diff --git a/examples/demo_coordinate_system.ipynb b/examples/demo_coordinate_system.ipynb
index e034fc9a2..0ba689190 100644
--- a/examples/demo_coordinate_system.ipynb
+++ b/examples/demo_coordinate_system.ipynb
@@ -171,7 +171,7 @@
        "<br> <b>and pzpdf:</b> shared_bins [ 0.    0.01  0.02  0.03  0.04 ...  9.96  9.97  9.98  9.99 10.  ]\n",
        "<br> 5 objects\n",
        "<br> \n",
-       "<table id=\"table139982163318272\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140158865710992\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>e1</th><th>e2</th><th>z</th><th>ztrue</th><th>pzpdf</th><th>id</th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64[1001]</th><th>int64</th></tr></thead>\n",
        "<tr><td>47.723234904384796</td><td>87.0656774075493</td><td>-0.011529738473189206</td><td>-0.02040149427643137</td><td>3.1805837221695556</td><td>3.043830614065144</td><td>3.647766317906808e-54 .. 1.9074233381687797e-247</td><td>0</td></tr>\n",
@@ -209,7 +209,7 @@
        "<br> <b>and pzpdf:</b> shared_bins [ 0.    0.01  0.02  0.03  0.04 ...  9.96  9.97  9.98  9.99 10.  ]\n",
        "<br> 5 objects\n",
        "<br> \n",
-       "<table id=\"table139982163313664\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140158865706768\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>e1</th><th>e2</th><th>z</th><th>ztrue</th><th>pzpdf</th><th>id</th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64[1001]</th><th>int64</th></tr></thead>\n",
        "<tr><td>47.723234904384796</td><td>87.0656774075493</td><td>-0.011529738473189206</td><td>0.02040149427643137</td><td>3.1805837221695556</td><td>3.043830614065144</td><td>3.647766317906808e-54 .. 1.9074233381687797e-247</td><td>0</td></tr>\n",
@@ -306,7 +306,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f5022860730>"
+       "<matplotlib.legend.Legend at 0x7f7946ce5db0>"
       ]
      },
      "execution_count": 16,
@@ -448,7 +448,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f502318fbe0>"
+       "<matplotlib.legend.Legend at 0x7f7946bdc580>"
       ]
      },
      "execution_count": 19,
@@ -491,7 +491,7 @@
      "data": {
       "text/html": [
        "<i>GCData length=10</i>\n",
-       "<table id=\"table139982147778016-84682\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140158854044624-84682\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>idx</th><th>radius_min</th><th>radius</th><th>radius_max</th><th>gt</th><th>gt_err</th><th>gx</th><th>gx_err</th><th>z</th><th>z_err</th><th>n_src</th><th>W_l</th></tr></thead>\n",
        "<tr><td>0</td><td>156.71960928359934</td><td>464.4671603593981</td><td>699.5921737891952</td><td>0.06413360677252622</td><td>0.004914333288851318</td><td>-1.715010709204343e-17</td><td>4.034498594037631e-18</td><td>1.0911552118175314</td><td>0.11083918127320175</td><td>22</td><td>22.0</td></tr>\n",
        "<tr><td>1</td><td>699.5921737891952</td><td>1011.2963458867513</td><td>1242.464738294791</td><td>0.039642488178504826</td><td>0.0016015681719071773</td><td>-1.50965113609602e-17</td><td>1.4037968563596243e-18</td><td>1.340843180212603</td><td>0.09927515578213908</td><td>54</td><td>54.0</td></tr>\n",
@@ -526,14 +526,14 @@
        "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
        "}});\n",
        "require([\"datatables\"], function(){\n",
-       "    console.log(\"$('#table139982147778016-84682').dataTable()\");\n",
+       "    console.log(\"$('#table140158854044624-84682').dataTable()\");\n",
        "    \n",
