filing in TRUE/FALSE in column of dataframe A based on information in dataframe B
I searched for other topics, but didn't find anything which was really matching what I was looking for.
My dataframes:
UN_match excerpt:
country country_code emissions sector_code year
Austria AT 65779.1172 1.AA 2005
Austria AT 62430.4336 1.AA 2006
Austria AT 59108.4180 1.AA 2007
Austria AT 58656.6719 1.AA 2008
Austria AT 55252.9922 1.AA 2009
Austria AT 58317.9570 1.AA 2010
Austria AT 55898.7344 1.AA 2011
Austria AT 53886.8242 1.AA 2012
Austria AT 53923.7578 1.AA 2013
Austria AT 50087.0000 1.AA 2014
Austria AT 51978.9609 1.AA 2015
Austria AT 52990.2305 1.AA 2016
Belgium BE 103917.1484 1.AA 2005
Belgium BE 102263.9297 1.AA 2006
Belgium BE 100104.8906 1.AA 2007
Belgium BE 99960.6328 1.AA 2008
Belgium BE 92900.2188 1.AA 2009
Belgium BE 96538.8047 1.AA 2010
Belgium BE 87202.2188 1.AA 2011
Belgium BE 86242.7656 1.AA 2012
Belgium BE 86289.1562 1.AA 2013
Belgium BE 80720.1406 1.AA 2014
Belgium BE 84283.8438 1.AA 2015
Belgium BE 84081.2031 1.AA 2016
ETS_match
country country_code value year smaller1.AA
Austria AT 16539.659 2005 0
Austria AT 15275.065 2006 0
Austria AT 14124.646 2007 0
Austria AT 14572.511 2008 0
Austria AT 12767.555 2009 0
Austria AT 15506.112 2010 0
Austria AT 15131.551 2011 0
Austria AT 13121.434 2012 0
Austria AT 8074.514 2013 0
Austria AT 6426.135 2014 0
Austria AT 7514.263 2015 0
Austria AT 7142.937 2016 0
Belgium BE 25460.856 2005 0
Belgium BE 24099.282 2006 0
Belgium BE 23706.084 2007 0
Belgium BE 23166.180 2008 0
Belgium BE 21185.552 2009 0
Belgium BE 22073.616 2010 0
Belgium BE 18950.876 2011 0
Belgium BE 17463.388 2012 0
Belgium BE 16728.267 2013 0
Belgium BE 15230.243 2014 0
Belgium BE 16053.800 2015 0
Belgium BE 15027.777 2016 0
I want to add TRUE or FALSE into ETS_match$smaller1.AA based on whether ETS_match$value < UN_match$emissions is true or false. This should be done for every row.
I tried some things myself with mutate and if_else, but didn't manage to finish it.
It should look like this:
country country_code value year smaller1.AA
Austria AT 16539.659 2005 TRUE
Austria AT 15275.065 2006 TRUE
Austria AT 14124.646 2007 TRUE
I know this is probably very basic, but I would be happy about any kind of help.
Best wishes,
nordsee
r dataframe
asked Nov 22 '18 at 11:34
NordseeNordsee
465
add a comment |
I searched for other topics, but didn't find anything which was really matching what I was looking for.
My dataframes:
UN_match excerpt:
country country_code emissions sector_code year
Austria AT 65779.1172 1.AA 2005
Austria AT 62430.4336 1.AA 2006
Austria AT 59108.4180 1.AA 2007
Austria AT 58656.6719 1.AA 2008
Austria AT 55252.9922 1.AA 2009
Austria AT 58317.9570 1.AA 2010
Austria AT 55898.7344 1.AA 2011
Austria AT 53886.8242 1.AA 2012
Austria AT 53923.7578 1.AA 2013
Austria AT 50087.0000 1.AA 2014
Austria AT 51978.9609 1.AA 2015
Austria AT 52990.2305 1.AA 2016
Belgium BE 103917.1484 1.AA 2005
Belgium BE 102263.9297 1.AA 2006
Belgium BE 100104.8906 1.AA 2007
Belgium BE 99960.6328 1.AA 2008
Belgium BE 92900.2188 1.AA 2009
Belgium BE 96538.8047 1.AA 2010
Belgium BE 87202.2188 1.AA 2011
Belgium BE 86242.7656 1.AA 2012
Belgium BE 86289.1562 1.AA 2013
Belgium BE 80720.1406 1.AA 2014
Belgium BE 84283.8438 1.AA 2015
Belgium BE 84081.2031 1.AA 2016
ETS_match
country country_code value year smaller1.AA
Austria AT 16539.659 2005 0
Austria AT 15275.065 2006 0
Austria AT 14124.646 2007 0
Austria AT 14572.511 2008 0
Austria AT 12767.555 2009 0
Austria AT 15506.112 2010 0
Austria AT 15131.551 2011 0
Austria AT 13121.434 2012 0
Austria AT 8074.514 2013 0
Austria AT 6426.135 2014 0
Austria AT 7514.263 2015 0
Austria AT 7142.937 2016 0
Belgium BE 25460.856 2005 0
Belgium BE 24099.282 2006 0
Belgium BE 23706.084 2007 0
Belgium BE 23166.180 2008 0
Belgium BE 21185.552 2009 0
Belgium BE 22073.616 2010 0
Belgium BE 18950.876 2011 0
Belgium BE 17463.388 2012 0
Belgium BE 16728.267 2013 0
Belgium BE 15230.243 2014 0
Belgium BE 16053.800 2015 0
Belgium BE 15027.777 2016 0
I want to add TRUE or FALSE into ETS_match$smaller1.AA based on whether ETS_match$value < UN_match$emissions is true or false. This should be done for every row.
