Fields may be from the original data and/or fields created by the app, e.g. `n` (frequency). When field is 'label', 'value' can contain a vector of search terms separated by ' OR '.
Text searches are case-insensitive.
Usage
pipe_find_factors(
graf,
field = "label",
value,
operator = "contains",
up = 1,
down = 1,
remove_isolated = F,
highlight_only = F
)Arguments
- field
Field (column, variable) to search
- value
Value to search for
- operator
c('contains','notcontains','=','notequals','greater','less','starts','ends'). How to search.
- up
integer. Default is 0.
- down
integer. Default is 0.
Value
A mapfile containing only matching factors; if `up`!=0 then also factors this number of steps upstream of the matching factors are also included and likewise for `down`!=0. The links are filtered correspondingly to return only the "ego network" i.e. links between the returned factors. If operator and field are both NULL, the value is treated as a simple search string for the field `label`.
Examples
pipe_find_factors(example2,field="label",value="Flood",operator="contains")
#> find factors
#> make info
#> pipe update
#> make info
#> pipe update
#> pipe update
#> finalise
#> pipe update
#> finalise transforms
#> recalc all
#> make info
#> pipe recalc factors
#> make info
#> finalise
#> make info
#> pipe update
#> finalise
#> pipe update
#> finalise
#> pipe update
#> recalc links
#> $factors
#> # A tibble: 8 x 29
#> label id factor_note factor_id0 factor_memo factor_map_id betweenness
#> <chr> <chr> <lgl> <int> <chr> <int> <dbl>
#> 1 "Better fl~ 6 NA 1 "" 1 2
#> 2 "Damage to~ 4 NA 3 "" 1 0
#> 3 "Damage to~ 3 NA 4 "" 1 0
#> 4 "Flood ris~ 7 NA 5 "" 1 2
#> 5 "Flooding ~ 2 NA 6 "" 1 2
#> 6 "Funds fro~ 5 NA 7 "" 1 0
#> 7 "High rain~ 1 NA 8 "" 1 0
#> 8 "Increased~ 8 NA 9 "" 1 0
#> # ... with 22 more variables: betweenness_rank <dbl>, in_degree <dbl>,
#> # out_degree <dbl>, frequency <dbl>, size <dbl>, found <lgl>,
#> # found_type <chr>, map_id <int>, is_flipped <lgl>, role <dbl>,
#> # driver_score <dbl>, outcome_score <dbl>, driver_rank <int>,
#> # outcome_rank <int>, is_opposable <lgl>, zoom_level <dbl>,
#> # top_level_label <chr>, top_level_frequency <dbl>, factor_id <int>,
#> # from_source_count <dbl>, to_source_count <dbl>, source_count <dbl>
#>
#> $links
#> # A tibble: 6 x 62
#> from_label to_label statement_id quote simple_bundle bundle from to note
#> <chr> <chr> <int> <chr> <chr> <chr> <int> <int> <lgl>
#> 1 "High rain~ "Floodi~ 1 Rece~ "High rainfa~ "High~ 8 6 NA
#> 2 "Flooding ~ "Damage~ 1 The ~ "Flooding \U~ "Floo~ 6 4 NA
#> 3 "Flooding ~ "Damage~ 1 The ~ "Flooding \U~ "Floo~ 6 3 NA
#> 4 "Funds fro~ "Better~ 1 Fund~ "Funds from ~ "Fund~ 7 1 NA
#> 5 "Better fl~ "Flood ~ 1 bett~ "Better floo~ "Bett~ 1 5 NA
#> 6 "Flood ris~ "Increa~ 1 redu~ "Flood risk ~ "Floo~ 5 9 NA
#> # ... with 53 more variables: link_id0 <int>, link_id <int>, weight <int>,
#> # strength <int>, certainty <int>, from_flipped <lgl>, to_flipped <lgl>,
#> # link_label <chr>, hashtag <chr>, link_memo <chr>, link_map_id <int>,
#> # s.text <chr>, s.statement_note <lgl>, s.#QuestionID <lgl>,
#> # s.#SourceID <lgl>, s.statement_memo <chr>, s.source_id <chr>,
#> # s.question_id <chr>, s.statement_map_id <dbl>, s.factor_id <int>,
#> # s.r.source_memo <chr>, s.r.source_map_id <dbl>, ...