        "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
        "    \"optionalnum-asc\": astropy_sort_num,\n",
        "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
        "});\n",
        "\n",
-       "    $('#table139982147778016-84682').dataTable({\n",
+       "    $('#table140158854044624-84682').dataTable({\n",
        "        order: [],\n",
        "        pageLength: 50,\n",
        "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
@@ -567,7 +567,7 @@
      "data": {
       "text/html": [
        "<i>GCData length=10</i>\n",
-       "<table id=\"table139982147772688-858330\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140158850345632-858330\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>idx</th><th>radius_min</th><th>radius</th><th>radius_max</th><th>gt</th><th>gt_err</th><th>gx</th><th>gx_err</th><th>z</th><th>z_err</th><th>n_src</th><th>W_l</th></tr></thead>\n",
        "<tr><td>0</td><td>156.71960928359934</td><td>464.4671603593981</td><td>699.5921737891952</td><td>0.06413360677252622</td><td>0.004914333288851318</td><td>3.236836304038542e-17</td><td>5.694604839281488e-18</td><td>1.0911552118175314</td><td>0.11083918127320175</td><td>22</td><td>22.0</td></tr>\n",
        "<tr><td>1</td><td>699.5921737891952</td><td>1011.2963458867513</td><td>1242.464738294791</td><td>0.039642488178504826</td><td>0.0016015681719071773</td><td>2.3942797975721554e-17</td><td>1.7339256407665797e-18</td><td>1.340843180212603</td><td>0.09927515578213908</td><td>54</td><td>54.0</td></tr>\n",
@@ -602,14 +602,14 @@
        "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
        "}});\n",
        "require([\"datatables\"], function(){\n",
-       "    console.log(\"$('#table139982147772688-858330').dataTable()\");\n",
+       "    console.log(\"$('#table140158850345632-858330').dataTable()\");\n",
        "    \n",
        "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
        "    \"optionalnum-asc\": astropy_sort_num,\n",
        "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
        "});\n",
        "\n",
-       "    $('#table139982147772688-858330').dataTable({\n",
+       "    $('#table140158850345632-858330').dataTable({\n",
        "        order: [],\n",
        "        pageLength: 50,\n",
        "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
@@ -783,11 +783,455 @@
     "### => Now the profiles are correct. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a5a7d1c8-1f41-40a8-987e-1834e1ae4b28",
+   "metadata": {},
+   "source": [
+    "## Same thing for Delta Sigma profiles"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "id": "84446929-dc27-4418-87c3-ecc119e3cc9e",
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/cosmology/parent_class.py:110: UserWarning: \n",
+      "Some source redshifts are lower than the cluster redshift.\n",
+      "Sigma_crit = np.inf for those galaxies.\n",
+      "  return compute_for_good_redshifts(\n",
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/dataops/__init__.py:174: RuntimeWarning: invalid value encountered in multiply\n",
+      "  cross_comp *= _sigma_c_arr\n"
+     ]
+    }
+   ],
+   "source": [
+    "cl_euclidean.compute_tangential_and_cross_components(\n",
+    "    shape_component1=\"e1\",\n",
+    "    shape_component2=\"e2\",\n",
+    "    tan_component=\"DeltaSigma_tan\",\n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "    add=True,\n",
+    "    cosmo=cosmo,\n",
+    "    is_deltasigma=True,\n",
+    ");\n",
+    "\n",
