JavaFX GridPane rowspan height error - javafx

It seems to me, that GridPane calculates wrong height over its Nodes when I use rowspan.
// 01 - Half OK
final GridPane gp = new GridPane();
gp.add( new Text( "aaa\nbbb\nccc\nddd\neee" ), 0, 0, 1, 2 );
gp.add( new Text( "aaaa1" ), 1, 0, 1, 1 );
gp.add( new Text( "aaaa2" ), 1, 1, 1, 1 );
gp.setGridLinesVisible( true );
new VBox( 8, new Text( "text1" ), gp, new Text( "text2" ) );
"Half OK" because height of "aaaa1" and "aaaa2" differs.
See the picture.
// 02 - BAD
final GridPane gp = new GridPane();
gp.add( new Text( "aaa\nbbb\nccc\nddd\neee" ), 0, 0, 1, 2 );
gp.add( new Text( "aaaa1" ), 1, 0, 1, 1 );
gp.add( new Text( "aaaa2" ), 1, 1, 1, 2 ); // '1' -> '2'
gp.setGridLinesVisible( true );
new VBox( 8, new Text( "text1" ), gp, new Text( "text2" ) );
// 03 - BAD
final GridPane gp = new GridPane();
gp.add( new Text( "aaa\nbbb\nccc\nddd\neee" ), 0, 0, 1, 3 );
gp.add( new Text( "aaaa1" ), 1, 0, 1, 1 );
gp.add( new Text( "aaaa2" ), 1, 1, 1, 2 );
gp.setGridLinesVisible( true );
new VBox( 8, new Text( "text1" ), gp, new Text( "text2" ) );
// 04 - BAD
final GridPane gp = new GridPane();
gp.add( new Text( "aaa\nbbb\nccc\nddd\neee" ), 0, 0, 1, 3 );
gp.add( new Text( "aaaa1" ), 1, 0, 1, 1 );
gp.add( new Text( "aaaa2" ), 1, 1, 1, 2 );
gp.add( new Text( "xxx11" ), 2, 0, 1, 1 );
gp.add( new Text( "xxx21" ), 2, 1, 1, 1 );
gp.add( new Text( "xxx22" ), 2, 2, 1, 1 );
gp.setGridLinesVisible( true );
new VBox( 8, new Text( "text1" ), gp, new Text( "text2" ) );
Is it JavaFX error or something can be fixed?
Image: https://imgur.com/3USWNyQ

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Combining values of two different keys [closed]

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I have an id that has a match nested deep in a map. I need to locate the match and return that map.
It's a bit more complicated than that though. Inside this large map there are keys called home and away and the id that I have could be nested in either one of those keys.
I'm trying to find a way to essentially flatten those two keys into one so that I can compare against all of the values.
CURRENT ATTEMPT:
Map.take(game, ["away", "home"]) |> Map.get("players")
But this return nil
To be a little more clear:
This is the method I'm using to dig into the map:
defp evaluate_player_points(game, question) do
Map.get(game, "away")
|> Map.get("players")
|> Enum.find(fn %{"id" => id} -> question.player_id == id end)
|> Map.get("statistics")
|> Map.get("points")
end
But as you can see the top Map.get needs to be dynamic to look for either home or away
MAP (I'm posting the entire thing but it's quite large)
%{"attendance" => 13548,
"away" => %{"alias" => "DET", "bonus" => true,
"coaches" => [%{"first_name" => "Charles", "full_name" => "Charles Klask",
"last_name" => "Klask", "position" => "Assistant Coach",
"reference" => "202894"},
%{"first_name" => "Aaron", "full_name" => "Aaron Gray",
"last_name" => "Gray", "position" => "Assistant Coach",
"reference" => "1628254"},
%{"first_name" => "Stan", "full_name" => "Stan Van Gundy",
"id" => "e4abb843-1259-4aee-95f3-2ab748d510e4",
"last_name" => "Van Gundy", "position" => "Head Coach",
"reference" => "1277"},
%{"first_name" => "Bob", "full_name" => "Bob Beyer",
"last_name" => "Beyer", "position" => "Assistant Coach",
"reference" => "2630"},
%{"first_name" => "Jon", "full_name" => "Jon Ishop",
"last_name" => "Ishop", "position" => "Trainer",
"reference" => "202605"},
%{"first_name" => "Otis", "full_name" => "Otis Smith",
"last_name" => "Smith", "position" => "Assistant Coach",
"reference" => "2542"},
%{"first_name" => "Malik", "full_name" => "Malik Allen",
"last_name" => "Allen", "position" => "Assistant Coach",
"reference" => "204229"},
%{"first_name" => "Tim", "full_name" => "Tim Hardaway",
"last_name" => "Hardaway", "position" => "Assistant Coach",
"reference" => "204230"}],
"id" => "583ec928-fb46-11e1-82cb-f4ce4684ea4c", "market" => "Detroit",
"name" => "Pistons",
"players" => [%{"active" => true, "first_name" => "Reggie",
"full_name" => "Reggie Jackson",
"id" => "7b745dde-a011-45a8-98a8-460a9facb3ce", "jersey_number" => "1",
"last_name" => "Jackson", "played" => true, "position" => "G",
"primary_position" => "PG", "reference" => "202704", "starter" => true,
"statistics" => %{"efficiency" => 2, "triple_double" => false,
"defensive_rating" => 110.206452594306, "second_chance_att" => 0,
"points" => 11, "minus" => 60, "points_in_paint_att" => 7,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 3,
"two_points_att" => 8, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 1, "offensive_rating" => 89.2874338761532,
"offensive_rebounds" => 0, "second_chance_pct" => 0.0,
"true_shooting_att" => 11.0, "two_points_pct" => 50.0,
"points_in_paint" => 6, "assists_turnover_ratio" => 1.25,
"steals_pct" => 0.0, "rebounds_pct" => 0.0, "field_goals_made" => 5,
"periods" => [%{"efficiency" => 6, "number" => 1, ...},
%{"efficiency" => -3, ...}, %{...}, ...], "offensive_fouls" => 0,
"free_throws_pct" => 0.0, "points_in_paint_made" => 3, ...}},
%{"first_name" => "Luis", "full_name" => "Luis Montero",
"id" => "9304e1de-0d5a-4ccb-9409-100342405041", "jersey_number" => "44",
"last_name" => "Montero", "position" => "G-F",
"primary_position" => "SG", "reference" => "1626242",
"statistics" => %{"efficiency" => 0, "triple_double" => false,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, "blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 0, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 0.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 0.0, "field_goals_made" => 0,
"periods" => [%{"efficiency" => 0, "number" => 1,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, ...},
%{"efficiency" => 0, "number" => 2, "second_chance_att" => 0,
"points" => 0, "minus" => 0, ...},
%{"efficiency" => 0, "number" => 3, "second_chance_att" => 0,
"points" => 0, ...},
%{"efficiency" => 0, "number" => 4, "second_chance_att" => 0,
"points" => 0, ...}], "offensive_fouls" => 0,
"free_throws_pct" => 0.0, "points_in_paint_made" => 0,
"second_chance_pts" => 0, "true_shooting_pct" => 0,
