diff --git a/Makefile b/Makefile
index 80b2ddade..76ab75647 100644
--- a/Makefile
+++ b/Makefile
@@ -32,7 +32,7 @@ help:
 clean:
 	@find . -name *pyc -exec rm {} \;
 	@find . -name *cache -maxdepth 1 -exec rm -r {} \;
-	@conda uninstall taxcalc --yes --quiet 2>&1 > /dev/null
+	@pip uninstall taxcalc --yes --quiet 2>&1 > /dev/null
 
 .PHONY=package
 package:
@@ -51,7 +51,7 @@ endef
 .PHONY=pytest-cps
 pytest-cps:
 	@$(pytest-setup)
-	@cd taxcalc ; pytest -n4 -m "not requires_pufcsv and not pre_release"
+	@cd taxcalc ; pytest -n4 --disable-warnings -m "not requires_pufcsv and not pre_release"
 	@$(pytest-cleanup)
 
 .PHONY=pytest
diff --git a/docs/about/releases.md b/docs/about/releases.md
index 7ea0c1c4c..b77ee4a71 100644
--- a/docs/about/releases.md
+++ b/docs/about/releases.md
@@ -3,6 +3,27 @@ Release history
 Go [here](https://github.com/PSLmodels/Tax-Calculator/pulls?q=is%3Apr+is%3Aclosed)
 for a complete commit history.
 
+2024-02-10 Release 3.5.0
+------------------------
+(last merged pull request is
+[#2715](https://github.com/PSLmodels/Tax-Calculator/pull/2715))
+
+**This is an enhancement and bug-fix release.**
+
+**API Changes**
+
+**New Features**
+- Add baseline table output to `cli` command [[#2714](https://github.com/PSLmodels/Tax-Calculator/pull/2714) by Martin Holmer]
+- Additional TAXSIM-35 validation tools, serveral PRS by Bodi Yang and Jason DeBacker
+
+**Bug Fixes**
+- Avoid Pandas deprecation warnings[[#2715](https://github.com/PSLmodels/Tax-Calculator/pull/2785) by Martin Holmer]
+- Correctly account for the `odc` variable as refundable in 2021 [[#2703](https://github.com/PSLmodels/Tax-Calculator/pull/2704) by Bodi Yang]
+- Fix incorrect value for `EITC_ps_MarriedJ` in 2020 [[#2699](https://github.com/PSLmodels/Tax-Calculator/pull/2699) by Bodi Yang]
+- Fix incorrect value for ACTC amount for 2023-2025 to reflect inflation adjustment [[#2691](https://github.com/PSLmodels/Tax-Calculator/pull/2691) by Jason DeBacker]
+
+
+
 2023-06-20 Release 3.4.1
 ------------------------
 (last merged pull request is
diff --git a/docs/index.md b/docs/index.md
index d6fd31818..058f1b2d2 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -51,7 +51,7 @@ The cross-model validation work with NBER's TAXSIM-27 model is described
 
 ## Latest release
 
-{doc}`3.4.1 (2023-06-20) <about/releases>`
+{doc}`3.5.0 (2024-02-10) <about/releases>`
 
 If you are already using Tax-Calculator, upgrade using the following command:
 
diff --git a/setup.py b/setup.py
index e86e0b007..b90594a85 100644
--- a/setup.py
+++ b/setup.py
@@ -3,7 +3,7 @@
 with open('README.md') as f:
     longdesc = f.read()
 
-version = '3.4.1'
+version = '3.5.0'
 
 config = {
     'description': 'Tax Calculator',
diff --git a/taxcalc.egg-info/PKG-INFO b/taxcalc.egg-info/PKG-INFO
index 906a36d35..0f8ed3e11 100644
--- a/taxcalc.egg-info/PKG-INFO
+++ b/taxcalc.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: taxcalc
-Version: 3.4.1
+Version: 3.5.0
 Summary: taxcalc
 Home-page: https://github.com/PSLmodels/Tax-Calculator
 Download-URL: https://github.com/PSLmodels/Tax-Calculator
@@ -16,6 +16,12 @@ Classifier: Programming Language :: Python :: 3.7
 Classifier: Programming Language :: Python :: 3.8
 Classifier: Programming Language :: Python :: 3.9
 Classifier: Topic :: Software Development :: Libraries :: Python Modules
+License-File: LICENSE.md
+Requires-Dist: setuptools
+Requires-Dist: numpy
+Requires-Dist: pandas
+Requires-Dist: bokeh
+Requires-Dist: numba
 
