diff --git a/notebooks/api/01_utils.ipynb b/notebooks/api/01_utils.ipynb
index 5152153..242206f 100644
--- a/notebooks/api/01_utils.ipynb
+++ b/notebooks/api/01_utils.ipynb
@@ -762,9 +762,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "plpy",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/api/02a_pds.indexes.ipynb b/notebooks/api/02a_pds.indexes.ipynb
index ef6c98f..400e1ff 100644
--- a/notebooks/api/02a_pds.indexes.ipynb
+++ b/notebooks/api/02a_pds.indexes.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "latest-oakland",
    "metadata": {},
    "outputs": [],
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "nervous-hunter",
    "metadata": {},
    "outputs": [],
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "commercial-pension",
    "metadata": {},
    "outputs": [],
@@ -42,7 +42,7 @@
     "from datetime import datetime\n",
     "from urllib.parse import urlsplit, urlunsplit\n",
     "from urllib.request import URLError\n",
-    "\n",
+    "from dask import dataframe as dd\n",
     "import tomlkit as toml\n",
     "from dateutil import parser\n",
     "from dateutil.parser import ParserError\n",
@@ -55,7 +55,7 @@
     "from planetarypy.config import config\n",
     "from planetarypy.pds.ctx_index import CTXIndex\n",
     "from planetarypy.pds.lroc_index import LROCIndex\n",
-    "from planetarypy.pds.utils import IndexLabel, fix_hirise_edrcumindex\n",
+    "from planetarypy.pds.utils import IndexLabel, fix_hirise_edrcumindex, convert_times\n",
     "\n",
     "logger = logging.getLogger(__name__)\n",
     "\n",
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "3bfb2fdb-fa60-4ab1-80a0-e847d0d95a74",
    "metadata": {},
    "outputs": [],
@@ -75,17 +75,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
+   "id": "0e87c9bf-dee7-422b-94a1-88fc5a56ac4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| hide\n",
+    "pd.set_option('display.max_columns', 100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
    "id": "welcome-humanitarian",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Path('/home/ayek72/mnt/slowdata/planetarypy')"
+       "Path('/media/ayek72/data/planetarypy')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -97,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "developed-entertainment",
    "metadata": {},
    "outputs": [],
@@ -233,14 +244,17 @@
     "    def label(self):\n",
     "        return IndexLabel(self.local_label_path)\n",
     "\n",
-    "    def read_index_data(self, convert_times=True):\n",
-    "        df = self.label.read_index_data(convert_times=convert_times)\n",
+    "    def read_index_data(self, do_convert_times=True):\n",
+    "        df = self.label.read_index_data(do_convert_times=do_convert_times)\n",
     "        return df\n",
     "\n",
     "    def convert_to_parquet(self):\n",
+    "        print(\"Reading index to memory for conversion to parquet. Will take up lots of memory for a bit.\")\n",
     "        df = self.read_index_data()\n",
     "        df = df.convert_dtypes()\n",
+    "        print(\"Storing into parquet.\")\n",
     "        df.to_parquet(self.local_parq_path)\n",
+    "        print(\"Finished. Enjoy your freshly baked PDS Index. :\")\n",
     "\n",
     "    def __str__(self):\n",
     "        s = f\"Key: {self.key}\\n\"\n",
@@ -254,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "865aff5d-e3eb-4e6a-8952-8992f7b70800",
    "metadata": {},
    "outputs": [],
@@ -279,14 +293,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "74b468af-9fb1-46e6-ae49-7769af8ed57b",
    "metadata": {},
    "outputs": [],
    "source": [
     "#| export\n",
     "@patch\n",
-    "def download(self:Index):\n",
+    "def download(\n",
+    "    self:Index,  # the Index object defined in this module\n",
+    "    convert_to_parquet:bool=True,  # set to False if you just want download the files\n",
+    "):\n",
     "    \"\"\"Wrapping URLs for downloading PDS indices and their label files.\"\"\"\n",
     "    # check timestamp\n",
     "    label_url = self.url\n",
@@ -295,22 +312,23 @@
     "    logger.info(\"Downloading %s.\", self.table_url)\n",
     "    utils.url_retrieve(self.table_url, self.local_table_path)\n",
     "    print(f\"Downloaded {self.local_label_path} and {self.local_table_path}\")\n",
-    "    if (\n",
-    "        self.key == \"missions.mro.hirise.indexes.edr\"\n",
-    "    ):  # HiRISE EDR index is broken on the PDS. Team knows.\n",
-    "        print(\"Fixing broken EDR index...\")\n",
-    "        fix_hirise_edrcumindex(\n",
-    "            self.local_table_path, self.local_table_path.with_name(\"temp.tab\")\n",
-    "        )\n",
-    "        self.local_table_path.with_name(\"temp.tab\").rename(self.local_table_path)\n",
+    "    # if (\n",
+    "    #     self.key == \"missions.mro.hirise.indexes.edr\"\n",
