|
Introduction to R Bern R Bootcamp |
from methodspace.com
In this practical you’ll learn how to work with basic data objects and functions. By the end of this practical you will know how to:
c()
class()
mean()
, median()
, table()
(and more!)read_csv()
and others$
data.frames
and tibbles
using data.frame()
and tibble()
Open your BernRBootcamp
R project. It should already have the folders 1_Data
and 2_Code
.
Open a new R script and save it as a new file called data_practical.R
in the 2_Code
folder. At the top of the script, using comments, write your name and the date. Then, load all package(s) listed in the Packages section above with library()
. Make sure that each of the datasets listed above lie in your 1_Data
folder.
The table below shows results from a (fictional) survey of 10 Baselers. In the first part of this practical, you will convert this table to R objects and then analyse them!
| id | sex | age | height | weight |
|---|---|---|---|---|
| 1 | male | 44 | 174.3 | 113.4 |
| 2 | male | 65 | 180.3 | 75.2 |
| 3 | female | 31 | 168.3 | 55.5 |
| 4 | male | 27 | 209 | 93.8 |
| 5 | male | 24 | 176.7 | |
| 6 | male | 63 | 186.6 | 67.4 |
| 7 | male | 71 | 151.6 | 83.3 |
| 8 | female | 41 | 155.7 | 67.8 |
| 9 | male | 43 | 176.1 | 69.3 |
| 10 | female | 31 | 166.1 | 66.3 |
id
that shows the id values. When you finish, print the vector object to see it!# Create a vector id
XX <- c(XX, XX, ...)
# Print the vector id
XX
# Create an id vector
id <- 1:10 # shortcut to creating the sequence from 1 to 10
# Print the vector
id
## [1] 1 2 3 4 5 6 7 8 9 10
class()
function, check the class of your id
vector. Is it "numeric"
?# Show the class of an object XX
class(XX)
# Show the class of the id vector
class(id)
## [1] "integer"
length()
function, find out the length of your id
vector. Does it have length 10? If not, make sure you defined it correctly!# Show the length of the id vector
length(XX)
# Show the length of the id vector
length(id)
## [1] 10
sex
that shows the sex values. Make sure to use quotation marks "" to enclose each element to tell R that the data are of type "character"
! When you finish, print the object to see it!# Create a character vector sex
XX <- c("XX", "XX", "...")
 Is it "character"
?#  Does it have length 10? If not, make sure you defined it correctly!# Show the length of the sex vector
length(sex)
## [1] 10
age
and height
vector.# Create a age vector
age <- c(44, 65, 31, 27, 24, 63, 71, 41, 43, 31)
# Print the age vector
age
## [1] 44 65 31 27 24 63 71 41 43 31
# Show the class of the age vector
class(age)
## [1] "numeric"
# Show the length of the age vector
length(age)
## [1] 10
# Create a height vector
height <- c(174.3, 180.3, 168.3, 209, 176.7, 186.6, 151.6, 155.7, 176.1, 166.1)
# Print the height vector
height
## [1] 174 180 168 209 177 187 152 156 176 166
# Show the class of the height vector
class(height)
## [1] "numeric"
# Show the length of the height vector
length(height)
## [1] 10
weight
containing these data, following the same steps as before, making sure to specify the missing value as NA
(no quotation marks).# Create a weight vector
weight <- c(113.4, 75.2, 55.5, 93.8, NA, 67.4, 83.3, 67.8, 69.3, 66.3)
# Print the weight vector
weight
## [1] 113.4 75.2 55.5 93.8 NA 67.4 83.3 67.8 69.3 66.3
# Show the class of the weight vector
class(weight)
## [1] "numeric"
# Show the length of the weight vector
length(weight)
## [1] 10
table()
function, find out how many males and females are in the data. You should find 7 males and 3 females!#  It should be 44!# Compute mean of age
mean(age)
## [1] 44
sex
. What happens? Why?# Compute mean of sex
mean(sex)
## [1] NA
weight
. You should get an NA
value. Why?# Compute mean of sex
mean(weight)
## [1] NA
mean()
function (using ?mean
) to look for an argument that will help you with your problem.# Inspect help for mean
?mean
NA
values. It should be 76.89!# Compute mean weight, ignoring NAs
mean(weight, na.rm = TRUE)
## [1] 76.9
In this section, you will read in a subset of the well known diamonds data set and prepare it for data analysis.
diamonds.csv
dataset using the ""
(quotation marks) auto-complete trick. Place the cursor between two quotation marks, hit ⇥ (tab-key), and browse through the folders. Save the file path, for now, in an object called diamonds_path
.# place cursor in-between "" and hit tab
diamonds_path <- ""
# place cursor in-between and hit tab
diamonds_path <- "1_Data/diamonds.csv"
diamonds_path
insdide the read_csv()
function to read in the diamonds.csv
dataset. Store it as a new object called diamonds
.# read diamonds data
diamonds <- read_csv(file = XX)
# read diamonds data
diamonds <- read_csv(file = diamonds_path)
diamonds
data and inspect the column names in the header line. Something’s wrong!# print diamonds
diamonds
## # A tibble: 99 x 7
## `0.8` `Very Good` H VVS1 `62.9` `58` `4468`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 0.74 Ideal H IF 60.9 57 3760
## 2 2.03 Premium I SI1 61.4 58 15683
## 3 0.41 Ideal G VVS1 62.1 55 1151
## 4 1.54 Premium G VS1 61.1 56 14438
## 5 0.3 Ideal E VS2 61.8 55 795
## 6 0.3 Ideal H VVS2 61.5 56 605
## 7 1.2 Ideal D SI1 61.8 58 7508
## 8 0.58 Ideal E VS2 62.3 54 1809
## 9 0.31 Ideal H VS2 62.6 57 489
## 10 1.24 Very Good F VS1 59 60 9885
## # … with 89 more rows
col_names
-argument. Assign to col_names
a character vector containing the correct column names: carat
, cut
, color
, clarity
, depth
, table
, price
.# read diamonds data with specified col_names
diamonds <- read_csv(file = "XX",
col_names = c('name_1','name_2','...')) # Vector of column names
# read diamonds data with specified col_names
diamonds <- read_csv(file = diamonds_path,
col_names = c("carat", "cut", "color", "clarity", "depth", "table", "price"))
# print diamonds
diamonds
## # A tibble: 100 x 7
## carat cut color clarity depth table price
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 0.8 Very Good H VVS1 62.9 58 4468