"free_throws_made" => 0, "three_points_pct" => 0.0, ...}},
%{"active" => true, "first_name" => "Stanley",
"full_name" => "Stanley Johnson",
"id" => "6ed42a42-6fd6-464c-8425-7e40489c679f", "jersey_number" => "7",
"last_name" => "Johnson", "played" => true, "position" => "F",
"primary_position" => "SF", "reference" => "1626169",
"statistics" => %{"efficiency" => 4, "triple_double" => false,
"defensive_rating" => 107.894802391447, "second_chance_att" => 1,
"points" => 2, "minus" => 32, "points_in_paint_att" => 1,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 16.6695606876194,
"points_off_turnovers" => 0, "two_points_att" => 1,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 0,
"offensive_rating" => 128.304656155027, "offensive_rebounds" => 0,
"second_chance_pct" => 100.0, "true_shooting_att" => 2.0,
"two_points_pct" => 100.0, "points_in_paint" => 2,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 8.12641083521444, "field_goals_made" => 1,
"periods" => [%{"efficiency" => 0, ...}, %{...}, ...],
"offensive_fouls" => 0, "free_throws_pct" => 0.0, ...}},
%{"active" => true, "first_name" => "Boban",
"full_name" => "Boban Marjanovic",
"id" => "24c17409-ac10-4859-be6c-59d6cc6b5810", "jersey_number" => "51",
"last_name" => "Marjanovic", "position" => "C",
"primary_position" => "C", "reference" => "1626246",
"statistics" => %{"efficiency" => 0, "triple_double" => false,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, "blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 0, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 0.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 0.0, "field_goals_made" => 0,
"periods" => [%{"efficiency" => 0, "number" => 1,
"second_chance_att" => 0, ...},
%{"efficiency" => 0, "number" => 2, ...}, %{"efficiency" => 0, ...},
%{"efficiency" => 0, ...}], "offensive_fouls" => 0,
"free_throws_pct" => 0.0, "points_in_paint_made" => 0,
"second_chance_pts" => 0, ...}},
%{"first_name" => "Dwight", "full_name" => "Dwight Buycks",
"id" => "14d86dbd-5e05-4a2e-951b-96d4e1e2e8f1", "jersey_number" => "20",
"last_name" => "Buycks", "position" => "G", "primary_position" => "PG",
"reference" => "202779",
"statistics" => %{"efficiency" => 0, "triple_double" => false,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, "blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 0, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 0.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 0.0, "field_goals_made" => 0,
"periods" => [%{"efficiency" => 0, "number" => 1,
"second_chance_att" => 0, ...},
%{"efficiency" => 0, "number" => 2, ...}, %{"efficiency" => 0, ...},
%{"efficiency" => 0, ...}], "offensive_fouls" => 0,
"free_throws_pct" => 0.0, "points_in_paint_made" => 0,
"second_chance_pts" => 0, ...}},
%{"active" => true, "first_name" => "Avery",
"full_name" => "Avery Bradley",
"id" => "b23917d2-bb0d-49fa-a384-80d994561d0c", "jersey_number" => "22",
"last_name" => "Bradley", "played" => true, "position" => "G",
"primary_position" => "SG", "reference" => "202340", "starter" => true,
"statistics" => %{"efficiency" => 12, "triple_double" => false,
"defensive_rating" => 105.701631730746, "second_chance_att" => 2,
"points" => 18, "minus" => 56, "points_in_paint_att" => 10,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 4.60962258715068,
"points_off_turnovers" => 0, "two_points_att" => 13,
"flagrant_fouls" => 0, "steals" => 1, "fast_break_att" => 3,
"offensive_rating" => 122.024148849322, "offensive_rebounds" => 0,
"second_chance_pct" => 50.0, "true_shooting_att" => 15.88,
"two_points_pct" => 38.5, "points_in_paint" => 8,
"assists_turnover_ratio" => 3.0, "steals_pct" => 1.96604637903408,
"rebounds_pct" => 2.24719101123596, ...}},
%{"first_name" => "Jon", "full_name" => "Jon Leuer",
"id" => "ee9ddf70-f50d-49b0-846c-f83719b095d8", "jersey_number" => "30",
"last_name" => "Leuer", "position" => "F", "primary_position" => "PF",
"reference" => "202720",
"statistics" => %{"efficiency" => 0, "triple_double" => false,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, "blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 0, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 0.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 0.0, "field_goals_made" => 0,
"periods" => [%{"efficiency" => 0, ...}, %{...}, ...],
"offensive_fouls" => 0, "free_throws_pct" => 0.0, ...}},
%{"active" => true, "first_name" => "Andre",
"full_name" => "Andre Drummond",
"id" => "440b769d-2b8b-477f-80d7-cb21d83c0d52", "jersey_number" => "0",
"last_name" => "Drummond", "played" => true, "position" => "C",
"primary_position" => "C", "reference" => "203083", "starter" => true,
"statistics" => %{"efficiency" => 35, "triple_double" => false,
"defensive_rating" => 90.4494098612691, "second_chance_att" => 4,
"points" => 12, "minus" => 72, "points_in_paint_att" => 11,
"blocks" => 2, "double_double" => true,
"defensive_rebounds_pct" => 46.3954893274265,
"points_off_turnovers" => 2, "two_points_att" => 11,
"flagrant_fouls" => 0, "steals" => 2, "fast_break_att" => 0,
"offensive_rating" => 119.432386646934, "offensive_rebounds" => 7,
"second_chance_pct" => 25.0, "true_shooting_att" => 12.76,
"two_points_pct" => 36.4, "points_in_paint" => 8,
"assists_turnover_ratio" => 2.67, ...}},
%{"active" => true, "first_name" => "Anthony",
"full_name" => "Anthony Tolliver",
"id" => "33a91bda-9f4d-4f80-97d8-9bc574f6afc2", "jersey_number" => "43",
"last_name" => "Tolliver", "played" => true, "position" => "F",
"primary_position" => "PF", "reference" => "201229",
"statistics" => %{"efficiency" => 2, "triple_double" => false,
"defensive_rating" => 108.985437894358, "second_chance_att" => 0,
"points" => 6, "minus" => 27, "points_in_paint_att" => 1,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 8.1595255235908,
"points_off_turnovers" => 0, "two_points_att" => 1,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 0,
"offensive_rating" => 87.2688729807194, "offensive_rebounds" => 1,
"second_chance_pct" => 0.0, "true_shooting_att" => 5.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0.0, ...}},
%{"active" => true, "first_name" => "Langston",
"full_name" => "Langston Galloway",