+    "    # ):  # HiRISE EDR index is broken on the PDS. Team knows.\n",
+    "    #     print(\"Fixing broken EDR index...\")\n",
+    "    #     fix_hirise_edrcumindex(\n",
+    "    #         self.local_table_path, self.local_table_path.with_name(\"temp.tab\")\n",
+    "    #     )\n",
+    "    #     self.local_table_path.with_name(\"temp.tab\").rename(self.local_table_path)\n",
     "    self.timestamp = self.remote_timestamp\n",
     "    self.update_timestamp()\n",
-    "    self.convert_to_parquet()"
+    "    if convert_to_parquet:\n",
+    "        self.convert_to_parquet()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "329db7ae-b55a-4b0c-b59a-f7755726b5a1",
    "metadata": {},
    "outputs": [],
@@ -327,30 +345,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "4de51298-40f3-475d-9bdf-24d6a110c82e",
    "metadata": {},
    "outputs": [],
    "source": [
     "key = \"missions.cassini.iss.indexes.moon_summary\"\n",
-    "key = \"missions.lro.lroc.edr\""
+    "key = \"missions.mro.hirise.edr\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "238e9b89-c0f9-4548-a641-e1a070454f1f",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Key: missions.lro.lroc.indexes.edr\n",
-       "URL: http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL\n",
-       "Timestamp: 2023-10-10 15:30:56.195462"
+       "Key: missions.mro.hirise.indexes.edr\n",
+       "URL: https://hirise-pds.lpl.arizona.edu/PDS/INDEX/EDRCUMINDEX.LBL\n",
+       "Timestamp: 2024-04-30 21:31:58"
       ]
      },
-     "execution_count": null,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -362,17 +380,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "e32c42b6",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'missions.lro.lroc.indexes.edr'"
+       "'missions.mro.hirise.indexes.edr'"
       ]
      },
-     "execution_count": null,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -383,17 +401,68 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
+   "id": "70970ef8-ad63-41fc-a3f6-8df070fafad4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# this will ALWAYS download!!\n",
+    "#index.download(convert_to_parquet=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "1bc7c9df-ceaa-4eab-84f8-7c739b05d3f8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading index to memory for conversion to parquet. Will take up lots of memory for a bit.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "df9a70d9536549869b371ed0274d7c80",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading index in chunks:   0%|          | 0/459 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Convert time strings to datetime objects.\n",
+      "Done reading, now storing into parquet.\n"
+     ]
+    }
+   ],
+   "source": [
+    "index.convert_to_parquet()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
    "id": "d74b39d0-77ab-4211-91d7-55e0b8401cf7",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Path('CUMINDEX.LBL')"
+       "Path('EDRCUMINDEX.LBL')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -411,7 +480,7 @@
     {
      "data": {
       "text/plain": [
-       "'http://pds.lroc.asu.edu/data/LRO-L-LROC-2-EDR-V1.0/LROLRC_0048C/INDEX/CUMINDEX.LBL'"
+       "'https://hirise-pds.lpl.arizona.edu/PDS/INDEX/EDRCUMINDEX.LBL'"
       ]
      },
      "execution_count": null,
@@ -432,7 +501,7 @@
     {
      "data": {
       "text/plain": [
-       "Path('/home/ayek72/mnt/slowdata/planetarypy/missions/lro/lroc/indexes/edr')"
+       "Path('/media/ayek72/data/planetarypy/missions/mro/hirise/indexes/edr')"
       ]
      },
      "execution_count": null,
@@ -741,9 +810,126 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "conda-env-py39-py",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-py39-py"
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {
+     "1d6e8b8a85ac4f6d822246aad4d590ee": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "25dba98611bc419f9417f7dd187f57ba": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "layout": "IPY_MODEL_e3c9c1526329420682b0a9cf6d5749d7",
+       "style": "IPY_MODEL_1d6e8b8a85ac4f6d822246aad4d590ee",
+       "value": "Loading index in chunks: "
+      }
+     },
+     "7ec3ddd103754c32883a0a287da14cb5": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "layout": "IPY_MODEL_a2d26e8855e14c9aa3e2bdb99604ee60",
+       "style": "IPY_MODEL_af777aecdde14514ac3d9919009ad2c6",
+       "value": " 460/? [00:28&lt;00:00, 13.08it/s]"
+      }
+     },
+     "8b96e37e399b4c74b781e8ffb257b5ff": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "901a9db0da4b4fa487e9d425cf4de306": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "children": [
+        "IPY_MODEL_25dba98611bc419f9417f7dd187f57ba",
+        "IPY_MODEL_f9f5d8a489ad49ba8cc7f6123e05420c",
+        "IPY_MODEL_7ec3ddd103754c32883a0a287da14cb5"
+       ],
