How to write the Mesh from PubMed into a data frame

-1

I recently downloaded the RISmed package to download a little under 500,000 article abstracts from PubMed, and I'm trying to input this data into a data frame. My problem comes when trying to include the Mesh data i get the error message

'Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows:'

Is there a way to nest this information into a data frame for analysis?

RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data.frame('PMID'=PMID(RCT_records), 

                       'Title'=ArticleTitle(RCT_records), 

                       'Abstract'=AbstractText(RCT_records), 

                       'YearPublished'=YearPubmed(RCT_records), 

                       'Month.Published'=MonthPubmed(RCT_records), 

                       'Country'=Country(RCT_records), 

                       'Grant'=GrantID(RCT_records), 

                       'Acronym'=Acronym(RCT_records), 

                       'Agency'=Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

1

Welcome to SO. - Your question will become more clear when you include a MCVE. stackoverflow.com/help/mcve

– Florian
Nov 24 '18 at 3:04

add a comment |

-1

'Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows:'

Is there a way to nest this information into a data frame for analysis?

RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data.frame('PMID'=PMID(RCT_records), 

                       'Title'=ArticleTitle(RCT_records), 

                       'Abstract'=AbstractText(RCT_records), 

                       'YearPublished'=YearPubmed(RCT_records), 

                       'Month.Published'=MonthPubmed(RCT_records), 

                       'Country'=Country(RCT_records), 

                       'Grant'=GrantID(RCT_records), 

                       'Acronym'=Acronym(RCT_records), 

                       'Agency'=Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

1

Welcome to SO. - Your question will become more clear when you include a MCVE. stackoverflow.com/help/mcve

– Florian
Nov 24 '18 at 3:04

add a comment |

-1

'Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows:'

Is there a way to nest this information into a data frame for analysis?

RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data.frame('PMID'=PMID(RCT_records), 

                       'Title'=ArticleTitle(RCT_records), 

                       'Abstract'=AbstractText(RCT_records), 

                       'YearPublished'=YearPubmed(RCT_records), 

                       'Month.Published'=MonthPubmed(RCT_records), 

                       'Country'=Country(RCT_records), 

                       'Grant'=GrantID(RCT_records), 

                       'Acronym'=Acronym(RCT_records), 

                       'Agency'=Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

'Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows:'

Is there a way to nest this information into a data frame for analysis?

RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data.frame('PMID'=PMID(RCT_records), 

                       'Title'=ArticleTitle(RCT_records), 

                       'Abstract'=AbstractText(RCT_records), 

                       'YearPublished'=YearPubmed(RCT_records), 

                       'Month.Published'=MonthPubmed(RCT_records), 

                       'Country'=Country(RCT_records), 

                       'Grant'=GrantID(RCT_records), 

                       'Acronym'=Acronym(RCT_records), 

                       'Agency'=Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

r mesh pubmed

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

asked Nov 24 '18 at 2:08

Manny Ma

asked Nov 24 '18 at 2:08

Manny Ma

asked Nov 24 '18 at 2:08

Manny Ma

1

Welcome to SO. - Your question will become more clear when you include a MCVE. stackoverflow.com/help/mcve

– Florian
Nov 24 '18 at 3:04

add a comment |

1

Welcome to SO. - Your question will become more clear when you include a MCVE. stackoverflow.com/help/mcve

– Florian
Nov 24 '18 at 3:04

Welcome to SO. - Your question will become more clear when you include a MCVE. stackoverflow.com/help/mcve

– Florian
Nov 24 '18 at 3:04

add a comment |

1 Answer
1

active

oldest

votes

Consider using a tibble:

library(RISmed)

library(dplyr) # tibble and other functions



RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data_frame('PMID'=PMID(RCT_records),

                       'Title'=ArticleTitle(RCT_records),

                       'Abstract'=AbstractText(RCT_records),

                       'YearPublished'=YearPubmed(RCT_records),

                       'Month.Published'=MonthPubmed(RCT_records),

                       'Country'= Country(RCT_records),

                       'Grant' =GrantID(RCT_records),

                       'Acronym' =Acronym(RCT_records),

                       'Agency' =Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

The Mesh column is now a list of dataframes:

select(RCT_data, PMID, Mesh)

# # A tibble: 100 x 2

#    PMID     Mesh                 

#    <chr>    <list>               

#  1 29288775 <data.frame [21 × 2]>

#  2 29288545 <data.frame [19 × 2]>

#  3 29288510 <data.frame [15 × 2]>

#  4 29288507 <data.frame [19 × 2]>

#  5 29288478 <data.frame [16 × 2]>

#  6 29288309 <data.frame [19 × 2]>

#  7 29288191 <data.frame [11 × 2]>

#  8 29288190 <data.frame [23 × 2]>

#  9 29288184 <data.frame [21 × 2]>

# 10 29288175 <data.frame [12 × 2]>

# # ... with 90 more rows

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

Consider using a tibble:

library(RISmed)

library(dplyr) # tibble and other functions



RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data_frame('PMID'=PMID(RCT_records),

                       'Title'=ArticleTitle(RCT_records),

                       'Abstract'=AbstractText(RCT_records),

                       'YearPublished'=YearPubmed(RCT_records),

                       'Month.Published'=MonthPubmed(RCT_records),

                       'Country'= Country(RCT_records),

                       'Grant' =GrantID(RCT_records),

                       'Acronym' =Acronym(RCT_records),

                       'Agency' =Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

The Mesh column is now a list of dataframes:

select(RCT_data, PMID, Mesh)