## 2 0.74 Ideal H IF 60.9 57 3760
## 3 2.03 Premium I SI1 61.4 58 15683
## 4 0.41 Ideal G VVS1 62.1 55 1151
## 5 1.54 Premium G VS1 61.1 56 14438
## 6 0.3 Ideal E VS2 61.8 55 795
## 7 0.3 Ideal H VVS2 61.5 56 605
## 8 1.2 Ideal D SI1 61.8 58 7508
## 9 0.58 Ideal E VS2 62.3 54 1809
## 10 0.31 Ideal H VS2 62.6 57 489
## # … with 90 more rows
Now pay attention to the classes of the individuals columns (variables). Have all classes been identified correctly? What about the carat
column? It should be numeric
, right?
Let’s see what went wrong. Select and print the carat
variable to identify the one entry that caused the variable to become a character
vector (Hint: look for a comma between entry 10 and 20).
# print the carat column
diamonds$carat
## [1] "0.8" "0.74" "2.03" "0.41" "1.54" "0.3" "0.3" "1.2" "0.58" "0.31"
## [11] "1.24" "0.91" "1.28" "0.31" "1.02" "1" "0,37" "0.55" "0.54" "0.34"
## [21] "0.91" "0.9" "0.5" "0.31" "1.66" "0.47" "0.3" "0.7" "1.72" "0.41"
## [31] "1.06" "0.32" "0.4" "0.71" "0.3" "1.31" "1.08" "0.45" "0.3" "0.62"
## [41] "1.01" "2" "0.38" "2.03" "1" "0.38" "0.41" "0.49" "0.71" "1.51"
## [51] "1.02" "1.3" "0.32" "1.52" "0.59" "1.31" "1.05" "1.08" "0.43" "1.08"
## [61] "0.3" "0.4" "0.52" "0.41" "1" "0.33" "0.75" "0.26" "0.34" "1.49"
## [71] "0.3" "0.4" "0.71" "0.92" "0.7" "0.55" "1.47" "0.42" "0.58" "0.44"
## [81] "0.31" "0.3" "0.55" "0.41" "0.31" "0.33" "0.32" "2.67" "0.88" "0.57"
## [91] "0.36" "0.53" "0.79" "0.9" "0.31" "1.03" "0.39" "0.51" "0.34" "0.25"
carat
by replacing XX
with the index of the incorrect value (i.e., the correct number between 10 and 20) and YY
with the correct entry with a period (.
) instead of a comma (,
) in the code below.# Change the value at position XX to YY
diamonds$carat[XX] <- YY
# Change the value at position XX to YY
diamonds$carat[17] <- 0.37
carat
is still character
. We can fix it with the type_convert()
function. Apply the type_convert()
function to the diamonds
data to have R fix all the data types. Make sure to assign the result back to diamonds
so that you change the object!# re-infer data types
diamonds <- type_convert(diamonds)
diamonds
object and look at the column types. Has the type of carat
changed to double
?# print diamonds data set
diamonds
## # A tibble: 100 x 7
## carat cut color clarity depth table price
## <dbl> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 0.8 Very Good H VVS1 62.9 58 4468
## 2 0.74 Ideal H IF 60.9 57 3760
## 3 2.03 Premium I SI1 61.4 58 15683
## 4 0.41 Ideal G VVS1 62.1 55 1151
## 5 1.54 Premium G VS1 61.1 56 14438
## 6 0.3 Ideal E VS2 61.8 55 795
## 7 0.3 Ideal H VVS2 61.5 56 605
## 8 1.2 Ideal D SI1 61.8 58 7508
## 9 0.580 Ideal E VS2 62.3 54 1809
## 10 0.31 Ideal H VS2 62.6 57 489
## # … with 90 more rows
.csv
file using the name diamonds_clean.csv
. Don’t forget to include both the file name and the folder (separated by /
) in the character string specifying the path
argument.# write clean diamonds data to disc
write_csv(x = XX, path = "XX")
# write clean diamonds data to disc
write_csv(x = diamonds, "1_Data/diamonds_clean.csv")
diamonds_clean.csv
back into R as a new object called diamonds_clean
. Then, print the object and verify that this time the types been correctly identified from the start.# read clean diamonds data from disc
diamonds_clean <- read_csv(file = "1_Data/diamonds_clean.csv")
carat
or price
(use mean()
)? What cut
and clarity
levels exist and how often do they occur (use table()
on both variables)? You can learn more about the variable values from the help file ?diamonds
.# simple stats of diamonds
mean(diamonds$carat)
## [1] 0.742
mean(diamonds$price)
## [1] 3543
table(diamonds$cut)
##
## Fair Good Ideal Premium Very Good
## 2 5 46 31 16
table(diamonds$clarity)
##
## I1 IF SI1 SI2 VS1 VS2 VVS1 VVS2
## 1 4 17 19 15 24 10 10
$
TRUE
and FALSE
(and NA
s). Create a new logical vector called expensive
indicating which diamonds are more expensive than $10000. To do this, select the price
variable from the data frame using $
use the >
(greater than) operator á la vector > value
.# Create a logical vector expensive indicating
# which dimaonds cost more than 10,000
ZZ <- diamonds$XX > YY
# Create a logical vector expensive indicating
# which dimaonds cost more than 10,000
expensive <- diamonds$price > 10000
expensive
vector to the console. Do you see only TRUE and FALSE values?  See below?# add vector to data frame
XX$YY <- ZZ
# add vector to data frame
diamonds$expensive <- expensive
table()
function, create a table showing how many of the diamonds are expensive how many are not. Select the variable directly from the data frame using $
.# count expensive diamonds
table(diamonds$expensive)
##
## FALSE TRUE
## 92 8
mean()
function, determine the percentage of the diamonds that are expensive, i.e., mean(expensive)
. Should this have worked?# percentage of expensive diamonds
mean(diamonds$expensive)
## [1] 0.08
carat
(i.e., more than .2 gram)?# percentage of diamonds heavier than 1 carat
mean(diamonds$carat > 1)
## [1] 0.26
read_excel()
, read in the titanic.xls
dataset as a new object called titanic
(Make sure you have alredy loaded the readxl
package at the beginning of your script).titanic <- read_excel(path = "XX")
# Read titanic data
titanic <- read_excel("1_Data/titanic.xls")
titanic
and evaluate its dimensions using dim()
.# print and show dimenisons
titanic
## # A tibble: 1,309 x 14
## pclass survived name sex age sibsp parch ticket fare cabin embarked
## <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr> <chr>
## 1 1 1 Alle… fema… 29 0 0 24160 211. B5 S
## 2 1 1 Alli… male 0.917 1 2 113781 152. C22 … S
## 3 1 0 Alli… fema… 2 1 2 113781 152. C22 … S
## 4 1 0 Alli… male 30 1 2 113781 152. C22 … S
## 5 1 0 Alli… fema… 25 1 2 113781 152. C22 … S
## 6 1 1 Ande… male 48 0 0 19952 26.6 E12 S
## 7 1 1 Andr… fema… 63 1 0 13502 78.0 D7 S
## 8 1 0 Andr… male 39 0 0 112050 0 A36 S
## 9 1 1 Appl… fema… 53 2 0 11769 51.5 C101 S
## 10 1 0 Arta… male 71 0 0 PC 17… 49.5 <NA> C
## # … with 1,299 more rows, and 3 more variables: boat <chr>, body <dbl>,
## # home.dest <chr>
dim(titanic)
## [1] 1309 14
table()
, how many people survived (variable survived
