Build an histogram in R Studio - Beginner

General
1

Dear all,

I am quite new to R Studio and I would like to build an histogram with the following table (see picture)

Table explanation :

  • Column A : my cities
  • Line 1 : pollution values (between 8.5 and 9.1)

As an example, for Bresson city we found one station showing 8,5 as a value, height stations showing 8,6 and 2 stations giving 8,7.

Now I would like to show the pollution distribution as an histogram for each city (for example for Bresson) ?

Does anyone know how to do this ?

Many thanks for your help,

Marie-Laure

table
table2161×477 110 KB

2

Hi @MLaure19, have you imported the data into RStudio already, or is that something you need help with, too?

3

Hi @dromano, yes I have imported the full set of data into my RStudio
Thanks a lot!

4

In that case, supposing the name of your imported table is my_table, could you run the command dput(head(my_table, 50)) and post the output from the console here, like this?

```
<--- paste output here, with both ```s
```
5 
structure(list(X = structure(c(1L, 5L, 2L, 4L, 3L), .Label = c("Bresson", 
"Claix  ", "Corenc", "Coteau", "Plaine  "), class = "factor"), 
    X8.5 = c(1L, 0L, 0L, 1L, 0L), X8.6 = c(8L, 0L, 0L, 2L, 1L
    ), X8.7 = c(2L, 1L, 0L, 1L, 2L), X8.8 = c(0L, 2L, 0L, 0L, 
    1L), X8.9 = c(0L, 1L, 1L, 0L, 0L), X9 = c(0L, 0L, 3L, 0L, 
    0L), X9.1 = c(0L, 0L, 1L, 0L, 0L)), row.names = c(NA, 5L), class = "data.frame")
6

Thank you, @MLaure19! This is the first step in building what's called a 'reprex', which is ideal way to post questions so folks can help you more easily. (See FAQ: How to do a minimal reproducible example ( reprex ) for beginners for helpful details.) I'll add the assignment to my_table to make it easier to copy:

my_table <-
structure(list(X = structure(c(1L, 5L, 2L, 4L, 3L), .Label = c("Bresson", 
"Claix  ", "Corenc", "Coteau", "Plaine  "), class = "factor"), 
    X8.5 = c(1L, 0L, 0L, 1L, 0L), X8.6 = c(8L, 0L, 0L, 2L, 1L
    ), X8.7 = c(2L, 1L, 0L, 1L, 2L), X8.8 = c(0L, 2L, 0L, 0L, 
    1L), X8.9 = c(0L, 1L, 1L, 0L, 0L), X9 = c(0L, 0L, 3L, 0L, 
    0L), X9.1 = c(0L, 0L, 1L, 0L, 0L)), row.names = c(NA, 5L), class = "data.frame")

Is this all the data you're working with? It seems quite small to require a histogram -- could you say what you need it for? That might help folks understand your context better.

7

I see, I will improve next time !!

In reality my csv file is much bigger (177obs. of 765 pollution variables).
But I tried to make things easier for you. And I did not find any way to post it here.

I already spent many hours trying to find the same kind of example but I did not find anything.
There might be a specific english name for this kind of frequency tables but I don't find it :frowning:

8

In fact I got this table from a GIS tool. I extracted pixel values from a pollution map and I want to modelize pollution values over each city

9

I see, and from the table you posted, it looks like you may prefer another way of importing the data -- what command did you use to import the csv file?

10

I have used the "Import dataset command". Don't know if this helps

11

Have you installed the tidyverse package?

12

Yes I have tidyverse installed

13

In that case, you could try running this:

library(tidyverse)
my_table <- read_csv('my_file.csv')
my_table

which should look a little cleaner, and then you could run

dput(my_table %>% select(1:20) %>% head(20))

and paste the output here as you did before, so the data is a little more realistic -- could you do that?

14

Hi dromano,

When I enter :

dput(my_table %>% select(1:20) %>% head(20))

I am getting this error message :

Error in inds_combine(.vars, ind_list) : Position must be between 0 and n

15

That likely means my_table has fewer than the 20 columns select() is asking for: Didn't you say your table had 765 columns?

