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Stephen Mildenhall
2025-03-12 20:58:06 +00:00
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commit 7a4a27fd3e
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README.md
+15 -161
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@@ -1,16 +1,12 @@
# Greater Tables
Creating presentation quality tables from pandas dataframes is
frustrating. It is hard to left-align text and right-align numbers using
pandas `display` or `df.to_html`. The `great_tables` package does a
really nice job with pandas and polars dataframes but does not support
indexes or TeX output.
Creating presentation quality tables from pandas dataframes is frustrating. It is hard to left-align text and right-align numbers using pandas `display` or `df.to_html`. The `great_tables` package does a really nice job with pandas and polars dataframes but does not support indexes or TeX output.
This package is provides consistent HTML and TeX table output with
flexible type-based formatting, and table rules. Its main class `GT` can
be subclassed to set appropriate defaults for your project.
This package provides consistent HTML and TeX table output with flexible type-based formatting, and table rules. Neither output relies on the pandas `to_html` or `to_latex` functions. TeX output uses Tikz tables for very tight control over layout and grid lines. The package is designed for use in Jupyter Lab notebooks Quarto documents.
The project is currently in **beta** status.
Usage: the main class `GT` should be subclassed to set appropriate defaults for your project. `sGT` provides an example.
The project is currently in **beta** status. HTML output is better developed than TeX.
## The Name
@@ -36,7 +32,7 @@ import pandas as pd
import numpy as np
from greater_tables import sGT
level_1 = ["Group A", "Group A", "Group B", "Group B", 'Group C']
level_2 = ['Sub 1', 'Sub 2', 'Sub 2', 'Sub 1', 'Sub 1']
level_2 = ['Sub 1', 'Sub 2', 'Sub 2', 'Sub 3', 'Sub 3']
multi_index = pd.MultiIndex.from_arrays([level_1, level_2])
@@ -49,167 +45,25 @@ hard = pd.DataFrame(
'b': 10. ** np.linspace(-9, 9, 5),
'c': np.linspace(601, 4000, 5),
'd': pd.date_range(start=start, end=end, periods=5),
'e': 'once upon a time, lived happily ever after, not in Kansas anymore, neutrinos are hard to detect, risk is hard to define'.split(',')
'e': 'once upon a time, risk is hard to define, not in Kansas anymore, neutrinos are hard to detect, $\\int_\\infty^\\infty e^{-x^2/2}dx$ is a hard integral'.split(',')
}).set_index('x')
hard.columns = multi_index
print(sGT(hard, 'A hard table.').html)
sGT(hard, 'A hard table.')
```
![HTML output.](img/hard-html.png){width=66%}
![TeX output.](img/hard-tex.png){width=66%}
<style>#TS76FPUXL623T { border-collapse: collapse; font-family: "Roboto", "Open Sans Condensed", "Arial", 'Segoe UI', sans-serif; font-size: 0.9em; width: auto; border: none; overflow: auto; } #TS76FPUXL623T caption { padding: 8px 10px 4px 10px; font-size: 0.99em; text-align: center; font-weight: normal; caption-side: top; } #TS76FPUXL623T thead { border-top: 1px solid #000; border-bottom: 1px solid #000; font-size: 0.99em; } #TS76FPUXL623T tbody { border-bottom: 1px solid #000; } #TS76FPUXL623T th { vertical-align: bottom; padding: 8px 10px 8px 10px; } #TS76FPUXL623T td { padding: 4px 10px 4px 10px; vertical-align: top; } #TS76FPUXL623T .grt-hrule-0 { border-top: 0px solid #000; } #TS76FPUXL623T .grt-hrule-1 { border-top: 0px solid #000; } #TS76FPUXL623T .grt-hrule-2 { border-top: 0px solid #000; } #TS76FPUXL623T .grt-bhrule-0 { border-bottom: 1.5px solid #000; } #TS76FPUXL623T .grt-bhrule-1 { border-bottom: 1px solid #000; } #TS76FPUXL623T .grt-vrule-index { border-left: 1.5px solid #000; } #TS76FPUXL623T .grt-vrule-0 { border-left: 1.5px solid #000; } #TS76FPUXL623T .grt-vrule-1 { border-left: 1px solid #000; } #TS76FPUXL623T .grt-vrule-2 { border-left: 0.5px solid #000; } #TS76FPUXL623T .grt-left { text-align: left; } #TS76FPUXL623T .grt-center { text-align: center; } #TS76FPUXL623T .grt-right { text-align: right; font-variant-numeric: tabular-nums; } #TS76FPUXL623T .grt-head { font-family: "Times New Roman", 'Courier New'; font-size: 0.99em; } #TS76FPUXL623T .grt-bold { font-weight: bold; }</style>
<table id="TS76FPUXL623T">
<caption>
A hard table.