) in each cabin class (variable pclass
)?# determine survival rate by cabin class
table(titanic$XX,
titanic$XX)
# determine survival rate by cabin class
table(titanic$pclass, titanic$survived)
##
## 0 1
## 1 123 200
## 2 158 119
## 3 528 181
write_csv()
, write the titanic
dataframe as a new comma separated text file called titanic.csv
in your 1_Data
folder. Now you have the data saved as a text file any software can use!# write data to .csv
write_csv(x = titanic,
path = "1_Data/titanic.csv")
read_spss()
read in the sleep data set sleep.sav
of staff at he University of Melbourne as a new object called sleep
. (Make sure that you have first loaded the haven
package).XX <- read_spss(file = "XX")
# Read sleep data
sleep <- read_spss(file = "1_Data/sleep.sav")
sleep
object and evaluate its dimensions using dim()
.# print and show dimensions
sleep
## # A tibble: 271 x 55
## id sex age marital edlevel weight height healthrate fitrate
## <dbl> <dbl+l> <dbl> <dbl+l> <dbl+l> <dbl> <dbl> <dbl+lbl> <dbl+l>
## 1 83 0 [fem… 42 2 [mar… 2 [sec… 52 162 10 [very … 7
## 2 294 0 [fem… 54 2 [mar… 5 [pos… 65 174 8 7
## 3 425 1 [mal… NA 2 [mar… 2 [sec… 89 170 6 5
## 4 64 0 [fem… 41 2 [mar… 5 [pos… 66 178 9 7
## 5 536 0 [fem… 39 2 [mar… 5 [pos… 62 160 9 5
## 6 57 0 [fem… 66 2 [mar… 4 [und… 62 165 8 8
## 7 251 0 [fem… 36 1 [sin… 3 [tra… 62 165 9 7
## 8 255 0 [fem… 35 2 [mar… 5 [pos… 75 174 6 6
## 9 265 1 [mal… NA 2 [mar… 5 [pos… 90 180 6 6
## 10 290 1 [mal… 41 2 [mar… 5 [pos… 75 187 9 9
## # … with 261 more rows, and 46 more variables: weightrate <dbl+lbl>,
## # smoke <dbl+lbl>, smokenum <dbl>, alchohol <dbl>, caffeine <dbl>,
## # hourwnit <dbl>, hourwend <dbl>, hourneed <dbl>, trubslep <dbl+lbl>,
## # trubstay <dbl+lbl>, wakenite <dbl+lbl>, niteshft <dbl+lbl>,
## # liteslp <dbl+lbl>, refreshd <dbl+lbl>, satsleep <dbl+lbl>,
## # qualslp <dbl+lbl>, stressmo <dbl+lbl>, medhelp <dbl+lbl>,
## # problem <dbl+lbl>, impact1 <dbl+lbl>, impact2 <dbl+lbl>, impact3 <dbl+lbl>,
## # impact4 <dbl+lbl>, impact5 <dbl+lbl>, impact6 <dbl+lbl>, impact7 <dbl+lbl>,
## # stopb <dbl+lbl>, restlss <dbl+lbl>, drvsleep <dbl+lbl>, drvresul <dbl+lbl>,
## # ess <dbl>, anxiety <dbl>, depress <dbl>, fatigue <dbl>, lethargy <dbl>,
## # tired <dbl>, sleepy <dbl>, energy <dbl>, stayslprec <dbl+lbl>,
## # getsleprec <dbl+lbl>, qualsleeprec <dbl+lbl>, totsas <dbl>,
## # cigsgp3 <dbl+lbl>, agegp3 <dbl+lbl>, probsleeprec <dbl+lbl>,
## # drvslprec <dbl+lbl>
dim(sleep)
## [1] 271 55
alcohol
). To do this, use the mean()
function, while taking care of missing values using the na.rm
argument.# compute mean number of drinks
mean(x = sleep, na.rm = TRUE)
## [1] NA
write_csv()
function, write the sleep
data to a new file called sleep.csv
in your 1_Data
folder. Now you have the sleep
data stored as a text file any software can use!# write data to .csv
write_csv(x = sleep,
path = "1_Data/sleep.csv")
read_sas()
, read in airbnb_zuerich.sas7bdat
containing AirBnB listings in Zürich, Switzerland and call the object airbnb_zuerich
.# read sas data
XX <- read_sas(data_file = "XX")
# read airbnb_zuerich.sas7bdat
airbnb_zuerich <- read_sas(data_file = "1_Data/airbnb_zuerich.sas7bdat")
airbnb_zuerich
and then evaluate its dimensions using dim()
.# print and show dimenisons
airbnb_zuerich
## # A tibble: 2,392 x 20
## room_id survey_id host_id room_type country city borough neighborhood
## <dbl> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr>
## 1 1.37e7 1363 5.63e7 Entire h… "" Zuri… "" Kreis 12
## 2 8.00e6 1363 1.65e7 Entire h… "" Zuri… "" Kreis 7
## 3 1.52e7 1363 5.03e7 Entire h… "" Zuri… "" Kreis 4
## 4 7.56e6 1363 4.92e6 Entire h… "" Zuri… "" Kreis 1
## 5 1.86e7 1363 2.04e7 Entire h… "" Zuri… "" Kreis 12
## 6 6.44e6 1363 1.24e7 Entire h… "" Zuri… "" Kreis 2
## 7 1.88e6 1363 1.60e6 Entire h… "" Zuri… "" Kreis 7
## 8 3.63e6 1363 1.83e7 Entire h… "" Zuri… "" Kreis 8
## 9 1.44e7 1363 5.19e7 Entire h… "" Zuri… "" Kreis 2
## 10 1.28e7 1363 2.64e5 Entire h… "" Zuri… "" Kreis 2
## # … with 2,382 more rows, and 12 more variables: reviews <dbl>,
## # overall_satisfaction <dbl>, accommodates <dbl>, bedrooms <dbl>,
## # bathrooms <chr>, price <dbl>, minstay <chr>, name <chr>,
## # last_modified <dttm>, latitude <dbl>, longitude <dbl>, location <chr>
dim(airbnb_zuerich)
## [1] 2392 20
room_type
in Zürich? (Hint: use table()
)# table room type
table(airbnb_zuerich$room_type)
##
## Entire home/apt Private room Shared room
## 1386 975 31
write_csv()
write your airbnb_zuerich
data frame to as new comma-separated text file called airbnb_zuerich.csv
in your 1_Data
folder.# write data to .csv
write_csv(x = airbnb_zuerich,
path = "1_Data/airbnb_zuerich.csv")
data.frame()
function, create a data frame called ten_df
that contains each of the vectors you just created: id
, age
, sex
, height
, weight
.# Create data frame ten_df containing vectors id, age, sex, height, and weight.
XX <- data.frame(XX, XX, XX, XX, XX, XX)
# Create ten_df data frame from vectors
ten_df <- data.frame(id, age, sex, height, weight)
ten_df
object to see how it looks! Does it contain all of the vectors?# Print ten_df
ten_df
## id age sex height weight
## 1 1 44 male 174 113.4
## 2 2 65 male 180 75.2
## 3 3 31 female 168 55.5
## 4 4 27 male 209 93.8
## 5 5 24 male 177 NA
## 6 6 63 male 187 67.4
## 7 7 71 male 152 83.3
## 8 8 41 female 156 67.8
## 9 9 43 male 176 69.3
## 10 10 31 female 166 66.3
dim()
function, print the number of rows and columns in your data frame. Do you get 10 rows and 5 columns?# Inspect dimensions
dim(ten_df)
## [1] 10 5
ten_df
object? Use the class()
function to find out!# Inspect class
class(ten_df)
## [1] "data.frame"
summary()
function to print descriptive statistics from each column of ten_df
# Inspect class
summary(ten_df)
## id age sex height
## Min. : 1.00 Min. :24.0 Length:10 Min. :152
## 1st Qu.: 3.25 1st Qu.:31.0 Class :character 1st Qu.:167
## Median : 5.50 Median :42.0 Mode :character Median :175
## Mean : 5.50 Mean :44.0 Mean :174
## 3rd Qu.: 7.75 3rd Qu.:58.2 3rd Qu.:179
## Max. :10.00 Max. :71.0 Max. :209
##
## weight
## Min. : 55.5
## 1st Qu.: 67.4
## Median : 69.3
## Mean : 76.9
## 3rd Qu.: 83.3
## Max. :113.4
## NA's :1
$
