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How do you figure out the numerical columns of the Orange data set?

E
esther last edited by

The mean values for all the numerical columns of the set should be calculated and removed. Data Orange and descriptive statistics on the Orange data set.
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Marcee last edited by
Perhaps you'd like to see the average age and length of the tree ring from the dateset. Orange♪ This can be done as follows by grouping the tree number:
```
library(tidyverse)
Orange %>%

group_by(Tree) %>%

summarise(mean_age = mean(age, na.rm = TRUE),

mean_cir = mean(circumference, na.rm = TRUE))
```
Basic narrative statistics can be obtained using the function summary to date.
Next time, please clarify the question: give an example of the data, the expected outcome, etc.
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Something like that can be done on the account of height/lossdf <- data.frame(year=c(1,2,2,3,4,1,6,3,4,2)) test <- function(x,n) { if(x==1) return( NA) else{ if (df[x,n]<df[x-1,n]) return ("UP") else return ("DOWN")} } a=1:nrow(df) df$b=unlist(lapply(a, FUN=function(i) test(i,1))) And then figuring out UP/DOWN
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var fdata = {'login': login, 'pass': pass}; function myfunc(fdata) { //... fdata.token = 'test'; $.ajax({ type: 'POST', url: '/test.php', data: fdata, // <---------сюда //... }
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If you only look for that then an option might first be to pass the values of table A to table C with the following:INSERT INTO TABLA_C(nombre) SELECT nombre FROM TABLA_A And then pass the values of table B to table CINSERT INTO TABLA_C(nombre) SELECT nombre FROM TABLA_B The other option is to make UNION of tables A and B.
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The following code should do what you need:df_long <- plyr::ldply(1:5, function(i){ aux <- df[,(2*i -1):(2*i)] names(aux) <- c("valor_letra", "valor_k") aux$letra <- LETTERS[i] aux$K <- i aux }) df_long$K_menor <- ifelse(df_long$valor_k < 0.05, "menor", "maior") ggplot(df_long, aes(x = valor_letra, y = valor_k, shape = K_menor)) + geom_point() + facet_wrap(~letra) My code first The complete list of shapes is here: Starting from scratch and the direction is from top to bottom and from left to right.
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I just got a way to fix the problem.If the minimum value is greater than the maximum creates a new column in which it is fulfilled puts the minimum values and where it does not put the maximum values data_frame$min_customizado<-ifelse(data_frame$min > data_frame$max,data_frame$max,data_frame$min) On the contrary, if the maximum value is less than the minimum value creates a new column in which it puts where the maximum values are met and where not, puts the minimum values data_frame$max_customizado<-ifelse(data_frame$min< data_frame$max,data_frame$max,data_frame$min)
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Details http://php.net/manual/ru/function.var-export.php ♪$config = array( 'description' => 'Введите описание!', 'keywords' => 'ключевые слова', 'blog_name' => 'Название сайта', 'template' => 'briton', 'db' => array( 'host' => 'localhost', 'user' => 'root', 'password' => '', 'basename' => 'armor' ) ); $contents = var_export($config, true); // Если передано и значение равно TRUE, var_export() вернет представление переменной вместо его вывода. file_put_contents('config.php', "<?php\n return {$contents};\n"); Result config.php:<?php return array ( 'description' => 'Введите описание!', 'keywords' => 'ключевые слова', 'blog_name' => 'Название сайта', 'template' => 'briton', 'db' => array ( 'host' => 'localhost', 'user' => 'root', 'password' => '', 'basename' => 'armor', ), );UPDATE Just to rewrite the line. $for_edit = "template"; // Ищем ключ который нужно заменить $what = "'template' => 'my_own',\n"; // А тут делаем строку из ключа и нового значения этого ключа $fopen = @file("config.php"); foreach ($fopen as $key => $value) { if (substr_count($value,$for_edit)) { array_splice($fopen, $key, 1, $what); // Если нашли совпадение, то заменяем } $f = fopen("config.php", "w"); // Перезаписали в файл for($i = 0; $i < count($fopen); $i++) { fwrite($f, $fopen[$i]); } fclose($f); }