I tried some things myself with mutate and if_else, but didn't manage to finish it.
It should look like this:
country country_code value year smaller1.AA
Austria AT 16539.659 2005 TRUE
Austria AT 15275.065 2006 TRUE
Austria AT 14124.646 2007 TRUE
I know this is probably very basic, but I would be happy about any kind of help.
Best wishes,
nordsee
r dataframe
asked Nov 22 '18 at 11:34
NordseeNordsee
465
add a comment |
I searched for other topics, but didn't find anything which was really matching what I was looking for.
My dataframes:
UN_match excerpt:
country country_code emissions sector_code year
Austria AT 65779.1172 1.AA 2005
Austria AT 62430.4336 1.AA 2006
Austria AT 59108.4180 1.AA 2007
Austria AT 58656.6719 1.AA 2008
Austria AT 55252.9922 1.AA 2009
Austria AT 58317.9570 1.AA 2010
Austria AT 55898.7344 1.AA 2011
Austria AT 53886.8242 1.AA 2012
Austria AT 53923.7578 1.AA 2013
Austria AT 50087.0000 1.AA 2014
Austria AT 51978.9609 1.AA 2015
Austria AT 52990.2305 1.AA 2016
Belgium BE 103917.1484 1.AA 2005
Belgium BE 102263.9297 1.AA 2006
Belgium BE 100104.8906 1.AA 2007
Belgium BE 99960.6328 1.AA 2008
Belgium BE 92900.2188 1.AA 2009
Belgium BE 96538.8047 1.AA 2010
Belgium BE 87202.2188 1.AA 2011
Belgium BE 86242.7656 1.AA 2012
Belgium BE 86289.1562 1.AA 2013
Belgium BE 80720.1406 1.AA 2014
Belgium BE 84283.8438 1.AA 2015
Belgium BE 84081.2031 1.AA 2016
ETS_match
country country_code value year smaller1.AA
Austria AT 16539.659 2005 0
Austria AT 15275.065 2006 0
Austria AT 14124.646 2007 0
Austria AT 14572.511 2008 0
Austria AT 12767.555 2009 0
Austria AT 15506.112 2010 0
Austria AT 15131.551 2011 0
Austria AT 13121.434 2012 0
Austria AT 8074.514 2013 0
Austria AT 6426.135 2014 0
Austria AT 7514.263 2015 0
Austria AT 7142.937 2016 0
Belgium BE 25460.856 2005 0
Belgium BE 24099.282 2006 0
Belgium BE 23706.084 2007 0
Belgium BE 23166.180 2008 0
Belgium BE 21185.552 2009 0
Belgium BE 22073.616 2010 0
Belgium BE 18950.876 2011 0
Belgium BE 17463.388 2012 0
Belgium BE 16728.267 2013 0
Belgium BE 15230.243 2014 0
Belgium BE 16053.800 2015 0
Belgium BE 15027.777 2016 0
I want to add TRUE or FALSE into ETS_match$smaller1.AA based on whether ETS_match$value < UN_match$emissions is true or false. This should be done for every row.
I tried some things myself with mutate and if_else, but didn't manage to finish it.
It should look like this:
country country_code value year smaller1.AA
Austria AT 16539.659 2005 TRUE
Austria AT 15275.065 2006 TRUE
Austria AT 14124.646 2007 TRUE
I know this is probably very basic, but I would be happy about any kind of help.
