual.s3.amazonaws.com/CPmanual/LoadData.html) CSV files provide Metadata associated with the images to be processed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "21a770f0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "load_data = []\n",
+    "for _, row in sample.iterrows():\n",
+    "    s3_path = loaddata_formatter.format(**row.to_dict())\n",
+    "    load_data.append(pd.read_parquet(s3_path, storage_options={\"anon\": True}))\n",
+    "load_data = pd.concat(load_data)\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "43218598",
+   "metadata": {},
+   "source": [
+    "Let's pick a row at random and inspect it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f7323582",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Metadata_Source</td>\n",
+       "      <td>source_11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Metadata_Batch</td>\n",
+       "      <td>Batch5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Metadata_Plate</td>\n",
+       "      <td>LM71-102_1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Metadata_Well</td>\n",
+       "      <td>F09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Metadata_Site</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>FileName_IllumAGP</td>\n",
+       "      <td>LM71-102_1_IllumAGP.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>FileName_IllumDNA</td>\n",
+       "      <td>LM71-102_1_IllumDNA.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>FileName_IllumER</td>\n",
+       "      <td>LM71-102_1_IllumER.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>FileName_IllumMito</td>\n",
+       "      <td>LM71-102_1_IllumMito.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>FileName_IllumRNA</td>\n",
+       "      <td>LM71-102_1_IllumRNA.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>FileName_OrigAGP</td>\n",
+       "      <td>r06c09f04p01-ch3sk1fk1fl1.tiff</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>FileName_OrigDNA</td>\n",
+       "      <td>r06c09f04p01-ch1sk1fk1fl1.tiff</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>FileName_OrigER</td>\n",
+       "      <td>r06c09f04p01-ch2sk1fk1fl1.tiff</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>FileName_OrigMito</td>\n",
+       "      <td>r06c09f04p01-ch5sk1fk1fl1.tiff</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>FileName_OrigRNA</td>\n",
+       "      <td>r06c09f04p01-ch4sk1fk1fl1.tiff</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>PathName_IllumAGP</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>PathName_IllumDNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>PathName_IllumER</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>PathName_IllumMito</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>PathName_IllumRNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>PathName_OrigAGP</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>PathName_OrigDNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>PathName_OrigER</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>PathName_OrigMito</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>PathName_OrigRNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              variable                                              value\n",
+       "0      Metadata_Source                                          source_11\n",
+       "1       Metadata_Batch                                             Batch5\n",
+       "2       Metadata_Plate                                         LM71-102_1\n",
+       "3        Metadata_Well                                                F09\n",
+       "4        Metadata_Site                                                  4\n",
+       "5    FileName_IllumAGP                            LM71-102_1_IllumAGP.npy\n",
+       "6    FileName_IllumDNA                            LM71-102_1_IllumDNA.npy\n",
+       "7     FileName_IllumER                             LM71-102_1_IllumER.npy\n",
+       "8   FileName_IllumMito                           LM71-102_1_IllumMito.npy\n",
+       "9    FileName_IllumRNA                            LM71-102_1_IllumRNA.npy\n",
+       "10    FileName_OrigAGP                     r06c09f04p01-ch3sk1fk1fl1.tiff\n",
+       "11    FileName_OrigDNA                     r06c09f04p01-ch1sk1fk1fl1.tiff\n",
+       "12     FileName_OrigER                     r06c09f04p01-ch2sk1fk1fl1.tiff\n",
+       "13   FileName_OrigMito                     r06c09f04p01-ch5sk1fk1fl1.tiff\n",
+       "14    FileName_OrigRNA                     r06c09f04p01-ch4sk1fk1fl1.tiff\n",
+       "15   PathName_IllumAGP  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "16   PathName_IllumDNA  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "17    PathName_IllumER  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "18  PathName_IllumMito  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "19   PathName_IllumRNA  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "20    PathName_OrigAGP  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "21    PathName_OrigDNA  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "22     PathName_OrigER  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "23   PathName_OrigMito  s3://cellpainting-gallery/cpg0016-jump/source_...\n",
+       "24    PathName_OrigRNA  s3://cellpainting-gallery/cpg0016-jump/source_..."
