diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 00000000..f8c8dec2
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1,36 @@
+# Claude Development Guidelines for microdf
+
+## Code Style
+- All files must end with a newline character
+- Run `make lint` before committing to catch style issues
+
+## Changelog Requirements
+- Every PR must include a `changelog_entry.yaml` file at the root
+- Format:
+  ```yaml
+  - bump: patch|minor|major
+    changes:
+      added|changed|removed|fixed:
+      - Description of change
+  ```
+- The file must not be empty and must end with a newline
+
+## Testing
+- Run tests with: `python3 -m pytest microdf/tests/ -v`
+- Ensure all tests pass before creating a PR
+
+## Pull Request Process
+1. Create a feature branch from master
+2. Make changes and ensure they follow code style guidelines
+3. Add a changelog entry
+4. Create PR with descriptive title and body
+5. PRs should close related issues using "Closes #XXX" in the body
+
+## Dependencies
+- Dependencies are managed in `pyproject.toml`
+- Optional dependencies go in `[project.optional-dependencies]`
+- When removing dependencies, also remove from `microdf/_optional.py` VERSIONS dict
+
+## Documentation
+- Documentation notebooks are in `docs/` directory
+- When removing functionality, consider impact on documentation examples
\ No newline at end of file
diff --git a/changelog_entry.yaml b/changelog_entry.yaml
index e69de29b..ce5c4f79 100644
--- a/changelog_entry.yaml
+++ b/changelog_entry.yaml
@@ -0,0 +1,7 @@
+- bump: minor
+  changes:
+    removed:
+    - Remove all taxcalc functionality and dependencies from the package.
+    - Delete taxcalc.py module and associated test file.
+    - Remove taxcalc from optional dependencies in pyproject.toml.
+    - Remove documentation notebooks that depend on taxcalc functionality.
diff --git a/docs/_toc.yml b/docs/_toc.yml
index 0ba84085..d7ff41ff 100644
--- a/docs/_toc.yml
+++ b/docs/_toc.yml
@@ -3,9 +3,4 @@ root: home
 sections:
 - file: examples
   sections:
-  - file: agg
-  - file: custom_taxes
-  - file: demo
   - file: gini
-  - file: income_measures
-  - file: weighting
diff --git a/docs/agg.ipynb b/docs/agg.ipynb
deleted file mode 100644
index 76e250ba..00000000
--- a/docs/agg.ipynb
+++ /dev/null
@@ -1,417 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# The `agg` function\n",
-    "\n",
-    "Use `agg` to see the effect of a $10,000 UBI by marital status.\n",
-    "\n",
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import taxcalc as tc\n",
-    "import microdf as mdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'5.0.4'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tc.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load data\n",
-    "\n",
-    "Start with a standard `DataFrame`, then add a UBI manually in a reform copy."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "base = mdf.calc_df(group_vars=['expanded_income', 'MARS', 'XTOT'],\n",
-    "                   metric_vars='aftertax_income')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "reform = base.copy(deep=True)\n",
-    "UBI_PP = 10000\n",
-    "reform['ubi'] = reform.XTOT * UBI_PP\n",
-    "reform['aftertax_income'] = reform.aftertax_income + reform.ubi\n",
-    "mdf.add_weighted_metrics(reform, 'aftertax_income')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## `agg`\n",
-    "\n",
-    "### Change in aftertax income by marital status."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "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>aftertax_income_m_base</th>\n",
-       "      <th>aftertax_income_m_reform</th>\n",
-       "      <th>aftertax_income_pctchg</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>MARS</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1.0</th>\n",
-       "      <td>4.454948e+06</td>\n",
-       "      <td>5.692781e+06</td>\n",
-       "      <td>0.277856</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2.0</th>\n",
-       "      <td>8.086353e+06</td>\n",
-       "      <td>1.007139e+07</td>\n",
-       "      <td>0.245480</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3.0</th>\n",
-       "      <td>1.747066e+05</td>\n",
-       "      <td>2.200549e+05</td>\n",
-       "      <td>0.259568</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>1.082960e+06</td>\n",
-       "      <td>1.584130e+06</td>\n",
-       "      <td>0.462778</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      aftertax_income_m_base  aftertax_income_m_reform  aftertax_income_pctchg\n",
-       "MARS                                                                          \n",
-       "1.0             4.454948e+06              5.692781e+06                0.277856\n",
-       "2.0             8.086353e+06              1.007139e+07                0.245480\n",
-       "3.0             1.747066e+05              2.200549e+05                0.259568\n",
-       "4.0             1.082960e+06              1.584130e+06                0.462778"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.agg(base, reform, 'MARS', 'aftertax_income')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Also sum baseline `expanded_income`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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>aftertax_income_m_base</th>\n",
-       "      <th>expanded_income</th>\n",
-       "      <th>aftertax_income_m_reform</th>\n",
-       "      <th>aftertax_income_pctchg</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>MARS</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1.0</th>\n",
-       "      <td>4.454948e+06</td>\n",
-       "      <td>6.176263e+09</td>\n",
-       "      <td>5.692781e+06</td>\n",
-       "      <td>0.277856</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2.0</th>\n",
-       "      <td>8.086353e+06</td>\n",
-       "      <td>1.429634e+10</td>\n",
-       "      <td>1.007139e+07</td>\n",
-       "      <td>0.245480</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3.0</th>\n",
-       "      <td>1.747066e+05</td>\n",
-       "      <td>2.233541e+08</td>\n",
-       "      <td>2.200549e+05</td>\n",
-       "      <td>0.259568</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>1.082960e+06</td>\n",
-       "      <td>1.362624e+09</td>\n",
-       "      <td>1.584130e+06</td>\n",
-       "      <td>0.462778</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      aftertax_income_m_base  expanded_income  aftertax_income_m_reform  \\\n",
-       "MARS                                                                      \n",
-       "1.0             4.454948e+06     6.176263e+09              5.692781e+06   \n",
-       "2.0             8.086353e+06     1.429634e+10              1.007139e+07   \n",
-       "3.0             1.747066e+05     2.233541e+08              2.200549e+05   \n",
-       "4.0             1.082960e+06     1.362624e+09              1.584130e+06   \n",
-       "\n",
-       "      aftertax_income_pctchg  \n",
-       "MARS                          \n",
-       "1.0                 0.277856  \n",
-       "2.0                 0.245480  \n",
-       "3.0                 0.259568  \n",
-       "4.0                 0.462778  "
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.agg(base, reform, 'MARS', 'aftertax_income', 'expanded_income')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Also sum UBI amount"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "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>aftertax_income_m_base</th>\n",
-       "      <th>aftertax_income_m_reform</th>\n",
-       "      <th>ubi_m</th>\n",