 [![PSL cataloged](https://img.shields.io/badge/PSL-cataloged-a0a0a0.svg)](https://www.PSLmodels.org)
 [![Python 3.6+](https://img.shields.io/badge/python-3.6%2B-blue.svg)](https://www.python.org/downloads/release/python-360/)
diff --git a/taxcalc.egg-info/SOURCES.txt b/taxcalc.egg-info/SOURCES.txt
index d45a5fe97..747863a02 100644
--- a/taxcalc.egg-info/SOURCES.txt
+++ b/taxcalc.egg-info/SOURCES.txt
@@ -1,3 +1,4 @@
+LICENSE.md
 MANIFEST.in
 README.md
 setup.py
diff --git a/taxcalc/__init__.py b/taxcalc/__init__.py
index bf0cf2258..520ea9d96 100644
--- a/taxcalc/__init__.py
+++ b/taxcalc/__init__.py
@@ -14,4 +14,4 @@
 from taxcalc.utils import *
 from taxcalc.cli import *
 
-__version__ = '3.4.1'
+__version__ = '3.5.0'
diff --git a/taxcalc/calcfunctions.py b/taxcalc/calcfunctions.py
index d911ca2f8..d1aa5ff0a 100644
--- a/taxcalc/calcfunctions.py
+++ b/taxcalc/calcfunctions.py
@@ -577,7 +577,7 @@ def CapGains(p23250, p22250, sep, ALD_StudentLoan_hc,
 
 
 @iterate_jit(nopython=True)
-def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
+def SSBenefits(MARS, ymod, e02400, SS_all_in_agi, SS_thd50, SS_thd85,
                SS_percentage1, SS_percentage2, c02500):
     """
     Calculates OASDI benefits included in AGI, c02500.
@@ -590,6 +590,8 @@ def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
         Variable that is used in OASDI benefit taxation logic
     e02400: float
         Total social security (OASDI) benefits
+    SS_all_in_agi: bool
+        Whether all social security benefits are included in AGI
     SS_thd50: list
         Threshold for social security benefit taxability (1)
     SS_thd85: list
@@ -615,6 +617,8 @@ def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
                      SS_percentage1 *
                      min(e02400, SS_thd85[MARS - 1] -
                          SS_thd50[MARS - 1]), SS_percentage2 * e02400)
+    if SS_all_in_agi:
+        c02500 = e02400
     return c02500
 
 
@@ -1595,7 +1599,7 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
              CG_nodiff, PT_EligibleRate_active, PT_EligibleRate_passive,
              PT_wages_active_income, PT_top_stacking,
              CG_rt1, CG_rt2, CG_rt3, CG_rt4, CG_brk1, CG_brk2, CG_brk3,
-             dwks10, dwks13, dwks14, dwks19, c05700, taxbc):
+             dwks10, dwks13, dwks14, dwks19, dwks43, c05700, taxbc):
     """
     GainsTax function implements (2015) Schedule D Tax Worksheet logic for
     the special taxation of long-term capital gains and qualified dividends
@@ -1725,6 +1729,8 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         Maximum of 0 and dwks1 - dwks13
     dwks19: float
         Maximum of dwks17 and dwks16
+    dwks43: float
+        separate tax on long-term capital gains and qualified dividends
     c05700: float
         Lump sum distributions
     taxbc: float
@@ -1740,6 +1746,8 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         Maximum of 0 and dwks1 - dwks13
     dwks19: float
         Maximum of dwks17 and dwks16
+    dwks43: float
+        separate tax on long-term capital gains and qualified dividends
     c05700: float
         Lump sum distributions
     taxbc: float
@@ -1834,12 +1842,13 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         dwks13 = 0.
         dwks14 = 0.
         dwks19 = 0.
+        dwks43 = 0.
 
     # final calculations done no matter what the value of hasqdivltcg
     c05100 = c24580  # because foreign earned income exclusion is assumed zero
     c05700 = 0.  # no Form 4972, Lump Sum Distributions
     taxbc = c05700 + c05100
-    return (dwks10, dwks13, dwks14, dwks19, c05700, taxbc)
+    return (dwks10, dwks13, dwks14, dwks19, dwks43, c05700, taxbc)
 
