ENH: multirow naive implementation Styler.to_latex part1
#43369
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attack68
changed the title
multirow naive implementation Styler.to_latexmultirow naive implementation Styler.to_latex part1
jreback
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IO LaTeX
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seems ok, ideally let's have a latex user comment here. umm @bashtage IIRC? |
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cc @ivanovmg if any comments |
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Minor comments from my side, regarding the test.
As for the name of the kwarg, then on the one hand I would suggest "none" over "naive".
But on the other hand, considering the similar implementation for the multicolumns, "naive" seems to be fine (I mean, "none-left" and "none-right" would look bizarre, in case of multicols IMHO).
| df.loc[2, :] = [2, -2.22, "de"] | ||
| df = df.astype({"A": int}) |
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Consider simplifying the dataframe creation to this:
df = DataFrame(
{"A": [0, 1, 2], "B": [-0.61, -1.22, -2.22], "C": ["ab", "cd", "de"]},
index=ridx,
)This way, it is clearer what the dataframe actually look like.
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used in multiple tests so I cleaned up module with a fixture
| @@ -242,6 +242,25 @@ def test_multiindex_row(df): | |||
| assert expected == s.to_latex(sparse_index=False) | |||
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| def test_multirow_naive(df): | |||
| ridx = MultiIndex.from_tuples([("A", "a"), ("A", "b"), ("B", "c")]) | |||
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I suggest that the letters A and B should not be repeated in both the index and columns.
What if you use these for the index?
ridx = MultiIndex.from_tuples([("X", "x"), ("X", "y"), ("Z", "z")])I guess it will be easier to differentiate from the columns.
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fully agree. silly oversight.
| """ | ||
| ) | ||
| s = df.style.format(precision=2) | ||
| assert expected == s.to_latex(multirow_align="naive") |
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I suggest that result variable is extracted:
result = s.to_latex(multirow_align="naive")
assert result == expectedBesides, s is not a preferred variable name, because one-letter variables make debugging more complicated.
What about making it more explicit, styler?
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yes cleaned up module wide (somewhat)
| df = df.copy() | ||
| df.loc[2, :] = [2, -2.22, "de"] | ||
| df = df.astype({"A": int}) | ||
| return df |
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What about just this?
return DataFrame({"A": [0, 1, 2], "B": [-0.61, -1.22, -2.22], "C": ["ab", "cd", "de"]})I mean, there is probably no reason to couple two fixtures together.
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| def test_multirow_naive(df_ext): | ||
| ridx = MultiIndex.from_tuples([("X", "x"), ("X", "x"), ("Y", "y")]) |
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Maybe better to avoid a duplicate in the tuples (like ("X", "x")).
This would do:
[("X", "x"), ("X", "z"), ("Y", "y")]
sure. done. |
…dev#43369) * multirow naive implementation * multirow naive implementation * fix tests * fixture * clean up tests with fixture * (ivanomg req) ref tests * ivoanovmg req Co-authored-by: JHM Darbyshire (iMac) <[email protected]>
this is also for compatability with
DataFrame.to_latex. #41649I think its a nice feature though, although opinions on the argument input choice are welcome. Maybe
"none"is better than"naive".When implementing this for multicol there will be the option for left or right alignment, so the likes of
"naive-left"or"naive-r"will be used. see #43382