operator, print the age
column from the ten_df
data frame.# Inspect age
ten_df$age
## [1] 44 65 31 27 24 63 71 41 43 31
age
value from the ten_df
data frame using max()
. Do you get the same result from when you calculated it from the original vector age
?# Get max
max(ten_df$age)
## [1] 71
data.frame()
function, try creating a tibble called ten_tibble
using the tibble()
function. tibble
s are a more modern, leaner variant of data frame that we prefer over classic data.frame
. You can use the exact same arguments you used before.# create tibble
ten_tibble = tibble(id, age, sex, height, weight)
ten_tibble
object, how does it look different from ten_df
? Try calculating the maximum age
from this object. Is it different from what you got before?# print tibble
ten_tibble
## # A tibble: 10 x 5
## id age sex height weight
## <int> <dbl> <chr> <dbl> <dbl>
## 1 1 44 male 174. 113.
## 2 2 65 male 180. 75.2
## 3 3 31 female 168. 55.5
## 4 4 27 male 209 93.8
## 5 5 24 male 177. NA
## 6 6 63 male 187. 67.4
## 7 7 71 male 152. 83.3
## 8 8 41 female 156. 67.8
## 9 9 43 male 176. 69.3
## 10 10 31 female 166. 66.3
max(ten_tibble$age) == max(ten_df$age)
## [1] TRUE
sum()
of a logical vector, R will return the number of cases that are TRUE
. Using this, find out how many of the ten Baselers are male while using the is-equal-to operator ==
.# Determine the frequency of a case in a vector
sum(XX == XX)
# Determine the frequency of a case in a vector
sum(ten_tibble$sex == "male")
## [1] 7
# Create a logical vector indicating which baselers are younger than 30
young_30 <- XX$XX < 30
# Print the ids of baselers younger than 30
XX$XX[young_30]
# Create a logical vector indicating which baselers are younger than 30
young_30 <- ten_tibble$age < 30
# Print the ids of baselers younger than 30
ten_tibble$id[young_30]
## [1] 4 5
mean()
function to answer the question: “What is the mean age of Baselers who are heavier than 80kg?”# Mean age of baselers heavier than 80kg
mean(ten_tibble$age[ten_tibble$weight > 80])
## [1] NA
&
to combine multiple logical vectors)# Mean age of baselers heavier than 80kg
ten_tibble$id[ten_tibble$sex == "male" & ten_tibble$height < 165]
## [1] 7
library(tidyverse)
library(readr)
library(readxl)
library(haven)
# Create vectors of (fake) stock data
name <- c("apple", "microsoft", "dell", "google", "twitter")
yesterday <- c(100, 89, 65, 54, 89)
today <- c(102, 85, 72, 60, 95)
# Summary statistics
mean(today)
mean(yesterday)
# Show classes
class(name)
class(yesterday)
# Operations of vectors
change <- today - yesterday
change # Print result
# Create a logical vector from two numerics
increase <- today > yesterday
increase # Print result
# Create a tibble combining multiple vectors
stocks <- tibble(name, yesterday, today, change, increase)
# Get column names
names(stocks)
# Access columns by name
stocks$name
stocks$today
# Calculate descriptives on columns
mean(stocks$yesterday)
median(stocks$today)
table(stocks$increase)
max(stocks$increase)
# read/write delim-separated -------------------
# read chickens data
chickens <- read_csv(file = "1_Data/chickens.csv")
# fix header of chickens_nohead.csv with known column names
chickens <- read_csv(file = "1_Data/chickens_nohead.csv",
col_names = c("weight", "time", "chick", "diet"))
# fix NA values of chickens_na.csv
chickens <- read_csv(file = "1_Data/chickens_na.csv",
na = c('NA', 'NULL'))
# write clean data to disc
write_csv(x = chickens,
path = "1_Data/chickens_clean.csv")
# fix types -------------------
# Note: the survey data is fictional!
# remove character from rating
survey$rating[survey$rating == "2,1"] <- 2.1
# rerun type convert
survey <- type_convert(survey)
# other formats -------------------
# .xlsx (Excel)
chickens <- read_excel("1_Data/chickens.xlsx")
# .sav (SPSS)
chickens <- read_spss("1_Data/chickens.sav")
# .sad7bdata (SAS)
chickens <- read_sas("1_Data/chickens.sas7bdat")
library(tidyverse)
library(haven)
| File | Rows | Columns | Description |
|---|---|---|---|
| diamonds.csv | 100 | 7 | Subset of the well-known diamonds data set containing specifications and prices of a large number of recorded diamonds. |
| titanic.xls | 1309 | 14 | Information on the survival of titanic passengers. |
| sleep.sav | 271 | 55 | Survey on sleeping behavior completed by staff at the University of Melbourne. |
| airbnb_zuerich.sas7bdat | 2392 | 20 | Data on AirBnB listings in Zürich, Switzerland |
| Package | Installation |
|---|---|
tidyverse |
install.packages("tidyverse") |
readr |
install.packages("readr") |
haven |
install.packages("haven") |
readxl |
install.packages("readxl") |
Creating vectors
| Function | Description |
|---|---|
c("a", "b", "c") |
Create a character vector |
c(1, 2, 3) |
Create a numeric vector |
c(TRUE, FALSE, TRUE) |
Create a logical vector |
Vector functions
| Function | Description |
|---|---|
mean(x), median(x), sd(x), sum(x) |
Mean, median standard deviation, sum |
max(x), min(x) |
Maximum, minimum |
table(x) |
Table of frequency counts |
round(x, digits) |
Round a numeric vector x to digits |
Accessing vectors from data frames
| Function | Description |
|---|---|
df$name |
Access vector name from a data frame df |
Reading/writing text data
| Extension | File Type | Read | Write |
|---|---|---|---|
.csv |
Comma-separated text | read_csv(file) |
write_csv(x, file) |
.csv |
Semi-colon separated text | read_csv2(file) |
not available |
.txt |
Other text | read_delim(file) |
write_delim(x, file) |
Reading/writing other data formats
| Extension | File Type | Read | Write |
|---|---|---|---|
.xls , .xlsx |
Excel | read_excel(file) |
xlsx::write.xlsx() |
.sav |
SPSS | read_spss(file) |
write_spss(x, file) |
.sas7bdat |
SAS | read_sas(file) |
write_sas(x, file) |
Creating data frames from vectors
| Function | Description |
|---|---|
data.frame(a, b, c) |
Create a data frame from vectors a, b, c |
tibble(a, b, c) |
Create a tibble from vectors a, b, c |