 
 @iterate_jit(nopython=True)
diff --git a/taxcalc/cli/tc.py b/taxcalc/cli/tc.py
index 555f497d0..3c123d4aa 100644
--- a/taxcalc/cli/tc.py
+++ b/taxcalc/cli/tc.py
@@ -109,7 +109,8 @@ def cli_tc_main():
                         default=None)
     parser.add_argument('--sqldb',
                         help=('optional flag that writes SQLite database '
-                              'with dump table containing same output as '
+                              'with two tables (baseline and reform) each '
+                              'containing same output variables as '
                               'produced by --dump option.'),
                         default=False,
                         action="store_true")
diff --git a/taxcalc/policy_current_law.json b/taxcalc/policy_current_law.json
index 040a241ef..cd8d8303e 100644
--- a/taxcalc/policy_current_law.json
+++ b/taxcalc/policy_current_law.json
@@ -356,6 +356,32 @@
             "cps": true
         }
     },
+    "SS_all_in_agi": {
+        "title": "Include all social security benefits in AGI",
+        "description": "All social security benefits will be included in AGI.",
+        "notes": "",
+        "section_1": "Social Security Taxability",
+        "section_2": "Social Security Benefit Taxability",
+        "indexable": false,
+        "indexed": false,
+        "type": "bool",
+        "value": [
+            {
+                "year": 2013,
+                "value": false
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": false,
+                "max": true
+            }
+        },
+        "compatible_data": {
+            "puf": true,
+            "cps": true
+        }
+    },
     "SS_thd50": {
         "title": "Threshold for Social Security benefit taxability 1",
         "description": "The first threshold for Social Security benefit taxability: if taxpayers have provisional income greater than this threshold, up to rate 1 of their Social Security benefit will be subject to tax under current law.",
@@ -20666,4 +20692,4 @@
             "cps": true
         }
     }
-}
\ No newline at end of file
+}
diff --git a/taxcalc/records.py b/taxcalc/records.py
index 4da7ef623..a5b80ef08 100644
--- a/taxcalc/records.py
+++ b/taxcalc/records.py
@@ -350,7 +350,7 @@ def _adjust(self, year):
         # pylint: disable=no-member
         if self.ADJ.size > 0:
             # Interest income
-            self.e00300 *= self.ADJ['INT{}'.format(year)][self.agi_bin].values
+            self.e00300 *= self.ADJ[f'INT{year}'].iloc[self.agi_bin].values
 
     def _read_ratios(self, ratios):
         """
diff --git a/taxcalc/records_variables.json b/taxcalc/records_variables.json
index ff97c3558..ceed4af15 100644
--- a/taxcalc/records_variables.json
+++ b/taxcalc/records_variables.json
@@ -1081,6 +1081,11 @@
       "desc": "search taxcalc/calcfunctions.py for how calculated and used",
       "form": {"2013-20??": "calculated variable"}
     },
+    "dwks43": {
+      "type": "float",
+      "desc": "separate tax on long-term capital gains and qualified dividends",
+      "form": {"2013-20??": "calculated variable"}
+    },
     "fstax": {
       "type": "float",
       "desc": "search taxcalc/calcfunctions.py for how calculated and used",
diff --git a/taxcalc/taxcalcio.py b/taxcalc/taxcalcio.py
index 0756cb1fa..ac85af4bb 100644
--- a/taxcalc/taxcalcio.py
+++ b/taxcalc/taxcalcio.py
@@ -427,8 +427,9 @@ def analyze(self, writing_output_file=False,
            calculated variables using their Tax-Calculator names
 
         output_sqldb: boolean
-           whether or not to write SQLite3 database with dump table
-           containing same output as written by output_dump to a csv file
+           whether or not to write SQLite3 database with two tables
+           (baseline and reform) each containing same output as written
+           by output_dump to a csv file
 
         Returns
         -------
@@ -449,10 +450,17 @@ def analyze(self, writing_output_file=False,
             (mtr_paytax, mtr_inctax,
              _) = self.calc.mtr(wrt_full_compensation=False,
                                 calc_all_already_called=True)
+            self.calc_base.calc_all()
+            calc_base_calculated = True
+            (mtr_paytax_base, mtr_inctax_base,
+             _) = self.calc_base.mtr(wrt_full_compensation=False,
+                                     calc_all_already_called=True)
         else:
             # definitely do not need marginal tax rates
             mtr_paytax = None
             mtr_inctax = None
+            mtr_paytax_base = None
+            mtr_inctax_base = None
         # extract output if writing_output_file
         if writing_output_file:
             self.write_output_file(output_dump, dump_varset,
@@ -460,7 +468,10 @@ def analyze(self, writing_output_file=False,
             self.write_doc_file()
         # optionally write --sqldb output to SQLite3 database
         if output_sqldb:
-            self.write_sqldb_file(dump_varset, mtr_paytax, mtr_inctax)
+            self.write_sqldb_file(
+                dump_varset, mtr_paytax, mtr_inctax,
+                mtr_paytax_base, mtr_inctax_base
+            )
         # optionally write --tables output to text file
         if output_tables:
             if not calc_base_calculated:
@@ -480,7 +491,9 @@ def write_output_file(self, output_dump, dump_varset,
         Write output to CSV-formatted file.
         """
         if output_dump:
-            outdf = self.dump_output(dump_varset, mtr_inctax, mtr_paytax)
+            outdf = self.dump_output(
+                self.calc, dump_varset, mtr_inctax, mtr_paytax
+            )
             column_order = sorted(outdf.columns)
         else:
             outdf = self.minimal_output()
@@ -504,15 +517,25 @@ def write_doc_file(self):
         with open(doc_fname, 'w') as dfile:
             dfile.write(doc)
 