"id" => "138f5c1f-b8e6-4e7c-b8ef-ecb7faa7b936", "jersey_number" => "9",
"last_name" => "Galloway", "played" => true, "position" => "G",
"primary_position" => "PG", "reference" => "204038",
"statistics" => %{"efficiency" => 16, "triple_double" => false,
"defensive_rating" => 97.5742878357504, "second_chance_att" => 2,
"points" => 17, "minus" => 30, "points_in_paint_att" => 0,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 11.3872249570014,
"points_off_turnovers" => 8, "two_points_att" => 2,
"flagrant_fouls" => 0, "steals" => 2, "fast_break_att" => 3,
"offensive_rating" => 149.110748320568, "offensive_rebounds" => 1,
"second_chance_pct" => 50.0, "true_shooting_att" => 11.0,
"two_points_pct" => 50.0, "points_in_paint" => 0, ...}},
%{"active" => true, "first_name" => "Luke", "full_name" => "Luke Kennard",
"id" => "a537047d-c29f-4dfe-99b0-3bac4e258dc7", "jersey_number" => "5",
"last_name" => "Kennard", "played" => true, "position" => "G",
"primary_position" => "SG", "reference" => "1628379",
"statistics" => %{"efficiency" => 1, "triple_double" => false,
"defensive_rating" => 93.8002338872659, "second_chance_att" => 2,
"points" => 4, "minus" => 29, "points_in_paint_att" => 1,
"blocks" => 1, "double_double" => false,
"defensive_rebounds_pct" => 6.39360639360639,
"points_off_turnovers" => 4, "two_points_att" => 4,
"flagrant_fouls" => 0, "steals" => 2, "fast_break_att" => 2,
"offensive_rating" => 61.1978132880953, "offensive_rebounds" => 1,
"second_chance_pct" => 50.0, "true_shooting_att" => 8.88,
"two_points_pct" => 25.0, ...}},
%{"active" => true, "first_name" => "Ish", "full_name" => "Ish Smith",
"id" => "05a90cd6-73de-43d5-9d30-bc2588d03262", "jersey_number" => "14",
"last_name" => "Smith", "played" => true, "position" => "G",
"primary_position" => "PG", "reference" => "202397",
"statistics" => %{"efficiency" => -3, "triple_double" => false,
"defensive_rating" => 105.148783281487, "second_chance_att" => 0,
"points" => 4, "minus" => 19, "points_in_paint_att" => 3,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 11.988011988012,
"points_off_turnovers" => 0, "two_points_att" => 5,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 1,
"offensive_rating" => 79.5442808328467, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 5.0, ...}},
%{"active" => true, "first_name" => "Tobias",
"full_name" => "Tobias Harris",
"id" => "82f09975-6a8d-42e4-b42c-a52b9349ed50", "jersey_number" => "34",
"last_name" => "Harris", "played" => true, "position" => "F",
"primary_position" => "PF", "reference" => "202699", "starter" => true,
"statistics" => %{"efficiency" => 20, "triple_double" => false,
"defensive_rating" => 103.725507249097, "second_chance_att" => 1,
"points" => 19, "minus" => 59, "points_in_paint_att" => 3,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 15.91537661625,
"points_off_turnovers" => 2, "two_points_att" => 8,
"flagrant_fouls" => 0, "steals" => 1, "fast_break_att" => 0,
"offensive_rating" => 151.395288813852, "offensive_rebounds" => 0,
...}},
%{"active" => true, "first_name" => "Eric", "full_name" => "Eric Moreland",
"id" => "e54fcd7e-82d0-4599-9d64-ac14532f0cde", "jersey_number" => "24",
"last_name" => "Moreland", "played" => true, "position" => "F-C",
"primary_position" => "PF", "reference" => "203961",
"statistics" => %{"efficiency" => 9, "triple_double" => false,
"defensive_rating" => 92.9346584762599, "second_chance_att" => 1,
"points" => 0, "minus" => 17, "points_in_paint_att" => 2,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 55.8286525605163,
"points_off_turnovers" => 0, "two_points_att" => 2,
"flagrant_fouls" => 0, "steals" => 1, "fast_break_att" => 0,
"offensive_rating" => 85.0907292301888, "offensive_rebounds" => 4,
...}},
%{"active" => true, "first_name" => "Reggie",
"full_name" => "Reggie Bullock",
"id" => "42fa4c2c-6520-4d04-a753-cfe4a5c5e2e1", "jersey_number" => "25",
"last_name" => "Bullock", "played" => true, "position" => "F",
"primary_position" => "SF", "reference" => "203493", "starter" => true,
"statistics" => %{"efficiency" => 6, "triple_double" => false,
"defensive_rating" => 104.77107348445, "second_chance_att" => 3,
"points" => 10, "minus" => 49, "points_in_paint_att" => 4,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 5.14933887316374,
"points_off_turnovers" => 3, "two_points_att" => 4,
"flagrant_fouls" => 0, "steals" => 1, "fast_break_att" => 0, ...}},
%{"active" => true, "first_name" => "Henry",
"full_name" => "Henry Ellenson",
"id" => "eef64529-e381-43d1-a72b-8dcde914fee9", "jersey_number" => "8",
"last_name" => "Ellenson", "played" => true, "position" => "F",
"primary_position" => "PF", "reference" => "1627740",
"statistics" => %{"efficiency" => 2, "triple_double" => false,
"defensive_rating" => 110.995584750072, "second_chance_att" => 1,
"points" => 2, "minus" => 5, "points_in_paint_att" => 0, "blocks" => 0,
"double_double" => false, "defensive_rebounds_pct" => 0.0,
"points_off_turnovers" => 0, "two_points_att" => 1,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 0,
"offensive_rating" => 200.0, ...}}], "points" => 105,
"reference" => "1610612765",
"scoring" => [%{"number" => 1, "points" => 30, "sequence" => 1,
"type" => "quarter"},
%{"number" => 2, "points" => 29, "sequence" => 2, "type" => "quarter"},
%{"number" => 3, "points" => 26, "sequence" => 3, "type" => "quarter"},
%{"number" => 4, "points" => 20, "sequence" => 4, "type" => "quarter"}],
"statistics" => %{"efficiency" => 106,
"defensive_rating" => 99.5188101487314, "second_chance_att" => 17,
"points" => 105, "team_tech_fouls" => 0, "team_offensive_rebounds" => 8,
"points_in_paint_att" => 43, "blocks" => 3, "bench_points" => 35,
"points_off_turnovers" => 22, "player_tech_fouls" => 1,
"two_points_att" => 60, "flagrant_fouls" => 0, "steals" => 10,
"fast_break_att" => 10, "offensive_rating" => 109.05691732447,
"offensive_rebounds" => 14, "second_chance_pct" => 47.1,
"possessions" => 96.28, "true_shooting_att" => 95.28,
"biggest_lead" => 24, "two_points_pct" => 46.7, "points_in_paint" => 38,
"total_fouls" => 23, "assists_turnover_ratio" => 1.73, "ejections" => 0,
"field_goals_made" => 41,