16

Sorry, I was using the small table. Now with my original csv file, this is wat I get :

structure(list(NOM_IRIS = structure(c(18L, 127L, 23L, 89L, 28L, 
103L, 87L, 41L, 26L, 175L, 42L, 43L, 40L, 171L, 102L, 101L, 159L, 
63L, 99L, 98L), .Label = c("Abbaye", "Abry", "Aigle", "AlliŽs-Clos d'Or", 
"Alpins", "Ambroise Croizat", "Arc-En-Ciel", "Aristide Briand", 
"Arlequin", "Ayguinards", "Bajati\217re Est", "Bajati\217re Ouest", 
"Baladins", "Barnave-Saint-Robert", "Bastille", "Beauvert", "Berriat-Amp\217re", 
"Bresson", "BŽali\217res", "Capuche", "Champaviotte", "Championnet", 
"Claix Centre Bourg", "Clemenceau", "Clinique Mutualiste", "Comboire", 
"Constantine", "Corenc", "Cours Berriat", "Croix Rouge", "CrŽqui-Victor Hugo", 
"Curie-Rolland", "Diables Bleus", "Diderot", "Domaine Universitaire", 
"Drac-Ampere", "Drac-Vercors", "Eaux Claires-Champs Elysees", 
"Eaux Claires-PainlevŽ", "Echirolles Centre", "Echirolles Ouest-Nord", 
"Echirolles Ouest-Sud", "Echirolles Za du Centre", "Engenieres-Rolandiere", 
"Esplanade", "Europole", "Eybens Nord", "Eybens Sud Est", "Eybens Sud Ouest", 
"FerriŽ-Stalingrad", "Fiancey-Brieux", "Foch Est", "Foch Ouest", 
"Fontaine Mairie", "Fontaine Zone Industrielle", "Fontanil-Cornillon", 
"Frange Verte-Commanderie", "Gabriel PŽri", "Gare", "Gi\217res Nord", 
"Gi\217res Sud", "Glairons", "Grand-Place", "Grand Place Alpexpo", 
"Grand Pre-Buclos-Eyminees", "Grenette", "Gringalet", "Gustave Rivet", 
"GŽnissieu", "Haut de la Commune", "Haut Meylan", "Hebert-Mutualite", 
"Helbronner-Geants", "Hoche", "Houille Blanche", "Ile Verte-MarŽchal Randon", 
"Ile Verte-Saint Roch", "Jaur\217s-Vallier", "Jean Jaures", "Jean MacŽ", 
"Jeanne d'Arc", "Jouhaux", "La Bruyere", "La Falaise", "La Fauconni\217re", 
"La Monta-Visancourt", "Le Bourg-Les Chenevi\217res-Chantavot-Zone Indu", 
"Le Bourg-Les C\231tes", "Le Coteau", "Le Gua", "Le Pont-de-Claix Zone d'ActivitŽs des ëles", 
"Les Alloves", "Les Alpes", "Les Buissonnees", "Les ëles de Mars-Les Olympiades", 
"Les ëles Nord", "Les ëles Sud", "Les Essarts-Nord", "Les Essarts-Sud", 
"Les Floralies", "Les Granges-Nord", "Les Granges-Sud", "Les Mortes l'Oratoire Les Contamines", 
"Les Trembles", "Les Vouillands", "Lustucru", "Mairie-Langevin", 
"Malherbe", "Maquis du Gresivaudan-Nord", "Maquis du Gresivaudan-Sud", 
"Maupertuis-St Mury-Charlaix", "Meylan Zone d'ActivitŽs 1", "Meylan Zone d'ActivitŽs 2", 
"Meylan Zone d'ActivitŽs 3", "Mistral", "Moutonnees", "Murianette", 
"Mžrier", "Neyrpic", "Notre Dame", "Noyarey", "Pacalaire", "Paul-Eluard", 