#>
#> $statements
#> # A tibble: 2 x 21
#> statement_id text statement_note `#QuestionID` `#SourceID` statement_memo
#> <dbl> <chr> <lgl> <lgl> <lgl> <chr>
#> 1 1 Welcome ~ NA NA NA st memo
#> 2 2 Rising s~ NA NA NA NA
#> # ... with 15 more variables: statement_map_id <dbl>, factor_id <int>,
#> # r.source_memo <chr>, r.source_map_id <dbl>, q.question_text <chr>,
#> # q.question_memo <chr>, q.question_map_id <dbl>, label <dbl>,
#> # source_id <chr>, source_memo <chr>, source_map_id <dbl>, question_id <chr>,
#> # question_text <chr>, question_memo <chr>, question_map_id <dbl>
#>
#> $sources
#> # A tibble: 1 x 3
#> source_id source_memo source_map_id
#> <chr> <chr> <dbl>
#> 1 1 ooh 1
#>
#> $questions
#> # A tibble: 1 x 4
#> question_id question_text question_memo question_map_id
#> <chr> <chr> <chr> <dbl>
#> 1 1 global question q memo 1
#>
#> $settings
#> # A tibble: 1 x 3
#> setting_id value map_id
#> <chr> <chr> <chr>
#> 1 background_colour NA 1
#>
#> attr(,"info")
#> attr(,"info")$pipe_find_factors
#> attr(,"info")$pipe_find_factors[[1]]
#> pipe_find_factors
#>
#> attr(,"info")$pipe_find_factors$graf
#> example2
#>
#> attr(,"info")$pipe_find_factors$field
#> [1] "label"
#>
#> attr(,"info")$pipe_find_factors$value
#> [1] "Flood"
#>
#> attr(,"info")$pipe_find_factors$operator
#> [1] "contains"
#>
#>
#> attr(,"info")$pipe_recalculate_factors
#> attr(,"info")$pipe_recalculate_factors[[1]]
#> pipe_recalculate_factors
#>
#> attr(,"info")$pipe_recalculate_factors$graf
#> .
#>
#>
#> attr(,"info")$pipe_recalculate_links
#> attr(,"info")$pipe_recalculate_links[[1]]
#> pipe_recalculate_links
#>
#> attr(,"info")$pipe_recalculate_links$graf
#> .
#>
#>
pipe_find_factors(example2,value="Flood") %>% make_interactive_map
#> find factors
#> make info
#> pipe update
#> make info
#> pipe update
#> pipe update
#> finalise
#> pipe update
#> finalise transforms
#> recalc all
#> make info
#> pipe recalc factors
#> make info
#> finalise
#> make info
#> pipe update
#> finalise
#> pipe update
#> finalise
#> pipe update
#> recalc links
#> pipe update
#> pipe update
#> fix col factors
#> Error: Problem with `mutate()` column `title`.
#> i `title = paste0(...)`.
#> x could not find function "HTML"
pipe_find_factors(example2,value="Flood")
#> find factors
#> make info
#> pipe update
#> make info
#> pipe update
#> pipe update
#> finalise
#> pipe update
#> finalise transforms
#> recalc all
#> make info
#> pipe recalc factors
#> make info
#> finalise
#> make info
#> pipe update
#> finalise
#> pipe update
#> finalise
#> pipe update
#> recalc links
#> $factors
#> # A tibble: 8 x 29
#> label id factor_note factor_id0 factor_memo factor_map_id betweenness
#> <chr> <chr> <lgl> <int> <chr> <int> <dbl>
#> 1 "Better fl~ 6 NA 1 "" 1 2
#> 2 "Damage to~ 4 NA 3 "" 1 0
#> 3 "Damage to~ 3 NA 4 "" 1 0
#> 4 "Flood ris~ 7 NA 5 "" 1 2
#> 5 "Flooding ~ 2 NA 6 "" 1 2
#> 6 "Funds fro~ 5 NA 7 "" 1 0
#> 7 "High rain~ 1 NA 8 "" 1 0
#> 8 "Increased~ 8 NA 9 "" 1 0
#> # ... with 22 more variables: betweenness_rank <dbl>, in_degree <dbl>,
#> # out_degree <dbl>, frequency <dbl>, size <dbl>, found <lgl>,
#> # found_type <chr>, map_id <int>, is_flipped <lgl>, role <dbl>,