+       "layout": "IPY_MODEL_d479f9f494334d258c41c3bb946452b1"
+      }
+     },
+     "932563a1091d49fab34861d7c79fc296": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "description_width": ""
+      }
+     },
+     "a2d26e8855e14c9aa3e2bdb99604ee60": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "af777aecdde14514ac3d9919009ad2c6": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "d479f9f494334d258c41c3bb946452b1": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "e3c9c1526329420682b0a9cf6d5749d7": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "f9f5d8a489ad49ba8cc7f6123e05420c": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "bar_style": "success",
+       "layout": "IPY_MODEL_8b96e37e399b4c74b781e8ffb257b5ff",
+       "max": 459,
+       "style": "IPY_MODEL_932563a1091d49fab34861d7c79fc296",
+       "value": 459
+      }
+     }
+    },
+    "version_major": 2,
+    "version_minor": 0
+   }
   }
  },
  "nbformat": 4,
diff --git a/notebooks/api/02f_pds.utils.ipynb b/notebooks/api/02f_pds.utils.ipynb
index 32a26c4..bdb7410 100644
--- a/notebooks/api/02f_pds.utils.ipynb
+++ b/notebooks/api/02f_pds.utils.ipynb
@@ -2,12 +2,12 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "4ff7aba3-ed81-468c-a7f8-a9b10d4fd89d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| default_exp pds.utils"
+    "# | default_exp pds.utils"
    ]
   },
   {
@@ -21,42 +21,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "b9ce5d2f-52a4-44dc-a377-c04a0c49c60c",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| hide\n",
+    "# | hide\n",
     "from nbdev.showdoc import show_doc  # noqa"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "822f5338-aa84-4d2c-b409-de69db64f34b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "import warnings\n",
     "from typing import Union\n",
     "\n",
-    "from tqdm.auto import tqdm\n",
-    "\n",
     "import pandas as pd\n",
     "import pvl\n",
     "from fastcore.utils import Path\n",
+    "from tqdm.auto import tqdm\n",
+    "\n",
     "from planetarypy import utils"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "4bbda197-6a07-4b86-82fb-7839b2eeb470",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "class IndexLabel:\n",
     "    \"Support working with label files of PDS Index tables.\"\n",
     "\n",
@@ -123,18 +123,40 @@
     "                colspecs.extend(pvlcol.colspecs)\n",
     "        return colspecs\n",
     "\n",
-    "    def read_index_data(self, convert_times=True):\n",
-    "        return index_to_df(self.index_path, self, convert_times=convert_times)"
+    "    def read_index_data(self, do_convert_times=True):\n",
+    "        return index_to_df(self.index_path, self, do_convert_times=do_convert_times)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
+   "id": "02d82502-366e-4304-a81f-1332dd1bf877",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# | export\n",
+    "def convert_times(df):\n",
+    "    for column in [col for col in df.columns if \"TIME\" in col]:\n",
+    "        if column in [\"LOCAL_TIME\", \"DWELL_TIME\"]:\n",
+    "            continue\n",
+    "        try:\n",
+    "            df[column] = pd.to_datetime(df[column])\n",
+    "        except ValueError:\n",
+    "            df[column] = pd.to_datetime(\n",
+    "                df[column], format=utils.nasa_dt_format_with_ms, errors=\"coerce\"\n",
+    "            )\n",
+    "    print(\"Convert time strings to datetime objects.\")\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "id": "4d905955-8ca2-4438-b37c-aeb17de10f4b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "def index_to_df(\n",
     "    # Path to the index TAB file\n",
     "    indexpath: Union[str, Path],\n",
@@ -142,7 +164,7 @@
     "    # 'colnames' and 'colspecs'\n",
     "    label: IndexLabel,\n",
     "    # Switch to control if to convert columns with \"TIME\" in name (unless COUNT is as well in name) to datetime\n",
-    "    convert_times=True,\n",
+    "    do_convert_times=True,\n",
     "):\n",
     "    \"\"\"The main reader function for PDS Indexfiles.\n",
     "\n",
@@ -150,18 +172,24 @@
     "    this reader should work for all PDS TAB files.\n",
     "    \"\"\"\n",
     "    indexpath = Path(indexpath)\n",
-    "    df = pd.read_csv(indexpath,header=None,names=label.colnames,)\n",
-    "    if convert_times:\n",
-    "        for column in [col for col in df.columns if \"TIME\" in col]:\n",
-    "            if column in [\"LOCAL_TIME\", \"DWELL_TIME\"]:\n",
-    "                continue\n",
-    "            try:\n",
-    "                df[column] = pd.to_datetime(df[column])\n",
-    "            except ValueError:\n",
-    "                df[column] = pd.to_datetime(df[column], format=utils.nasa_dt_format_with_ms, errors=\"coerce\")\n",
-    "            except KeyError:\n",