-       "      <th>aftertax_income_pctchg</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>MARS</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1.0</th>\n",
-       "      <td>4.454948e+06</td>\n",
-       "      <td>5.692781e+06</td>\n",
-       "      <td>1.237833e+06</td>\n",
-       "      <td>0.277856</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2.0</th>\n",
-       "      <td>8.086353e+06</td>\n",
-       "      <td>1.007139e+07</td>\n",
-       "      <td>1.985039e+06</td>\n",
-       "      <td>0.245480</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3.0</th>\n",
-       "      <td>1.747066e+05</td>\n",
-       "      <td>2.200549e+05</td>\n",
-       "      <td>4.534831e+04</td>\n",
-       "      <td>0.259568</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>1.082960e+06</td>\n",
-       "      <td>1.584130e+06</td>\n",
-       "      <td>5.011703e+05</td>\n",
-       "      <td>0.462778</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      aftertax_income_m_base  aftertax_income_m_reform         ubi_m  \\\n",
-       "MARS                                                                   \n",
-       "1.0             4.454948e+06              5.692781e+06  1.237833e+06   \n",
-       "2.0             8.086353e+06              1.007139e+07  1.985039e+06   \n",
-       "3.0             1.747066e+05              2.200549e+05  4.534831e+04   \n",
-       "4.0             1.082960e+06              1.584130e+06  5.011703e+05   \n",
-       "\n",
-       "      aftertax_income_pctchg  \n",
-       "MARS                          \n",
-       "1.0                 0.277856  \n",
-       "2.0                 0.245480  \n",
-       "3.0                 0.259568  \n",
-       "4.0                 0.462778  "
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.add_weighted_metrics(reform, 'ubi')  # Creates ubi_m = ubi * s006 / 1e6.\n",
-    "\n",
-    "mdf.agg(base, reform, 'MARS', 'aftertax_income', reform_metrics='ubi_m')"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "pe",
-   "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": "3.11.11"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/docs/custom_taxes.ipynb b/docs/custom_taxes.ipynb
deleted file mode 100644
index e697e8a2..00000000
--- a/docs/custom_taxes.ipynb
+++ /dev/null
@@ -1,1053 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Custom taxes\n",
-    "\n",
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import taxcalc as tc\n",
-    "import microdf as mdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'5.0.4'"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tc.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load data\n",
-    "\n",
-    "Start with a `DataFrame` with `aftertax_income` and necessary ingredients of `tpc_eci`. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['mcaid_ben', 'tanf_ben', 'expanded_income', 'XTOT', 'snap_ben', 's006',\n",
-       "       'vet_ben', 'e02400', 'ssi_ben', 'mcare_ben', 'other_ben', 'housing_ben',\n",
-       "       'aftertax_income', 'wic_ben', 'e02300', 'market_income', 'bens', 'tax',\n",
-       "       's006_m', 'XTOT_m'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = mdf.calc_df(group_vars=['expanded_income', 'aftertax_income'] +\n",
-    "                 mdf.ECI_REMOVE_COLS,\n",
-    "                 metric_vars=['XTOT'])\n",
-    "df.columns"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Calculate Tax Policy Center's Expanded Cash Income measure, used for the analysis."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['tpc_eci'] = mdf.tpc_eci(df)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Incidence of a VAT per Tax Policy Center."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['mcaid_ben', 'tanf_ben', 'expanded_income', 'XTOT', 'snap_ben', 's006',\n",
-       "       'vet_ben', 'e02400', 'ssi_ben', 'mcare_ben', 'other_ben', 'housing_ben',\n",
-       "       'aftertax_income', 'wic_ben', 'e02300', 'market_income', 'bens', 'tax',\n",
-       "       's006_m', 'XTOT_m', 'tpc_eci', 'vat'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.add_vat(df)\n",
-    "df.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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>mcaid_ben</th>\n",
-       "      <th>tanf_ben</th>\n",
-       "      <th>expanded_income</th>\n",
-       "      <th>XTOT</th>\n",
-       "      <th>snap_ben</th>\n",
-       "      <th>s006</th>\n",
-       "      <th>vet_ben</th>\n",
-       "      <th>e02400</th>\n",
-       "      <th>ssi_ben</th>\n",
-       "      <th>mcare_ben</th>\n",
-       "      <th>...</th>\n",
-       "      <th>aftertax_income</th>\n",
-       "      <th>wic_ben</th>\n",
-       "      <th>e02300</th>\n",
-       "      <th>market_income</th>\n",
-       "      <th>bens</th>\n",
-       "      <th>tax</th>\n",
-       "      <th>s006_m</th>\n",
-       "      <th>XTOT_m</th>\n",
-       "      <th>tpc_eci</th>\n",
-       "      <th>vat</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>RECID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>192722</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>-303140.163141</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>381.90</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-299540.163141</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-303140.163141</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-3600.0</td>\n",
-       "      <td>0.000382</td>\n",
-       "      <td>0.000764</td>\n",
-       "      <td>-303140.163141</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>166558</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>501.66</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-232338.542464</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5188.764042</td>\n",
-       "      <td>-241127.306506</td>\n",
-       "      <td>5188.764042</td>\n",
-       "      <td>-3600.0</td>\n",
-       "      <td>0.000502</td>\n",
-       "      <td>0.001003</td>\n",
-       "      <td>-235938.542464</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12643</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>-169432.325500</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>414.87</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-167632.325500</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-169432.325500</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1800.0</td>\n",
-       "      <td>0.000415</td>\n",
-       "      <td>0.000415</td>\n",
-       "      <td>-169432.325500</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>262111</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>-166304.985475</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>585.69</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-162704.985475</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5724.820074</td>\n",
-       "      <td>-172029.805549</td>\n",
-       "      <td>5724.820074</td>\n",
-       "      <td>-3600.0</td>\n",
-       "      <td>0.000586</td>\n",
-       "      <td>0.001171</td>\n",
-       "      <td>-166304.985475</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12729</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>-158776.447320</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>304.88</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-156976.447320</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-158776.447320</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1800.0</td>\n",
-       "      <td>0.000305</td>\n",
-       "      <td>0.000305</td>\n",
-       "      <td>-158776.447320</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 22 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        mcaid_ben  tanf_ben  expanded_income  XTOT  snap_ben    s006  vet_ben  \\\n",