"periods" => [%{"efficiency" => 28, "number" => 1,
"defensive_rating" => 128.737541528239, "second_chance_att" => 5,
"points" => 30, "team_tech_fouls" => 0, "team_offensive_rebounds" => 2,
"points_in_paint_att" => 12, "blocks" => 2, ...},
%{"efficiency" => 35, "number" => 2,
"defensive_rating" => 68.5557586837294, "second_chance_att" => 5,
"points" => 29, "team_tech_fouls" => 0, "team_offensive_rebounds" => 3,
"points_in_paint_att" => 14, ...},
%{"efficiency" => 29, "number" => 3,
"defensive_rating" => 77.9896013864818, "second_chance_att" => 2,
"points" => 26, "team_tech_fouls" => 0, "team_offensive_rebounds" => 3,
...},
%{"efficiency" => 14, "number" => 4,
"defensive_rating" => 120.535714285714, "second_chance_att" => 5,
"points" => 20, "team_tech_fouls" => 0, "team_offensive_rebounds" => 0,
...}], "offensive_fouls" => 1, "free_throws_pct" => 83.3,
"offensive_points_per_possession" => 1.09, "total_rebounds" => 57,
"points_in_paint_made" => 19, "second_chance_pts" => 18,
"true_shooting_pct" => 55.1, "free_throws_made" => 10,
"three_points_pct" => 43.3, "rebounds" => 46, ...}}, "clock" => "00:00",
"coverage" => "full", "duration" => "2:06", "entry_mode" => "WEBSOCKET",
"home" => %{"alias" => "ATL", "bonus" => true,
"coaches" => [%{"first_name" => "Ben", "full_name" => "Ben Sullivan",
"last_name" => "Sullivan", "position" => "Assistant Coach",
"reference" => "204224"},
%{"first_name" => "Scottie", "full_name" => "Scottie Parker",
"last_name" => "Parker", "position" => "Trainer",
"reference" => "1628764"},
%{"first_name" => "Pat", "full_name" => "Pat St. Andrews",
"last_name" => "St. Andrews", "position" => "Assistant Coach",
"reference" => "1628784"},
%{"first_name" => "Darvin", "full_name" => "Darvin Ham",
"last_name" => "Ham", "position" => "Assistant Coach",
"reference" => "203005"},
%{"first_name" => "Mike", "full_name" => "Mike Budenholzer",
"id" => "6c9c23f1-d87d-4aca-8414-3d86b0b3993e",
"last_name" => "Budenholzer", "position" => "Head Coach",
"reference" => "1371"},
%{"first_name" => "Chris", "full_name" => "Chris Jent",
"last_name" => "Jent", "position" => "Assistant Coach",
"reference" => "2607"},
%{"first_name" => "Wally", "full_name" => "Wally Blase",
"last_name" => "Blase", "position" => "Trainer", "reference" => "2150"},
%{"first_name" => "Taylor", "full_name" => "Taylor Jenkins",
"last_name" => "Jenkins", "position" => "Assistant Coach",
"reference" => "203624"},
%{"first_name" => "Charles", "full_name" => "Charles Lee",
"last_name" => "Lee", "position" => "Assistant Coach",
"reference" => "204225"}],
"id" => "583ecb8f-fb46-11e1-82cb-f4ce4684ea4c", "market" => "Atlanta",
"name" => "Hawks",
"players" => [%{"first_name" => "Mike", "full_name" => "Mike Muscala",
"id" => "7c636961-816a-4b44-8991-671df9d91d9c", "jersey_number" => "31",
"last_name" => "Muscala", "position" => "F-C",
"primary_position" => "PF", "reference" => "203488",
"statistics" => %{"efficiency" => 0, "triple_double" => false,
"second_chance_att" => 0, "points" => 0, "minus" => 0,
"points_in_paint_att" => 0, "blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 0, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 0.0,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0,
"rebounds_pct" => 0.0, "field_goals_made" => 0,
"periods" => [%{"efficiency" => 0, "number" => 1, ...},
%{"efficiency" => 0, ...}, %{...}, ...], "offensive_fouls" => 0,
"free_throws_pct" => 0.0, "points_in_paint_made" => 0, ...}},
%{"active" => true, "first_name" => "Kent", "full_name" => "Kent Bazemore",
"id" => "2c157857-fffd-4eb5-8e2a-b28ebea8da77", "jersey_number" => "24",
"last_name" => "Bazemore", "played" => true, "position" => "G",
"primary_position" => "SG", "reference" => "203145", "starter" => true,
"statistics" => %{"efficiency" => 8, "triple_double" => false,
"defensive_rating" => 106.069502377609, "second_chance_att" => 1,
"points" => 8, "minus" => 50, "points_in_paint_att" => 3,
"blocks" => 3, "double_double" => false,
"defensive_rebounds_pct" => 20.1416207710464,
"points_off_turnovers" => 0, "two_points_att" => 4,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 0,
"offensive_rating" => 82.2342730948014, "offensive_rebounds" => 1,
"second_chance_pct" => 0.0, "true_shooting_att" => 10.88,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 2.0, "steals_pct" => 0.0, ...}},
%{"active" => true, "first_name" => "Luke", "full_name" => "Luke Babbitt",
"id" => "d8298a51-2639-422a-869b-61c6fe27afd1", "jersey_number" => "8",
"last_name" => "Babbitt", "played" => true, "position" => "F",
"primary_position" => "SF", "reference" => "202337",
"statistics" => %{"efficiency" => 10, "triple_double" => false,
"defensive_rating" => 112.231151758584, "second_chance_att" => 0,
"points" => 7, "minus" => 41, "points_in_paint_att" => 0,
"blocks" => 0, "double_double" => false,
"defensive_rebounds_pct" => 20.0888186193587,
"points_off_turnovers" => 0, "two_points_att" => 1,
"flagrant_fouls" => 0, "steals" => 0, "fast_break_att" => 0,
"offensive_rating" => 135.261953010297, "offensive_rebounds" => 0,
"second_chance_pct" => 0.0, "true_shooting_att" => 5.76,
"two_points_pct" => 0.0, "points_in_paint" => 0,
"assists_turnover_ratio" => 0, "steals_pct" => 0.0, ...}},
%{"active" => true, "first_name" => "DeAndre'",
"full_name" => "DeAndre' Bembry",
"id" => "db42a3d8-e493-4f0e-aa9f-149397877fea", "jersey_number" => "95",
"last_name" => "Bembry", "played" => true, "position" => "F-G",
"primary_position" => "SF", "reference" => "1627761",
"statistics" => %{"efficiency" => -5, "triple_double" => false,
"defensive_rating" => 119.305763024204, "second_chance_att" => 0,
"points" => 0, "minus" => 40, "points_in_paint_att" => 2,
"blocks" => 1, "double_double" => false,
"defensive_rebounds_pct" => 0.0, "points_off_turnovers" => 0,
"two_points_att" => 2, "flagrant_fouls" => 0, "steals" => 0,
"fast_break_att" => 0, "offensive_rating" => 15.8695381624177,
"offensive_rebounds" => 0, "second_chance_pct" => 0.0,
"true_shooting_att" => 3.0, "two_points_pct" => 0.0,
"points_in_paint" => 0, "assists_turnover_ratio" => 0.5, ...}},
Hopefully showing the map might help you understand what I'm trying to accomplish.

players is a list.
