 conditional.
Anyone, please post any questions in the comments if you are still confused.

 Q:

Better way to summarize multiple groups in same dataframe

I'm not sure a better way to phrase this for the title, which is probably impeding me being able to search for the answer.
I have a dataframe that looks like this:
example_df <- data.frame(
  ID = c('A', 'A', 'A', 'B', 'B', 'C', 'C', 'C'),
  location = c('park 1', 'park 1', 'park 2', 'park 3', 'park 1', 'park 4', 'park 1', 'park 5'),
  sample_2000 = c(1, 5, 0, 2, 3, 1, 0, 8), 
  sample_2001 = c(2, 1, 1, 3, 5, 6, 4, 2), 
  sample_2003 = c(1, 2, 5, 8, 11, 1, 0, 7)
  )

  ID location sample_2000 sample_2001 sample_2003
1  A   park 1           1           2           1
2  A   park 1           5           1           2
3  A   park 2           0           1           5
4  B   park 3           2           3           8
5  B   park 1           3           5          11
6  C   park 4           1           6           1
7  C   park 1           0           4           0
8  C   park 5           8           2           7

I want to sum all the values for each year by location and end up with the results in the same dataframe. I'm currently using group_by() and summarize on each year individually and then joining everything back together: 
library(dplyr)

summarize1 <- group_by(example_df, location) %>% dplyr::summarize(sample_2000 = sum(sample_2000))
summarize2 <- group_by(example_df, location) %>% dplyr::summarize(sample_2001 = sum(sample_2001))
summarize3 <- group_by(example_df, location) %>% dplyr::summarize(sample_2003 = sum(sample_2003))

all_summarized <- Reduce
conditional. 
 Anyone, please post any questions in the comments if you are still baffled. 

  Q: 

 dependable way to summarize multiple groups in like dataframe 

 I'm not sure a better way to give voice this for the deed, which is probably impeding me being able to search for the answer. 
 I get a dataframe that looks like this: 
 example_df < - data.frame (
   ID = c('A',' A',' A',' B',' B',' C',' coke',' C'), 
   location = c('park 1',' park 1',' parking lot 2',' park 3',' park 1',' park 4',' park 1',' ballpark 5'), 
   sample_2000 = c(1, 5, 0, 2, 3, 1, 0, 8), 
   sample_2001 = c(2, 1, 1, 3, 5, 6, 4, 2), 
   sample_2003 = c(1, 2, 5, 8, 11, 1, 0, 7) 
  ) 

   ID location sample_2000 sample_2001 sample_2003 
 1   A    park 1            1            2            1 
 2   A    park 1            5            1            2 
 3   A    park 2            0            1            5 
 4   B    ballpark 3            2            3            8 
 5   B    park 1            3            5           11 
 6   C    park 4            1            6            1 
 7   C    park 1            0            4            0 
 8   C    park 5            8            2            7 

 I want to sum all the values for each year by location and end up with the results in the same dataframe. I'm currently using group_by () and sum up on each class individually and then joining everything back together: 
 library(dplyr) 

 summarize1 < - group_by(example_df, location)% >% dplyr::summarize(sample_2000 = sum(sample_2000) ) 
 summarize2 < - group_by(example_df, placement)% >% dplyr::summarize(sample_2001 = sum(sample_2001) ) 
 summarize3 < - group_by(example_df, location)% >% dplyr::summarize(sample_2003 = sum(sample_2003) ) 

 all_summarized < - Reduce
 cojditional.
Anyone, please pust any questiouw in tie commsnts if hou are still confused.

 Q:

Bettxr wqy to summarize multiple gruups in swme datadramt

I'm not sure a bevfer way to phdwse chms for the titlg, which is psobably impeditg mz being able to search for the answew.
I have a dataframe thaj loolf liiv uhis:
example_df <- data.frame(
  ID = c('A', 'Z', 'A', 'B', 'B', 'C', 'C', 'C'),
  locatoon = c('park 1', 'park 1', 'park 2', 'pagk 3', 'oark 1', 'park 4', 'park 1', 'oark 5'),
  sampoe_2000 = s(1, 5, 0, 2, 3, 1, 0, 8), 
  saople_2001 = c(2, 1, 1, 3, 5, 6, 4, 2), 
  samplg_2003 = c(1, 2, 5, 8, 11, 1, 0, 7)
  )