-    def write_sqldb_file(self, dump_varset, mtr_paytax, mtr_inctax):
+    def write_sqldb_file(self, dump_varset, mtr_paytax, mtr_inctax,
+                         mtr_paytax_base, mtr_inctax_base):
         """
         Write dump output to SQLite3 database table dump.
         """
-        outdf = self.dump_output(dump_varset, mtr_inctax, mtr_paytax)
-        assert len(outdf.index) == self.calc.array_len
         db_fname = self._output_filename.replace('.csv', '.db')
         dbcon = sqlite3.connect(db_fname)
-        outdf.to_sql('dump', dbcon, if_exists='replace', index=False)
+        # write baseline table
+        outdf = self.dump_output(
+            self.calc_base, dump_varset, mtr_inctax_base, mtr_paytax_base
+        )
+        assert len(outdf.index) == self.calc.array_len
+        outdf.to_sql('baseline', dbcon, if_exists='replace', index=False)
+        # write reform table
+        outdf = self.dump_output(
+            self.calc, dump_varset, mtr_inctax, mtr_paytax
+        )
+        assert len(outdf.index) == self.calc.array_len
+        outdf.to_sql('reform', dbcon, if_exists='replace', index=False)
         dbcon.close()
         del outdf
         gc.collect()
@@ -565,7 +588,7 @@ def write_decile_table(dfx, tfile, tkind='Totals'):
                                               decile_details=False,
                                               pop_quantiles=False,
                                               weight_by_income_measure=False)
-        gdfx = dfx.groupby('table_row', as_index=False)
+        gdfx = dfx.groupby('table_row', as_index=False, observed=True)
         rtns_series = gdfx.apply(unweighted_sum, 's006').values[:, 1]
         xinc_series = gdfx.apply(weighted_sum, 'expanded_income').values[:, 1]
         itax_series = gdfx.apply(weighted_sum, 'iitax').values[:, 1]
@@ -687,7 +710,7 @@ def minimal_output(self):
         odf = pd.DataFrame(data=odict, columns=varlist)
         return odf
 
-    def dump_output(self, dump_varset, mtr_inctax, mtr_paytax):
+    def dump_output(self, calcx, dump_varset, mtr_inctax, mtr_paytax):
         """
         Extract dump output and return it as Pandas DataFrame.
         """
@@ -699,7 +722,7 @@ def dump_output(self, dump_varset, mtr_inctax, mtr_paytax):
         # create and return dump output DataFrame
         odf = pd.DataFrame()
         for varname in varset:
-            vardata = self.calc.array(varname)
+            vardata = calcx.array(varname)
             if varname in recs_vinfo.INTEGER_VARS:
                 odf[varname] = vardata
             else:
diff --git a/taxcalc/tests/conftest.py b/taxcalc/tests/conftest.py
index 511253029..4d0419843 100644
--- a/taxcalc/tests/conftest.py
+++ b/taxcalc/tests/conftest.py
@@ -4,7 +4,6 @@
 import numpy
 import pandas
 import pytest
-
 from pytest_harvest import get_session_results_df
 
 
@@ -143,27 +142,33 @@ def pytest_sessionfinish(session):
     new_stats_df = get_session_results_df(session)
     # move test_id from index into unique column
     new_stats_df.reset_index(inplace=True)
-    old_stats_df = pandas.read_csv(os.path.join(tests_path, 'test_stats_benchmark.csv'))
+    old_stats_df = pandas.read_csv(os.path.join(
+        tests_path, 'test_stats_benchmark.csv')
+    )
 
     merge_df = new_stats_df.merge(old_stats_df, on=['test_id'], how='left')
     # time diff for new tests is set to 0
-    merge_df['time_diff'] = merge_df['duration_ms_x'] - merge_df['duration_ms_y']
+    merge_df['time_diff'] = (
+        merge_df['duration_ms_x'] - merge_df['duration_ms_y']
+    )
     merge_df['time_diff'] = merge_df['time_diff'].fillna(0)
 