-    "                raise KeyError(f\"{column} not in {df.columns}\")\n",
-    "        print(\"Done.\")\n",
+    "    # get n_lines fast for progress bar\n",
+    "    with open(indexpath, \"rb\") as f:  # courtesy of https://stackoverflow.com/a/1019572\n",
+    "        num_lines = sum(1 for _ in f)\n",
+    "    chunksize = 5000\n",
+    "    df = pd.concat(\n",
+    "        [\n",
+    "            chunk\n",
+    "            for chunk in tqdm(\n",
+    "                pd.read_csv(\n",
+    "                    indexpath, header=None, names=label.colnames, chunksize=chunksize\n",
+    "                ),\n",
+    "                total=int(num_lines / chunksize),\n",
+    "                desc=\"Loading index in chunks\",\n",
+    "            )\n",
+    "        ]\n",
+    "    )\n",
+    "    if do_convert_times:\n",
+    "        df = convert_times(df)\n",
     "    return df"
    ]
   },
@@ -172,7 +200,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "class PVLColumn:\n",
     "    \"Manages just one of the columns in a table that is described via PVL.\"\n",
     "\n",
@@ -231,7 +259,7 @@
     "            return linedata[start:stop]\n",
     "        else:\n",
     "            bucket = []\n",
-    "            for (start, stop) in self.colspecs:\n",
+    "            for start, stop in self.colspecs:\n",
     "                bucket.append(linedata[start:stop])\n",
     "            return bucket\n",
     "\n",
@@ -246,10 +274,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "def decode_line(\n",
-    "        linedata: str,  # One line of a .tab data file\n",
-    "        labelpath: Union[str, Path],  # Path to the appropriate label that describes the data.\n",
+    "    linedata: str,  # One line of a .tab data file\n",
+    "    labelpath: Union[\n",
+    "        str, Path\n",
+    "    ],  # Path to the appropriate label that describes the data.\n",
     "):\n",
     "    \"Decode one line of tabbed data with the appropriate label file.\"\n",
     "    label = IndexLabel(labelpath)\n",
@@ -265,7 +295,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "def find_mixed_type_cols(\n",
     "    # Dataframe to be searched for mixed data-types\n",
     "    df: pd.DataFrame,\n",
@@ -296,10 +326,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
+    "# | export\n",
     "def fix_hirise_edrcumindex(\n",
-    "        infname: Union[str, Path],  # Path to broken EDRCUMINDEX.TAB\n",
-    "        outfname: Union[str, Path],  # Path where to store the fixed TAB file\n",
+    "    infname: Union[str, Path],  # Path to broken EDRCUMINDEX.TAB\n",
+    "    outfname: Union[str, Path],  # Path where to store the fixed TAB file\n",
     "):\n",
     "    \"\"\"Fix HiRISE EDRCUMINDEX.\n",
     "\n",
@@ -330,9 +360,28 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "conda-env-py39-py",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-py39-py"
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
   }
  },
  "nbformat": 4,
diff --git a/planetarypy/_modidx.py b/planetarypy/_modidx.py
index 17f6c94..30968ce 100644
--- a/planetarypy/_modidx.py
+++ b/planetarypy/_modidx.py
@@ -573,6 +573,8 @@
                                                                                          'planetarypy/pds/utils.py'),
                                        'planetarypy.pds.utils.PVLColumn.start': ('api/pds.utils.html#start', 'planetarypy/pds/utils.py'),
                                        'planetarypy.pds.utils.PVLColumn.stop': ('api/pds.utils.html#stop', 'planetarypy/pds/utils.py'),
+                                       'planetarypy.pds.utils.convert_times': ( 'api/pds.utils.html#convert_times',
+                                                                                'planetarypy/pds/utils.py'),
                                        'planetarypy.pds.utils.decode_line': ('api/pds.utils.html#decode_line', 'planetarypy/pds/utils.py'),
                                        'planetarypy.pds.utils.find_mixed_type_cols': ( 'api/pds.utils.html#find_mixed_type_cols',
                                                                                        'planetarypy/pds/utils.py'),
diff --git a/planetarypy/pds/indexes.py b/planetarypy/pds/indexes.py
index 983748d..ac33d0d 100644
--- a/planetarypy/pds/indexes.py
+++ b/planetarypy/pds/indexes.py
@@ -8,7 +8,7 @@
 from datetime import datetime
 from urllib.parse import urlsplit, urlunsplit
 from urllib.request import URLError
-
+from dask import dataframe as dd
 import tomlkit as toml
 from dateutil import parser
 from dateutil.parser import ParserError
@@ -21,7 +21,7 @@
 from ..config import config
 from .ctx_index import CTXIndex
 from .lroc_index import LROCIndex
-from .utils import IndexLabel, fix_hirise_edrcumindex
+from .utils import IndexLabel, fix_hirise_edrcumindex, convert_times
 
