Appendix B

Hojas de datos en el campo

Por: Raymond L. Tremblay

La hoja de recolección de datos debería estar preparada antes de ir al campo y estar imprimido sobre papel que es impermeable y escribir con lápiz. Ese ultimo punto es bien importante ya que la gran mayoría de los bolígrafos son soluble en agua y si el papel se moja se puede perder sus datos. Considerando que estas hojas de datos pudiese ser usado como fuente de averiguar los datos por decadas en el futuro. RECUERDA que no se puede regresar en el tiempo para recoger los datos. Si Ud tiene su hoja de datos en el laboratorio y se le cae la taza cafe y fue escrito con bolígrafo se puede perder los datos. No se arriesga!!

Antes de ir al campo es importante tener la lista completa de todos los individuos en la hoja de datos, ya que esto le ayuda asegurarse durante el muestreo que no se le olvida ningún individuo. Datos olvidado no se puede recuperar.

Hoja en blanco para llevarse

Hoja_de_campo %>% gt()

anio	Número_de_Ind	Etapa	Cantidad_flores_abierta	Cantidad_capullo	Cantidad_Frutos	Numero_Hojas	Ancho_hoja_mm	etc
2023	23001	...	...	...	...	...	...	...
2023	23002	...	...	...	...	...	...	...
2023	23003	...	...	...	...	...	...	...
2024	23001	...	...	...	...	...	...	...
2024	23002	...	...	...	...	...	...	...
2024	24003	...	...	...	...	...	...	...
2024	24004	...	...	...	...	...	...	...
2024	24005	...	...	...	...	...	...	...

---

Ejemplos de tablas de Datos

Usando ejemplo de Tremblay [] y su codificación

• p == plantula.
• j == juvenil
• A0 == adulto non-reproductivo
• A1 == adulto reproductivo
• M = muerto

Hoja llena al final del muestreo

library(tidyverse)
library(gt)
Hoja_llena = tribble(
  ~Número_de_Ind, ~Etapa, ~Cantidad_flores_abierta, ~Cantidad_capullo, ~ Cantidad_Frutos, ~Numero_Hojas, ~Ancho_hoja_mm, ~etc,
  23001,"p",NA, NA,NA,NA,NA,NA,
  23002,"j",NA, NA,NA,2,10,NA,
  23003,"A1",5, 10,1, 5,32,NA,
  23004,"Ao",0, 0,0,2,14,NA,
  23005,"m",NA, NA,NA,NA,NA,NA,
  24006,"p",NA, NA,NA,NA,NA,NA,
  24007,"j",NA, NA,NA,1,7,NA,
  24008,"p",NA, NA,NA,NA,NA,NA,
  
)

Hoja_llena %>% gt()

Número_de_Ind	Etapa	Cantidad_flores_abierta	Cantidad_capullo	Cantidad_Frutos	Numero_Hojas	Ancho_hoja_mm	etc
23001	p	NA	NA	NA	NA	NA	NA
23002	j	NA	NA	NA	2	10	NA
23003	A1	5	10	1	5	32	NA
23004	Ao	0	0	0	2	14	NA
23005	m	NA	NA	NA	NA	NA	NA
24006	p	NA	NA	NA	NA	NA	NA
24007	j	NA	NA	NA	1	7	NA
24008	p	NA	NA	NA	NA	NA	NA

Nota que solamente los individuos 23003 y 23004 son adultos, uno tiene flores, capullos y frutos y el otro nada. A todos los adultos hay que llenar la información, no dejarlo en blanco. Para las otras etapas, no es necesario llenar la mayoria de las columnas ya que para las plantulas y muertos no PUEDEN tener esas, pero los juveniles, se puede llenar la cantidad de hojas y sus tamaño. Nota que el individuo 23005 se murio.

Almacenamiento de datos de forma digital

Esa misma estructura de recoger los dados puede ser utilizado para ponerlo en una hoja de MSExcel, Google Sheet o MacOS Numbers.

• Es muy importante que haya dos hojas, una para los datos y otra para la metadata.
• La metadata es la descripción de los datos, como se recogieron, donde, cuando, por quien, las unidades, objetivo de la investigación, etc.
• En la hoja de datos, cada columna tiene información de solamente UNA variable y cada fila tiene información de solamente UN individuo. No debería tener las unidades indicado en las celdas de la hoja de datos, sino en la metadata o en nombre de la columna.
  • La primera fila tiene los nombres de las variables y la primera columna tiene los nombres de los individuos.
  • Los nombres de las columnas no pueden tener espacios, ni caracteres especiales, ni acentos, ni tildes, como en ñ.
  • Los nombres de los individuos no pueden tener espacios, ni caracteres especiales, ni acentos, ni tildes, como en ñ, Preferiblemente que sea un alfanumérico.
• La hojas de datos preferiblemente se guarda en hoja de datos separados, como .csv, .xls, .xlsx, .ods, etc. La ventaja de usar .csv es que es un archivo de texto y se puede abrir en cualquier programa de hoja de datos. Ese formato .csv, comma seperated variable, es uno de los más viejo para almacenar datos, y es compatible con casi todos los programa de estadística. NUNCA guarda sus datos en un formato de programas especializados como SPSS, STATA, JMP, SAS, porque típicamente no se puede abrir en otros programas, y si no tiene la licencias se puede que no los podrán abrir en el futuro.

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