     tol = 1.0 # choose tolerance in seconds
     tol *= 1000
 
+    print('\n')
     for ind, row in merge_df.iterrows():
         if row['time_diff'] > tol:
             diff = round(abs(row['time_diff']), 3)
-            print(f"{row['test_id']} is slower than the current benchmark by {diff} ms")
+            print((f"{row['test_id']} is slower than the "
+                   f"current benchmark by {diff} ms"))
 
     print('\n')
-
     for ind, row in merge_df.iterrows():
         if row['time_diff'] < (-1 * tol):
             diff = round(abs(row['time_diff']), 3)
-            print(f"{row['test_id']} is faster than the current benchmark by {diff} ms")
+            print((f"{row['test_id']} is faster than the "
+                   f"current benchmark by {diff} ms"))
 
     # Save new test stats to disk including time diff
     new_stats_df['time_diff'] = merge_df['time_diff'].values
diff --git a/taxcalc/tests/test_stats_benchmark.csv b/taxcalc/tests/test_stats_benchmark.csv
new file mode 100644
index 000000000..f90f0042b
--- /dev/null
+++ b/taxcalc/tests/test_stats_benchmark.csv
@@ -0,0 +1,335 @@
+,test_id,pytest_obj,status,duration_ms,test_tuple,expected_value,revision,expect,fname,jfname,pfname,good_revision,params,is_paramtools,set_year,csv,fyear,input_data,baseline,reform,assump,outdir,year,base,ref,asm,dumpvar_str,str_valid,num_vars,time_diff
+0,taxcalc/tests/test_4package.py::test_for_consistency,<function test_for_consistency at 0x7f9812faea60>,passed,3.8895980000006602,,,,,,,,,,,,,,,,,,,,,,,,,,-0.020227999982580513
+1,taxcalc/tests/test_benefits.py::test_benefits,<function test_benefits at 0x7f9812fae670>,passed,3956.398976999992,,,,,,,,,,,,,,,,,,,,,,,,,,-66.61906400000771
+2,taxcalc/tests/test_calcfunctions.py::test_calc_and_used_vars,<function test_calc_and_used_vars at 0x7f9812fae9d0>,passed,35.43788800001835,,,,,,,,,,,,,,,,,,,,,,,,,,-2.54297399996517
+3,taxcalc/tests/test_calcfunctions.py::test_function_args_usage,<function test_function_args_usage at 0x7f9812fae5e0>,passed,1.92459600000916,,,,,,,,,,,,,,,,,,,,,,,,,,-0.0026310000009743817
+4,taxcalc/tests/test_calcfunctions.py::test_DependentCare,<function test_DependentCare at 0x7f9812faeee0>,passed,0.23930599999744118,,,,,,,,,,,,,,,,,,,,,,,,,,-0.014379000020880939
+5,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, young]",<function test_StdDed at 0x7f9812fae940>,passed,0.18724900002098366,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 45, 44, [1500, 1200, 1500, 1500, 1500], 1000, 2, 0, 0, 0, 2, 0, False, 0)",12000,,,,,,,,,,,,,,,,,,,,,,,,0.002753999979177052
+6,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, allow charity]",<function test_StdDed at 0x7f9812fae940>,passed,0.17498599999044018,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 66, 44, [1500, 1200, 1500, 1500, 1500], 1000, 2, 0, 1, 1, 2, 200, True, 300)",15800,,,,,,,,,,,,,,,,,,,,,,,,-0.0003819999960796294
+7,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, allow charity, over limit]",<function test_StdDed at 0x7f9812fae940>,passed,0.17825199998355856,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 44, 66, [1500, 1200, 1500, 1500, 1500], 1000, 2, 0, 0, 0, 2, 400, True, 300)",13500,,,,,,,,,,,,,,,,,,,,,,,,-0.02454700003795543
+8,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, two old]",<function test_StdDed at 0x7f9812fae940>,passed,0.17366299999821422,"(0, 1200, [6000, 12000, 6000, 12000, 12000], 66, 67, [1500, 1200, 1500, 1500, 1500], 1000, 2, 0, 0, 0, 2, 0, True, 0)",14400,,,,,,,,,,,,,,,,,,,,,,,,0.00669000002062603
+9,taxcalc/tests/test_calcfunctions.py::test_StdDed[Single 1],<function test_StdDed at 0x7f9812fae940>,passed,0.1744950000102108,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 44, 0, [1500, 1200, 1500, 1500, 1500], 1000, 1, 0, 0, 0, 2, 0, True, 0)",6000,,,,,,,,,,,,,,,,,,,,,,,,0.006421000023237894