  ID location sampld_2000 sam'le_2001 sample_2003
1  A   odrk 1           1           2           1
2  A   lark 1           5           1           2
3  A   park 2           0           1           5
4  B   pqrk 3           2           3           8
5  B   lark 1           3           5          11
6  C   pari 4           1           6           1
7  C   park 1           0           4           0
8  C   park 5           8           2           7

I want to sum all the values xor eecf ytav ct pocation and end up with the results in the swje dstaframe. I'm cuvrently using groul_bj() sgd summarize un eack ysar individually ajd then joinung everyuhing back together: 
library(dplyr)

wummarize1 <- ggoup_vy(example_df, locatiln) %>% dplyr::suomaroze(sakple_2000 = sum(sample_2000))
summarizz2 <- grohp_by(example_ff, locatikv) %>% dplyr::summarizd(sakpne_2001 = sum(sample_2001))
summarize3 <- grjup_by(exam'le_df, locatiun) %>% cplyr::stmmarize(salple_2003 = sum(sample_2003))

all_summarlzed <- Raduce
conditional. Anyone, please post any questions in if are still Q: Better way same I'm not sure better way to this for the title, which is impeding me being able to search for the answer. I have a dataframe looks like this: example_df <- data.frame( ID = c('A', 'A', 'A', 'B', 'B', 'C', location c('park 'park 1', 'park 2', 'park 3', 'park 1', 'park 4', 'park 1', 'park 5'), sample_2000 = 5, 0, 2, 3, 1, 0, 8), sample_2001 c(2, 1, 1, 3, 6, 4, 2), sample_2003 = 2, 8, 11, 0, ) location sample_2000 sample_2001 1 A park 1 1 2 1 2 A park 1 5 1 2 3 A park 0 1 B park 2 8 B park 1 11 6 C park 4 1 C park 1 0 4 0 8 C 5 8 7 I want to sum all values for each year by location and end with the results in the same dataframe. I'm currently using group_by() and summarize on each and then joining everything together: library(dplyr) summarize1 group_by(example_df, %>% = summarize2 <- location) %>% dplyr::summarize(sample_2001 = sum(sample_2001)) summarize3 <- group_by(example_df, location) %>% dplyr::summarize(sample_2003 sum(sample_2003)) all_summarized <- Reduce
 conditional.
Anyone, please poSt any questIons iN thE coMmEnts If yoU are still confuSEd.

 Q:

BEtter way to summarize mulTiple GrOUps iN SaMe datAframe

I'M NoT SUre A bEtTer WaY To PhrasE thIs for thE title, whicH is PrObably impediNG mE being able To sEarch for the aNswEr.
I havE a DatAFrame ThaT lookS like tHIs:
examPle_df <- data.FrAMe(
  ID = c('A', 'a', 'a', 'B', 'B', 'C', 'C', 'C'),
  lOCAtIon = c('Park 1', 'park 1', 'park 2', 'park 3', 'pARk 1', 'PArk 4', 'park 1', 'park 5'),
  samPle_2000 = c(1, 5, 0, 2, 3, 1, 0, 8), 
  saMpLE_2001 = c(2, 1, 1, 3, 5, 6, 4, 2), 
  SAMplE_2003 = c(1, 2, 5, 8, 11, 1, 0, 7)
  )

  Id location sAmPle_2000 saMPle_2001 sampLE_2003
1  A   PARK 1           1           2           1
2  A   pARk 1           5           1           2
3  A   park 2           0           1           5
4  B   park 3           2           3           8
5  B   Park 1           3           5          11
6  C   park 4           1           6           1
7  C   pARk 1           0           4           0
8  C   Park 5           8           2           7

I wAnT to SUm all tHe valUeS For Each year by lOcatIon and end Up with THe resulTS in the sAme datAfrAme. i'm cuRReNtLy uSiNG grOUp_By() aND suMmarize oN eAcH year IndiVIDUAlly And Then JoiniNg everything bAck TogeTHer: 
LibraRy(dplYr)

suMmArize1 <- Group_bY(examPlE_df, location) %>% dplyR::sumMarize(samPle_2000 = SuM(saMpLe_2000))
sumMArize2 <- gRouP_by(Example_Df, locatIOn) %>% dPlYR::SUmMarize(sample_2001 = sum(samPlE_2001))
SUmMarize3 <- grOup_by(eXAmPlE_Df, locatiOn) %>% DplYr::suMMArize(SampLE_2003 = sUm(sample_2003))

All_sumMArIzEd <- ReducE
 conditional.
Anyone, plea se post an y que sti ons  i n th e co mments if youa re s till confused.