Map.take(game, ["away", "home"]) should definitely work, but Kernel.get_in/2 and using Access behaviour is way more idiomatic.
Everything you need is to intersperse Kernel.get_in/2 with Enum.find/2 for lookup:
game
|> get_in(~w|away players|)
|> Enum.find(fn e -> CONDITION end)
|> get_in(~w|statistics points|)
If you were to post MCVE instead of non-valid object, I could be able to test this.

Function to iterate through a list and sum columns based on conditional statement

I have a list of dataframes that look like (sample dput attached below):
[[1]]
SPY.HIGH SPY.ADX SPY.MA SPY.CLOSE
2014-08-11 -1 1 1 5
2014-08-12 -1 1 1 10
[[2]]]
MSCI.HIGH MSCI.ADX MSCI.MA MSCI.CLOSE
2014-08-29 -1 -1 1 3
2014-09-01 -1 1 1 1
2014-09-02 0 -1 0 2
I'm trying to create a function that would only sum up the last columns of the above data sample based on the conditions that the first column is nonzero, second column is positive and third column is nonnegative. I made the following attempt:
marketsum <- function(x) {
#Conditional columns
validrows <- FlaggingTrend[[x]][,1] != 0 | FlaggingTrend[[x]][,2] > 0 | FlaggingTrend[[x]][,3] != 0
# Only calculates the sum of fourth column for the rows if above conditions are met
sum(FlaggingTrend[[x]][validrows,4])
}
returnsum <- list()
# Use sapply to run function to work out sums
returnsum <- sapply(1:length(FlaggingTrend), function(x) marketsum(x))
However, I'm getting NA instead of summed values?
names close
1 EUR NA
2 JPY NA
3 GBP NA
4 CHF NA
5 AUD NA
6 CAD NA
7 NZD NA
I would appreciate help or guidance as to where I'm going wrong. Sample dput is attached below:
list(structure(list(EUR.CLOSE = c(-1, -1, -1, 0, 1, 0, 0, -1,
0, 1), EUR.CLOSE.1 = c(1, -1, -1, 1, 1, 1, 1, -1, -1, -1), EUR.50D = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), EUR.CLOSE.2 = c(-0.0011268664916733,
-0.00423709498833686, -0.00188893142678216, 0.00217196364717242,
0.00686254162079234, -0.00544858088184653, -0.000188412624203348,
-0.00737591996472312, 0.00208590196044455, 0.00227057808051545
)), .Names = c("EUR.CLOSE", "EUR.CLOSE.1", "EUR.50D", "EUR.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14", "2017-02-15",
"2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21", "2017-02-22",
"2017-02-23"), class = "data.frame"), structure(list(JPY.CLOSE = c(0,
0, 1, 0, -1, -1, 0, 1, 0, -1), JPY.CLOSE.1 = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), JPY.50D = c(1, 1, 1, 1, 1, 1, 1, 1,
1, 1), JPY.CLOSE.2 = c(-0.000264935754629825, 0.00458231327013969,
0.00456141141766331, -0.000875580127735809, -0.00809151292488242,
-0.00353857410990255, 0.00230149698827908, 0.00511510066677001,
-0.00326005839636956, -0.00619690368354142)), .Names = c("JPY.CLOSE",
"JPY.CLOSE.1", "JPY.50D", "JPY.CLOSE.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(GBP.CLOSE = c(0, 1, 0, 0, 1, -1, 0, 0, 0,
1), GBP.CLOSE.1 = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), GBP.50D = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), GBP.CLOSE.2 = c(-0.00048023051987453,
0.00279809911944895, -0.00464112219813048, -0.000561594944360089,
0.0022444899202175, -0.00618451029481418, 0.00410050825810596,
0.000802053299332334, -0.00184568523285542, 0.00847801606899046
)), .Names = c("GBP.CLOSE", "GBP.CLOSE.1", "GBP.50D", "GBP.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
CHF.OPEN = c(1, 0, 0, 0, -1, 0, 0, 1, 0, -1), CHF.OPEN.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, 1, -1), CHF50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), CHF.OPEN.2 = c(0.000698567964139939,
0.00328669186857626, 0.00049704260678339, -0.000695928844511353,
-0.00838914337795957, 0.00550083899465574, 0.000199461454735274,
0.00685716972613716, 0.000594059423411153, -0.00396707849439904
)), .Names = c("CHF.OPEN", "CHF.OPEN.1", "CHF50D", "CHF.OPEN.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
AUD.CLOSE = c(1, 0, 0, 1, 0, -1, 0, 0, 1, 0), AUD.CLOSE.1 = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1), AUD.50D = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), AUD.CLOSE.2 = c(0.00640566933128534,
-0.00444038864633145, 0.00300594880983807, 0.0061146355869709,
-0.00207738324513479, -0.00390676366154397, 0.00312663099943206,
-0.00169237819473061, 0.00364156989756792, 0.00155662244429539
)), .Names = c("AUD.CLOSE", "AUD.CLOSE.1", "AUD.50D",
"AUD.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CAD.CLOSE = c(-1, 0, 0, 0, 0, 1, 0, 1, 0,
-1), CAD.CLOSE.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), CAD.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CAD.CLOSE.2 = c(-0.00472778065310547,
-0.000917641725324381, 0.000382453058549392, 0.000305857167088586,
-0.000688310225637978, 0.00191080426541917, 0.000763300548471235,
0.00266697304419594, 0.00174871741959248, -0.00449199430572389
)), .Names = c("CAD.CLOSE", "CAD.CLOSE.1", "CAD.50D", "CAD.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
NZD.CLOSE = c(0, 0, 0, 1, 0, -1, 0, -1, 0, 1), NZD.CLOSE.1 = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1), NZD.50D = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), NZD.CLOSE.2 = c(0.00041733324664972,
-0.00208841008727045, -0.000836586774949688, 0.00750420419797471,
-0.00180142777185216, -0.00389105549296664, 0.00111327592906424,
-0.00404153570815258, 0.00390244397693174, 0.00568695616893883
)), .Names = c("NZD.CLOSE", "NZD.CLOSE.1", "NZD.50D",
"NZD.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(SEK.OPEN = c(1, 1, 0, 0, -1, 0, 1, 1, 0, 0
), SEK.OPEN.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, 1),
SEK.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), SEK.OPEN.2 = c(0.00163829609003363,
0.0023181988913219, -0.000716164076936199, -0.00145628918509555,
-0.00677152707834994, 0.00582941106111079, 0.00270059947077783,
0.00455540960162004, -0.000256248852460228, 0.00199255363165785
)), .Names = c("SEK.OPEN", "SEK.OPEN.1", "SEK.50D", "SEK.OPEN.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
NOK.CLOSE = c(1, 0, 0, -1, -1, 0, 0, 1, 0, 0), NOK.CLOSE.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), NOK.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), NOK.CLOSE.2 = c(0.00323283885094217,
0.00303175214315887, 0.000941075635438882, -0.00716968871997281,
-0.00617111408142934, 0.00665069589528811, -0.000467589464977269,
0.00246736261239189, 0.000837040274633605, -0.00324444329976892
)), .Names = c("NOK.CLOSE", "NOK.CLOSE.1", "NOK.50D",
"NOK.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CZK.CLOSE = c(1, 1, 1, 0, -1, 0, 0, 1, 0,
-1), CZK.CLOSE.1 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CZK.50D = c(1,
1, 1, -1, -1, 1, -1, 1, -1, -1), CZK.CLOSE.2 = c(0.00144601789180365,
