fixing stuff

Author: Nicolas Greliche

Index.Rmd

@@ -19,10 +19,7 @@ library(learnr)
 
 experiment2017<-read.csv("experiment2017.csv")
 interview2019<-read.csv("interview2019.csv")
-experiment2017$Farmer <- iconv(experiment2017$Farmer, to = "UTF-8")
-Encoding(experiment2017$Farmer) <- "UTF-8"
-interview2019$Name <- iconv(interview2019$Name, "UTF-8")
-Encoding(interview2019$Name) <- "UTF-8"
+
 
 MergedData<-inner_join(experiment2017,interview2019,by=c("Farmer"="Name"))
 
@@ -56,9 +53,9 @@ library(tidyr)
 
 ## Data for this session
 
-In this session we will use two related fictive datasets. The first one, called `experiment2017` is an on farm experiment, where each of 20 farmers has collected values of yield for two plots, one where a new treatment has been applied (column "Treatment"), and one where this new treatment has not been applied (column "Control"). You can download this dataset [here](https://github.com/stats4sd/R4CCRP_08Merge/raw/main/experiment2017.csv)  
+In this session we will use two related fictive datasets. The first one, called `experiment2017` is an on farm experiment, where each of 20 farmers has collected values of yield for two plots, one where a new treatment has been applied (column "Treatment"), and one where this new treatment has not been applied (column "Control").  
 
-The other dataset called `interview2019` contains the responses of 71 farmers - some of which participated in the 2017 experiment - when asked whether they would accept to participate to a new experiment (column "Accept"). You can download this dataset [here](https://github.com/stats4sd/R4CCRP_08Merge/raw/main/interview2019.csv) 
+The other dataset called `interview2019` contains the responses of 71 farmers - some of which participated in the 2017 experiment - when asked whether they would accept to participate to a new experiment (column "Accept"). You can download these two datasets [here](https://github.com/stats4sd/R4CCRP_08Merge/raw/main/data-merge.zip) 
 
 Our goal will be to combine these two datasets in order to explore whether for a farmer, the outcome of the 2017 experiment is related to their willingness to participate in a new experiment.
 
@@ -168,7 +165,7 @@ knitr::include_graphics("images/longCCRP.jpg")
 And if you think to when we've used `ggplot2`, we always had one unique variable for our y argument, and we used categorical variables to separate it into groups, facets, colours and it was similar for modelling. We had one dependant variable only and the groups of the Anova were defined by come categorical variable. So in general long formats work much better than wide formats for making graphs or doing some statistical modelling.
 
 
-And to help us analyse our dataframe `MergedData` where the experimental data is in long format, we should turn it into long format.
+And to help us analyse our dataframe `MergedData` where the experimental data is in wide format, we should turn it into long format.
 
 The `pivot_longer()` function from the `tidyr` library allows us to do this. 
 
@@ -217,7 +214,7 @@ LongData %>%
 ```
 Notice that it is the group aesthetics that define which are the points connected by the lines. In our case, these are the points corresponding to a same farmer.
 
-We can see that most of the lines that go down are red, that is most of the farmers who saw a decrease in yield between the control and treatment plots during the 2017 experiment, did not want to participate in a new experiment according to the 2019 interview. In contrast, the lines that go up seem to often be blue. This might be easier to see using facets:
+We can see that most of the lines that go down are red, that is most of the farmers who saw a decrease in yield between the control and treatment plots during the 2017 experiment, did not want to participate in a new experiment according to the 2019 interview. In contrast, the lines that go up are blue. This might be easier to see using facets:
 
