diff --git a/notebooks/SDSS/APOGEE_TESS_tutorial/APOGEE_TESS_tutorial.ipynb b/notebooks/SDSS/APOGEE_TESS_tutorial/APOGEE_TESS_tutorial.ipynb
index 25d55bd3..a7b9436d 100644
--- a/notebooks/SDSS/APOGEE_TESS_tutorial/APOGEE_TESS_tutorial.ipynb
+++ b/notebooks/SDSS/APOGEE_TESS_tutorial/APOGEE_TESS_tutorial.ipynb
@@ -613,23 +613,20 @@
     "            \n",
     "    plt.colorbar(im, ax=ax1, location='bottom', label='Metallicity [Fe/H]')\n",
     "            \n",
-    "            \n",
     "    # Plot the specific star\n",
     "    indx = np.where(allstar['APOGEE_ID'] == apogee_spec[4].data['APOGEE_ID'][0])[0][0]\n",
     "    if allstar['TEFF'][indx]: # if the star has valid apogee parameters\n",
-    "        ax1.scatter(allstar['TEFF'][indx], allstar['LOGG'][indx],c=allstar['FE_H'][indx],\n",
-    "                    marker='*',s=1000, cmap='jet', edgecolor='k', lw=2,\n",
-    "                    vmin=-1,vmax=0.5, zorder=5, label='APOGEE Parameters')\n",
+    "        ax1.scatter(allstar['TEFF'][indx], allstar['LOGG'][indx], c=allstar['FE_H'][indx],\n",
+    "                    marker='*', s=1000, cmap='jet', edgecolor='k', lw=2,\n",
+    "                    vmin=-1, vmax=0.5, zorder=5, label='APOGEE Parameters')\n",
     "    else: # params from aspcapstar (uncalibrated)\n",
     "        print('WARNING: Quality Warning Flags on ASPCAP star parameters. ASPCAP parameters may not be reliable for this star.')\n",
     "        ax1.scatter(apogee_spec[4].data['FPARAM'][0][0], apogee_spec[4].data['FPARAM'][0][1], c=apogee_spec[4].data['FPARAM'][0][3],\n",
     "                    marker='*', s=1000, cmap='jet', edgecolor='k', lw=2, vmin=-1, vmax=0.5, zorder=5, label='APOGEE Parameters')\n",
-    "       \n",
-    "    \n",
-    "            \n",
+    "                \n",
     "    # Labels and titles\n",
     "    ax1.set_xlim(7000, 3000)\n",
-    "    ax1.set_ylim(5.5 -0.5)\n",
+    "    ax1.set_ylim(5.5, -0.5)\n",
     "    ax1.set_xlabel(r'Effective Temperature [$T_{\\rm{eff}}$, K]')\n",
     "    ax1.set_ylabel(r'Surface Gravity [$\\log(g)$]')\n",
     "    ax1.grid()\n",
@@ -651,10 +648,9 @@
     "    # Plot the model spectrum\n",
     "    ax2.plot(apogee_wls[pixel_mask], model_flux[pixel_mask], c='darkred', label='Best Fit Model Spectrum')\n",
     "    \n",
-    "    \n",
     "    # Set axes limits\n",
-    "    ax2.set_ylim(0.6,1.1)\n",
-    "    ax2.set_xlim(np.min(apogee_wls),np.max(apogee_wls))\n",
+    "    ax2.set_ylim(0.6, 1.1)\n",
+    "    ax2.set_xlim(np.min(apogee_wls), np.max(apogee_wls))\n",
     "    \n",
     "    apogee_id = apogee_spec[4].data['APOGEE_ID'][0] # String containing star's name\n",
     "    ax2.set_title(f\"APOGEE Spectrum - {apogee_id}\")\n",
@@ -762,11 +758,10 @@
     "                                           radius=(1/60/60)*u.deg, # search within 1 arcsecond\n",
     "                                           obs_collection='TESS', # Search for TESS observations\n",
     "                                           intentType='science', # Select only Science observations (not calibration files)\n",
-    "                                           dataproduct_type = 'timeseries', dataURL = \"*lc.fits\") # Search for time series data (light curves)\n",
-    "\n",
+    "                                           dataproduct_type='timeseries', dataURL=\"*lc.fits\") # Search for time series data (light curves)\n",
     "\n",
     "    # Pick closest match by distance\n",
-    "    tess_obs=tess_obs[np.argmin(tess_obs['distance'])]\n",
+    "    tess_obs = tess_obs[np.argmin(tess_obs['distance'])]\n",
     "\n",
     "    # Download TESS Light Curve\n",
     "    print(\"Downloading TESS Data...\")\n",