#> # driver_score <dbl>, outcome_score <dbl>, driver_rank <int>,
#> # outcome_rank <int>, is_opposable <lgl>, zoom_level <dbl>,
#> # top_level_label <chr>, top_level_frequency <dbl>, factor_id <int>,
#> # from_source_count <dbl>, to_source_count <dbl>, source_count <dbl>
#>
#> $links
#> # A tibble: 6 x 62
#> from_label to_label statement_id quote simple_bundle bundle from to note
#> <chr> <chr> <int> <chr> <chr> <chr> <int> <int> <lgl>
#> 1 "High rain~ "Floodi~ 1 Rece~ "High rainfa~ "High~ 8 6 NA
#> 2 "Flooding ~ "Damage~ 1 The ~ "Flooding \U~ "Floo~ 6 4 NA
#> 3 "Flooding ~ "Damage~ 1 The ~ "Flooding \U~ "Floo~ 6 3 NA
#> 4 "Funds fro~ "Better~ 1 Fund~ "Funds from ~ "Fund~ 7 1 NA
#> 5 "Better fl~ "Flood ~ 1 bett~ "Better floo~ "Bett~ 1 5 NA
#> 6 "Flood ris~ "Increa~ 1 redu~ "Flood risk ~ "Floo~ 5 9 NA
#> # ... with 53 more variables: link_id0 <int>, link_id <int>, weight <int>,
#> # strength <int>, certainty <int>, from_flipped <lgl>, to_flipped <lgl>,
#> # link_label <chr>, hashtag <chr>, link_memo <chr>, link_map_id <int>,
#> # s.text <chr>, s.statement_note <lgl>, s.#QuestionID <lgl>,
#> # s.#SourceID <lgl>, s.statement_memo <chr>, s.source_id <chr>,
#> # s.question_id <chr>, s.statement_map_id <dbl>, s.factor_id <int>,
#> # s.r.source_memo <chr>, s.r.source_map_id <dbl>, ...
#>
#> $statements
#> # A tibble: 2 x 21
#> statement_id text statement_note `#QuestionID` `#SourceID` statement_memo
#> <dbl> <chr> <lgl> <lgl> <lgl> <chr>
#> 1 1 Welcome ~ NA NA NA st memo
#> 2 2 Rising s~ NA NA NA NA
#> # ... with 15 more variables: statement_map_id <dbl>, factor_id <int>,
#> # r.source_memo <chr>, r.source_map_id <dbl>, q.question_text <chr>,
#> # q.question_memo <chr>, q.question_map_id <dbl>, label <dbl>,
#> # source_id <chr>, source_memo <chr>, source_map_id <dbl>, question_id <chr>,
#> # question_text <chr>, question_memo <chr>, question_map_id <dbl>
#>
#> $sources
#> # A tibble: 1 x 3
#> source_id source_memo source_map_id
#> <chr> <chr> <dbl>
#> 1 1 ooh 1
#>
#> $questions
#> # A tibble: 1 x 4
#> question_id question_text question_memo question_map_id
#> <chr> <chr> <chr> <dbl>
#> 1 1 global question q memo 1
#>
#> $settings
#> # A tibble: 1 x 3
#> setting_id value map_id
#> <chr> <chr> <chr>
#> 1 background_colour NA 1
#>
#> attr(,"info")
#> attr(,"info")$pipe_find_factors
#> attr(,"info")$pipe_find_factors[[1]]
#> pipe_find_factors
#>
#> attr(,"info")$pipe_find_factors$graf
#> example2
#>
#> attr(,"info")$pipe_find_factors$value
#> [1] "Flood"
#>
#>
#> attr(,"info")$pipe_recalculate_factors
#> attr(,"info")$pipe_recalculate_factors[[1]]
#> pipe_recalculate_factors
#>
#> attr(,"info")$pipe_recalculate_factors$graf
#> .
#>
#>
#> attr(,"info")$pipe_recalculate_links
#> attr(,"info")$pipe_recalculate_links[[1]]
#> pipe_recalculate_links
#>
#> attr(,"info")$pipe_recalculate_links$graf
#> .
#>
#>
pipe_find_factors(example2,field="id",value=5,operator="greater")
#> find factors
#> make info
#> Error in if (df$found %>% sum %>% ==0) { graf <- (pipe_update_mapfile(graf, factors = graf$factors %>% filter(F), links = graf$links %>% filter(F))) return(graf %>% pipe_recalculate_all())}: missing value where TRUE/FALSE needed