 ```{r gather3, exercise=TRUE}
 LongData %>%

Index.html

@@ -131,15 +131,15 @@ <h2>Overview</h2>
 </div>
 <div id="section-data-for-this-session" class="section level2">
 <h2>Data for this session</h2>
-<p>In this session we will use two related fictive datasets. The first one, called <code>experiment2017</code> is an on farm experiment, where each of 20 farmers has collected values of yield for two plots, one where a new treatment has been applied (column “Treatment”), and one where this new treatment has not been applied (column “Control”).</p>
-<p>The other dataset called <code>interview2019</code> contains the responses of 71 farmers - some of which participated in the 2017 experiment - when asked whether they would accept to participate to a new experiment (column “Accept”).</p>
+<p>In this session we will use two related fictive datasets. The first one, called <code>experiment2017</code> is an on farm experiment, where each of 20 farmers has collected values of yield for two plots, one where a new treatment has been applied (column “Treatment”), and one where this new treatment has not been applied (column “Control”). You can download this dataset <a href="https://github.com/stats4sd/R4CCRP_08Merge/raw/main/experiment2017.csv">here</a></p>
+<p>The other dataset called <code>interview2019</code> contains the responses of 71 farmers - some of which participated in the 2017 experiment - when asked whether they would accept to participate to a new experiment (column “Accept”). You can download this dataset <a href="https://github.com/stats4sd/R4CCRP_08Merge/raw/main/interview2019.csv">here</a></p>
 <p>Our goal will be to combine these two datasets in order to explore whether for a farmer, the outcome of the 2017 experiment is related to their willingness to participate in a new experiment.</p>
 <p>You can have a look at the <code>experiment2017</code> dataset here:</p>
-<div id="htmlwidget-e53f832da80b88b740c9" style="width:100%;height:auto;" class="datatables html-widget"></div>
-<script type="application/json" data-for="htmlwidget-e53f832da80b88b740c9">{"x":{"filter":"none","data":[["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20"],["Anu Malimba","Djamilatou Itondo","Elone Ngoma","Zonga Mulongo","Hawaou Etamè","Éliane Ouandié","Romaine Makau","Coline Kiessou","Nadia Yondo","Yolande Kiki","Mbiybe Yumè","Agbor Mukala","Ndedi Ebodé","Yaya Mbakop","Lawal Ngandu","Robin Boko","Fabien Nde","Alexandre Esanji","Jacob Kuka","Anthony Kamalandua"],[331,304,750,104,10,540,424,798,763,743,941,369,807,261,574,913,450,645,373,262],[949,153,28,622,299,721,412,971,481,578,953,538,113,369,919,839,348,537,115,285],[4.159839,4.127491,4.125305,4.130613,4.13676,4.14545,4.145878,4.146338,4.14271,4.130234,4.146678,4.157985,4.152868,4.102666,4.09906,4.107758,4.145783,4.085736,4.114845,4.14889],[11.582091,11.564142,11.566062,11.531707,11.54421,11.491345,11.487472,11.483642,11.477913,11.516895,11.87906,11.88563,11.858833,11.875491,11.87165,11.8495,11.86696,11.895782,11.823748,11.87564]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Farmer<\/th>\n      <th>Control<\/th>\n      <th>Treatment<\/th>\n      <th>Latitude<\/th>\n      <th>Longitude<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"columnDefs":[{"className":"dt-right","targets":[2,3,4,5]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
+<div id="htmlwidget-73285f9ba81277aa59f8" style="width:100%;height:auto;" class="datatables html-widget"></div>
+<script type="application/json" data-for="htmlwidget-73285f9ba81277aa59f8">{"x":{"filter":"none","data":[["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20"],["Anu Malimba","Djamilatou Itondo","Elone Ngoma","Zonga Mulongo","Hawaou Etame","Eliane Ouandie","Romaine Makau","Coline Kiessou","Nadia Yondo","Yolande Kiki","Mbiybe Yume","Agbor Mukala","Ndedi Ebode","Yaya Mbakop","Lawal Ngandu","Robin Boko","Fabien Nde","Alexandre Esanji","Jacob Kuka","Anthony Kamalandua"],[331,304,750,104,10,540,424,798,763,743,941,369,807,261,574,913,450,645,373,262],[949,153,28,622,299,721,412,971,481,578,953,538,113,369,919,839,348,537,115,285],[4.159839,4.127491,4.125305,4.130613,4.13676,4.14545,4.145878,4.146338,4.14271,4.130234,4.146678,4.157985,4.152868,4.102666,4.09906,4.107758,4.145783,4.085736,4.114845,4.14889],[11.582091,11.564142,11.566062,11.531707,11.54421,11.491345,11.487472,11.483642,11.477913,11.516895,11.87906,11.88563,11.858833,11.875491,11.87165,11.8495,11.86696,11.895782,11.823748,11.87564]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Farmer<\/th>\n      <th>Control<\/th>\n      <th>Treatment<\/th>\n      <th>Latitude<\/th>\n      <th>Longitude<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"columnDefs":[{"className":"dt-right","targets":[2,3,4,5]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