ViewRoutes
AddRoute
UpdateRoute
routeName
routeZoneId
routeStatus
routeName
routeZoneId
routeStatus
AddRoute
routeName
routeZoneId
routeStatus
UpdateRoute


Show modal with close on x
Show modal with close on overlay
Show modal with close on escape
Show modal with close on escape, overlay, or x
Show a custom modal.


A Home Changes Everything!
Buying or selling a home is very stressful. We, at VM Home understand that, and help guide you throughout the process and make it the most joyous experience for you. We are from the peninsula and understand all of the important factors that come into play. Neighbourhood, schools, parks, public transportation and more.
We can recommend trustworthy contractors (carpentry, plumbing, electrical, mechanical, landscape, inspection, handyman) and mortgage lenders. You will love working with us!
137 Stanley Rd BURLINGAME
Buyer's Representative
Michelle Green and Vidya Mahalaxmi
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34618 Pueblo Ter, Fremont
Buyer's Representative
Michelle Green and Vidya Mahalaxmi
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1917 Vista Cay, San Mateo
Buyer's Representative
Michelle Green and Vidya Mahalaxmi
Bought on Dec 2019
721, 3rd Ave, Redwood City.
Seller's Representative :: Michelle Green
Sold on Oct 2019
721, 3rd Ave, Redwood City.
Buyer's Representative :: Vidya Mahalaxmi
Bought on Oct 2019