+    "#cl_euclidean.profile.show_in_notebook()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "e69ba994-e45b-4255-b639-b11735ca7866",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cl_euclidean.make_radial_profile(\n",
+    "    \"Mpc\",\n",
+    "    cosmo=cosmo,\n",
+    "    tan_component_in=\"DeltaSigma_tan\",\n",
+    "    cross_component_in=\"DeltaSigma_cross\",\n",
+    "    tan_component_out=\"DeltaSigma_tan\",\n",
+    "    cross_component_out=\"DeltaSigma_cross\",\n",
+    "    table_name=\"DeltaSigma_profile\",\n",
+    "    use_weights=False,\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "5d9307d8-88dc-43fe-8e85-aed47f574282",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig1, ax1 = cl_euclidean.plot_profiles(tangential_component=\"DeltaSigma_tan\",\n",
+    "                                       cross_component=\"DeltaSigma_cross\", \n",
+    "                                       tangential_component_error=\"DeltaSigma_tan_err\", \n",
+    "                                       cross_component_error=\"DeltaSigma_cross_err\",\n",
+    "                                       table_name=\"DeltaSigma_profile\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "18834199-201d-4f17-8558-1c6236515211",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/cosmology/parent_class.py:110: UserWarning: \n",
+      "Some source redshifts are lower than the cluster redshift.\n",
+      "Sigma_crit = np.inf for those galaxies.\n",
+      "  return compute_for_good_redshifts(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cl_celestial.compute_tangential_and_cross_components(\n",
+    "    shape_component1=\"e1\",\n",
+    "    shape_component2=\"e2\",\n",
+    "    tan_component=\"DeltaSigma_tan\",\n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "    add=True,\n",
+    "    cosmo=cosmo,\n",
+    "    is_deltasigma=True,\n",
+    ");\n",
+    "\n",
+    "cl_celestial.make_radial_profile(\n",
+    "    \"Mpc\",\n",
+    "    cosmo=cosmo,\n",
+    "    tan_component_in=\"DeltaSigma_tan\",\n",
+    "    cross_component_in=\"DeltaSigma_cross\",\n",
+    "    tan_component_out=\"DeltaSigma_tan\",\n",
+    "    cross_component_out=\"DeltaSigma_cross\",\n",
+    "    table_name=\"DeltaSigma_profile\",\n",
+    "    use_weights=False,\n",
+    ");\n",
+    "\n",
+    "fig2, ax2 = cl_celestial.plot_profiles(\n",
+    "    tangential_component=\"DeltaSigma_tan\", \n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "        tangential_component_error=\"DeltaSigma_tan_err\", \n",
+    "    cross_component_error=\"DeltaSigma_cross_err\",\n",
+    "    table_name=\"DeltaSigma_profile\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "63ce64f4-b8ea-44a8-a34e-a2f875bdcc2a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/galaxycluster.py:630: UserWarning: overwriting DeltaSigma_profile table.\n",
+      "  warnings.warn(f\"overwriting {table_name} table.\")\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cl_wrong_coordinate.compute_tangential_and_cross_components(\n",
+    "    shape_component1=\"e1\",\n",
+    "    shape_component2=\"e2\",\n",
+    "    tan_component=\"DeltaSigma_tan\",\n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "    add=True,\n",
+    "    cosmo=cosmo,\n",
+    "    is_deltasigma=True,\n",
+    ");\n",
+    "\n",
+    "cl_wrong_coordinate.make_radial_profile(\n",
+    "    \"Mpc\",\n",
+    "    cosmo=cosmo,\n",
+    "    tan_component_in=\"DeltaSigma_tan\",\n",
+    "    cross_component_in=\"DeltaSigma_cross\",\n",