-       "RECID                                                                           \n",
-       "192722        0.0       0.0   -303140.163141   2.0       0.0  381.90      0.0   \n",
-       "166558        0.0       0.0   -235938.542464   2.0       0.0  501.66      0.0   \n",
-       "12643         0.0       0.0   -169432.325500   1.0       0.0  414.87      0.0   \n",
-       "262111        0.0       0.0   -166304.985475   2.0       0.0  585.69      0.0   \n",
-       "12729         0.0       0.0   -158776.447320   1.0       0.0  304.88      0.0   \n",
-       "\n",
-       "        e02400  ssi_ben  mcare_ben  ...  aftertax_income  wic_ben  \\\n",
-       "RECID                               ...                             \n",
-       "192722     0.0      0.0        0.0  ...   -299540.163141      0.0   \n",
-       "166558     0.0      0.0        0.0  ...   -232338.542464      0.0   \n",
-       "12643      0.0      0.0        0.0  ...   -167632.325500      0.0   \n",
-       "262111     0.0      0.0        0.0  ...   -162704.985475      0.0   \n",
-       "12729      0.0      0.0        0.0  ...   -156976.447320      0.0   \n",
-       "\n",
-       "             e02300  market_income         bens     tax    s006_m    XTOT_m  \\\n",
-       "RECID                                                                         \n",
-       "192722     0.000000 -303140.163141     0.000000 -3600.0  0.000382  0.000764   \n",
-       "166558  5188.764042 -241127.306506  5188.764042 -3600.0  0.000502  0.001003   \n",
-       "12643      0.000000 -169432.325500     0.000000 -1800.0  0.000415  0.000415   \n",
-       "262111  5724.820074 -172029.805549  5724.820074 -3600.0  0.000586  0.001171   \n",
-       "12729      0.000000 -158776.447320     0.000000 -1800.0  0.000305  0.000305   \n",
-       "\n",
-       "              tpc_eci  vat  \n",
-       "RECID                       \n",
-       "192722 -303140.163141  0.0  \n",
-       "166558 -235938.542464  0.0  \n",
-       "12643  -169432.325500  0.0  \n",
-       "262111 -166304.985475  0.0  \n",
-       "12729  -158776.447320  0.0  \n",
-       "\n",
-       "[5 rows x 22 columns]"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.head()  # Note these are zero because we block negative tax liability."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>mcaid_ben</th>\n",
-       "      <th>tanf_ben</th>\n",
-       "      <th>expanded_income</th>\n",
-       "      <th>XTOT</th>\n",
-       "      <th>snap_ben</th>\n",
-       "      <th>s006</th>\n",
-       "      <th>vet_ben</th>\n",
-       "      <th>e02400</th>\n",
-       "      <th>ssi_ben</th>\n",
-       "      <th>mcare_ben</th>\n",
-       "      <th>...</th>\n",
-       "      <th>aftertax_income</th>\n",
-       "      <th>wic_ben</th>\n",
-       "      <th>e02300</th>\n",
-       "      <th>market_income</th>\n",
-       "      <th>bens</th>\n",
-       "      <th>tax</th>\n",
-       "      <th>s006_m</th>\n",
-       "      <th>XTOT_m</th>\n",
-       "      <th>tpc_eci</th>\n",
-       "      <th>vat</th>\n",
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-       "      <th>121269</th>\n",
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-       "      <td>8136.356254</td>\n",
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-       "      <td>1260.65</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>13400.315817</td>\n",
-       "      <td>-1800.000000</td>\n",
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-       "    <tr>\n",
-       "      <th>263725</th>\n",
-       "      <td>0.000000</td>\n",
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-       "      <td>130030.151888</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>408.48</td>\n",
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-       "    <tr>\n",
-       "      <th>50399</th>\n",
-       "      <td>8801.561911</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>32464.654558</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>2748.094474</td>\n",
-       "      <td>16316.244268</td>\n",
-       "      <td>16148.410290</td>\n",
-       "      <td>-5565.016839</td>\n",
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-       "      <td>0.000915</td>\n",
-       "      <td>23663.092647</td>\n",
-       "      <td>1369.068170</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>220548</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>25110.711217</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3234.713349</td>\n",
-       "      <td>581.98</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5513.641949</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>14469.708379</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>25110.711217</td>\n",
-       "      <td>-1800.000000</td>\n",
-       "      <td>0.000582</td>\n",
-       "      <td>0.000582</td>\n",
-       "      <td>10641.002838</td>\n",
-       "      <td>1049.517737</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 22 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          mcaid_ben  tanf_ben  expanded_income  XTOT     snap_ben     s006  \\\n",
-       "RECID                                                                        \n",
-       "121269     0.000000       0.0     91950.879154   2.0     0.000000  1030.13   \n",
-       "113379  8801.561911       0.0     13400.315817   1.0     0.000000  1260.65   \n",
-       "263725     0.000000       0.0    130030.151888   2.0     0.000000   408.48   \n",
-       "50399   8801.561911       0.0     32464.654558   2.0     0.000000   457.48   \n",
-       "220548     0.000000       0.0     25110.711217   1.0  3234.713349   581.98   \n",
-       "\n",
-       "        vet_ben        e02400      ssi_ben     mcare_ben  ...  \\\n",
-       "RECID                                                     ...   \n",
-       "121269      0.0  39477.851082  8136.356254  14469.708379  ...   \n",
-       "113379      0.0      0.000000     0.000000      0.000000  ...   \n",
-       "263725      0.0  59718.562813     0.000000  28940.650007  ...   \n",
-       "50399       0.0      0.000000     0.000000      0.000000  ...   \n",
-       "220548      0.0   5513.641949     0.000000  14469.708379  ...   \n",
-       "\n",
-       "        aftertax_income  wic_ben       e02300  market_income          bens  \\\n",
-       "RECID                                                                        \n",
-       "121269     91695.524384      0.0     0.000000   24687.942237  67262.936917   \n",
-       "113379     15200.315817      0.0     0.000000       0.000000  13400.315817   \n",
-       "263725    132584.497393      0.0     0.000000   41370.939069  88659.212820   \n",
-       "50399      38029.671397      0.0  2748.094474   16316.244268  16148.410290   \n",
-       "220548     26910.711217      0.0     0.000000       0.000000  25110.711217   \n",
-       "\n",
-       "                tax    s006_m    XTOT_m        tpc_eci          vat  \n",
-       "RECID                                                                \n",
-       "121269   255.354770  0.001030  0.002060   77481.170775  3301.038878  \n",
-       "113379 -1800.000000  0.001261  0.001261    4598.753905   592.812317  \n",
-       "263725 -2554.345505  0.000408  0.000817  101089.501882  4507.872911  \n",
-       "50399  -5565.016839  0.000457  0.000915   23663.092647  1369.068170  \n",
-       "220548 -1800.000000  0.000582  0.000582   10641.002838  1049.517737  \n",
-       "\n",