Objective
Research Assistant
Experience
Immigrations Co., Immigrations Website (2016 - Present)
- Build an immigrations guide for work permits
- Wrote documents on how to get employment visas in other countries
Skills
- English as a Second Language (ESL)
- Knowledge in handling a Recording studio.
- Knowledgeable in:
- Adobe Photoshop
- Adobe Premiere
- Adobe After effects
- MangaStudio
- Microsoft Word
- Microsoft Excel
- Microsoft Publisher
Education
Tertiary
BS, Information Technology, University of the Cordilleras
Secondary
University of Baguio Science High School
Primary
Small World Christian School Foundation


Spanish voter turnout at 38% at 2 p.m., down from April election
MADRID (Reuters) - Turnout in Spain’s repeat parliamentary election stood at 37.9% at 2 p.m. (1300 GMT) on Sunday, according to the interior ministry, a drop from the 41.5% recorded at the same time during the previous election in April.
(This story corrects turnout to 37.9% from 38.8% to reflect updated data)


Same issue, weapons page doesn't show hits or percentage. BBLOG 3.6.0 and Firefox 23.0.1. Just a couple of days ago, worked perfectly.
http://i.imgur.com/wKjGWk3.png
Amkhatar
Theme Developer
Hi...i had the same issue few days ago... but today it's working...sometimes top% disappears and appears with reloading page (ctrl + f5)
dev release<PHONE_NUMBER>
Chrome 29.0.1547.66 m
Post edited 2 x times, last by
rickdekkard
rickdekkard
Yes now is working again... but fails other times.
EDIT. Seem to work when "cem_ea_id/" appears at the end of url.
Post edited 3 x times, last by
BrainFooLong
Administrator
BrainFooLong
Administrator
If "top%" fails randomly, than it's maybe because bf3stats.com have some temporarily problems.
If this fails everytime than it's a BBLog bug.
For me it has nothing todo with the URL, it works with cem_ea_id/ or pc/ or anything else at the end of the url.
EDIT: Found it, when the soldier number is the last section in the URL (without pc/ or cem_ea_id/) than it not works, but currently i can't find a url on battlelog that link to that "broken" page? Anyone has an idea?
EDIT2: Forget it, found the way to get this url. When you goto a profile page from a friend, than to the soldier page from that and than switch the tab to weapons. Than it has this url.


My name is Binila.I am from Amal Jyothi college of engineering. My hobbies are doing coding and it is my passion.


La Caixa Bank Avenida España Centro 25, 28004 Madrid, Spain. My Dear Friend, Permit me to introduce myself, my name is Dennis Platt.I work with La Caixa Bank of Madrid, Spain as(Senior Accountant),in the discharge of my duty, I stumbled on this domiciliary account that has remained dormant for three years now with US$9m (Nine million dollars) on it with account name Mr. John Isaac. I contacted my director and we sent out staff for enquiries and discovered that the account holder died in an accident. I am writing you so that we can work together to remit the money to you as the next of kin because this money belong to a foreigner and has to be claimed by a foreigner.I guarantee this transaction under a legitimate arrangement that will not breach the law by both parties, it is simple process which will take a short while to process.  Please Reply me on this<EMAIL_ADDRESS><EMAIL_ADDRESS>Best Regards, Dr.Dennis Platt.