"Paul Bert", "Paul Cocat", "Peretto", "Plaine du Pont Rouge", 
"Plaine Fleurie", "Plateforme Chimique", "Poisat", "Polygone", 
"Pont-de-Claix Bourg", "Portail Rouge", "Poterne", "Poya-Plans", 
"Predieu", "PrŽfecture", "Renaudie", "Reviree", "Reynies", "Rochepleine", 
"Rondeau-Liberation", "Saint-Andre", "Saint-Bruno", "Saint-ƒgr\217ve Zone Industrielle", 
"Saint-Laurent-Lavalette", "Saint-Martin-d'H\217res La Plaine", 
"Saint-Martin-d'H\217res Le Village", "Saint-Martin-le-Vinoux Nord Est", 
"Saint-Martin-le-Vinoux Sud Ouest et ZI", "Saint-Paul-de-Varces", 
"Sassenage La Plaine", "Semard", "Seyssinet-Pariset Le Village", 
"Seyssins La Plaine", "Seyssins Le Centre", "Seyssins Le Village", 
"Sidi-Brahim", "Surieux", "Taillees", "Teisseire", "Trois Cours", 
"Vallier", "Valmy", "Varces Centre", "Varces PŽriphŽrie", "Veurey-Voroize", 
"Vif Centre Ville", "Vif PŽriphŽrie", "Vigny-Musset", "Village 2", 
"Village Olympique Nord", "Village Olympique Sud", "Villancourt", 
"Viscose-Luire", "Waldeck-Rousseau", "Zone SpŽcifique l'ële d'Amour"
), class = "factor"), HISTO_8.5 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_8.6 = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_8.7 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_8.8 = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_8.9 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_9 = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_9.1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_9.2 = c(0L, 
0L, 0L, 651L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_9.3 = c(0L, 0L, 0L, 1095L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_9.4 = c(0L, 
0L, 0L, 6401L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_9.5 = c(0L, 0L, 0L, 1829L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_9.6 = c(0L, 
0L, 0L, 5056L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_9.7 = c(0L, 0L, 0L, 6093L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_9.8 = c(0L, 
0L, 0L, 3236L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_9.9 = c(0L, 0L, 0L, 7941L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_10 = c(0L, 
0L, 0L, 5221L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_10.1 = c(0L, 0L, 0L, 6178L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_10.2 = c(0L, 
0L, 0L, 7457L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_10.3 = c(0L, 0L, 0L, 5199L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA, 
-20L), class = c("tbl_df", "tbl", "data.frame"))```
17