0.00379617459269976, 0.00202579528819546, -0.00220231606416821,
-0.00688897736863447, 0.00560532297819627, 0.000184602212216056,
0.00710284457208665, -0.00197121312914339, -0.00224919172846905
)), .Names = c("CZK.CLOSE", "CZK.CLOSE.1", "CZK.50D", "CZK.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
HUF.LOW.1 = c(0, 1, 1, 0, -1, 0, 0, 1, 0, 0), HUF.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, 1, -1, 1), HUF.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), HUF.LOW.1.2 = c(0.0013470806658562,
0.00413351833762921, 0.000927691660614904, -0.00161542594720476,
-0.00908798735735505, 0.00843420139734707, -0.00110208028787984,
0.00632043873779775, -0.00133632598823841, 0.000719782039952932
)), .Names = c("HUF.LOW.1", "HUF.LOW.1.1", "HUF.50D",
"HUF.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(ILS.LOW.1 = c(0, 0, 0, -1, -1, -1, 0, 0, 0,
0), ILS.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), ILS.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ILS.LOW.1.2 = c(0.000933818987030266,
0.000959590648321962, -0.00159982969276018, -0.00296644925366696,
-0.00509821862018822, -0.00393531505179312, 0.00242770943578163,
-0.00285991992901691, -0.000567559913074556, 0.00091874516690349
)), .Names = c("ILS.LOW.1", "ILS.LOW.1.1", "ILS.50D", "ILS.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
PLN.LOW.1 = c(0, 1, 0, 0, -1, 1, 0, 0, 0, 0), PLN.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), PLN.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), PLN.LOW.1.2 = c(-0.00274633685326608,
0.00755279414139087, 0.000417931735706034, -0.000491702529882065,
-0.00490565626173578, 0.00929781633628868, -0.00365469691428677,
0.00186580959045224, -0.00137446945036213, -0.00149934278232444
)), .Names = c("PLN.LOW.1", "PLN.LOW.1.1", "PLN.50D",
"PLN.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(RUB.LOW.1 = c(-1, -1, -1, -1, 0, 0, 1, 0,
-1, 1), RUB.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), RUB.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), RUB.LOW.1.2 = c(-0.00446008580014645,
-0.0121748200414373, -0.00422818336649922, -0.0153488129381678,
0.0022241309795028, 0.00590173583792808, 0.014758577509606,
-0.00824954514944221, -0.00941636498473652, 0.0111898627811513
)), .Names = c("RUB.LOW.1", "RUB.LOW.1.1", "RUB.50D", "RUB.LOW.1.2"
), row.names = c("2017-02-09", "2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22"), class = "data.frame"), structure(list(
TRY.HIGH.1 = c(0, 0, -1, 0, 0, -1, -1, 0, -1, -1), TRY.HIGH.1.1 = c(1,
1, 1, 1, 1, -1, -1, -1, -1, -1), TRY.50D = c(-1, -1,
-1, -1, -1, -1, -1, -1, -1, -1), TRY.HIGH.1.2 = c(0.00417356089701015,
-0.00686579177053992, -0.00568012668941198, 0.00229778255761226,
0.00204713949728741, -0.0100024127023963, -0.00176420367173535,
-0.00113183078791668, -0.011249649909296, -0.00307744199905646
)), .Names = c("TRY.HIGH.1", "TRY.HIGH.1.1", "TRY.50D",
"TRY.HIGH.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(ZAR.LOW.1 = c(-1, 0, -1, -1, 0, 0, 0, 0, -1,
-1), ZAR.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), ZAR.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ZAR.LOW.1.2 = c(-0.0050112296343281,
-0.000119978703923884, -0.0173679300039469, -0.0145343910929765,
0.00897924634581271, 0.000421926368602055, 0.000521408427958114,
0.00716476609655059, -0.0126608692527035, -0.00785440574245699
)), .Names = c("ZAR.LOW.1", "ZAR.LOW.1.1", "ZAR.50D", "ZAR.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
BRL.LOW.1 = c(0, 0, -1, -1, 0, 1, 0, 0, -1, -1), BRL.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), BRL.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), BRL.LOW.1.2 = c(-0.00371652356533581,
-0.00160621962638552, -0.00832934597660584, -0.00902065874268554,
0.010543197464703, 0.00316721872930192, -0.00362049854021018,
0.00278119317749237, -0.0100617531753731, -0.0006199931673041
)), .Names = c("BRL.LOW.1", "BRL.LOW.1.1", "BRL.50D",
"BRL.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CLP.LOW.1 = c(-1, 0, 0, 0, 0, 1, 0, 0, 0,
0), CLP.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), CLP.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CLP.LOW.1.2 = c(-0.00993671434599985,
0.00456853190734918, -0.00172828592427443, -0.00404432121904819,
-0.00048516719656444, 0.00933326604643625, -0.00561445365426927,
0.00353409520664982, -0.00208469536279665, -0.00105956972687871
)), .Names = c("CLP.LOW.1", "CLP.LOW.1.1", "CLP.50D", "CLP.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
COP.CLOSE = c(-1, 1, 0, 0, 0, 1, 0, 1, 0, -1), COP.CLOSE.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), COP.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), COP.CLOSE.2 = c(-0.00197341552292052,
0.00662211307234362, 0.000580874632634121, -0.00202234392720335,
0.00204668459925017, 0.00543743450560008, -0.00266994190200176,
0.00607751193077277, -0.00217715796204931, -0.00905605289811184
)), .Names = c("COP.CLOSE", "COP.CLOSE.1", "COP.50D",
"COP.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(MXN.LOW.1 = c(0, 0, -1, 0, 0, 1, -1, -1, -1,
-1), MXN.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), MXN.50D = c(-1, -1, 1, 1, 1, 1, 1, 1, 1, 1), MXN.LOW.1.2 = c(-0.000211320384603475,
-0.00314066280938086, -0.00107540683430729, 0.000705557901050646,
0.00518510570127306, 0.00240140867288519, -0.00281365838425973,
-0.0177295559643031, -0.00536567713104841, -0.0121193389083811
)), .Names = c("MXN.LOW.1", "MXN.LOW.1.1", "MXN.50D", "MXN.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
PEN.HIGH.1 = c(-1, 0, -1, -1, 0, 1, -1, 0, -1, 0), PEN.HIGH.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), PEN.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), PEN.HIGH.1.2 = c(-0.00429316820091041,
0.00214888801033619, -0.000859001157250239, -0.0038438522704316,
0.00101621330746293, 0.00460618041489735, -0.00522194398115183,
0, -0.000462071629322658, -0.000154071335332739)), .Names = c("PEN.HIGH.1",
"PEN.HIGH.1.1", "PEN.50D", "PEN.HIGH.1.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CNY.CLOSE = c(1, 0, -1, 0, -1, 1, 1, 1, 0,
-1), CNY.CLOSE.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), CNY.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CNY.CLOSE.2 = c(0.00135295379134326,
0.000247116371263401, -0.00184758230288495, 0.000524070878021865,
-0.0026376972616271, 0.001968002384513, 0.00174608993071379,
0.000799273430379666, -0.00090104498241117, -0.00170257391661588
)), .Names = c("CNY.CLOSE", "CNY.CLOSE.1", "CNY.50D", "CNY.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
IDR.LOW.1 = c(-1, 0, 0, 0, 0, 0, 1, 1, 0, 0), IDR.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, 1, -1, -1), IDR.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), IDR.LOW.1.2 = c(-0.00225360672301989,