 logger = logging.getLogger(__name__)
 
@@ -30,7 +30,7 @@
 # %% ../../notebooks/api/02a_pds.indexes.ipynb 4
 dynamic_urls = {"mro.ctx": CTXIndex, "lro.lroc": LROCIndex}
 
-# %% ../../notebooks/api/02a_pds.indexes.ipynb 6
+# %% ../../notebooks/api/02a_pds.indexes.ipynb 7
 class Index:
     """Index manager class.
 
@@ -161,14 +161,17 @@ def update_timestamp(self):
     def label(self):
         return IndexLabel(self.local_label_path)
 
-    def read_index_data(self, convert_times=True):
-        df = self.label.read_index_data(convert_times=convert_times)
+    def read_index_data(self, do_convert_times=True):
+        df = self.label.read_index_data(do_convert_times=do_convert_times)
         return df
 
     def convert_to_parquet(self):
+        print("Reading index to memory for conversion to parquet. Will take up lots of memory for a bit.")
         df = self.read_index_data()
         df = df.convert_dtypes()
+        print("Storing into parquet.")
         df.to_parquet(self.local_parq_path)
+        print("Finished. Enjoy your freshly baked PDS Index. :")
 
     def __str__(self):
         s = f"Key: {self.key}\n"
@@ -179,7 +182,7 @@ def __str__(self):
     def __repr__(self):
         return self.__str__()
 