-       "[5 rows x 22 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.sample(5)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Add carbon tax and financial transaction tax."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['mcaid_ben', 'tanf_ben', 'expanded_income', 'XTOT', 'snap_ben', 's006',\n",
-       "       'vet_ben', 'e02400', 'ssi_ben', 'mcare_ben', 'other_ben', 'housing_ben',\n",
-       "       'aftertax_income', 'wic_ben', 'e02300', 'market_income', 'bens', 'tax',\n",
-       "       's006_m', 'XTOT_m', 'tpc_eci', 'vat', 'carbon_tax', 'ftt'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.add_carbon_tax(df)\n",
-    "mdf.add_ftt(df)\n",
-    "df.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "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>mcaid_ben</th>\n",
-       "      <th>tanf_ben</th>\n",
-       "      <th>expanded_income</th>\n",
-       "      <th>XTOT</th>\n",
-       "      <th>snap_ben</th>\n",
-       "      <th>s006</th>\n",
-       "      <th>vet_ben</th>\n",
-       "      <th>e02400</th>\n",
-       "      <th>ssi_ben</th>\n",
-       "      <th>mcare_ben</th>\n",
-       "      <th>...</th>\n",
-       "      <th>e02300</th>\n",
-       "      <th>market_income</th>\n",
-       "      <th>bens</th>\n",
-       "      <th>tax</th>\n",
-       "      <th>s006_m</th>\n",
-       "      <th>XTOT_m</th>\n",
-       "      <th>tpc_eci</th>\n",
-       "      <th>vat</th>\n",
-       "      <th>carbon_tax</th>\n",
-       "      <th>ftt</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>RECID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>90662</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>28793.150170</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>549.21</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.879315e+04</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>3563.937374</td>\n",
-       "      <td>0.000549</td>\n",
-       "      <td>0.000549</td>\n",
-       "      <td>28793.150170</td>\n",
-       "      <td>908.251661</td>\n",
-       "      <td>353.208979</td>\n",
-       "      <td>25.229213</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>65944</th>\n",
-       "      <td>8801.561911</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>53460.313714</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>434.350848</td>\n",
-       "      <td>487.52</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>11987.175218</td>\n",
-       "      <td>2992.95945</td>\n",
-       "      <td>14469.708379</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>-7.275958e-12</td>\n",
-       "      <td>53460.313714</td>\n",
-       "      <td>-1800.000000</td>\n",
-       "      <td>0.000488</td>\n",
-       "      <td>0.000488</td>\n",
-       "      <td>22172.972610</td>\n",
-       "      <td>2155.152235</td>\n",
-       "      <td>663.123765</td>\n",
-       "      <td>55.260314</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>71166</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>32369.951771</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>706.99</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.236995e+04</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-2521.089362</td>\n",
-       "      <td>0.000707</td>\n",
-       "      <td>0.001414</td>\n",
-       "      <td>32369.951771</td>\n",
-       "      <td>1256.077481</td>\n",
-       "      <td>488.474576</td>\n",
-       "      <td>34.891041</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2393</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>31734.531431</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>220.26</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>16905.662709</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>14469.708379</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.591603e+02</td>\n",
-       "      <td>31375.371088</td>\n",
-       "      <td>-1800.000000</td>\n",
-       "      <td>0.000220</td>\n",
-       "      <td>0.000220</td>\n",
-       "      <td>17264.823052</td>\n",
-       "      <td>1307.846726</td>\n",
-       "      <td>402.414377</td>\n",
-       "      <td>33.534531</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10731</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>131398.237894</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>458.54</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>72074.842999</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>28940.650007</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.038274e+04</td>\n",
-       "      <td>101015.493006</td>\n",
-       "      <td>-3600.000000</td>\n",
-       "      <td>0.000459</td>\n",
-       "      <td>0.000917</td>\n",
-       "      <td>102457.587887</td>\n",
-       "      <td>4589.940088</td>\n",
-       "      <td>2429.968282</td>\n",
-       "      <td>269.996476</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 24 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         mcaid_ben  tanf_ben  expanded_income  XTOT    snap_ben    s006  \\\n",
-       "RECID                                                                     \n",
-       "90662     0.000000       0.0     28793.150170   1.0    0.000000  549.21   \n",
-       "65944  8801.561911       0.0     53460.313714   1.0  434.350848  487.52   \n",
-       "71166     0.000000       0.0     32369.951771   2.0    0.000000  706.99   \n",
-       "2393      0.000000       0.0     31734.531431   1.0    0.000000  220.26   \n",
-       "10731     0.000000       0.0    131398.237894   2.0    0.000000  458.54   \n",
-       "\n",
-       "       vet_ben        e02400     ssi_ben     mcare_ben  ...  e02300  \\\n",
-       "RECID                                                   ...           \n",
-       "90662      0.0      0.000000     0.00000      0.000000  ...     0.0   \n",
-       "65944      0.0  11987.175218  2992.95945  14469.708379  ...     0.0   \n",
-       "71166      0.0      0.000000     0.00000      0.000000  ...     0.0   \n",
-       "2393       0.0  16905.662709     0.00000  14469.708379  ...     0.0   \n",
-       "10731      0.0  72074.842999     0.00000  28940.650007  ...     0.0   \n",
-       "\n",
-       "       market_income           bens          tax    s006_m    XTOT_m  \\\n",
-       "RECID                                                                  \n",
-       "90662   2.879315e+04       0.000000  3563.937374  0.000549  0.000549   \n",
-       "65944  -7.275958e-12   53460.313714 -1800.000000  0.000488  0.000488   \n",
-       "71166   3.236995e+04       0.000000 -2521.089362  0.000707  0.001414   \n",
-       "2393    3.591603e+02   31375.371088 -1800.000000  0.000220  0.000220   \n",
-       "10731   3.038274e+04  101015.493006 -3600.000000  0.000459  0.000917   \n",
-       "\n",
-       "             tpc_eci          vat   carbon_tax         ftt  \n",
-       "RECID                                                       \n",
-       "90662   28793.150170   908.251661   353.208979   25.229213  \n",
-       "65944   22172.972610  2155.152235   663.123765   55.260314  \n",
-       "71166   32369.951771  1256.077481   488.474576   34.891041  \n",
-       "2393    17264.823052  1307.846726   402.414377   33.534531  \n",
-       "10731  102457.587887  4589.940088  2429.968282  269.996476  \n",
-       "\n",
-       "[5 rows x 24 columns]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.sample(5)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "VAT with a custom amount generated."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Multiplying tax by 1.08.\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Index(['mcaid_ben', 'tanf_ben', 'expanded_income', 'XTOT', 'snap_ben', 's006',\n",
