blocks|key|523162|text|你希望得到什么？在我看来这是正确的..。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|523163|import+numpy+as+np
import+pandas+as+pd
arrays+=+[['bar',+'bar',+'baz',+'baz',+'foo',+'foo',+'qux',+'qux'],['one',+'two',+'one',+'two',+'one',+'two',+'one',+'two']]
tuples+=+list(zip(*arrays))
index+=+pd.MultiIndex.from_tuples(tuples,+names=['first',+'second'])
s+=+pd.DataFrame(np.random.randn(8,+4),+index=arrays)
s.to_latex()

u'\\begin{tabular}{llrrrr}\n\\toprule\n++++&+++++&+++++++++0+&+++++++++1+&+++++++++2+&+++++++++3+\\\\\n\\midrule\nbar+&+one+&+-0.792068+&++1.667280+&++0.996496+&++0.278456+\\\\\n++++&+two+&+-0.558638+&++0.329949+&+-0.051455+&++0.586003+\\\\\nbaz+&+one+&++0.400601+&+-0.371393+&++1.041784+&+-0.956686+\\\\\n++++&+two+&+-0.007604+&+-1.332577+&+-1.010781+&+-0.448133+\\\\\nfoo+&+one+&++0.567487+&+-0.929883+&++0.022723+&++0.945251+\\\\\n++++&+two+&++0.009925+&++0.556380+&++0.038697+&++0.067532+\\\\\nqux+&+one+&+-1.518476+&+-1.706236+&++0.598467+&++1.439247+\\\\\n++++&+two+&++0.644754+&++0.929502+&++0.327730+&++0.557668+\\\\\n\\bottomrule\n\\end{tabular}\n'|code-block|syntax|javascript|523164|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

What were you expecting to get? this looks correct to me...

<pre><code>import numpy as np
import pandas as pd
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
s = pd.DataFrame(np.random.randn(8, 4), index=arrays)
s.to_latex()

u'\\begin{tabular}{llrrrr}\n\\toprule\n &amp; &amp; 0 &amp; 1 &amp; 2 &amp; 3 \\\\\n\\midrule\nbar &amp; one &amp; -0.792068 &amp; 1.667280 &amp; 0.996496 &amp; 0.278456 \\\\\n &amp; two &amp; -0.558638 &amp; 0.329949 &amp; -0.051455 &amp; 0.586003 \\\\\nbaz &amp; one &amp; 0.400601 &amp; -0.371393 &amp; 1.041784 &amp; -0.956686 \\\\\n &amp; two &amp; -0.007604 &amp; -1.332577 &amp; -1.010781 &amp; -0.448133 \\\\\nfoo &amp; one &amp; 0.567487 &amp; -0.929883 &amp; 0.022723 &amp; 0.945251 \\\\\n &amp; two &amp; 0.009925 &amp; 0.556380 &amp; 0.038697 &amp; 0.067532 \\\\\nqux &amp; one &amp; -1.518476 &amp; -1.706236 &amp; 0.598467 &amp; 1.439247 \\\\\n &amp; two &amp; 0.644754 &amp; 0.929502 &amp; 0.327730 &amp; 0.557668 \\\\\n\\bottomrule\n\\end{tabular}\n'
</code></pre>

blocks|key|523155|text|我一整天都被这玩意儿弄得头破血流。我假设您和我一样，在Jupyter环境中工作，并希望将结果复制到LaTex源中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|523156|为此，您可以使用print()指令围绕s.to_latex，输出将是您的LaTeX文档所需的内容。|offset|length|style|CODE|523157|在你的例子中。|523158|import+numpy+as+np
import+pandas+as+pd
arrays+=+[['bar',+'bar',+'baz',+'baz',+'foo',+'foo',+'qux',+'qux'],['one',+'two',+'one',+'two',+'one',+'two',+'one',+'two']]
tuples+=+list(zip(*arrays))
index+=+pd.MultiIndex.from_tuples(tuples,+names=['first',+'second'])
s+=+pd.DataFrame(np.random.randn(8,+4),+index=arrays)
print(s.to_latex())|code-block|syntax|javascript|523159|\begin{tabular}{llrrrr}
\toprule
++++&+++++&+++++++++0+&+++++++++1+&+++++++++2+&+++++++++3+\\
\midrule
bar+&+one+&++0.371649+&+-0.898747+&++1.996738+&++0.051273+\\
++++&+two+&+-0.409381+&+-0.415512+&+-1.975661+&+-0.233850+\\
baz+&+one+&++1.014193+&+-0.789155+&++0.046733+&++0.142827+\\
++++&+two+&+-1.831074+&+-1.743929+&+-0.778236+&++1.408626+\\
foo+&+one+&++0.040501+&+-0.232053+&++0.979267+&++0.709616+\\
++++&+two+&+-0.407516+&+-0.036641+&+-0.286853+&+-1.320493+\\
qux+&+one+&+-1.770540+&++0.490122+&++0.745257+&+-0.921023+\\
++++&+two+&+-0.025855+&+-1.567346+&+-1.646400+&+-2.411050+\\
\bottomrule
\end{tabular}|523160|entityMap^0|0|8|7|J|A|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@$D|U|E|V|F|G]|$D|W|E|X|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|Y|8|@]|9|@]|A|$]]|$1|J|3|K|5|L|7|Z|8|@]|9|@]|A|$M|N]]|$1|O|3|P|5|L|7|10|8|@]|9|@]|A|$M|N]]|$1|Q|3|-4|5|6|7|11|8|@]|9|@]|A|$]]]|R|$]]

I was breaking my head with this the whole day.
I'd assume that you, like me, were working in a Jupyter environment and wanted to copy your results to a LaTex source.