Great -- next time be sure to include the line my_table <- above the structure() command, too.

In terms of your table, the values are all zero except one, so I'm afraid this won't help illustrate a proper solution. Where did the zeros come from? Are they in your original data?

18

The zeros are dominating between the first and the 20th columns because those pollution values are rare.
If I write this instead :

dput(my_table%>% select(100:120) %>% head(20))

I am getting that :

structure(list(HISTO_18.3 = c(208L, 233L, 39L, 2L, 802L, 83L, 
385L, 0L, 53L, 0L, 2L, 0L, 271L, 29L, 0L, 0L, 0L, 0L, 0L, 0L), 
    HISTO_18.4 = c(182L, 214L, 14L, 105L, 689L, 88L, 258L, 0L, 
    54L, 2L, 21L, 0L, 230L, 28L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.5 = c(173L, 
    184L, 14L, 107L, 570L, 57L, 336L, 0L, 39L, 10L, 67L, 0L, 
    253L, 32L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.6 = c(126L, 
    178L, 17L, 38L, 450L, 67L, 268L, 0L, 35L, 42L, 77L, 0L, 231L, 
    24L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.7 = c(115L, 123L, 
    8L, 33L, 465L, 34L, 284L, 0L, 44L, 84L, 79L, 0L, 184L, 18L, 
    0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.8 = c(104L, 182L, 10L, 
    0L, 435L, 31L, 173L, 0L, 37L, 135L, 70L, 0L, 166L, 24L, 0L, 
    0L, 0L, 0L, 0L, 0L), HISTO_18.9 = c(104L, 158L, 14L, 0L, 
    366L, 33L, 240L, 0L, 88L, 146L, 48L, 0L, 155L, 25L, 0L, 0L, 
    0L, 0L, 0L, 0L), HISTO_19 = c(84L, 147L, 16L, 0L, 328L, 20L, 
    192L, 0L, 60L, 136L, 50L, 0L, 135L, 20L, 0L, 0L, 0L, 0L, 
    0L, 0L), HISTO_19.1 = c(100L, 139L, 4L, 0L, 314L, 16L, 110L, 
    0L, 49L, 111L, 93L, 0L, 172L, 14L, 0L, 0L, 0L, 0L, 0L, 0L
    ), HISTO_19.2 = c(83L, 112L, 18L, 0L, 286L, 20L, 138L, 0L, 
    34L, 110L, 97L, 0L, 215L, 11L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.3 = c(75L, 
    136L, 11L, 0L, 266L, 23L, 141L, 0L, 51L, 117L, 72L, 0L, 240L, 
    19L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.4 = c(65L, 142L, 10L, 
    0L, 230L, 18L, 101L, 0L, 50L, 107L, 70L, 0L, 211L, 19L, 0L, 
    0L, 0L, 0L, 0L, 0L), HISTO_19.5 = c(64L, 100L, 8L, 0L, 219L, 
    19L, 97L, 0L, 39L, 107L, 62L, 41L, 211L, 13L, 0L, 0L, 0L, 
    0L, 0L, 0L), HISTO_19.6 = c(69L, 118L, 15L, 36L, 218L, 15L, 
    93L, 0L, 44L, 76L, 49L, 104L, 189L, 6L, 0L, 0L, 0L, 0L, 0L, 
    0L), HISTO_19.7 = c(41L, 90L, 4L, 19L, 149L, 36L, 87L, 0L, 
    37L, 94L, 55L, 79L, 159L, 10L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.8 = c(64L, 
    87L, 9L, 40L, 153L, 16L, 99L, 0L, 42L, 94L, 50L, 73L, 161L, 
    7L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.9 = c(30L, 119L, 9L, 
    0L, 126L, 55L, 107L, 0L, 35L, 80L, 49L, 75L, 182L, 10L, 0L, 
    0L, 0L, 0L, 0L, 0L), HISTO_20 = c(28L, 88L, 10L, 16L, 121L, 
    10L, 54L, 0L, 35L, 78L, 50L, 69L, 167L, 8L, 0L, 0L, 0L, 0L, 
    0L, 0L), HISTO_20.1 = c(42L, 53L, 3L, 0L, 113L, 28L, 71L, 
    0L, 31L, 70L, 42L, 72L, 214L, 8L, 0L, 0L, 0L, 0L, 0L, 0L), 
    HISTO_20.2 = c(23L, 66L, 6L, 2L, 97L, 20L, 57L, 0L, 29L, 
    77L, 20L, 69L, 240L, 7L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_20.3 = c(24L, 
    65L, 4L, 10L, 91L, 7L, 36L, 0L, 27L, 76L, 39L, 76L, 246L, 
    7L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA, -20L), class = c("tbl_df", 
"tbl", "data.frame"))

Does this help ?

19

The city column is missing, but you can include it by using select(1, 100:120) in your code, instead of select(100:120)

20

Here we are :