</caption>
<thead>
<tr>
<th class="grt-left">
</th>
<th class="grt-center grt-bhrule-0 grt-vrule-index" colspan="2">
Group A
</th>
<th class="grt-center grt-bhrule-0 grt-vrule-0" colspan="2">
Group B
</th>
<th class="grt-center grt-bhrule-0 grt-vrule-0" colspan="1">
Group C
</th>
</tr>
<tr>
<th class="grt-left">
x
</th>
<th class="grt-center grt-vrule-index" colspan="1">
Sub 1
</th>
<th class="grt-center grt-vrule-1" colspan="1">
Sub 2
</th>
<th class="grt-center grt-vrule-0" colspan="1">
Sub 2
</th>
<th class="grt-center grt-vrule-1" colspan="1">
Sub 1
</th>
<th class="grt-center grt-vrule-0" colspan="1">
Sub 1
</th>
</tr>
</thead>
<tbody>
<tr>
<td class="grt-left">
2020
</td>
<td class="grt-right grt-vrule-index">
100
</td>
<td class="grt-right grt-vrule-1">
1.000n
</td>
<td class="grt-right grt-vrule-0">
601.00
</td>
<td class="grt-center grt-vrule-1">
2025-03-12
</td>
<td class="grt-left grt-vrule-0">
once upon a time
</td>
</tr>
<tr>
<td class="grt-left grt-hrule-0">
2021
</td>
<td class="grt-right grt-hrule-0 grt-vrule-index">
105
</td>
<td class="grt-right grt-hrule-0 grt-vrule-1">
31.623u
</td>
<td class="grt-right grt-hrule-0 grt-vrule-0">
1,450.75
</td>
<td class="grt-center grt-hrule-0 grt-vrule-1">
2025-05-24
</td>
<td class="grt-left grt-hrule-0 grt-vrule-0">
lived happily ever after
</td>
</tr>
<tr>
<td class="grt-left grt-hrule-0">
2022
</td>
<td class="grt-right grt-hrule-0 grt-vrule-index">
2,000
</td>
<td class="grt-right grt-hrule-0 grt-vrule-1">
1.000
</td>
<td class="grt-right grt-hrule-0 grt-vrule-0">
2,300.50
</td>
<td class="grt-center grt-hrule-0 grt-vrule-1">
2025-08-06
</td>
<td class="grt-left grt-hrule-0 grt-vrule-0">
not in Kansas anymore
</td>
</tr>
<tr>
<td class="grt-left grt-hrule-0">
2023
</td>
<td class="grt-right grt-hrule-0 grt-vrule-index">
2,025
</td>
<td class="grt-right grt-hrule-0 grt-vrule-1">
31.623k
</td>
<td class="grt-right grt-hrule-0 grt-vrule-0">
3,150.25
</td>
<td class="grt-center grt-hrule-0 grt-vrule-1">
2025-10-18
</td>
<td class="grt-left grt-hrule-0 grt-vrule-0">
neutrinos are hard to detect
</td>
</tr>
<tr>
<td class="grt-left grt-hrule-0">
2024
</td>
<td class="grt-right grt-hrule-0 grt-vrule-index">
100,000
</td>
<td class="grt-right grt-hrule-0 grt-vrule-1">
1.000G
</td>
<td class="grt-right grt-hrule-0 grt-vrule-0">
4,000.00
</td>
<td class="grt-center grt-hrule-0 grt-vrule-1">
2025-12-31
</td>
<td class="grt-left grt-hrule-0 grt-vrule-0">
risk is hard to define
</td>
</tr>
</tbody>
</table>
Note the following features:
The output illustrates:
- Quarto or Jupyter automatically the class's `_repr_html_` method (or
`_repr_latex_` for pdf/TeX/Beamer output), providing seamless
integration across different output formats.