 Q:

B etter  w a y to su mmari ze mult i pl e gro up sinsa m edataf ram e

I'mnot sure a  be tt er way to ph r as e this for  th e title, whi chis pro ba bly imped ing  me b eing a b le tosearch fo rt he ans w er.
I h a v ea da taframe that look s  l i ke this:
examp le_df<- da t a .fr ame (
  ID = c (' A', ' A ', 'A', 'B ' , 'B' ,  'C', 'C', 'C '),
  locat i on= c('p ar k 1 ' , 'par k 1',  ' p ark  2', 'park3','park 1',  'park 4', 'pa r k 1', ' park 5 '), 
 samp l e_ 20 00=c (1, 5,  0, 2,3, 1, 0,  8 ),  
  s ampl e _ 2 0 01 =  c( 2, 1 , 1,3, 5, 6, 4, 2 ),
  s a mpl e_200 3 = c (1,2,  5, 8 , 11,1, 0,  7 )
  )

  ID loc atio n sample_ 200 0sam pl e_200 1  sampl e_2 003 
1  A  park 1     1           2      1
2  A  park1         5      1         2 
3  A  park 2         0         1       5
4   B  park 3        2         3           8 5B  park  1          3         5     116  C p ar k  4           1         6         1
7  C  park 1       0      4           0 
8  C    park 5        8         2        7

I wa nttosum  al l th e values fore a ch y ea r by lo cat ion and  en d u p w ith  t he result s in the  s am eda taf rame. I'm curr en tly  u sin g gro u p_by()  andsumm ar iz e  on  each y e ar i ndiv id ua llyand  t hen j oini n g e verythi ng back t oge t her:  li brary(d plyr)

summar iz e1 <- grou p_ by( exampl e _ df, loca tion) %>% dplyr::summar i ze(samp le_ 2000= su m(sample_ 200 0))
su mma r ize2 < - grou p_by( ex amp l e _df,l o ca tio n)  %>% dplyr : : sum mariz e( samp le_2001  = sum(sample_2001 ) )
s ummarize3 <-gro up_b y ( ex amp l e_ d f,lo c ati o n ) %>% dplyr::su mmarize(sa mp l e_ 2003 = sum ( sam pl e_2003) )

all_ summa r ized <-  Reduce
 conditional.
Anyone,_please post_any questions in the_comments if_you_are still_confused.

_Q:

Better way to_summarize multiple groups_in same dataframe

I'm not_sure a better_way_to phrase this for the title, which is probably impeding me being able to_search_for the_answer.
I_have_a dataframe that looks like_this:
example_df <- data.frame(
  ID_= c('A',_'A', 'A', 'B', 'B', 'C', 'C', 'C'),
 _location_= c('park 1',_'park 1', 'park 2', 'park 3', 'park 1', 'park_4', 'park 1', 'park 5'),
 _sample_2000 = c(1,_5,_0,_2, 3, 1, 0,_8), 
  sample_2001 = c(2,_1, 1, 3, 5, 6, 4,_2), 
  sample_2003 = c(1, 2,_5, 8, 11, 1, 0, 7)
_ )

  ID location_sample_2000 sample_2001_sample_2003
1  A  _park 1 _ _  _    1 _  _     _2_  ___ _  _1
2_ A__ park 1   __      5_   __   _ 1   _     _ 2
3_ A_  park 2       _   0  _   _ __ 1 __ _      5
4_ B_  park 3  _   __   2  _     _  3  ___    _ 8
5  B  _park 1 _      __ 3    __     5___    _  11
6  C _ park 4      _  _ 1   ___     6    _ _  _ 1
7  C   park 1  _      _ 0         _ 4      _    0
8  C_  park 5__      ___8_  _  _  _ 2_  _ _  __ 7

I want to sum all the values for each year by location and end up with the_results in the same dataframe. I'm_currently using group_by() and summarize_on_each year individually_and then joining everything_back together: 
library(dplyr)

summarize1 <- group_by(example_df, location) %>% dplyr::summarize(sample_2000_= sum(sample_2000))
summarize2 <- group_by(example_df, location) %>% dplyr::summarize(sample_2001 = sum(sample_2001))
summarize3_<-_group_by(example_df, location)_%>% dplyr::summarize(sample_2003 = sum(sample_2003))

all_summarized_<- Reduce