# # A tibble: 100 x 2

#    PMID     Mesh                 

#    <chr>    <list>               

#  1 29288775 <data.frame [21 × 2]>

#  2 29288545 <data.frame [19 × 2]>

#  3 29288510 <data.frame [15 × 2]>

#  4 29288507 <data.frame [19 × 2]>

#  5 29288478 <data.frame [16 × 2]>

#  6 29288309 <data.frame [19 × 2]>

#  7 29288191 <data.frame [11 × 2]>

#  8 29288190 <data.frame [23 × 2]>

#  9 29288184 <data.frame [21 × 2]>

# 10 29288175 <data.frame [12 × 2]>

# # ... with 90 more rows

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

add a comment |

Consider using a tibble:

library(RISmed)

library(dplyr) # tibble and other functions



RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data_frame('PMID'=PMID(RCT_records),

                       'Title'=ArticleTitle(RCT_records),

                       'Abstract'=AbstractText(RCT_records),

                       'YearPublished'=YearPubmed(RCT_records),

                       'Month.Published'=MonthPubmed(RCT_records),

                       'Country'= Country(RCT_records),

                       'Grant' =GrantID(RCT_records),

                       'Acronym' =Acronym(RCT_records),

                       'Agency' =Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

The Mesh column is now a list of dataframes:

select(RCT_data, PMID, Mesh)

# # A tibble: 100 x 2

#    PMID     Mesh                 

#    <chr>    <list>               

#  1 29288775 <data.frame [21 × 2]>

#  2 29288545 <data.frame [19 × 2]>

#  3 29288510 <data.frame [15 × 2]>

#  4 29288507 <data.frame [19 × 2]>

#  5 29288478 <data.frame [16 × 2]>

#  6 29288309 <data.frame [19 × 2]>

#  7 29288191 <data.frame [11 × 2]>

#  8 29288190 <data.frame [23 × 2]>

#  9 29288184 <data.frame [21 × 2]>

# 10 29288175 <data.frame [12 × 2]>

# # ... with 90 more rows

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

add a comment |

Consider using a tibble:

library(RISmed)

library(dplyr) # tibble and other functions



RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data_frame('PMID'=PMID(RCT_records),

                       'Title'=ArticleTitle(RCT_records),

                       'Abstract'=AbstractText(RCT_records),

                       'YearPublished'=YearPubmed(RCT_records),

                       'Month.Published'=MonthPubmed(RCT_records),

                       'Country'= Country(RCT_records),

                       'Grant' =GrantID(RCT_records),

                       'Acronym' =Acronym(RCT_records),

                       'Agency' =Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

The Mesh column is now a list of dataframes:

select(RCT_data, PMID, Mesh)

# # A tibble: 100 x 2

#    PMID     Mesh                 

#    <chr>    <list>               

#  1 29288775 <data.frame [21 × 2]>

#  2 29288545 <data.frame [19 × 2]>

#  3 29288510 <data.frame [15 × 2]>

#  4 29288507 <data.frame [19 × 2]>

#  5 29288478 <data.frame [16 × 2]>

#  6 29288309 <data.frame [19 × 2]>

#  7 29288191 <data.frame [11 × 2]>

#  8 29288190 <data.frame [23 × 2]>

#  9 29288184 <data.frame [21 × 2]>

# 10 29288175 <data.frame [12 × 2]>

# # ... with 90 more rows

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

Consider using a tibble:

library(RISmed)

library(dplyr) # tibble and other functions



RCT_topic <- 'randomized clinical trial'

RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)

summary(RCT_query)

RCT_records <- EUtilsGet(RCT_query)



RCT_data <- data_frame('PMID'=PMID(RCT_records),

                       'Title'=ArticleTitle(RCT_records),

                       'Abstract'=AbstractText(RCT_records),

                       'YearPublished'=YearPubmed(RCT_records),

                       'Month.Published'=MonthPubmed(RCT_records),

                       'Country'= Country(RCT_records),

                       'Grant' =GrantID(RCT_records),

                       'Acronym' =Acronym(RCT_records),

                       'Agency' =Agency(RCT_records),

                       'Mesh'=Mesh(RCT_records))

The Mesh column is now a list of dataframes:

select(RCT_data, PMID, Mesh)

# # A tibble: 100 x 2

#    PMID     Mesh                 

#    <chr>    <list>               

#  1 29288775 <data.frame [21 × 2]>

#  2 29288545 <data.frame [19 × 2]>

#  3 29288510 <data.frame [15 × 2]>

#  4 29288507 <data.frame [19 × 2]>

#  5 29288478 <data.frame [16 × 2]>

#  6 29288309 <data.frame [19 × 2]>

#  7 29288191 <data.frame [11 × 2]>

#  8 29288190 <data.frame [23 × 2]>

#  9 29288184 <data.frame [21 × 2]>

# 10 29288175 <data.frame [12 × 2]>

# # ... with 90 more rows

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

edited Nov 25 '18 at 21:39

marc_s

578k12911161262

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

answered Nov 24 '18 at 3:42

Weihuang Wong

9,6801835

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

add a comment |

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

OMG it works like a charm thank you very much,

– Manny Ma
Nov 24 '18 at 4:09

saving this data frame wouldn't work for a csv correct? what would be the correct format to be able to export data frame ingrained with data frames?

– Manny Ma
Nov 26 '18 at 21:39

Usually, you would raise follow-up questions as a new question. This will allow others to find the answer. In the mean time, you can check out github.com/tidyverse/tibble/issues/202 (or just save it as an RDS file).

– Weihuang Wong
Nov 27 '18 at 3:40

add a comment |

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