-       "       'vet_ben', 'e02400', 'ssi_ben', 'mcare_ben', 'other_ben', 'housing_ben',\n",
-       "       'aftertax_income', 'wic_ben', 'e02300', 'market_income', 'bens', 'tax',\n",
-       "       's006_m', 'XTOT_m', 'tpc_eci', 'vat', 'carbon_tax', 'ftt', 'vat2'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.add_vat(df, total=500e9, name='vat2')\n",
-    "df.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "464.5240745518526"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.weighted_sum(df, 'vat', 's006') / 1e9"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "500.0000000000001"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.weighted_sum(df, 'vat2', 's006') / 1e9"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Calculate by hand using `add_custom_tax`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Multiplying tax by 2.15.\n"
-     ]
-    }
-   ],
-   "source": [
-    "mdf.add_custom_tax(df, 'tpc_eci', 'XTOT_m', 'aftertax_income', \n",
-    "                   mdf.VAT_INCIDENCE, 'vat3', 1e12)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1000.0000000000002"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.weighted_sum(df, 'vat3', 's006') / 1e9"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "pe",
-   "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": "3.11.11"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/demo.ipynb b/docs/demo.ipynb
deleted file mode 100644
index b9d10f1a..00000000
--- a/docs/demo.ipynb
+++ /dev/null
@@ -1,381 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# `microdf` demo"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import taxcalc as tc\n",
-    "import microdf as mdf"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Generate data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "base = mdf.calc_df(group_vars=['expanded_income', 'MARS'],\n",
-    "                   metric_vars=['aftertax_income', 'XTOT'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['vet_ben', 's006', 'tanf_ben', 'e02400', 'expanded_income', 'ssi_ben',\n",
-       "       'wic_ben', 'aftertax_income', 'housing_ben', 'e02300', 'mcare_ben',\n",
-       "       'XTOT', 'snap_ben', 'MARS', 'other_ben', 'mcaid_ben', 'market_income',\n",
-       "       'bens', 'tax', 's006_m', 'XTOT_m', 'aftertax_income_m'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "base.columns"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Define a reform that treats capital gains as ordinary income and sets the top marginal rate to 70%."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "CG_REFORM = {\n",
-    "    'CG_nodiff': {2019: True},\n",
-    "    'II_rt7': {2019: 0.7}\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "reform = mdf.calc_df(reform=CG_REFORM, group_vars=['MARS'], group_n65=True, \n",
-    "                     metric_vars=['aftertax_income', 'XTOT'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['s006', 'ssi_ben', 'e02300', 'aftertax_income', 'mcare_ben',\n",
-       "       'expanded_income', 'wic_ben', 'XTOT', 'MARS', 'mcaid_ben', 'vet_ben',\n",
-       "       'tanf_ben', 'e02400', 'housing_ben', 'snap_ben', 'other_ben',\n",
-       "       'market_income', 'bens', 'tax', 'n65', 's006_m', 'XTOT_m',\n",
-       "       'aftertax_income_m'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "reform.columns"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Calculate senior UBI.\n",
-    "\n",
-    "Start with total revenue ($ billions)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "337.44427805705"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "new_rev_m = base.aftertax_income_m.sum() - reform.aftertax_income_m.sum()\n",
-    "new_rev_m / 1e3"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "How many seniors are there?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "60.66105169000002"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.add_weighted_metrics(reform, 'n65')\n",
-    "\n",
-    "n65_total_m = reform.n65_m.sum()\n",
-    "n65_total_m"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Divide."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "5562.7831805738"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "senior_ubi = new_rev_m / reform.n65_m.sum()\n",
-    "senior_ubi"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Add senior UBI to `aftertax_income` and recalculate"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "reform['ubi'] = senior_ubi * reform.n65\n",
-    "reform['aftertax_income'] = reform.aftertax_income + reform.ubi\n",
-    "mdf.add_weighted_metrics(reform, 'aftertax_income')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.allclose(base.aftertax_income_m.sum(), reform.aftertax_income_m.sum())"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Analyze\n",
-    "\n",
-    "Gini, FPL, distributional impact chart\n",
-    "\n",
-    "### Change to Gini index"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4810691765589658"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.gini(base, 'aftertax_income', 's006')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.464648453442316"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.gini(reform, 'aftertax_income', 's006')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Change to poverty rate\n",
-    "\n",
-    "Add federal poverty line with `mdf.fpl`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "base['fpl'] = mdf.fpl(base.XTOT)\n",
-    "reform['fpl'] = mdf.fpl(reform.XTOT)\n",
-    "\n",
-    "base['fpl_XTOT_m'] = np.where(base.aftertax_income < base.fpl,\n",
-    "                              base.XTOT_m, 0)\n",
-    "reform['fpl_XTOT_m'] = np.where(reform.aftertax_income < reform.fpl,\n",
-    "                                reform.XTOT_m, 0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-0.04505398741648947"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "reform.fpl_XTOT_m.sum() / base.fpl_XTOT_m.sum() - 1"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "pe",
-   "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": "3.11.11"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/docs/income_measures.ipynb b/docs/income_measures.ipynb
deleted file mode 100644
index 65e7339c..00000000
--- a/docs/income_measures.ipynb
+++ /dev/null
@@ -1,360 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Income measures\n",
-    "\n",
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import taxcalc as tc\n",
-    "import microdf as mdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'2.3.0'"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tc.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load data\n",
-    "\n",
-    "Start with a `DataFrame` with `expanded_income` and the variables in `expanded_income` excluded from `tpc_eci`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = mdf.calc_df(group_vars=['expanded_income', 'wic_ben', 'housing_ben', \n",
-    "                             'vet_ben', 'mcare_ben', 'mcaid_ben'],\n",
-    "                 metric_vars=['XTOT'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Calculate `tpc_eci`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['tpc_eci'] = mdf.tpc_eci(df)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "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>snap_ben</th>\n",
-       "      <th>vet_ben</th>\n",
-       "      <th>mcaid_ben</th>\n",
-       "      <th>mcare_ben</th>\n",
-       "      <th>aftertax_income</th>\n",
-       "      <th>e02300</th>\n",
-       "      <th>ssi_ben</th>\n",
-       "      <th>wic_ben</th>\n",
-       "      <th>s006</th>\n",
-       "      <th>expanded_income</th>\n",
-       "      <th>...</th>\n",
-       "      <th>tanf_ben</th>\n",