-# %% ../../notebooks/api/02a_pds.indexes.ipynb 7
+# %% ../../notebooks/api/02a_pds.indexes.ipynb 8
 @patch
 def parse_key(
     self:Index,
@@ -196,9 +199,12 @@ def parse_key(
         subs.insert(3, "indexes")
     return ".".join(subs)
 
-# %% ../../notebooks/api/02a_pds.indexes.ipynb 8
+# %% ../../notebooks/api/02a_pds.indexes.ipynb 9
 @patch
-def download(self:Index):
+def download(
+    self:Index,  # the Index object defined in this module
+    convert_to_parquet:bool=True,  # set to False if you just want download the files
+):
     """Wrapping URLs for downloading PDS indices and their label files."""
     # check timestamp
     label_url = self.url
@@ -207,19 +213,20 @@ def download(self:Index):
     logger.info("Downloading %s.", self.table_url)
     utils.url_retrieve(self.table_url, self.local_table_path)
     print(f"Downloaded {self.local_label_path} and {self.local_table_path}")
-    if (
-        self.key == "missions.mro.hirise.indexes.edr"
-    ):  # HiRISE EDR index is broken on the PDS. Team knows.
-        print("Fixing broken EDR index...")
-        fix_hirise_edrcumindex(
-            self.local_table_path, self.local_table_path.with_name("temp.tab")
-        )
-        self.local_table_path.with_name("temp.tab").rename(self.local_table_path)
+    # if (
+    #     self.key == "missions.mro.hirise.indexes.edr"
+    # ):  # HiRISE EDR index is broken on the PDS. Team knows.
+    #     print("Fixing broken EDR index...")
+    #     fix_hirise_edrcumindex(
+    #         self.local_table_path, self.local_table_path.with_name("temp.tab")
+    #     )
+    #     self.local_table_path.with_name("temp.tab").rename(self.local_table_path)
     self.timestamp = self.remote_timestamp
     self.update_timestamp()
-    self.convert_to_parquet()
+    if convert_to_parquet:
+        self.convert_to_parquet()
 
-# %% ../../notebooks/api/02a_pds.indexes.ipynb 9
+# %% ../../notebooks/api/02a_pds.indexes.ipynb 10
 @patch(as_prop=True)
 def update_available(
         self: Index) -> bool:  # Boolean indicating if there's a new index
diff --git a/planetarypy/pds/utils.py b/planetarypy/pds/utils.py
index 3374c18..df76418 100644
--- a/planetarypy/pds/utils.py
+++ b/planetarypy/pds/utils.py
@@ -1,17 +1,18 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../notebooks/api/02f_pds.utils.ipynb.
 
 # %% auto 0
-__all__ = ['IndexLabel', 'index_to_df', 'PVLColumn', 'decode_line', 'find_mixed_type_cols', 'fix_hirise_edrcumindex']
+__all__ = ['IndexLabel', 'convert_times', 'index_to_df', 'PVLColumn', 'decode_line', 'find_mixed_type_cols',
+           'fix_hirise_edrcumindex']
 
 # %% ../../notebooks/api/02f_pds.utils.ipynb 3
 import warnings
 from typing import Union
 
-from tqdm.auto import tqdm
-
 import pandas as pd
 import pvl
 from fastcore.utils import Path
+from tqdm.auto import tqdm
+
 from .. import utils
 
 # %% ../../notebooks/api/02f_pds.utils.ipynb 4
@@ -81,10 +82,24 @@ def colspecs(self):
                 colspecs.extend(pvlcol.colspecs)
         return colspecs
 
-    def read_index_data(self, convert_times=True):
-        return index_to_df(self.index_path, self, convert_times=convert_times)
+    def read_index_data(self, do_convert_times=True):
+        return index_to_df(self.index_path, self, do_convert_times=do_convert_times)
 
 # %% ../../notebooks/api/02f_pds.utils.ipynb 5
+def convert_times(df):
+    for column in [col for col in df.columns if "TIME" in col]:
+        if column in ["LOCAL_TIME", "DWELL_TIME"]:
+            continue
+        try:
+            df[column] = pd.to_datetime(df[column])
+        except ValueError:
+            df[column] = pd.to_datetime(
+                df[column], format=utils.nasa_dt_format_with_ms, errors="coerce"
+            )
+    print("Convert time strings to datetime objects.")
+    return df
+
+# %% ../../notebooks/api/02f_pds.utils.ipynb 6
 def index_to_df(
     # Path to the index TAB file
     indexpath: Union[str, Path],
@@ -92,7 +107,7 @@ def index_to_df(
     # 'colnames' and 'colspecs'
     label: IndexLabel,
     # Switch to control if to convert columns with "TIME" in name (unless COUNT is as well in name) to datetime
-    convert_times=True,
+    do_convert_times=True,
 ):
     """The main reader function for PDS Indexfiles.
 