 <p>And you can explore the <code>interview2019</code> dataset below:</p>
-<div id="htmlwidget-1c3cccf86b51b2df1d10" style="width:100%;height:auto;" class="datatables html-widget"></div>
-<script type="application/json" data-for="htmlwidget-1c3cccf86b51b2df1d10">{"x":{"filter":"none","data":[["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49","50","51","52","53","54","55","56","57","58","59","60","61","62","63","64","65","66","67","68","69","70","71"],["Zaitouna Bebey","Mariamou Ngolu","Rougayatou Kiatoko","Sahndra Masikini",null,null,"Amber Nkumu","Mia Mvone","Manon Koagne",null,"Lawal Nenne",null,"Nforbi Toguo","Mvondo Boko","Kimbu Lemnyuy","Silvain Mboumoua","Fabrice Emade","Ashton Linzenge","Alphonse Mejo'o",null,"Rachidatou Mejo'o","Naghen Liboko",null,null,null,"Manon Mpongo",null,null,"Lucile Meba'a","Ange Masuka","Djal Mvone","Nzo Ndongue","Langke Abba","Neba Likuta","Adamou Arabo","Dominique Hamilou","Ellis Mbok","Daniel Zula",null,null,null,null,"Romaine Makau","Coline Kiessou","Nadia Yondo","Yolande Kiki","Robin Boko","Fabien Nde","Alexandre Esanji","Jacob Kuka","Anthony Kamalandua","Angu Nyassa","Anyi Billong",null,"Kien Ahmadou",null,"Peggy Tanga","Claude Kabange","Aline Nadege","Cerys Makeda","Amanda Kibangi",null,"Mbiybe Kumba","Mbe Eyene","Kenjo Maleta","Lazare Hamilou",null,"David Dikuta",null,"Samuel Moundi",null],["Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male"],["Yes","No","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes"]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Name<\/th>\n      <th>Gender<\/th>\n      <th>Accept<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"order":[],"autoWidth":false,"orderClasses":false,"columnDefs":[{"orderable":false,"targets":0}]}},"evals":[],"jsHooks":[]}</script>
+<div id="htmlwidget-ea89fb7f465badf783b3" style="width:100%;height:auto;" class="datatables html-widget"></div>
+<script type="application/json" data-for="htmlwidget-ea89fb7f465badf783b3">{"x":{"filter":"none","data":[["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49","50","51","52","53","54","55","56","57","58","59","60","61","62","63","64","65","66","67","68","69","70","71"],["Zaitouna Bebey","Mariamou Ngolu","Rougayatou Kiatoko","Sahndra Masikini","Zeinabou Obambe","Violaine Suke","Amber Nkumu","Mia Mvone","Manon Koagne","Veronique Njoya","Lawal Nenne","Fote Bebey","Nforbi Toguo","Mvondo Boko","Kimbu Lemnyuy","Silvain Mboumoua","Fabrice Emade","Ashton Linzenge","Alphonse Mejo'o","Jose Lekunze","Rachidatou Mejo'o","Naghen Liboko","Fua Songe","Amaniyatou Assale","Azah Elame","Manon Mpongo","Ella Mubambwe","Harmonie Ewale","Lucile Meba'a","Ange Masuka","Djal Mvone","Nzo Ndongue","Langke Abba","Neba Likuta","Adamou Arabo","Dominique Hamilou","Ellis Mbok","Daniel Zula","Benoit Alima","Sebastien Okapi","Hawaou Etame","Eliane Ouandie","Romaine Makau","Coline Kiessou","Nadia Yondo","Yolande Kiki","Robin Boko","Fabien Nde","Alexandre Esanji","Jacob Kuka","Anthony Kamalandua","Angu Nyassa","Anyi Billong","Ateh Tebi","Kien Ahmadou","Ngwi Ebenye","Peggy Tanga","Claude Kabange","Aline Nadege","Cerys Makeda","Amanda Kibangi","Tanzetanau Mpembe","Mbiybe Kumba","Mbe Eyene","Kenjo Maleta","Lazare Hamilou","Timothee Milandu","David Dikuta","Abelin Elombe","Samuel Moundi","Michael Nzoumba"],["Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Female","Female","Female","Female","Female","Female","Female","Female","Female","Female","Male","Male","Male","Male","Male","Male","Male","Male","Male","Male"],["Yes","No","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes","Yes","Yes","Yes","Yes","No","Yes","Yes","Yes","Yes","No","No","No","No","No","No","No","No","Yes"]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Name<\/th>\n      <th>Gender<\/th>\n      <th>Accept<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"order":[],"autoWidth":false,"orderClasses":false,"columnDefs":[{"orderable":false,"targets":0}]}},"evals":[],"jsHooks":[]}</script>
 </div>
 <div id="section-full-joins" class="section level2">
 <h2>Full joins</h2>
@@ -259,10 +259,7 @@ <h2>More complex transformations</h2>
 