Best wishes,
nordsee
r dataframe
asked Nov 22 '18 at 11:34
NordseeNordsee
465
I searched for other topics, but didn't find anything which was really matching what I was looking for.
My dataframes:
UN_match excerpt:
country country_code emissions sector_code year
Austria AT 65779.1172 1.AA 2005
Austria AT 62430.4336 1.AA 2006
Austria AT 59108.4180 1.AA 2007
Austria AT 58656.6719 1.AA 2008
Austria AT 55252.9922 1.AA 2009
Austria AT 58317.9570 1.AA 2010
Austria AT 55898.7344 1.AA 2011
Austria AT 53886.8242 1.AA 2012
Austria AT 53923.7578 1.AA 2013
Austria AT 50087.0000 1.AA 2014
Austria AT 51978.9609 1.AA 2015
Austria AT 52990.2305 1.AA 2016
Belgium BE 103917.1484 1.AA 2005
Belgium BE 102263.9297 1.AA 2006
Belgium BE 100104.8906 1.AA 2007
Belgium BE 99960.6328 1.AA 2008
Belgium BE 92900.2188 1.AA 2009
Belgium BE 96538.8047 1.AA 2010
Belgium BE 87202.2188 1.AA 2011
Belgium BE 86242.7656 1.AA 2012
Belgium BE 86289.1562 1.AA 2013
Belgium BE 80720.1406 1.AA 2014
Belgium BE 84283.8438 1.AA 2015
Belgium BE 84081.2031 1.AA 2016
ETS_match
country country_code value year smaller1.AA
Austria AT 16539.659 2005 0
Austria AT 15275.065 2006 0
Austria AT 14124.646 2007 0
Austria AT 14572.511 2008 0
Austria AT 12767.555 2009 0
Austria AT 15506.112 2010 0
Austria AT 15131.551 2011 0
Austria AT 13121.434 2012 0
Austria AT 8074.514 2013 0
Austria AT 6426.135 2014 0
Austria AT 7514.263 2015 0
Austria AT 7142.937 2016 0
Belgium BE 25460.856 2005 0
Belgium BE 24099.282 2006 0
Belgium BE 23706.084 2007 0
Belgium BE 23166.180 2008 0
Belgium BE 21185.552 2009 0
Belgium BE 22073.616 2010 0
Belgium BE 18950.876 2011 0
Belgium BE 17463.388 2012 0
Belgium BE 16728.267 2013 0
Belgium BE 15230.243 2014 0
Belgium BE 16053.800 2015 0
Belgium BE 15027.777 2016 0
I want to add TRUE or FALSE into ETS_match$smaller1.AA based on whether ETS_match$value < UN_match$emissions is true or false. This should be done for every row.
I tried some things myself with mutate and if_else, but didn't manage to finish it.
It should look like this:
country country_code value year smaller1.AA
Austria AT 16539.659 2005 TRUE
Austria AT 15275.065 2006 TRUE
Austria AT 14124.646 2007 TRUE
I know this is probably very basic, but I would be happy about any kind of help.
Best wishes,
nordsee
r dataframe
r dataframe
asked Nov 22 '18 at 11:34
NordseeNordsee
465
asked Nov 22 '18 at 11:34
NordseeNordsee
465
asked Nov 22 '18 at 11:34
NordseeNordsee
465
asked Nov 22 '18 at 11:34
NordseeNordsee
465
asked Nov 22 '18 at 11:34
NordseeNordsee
465
465
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
Something like this, with dplyr, maybe:
library(dplyr)
UN_match %>% left_join(ETS_match) %>% # join the data
mutate(smaller1.AA = value < emissions, TRUE, FALSE) %>% # add the true false
select(country, country_code, value, year, smaller1.AA) # only useful columns
But all your value are < of emission, so the data are rows are all TRUE in this case.
Improved removing if_else, thanks @Rui Barradas.
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
1
You don't needif_else, just the condition is simpler.
– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
add a comment |
If the datasets have the same number of rows and all the rows align correctly, you can just do:
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
answered Nov 22 '18 at 11:44
ClelandCleland
1556
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
add a comment |
Because the data you're working with are from two different data frames, you have either two options:
- Compare them independently
- Combine the data into one data frame.
For 1, you can do something like
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
For 2, you could use merge to bring the data frames together.
How to join (merge) data frames (inner, outer, left, right)?
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
add a comment |
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3 Answers
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3 Answers
3
active
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active
oldest
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active
oldest
votes
Something like this, with dplyr, maybe:
library(dplyr)
UN_match %>% left_join(ETS_match) %>% # join the data
mutate(smaller1.AA = value < emissions, TRUE, FALSE) %>% # add the true false
select(country, country_code, value, year, smaller1.AA) # only useful columns
But all your value are < of emission, so the data are rows are all TRUE in this case.