+    "    tan_component_out=\"DeltaSigma_tan\",\n",
+    "    cross_component_out=\"DeltaSigma_cross\",\n",
+    "    table_name=\"DeltaSigma_profile\",\n",
+    "    use_weights=False,\n",
+    ");\n",
+    "\n",
+    "fig2, ax2 = cl_wrong_coordinate.plot_profiles(\n",
+    "    tangential_component=\"DeltaSigma_tan\", \n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "    tangential_component_error=\"DeltaSigma_tan_err\", \n",
+    "    cross_component_error=\"DeltaSigma_cross_err\",\n",
+    "    table_name=\"DeltaSigma_profile\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "591d800d-8316-4c70-b415-09a73e6b2574",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/cosmology/parent_class.py:110: UserWarning: \n",
+      "Some source redshifts are lower than the cluster redshift.\n",
+      "Sigma_crit = np.inf for those galaxies.\n",
+      "  return compute_for_good_redshifts(\n"
+     ]
+    }
+   ],
+   "source": [
+    "sigma_c = cosmo.eval_sigma_crit(cl_wrong_coordinate.z, cl_wrong_coordinate.galcat['z'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "2fed7d27-b626-4a7e-bf24-317bad5a888c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#to recover the correct profile we need to compute the quantities outside of \n",
+    "#the GalaxyCluster object and add them back as galcat column in the GalacyCluster object\n",
+    "\n",
+    "#ideally, we would like to just do \n",
+    "#cl_wrong_coordinate.compute_tangential_and_cross_components(coordinate_system='celestial', add=True)\n",
+    "#but this does not work at the moment\n",
+    "\n",
+    "theta, dstan, dscross = compute_tangential_and_cross_components(\n",
+    "    cl_wrong_coordinate.ra, cl_wrong_coordinate.dec, \n",
+    "    cl_wrong_coordinate.galcat['ra'],cl_wrong_coordinate.galcat['dec'], \n",
+    "    cl_wrong_coordinate.galcat['e1'],cl_wrong_coordinate.galcat['e2'],\n",
+    "    coordinate_system='celestial', \n",
+    "    is_deltasigma=True,\n",
+    "    sigma_c = sigma_c )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "f8248bda-030a-47aa-8733-a43b37ef7a78",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cl_wrong_coordinate.galcat.add_column(dstan,name='DeltaSigma_tan_celestial')\n",
+    "cl_wrong_coordinate.galcat.add_column(dscross,name='DeltaSigma_cross_celestial')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "46c8bd61-5959-4c7b-b7b9-dd35511e495f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/pbs/home/m/mricci/.conda/envs/clmm/lib/python3.10/site-packages/clmm/galaxycluster.py:630: UserWarning: overwriting DeltaSigma_profile table.\n",
+      "  warnings.warn(f\"overwriting {table_name} table.\")\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<b>GCData</b>\n",
+       "<br> <b>defined by:</b> cosmo='CCLCosmology(H0=70.0, Omega_dm0=0.22500000000000003, Omega_b0=0.045, Omega_k0=0.0)', bin_units='Mpc'\n",
+       "<br> <b>with columns:</b> radius_min, radius, radius_max, DeltaSigma_tan, DeltaSigma_tan_err, DeltaSigma_cross, DeltaSigma_cross_err, z, z_err, n_src, W_l\n",
+       "<br> 10 objects\n",
+       "<br> \n",
+       "<table id=\"table140158846394832\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<thead><tr><th>radius_min</th><th>radius</th><th>radius_max</th><th>DeltaSigma_tan</th><th>DeltaSigma_tan_err</th><th>DeltaSigma_cross</th><th>DeltaSigma_cross_err</th><th>z</th><th>z_err</th><th>n_src</th><th>W_l</th></tr></thead>\n",
+       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th></tr></thead>\n",