Mitr is a Thai word that means “friend” in Thai. Mitr is a sans serif Latin and loopless Thai typeface that combines senses of organic and humanist sans serif designs with rounded terminals. It has a wide structure and airy negative space that preserves legibility and readability. Mitr is a novel and friendly typeface that is suitable for casual usage such as celebration cards, magazines, and posters.
A similarity between some glyphs such as ก ถ ภ ฤ ฦ, ฎ ฏ, บ ป, or ข ช is something to take into consideration because it might lead to confusion when typesetting very short texts. Mitr has a specific approach to the thick and thin strokes of Thai glyphs. Other type designers may consider this font as an example when developing new fonts. Informal looped Thai typefaces have slightly simplified details, as compared to formal ones, and this allows type designers to extend them to heavier weights. The size and position of Thai vowel and tone marks have been managed carefully because they are all relevant to readability, legibility, and overall texture.
The Mitr project is led by Cadson Demak, a type foundry in Thailand. To contribute, see github.com/cadsondemak/mitr


Specifies the message (payload) as published to the SNS topic. This can
be set (or overridden) in individual job configurations.
Build variables can be used and are resolved before message is sent.
Additional variables include:
$BUILD_PHASE ("STARTED", "COMPLETED", etc)
$BUILD_ARTIFACT_PATHS (new-line separated list of artifact paths)


from san francisco | boston college graduate | degree in english literature and composition | enjoys traveling, playing soccer, and building awesome websites
website design
html | css | javascript
interfaces that are user friendly
my sites work on screens of all sizes
interested in starting your next project with me? that's great! use the below form to send me a message and i will get back to you as soon as possible.


This demonstrator shows how Fortune's Algorithm can be used to construct a Voronoi diagram from a set of points. To start the demonstration, either add points to the plane below and press "Start Algorithm", or try one of the demo diagrams with the buttons above. The algorithm will start with the sweep line at the very top and handle all events sequentially on its way down. The red points on the plane represent circle events that are also handled by the sweep line to check for possible Voronoi edges.


- WhiteCandle - Class in in.kncsolutions.dhelm.candlebasic
-
According to literature a white candle is made of white body, i.e closing
price is higher than the opening price.The upper and lower shadows are required.
- WhiteCandle(List<Double>, List<Double>, List<Double>, List<Double>, int, int, double) - Constructor for class in.kncsolutions.dhelm.candlebasic.WhiteCandle
-
- WhiteMarubozu - Class in in.kncsolutions.dhelm.candlebasic
-
According to literature a white marubozu candle is made of white body, i.e closing
price is higher than the opening price.There are no upper and lowe shadows.
- WhiteMarubozu(List<Double>, List<Double>, List<Double>, List<Double>) - Constructor for class in.kncsolutions.dhelm.candlebasic.WhiteMarubozu
-
- WhiteSpinningTop - Class in in.kncsolutions.dhelm.candlebasic
-
According to litarature a white spinning top candle is made of white body, i.e closing
price is higher than the opening price.There must be one shadow present.
- WhiteSpinningTop(List<Double>, List<Double>, List<Double>, List<Double>, int, double) - Constructor for class in.kncsolutions.dhelm.candlebasic.WhiteSpinningTop
-


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{% extends 'static_page.html' %} {% load crispy_forms_tags %} {% load spotify_tags %} {% block content %}
We have received your request and will review it shortly.{% if runtime %}
Estimated wait: {{ runtime }} minute{{ runtime|pluralize }}{% endif %}
Powered by: Spotify
{% if complete %}
Note: Lens and Lights reserves the right to decline your request at any time and for any
reason with or without advance notice.
{% endif %}By using this site you agree to
Spotify's Terms of Use as well as LNL's
Privacy Policy.