+10,taxcalc/tests/test_calcfunctions.py::test_StdDed[Single 2],<function test_StdDed at 0x7f9812fae940>,passed,0.1748549999831539,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 44, 0, [1500, 1200, 1500, 1500, 1500], 1000, 1, 0, 0, 0, 2, 0, True, 0)",6000,,,,,,,,,,,,,,,,,,,,,,,,0.003854999960140104
+11,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, Single]",<function test_StdDed at 0x7f9812fae940>,passed,0.18527499997844643,"(0, 1000, [6000, 12000, 6000, 12000, 12000], 44, 0, [1500, 1200, 1500, 1500, 1500], 1000, 3, 1, 0, 0, 2, 0, True, 0)",0,,,,,,,,,,,,,,,,,,,,,,,,0.018552999961229943
+12,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Marrid, Single, dep, under earn]",<function test_StdDed at 0x7f9812fae940>,passed,0.19310999999788692,"(1, 200, [6000, 12000, 6000, 12000, 12000], 44, 0, [1500, 1200, 1500, 1500, 1500], 1000, 3, 0, 0, 0, 2, 0, True, 0)",1000,,,,,,,,,,,,,,,,,,,,,,,,0.02305200001728741
+13,"taxcalc/tests/test_calcfunctions.py::test_StdDed[Married, Single, dep, over earn]",<function test_StdDed at 0x7f9812fae940>,passed,0.17417500001215558,"(1, 1000, [6000, 12000, 6000, 12000, 12000], 44, 0, [1500, 1200, 1500, 1500, 1500], 1000, 3, 0, 0, 0, 2, 0, True, 0)",1350,,,,,,,,,,,,,,,,,,,,,,,,-0.00010099998348772621
+14,taxcalc/tests/test_calcfunctions.py::test_EI_PayrollTax[case 1],<function test_EI_PayrollTax at 0x7f9812f8b9d0>,passed,0.24382399999467452,"(120000, 10000, 15000, 100, 2000, 0.12, 0.03, 0, 99999999999, 400, 0, 0, 0, 0, 0, 0, None, None, None, None, None, None, None, None, None, None, None)","(0, 4065, 4065, 0, 0, 3252, 25000, 10000, 15000, 10100, 17000)",,,,,,,,,,,,,,,,,,,,,,,,-0.0058740000099532785
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+18,taxcalc/tests/test_calcfunctions.py::test_EI_PayrollTax[case 5],<function test_EI_PayrollTax at 0x7f9812f8b9d0>,passed,0.2199399999938123,"(120000, 10000, 15000, 100, 2000, 0.12, 0.03, 0, 99999999999, 400, 300, 0, 0, 0, 0, 0, None, None, None, None, None, None, None, None, None, None, None)","(300, 4065, 4065, 0, 0, 3285.3, 25300, 10279.1875, 15000, 10382, 17000)",,,,,,,,,,,,,,,,,,,,,,,,0.006000000013273221
+19,taxcalc/tests/test_calcfunctions.py::test_EI_PayrollTax[case 6],<function test_EI_PayrollTax at 0x7f9812f8b9d0>,passed,0.24201100001164377,"(120000, 10000, 15000, 100, 2000, 0.12, 0.03, 0, 99999999999, 400, 0, 0, 0, 0, -40000, 0, None, None, None, None, None, None, None, None, None, None, None)","(-40000, 4065, 4065, 0, 0, 3252, 0, 0, 15000, 10100, 17000)",,,,,,,,,,,,,,,,,,,,,,,,0.02760999996098698
+20,taxcalc/tests/test_calcfunctions.py::test_AfterTaxIncome,<function test_AfterTaxIncome at 0x7f9812f8b940>,passed,0.18071700000632518,,,,,,,,,,,,,,,,,,,,,,,,,,0.0022229999956380753
+21,taxcalc/tests/test_calcfunctions.py::test_ExpandIncome,<function test_ExpandIncome at 0x7f9812f8b8b0>,passed,0.1776309999854675,,,,,,,,,,,,,,,,,,,,,,,,,,0.012813000012101894
+22,taxcalc/tests/test_calcfunctions.py::test_LumpSumTax[test_tuple0-expected_value0],<function test_LumpSumTax at 0x7f9812f8b5e0>,passed,0.1780919999987418,"(1, 1, 2, 0, 0, 1000)","(0, 1000)",,,,,,,,,,,,,,,,,,,,,,,,0.003275000040048326
+23,taxcalc/tests/test_calcfunctions.py::test_LumpSumTax[test_tuple1-expected_value1],<function test_LumpSumTax at 0x7f9812f8b5e0>,passed,0.16859500001942251,"(0, 1, 2, 0, 0, 1000)","(0, 1000)",,,,,,,,,,,,,,,,,,,,,,,,0.0037970000619225175
+24,taxcalc/tests/test_calcfunctions.py::test_LumpSumTax[test_tuple2-expected_value2],<function test_LumpSumTax at 0x7f9812f8b5e0>,passed,0.1696060000142552,"(1, 1, 2, 100, 0, 1000)","(0, 1000)",,,,,,,,,,,,,,,,,,,,,,,,0.004747000019733688
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+26,taxcalc/tests/test_calcfunctions.py::test_LumpSumTax[test_tuple4-expected_value4],<function test_LumpSumTax at 0x7f9812f8b5e0>,passed,0.17028799999252442,"(0, 1, 3, 100, 300, 1000)","(300, 1300)",,,,,,,,,,,,,,,,,,,,,,,,0.0034760000175993178