structure(list(NOM_IRIS = structure(c(18L, 127L, 23L, 89L, 28L, 
103L, 87L, 41L, 26L, 175L, 42L, 43L, 40L, 171L, 102L, 101L, 159L, 
63L, 99L, 98L), .Label = c("Abbaye", "Abry", "Aigle", "AlliŽs-Clos d'Or", 
"Alpins", "Ambroise Croizat", "Arc-En-Ciel", "Aristide Briand", 
"Arlequin", "Ayguinards", "Bajati\217re Est", "Bajati\217re Ouest", 
"Baladins", "Barnave-Saint-Robert", "Bastille", "Beauvert", "Berriat-Amp\217re", 
"Bresson", "BŽali\217res", "Capuche", "Champaviotte", "Championnet", 
"Claix Centre Bourg", "Clemenceau", "Clinique Mutualiste", "Comboire", 
"Constantine", "Corenc", "Cours Berriat", "Croix Rouge", "CrŽqui-Victor Hugo", 
"Curie-Rolland", "Diables Bleus", "Diderot", "Domaine Universitaire", 
"Drac-Ampere", "Drac-Vercors", "Eaux Claires-Champs Elysees", 
"Eaux Claires-PainlevŽ", "Echirolles Centre", "Echirolles Ouest-Nord", 
"Echirolles Ouest-Sud", "Echirolles Za du Centre", "Engenieres-Rolandiere", 
"Esplanade", "Europole", "Eybens Nord", "Eybens Sud Est", "Eybens Sud Ouest", 
"FerriŽ-Stalingrad", "Fiancey-Brieux", "Foch Est", "Foch Ouest", 
"Fontaine Mairie", "Fontaine Zone Industrielle", "Fontanil-Cornillon", 
"Frange Verte-Commanderie", "Gabriel PŽri", "Gare", "Gi\217res Nord", 
"Gi\217res Sud", "Glairons", "Grand-Place", "Grand Place Alpexpo", 
"Grand Pre-Buclos-Eyminees", "Grenette", "Gringalet", "Gustave Rivet", 
"GŽnissieu", "Haut de la Commune", "Haut Meylan", "Hebert-Mutualite", 
"Helbronner-Geants", "Hoche", "Houille Blanche", "Ile Verte-MarŽchal Randon", 
"Ile Verte-Saint Roch", "Jaur\217s-Vallier", "Jean Jaures", "Jean MacŽ", 
"Jeanne d'Arc", "Jouhaux", "La Bruyere", "La Falaise", "La Fauconni\217re", 
"La Monta-Visancourt", "Le Bourg-Les Chenevi\217res-Chantavot-Zone Indu", 
"Le Bourg-Les C\231tes", "Le Coteau", "Le Gua", "Le Pont-de-Claix Zone d'ActivitŽs des ëles", 
"Les Alloves", "Les Alpes", "Les Buissonnees", "Les ëles de Mars-Les Olympiades", 
"Les ëles Nord", "Les ëles Sud", "Les Essarts-Nord", "Les Essarts-Sud", 
"Les Floralies", "Les Granges-Nord", "Les Granges-Sud", "Les Mortes l'Oratoire Les Contamines", 
"Les Trembles", "Les Vouillands", "Lustucru", "Mairie-Langevin", 
"Malherbe", "Maquis du Gresivaudan-Nord", "Maquis du Gresivaudan-Sud", 
"Maupertuis-St Mury-Charlaix", "Meylan Zone d'ActivitŽs 1", "Meylan Zone d'ActivitŽs 2", 
"Meylan Zone d'ActivitŽs 3", "Mistral", "Moutonnees", "Murianette", 
"Mžrier", "Neyrpic", "Notre Dame", "Noyarey", "Pacalaire", "Paul-Eluard", 
"Paul Bert", "Paul Cocat", "Peretto", "Plaine du Pont Rouge", 
"Plaine Fleurie", "Plateforme Chimique", "Poisat", "Polygone", 
"Pont-de-Claix Bourg", "Portail Rouge", "Poterne", "Poya-Plans", 
"Predieu", "PrŽfecture", "Renaudie", "Reviree", "Reynies", "Rochepleine", 
"Rondeau-Liberation", "Saint-Andre", "Saint-Bruno", "Saint-ƒgr\217ve Zone Industrielle", 
"Saint-Laurent-Lavalette", "Saint-Martin-d'H\217res La Plaine", 
"Saint-Martin-d'H\217res Le Village", "Saint-Martin-le-Vinoux Nord Est", 
"Saint-Martin-le-Vinoux Sud Ouest et ZI", "Saint-Paul-de-Varces", 
"Sassenage La Plaine", "Semard", "Seyssinet-Pariset Le Village", 