+       "<tr><td>0.15671960928359935</td><td>0.46446716035939806</td><td>0.6995921737891952</td><td>190051501875241.06</td><td>9649983174328.586</td><td>0.09215345961649268</td><td>0.015270074502458262</td><td>1.0911552118175314</td><td>0.11083918127320175</td><td>22</td><td>22.0</td></tr>\n",
+       "<tr><td>0.6995921737891952</td><td>1.0112963458867514</td><td>1.242464738294791</td><td>114653094293426.97</td><td>2898979264141.766</td><td>0.06784158721185626</td><td>0.004167236144654282</td><td>1.340843180212603</td><td>0.09927515578213908</td><td>54</td><td>54.0</td></tr>\n",
+       "<tr><td>1.242464738294791</td><td>1.546819799803977</td><td>1.785337302800387</td><td>76228503835158.64</td><td>1289719458562.2153</td><td>0.04429997672191164</td><td>0.002370525789413681</td><td>1.141074816459248</td><td>0.07695590512125049</td><td>75</td><td>75.0</td></tr>\n",
+       "<tr><td>1.785337302800387</td><td>2.0639912174507593</td><td>2.328209867305983</td><td>58120008332907.984</td><td>1534873725602.767</td><td>0.03498729466831276</td><td>0.0016337497972184402</td><td>1.1760684211114605</td><td>0.05471300278442932</td><td>125</td><td>125.0</td></tr>\n",
+       "<tr><td>2.328209867305983</td><td>2.584348460286765</td><td>2.871082431811579</td><td>43811132825732.35</td><td>818536036351.0841</td><td>0.027372871133279072</td><td>0.001264376953028166</td><td>1.2143592720456875</td><td>0.054067348171772577</td><td>138</td><td>138.0</td></tr>\n",
+       "<tr><td>2.871082431811579</td><td>3.1541249537829494</td><td>3.4139549963171745</td><td>34918820509793.312</td><td>715700841252.0444</td><td>0.02161699742545974</td><td>0.0006777947504387136</td><td>1.2083318981155682</td><td>0.05274388342400906</td><td>192</td><td>192.0</td></tr>\n",
+       "<tr><td>3.4139549963171745</td><td>3.6807344103619006</td><td>3.95682756082277</td><td>27867318283193.94</td><td>288016404616.3745</td><td>0.01764751408471792</td><td>0.0006936147755028247</td><td>1.311099393646099</td><td>0.05334127819405377</td><td>177</td><td>177.0</td></tr>\n",
+       "<tr><td>3.95682756082277</td><td>4.1857905887279125</td><td>4.499700125328366</td><td>23676492252914.723</td><td>325892892395.3659</td><td>0.013206030331073563</td><td>0.0006652124116508021</td><td>1.2856917023015786</td><td>0.07887750338660866</td><td>121</td><td>121.0</td></tr>\n",
+       "<tr><td>4.499700125328366</td><td>4.733676256494335</td><td>5.042572689833962</td><td>20277822255721.855</td><td>348381428571.66223</td><td>0.01301421018866444</td><td>0.0009175728511681354</td><td>1.3173896415983801</td><td>0.08741388146537891</td><td>67</td><td>67.0</td></tr>\n",
+       "<tr><td>5.042572689833962</td><td>5.250313838563014</td><td>5.585445254339558</td><td>17285265196381.973</td><td>417833907597.3777</td><td>0.009340141033264028</td><td>0.0008101011774997349</td><td>1.195583526441637</td><td>0.1086754688799238</td><td>29</td><td>29.0</td></tr>\n",
+       "</table></div>"
+      ],
+      "text/plain": [
+       "GCData(cosmo='CCLCosmology(H0=70.0, Omega_dm0=0.22500000000000003, Omega_b0=0.045, Omega_k0=0.0)', bin_units='Mpc', columns: radius_min, radius, radius_max, DeltaSigma_tan, DeltaSigma_tan_err, DeltaSigma_cross, DeltaSigma_cross_err, z, z_err, n_src, W_l)"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cl_wrong_coordinate.make_radial_profile(\"Mpc\",\n",
+    "    cosmo=cosmo,\n",
+    "    tan_component_in=\"DeltaSigma_tan_celestial\",\n",
+    "    cross_component_in=\"DeltaSigma_cross_celestial\",\n",
