quitar colummnas de comunidades que se repiten

[davidperezmartorell]

en las tablas tenemos info delestudio y info de las comunidades. se esta repitiendo info. quitar de abajo (donde las cassemblages) de las comunidades todas las disturbances, origina effort, numero de comunities

[davidperezmartorell]

hecho

[davidperezmartorell]

me doy cuena que algunos estudios tienen columnas comunes o diferentes que no son las mismas que otros estdios. asi que vuelvo a la version que tenia que esta division era dinámica. Los campos comunes apareceran arriba y los campos diferentes apareceran abajo.

[davidperezmartorell]

ok, realizado. solo nos queda saber las columnas de assembleages que definitivamente no queremos nunca.

Veamos los pasos que hago [paso1] elimino las siguientes columnas -id,-id_comm, -plot, -exact_lat, -exact_long, -country, -ScaleRank, -LabelRank, -FeatureCla, -SOV_A3, -ADM0_DIF, -ADM0_DIF, -LEVEL, -TYPE, -ADMIN, -ADM0_A3, -GEOU_DIF, -GEOUNIT, -GU_A3, -SU_DIF, -SUBUNIT, -SU_A3 , -NAME , -ABBREV , -POSTAL , -NAMEFORMA , -TERR, -NAME_SORT, -MAP_COLOR, -POP_EST, -GDP_MD_EST, -FIPS10, -ISO_A2, -ISO_A3, -ISO_N3, -ISO3, -LON, -LAT, -ISO3.1, -ADMIN.1, -REGION, -continent, -GEO3major , -GEO3, -IMAGE24, -GLOCAF, -Stern, -SRESmajor, -SRES, -GBD, -AVOIDnumeric, -AVOIDname, -LDC, -SID, -LLDC, -Country

[paso2] quito los valores que contienen para todo el dataframe NA [paso3] separo los datos entre unicos o repetidos

Lo que me interesa es saber las columnas que segun el origen y tu experiencia deben filtrarse siempre. Esta info aparecerá en la tabla que contendrá el study_clicked divididos por datos comunes y las assembleages con valors diferentes.

recuerdo alguna columna que no nos interesaba como el shanon, notes, history, abund. aqui las columnas posibles a filtrar la idea es marcar de alguna manera las que no quieres que aparezcan nunca y ponerlas junto al paso1 AQUI mi propuesta

