Updates for newer versions of dependencies

.github/workflows/build_and_test.yml

@@ -1,19 +1,41 @@
-name: Build Package and Test Source Code [Python 3.7, 3.8]
+name: Build Package and Test Source Code [Python 3.9, 3.10, 3.11]
 
 on: [push, pull_request]
 
 jobs:
   build:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.7, 3.8]
+        os: [ubuntu-latest, macos-latest]
+        python-version: ["3.9", "3.10", "3.11"]
 
     steps:
       - name: Checkout
         uses: actions/checkout@master
         with:
           persist-credentials: false
+      - name: Setup TeX Live
+        uses: teatimeguest/setup-texlive-action@v3
+        with:
+          packages: >-
+            scheme-basic
+            cleveref
+            hyperref
+            iftex
+            listings
+            fancyvrb
+            longtable
+            booktabs
+            graphicx
+            bookmark
+            xcolor
+            soul
+            geometry
+            setspace
+            babel
+            etoolbox
+            footnote
       - name: Setup Miniconda using Python ${{ matrix.python-version }}
         uses: conda-incubator/setup-miniconda@v2
         with:
@@ -24,8 +46,6 @@ jobs:
       - name: Build
         shell: bash -l {0}
         run: |
-          sudo apt update
-          sudo apt-get install texlive texlive-latex-extra
           pip install -e .
           pip install pytest-cov
           pip install pytest-pycodestyle
@@ -35,7 +55,7 @@ jobs:
         run: |
           pytest --cov=./ --cov-report=xml
       - name: Upload coverage to Codecov
-        uses: codecov/codecov-action@v1
+        uses: codecov/codecov-action@v3
         with:
           token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
           file: ./coverage.xml

.github/workflows/check_jupyterbook.yml

@@ -15,13 +15,14 @@ jobs:
         with:
           activate-environment: taxbrain-dev
           environment-file: environment.yml
-          python-version: 3.7
+          python-version: "3.10"
           auto-activate-base: false
 
       - name: Build # Build Jupyter Book
         shell: bash -l {0}
         run: |
           pip install jupyter-book
           pip install -e .
+          python -m ipykernel install --user --name=taxbrain-dev
           cd docs
           jb build ./book

.github/workflows/deploy_jupyterbook.yml

@@ -1,7 +1,7 @@
 name: Build and Deploy Jupyter Book
 on:
   push:
-    branches:    
+    branches:
       - master
 jobs:
   build-and-deploy:
@@ -18,14 +18,15 @@ jobs:
         with:
           activate-environment: taxbrain-dev
           environment-file: environment.yml
-          python-version: 3.7
+          python-version: "3.10"
           auto-activate-base: false
 
       - name: Build # Build Jupyter Book
         shell: bash -l {0}
         run: |
           pip install jupyter-book
           pip install -e .
+          python -m ipykernel install --user --name=taxbrain-dev
           cd docs
           jb build ./book
 

cs-config/cs_config/helpers.py

@@ -301,7 +301,7 @@ def arbitrary_defaultdict():
                 # format table
                 for col in tbl.columns:
                     if col in MONEY_VARS:
-                        tbl.update(tbl[col].apply("${:,.2f}".format))
+                        tbl[col] = tbl[col].apply("${:,.2f}".format)
 
                 tags = RESULTS_TABLE_TAGS[id]
                 tbl_type = tags["table_type"]

cs-config/cs_config/outputs.py

@@ -3,7 +3,7 @@
 """
 from bokeh.models import (ColumnDataSource, Toggle, CustomJS,
                           NumeralTickFormatter, HoverTool)
-from bokeh.models.widgets import Tabs, Panel, Div
+from bokeh.models import TabPanel, Tabs, Div
 from bokeh.embed import json_item
 from bokeh.layouts import layout
 from bokeh.plotting import figure
@@ -127,11 +127,11 @@ def create_layout(data, start_year, end_year):
     change_table = Div(text=ct_title + agg_data["change"]["renderable"],
                        width=1000)
 
-    current_tab = Panel(child=current_law_table,
+    current_tab = TabPanel(child=current_law_table,
                         title="Current Law")
-    reform_tab = Panel(child=reform_table,
+    reform_tab = TabPanel(child=reform_table,
                        title="Reform")
-    change_tab = Panel(child=change_table,
+    change_tab = TabPanel(child=change_table,
                        title="Change")
     agg_tabs = Tabs(tabs=[current_tab, reform_tab, change_tab])
 