"Seyssins La Plaine", "Seyssins Le Centre", "Seyssins Le Village", 
"Sidi-Brahim", "Surieux", "Taillees", "Teisseire", "Trois Cours", 
"Vallier", "Valmy", "Varces Centre", "Varces PŽriphŽrie", "Veurey-Voroize", 
"Vif Centre Ville", "Vif PŽriphŽrie", "Vigny-Musset", "Village 2", 
"Village Olympique Nord", "Village Olympique Sud", "Villancourt", 
"Viscose-Luire", "Waldeck-Rousseau", "Zone SpŽcifique l'ële d'Amour"
), class = "factor"), HISTO_18.3 = c(208L, 233L, 39L, 2L, 802L, 
83L, 385L, 0L, 53L, 0L, 2L, 0L, 271L, 29L, 0L, 0L, 0L, 0L, 0L, 
0L), HISTO_18.4 = c(182L, 214L, 14L, 105L, 689L, 88L, 258L, 0L, 
54L, 2L, 21L, 0L, 230L, 28L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.5 = c(173L, 
184L, 14L, 107L, 570L, 57L, 336L, 0L, 39L, 10L, 67L, 0L, 253L, 
32L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.6 = c(126L, 178L, 17L, 
38L, 450L, 67L, 268L, 0L, 35L, 42L, 77L, 0L, 231L, 24L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_18.7 = c(115L, 123L, 8L, 33L, 465L, 34L, 
284L, 0L, 44L, 84L, 79L, 0L, 184L, 18L, 0L, 0L, 0L, 0L, 0L, 0L
), HISTO_18.8 = c(104L, 182L, 10L, 0L, 435L, 31L, 173L, 0L, 37L, 
135L, 70L, 0L, 166L, 24L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_18.9 = c(104L, 
158L, 14L, 0L, 366L, 33L, 240L, 0L, 88L, 146L, 48L, 0L, 155L, 
25L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19 = c(84L, 147L, 16L, 0L, 
328L, 20L, 192L, 0L, 60L, 136L, 50L, 0L, 135L, 20L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_19.1 = c(100L, 139L, 4L, 0L, 314L, 16L, 110L, 
0L, 49L, 111L, 93L, 0L, 172L, 14L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.2 = c(83L, 
112L, 18L, 0L, 286L, 20L, 138L, 0L, 34L, 110L, 97L, 0L, 215L, 
11L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.3 = c(75L, 136L, 11L, 
0L, 266L, 23L, 141L, 0L, 51L, 117L, 72L, 0L, 240L, 19L, 0L, 0L, 
0L, 0L, 0L, 0L), HISTO_19.4 = c(65L, 142L, 10L, 0L, 230L, 18L, 
101L, 0L, 50L, 107L, 70L, 0L, 211L, 19L, 0L, 0L, 0L, 0L, 0L, 
0L), HISTO_19.5 = c(64L, 100L, 8L, 0L, 219L, 19L, 97L, 0L, 39L, 
107L, 62L, 41L, 211L, 13L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.6 = c(69L, 
118L, 15L, 36L, 218L, 15L, 93L, 0L, 44L, 76L, 49L, 104L, 189L, 
6L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.7 = c(41L, 90L, 4L, 19L, 
149L, 36L, 87L, 0L, 37L, 94L, 55L, 79L, 159L, 10L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_19.8 = c(64L, 87L, 9L, 40L, 153L, 16L, 99L, 
0L, 42L, 94L, 50L, 73L, 161L, 7L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_19.9 = c(30L, 
119L, 9L, 0L, 126L, 55L, 107L, 0L, 35L, 80L, 49L, 75L, 182L, 
10L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_20 = c(28L, 88L, 10L, 16L, 
121L, 10L, 54L, 0L, 35L, 78L, 50L, 69L, 167L, 8L, 0L, 0L, 0L, 
0L, 0L, 0L), HISTO_20.1 = c(42L, 53L, 3L, 0L, 113L, 28L, 71L, 
0L, 31L, 70L, 42L, 72L, 214L, 8L, 0L, 0L, 0L, 0L, 0L, 0L), HISTO_20.2 = c(23L, 
66L, 6L, 2L, 97L, 20L, 57L, 0L, 29L, 77L, 20L, 69L, 240L, 7L, 
0L, 0L, 0L, 0L, 0L, 0L), HISTO_20.3 = c(24L, 65L, 4L, 10L, 91L, 
7L, 36L, 0L, 27L, 76L, 39L, 76L, 246L, 7L, 0L, 0L, 0L, 0L, 0L, 
0L)), row.names = c(NA, -20L), class = c("tbl_df", "tbl", "data.frame"
))