-       "      <th>other_ben</th>\n",
-       "      <th>e02400</th>\n",
-       "      <th>XTOT</th>\n",
-       "      <th>market_income</th>\n",
-       "      <th>bens</th>\n",
-       "      <th>tax</th>\n",
-       "      <th>s006_m</th>\n",
-       "      <th>XTOT_m</th>\n",
-       "      <th>tpc_eci</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>RECID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>43371.012504</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>250.14</td>\n",
-       "      <td>53636.919015</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>53636.919015</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>10265.906511</td>\n",
-       "      <td>0.000250</td>\n",
-       "      <td>0.000500</td>\n",
-       "      <td>53636.919015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>20937.886511</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>211.63</td>\n",
-       "      <td>18650.034959</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>18650.034959</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-2287.851553</td>\n",
-       "      <td>0.000212</td>\n",
-       "      <td>0.000635</td>\n",
-       "      <td>18650.034959</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1734.12939</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8211.593627</td>\n",
-       "      <td>13640.390612</td>\n",
-       "      <td>52516.165397</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3374.52239</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>323.50</td>\n",
-       "      <td>52516.165397</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6663.701623</td>\n",
-       "      <td>13227.079816</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>52516.165397</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000324</td>\n",
-       "      <td>0.000324</td>\n",
-       "      <td>24999.433219</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8211.593627</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>36857.709188</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>186.32</td>\n",
-       "      <td>37764.286717</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3906.542368</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>25646.150723</td>\n",
-       "      <td>12118.135995</td>\n",
-       "      <td>906.577529</td>\n",
-       "      <td>0.000186</td>\n",
-       "      <td>0.000373</td>\n",
-       "      <td>29552.693091</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>27280.781223</td>\n",
-       "      <td>63941.158283</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>343.08</td>\n",
-       "      <td>63941.158283</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>35560.553286</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1099.823774</td>\n",
-       "      <td>62841.334509</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000343</td>\n",
-       "      <td>0.000686</td>\n",
-       "      <td>36660.377060</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         snap_ben  vet_ben    mcaid_ben     mcare_ben  aftertax_income  \\\n",
-       "RECID                                                                    \n",
-       "1         0.00000      0.0     0.000000      0.000000     43371.012504   \n",
-       "2         0.00000      0.0     0.000000      0.000000     20937.886511   \n",
-       "3      1734.12939      0.0  8211.593627  13640.390612     52516.165397   \n",
-       "4         0.00000      0.0  8211.593627      0.000000     36857.709188   \n",
-       "5         0.00000      0.0     0.000000  27280.781223     63941.158283   \n",
-       "\n",
-       "       e02300     ssi_ben  wic_ben    s006  expanded_income  ...  tanf_ben  \\\n",
-       "RECID                                                        ...             \n",
-       "1         0.0     0.00000      0.0  250.14     53636.919015  ...       0.0   \n",
-       "2         0.0     0.00000      0.0  211.63     18650.034959  ...       0.0   \n",
-       "3         0.0  3374.52239      0.0  323.50     52516.165397  ...       0.0   \n",
-       "4         0.0     0.00000      0.0  186.32     37764.286717  ...       0.0   \n",
-       "5         0.0     0.00000      0.0  343.08     63941.158283  ...       0.0   \n",
-       "\n",
-       "         other_ben        e02400  XTOT  market_income          bens  \\\n",
-       "RECID                                                                 \n",
-       "1         0.000000      0.000000   2.0   53636.919015      0.000000   \n",
-       "2         0.000000      0.000000   3.0   18650.034959      0.000000   \n",
-       "3      6663.701623  13227.079816   1.0       0.000000  52516.165397   \n",
-       "4      3906.542368      0.000000   2.0   25646.150723  12118.135995   \n",
-       "5         0.000000  35560.553286   2.0    1099.823774  62841.334509   \n",
-       "\n",
-       "                tax    s006_m    XTOT_m       tpc_eci  \n",
-       "RECID                                                  \n",
-       "1      10265.906511  0.000250  0.000500  53636.919015  \n",
-       "2      -2287.851553  0.000212  0.000635  18650.034959  \n",
-       "3          0.000000  0.000324  0.000324  24999.433219  \n",
-       "4        906.577529  0.000186  0.000373  29552.693091  \n",
-       "5          0.000000  0.000343  0.000686  36660.377060  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.head()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "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": "3.7.3"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/docs/weighting.ipynb b/docs/weighting.ipynb
deleted file mode 100644
index e7c71b72..00000000
--- a/docs/weighting.ipynb
+++ /dev/null
@@ -1,482 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Weighting in taxcalc_helpers\n",
-    "\n",
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import taxcalc as tc\n",
-    "import microdf as mdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'3.0.0'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tc.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load data\n",
-    "\n",
-    "Start with a `DataFrame` with `nu18` and `XTOT`, and also calculate `XTOT_m`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['s006', 'other_ben', 'snap_ben', 'aftertax_income', 'mcaid_ben',\n",
-       "       'mcare_ben', 'ssi_ben', 'e02300', 'nu18', 'expanded_income',\n",
-       "       'housing_ben', 'vet_ben', 'wic_ben', 'e02400', 'tanf_ben', 'XTOT',\n",
-       "       'market_income', 'bens', 'tax', 's006_m', 'XTOT_m'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = mdf.calc_df(group_vars=['nu18'], metric_vars=['XTOT'])\n",
-    "df.columns"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "From this we can calculate the number of people and tax units by the tax unit's number of children."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "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>s006_m</th>\n",
-       "      <th>XTOT_m</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>nu18</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0.0</th>\n",
-       "      <td>152.988772</td>\n",
-       "      <td>209.816367</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1.0</th>\n",
-       "      <td>22.688253</td>\n",
-       "      <td>54.115850</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2.0</th>\n",
-       "      <td>18.859945</td>\n",
-       "      <td>68.880292</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3.0</th>\n",
-       "      <td>7.438481</td>\n",
-       "      <td>34.795527</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>2.371111</td>\n",