 experiment2017<-read.csv("experiment2017.csv")
 interview2019<-read.csv("interview2019.csv")
-experiment2017$Farmer <- iconv(experiment2017$Farmer, to = "UTF-8")
-Encoding(experiment2017$Farmer) <- "UTF-8"
-interview2019$Name <- iconv(interview2019$Name, "UTF-8")
-Encoding(interview2019$Name) <- "UTF-8"
+
 
 MergedData<-inner_join(experiment2017,interview2019,by=c("Farmer"="Name"))
 

data-merge.zip

@@ -3,15 +3,15 @@ Anu Malimba,331,949,4.159839,11.582091
 Djamilatou Itondo,304,153,4.127491,11.564142
 Elone Ngoma,750,28,4.125305,11.566062
 Zonga Mulongo,104,622,4.130613,11.531707
-Hawaou Etam�,10,299,4.13676,11.54421
-�liane Ouandi�,540,721,4.14545,11.491345
+Hawaou Etame,10,299,4.13676,11.54421
+Eliane Ouandie,540,721,4.14545,11.491345
 Romaine Makau,424,412,4.145878,11.487472
 Coline Kiessou,798,971,4.146338,11.483642
 Nadia Yondo,763,481,4.14271,11.477913
 Yolande Kiki,743,578,4.130234,11.516895
-Mbiybe Yum�,941,953,4.146678,11.87906
+Mbiybe Yume,941,953,4.146678,11.87906
 Agbor Mukala,369,538,4.157985,11.88563
-Ndedi Ebod�,807,113,4.152868,11.858833
+Ndedi Ebode,807,113,4.152868,11.858833
 Yaya Mbakop,261,369,4.102666,11.875491
 Lawal Ngandu,574,919,4.09906,11.87165
 Robin Boko,913,839,4.107758,11.8495

experiment2017.csv

@@ -3,30 +3,30 @@ Zaitouna Bebey,Female,Yes
 Mariamou Ngolu,Female,No
 Rougayatou Kiatoko,Female,Yes
 Sahndra Masikini,Female,No
-Ze�nabou Obamb�,Female,Yes
-Violaine Suk�,Female,Yes
+Zeinabou Obambe,Female,Yes
+Violaine Suke,Female,Yes
 Amber Nkumu,Female,Yes
 Mia Mvone,Female,Yes
 Manon Koagne,Female,No
-V�ronique Njoya,Female,No
+Veronique Njoya,Female,No
 Lawal Nenne,Male,No
-Fot� Bebey,Male,No
+Fote Bebey,Male,No
 Nforbi Toguo,Male,No
 Mvondo Boko,Male,No
 Kimbu Lemnyuy,Male,No
 Silvain Mboumoua,Male,No
 Fabrice Emade,Male,Yes
 Ashton Linzenge,Male,Yes
 Alphonse Mejo'o,Male,Yes
-Jos� L�kunz�,Male,Yes
+Jose Lekunze,Male,Yes
 Rachidatou Mejo'o,Female,Yes
 Naghen Liboko,Female,No
-Fua Song�,Female,Yes
-Amaniyatou Assal�,Female,Yes
-Azah Elam�,Female,Yes
+Fua Songe,Female,Yes
+Amaniyatou Assale,Female,Yes
+Azah Elame,Female,Yes
 Manon Mpongo,Female,Yes
-Ella Mubambw�,Female,No
-Harmonie Ewal�,Female,No
+Ella Mubambwe,Female,No
+Harmonie Ewale,Female,No
 Lucile Meba'a,Female,No
 Ange Masuka,Female,No
 Djal Mvone,Male,No
@@ -37,10 +37,10 @@ Adamou Arabo,Male,Yes
 Dominique Hamilou,Male,Yes
 Ellis Mbok,Male,Yes
 Daniel Zula,Male,Yes
-Beno�t Alima,Male,Yes
-S�bastien Okapi,Male,No
-Hawaou Etam�,Female,Yes
-�liane Ouandi�,Female,Yes
+Benoit Alima,Male,Yes
+Sebastien Okapi,Male,No
+Hawaou Etame,Female,Yes
+Eliane Ouandie,Female,Yes
 Romaine Makau,Female,Yes
 Coline Kiessou,Female,Yes
 Nadia Yondo,Female,No
@@ -52,21 +52,21 @@ Jacob Kuka,Male,No
 Anthony Kamalandua,Male,No
 Angu Nyassa,Female,No
 Anyi Billong,Female,Yes
-Ateh T�bi,Female,Yes
+Ateh Tebi,Female,Yes
 Kien Ahmadou,Female,Yes
-Ngwi Eb�ny�,Female,Yes
+Ngwi Ebenye,Female,Yes
 Peggy Tanga,Female,Yes
 Claude Kabange,Female,No
 Aline Nadege,Female,Yes
 Cerys Makeda,Female,Yes
 Amanda Kibangi,Female,Yes
-Tanzetanau Mp�mb�,Male,Yes
+Tanzetanau Mpembe,Male,Yes
 Mbiybe Kumba,Male,No
 Mbe Eyene,Male,No
 Kenjo Maleta,Male,No
 Lazare Hamilou,Male,No
-Timoth�e Milandu,Male,No
+Timothee Milandu,Male,No
 David Dikuta,Male,No
-Abelin Elomb�,Male,No
+Abelin Elombe,Male,No
 Samuel Moundi,Male,No
-Micha�l Nzoumba,Male,Yes
+Michael Nzoumba,Male,Yes