+    "    tan_component_out=\"DeltaSigma_tan\",\n",
+    "    cross_component_out=\"DeltaSigma_cross\",\n",
+    "    table_name=\"DeltaSigma_profile\",\n",
+    "    use_weights=False,)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "e300fcc2-ed7d-4ed1-ac63-9586375d0ee8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<b>GCData</b>\n",
+       "<br> <b>defined by:</b> cosmo='CCLCosmology(H0=70.0, Omega_dm0=0.22500000000000003, Omega_b0=0.045, Omega_k0=0.0)', bin_units='Mpc'\n",
+       "<br> <b>with columns:</b> radius_min, radius, radius_max, DeltaSigma_tan, DeltaSigma_tan_err, DeltaSigma_cross, DeltaSigma_cross_err, z, z_err, n_src, W_l\n",
+       "<br> 10 objects\n",
+       "<br> \n",
+       "<table id=\"table140158846394832\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<thead><tr><th>radius_min</th><th>radius</th><th>radius_max</th><th>DeltaSigma_tan</th><th>DeltaSigma_tan_err</th><th>DeltaSigma_cross</th><th>DeltaSigma_cross_err</th><th>z</th><th>z_err</th><th>n_src</th><th>W_l</th></tr></thead>\n",
+       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th></tr></thead>\n",
+       "<tr><td>0.15671960928359935</td><td>0.46446716035939806</td><td>0.6995921737891952</td><td>190051501875241.06</td><td>9649983174328.586</td><td>0.09215345961649268</td><td>0.015270074502458262</td><td>1.0911552118175314</td><td>0.11083918127320175</td><td>22</td><td>22.0</td></tr>\n",
+       "<tr><td>0.6995921737891952</td><td>1.0112963458867514</td><td>1.242464738294791</td><td>114653094293426.97</td><td>2898979264141.766</td><td>0.06784158721185626</td><td>0.004167236144654282</td><td>1.340843180212603</td><td>0.09927515578213908</td><td>54</td><td>54.0</td></tr>\n",
+       "<tr><td>1.242464738294791</td><td>1.546819799803977</td><td>1.785337302800387</td><td>76228503835158.64</td><td>1289719458562.2153</td><td>0.04429997672191164</td><td>0.002370525789413681</td><td>1.141074816459248</td><td>0.07695590512125049</td><td>75</td><td>75.0</td></tr>\n",
+       "<tr><td>1.785337302800387</td><td>2.0639912174507593</td><td>2.328209867305983</td><td>58120008332907.984</td><td>1534873725602.767</td><td>0.03498729466831276</td><td>0.0016337497972184402</td><td>1.1760684211114605</td><td>0.05471300278442932</td><td>125</td><td>125.0</td></tr>\n",
+       "<tr><td>2.328209867305983</td><td>2.584348460286765</td><td>2.871082431811579</td><td>43811132825732.35</td><td>818536036351.0841</td><td>0.027372871133279072</td><td>0.001264376953028166</td><td>1.2143592720456875</td><td>0.054067348171772577</td><td>138</td><td>138.0</td></tr>\n",
+       "<tr><td>2.871082431811579</td><td>3.1541249537829494</td><td>3.4139549963171745</td><td>34918820509793.312</td><td>715700841252.0444</td><td>0.02161699742545974</td><td>0.0006777947504387136</td><td>1.2083318981155682</td><td>0.05274388342400906</td><td>192</td><td>192.0</td></tr>\n",
+       "<tr><td>3.4139549963171745</td><td>3.6807344103619006</td><td>3.95682756082277</td><td>27867318283193.94</td><td>288016404616.3745</td><td>0.01764751408471792</td><td>0.0006936147755028247</td><td>1.311099393646099</td><td>0.05334127819405377</td><td>177</td><td>177.0</td></tr>\n",
+       "<tr><td>3.95682756082277</td><td>4.1857905887279125</td><td>4.499700125328366</td><td>23676492252914.723</td><td>325892892395.3659</td><td>0.013206030331073563</td><td>0.0006652124116508021</td><td>1.2856917023015786</td><td>0.07887750338660866</td><td>121</td><td>121.0</td></tr>\n",