-       "      <td>13.539261</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5.0</th>\n",
-       "      <td>0.744276</td>\n",
-       "      <td>5.015182</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6.0</th>\n",
-       "      <td>0.216158</td>\n",
-       "      <td>1.688063</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7.0</th>\n",
-       "      <td>0.090332</td>\n",
-       "      <td>0.790239</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8.0</th>\n",
-       "      <td>0.026501</td>\n",
-       "      <td>0.258552</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9.0</th>\n",
-       "      <td>0.012238</td>\n",
-       "      <td>0.134320</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10.0</th>\n",
-       "      <td>0.007196</td>\n",
-       "      <td>0.084201</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12.0</th>\n",
-       "      <td>0.000265</td>\n",
-       "      <td>0.003715</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          s006_m      XTOT_m\n",
-       "nu18                        \n",
-       "0.0   152.988772  209.816367\n",
-       "1.0    22.688253   54.115850\n",
-       "2.0    18.859945   68.880292\n",
-       "3.0     7.438481   34.795527\n",
-       "4.0     2.371111   13.539261\n",
-       "5.0     0.744276    5.015182\n",
-       "6.0     0.216158    1.688063\n",
-       "7.0     0.090332    0.790239\n",
-       "8.0     0.026501    0.258552\n",
-       "9.0     0.012238    0.134320\n",
-       "10.0    0.007196    0.084201\n",
-       "12.0    0.000265    0.003715"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.groupby('nu18')[['s006_m', 'XTOT_m']].sum()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "What if we also want to calculate the total number of *children* by the tax unit's number of children?\n",
-    "\n",
-    "For this we can use `add_weighted_metrics`, the function called within `calc_df`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "mdf.add_weighted_metrics(df, ['nu18'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we can do the same thing as before, with the new `nu18_m` column."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "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>nu18_m</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>nu18</th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0.0</th>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1.0</th>\n",
-       "      <td>22.688253</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2.0</th>\n",
-       "      <td>37.719889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3.0</th>\n",
-       "      <td>22.315444</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>9.484444</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5.0</th>\n",
-       "      <td>3.721381</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6.0</th>\n",
-       "      <td>1.296949</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7.0</th>\n",
-       "      <td>0.632325</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8.0</th>\n",
-       "      <td>0.212008</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9.0</th>\n",
-       "      <td>0.110139</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10.0</th>\n",
-       "      <td>0.071958</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12.0</th>\n",
-       "      <td>0.003184</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         nu18_m\n",
-       "nu18           \n",
-       "0.0    0.000000\n",
-       "1.0   22.688253\n",
-       "2.0   37.719889\n",
-       "3.0   22.315444\n",
-       "4.0    9.484444\n",
-       "5.0    3.721381\n",
-       "6.0    1.296949\n",
-       "7.0    0.632325\n",
-       "8.0    0.212008\n",
-       "9.0    0.110139\n",
-       "10.0   0.071958\n",
-       "12.0   0.003184"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.groupby('nu18')[['nu18_m']].sum()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can also calculate weighted sums without adding the weighted metric."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Total children: 98M.'"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "total_children = mdf.weighted_sum(df, 'nu18', 's006')\n",
-    "# Fix this decimal.\n",
-    "'Total children: ' + str(round(total_children / 1e6)) + 'M.'"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can also calculate the weighted mean and median."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4782626894263673"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mdf.weighted_mean(df, 'nu18', 's006')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "weighted_quantile() missing 1 required positional argument: 'quantiles'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-9-896d4579ebca>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweighted_median\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'nu18'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m's006'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/microdf/weighted.py\u001b[0m in \u001b[0;36mweighted_median\u001b[0;34m(df, col, w)\u001b[0m\n\u001b[1;32m     84\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m     \"\"\"\n\u001b[0;32m---> 86\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mweighted_quantile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mTypeError\u001b[0m: weighted_quantile() missing 1 required positional argument: 'quantiles'"
-     ]
-    }
-   ],
-   "source": [
-    "mdf.weighted_median(df, 'nu18', 's006')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can also look at more quantiles.\n",
-    "\n",
-    "*Note that weighted quantiles have a different interface.*"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "decile_bounds = np.arange(0, 1.1, 0.1)\n",
-    "deciles = mdf.weighted_quantile(df, 'nu18', 's006', decile_bounds)\n",
-    "pd.DataFrame(deciles, index=decile_bounds)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "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": "3.7.9"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/microdf/__init__.py b/microdf/__init__.py
index ec8e8585..905bca37 100644
--- a/microdf/__init__.py
+++ b/microdf/__init__.py
@@ -47,13 +47,6 @@
     squared_poverty_gap,
 )
 from .tax import mtr, tax_from_mtrs
-from .taxcalc import (
-    add_weighted_metrics,
-    calc_df,
-    n65,
-    recalculate,
-    static_baseline_calc,
-)
 from .ubi import ubi_or_bens
 from .utils import (
     cartesian_product,
@@ -129,12 +122,6 @@
     # tax.py
     "mtr",
     "tax_from_mtrs",
-    # taxcalc.py
-    "static_baseline_calc",
-    "add_weighted_metrics",
-    "n65",
-    "calc_df",
-    "recalculate",
     # ubi.py
     "ubi_or_bens",
     # utils.py
diff --git a/microdf/_optional.py b/microdf/_optional.py
index 86ebdf93..3d795745 100644
--- a/microdf/_optional.py
+++ b/microdf/_optional.py
@@ -7,9 +7,7 @@
 # Adapted from:
 # https://github.com/pandas-dev/pandas/blob/master/pandas/compat/_optional.py
 
-VERSIONS = {
-    "taxcalc": "2.0.0",
-}
+VERSIONS = {}
 
 
 def _get_version(module: types.ModuleType) -> str:
diff --git a/microdf/taxcalc.py b/microdf/taxcalc.py
deleted file mode 100644
index 84b4ad3b..00000000
--- a/microdf/taxcalc.py
+++ /dev/null
@@ -1,161 +0,0 @@
-from typing import Optional
-
-import pandas as pd
-import taxcalc
-
-import microdf as mdf
-from microdf._optional import import_optional_dependency
-
-
-def static_baseline_calc(
-    recs: pd.DataFrame, year: int
-) -> "taxcalc.Calculator":
-    """Creates a static Calculator object.
-
-    :param recs: Records object.
-    :param year: Year to advance to.
-    :returns: Calculator object.