+27,taxcalc/tests/test_calcfunctions.py::test_FairShareTax[test_tuple0-expected_value0],<function test_FairShareTax at 0x7f9812f8bf70>,passed,0.17505600001754829,"(1100000, 1, 1000, 100, 100, 0.1, [1000000, 1000000, 500000, 1000000, 1000000], [2000000, 2000000, 1000000, 2000000, 2000000], 100, 200, 2000, 300)","(10915, 11115, 12915, 11215)",,,,,,,,,,,,,,,,,,,,,,,,0.0027730000340397964
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+32,taxcalc/tests/test_calcfunctions.py::test_FairShareTax[test_tuple5-expected_value5],<function test_FairShareTax at 0x7f9812f8bf70>,passed,0.17118799999593648,"(1100000, 2, 1000, 100, 100, 0, [1000000, 1000000, 500000, 1000000, 1000000], [2000000, 2000000, 1000000, 2000000, 2000000], 100, 200, 2000, 300)","(0, 200, 2000, 300)",,,,,,,,,,,,,,,,,,,,,,,,0.008001999987072878
+33,taxcalc/tests/test_calcfunctions.py::test_FairShareTax[test_tuple6-expected_value6],<function test_FairShareTax at 0x7f9812f8bf70>,passed,0.1706379999859564,"(510000, 3, 1000, 100, 100, 0.1, [1000000, 1000000, 500000, 1000000, 1000000], [2000000, 2000000, 1000000, 2000000, 2000000], 100, 200, 2000, 300)","(1003, 1203, 3003, 1303)",,,,,,,,,,,,,,,,,,,,,,,,0.004337000007126418
+34,taxcalc/tests/test_calcfunctions.py::test_FairShareTax[test_tuple7-expected_value7],<function test_FairShareTax at 0x7f9812f8bf70>,passed,0.1700359999858847,"(1100000, 3, 1000, 100, 100, 0.1, [1000000, 1000000, 500000, 1000000, 1000000], [2000000, 2000000, 1000000, 2000000, 2000000], 100, 200, 2000, 300)","(109150, 109350, 111150, 109450)",,,,,,,,,,,,,,,,,,,,,,,,0.0042460000031497025
+35,taxcalc/tests/test_calcfunctions.py::test_FairShareTax[test_tuple8-expected_value8],<function test_FairShareTax at 0x7f9812f8bf70>,passed,0.16863499999431042,"(510000, 3, 1000, 100, 100, 0, [1000000, 1000000, 500000, 1000000, 1000000], [2000000, 2000000, 1000000, 2000000, 2000000], 100, 200, 2000, 300)","(0, 200, 2000, 300)",,,,,,,,,,,,,,,,,,,,,,,,0.005609999988109932
+36,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple0-expected_value0],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.18919300001130068,"(1, 50000, 1, 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 1400)",,,,,,,,,,,,,,,,,,,,,,,,0.02116900000714858
+37,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple1-expected_value1],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.1702780000130133,"(1, 76000, 1, 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 1120)",,,,,,,,,,,,,,,,,,,,,,,,0.004078000046092711
+38,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple2-expected_value2],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.18817100001911058,"(1, 90000, 1, 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 0)",,,,,,,,,,,,,,,,,,,,,,,,0.00897600003213489
+39,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple3-expected_value3],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.17077800001175092,"(2, 50000, 3, 1, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 4200)",,,,,,,,,,,,,,,,,,,,,,,,0.002523999995673931
+40,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple4-expected_value4],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.1694749999785472,"(2, 155000, 4, 2, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 2800)",,,,,,,,,,,,,,,,,,,,,,,,0.0022819999969670157
+41,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple5-expected_value5],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.17029700001103265,"(2, 170000, 4, 2, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 1400, [75000, 150000, 75000, 112500, 150000], [80000, 160000, 80000, 120000, 160000], 0, 0, [0, 0, 0, 0, 0], 0, 0, 0)","(0, 0, 0)",,,,,,,,,,,,,,,,,,,,,,,,0.0043869999899471546