+       "<tr><td>4.499700125328366</td><td>4.733676256494335</td><td>5.042572689833962</td><td>20277822255721.855</td><td>348381428571.66223</td><td>0.01301421018866444</td><td>0.0009175728511681354</td><td>1.3173896415983801</td><td>0.08741388146537891</td><td>67</td><td>67.0</td></tr>\n",
+       "<tr><td>5.042572689833962</td><td>5.250313838563014</td><td>5.585445254339558</td><td>17285265196381.973</td><td>417833907597.3777</td><td>0.009340141033264028</td><td>0.0008101011774997349</td><td>1.195583526441637</td><td>0.1086754688799238</td><td>29</td><td>29.0</td></tr>\n",
+       "</table></div>"
+      ],
+      "text/plain": [
+       "GCData(cosmo='CCLCosmology(H0=70.0, Omega_dm0=0.22500000000000003, Omega_b0=0.045, Omega_k0=0.0)', bin_units='Mpc', columns: radius_min, radius, radius_max, DeltaSigma_tan, DeltaSigma_tan_err, DeltaSigma_cross, DeltaSigma_cross_err, z, z_err, n_src, W_l)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cl_wrong_coordinate.DeltaSigma_profile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "03cb3671-63ab-4e11-939b-e8c2d0d6ee60",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<ErrorbarContainer object of 3 artists>"
+      ]
+     },
+     "execution_count": 37,
+     "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": [
+    "fig3, ax3 = cl_wrong_coordinate.plot_profiles(\n",
+    "    tangential_component=\"DeltaSigma_tan\", \n",
+    "    cross_component=\"DeltaSigma_cross\",\n",
+    "    tangential_component_error=\"DeltaSigma_tan_err\", \n",
+    "    cross_component_error=\"DeltaSigma_cross_err\",\n",
+    "    table_name=\"DeltaSigma_profile\")\n",
+    "\n",
+    "\n",
+    "ax3.errorbar(cl_celestial.DeltaSigma_profile['radius']*1.02, cl_celestial.DeltaSigma_profile['DeltaSigma_tan'],\n",
+    "            yerr= cl_celestial.DeltaSigma_profile['DeltaSigma_tan_err'],alpha=0.3)\n",
+    "\n",
+    "ax3.errorbar(cl_celestial.DeltaSigma_profile['radius']*1.02, cl_celestial.DeltaSigma_profile['DeltaSigma_cross'],\n",
+    "            yerr= cl_celestial.DeltaSigma_profile['DeltaSigma_cross_err'],alpha=0.3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bebded34-7b95-4df6-a3a9-b64b31e64f43",
+   "metadata": {},
+   "source": [
+    "### => Similarly, we recover correct profiles, but not sure this olds when accounting for weights. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "c9ffcb49-b6fb-46f1-b29b-9cf8f2ccaf9d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Column name='DeltaSigma_tan' dtype='float64' length=10>\n",
+       " 190051501875241.06\n",
+       " 114653094293426.97\n",
+       "  76228503835158.64\n",
+       " 58120008332907.984\n",
+       "  43811132825732.35\n",
+       " 34918820509793.312\n",
+       "  27867318283193.94\n",
+       " 23676492252914.723\n",
+       " 20277822255721.855\n",
+       " 17285265196381.973,\n",
+       " <Column name='DeltaSigma_tan' dtype='float64' length=10>\n",
+       " 190051501875241.06\n",
+       " 114653094293426.97\n",
+       "  76228503835158.64\n",
+       " 58120008332907.984\n",
+       "  43811132825732.35\n",
+       " 34918820509793.312\n",
+       "  27867318283193.94\n",
+       " 23676492252914.723\n",
+       " 20277822255721.855\n",
+       " 17285265196381.973)"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cl_celestial.DeltaSigma_profile['DeltaSigma_tan'],cl_wrong_coordinate.DeltaSigma_profile['DeltaSigma_tan']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c71893c8-dadf-40ce-85a3-f63a5c6a5edc",
+   "metadata": {},
    "outputs": [],
    "source": []
   }