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_loaddata = load_data.sample(1, random_state=42)\n",
+    "pd.melt(sample_loaddata)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "305b5576",
+   "metadata": {},
+   "source": [
+    "The `Metadata_` columns can be used to link the images to profiles. \n",
+    "Let's pick a profile and view it's corresponding image. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "1bb2961c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Metadata_JCP2022</td>\n",
+       "      <td>JCP2022_109917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Metadata_InChIKey</td>\n",
+       "      <td>YPHMISFOHDHNIV-UHFFFAOYSA-N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Metadata_InChI</td>\n",
+       "      <td>InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Metadata_Source</td>\n",
+       "      <td>source_5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Metadata_Plate</td>\n",
+       "      <td>ACPJUM062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Metadata_Well</td>\n",
+       "      <td>K08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Cells_AreaShape_Eccentricity</td>\n",
+       "      <td>0.85995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Nuclei_AreaShape_Area</td>\n",
+       "      <td>716.3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       variable  \\\n",
+       "0              Metadata_JCP2022   \n",
+       "1             Metadata_InChIKey   \n",
+       "2                Metadata_InChI   \n",
+       "3               Metadata_Source   \n",
+       "4                Metadata_Plate   \n",
+       "5                 Metadata_Well   \n",
+       "6  Cells_AreaShape_Eccentricity   \n",
+       "7         Nuclei_AreaShape_Area   \n",
+       "\n",
+       "                                               value  \n",
+       "0                                     JCP2022_109917  \n",
+       "1                        YPHMISFOHDHNIV-UHFFFAOYSA-N  \n",
+       "2  InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...  \n",
+       "3                                           source_5  \n",
+       "4                                          ACPJUM062  \n",
+       "5                                                K08  \n",
+       "6                                            0.85995  \n",
+       "7                                              716.3  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_profile = ann_dframe.sample(1, random_state=42)\n",
+    "sample_profile.melt()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "9b9a4a99",
+   "metadata": {},
+   "source": [
+    "First link the profile to it's images.\n",
+    "These are well-level profiles, and each well has typically 9 sites imaged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "5121ec3d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Metadata_Well</th>\n",
+       "      <th>Metadata_Site</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>K08</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Metadata_Well Metadata_Site\n",
+       "0           K08             1\n",
+       "1           K08             2\n",
+       "2           K08             3\n",
+       "3           K08             4\n",
+       "4           K08             5\n",
+       "5           K08             6\n",
+       "6           K08             7\n",
+       "7           K08             8\n",
+       "8           K08             9"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_linked = pd.merge(\n",
+    "    load_data, sample_profile, on=[\"Metadata_Source\", \"Metadata_Plate\", \"Metadata_Well\"]\n",
+    ")\n",
+    "sample_linked[['Metadata_Well', 'Metadata_Site']]"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "81a5da16",
+   "metadata": {},
+   "source": [
+    "Inspect details of a single site for this profile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "5f4450d3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Metadata_Source</td>\n",
+       "      <td>source_5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Metadata_Batch</td>\n",
+       "      <td>JUMPCPE-20210716-Run12_20210719_162047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Metadata_Plate</td>\n",
+       "      <td>ACPJUM062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Metadata_Well</td>\n",
+       "      <td>K08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Metadata_Site</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>FileName_IllumAGP</td>\n",
+       "      <td>ACPJUM062_IllumAGP.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>FileName_IllumDNA</td>\n",
+       "      <td>ACPJUM062_IllumDNA.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>FileName_IllumER</td>\n",
+       "      <td>ACPJUM062_IllumER.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>FileName_IllumMito</td>\n",
+       "      <td>ACPJUM062_IllumMito.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>FileName_IllumRNA</td>\n",
+       "      <td>ACPJUM062_IllumRNA.npy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>FileName_OrigAGP</td>\n",
+       "      <td>P01_ACPJUM062_K08_T0001F001L01A04Z01C04.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>FileName_OrigDNA</td>\n",
+       "      <td>P01_ACPJUM062_K08_T0001F001L01A01Z01C01.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>FileName_OrigER</td>\n",
+       "      <td>P01_ACPJUM062_K08_T0001F001L01A02Z01C02.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>FileName_OrigMito</td>\n",
+       "      <td>P01_ACPJUM062_K08_T0001F001L01A05Z01C05.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>FileName_OrigRNA</td>\n",