In order to do that, you can surround the <code>s.to_latex</code> with a <code>print()</code> instruction and the output will be what you need for your LaTeX document.

In your example.

<pre><code>import numpy as np
import pandas as pd
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
s = pd.DataFrame(np.random.randn(8, 4), index=arrays)
print(s.to_latex())
</code></pre>

<pre><code>\begin{tabular}{llrrrr}
\toprule
 &amp; &amp; 0 &amp; 1 &amp; 2 &amp; 3 \\
\midrule
bar &amp; one &amp; 0.371649 &amp; -0.898747 &amp; 1.996738 &amp; 0.051273 \\
 &amp; two &amp; -0.409381 &amp; -0.415512 &amp; -1.975661 &amp; -0.233850 \\
baz &amp; one &amp; 1.014193 &amp; -0.789155 &amp; 0.046733 &amp; 0.142827 \\
 &amp; two &amp; -1.831074 &amp; -1.743929 &amp; -0.778236 &amp; 1.408626 \\
foo &amp; one &amp; 0.040501 &amp; -0.232053 &amp; 0.979267 &amp; 0.709616 \\
 &amp; two &amp; -0.407516 &amp; -0.036641 &amp; -0.286853 &amp; -1.320493 \\
qux &amp; one &amp; -1.770540 &amp; 0.490122 &amp; 0.745257 &amp; -0.921023 \\
 &amp; two &amp; -0.025855 &amp; -1.567346 &amp; -1.646400 &amp; -2.411050 \\
\bottomrule
\end{tabular}
</code></pre>

blocks|key|631375|text|以下是当我需要在latex文档中包含pandas数据帧/系列时的工作流程：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|631376|在python中将表导出到磁盘|631377|s.to_latex('./tables/the_table.tex')|code-block|syntax|javascript|631378|在表中读取的主.tex文件中|offset|length|style|CODE|631379|\input{./tables/the_table.tex}|631380|当您需要更新latex文档中的表时，您只需运行python代码(例如，notebook)，然后再运行另一个latex编译器，即可获得更新后的PDF。不需要从python中的print()函数中手动复制/粘贴。|631381|entityMap^0|0|0|0|7|4|0|0|2E|7|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|V|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|W|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|X|8|@$K|Y|L|Z|M|N]]|9|@]|A|$]]|$1|O|3|P|5|F|7|10|8|@]|9|@]|A|$G|H]]|$1|Q|3|R|5|6|7|11|8|@$K|12|L|13|M|N]]|9|@]|A|$]]|$1|S|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|T|$]]

The following is my workflow when I need to include a pandas dataframe/series in a latex document:

<h3>in python export your table to disk</h3>

<pre class="lang-py prettyprint-override"><code>s.to_latex('./tables/the_table.tex')
</code></pre>

<h3>in your main <code>.tex</code> file read in the table</h3>

<pre><code>\input{./tables/the_table.tex}
</code></pre>

When you need to update the table in your latex document you just have to run your python code (e.g., notebook) followed by another latex compile to get the updated PDF. No need for manually copy/pasting from a <code>print()</code> function in python.

Consider the multi-level index dataframe s

<pre><code>import numpy as np
import pandas as pd
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
 ...: ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
s = pd.DataFrame(np.random.randn(8, 4), index=arrays)
s
</code></pre>

How may I convert it to a nice table in latex using python codes? 

I tried 

<pre><code>print s.to_latex()
</code></pre>

but it failed and gave me this result 

<pre><code>File "&lt;ipython-input-45-d2f4611ecc13&gt;", line 1
 print s.to_latex()
 ^
SyntaxError: invalid syntax
</code></pre>

I also tried 

<pre><code>s.to_latex()
</code></pre>

And the result was not organized at all

<pre><code>'\\begin{tabular}{llrrrr}\n\\toprule\n &amp; &amp; 0 &amp; 1 &amp; 2 &amp; 3 \\\\\n\\midrule\nbar &amp; one &amp; -0.008518 &amp; -0.535653 &amp; -0.603135 &amp; 0.891277 \\\\\n &amp; two &amp; 0.191005 &amp; -1.470384 &amp; 0.697245 &amp; 1.054424 \\\\\nbaz &amp; one &amp; 0.414505 &amp; -0.312967 &amp; 0.703490 &amp; 0.933851 \\\\\n &amp; two &amp; -0.295505 &amp; -0.923843 &amp; -0.423998 &amp; 0.160162 \\\\\nfoo &amp; one &amp; -1.339702 &amp; 0.616059 &amp; 0.519983 &amp; 0.554584 \\\\\n &amp; two &amp; -1.003784 &amp; 0.674981 &amp; 1.609906 &amp; 0.274486 \\\\\nqux &amp; one &amp; -0.139274 &amp; -0.783004 &amp; 1.084794 &amp; 2.202673 \\\\\n &amp; two &amp; -0.730785 &amp; -0.468041 &amp; 0.762726 &amp; -0.532599 \\\\\n\\bottomrule\n\\end{tabular}\n'
</code></pre>

How to use the `to_latex` method of pandas in Jupyter to obtain code that one can use directly in LaTeX?

编译器

考虑多级索引dataframeimport numpy as npimport pandas as pdarrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],   ...:           ['one', 'two', 'one', '...

问如何使用Jupyter中的pandas的`to_latex`方法来获得可以直接在LaTeX中使用的代码？
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问如何使用Jupyter中的pandas的`to_latex`方法来获得可以直接在LaTeX中使用的代码？EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问如何使用Jupyter中的pandas的`to_latex`方法来获得可以直接在LaTeX中使用的代码？
EN