Improved removing if_else, thanks @Rui Barradas.
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
1
You don't needif_else, just the condition is simpler.
– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
add a comment |
Something like this, with dplyr, maybe:
library(dplyr)
UN_match %>% left_join(ETS_match) %>% # join the data
mutate(smaller1.AA = value < emissions, TRUE, FALSE) %>% # add the true false
select(country, country_code, value, year, smaller1.AA) # only useful columns
But all your value are < of emission, so the data are rows are all TRUE in this case.
Improved removing if_else, thanks @Rui Barradas.
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
1
You don't needif_else, just the condition is simpler.
– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
add a comment |
Something like this, with dplyr, maybe:
library(dplyr)
UN_match %>% left_join(ETS_match) %>% # join the data
mutate(smaller1.AA = value < emissions, TRUE, FALSE) %>% # add the true false
select(country, country_code, value, year, smaller1.AA) # only useful columns
But all your value are < of emission, so the data are rows are all TRUE in this case.
Improved removing if_else, thanks @Rui Barradas.
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
Something like this, with dplyr, maybe:
library(dplyr)
UN_match %>% left_join(ETS_match) %>% # join the data
mutate(smaller1.AA = value < emissions, TRUE, FALSE) %>% # add the true false
select(country, country_code, value, year, smaller1.AA) # only useful columns
But all your value are < of emission, so the data are rows are all TRUE in this case.
Improved removing if_else, thanks @Rui Barradas.
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
edited Nov 22 '18 at 11:52
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
answered Nov 22 '18 at 11:45
s_ts_t
3,22321030
3,22321030
1
You don't needif_else, just the condition is simpler.
– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
add a comment |
1
You don't needif_else, just the condition is simpler.
– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
1
1
You don't need
if_else, just the condition is simpler.– Rui Barradas
Nov 22 '18 at 11:50
You don't need
if_else, just the condition is simpler.– Rui Barradas
Nov 22 '18 at 11:50
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
Thank you very much for this. Most of the results will be TRUE, but there are also exceptions. The excerpt only showed "TRUE".
– Nordsee
Nov 22 '18 at 12:10
add a comment |
If the datasets have the same number of rows and all the rows align correctly, you can just do:
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
answered Nov 22 '18 at 11:44
ClelandCleland
1556
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
add a comment |
If the datasets have the same number of rows and all the rows align correctly, you can just do:
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
answered Nov 22 '18 at 11:44
ClelandCleland
1556
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
add a comment |
If the datasets have the same number of rows and all the rows align correctly, you can just do:
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
answered Nov 22 '18 at 11:44
ClelandCleland
1556
If the datasets have the same number of rows and all the rows align correctly, you can just do:
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
answered Nov 22 '18 at 11:44
ClelandCleland
1556
answered Nov 22 '18 at 11:44
ClelandCleland
1556
answered Nov 22 '18 at 11:44
ClelandCleland
1556
answered Nov 22 '18 at 11:44
ClelandCleland
1556
1556
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
add a comment |
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
Yes, they are of the same length. And this little code did exactly what I needed. Thank you very much!
– Nordsee
Nov 22 '18 at 12:09
add a comment |
Because the data you're working with are from two different data frames, you have either two options:
- Compare them independently
- Combine the data into one data frame.
For 1, you can do something like
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
For 2, you could use merge to bring the data frames together.
How to join (merge) data frames (inner, outer, left, right)?
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
add a comment |
Because the data you're working with are from two different data frames, you have either two options:
- Compare them independently
- Combine the data into one data frame.
For 1, you can do something like
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
For 2, you could use merge to bring the data frames together.
How to join (merge) data frames (inner, outer, left, right)?
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
add a comment |
Because the data you're working with are from two different data frames, you have either two options:
- Compare them independently
- Combine the data into one data frame.
For 1, you can do something like
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
For 2, you could use merge to bring the data frames together.
How to join (merge) data frames (inner, outer, left, right)?
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
Because the data you're working with are from two different data frames, you have either two options:
- Compare them independently
- Combine the data into one data frame.
For 1, you can do something like
ETS_match$smaller1.AA <- ETS_match$value < UN_match$emissions
For 2, you could use merge to bring the data frames together.
How to join (merge) data frames (inner, outer, left, right)?
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
answered Nov 22 '18 at 11:48
Ken OsborneKen Osborne
111
111
add a comment |
add a comment |
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