El Petén

Multi tool use
El Petén
|
Capital
|
Flores
|
População
|
366 735 habitantes
|
Censo
|
2002
|
Área
|
35 854 km²
|
Densidade
|
10,23 hab/km²
|
Mapa
|

|
El Petén é um dos 22 departamentos da Guatemala, país da América Central. Sua capital é a cidade de Flores.
História |
Em 2018, foram descobertas ruínas da civilização maia na região de El Petén.[1]
Municípios |
- Dolores
- Flores
- La Libertad
- Melchor de Mencos
- Poptún
- San Andrés
- San Benito
- San Francisco
- San José
- San Luis
- Santa Ana
- Sayaxché
Referências
↑ 'Megalópole' maia em plena selva é descoberta com nova tecnologia a laser BOL - site de notícias
 |
Este artigo sobre Geografia da Guatemala é um esboço. Você pode ajudar a Wikipédia expandindo-o. |
Departamentos da Guatemala |
- Alta Verapaz
- Baja Verapaz
- Chimaltenango
- Chiquimula
- El Petén
- El Progreso
- El Quiché
- Escuintla
- Guatemala
- Huehuetenango
- Izabal
- Jalapa
- Jutiapa
- Quetzaltenango
- Retalhuleu
- Sacatepéquez
- San Marcos
- Santa Rosa
- Sololá
- Suchitepéquez
- Totonicapán
- Zacapa
|
 |
UShg4bAtOJc,d,R NF4ISq8dIFVa VMK2kbGqzxTtM,OdGf7E,vGeBx8yfOs3wVA5eXPfLf,fmITKP,AqVDJs,2 LQduAj5BTicNIAnw XQF
Popular posts from this blog
0
I found a lot of questions abount appendices and ToC. Many users want appendices to be grouped in an Appendix part, however some problems arise with ToC, hyperref, PDF viewer bookmarks, and so on. There are different solutions which require extra packages, command patching and other extra code, however none of them satisfies me. I almost found an easy way to accomplish a good result, where appendices are added to bookmarks in the right way and hyperref links point to the right page. However, the number of the "Appendix" part page is wrong (it's the number of appendix A). Is there any EASY way to fix that? This is a MWE: documentclass{book} usepackage[nottoc,notlot,notlof]{tocbibind} usepackage{hyperref} begin{document} frontmatter tableofcontents mainmatter part{First} chapter{...
1
In the sklearn.model_selection.cross_val_predict page it is stated: Generate cross-validated estimates for each input data point. It is not appropriate to pass these predictions into an evaluation metric. Can someone explain what does it mean? If this gives estimate of Y (y prediction) for every Y (true Y), why can't I calculate metrics such as RMSE or coefficient of determination using these results?
python scikit-learn cross-validation
share | improve this question
edited Nov 28 '18 at 17:52
desertnaut
20.3k 7 43 79
...
0
I have problem with inserting data to MySQL from modal. My modal: <a href="#" class="badge badge-pill badge-success">6 komentarzy</a> <a href="#" class="badge badge-pill badge-danger">brak komentarzy</a> <a data-toggle="modal" href="#add_desk_comm_{$desk_['desk_id']}" data-target="#add_desk_comm_{$desk_['desk_id']}" class="ediiit">(dodaj)</a> <div class="modal fade" id="add_desk_comm_{$desk_['desk_id']}" tabindex="-1" role="dialog" aria-labelledby="edit_printer" aria-hidden="true"> <div class="modal-dialog" role="document"> ...