0.00142787383820853, 0.000750694427567922, 0.000375135991193432,
-0.000825485019296579, 0.000975500021079156, 0.00157380030235466,
0.00142178345498323, -0.000448765901323256, -0.00119769458137853
)), .Names = c("IDR.LOW.1", "IDR.LOW.1.1", "IDR.50D",
"IDR.LOW.1.2"), row.names = c("2017-02-09", "2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(INR.LOW.1 = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1
), INR.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), INR.50D = c(-1, -1, -1, -1, -1, -1, 0, -1, 0, -1), INR.LOW.1.2 = c(-0.000466530150061928,
-0.000531550320954643, -0.000443420116883253, -0.000392023361358795,
-0.000386278564721287, -0.000386427833512393, -0.000244913256195467,
-0.000181510566847898, -0.000126929400856568, -0.000132850348706803
)), .Names = c("INR.LOW.1", "INR.LOW.1.1", "INR.50D", "INR.LOW.1.2"
), row.names = c("2017-02-08", "2017-02-09", "2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-22"), class = "data.frame"), structure(list(
KRW.LOW.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1),
KRW.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, 1, -1, -1
), KRW.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), KRW.LOW.1.2 = c(0.000517860571988438,
0.000112542907102053, 0.00134952787013343, 0, -0.000337211266051574,
0.00112359562382647, 0.000449084996881899, 0.000785413785115541,
-0.00085276367906495, -0.000718681250895026)), .Names = c("KRW.LOW.1",
"KRW.LOW.1.1", "KRW.50D", "KRW.LOW.1.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"))

Here is a way to address your problem, d being the content of your dput:
vapply(d, function(x) {
valid_rows <- x[, 1] != 0 | x[, 2] > 0 | x[, 3] != 0
sum(x[valid_rows, 4])
}, numeric(1))
A few things to note:
first you say " first column is nonzero, second column is positive and third column is nonnegative" but you use | in your conditions. | means OR, if you want AND you would need to use &. In that case though, some of your examples don't match any rows, so you would get a sum of 0. If it's not what you want you'll need to modify the code to return NA when there is no rows that match your conditions, for instance:
vapply(d, function(x) {
valid_rows <- x[, 1] != 0 & x[, 2] > 0 & x[, 3] != 0
if (sum(valid_rows) > 0)
sum(x[valid_rows, 4])
else
NA_real_
}, numeric(1))
second, for your last condition you say "third column is nonnegative", but you write FlaggingTrend[[x]][,3] != 0 which tests for values different from 0, not positive values.
third, it's best to not use global variables within your functions. It might lead to a lot of confusion down the road.
here, I use vapply to enforce the data type of the returned objects. It's safer than sapply whose behavior can change depending on the data type of the returned objects.

How do I draw line after receiving data - Route from GPS Trace

I just started using Here Maps. Before I used Google Direction, I want to try use 'Here Maps' API. This is example JSON result. After I got this result, How do I implement this into Polyline or Direction (MAP Here)? Thanks
{
RouteLinks: [
{
linkId: 25664478,
functionalClass: 5,
shape: "51.1017723 0.3934907 51.1018066 0.3933491 51.1018295 0.39326",
linkLength: 15.575699313408467
},
{
linkId: 25664473,
functionalClass: 4,
shape: "51.1018295 0.39326 51.1022491 0.39348",
linkLength: 44.17562556306323
},
{
linkId: 25664459,
functionalClass: 4,
shape: "51.1022491 0.39348 51.1022987 0.39351",
linkLength: 5.305684979980019
},
{
linkId: 781742854,
functionalClass: 4,
shape: "51.1022987 0.39351 51.1025505 0.39365",
linkLength: 26.670487136749067
},
{
linkId: 781742855,
functionalClass: 4,
shape: "51.1025505 0.39365 51.1027794 0.39378",
linkLength: 24.302012297623005
},
{
linkId: 25664450,
functionalClass: 4,
shape: "51.1027794 0.39378 51.1030807 0.39403",
linkLength: 33.974229462422905
},
{
linkId: 25664444,
functionalClass: 4,
shape: "51.1030807 0.39403 51.103241 0.39413",
linkLength: 17.215963662407898
},
{
linkId: 25664440,
functionalClass: 4,
shape: "51.103241 0.39413 51.1033783 0.39421 51.1035385 0.39433 51.1036797 0.39445",
linkLength: 48.32839625333388
},
{
linkId: 25664427,
functionalClass: 4,
shape: "51.1036797 0.39445 51.1038017 0.39454",
linkLength: 13.445306290244636
},
{
linkId: 860272608,
functionalClass: 4,
shape: "51.1038017 0.39454 51.1039391 0.39465",
linkLength: 15.378381014646559
},
{
linkId: 860272609,
functionalClass: 4,
shape: "51.1039391 0.39465 51.1041908 0.39484",
linkLength: 27.85427285471891
},
{
linkId: 781742870,
functionalClass: 4,
shape: "51.1041908 0.39484 51.1043282 0.39494 51.1045609 0.39506",
linkLength: 39.56626207722863
},
{
linkId: 781742871,
functionalClass: 4,
shape: "51.1045609 0.39506 51.1047287 0.39515 51.1050262 0.3953021",
linkLength: 48.951382959921716
}
],
TracePoints: [
{
confidenceValue: 1, linkIdMatched: 25664478, matchDistance: 1.46,
routeLinkSeqNrMatched: 0, lat: 51.10177, lon: 0.39349,
elevation: 0, speedMps: 0, headingDegreeNorthClockwise: 10000,
latMatched: 51.10178065190155, lonMatched: 0.3934977183445852,
timestamp: 0, headingMatched: 114.46568884011239,
minError: 1.3027890756593314
},
{
confidenceValue: 1, linkIdMatched: 25664478, matchDistance: 1.57,
routeLinkSeqNrMatched: 0, lat: 51.10181, lon: 0.39335,
elevation: 0, speedMps: 0, headingDegreeNorthClockwise: 10000,
latMatched: 51.10182, lonMatched: 0.39336,
timestamp: 0, headingMatched: -65.53429247174023,
minError: 1000000
},
{
confidenceValue: 1, linkIdMatched: 781742854, matchDistance: 1,
routeLinkSeqNrMatched: 4, lat: 51.10255, lon: 0.39366,
elevation: 0, speedMps: 0, headingDegreeNorthClockwise: 10000,
latMatched: 51.102547928304084, lonMatched: 0.3936687569824506,
timestamp: 0, headingMatched: 20.644254301899522,
minError: 0.6541474931313044
},
{
confidenceValue: 1, linkIdMatched: 860272608, matchDistance: 4.59,
routeLinkSeqNrMatched: 10, lat: 51.10398, lon: 0.39466,
elevation: 0, speedMps: 0, headingDegreeNorthClockwise: 10000,
latMatched: 51.10394, lonMatched: 0.39465,
timestamp: 0, headingMatched: 25.217234923243595,
minError: 1.2405405512432781
},
{
confidenceValue: 1, linkIdMatched: 1022687693, matchDistance: 1.33,
routeLinkSeqNrMatched: 14, lat: 51.10501, lon: 0.39533,
elevation: 0, speedMps: 0, headingDegreeNorthClockwise: 10000,
latMatched: 51.105012239590245, lonMatched: 0.39531827230152644,
timestamp: 0, headingMatched: 16.91643828307876,
minError: 0.8568378930601925
}
],
Warnings: [
{
"tracePointSeqNum": -1,
"routeLinkSeqNum": 3,
"category": 3,
"text": "Entering link 781742854 into forbidden driving direction"
}
],
MapVersion: "2013Q4" }

*linkId,shape is like that trip points which is given by Heremap api step1.