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Spent a series of experiments. The answer to the question depends on the PHP version.Minimum exampleFile for the show ser_priv.php:class MyClass{ private $id; public function __construct($id) { $this->id = $id; } } $o = new MyClass(123); file_put_contents(DIR . '/data', serialize($o)); Desertion File unser.php:class MyClass { // Заменили на protected protected $id; public function __construct($id) { $this->id = $id; } public function test() { $prop = new ReflectionProperty('MyClass', 'id'); printf("prop is protected: %d\n", $prop->isProtected()); printf("prop has value: %d\n", $this->id); } } $data = file_get_contents(DIR . '/data'); $o = unserialize($data); $o->test(); https://github.com/dbfun/serialize-private ResultsPHP 7.3.0RC4: protected properties are correct correct, the same value as it was.PHP 5.6.33: protected characteristic not determined correctly after unserialize♪If you do var_dump($o);It'll come out.object(MyClass)#1 (2) { ["id":protected]=> NULL ["id":"MyClass":private]=> int(123) } var_export($o);:MyClass::__set_state(array( 'id' => NULL, 'id' => 123, )) "Take" 123 was not a good way. Unpleasant type of method var_export and the passwording of the result was not considered, but it is also an option.Now we're going to show the same object, but in the first case, it's gonna be privateSecond protected♪ Let's see the binary what happened:$ xxd data_priv 0000000: 4f3a 373a 224d 7943 6c61 7373 223a 313a O:7:"MyClass":1: 0000010: 7b73 3a31 313a 2200 4d79 436c 6173 7300 {s:11:".MyClass. 0000020: 6964 223b 693a 3132 333b 7d id";i:123;} $ xxd data_prot 0000000: 4f3a 373a 224d 7943 6c61 7373 223a 313a O:7:"MyClass":1: 0000010: 7b73 3a35 3a22 002a 0069 6422 3b69 3a31 {s:5:"..id";i:1 0000020: 3233 3b7d 23;} It turns out private stored like "MyClass.id," and protected It's like "..id," but instead of binary zeros. The length of the line is different.s:11 and s:5)The idea is to replace private ♪ protected♪ Something universal doesn't want to do, maybe someone's gonna freak out. Here's the minimum gear shift. id♪Fail unser_php56.php:class MyClass { // свойство с измененной областью видимости protected $id; } $data = file_get_contents(DIR . '/data_priv'); $data = bin2hex($data); // Заменяем определение свойства $data = str_replace('31313a22004d79436c617373', '353a22002a', $data); $data = hex2bin($data); $o = unserialize($data); var_dump($o); Result:object(MyClass)#1 (1) { ["id":protected]=> int(123) }
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It is possible to:df["new_col_name"] = (df['Age'] > 40) + 1 Description:df['Age'] > 40 - return the pole. If we add a unit to the bulb values, we will. 1 instead False and 2 instead True♪Example:In [25]: df = pd.DataFrame({"age": [20, 50, 60, 40]}) In [26]: df Out[26]: age 0 20 1 50 2 60 3 40 In [27]: df["age"] > 40 Out[27]: 0 False 1 True 2 True 3 False Name: age, dtype: bool In [28]: (df["age"] > 40) + 1 Out[28]: 0 1 1 2 2 2 3 1 Name: age, dtype: int32
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for (i in 1:ncol(df)) df[is.na(df[,i]),i]<-mean(df[,i],na.rm=T)
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append() adds only one elementUse many elements to add. extend()@clan.command() async def profile(self, ctx): author = ctx.message.author clan_id = cur.execute(f'SELECT ClanId FROM UserClans WHERE UserId = {author.id}').fetchone() cur.execute(f'SELECT UserName FROM UserClans WHERE {clan_id[0]}') users = cur.fetchall() l = [] l.extend(users) # одно изменение return print(l)
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For example, you can put an end to it. Image Total Gridand add a second subsidiary to the same Grid Your ellips.Order important: The sequence of the subsidiary components defines their Z-order.

How do you figure out the numerical columns of the Orange data set?

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