@@ -167,20 +167,20 @@ def create_layout(data, start_year, end_year):
                             "Averages and shares are as shown.</i></p>")
                     tbl = Div(text=title + note + _data["renderable"],
                               width=1000)
-                    grp_panel = Panel(child=tbl, title=grp.title())
+                    grp_panel = TabPanel(child=tbl, title=grp.title())
                     grp_panels.append(grp_panel)
                 grp_tab = Tabs(tabs=grp_panels)
                 # panel for the sub tables
-                content_panel = Panel(child=grp_tab, title=key_map[key])
+                content_panel = TabPanel(child=grp_tab, title=key_map[key])
                 content_panels.append(content_panel)
             content_tab = Tabs(tabs=content_panels)
             # panel for the table types
-            tbl_panel = Panel(child=content_tab,
+            tbl_panel = TabPanel(child=content_tab,
                               title=key_map[tbl_type])
             tbl_panels.append(tbl_panel)
         type_tab = Tabs(tabs=tbl_panels)
         # panel for the year
-        yr_panel = Panel(child=type_tab, title=str(yr))
+        yr_panel = TabPanel(child=type_tab, title=str(yr))
         yr_panels.append(yr_panel)
 
     yr_tabs = Tabs(tabs=yr_panels)

docs/book/_config.yml

@@ -2,7 +2,7 @@
 # Book settings
 title                    : Tax-Brain
 author                   : Anderson Frailey
-copyright                : '2021'
+copyright                : '2024'
 logo                     : '../taxbrain.png'
 
 ####################################################
@@ -42,7 +42,7 @@ launch_buttons:
 # Information about where the book exists on the web
 repository:
   url                    : https://github.com/PSLmodels/Tax-Brain
-  path_to_book           : 'book'
+  path_to_book           : 'docs/book'
 
 #######################################################################################
 # Advanced and power-user settings
@@ -51,6 +51,8 @@ sphinx:
                                'sphinx.ext.viewcode', 'sphinx.ext.napoleon',
                                'alabaster']   # A list of extra extensions to load by Sphinx.
   config                    :   # key-value pairs to directly over-ride the Sphinx configuration
+    bibtex_reference_style: author_year
+    mathjax_path          : https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
 
 ####################################################
 # LaTeX information

taxbrain/report.py

@@ -1,4 +1,5 @@
 import shutil
+import pandas as pd
 import behresp
 import taxbrain
 import taxcalc as tc
@@ -178,9 +179,9 @@ def export_plot(plot, graph):
         tb.start_year, "weighted_deciles", "combined"
     ).fillna(0)
     # move the "ALL" row to the bottom of the DataFrame
-    row = decile_diff_table.loc["ALL"].copy()
-    decile_diff_table.drop("ALL", inplace=True)
-    decile_diff_table = decile_diff_table.append(row)
+    target_row = decile_diff_table.loc["ALL", :]
+    decile_diff_table = decile_diff_table.shift(-1)
+    decile_diff_table.iloc[-1] = target_row.squeeze()
 
     # find which income bin sees the largest change in tax liability
     largest_change = largest_tax_change(diff_table)

taxbrain/tests/expected_weighted_table.csv

@@ -1,4 +1,4 @@
 ,2018,2019
-Base,2337568822215.7954,2466063728525.13
-Reform,2337568822215.7954,2498202959697.5903
-Difference,0.0,32139231172.46045
+Base,2333219200997.7583,2453853281529.6304
+Reform,2333219200997.7583,2485749384352.428
+Difference,0.0,31896102822.79785

taxbrain/utils.py

@@ -316,7 +316,7 @@ def lorenz_data(tb, year: int, var: str = "aftertax_income"):
     # each bin has 1% of the population
     _bins = np.arange(0, 1.01, step=0.01)
     data["bin"] = pd.cut(data['percentile'], bins=_bins)
-    gdf = data.groupby("bin")
+    gdf = data.groupby("bin", observed=False)
     base = gdf["wt_base"].sum()
     base = np.where(base < 0, 0, base)
     reform = gdf["wt_reform"].sum()