$ database [QUITAR. NO APORTA Y SE PODRÁ IR AL ESTUDIO] : chr [1:5] "RU" "RU" "RU" "RU" ...
$ id_study [QUITAR] : chr [1:5] "RU_Addo-Fordjour 2019_Liana" "RU_Addo-Fordjour 2019_Liana" "RU_Addo-Fordjour 2019_Liana" "RU_Addo-Fordjour 2019_Liana" ...
$ id_study_ori [QUITAR. NO APORTA Y SE PODRÁ IR AL ESTUDIO] : chr [1:5] NA NA NA NA ...
$ citation [MANTENER Y AGREGAR ENLACE] : chr [1:5] "Addo-Fordjour 2019" "Addo-Fordjour 2019" "Addo-Fordjour 2019" "Addo-Fordjour 2019" ...
$ study [MANTENER] : chr [1:5] "Liana" "Liana" "Liana" "Liana" ...
$ site [MANTENER, el unico que identificra indivualidad de comunidad] : chr [1:5] "Sit1" "Sit2" "Sit3" "Sit4" ...
$ id_comm_source [REPETIDO] : chr [1:5] "2-year" "14-year" "Stage 1" "Stage 4" ...
$ age [MANTENER] : num [1:5] 2 14 40 68 200
$ age_ori [REPETIDO] : chr [1:5] "2" "14" "40" "68" ...
$ study_year [MANTENER] : int [1:5] 2016 2016 2016 2016 2016
$ temp_persp_class2 [MANTENER] : chr [1:5] "exact" "exact" "exact" "exact" ...
$ stage [MANTENER] : chr [1:5] "recovering" "recovering" "recovering" "recovering" ...
$ study_common_taxon [MANTENER] : chr [1:5] "lianas" "lianas" "lianas" "lianas" ...
$ organism_threshold [MANTENER] : chr [1:5] "diameter (at 1.3 m from rooting base) >=1 cm" "diameter (at 1.3 m from rooting base) >=1 cm" "diameter (at 1.3 m from rooting base) >=1 cm" "diameter (at 1.3 m from rooting base) >=1 cm" ...
$ metric [MANTENER] : chr [1:5] "abundance" "abundance" "abundance" "abundance" ...
$ metric_source [MANTENER] : chr [1:5] "species abundance" "species abundance" "species abundance" "species abundance" ...
$ aggregated_data [MANTENER] : chr [1:5] "yes" "yes" "yes" "yes" ...
$ sampling_method [MANTENER] : chr [1:5] "lianas of a diameter (at 1.3 m from rooting base) >=1 cm were identified, counted and their diameter measured u"| truncated "lianas of a diameter (at 1.3 m from rooting base) >=1 cm were identified, counted and their diameter measured u"| truncated "lianas of a diameter (at 1.3 m from rooting base) >=1 cm were identified, counted and their diameter measured u"| truncated "lianas of a diameter (at 1.3 m from rooting base) >=1 cm were identified, counted and their diameter measured u"| truncated ...
$ sampling_effort_within [QUITAR. NO APORTA Y SE PODRÁ IR AL ESTUDIO] : num [1:5] 1 1 1 1 1
$ sampling_effort_among [QUITAR. NO APORTA Y SE PODRÁ IR AL ESTUDIO] : logi [1:5] NA NA NA NA NA
$ n_comm [MANTENER] : int [1:5] 20 20 20 20 20
$ n_comm_available [MANTENER] : int [1:5] 5 5 5 5 5
$ effort_ori [QUITAR. NO APORTA Y SE PODRÁ IR AL ESTUDIO] : num [1:5] 32000 32000 32000 32000 32000
$ historic_impact [QUITAR.DATOS DUDOSOS] : chr [1:5] "The Reserve, since its creation in 1938, has been managed for timber extraction" "The Reserve, since its creation in 1938, has been managed for timber extraction" "The Reserve, since its creation in 1938, has been managed for timber extraction" "The Reserve, since its creation in 1938, has been managed for timber extraction" ...
$ predisturbances [QUITAR] : chr [1:5] NA NA NA NA ...
$ disturbance1_age [QUITAR] : chr [1:5] "selective logging" "selective logging" "selective logging" "selective logging" ...
$ disturbance2 [QUITAR] : chr [1:5] NA NA NA NA ...
$ n_disturbances [QUITAR] : int [1:5] 1 1 1 1 0
$current_impact: [MANTENER] chr [1:5] "none" "none" "none" "none" ...
$ notes: [QUITAR] chr [1:5] "los datos están agregados no solo en cada pseudoreplica sino de las dos replicas de cada edad juntas" "los datos están agregados no solo en cada pseudoreplica sino de las dos replicas de cada edad juntas" "los datos están agregados no solo en cada pseudoreplica sino de las dos replicas de cada edad juntas" "los datos están agregados no solo en cada pseudoreplica sino de las dos replicas de cada edad juntas" ...
$ priority: [QUITAR]chr [1:5] NA NA NA NA ...
$ study_common_taxon_clean [QUITAR] : chr [1:5] "lianas" "lianas" "lianas" "lianas" ...
$ study_common_taxon_strgroup: [QUITAR] chr [1:5] "users" "users" "users" "users" ...
$ disturbance1_age_clean [MANTENER] : chr [1:5] "logging" "logging" "logging" "logging" ...
$ disturbance2_clean [MANTENER] : chr [1:5] NA NA NA NA ...
$ predisturbances_clean [MANTENER] : chr [1:5] NA NA NA NA ...
$ current_impact_clean [MANTENER] : chr [1:5] "none" "none" "none" "none" ...
$ postdisturbance [MANTENER] : chr [1:5] "none" "none" "none" "none" ...
$ restoration [MANTENER] : int [1:5] 0 0 0 0 0
$ protection [MANTENER] : int [1:5] 0 0 0 0 0
$ use: [MANTENER] chr [1:5] "none" "none" "none" "none" ...
$ recovering_cond:[MANTENER] chr [1:5] "regular" "regular" "regular" "regular" ...
$ coord_accuracy: [QUITAR]chr [1:5] "study" "study" "study" "study" ...
$ taxon_level:[MANTENER] chr [1:5] "species" "species" "species" "species" ...
$ richness_study [MANTENER] : int [1:5] 45 45 45 45 45
$ richness: [MANTENER] int [1:5] 24 30 31 28 25 $ abund : num [1:5] 808 917 849 649 1557
$ shannon: [QUITAR] num [1:5] 3.48 3.8 3.83 3.82 3.74 $ PD : num [1:5] 1325 1796 1563 1617 1459 $ SR : int [1:5] 20 25 23 23 20
$ error_class: [QUITAR] num [1:5] 0.0222 0.0222 0.0222 0.0222 0.0222
$ lon : num [1:5] -1.31 -1.31 -1.31 -1.31 -1.31
$ lat: num [QUITAR] [1:5] 6.7 6.7 6.7 6.7 6.7

[davidperezmartorell]

hecho. pintamos un esquema de la info que queermos y la que no. ya está ejcutado en el programa