Change table outputs to be tabulate based

Now using markdown-interpreted (through ipython) output of tabulate
package from compute cells for tables.

Removes issues around latex output for dataframes and leads to more
coherent output.

_drivers-of-inequality-djibouti.qmd

@@ -267,7 +267,7 @@ crosstab = pd.crosstab(aid_grouped['Year'], aid_grouped['Sector'], margins=True,
 # Rename and reorder columns
 crosstab = crosstab[['Trade development', 'Business growth', "Women's rights support", 'Food security', 'All']]
 
-crosstab.fillna('0.00')
+Markdown(tabulate(crosstab.fillna("0.00"), headers="keys", tablefmt="github", floatfmt=".2f"))
 ```
 
 ::: {custom-style="caption"}

_drivers-of-inequality-uganda.qmd

@@ -279,7 +279,7 @@ crosstab = pd.crosstab(wateraid_grouped['Year'], wateraid_grouped['Sector'], mar
 crosstab.columns = ['Basic water supply', 'Education and training', 'Large water supply', 'All']
 crosstab = crosstab[['Basic water supply', 'Large water supply', 'Education and training', 'All']]
 
-crosstab
+Markdown(tabulate(crosstab.fillna("0.00"), headers="keys", tablefmt="github", floatfmt=".2f"))
 ```
 
 ::: {custom-style="caption"}

_drivers-of-inequality-vietnam.qmd

@@ -314,8 +314,7 @@ crosstab = pd.crosstab(floodaid_grouped['Year'], floodaid_grouped['Sector'], mar
 crosstab.columns = ['Basic water supply', 'Disaster risk reduction', 'Large water supply', 'All']
 crosstab = crosstab[['Basic water supply', 'Large water supply', 'Disaster risk reduction', 'All']]
 
-#crosstab.style.format(escape="latex")
+Markdown(tabulate(crosstab.fillna("0.00"), headers="keys", tablefmt="github", floatfmt=".2f"))
-crosstab
 ```
 
 ::: {custom-style="caption"}

data-prep.qmd

@@ -35,6 +35,11 @@ uga = df.loc[df['c3'] == "UGA"]
 vnm = df.loc[df['c3'] == "VNM"]
 ```
 
+```{python}
+from IPython.display import Markdown
+from tabulate import tabulate
+```
+
 ```{python}
 # Set up the data extraction and figure drawing functions
 import plotly.express as px

poetry.lock

@@ -1028,6 +1028,17 @@ build = ["cython (>=0.29.26)"]
 develop = ["cython (>=0.29.26)"]
 docs = ["sphinx", "nbconvert", "jupyter-client", "ipykernel", "matplotlib", "nbformat", "numpydoc", "pandas-datareader"]
 
+[[package]]
+name = "tabulate"
+version = "0.8.10"
+description = "Pretty-print tabular data"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.extras]
+widechars = ["wcwidth"]
+
 [[package]]
 name = "tenacity"
 version = "8.0.1"
@@ -1124,7 +1135,7 @@ python-versions = ">=3.7"
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.9"
-content-hash = "dcd0e115c0c55bebb2a464655fe91c749ef16ed875ebfdf0d3b04f8ee1bb8ccc"
+content-hash = "9a8889c9ff9cf08f3529c276b3d41da95fcfdc871cacea6ab96d55ec3e8d3e0a"
 
 [metadata.files]
 appnope = [
@@ -2003,6 +2014,11 @@ statsmodels = [
     {file = "statsmodels-0.13.2-cp39-cp39-win_amd64.whl", hash = "sha256:39daab5a8a9332c8ea83d6464d065080c9ba65f236daf6a64aa18f64ef776fad"},
     {file = "statsmodels-0.13.2.tar.gz", hash = "sha256:77dc292c9939c036a476f1770f9d08976b05437daa229928da73231147cde7d4"},
 ]
+tabulate = [
+    {file = "tabulate-0.8.10-py3-none-any.whl", hash = "sha256:0ba055423dbaa164b9e456abe7920c5e8ed33fcc16f6d1b2f2d152c8e1e8b4fc"},
+    {file = "tabulate-0.8.10-py3.8.egg", hash = "sha256:436f1c768b424654fce8597290d2764def1eea6a77cfa5c33be00b1bc0f4f63d"},
+    {file = "tabulate-0.8.10.tar.gz", hash = "sha256:6c57f3f3dd7ac2782770155f3adb2db0b1a269637e42f27599925e64b114f519"},
+]
 tenacity = [
     {file = "tenacity-8.0.1-py3-none-any.whl", hash = "sha256:f78f4ea81b0fabc06728c11dc2a8c01277bfc5181b321a4770471902e3eb844a"},
     {file = "tenacity-8.0.1.tar.gz", hash = "sha256:43242a20e3e73291a28bcbcacfd6e000b02d3857a9a9fff56b297a27afdc932f"},

pyproject.toml

@@ -12,6 +12,7 @@ openpyxl = "^3.0.10"
 matplotlib = "^3.5.3"
 plotly-express = "^0.4.1"
 kaleido = "^0.2.1,!=0.2.1.post1"
+tabulate = "^0.8.10"
 
 [tool.poetry.dev-dependencies]