- Text is left-aligned, numbers are right-aligned.
- The index is displayed, was detected as likely years, and formatted
without a comma separator.
- The first column of integers does have a comma separator.
- The first column of integers does have a comma thousands separator.
- The second column of floats spans several orders of magnitude and is
formatted using Engineering format, n for nano through G for giga.
- The third column of floats is formatted with a comma separator and
README.qmd
+11 -6
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@@ -18,7 +18,7 @@ jupyter:
Creating presentation quality tables from pandas dataframes is frustrating. It is hard to left-align text and right-align numbers using pandas `display` or `df.to_html`. The `great_tables` package does a really nice job with pandas and polars dataframes but does not support indexes or TeX output.
This package is provides consistent HTML and TeX table output with flexible type-based formatting, and table rules. Its main class `GT` can be subclassed to set appropriate defaults for your project.
This package provides consistent HTML and TeX table output with flexible type-based formatting, and table rules. Its main class `GT` can be subclassed to set appropriate defaults for your project. It is designed for use in Jupyter Lab notebooks Quarto documents.
The project is currently in **beta** status.
@@ -43,7 +43,7 @@ import pandas as pd
import numpy as np
from greater_tables import sGT
level_1 = ["Group A", "Group A", "Group B", "Group B", 'Group C']
level_2 = ['Sub 1', 'Sub 2', 'Sub 2', 'Sub 1', 'Sub 1']
level_2 = ['Sub 1', 'Sub 2', 'Sub 2', 'Sub 3', 'Sub 3']
multi_index = pd.MultiIndex.from_arrays([level_1, level_2])
@@ -56,17 +56,22 @@ hard = pd.DataFrame(
'b': 10. ** np.linspace(-9, 9, 5),
'c': np.linspace(601, 4000, 5),
'd': pd.date_range(start=start, end=end, periods=5),
'e': 'once upon a time, lived happily ever after, not in Kansas anymore, neutrinos are hard to detect, risk is hard to define'.split(',')
'e': 'once upon a time, risk is hard to define, not in Kansas anymore, neutrinos are hard to detect, $\\int_\\infty^\\infty e^{-x^2/2}dx$ is a hard integral'.split(',')
}).set_index('x')
hard.columns = multi_index
print(sGT(hard, 'A hard table.').html)
sGT(hard, 'A hard table.')
```
Note the following features:
![HTML output](hard_table_html.png)
![TeX output](hard_table_tex.png)
The output illustrates:
* Quarto or Jupyter automatically the class's `_repr_html_` method (or `_repr_latex_` for pdf/TeX/Beamer output), providing seamless integration across different output formats.
* Text is left-aligned, numbers are right-aligned.
* The index is displayed, was detected as likely years, and formatted without a comma separator.
* The first column of integers does have a comma separator.
* The first column of integers does have a comma thousands separator.
* The second column of floats spans several orders of magnitude and is formatted using Engineering format, n for nano through G for giga.
* The third column of floats is formatted with a comma separator and two decimals, based on the average absolute value.
* The fourth column of date times is formatted as ISO standard dates (not date times).
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