@@ -100,21 +115,27 @@ def index_to_df(
     this reader should work for all PDS TAB files.
     """
     indexpath = Path(indexpath)
-    df = pd.read_csv(indexpath,header=None,names=label.colnames,)
-    if convert_times:
-        for column in [col for col in df.columns if "TIME" in col]:
-            if column in ["LOCAL_TIME", "DWELL_TIME"]:
-                continue
-            try:
-                df[column] = pd.to_datetime(df[column])
-            except ValueError:
-                df[column] = pd.to_datetime(df[column], format=utils.nasa_dt_format_with_ms, errors="coerce")
-            except KeyError:
-                raise KeyError(f"{column} not in {df.columns}")
-        print("Done.")
+    # get n_lines fast for progress bar
+    with open(indexpath, "rb") as f:  # courtesy of https://stackoverflow.com/a/1019572
+        num_lines = sum(1 for _ in f)
+    chunksize = 5000
+    df = pd.concat(
+        [
+            chunk
+            for chunk in tqdm(
+                pd.read_csv(
+                    indexpath, header=None, names=label.colnames, chunksize=chunksize
+                ),
+                total=int(num_lines / chunksize),
+                desc="Loading index in chunks",
+            )
+        ]
+    )
+    if do_convert_times:
+        df = convert_times(df)
     return df
 
-# %% ../../notebooks/api/02f_pds.utils.ipynb 6
+# %% ../../notebooks/api/02f_pds.utils.ipynb 7
 class PVLColumn:
     "Manages just one of the columns in a table that is described via PVL."
 
@@ -173,17 +194,19 @@ def decode(self, linedata):
             return linedata[start:stop]
         else:
             bucket = []
-            for (start, stop) in self.colspecs:
+            for start, stop in self.colspecs:
                 bucket.append(linedata[start:stop])
             return bucket
 
     def __repr__(self):
         return self.pvlobj.__repr__()
 
-# %% ../../notebooks/api/02f_pds.utils.ipynb 7
+# %% ../../notebooks/api/02f_pds.utils.ipynb 8
 def decode_line(
-        linedata: str,  # One line of a .tab data file
-        labelpath: Union[str, Path],  # Path to the appropriate label that describes the data.
+    linedata: str,  # One line of a .tab data file
+    labelpath: Union[
+        str, Path
+    ],  # Path to the appropriate label that describes the data.
 ):
     "Decode one line of tabbed data with the appropriate label file."
     label = IndexLabel(labelpath)
@@ -191,7 +214,7 @@ def decode_line(
         pvlcol = PVLColumn(column)
         print(pvlcol.name, pvlcol.decode(linedata))
 
-# %% ../../notebooks/api/02f_pds.utils.ipynb 8
+# %% ../../notebooks/api/02f_pds.utils.ipynb 9
 def find_mixed_type_cols(
     # Dataframe to be searched for mixed data-types
     df: pd.DataFrame,
@@ -214,10 +237,10 @@ def find_mixed_type_cols(
             df[col].fillna("UNKNOWN", inplace=True)
     return result
 
-# %% ../../notebooks/api/02f_pds.utils.ipynb 9
+# %% ../../notebooks/api/02f_pds.utils.ipynb 10
 def fix_hirise_edrcumindex(
-        infname: Union[str, Path],  # Path to broken EDRCUMINDEX.TAB
-        outfname: Union[str, Path],  # Path where to store the fixed TAB file
+    infname: Union[str, Path],  # Path to broken EDRCUMINDEX.TAB
+    outfname: Union[str, Path],  # Path where to store the fixed TAB file
 ):
     """Fix HiRISE EDRCUMINDEX.