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+50,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple14-expected_value14],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.16755199999352044,"(2, 300000, 2, 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 0, [75000, 150000, 75000, 112500, 75000], [0, 0, 0, 0, 0], 0.05, 500, [1200, 2400, 1200, 1200, 1200], 0, 0, 0)","(0, 0, 0)",,,,,,,,,,,,,,,,,,,,,,,,0.0019419999830461443
+51,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple15-expected_value15],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.16702100000998144,"(4, 50000, 3, 2, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 0, [75000, 150000, 75000, 112500, 75000], [0, 0, 0, 0, 0], 0.05, 500, [1200, 2400, 1200, 1200, 1200], 0, 0, 0)","(0, 0, 2200)",,,,,,,,,,,,,,,,,,,,,,,,-0.005651000009265772
+52,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple16-expected_value16],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.1662399999986519,"(4, 130000, 2, 1, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 0, [75000, 150000, 75000, 112500, 75000], [0, 0, 0, 0, 0], 0.05, 500, [1200, 2400, 1200, 1200, 1200], 0, 0, 0)","(0, 0, 825)",,,,,,,,,,,,,,,,,,,,,,,,0.0027250000016466047
+53,taxcalc/tests/test_calcfunctions.py::test_PersonalTaxCredit[test_tuple17-expected_value17],<function test_PersonalTaxCredit at 0x7f9812fa70d0>,passed,0.16919600000164792,"(4, 170000, 3, 2, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], 0, 0, [75000, 150000, 75000, 112500, 75000], [0, 0, 0, 0, 0], 0.05, 500, [1200, 2400, 1200, 1200, 1200], 0, 0, 0)","(0, 0, 0)",,,,,,,,,,,,,,,,,,,,,,,,0.004418000003170219
+54,taxcalc/tests/test_calcfunctions.py::test_EITCamount[test_tuple0-6660],<function test_EITCamount at 0x7f9812fa7160>,passed,262.56430200001546,"(0.0, 0.45, 19330, 6660, 19330, 19330, 0.2106)",6660,,,,,,,,,,,,,,,,,,,,,,,,-22.934080999988282
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+261,taxcalc/tests/test_utils.py::test_expanded_income_weighted,<function test_expanded_income_weighted at 0x7f9812d163a0>,passed,0.6167490000734688,,,,,,,,,,,,,,,,,,,,,,,,,,-0.04430599983606953
+262,taxcalc/tests/test_utils.py::test_weighted_sum,<function test_weighted_sum at 0x7f9812d16430>,passed,1.5304220000871283,,,,,,,,,,,,,,,,,,,,,,,,,,-0.10535499995967257
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+267,taxcalc/tests/test_utils.py::test_mtr_graph_data,<function test_mtr_graph_data at 0x7f9812d16700>,passed,2028.69897700009,,,,,,,,,,,,,,,,,,,,,,,,,,-16.03007299991077
+268,taxcalc/tests/test_utils.py::test_atr_graph_data,<function test_atr_graph_data at 0x7f9812d16790>,passed,2282.1828059999234,,,,,,,,,,,,,,,,,,,,,,,,,,-97.41538000014316
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+275,taxcalc/tests/test_utils.py::test_bootstrap_se_ci,<function test_bootstrap_se_ci at 0x7f9812d16c10>,passed,0.3898969999909241,,,,,,,,,,,,,,,,,,,,,,,,,,0.00764300000355439
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diff --git a/taxcalc/utils.py b/taxcalc/utils.py
index 4da525171..031e5631f 100644
--- a/taxcalc/utils.py
+++ b/taxcalc/utils.py
@@ -261,6 +261,7 @@ def add_income_table_row_variable(dframe, income_measure, bin_edges):
     assert isinstance(bin_edges, list)
     dframe['table_row'] = pd.cut(dframe[income_measure],
                                  bin_edges, right=False)
+
     return dframe
 
 
@@ -539,8 +540,7 @@ def count_gt_zero(dframe, col_name, tolerance=0.001):
             df2, baseline_expanded_income, SOI_AGI_BINS)
     del df2
     # create grouped Pandas DataFrame
-    gdf = dframe.groupby('table_row', as_index=False)
-    del dframe['table_row']
+    gdf = dframe.groupby('table_row', as_index=False, observed=False)
     # create additive difference table statistics from gdf
     diff_table = additive_stats_dataframe(gdf)
     # calculate additive statistics on sums row