+       "      <td>P01_ACPJUM062_K08_T0001F001L01A03Z01C03.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>PathName_IllumAGP</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>PathName_IllumDNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>PathName_IllumER</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>PathName_IllumMito</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>PathName_IllumRNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>PathName_OrigAGP</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>PathName_OrigDNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>PathName_OrigER</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>PathName_OrigMito</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>PathName_OrigRNA</td>\n",
+       "      <td>s3://cellpainting-gallery/cpg0016-jump/source_...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>Metadata_JCP2022</td>\n",
+       "      <td>JCP2022_109917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>Metadata_InChIKey</td>\n",
+       "      <td>YPHMISFOHDHNIV-UHFFFAOYSA-N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Metadata_InChI</td>\n",
+       "      <td>InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Cells_AreaShape_Eccentricity</td>\n",
+       "      <td>0.85995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Nuclei_AreaShape_Area</td>\n",
+       "      <td>716.3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        variable  \\\n",
+       "0                Metadata_Source   \n",
+       "1                 Metadata_Batch   \n",
+       "2                 Metadata_Plate   \n",
+       "3                  Metadata_Well   \n",
+       "4                  Metadata_Site   \n",
+       "5              FileName_IllumAGP   \n",
+       "6              FileName_IllumDNA   \n",
+       "7               FileName_IllumER   \n",
+       "8             FileName_IllumMito   \n",
+       "9              FileName_IllumRNA   \n",
+       "10              FileName_OrigAGP   \n",
+       "11              FileName_OrigDNA   \n",
+       "12               FileName_OrigER   \n",
+       "13             FileName_OrigMito   \n",
+       "14              FileName_OrigRNA   \n",
+       "15             PathName_IllumAGP   \n",
+       "16             PathName_IllumDNA   \n",
+       "17              PathName_IllumER   \n",
+       "18            PathName_IllumMito   \n",
+       "19             PathName_IllumRNA   \n",
+       "20              PathName_OrigAGP   \n",
+       "21              PathName_OrigDNA   \n",
+       "22               PathName_OrigER   \n",
+       "23             PathName_OrigMito   \n",
+       "24              PathName_OrigRNA   \n",
+       "25              Metadata_JCP2022   \n",
+       "26             Metadata_InChIKey   \n",
+       "27                Metadata_InChI   \n",
+       "28  Cells_AreaShape_Eccentricity   \n",
+       "29         Nuclei_AreaShape_Area   \n",
+       "\n",
+       "                                                value  \n",
+       "0                                            source_5  \n",
+       "1              JUMPCPE-20210716-Run12_20210719_162047  \n",
+       "2                                           ACPJUM062  \n",
+       "3                                                 K08  \n",
+       "4                                                   1  \n",
+       "5                              ACPJUM062_IllumAGP.npy  \n",
+       "6                              ACPJUM062_IllumDNA.npy  \n",
+       "7                               ACPJUM062_IllumER.npy  \n",
+       "8                             ACPJUM062_IllumMito.npy  \n",
+       "9                              ACPJUM062_IllumRNA.npy  \n",
+       "10        P01_ACPJUM062_K08_T0001F001L01A04Z01C04.tif  \n",
+       "11        P01_ACPJUM062_K08_T0001F001L01A01Z01C01.tif  \n",
+       "12        P01_ACPJUM062_K08_T0001F001L01A02Z01C02.tif  \n",
+       "13        P01_ACPJUM062_K08_T0001F001L01A05Z01C05.tif  \n",
+       "14        P01_ACPJUM062_K08_T0001F001L01A03Z01C03.tif  \n",
+       "15  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "16  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "17  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "18  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "19  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "20  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "21  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "22  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "23  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "24  s3://cellpainting-gallery/cpg0016-jump/source_...  \n",
+       "25                                     JCP2022_109917  \n",
+       "26                        YPHMISFOHDHNIV-UHFFFAOYSA-N  \n",
+       "27  InChI=1S/C15H23NO4/c1-8-3-9(2)15(20)11(4-8)12(...  \n",
+       "28                                            0.85995  \n",
+       "29                                              716.3  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_linked.iloc[:1].melt()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "5ee620aa",
+   "metadata": {},
+   "source": [
+    "Now load and display a single channel of this 5-channel image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "b5ed1058",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'s3://cellpainting-gallery/cpg0016-jump/source_5/images/JUMPCPE-20210716-Run12_20210719_162047/images/P01_ACPJUM062/P01_ACPJUM062_K08_T0001F001L01A01Z01C01.tif'"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import requests\n",
+    "from io import BytesIO\n",
+    "from matplotlib import pyplot as plt\n",
+    "from matplotlib import image as mpimg\n",
+    "import boto3\n",
+    "\n",
+    "image_url = os.path.join(\n",
+    "    sample_linked.iloc[0].PathName_OrigDNA, sample_linked.iloc[0].FileName_OrigDNA\n",
+    ")\n",
+    "s3_client = boto3.client(\"s3\")\n",
+    "response = s3_client.get_object(\n",
+    "    Bucket=image_url.split(\"/\")[2], Key=\"/\".join(image_url.split(\"/\")[3:])\n",
+    ")\n",
+    "image = mpimg.imread(BytesIO(response[\"Body\"].read()), format=\"tiff\")\n",
     "\n",
+    "plt.imshow(image, cmap=\"gray\")\n",
+    "image_url\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "9a82a8ac",
+   "metadata": {},
+   "source": [
     "There's a lot more to come! We will add more example notebooks as we go."
    ]
   }