interview2019.csv

@@ -4,45 +4,45 @@ Eposi Simbelela,Female,Yes
 Acha Tshika,Female,No
 Namondo Nguena,Female,Yes
 Zonga Bella,Female,Yes
-Mariette Ilong�,Female,No
+Mariette Ilonge,Female,No
 Bella Obama,Female,Yes
 Caitlin Wabou,Female,Yes
 Vivienne Suh,Female,No
 Amelie Zanga,Female,No
 Ateh Malembe,Male,No
-Leynywy Iwum�,Male,No
+Leynywy Iwume,Male,No
 Ilyassa Nguo,Male,No
-Fru B�nga,Male,Yes
+Fru Benga,Male,Yes
 Anacle Diwedi,Male,Yes
 Jenson Elad,Male,No
 Roland Babende,Male,No
 David Samba,Male,No
 Thibault Atangana,Male,Yes
-Daniel Mokat�,Male,Yes
-Liyshisha Elam�,Female,No
+Daniel Mokate,Male,Yes
+Liyshisha Elame,Female,No
 Panbela Dokunanga,Female,No
 Diddi Ebot,Female,No
 Mambo Simba,Female,No
 Rachidatou Kimbangu,Female,No
-St�phanie Mut�ng�n�,Female,Yes
-�meline Kibangi,Female,Yes
+Stephanie Mutengene,Female,Yes
+Emeline Kibangi,Female,Yes
 Miryam Halidou,Female,No
 Leila Limbay,Female,No
 Alix Fako,Female,No
 Nkanya Ezua,Male,Yes
 Ndamukong Mabiala,Male,Yes
 Anu Kimya,Male,No
-Awli A�ssatou,Male,No
+Awli Aissatou,Male,No
 Rachid Malimba,Male,No
 Aaron Malondo,Male,No
 Maurice Aloumbassa,Male,No
 Louis Meva'a,Male,Yes
 Gervais Prizo,Male,Yes
-Isa�e Liama,Male,No
+Isaie Liama,Male,No
 Bih Anyeni,Female,No
 Hadidjatou Makau,Female,No
 Atabong Simbelela,Female,Yes
-Namondo Ndoumb�,Female,Yes
+Namondo Ndoumbe,Female,Yes
 Nadjela Moussa,Female,Yes
 Katie Lamba,Female,Yes
 Nicole Kalala,Female,Yes
@@ -55,7 +55,7 @@ Ilyassa Lihuli,Male,Yes
 Kouomegui Zula,Male,No
 Njongai Lumbala,Male,No
 Justin Ekoto,Male,No
-Daniel Mbapp�,Male,Yes
+Daniel Mbappe,Male,Yes
 Pierre Ekowa,Male,Yes
 Ghislain Mbia,Male,Yes
 Zachary Ebot,Male,Yes