-    """
-    tc = import_optional_dependency("taxcalc")
-    calc = tc.Calculator(records=recs, policy=tc.Policy())
-    calc.advance_to_year(year)
-    calc.calc_all()
-    return calc
-
-
-def add_weighted_metrics(
-    df: pd.DataFrame,
-    metric_vars: list,
-    w: str = "s006",
-    divisor: float = 1e6,
-    suffix: str = "_m",
-) -> None:
-    """Adds weighted metrics in millions to a Tax-Calculator pandas DataFrame.
-
-    Columns are renamed to *_m.
-
-    :param df: A pandas DataFrame containing Tax-Calculator data.
-    :param metric_vars: A list of column names to weight, or a single column
-        name.
-    :param w: Weight column. Defaults to s006.
-    :param divisor: Number by which the product is divided. Defaults to 1e6.
-    :param suffix: Suffix to add to each weighted total. Defaults to '_m' to
-        match divisor default of 1e6.
-    :returns: Nothing. Weighted columns are added in place.
-    """
-    df[w + suffix] = df[w] / divisor
-    metric_vars = mdf.listify(metric_vars)
-    for metric_var in metric_vars:
-        df[metric_var + suffix] = df[metric_var] * df[w + suffix]
-
-
-def n65(
-    age_head: pd.Series, age_spouse: pd.Series, elderly_dependents: pd.Series
-) -> pd.Series:
-    """Calculates number of people in the tax unit age 65 or older.
-
-    :param age_head: Series representing age_head from taxcalc data.
-    :param age_spouse: Series representing age_spouse from taxcalc data.
-    :param elderly_dependents: Series representing elderly_dependents from
-        taxcalc data.
-    :returns: Series representing the number of people age 65 or older.
-    """
-    return (
-        (age_head >= 65).astype(int)
-        + (age_spouse >= 65).astype(int)
-        + elderly_dependents
-    )
-
-
-def calc_df(
-    records: Optional[pd.DataFrame] = None,
-    policy: Optional[taxcalc.Policy] = None,
-    year: int = 2020,
-    reform: Optional[dict] = None,
-    group_vars: Optional[list] = None,
-    metric_vars: Optional[list] = None,
-    group_n65: Optional[bool] = False,
-) -> pd.DataFrame:
-    """Creates a pandas DataFrame for given Tax-Calculator data.
-
-    s006 is always included, and RECID is used as an index.
-
-    :param records: An optional Records object. If not provided, uses CPS
-        records. (Default value = None)
-    :param policy: An optional Policy object. If not provided, uses default
-        Policy.
-    :param year: An optional year to advance to. If not provided, defaults to
-        2020.
-    :param reform: An optional reform to implement for the Policy object.
-        (Default value = None)
-    :param group_vars: An optional list of column names to include in the
-        DataFrame. (Default value = None)
-    :param metric_vars: An optional list of column names to include and
-        calculate weighted sums of (in millions named as *_m) in the DataFrame.
-        (Default value = None)
-    :param group_n65: Whether to calculate and group by n65. Defaults to False.
-    :returns: A pandas DataFrame. market_income is also always calculated.
-    """
-    tc = import_optional_dependency("taxcalc")
-    # Assign defaults.
-    if records is None:
-        records = tc.Records.cps_constructor()
-    if policy is None:
-        policy = tc.Policy()
-    if reform is not None:
-        policy.implement_reform(reform)
-    # Calculate.
-    calc = tc.Calculator(records=records, policy=policy, verbose=False)
-    calc.advance_to_year(year)
-    calc.calc_all()
-    # Get a deduplicated list of all columns.
-    if group_n65:
-        group_vars = group_vars + [
-            "age_head",
-            "age_spouse",
-            "elderly_dependents",
-        ]
-    # Include expanded_income and benefits to produce market_income.
-    all_cols = mdf.listify(
-        [
-            "RECID",
-            "s006",
-            "expanded_income",
-            "aftertax_income",
-            mdf.BENS,
-            group_vars,
-            metric_vars,
-        ]
-    )
-    df = calc.dataframe(all_cols)
-    # Create core elements.
-    df["market_income"] = mdf.market_income(df)
-    df["bens"] = df[mdf.BENS].sum(axis=1)
-    df["tax"] = df.expanded_income - df.aftertax_income
-    if group_n65:
-        df["n65"] = n65(df.age_head, df.age_spouse, df.elderly_dependents)
-        df.drop(
-            ["age_head", "age_spouse", "elderly_dependents"],
-            axis=1,
-            inplace=True,
-        )
-    # Add calculated columns for metrics.
-    mdf.add_weighted_metrics(df, metric_vars)
-    # Set RECID to int and set it as index before returning.
-    df["RECID"] = df.RECID.map(int)
-    return df.set_index("RECID")
-
-
-def recalculate(df: pd.DataFrame) -> None:
-    """Recalculates fields in the DataFrame for after components have changed.
-
-    :param df: DataFrame for use in microdf.
-    :returns: Nothing. Updates the DataFrame in place.
-    """
-    # Recalculate TPC's Expanded Cash Income measure.
-    cols = df.columns
-    if "tpc_eci" in cols:
-        df.tpc_eci = mdf.tpc_eci(df)
-    # Recalculate weighted metrics (anything ending in _m).
-    mcols = cols[cols.str.endswith("_m")]
-    mdf.add_weighted_metrics(df, mcols)
diff --git a/microdf/tests/test_taxcalc.py b/microdf/tests/test_taxcalc.py
deleted file mode 100644
index 96c670ba..00000000
--- a/microdf/tests/test_taxcalc.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import pytest
-
-import microdf as mdf
-
-try:
-    import taxcalc as tc
-
-    _HAVE_TAXCALC = True
-except ImportError:
-    _HAVE_TAXCALC = False
-
-
-def test_calc_df() -> None:
-    """"""
-    if not _HAVE_TAXCALC:
-        pytest.skip("taxcalc is not installed")
-    mdf.calc_df()
-
-
-def test_static_baseline_calc() -> None:
-    """"""
-    if not _HAVE_TAXCALC:
-        pytest.skip("taxcalc is not installed")
-    recs = tc.Records.cps_constructor()
-    mdf.static_baseline_calc(recs, 2020)
diff --git a/pyproject.toml b/pyproject.toml
index 25fc2908..730d755b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,9 +34,6 @@ dev = [
 docs = [
     "jupyter_book",
 ]
-taxcalc = [
-    "taxcalc",
-]
 
 [tool.setuptools.packages.find]
 where = ["."]