You just draw route by polyline function.
addPolylineToMap(map,linkId);
function addPolylineToMap(map,linkId) {
for (j = 0; j < (shape.length - 1); j = j + 2) {
var strip = new H.geo.Strip();
strip.pushPoint({lat: shape[j],lng: shape[j+1]});
}
}

Issue with datetime values and printing a spline plot between the data points

Anyone able to help with the following problem:
Trying to draw a chart with four data series, two of which are scatter and one is spline. Purpose of the spline is just to draw a line between specific spots on the chart, not joining all of them together. The following is my code so far:
$(function () {
var chart;
$(document).ready(function() {
chart = new Highcharts.Chart({
chart: {
renderTo: 'container',
type: 'scatter',
zoomType: 'xy'
},
title: {
text: ''
},
xAxis: {
type: 'datetime',
ordinal: false,
labels: {
formatter: function() {
return Highcharts.dateFormat('%H', this.value);
}
}
},
yAxis: {
categories: ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'],
gridLineWidth: 0,
step: 1,
title: '',
labels: {
style: {
color: '#6D869F',
fontSize: '9px',
}
},
},
tooltip: {
formatter: function() {
return ''+
this.x +' cm, '+ this.y +' kg';
}
},
legend: {
layout: 'vertical',
align: 'left',
verticalAlign: 'top',
x: 100,
y: 70,
floating: true,
backgroundColor: '#FFFFFF',
borderWidth: 1
},
plotOptions: {
scatter: {
marker: {
radius: 5,
states: {
hover: {
enabled: true,
lineColor: 'rgb(100,100,100)'
}
}
},
states: {
hover: {
marker: {
enabled: false
}
}
}
}
},
series: [{
name: 'sleep time',
marker: {
symbol: 'circle',
},
color: '#81c65b',
data: [[Date.UTC(2012, 1, 1, 22, 15), 0],
[Date.UTC(2012, 1, 1, 20, 30), 3],
[Date.UTC(2012, 1, 1, 21, 45), 5],
[Date.UTC(2012, 1, 1, 22, 00), 6]]
},
{
name: 'wakeup time',
marker: {
symbol: 'circle',
fillColor: '#76a4fb',
},
data: [[Date.UTC(2012, 1, 2, 08, 15), 0],
[Date.UTC(2012, 1, 2, 07, 10), 1],
[Date.UTC(2012, 1, 2, 09, 20), 2],
[Date.UTC(2012, 1, 2, 07, 40), 3],
[Date.UTC(2012, 1, 2, 07, 30), 4],
[Date.UTC(2012, 1, 2, 08, 20), 5],
[Date.UTC(2012, 1, 2, 09, 30), 6]],
},
{
name: 'sleep time over average',
color: 'rgba(119, 152, 191, .5)',
marker: {
symbol: 'square',
fillColor: '#000',
},
data: [[Date.UTC(2012, 1, 1, 20, 15), 1],
[Date.UTC(2012, 1, 1, 23, 40), 2],
[Date.UTC(2012, 1, 1, 21, 20), 4]]
},
{
name: '',
legend: {
enabled: false,
},
color: '#d62a9c',
type: 'spline',
marker: {
enabled: false,
},
data: [[Date.UTC(2012, 1, 1, 22, 15), 0],
[Date.UTC(2012, 1, 2, 08, 15), 0],
[Date.UTC(2012, 1, 1, 20, 15), 1],
[Date.UTC(2012, 1, 2, 07, 10), 1],
[Date.UTC(2012, 1, 1, 23, 40), 2],
[Date.UTC(2012, 1, 2, 09, 20), 2],
[Date.UTC(2012, 1, 1, 20, 30), 3],
[Date.UTC(2012, 1, 2, 07, 40), 3],
[Date.UTC(2012, 1, 1, 21, 20), 4],
[Date.UTC(2012, 1, 2, 07, 30), 4],
[Date.UTC(2012, 1, 1, 21, 45), 5],
[Date.UTC(2012, 1, 2, 08, 20), 5],
[Date.UTC(2012, 1, 1, 22, 00), 6],
[Date.UTC(2012, 1, 2, 09, 30), 6]]
}]
});
});
});
My problem now is, in the spline series, if I add a null between elements to prevent plotting the line between two points, the whole plot goes mayhem. The idea is to draw lines only so that points which are vertically on the same line get joined, eg. in this case "sleep time" and "wakeup time". For example,
data: [
[Date.UTC(2012, 1, 1, 22, 15), 0],
[Date.UTC(2012, 1, 2, 08, 15), 0], null,
[Date.UTC(2012, 1, 1, 20, 15), 1],
[Date.UTC(2012, 1, 2, 07, 10), 1], null,
[Date.UTC(2012, 1, 1, 23, 40), 2],
...
You may try out the code at this jsfiddle.

Try the following.
data: [
[Date.UTC(2012, 1, 1, 22, 15), 0],
[Date.UTC(2012, 1, 2, 08, 15), 0],
[Date.UTC(2012, 1, 2, 08, 15), null],
[Date.UTC(2012, 1, 1, 20, 15), 1],
[Date.UTC(2012, 1, 2, 07, 10), 1],
[Date.UTC(2012, 1, 2, 08, 15), null],
[Date.UTC(2012, 1, 1, 23, 40), 2],
[Date.UTC(2012, 1, 2, 09, 20), 2],
[Date.UTC(2012, 1, 2, 08, 15), null],
...
]
As you can see you have to pass an array which the first value have to be any date.
Demo

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