Macros | |
| #define | PD_LOOP 3 |
| #define | PD_LOOP2 4 |
| #define | SQRT sqrt |
Functions | |
| int | arParamObserv2Ideal (const ARdouble dist_factor[AR_DIST_FACTOR_NUM_MAX], const ARdouble ox, const ARdouble oy, ARdouble *ix, ARdouble *iy, const int dist_function_version) |
| Use lens distortion parameters to convert observed (distorted) window coordinates to idealised (zero-distortion) coordinates. More... | |
| int | arParamIdeal2Observ (const ARdouble dist_factor[AR_DIST_FACTOR_NUM_MAX], const ARdouble ix, const ARdouble iy, ARdouble *ox, ARdouble *oy, const int dist_function_version) |
| Use lens distortion parameters to convert idealised (zero-distortion) window coordinates to observed (distorted) coordinates. More... | |
Macro Definition Documentation
| #define PD_LOOP 3 |
| #define PD_LOOP2 4 |
| #define SQRT sqrt |
Function Documentation
| int arParamIdeal2Observ | ( | const ARdouble | dist_factor[AR_DIST_FACTOR_NUM_MAX], |
| const ARdouble | ix, | ||
| const ARdouble | iy, | ||
| ARdouble * | ox, | ||
| ARdouble * | oy, | ||
| const int | dist_function_version | ||
| ) |
Use lens distortion parameters to convert idealised (zero-distortion) window coordinates to observed (distorted) coordinates.
See function arParamObserv2Ideal() for full discussion.
This function is the output function of the pair. It's inputs are idealised coordinates, e.g. taken from OpenGL. The outputs are the location where in a distorted image where the same point would lie.
- Parameters
-
dist_factor An array of ARdouble values holding the lens distortion parameters. These values are generated as part of the camera calibration process in ARToolKit. The exact number of values from the array used by the function is determined by the distortion function version, but does not exceed AR_DIST_FACTOR_NUM_MAX. ix Input idealised normalised window coordinate x axis value. iy Input idealised normalised window coordinate y axis value. ox Pointer to ARdouble, which on return will hold the observed normalised window coordinate x axis value. oy Pointer to ARdouble, which on return will hold the observed normalised window coordinate y axis value. dist_function_version An integer, in the range [1, AR_DIST_FUNCTION_VERSION_MAX] which determines the algorithm used to interpret the dist_factor values.
See function arParamObserv2Ideal() for full discussion.
- Returns
- 0 in case of function success, or -1 if an error occured. At present the only error possible is an invalid value of dist_function_version.
| int arParamObserv2Ideal | ( | const ARdouble | dist_factor[AR_DIST_FACTOR_NUM_MAX], |
| const ARdouble | ox, | ||
| const ARdouble | oy, | ||
| ARdouble * | ix, | ||
| ARdouble * | iy, | ||
| const int | dist_function_version | ||
| ) |
Use lens distortion parameters to convert observed (distorted) window coordinates to idealised (zero-distortion) coordinates.
This function is used by ARToolKit to convert for the the effects of lens distortion in images which have been acquired from lens-based optical systems. All lenses introduce some amount of lens distortion. ARToolKit includes calibration utilities to measure the centre of distortion and the radial distortion factors in the x and y dimensions. This calibration information is saved as part of the camera parameters.
This function is one of a pair of functions which convert between OBSERVED window coordinates (i.e. the location of a known reference point, as measured in the x-y viewing plane of an image containing lens distortion) and IDEALISED coordinates (i.e. the location of the same reference point as measured in an image containing no radial distortion, e.g. an image rendered using OpenGL's viewing model.)
This function is the input function of the pair. It's inputs are distorted coordinates, e.g. taken from an image acquired from a camera The outputs are the location where in an idealised image (e.g. generated with OpenGL) where the same point would lie.
- Parameters
-
dist_factor An array of ARdouble values holding the lens distortion parameters. These values are generated as part of the camera calibration process in ARToolKit. The exact number of values from the array used by the function is determined by the distortion function version, but does not exceed AR_DIST_FACTOR_NUM_MAX. ix Input observed normalised window coordinate x axis value. iy Input observed normalised window coordinate y axis value. ox Pointer to ARdouble, which on return will hold the idealised normalised window coordinate x axis value. oy Pointer to ARdouble, which on return will hold the idealised normalised window coordinate y axis value. dist_function_version An integer, in the range [1, AR_DIST_FUNCTION_VERSION_MAX] which determines the algorithm used to interpret the dist_factor values.
The values correspond to the following algorithms:
version 1: The original ARToolKit lens model, with a single radial distortion factor, plus center of distortion.
version 2: Improved distortion model, introduced in ARToolKit v4.0. This algorithm adds a quadratic term to the radial distortion factor of the version 1 algorithm.
version 3: Improved distortion model with aspect ratio, introduced in ARToolKit v4.0. The addition of an aspect ratio to the version 2 algorithm allows for non-square pixels, as found e.g. in DV image streams.
version 4: OpenCV-based distortion model, introduced in ARToolKit v4.3. This differs from the standard OpenCV model by the addition of a scale factor, so that input values do not exceed the range [-1.0, 1.0] in either forward or inverse conversions.
- Returns
- 0 in case of function success, or -1 if an error occured. At present the only error possible is an invalid value of dist_function_version.


import {ChronoLocalDate} from<EMAIL_ADDRESS>ChronoLocalDate
Extends:
Direct Subclass:
A date without time-of-day or time-zone in an arbitrary chronology, intended for advanced globalization use cases.
Most applications should declare method signatures, fields and variables as LocalDate, not this interface.
A ChronoLocalDate is the abstract representation of a date where the Chronology, or calendar system, is pluggable. The date is defined in terms of fields expressed by TemporalField, where most common implementations are defined in ChronoField. The chronology defines how the calendar system operates and the meaning of the standard fields.
When to use this interface
The design of the API encourages the use of LocalDate rather than this interface, even in the case where the application needs to deal with multiple calendar systems. The rationale for this is explored in the following documentation.
The primary use case where this interface should be used is where the generic
type parameter C
is fully defined as a specific chronology.
In that case, the assumptions of that chronology are known at development
time and specified in the code.
When the chronology is defined in the generic type parameter as ? or otherwise unknown at development time, the rest of the discussion below applies.
To emphasize the point, declaring a method signature, field or variable as this interface type can initially seem like the sensible way to globalize an application, however it is usually the wrong approach. As such, it should be considered an application-wide architectural decision to choose to use this interface as opposed to LocalDate.
Architectural issues to consider
These are some of the points that must be considered before using this interface throughout an application.
1) Applications using this interface, as opposed to using just LocalDate, face a significantly higher probability of bugs. This is because the calendar system in use is not known at development time. A key cause of bugs is where the developer applies assumptions from their day-to-day knowledge of the ISO calendar system to code that is intended to deal with any arbitrary calendar system. The section below outlines how those assumptions can cause problems The primary mechanism for reducing this increased risk of bugs is a strong code review process. This should also be considered a extra cost in maintenance for the lifetime of the code.
2) This interface does not enforce immutability of implementations. While the implementation notes indicate that all implementations must be immutable there is nothing in the code or type system to enforce this. Any method declared to accept a ChronoLocalDate could therefore be passed a poorly or maliciously written mutable implementation.
3) Applications using this interface must consider the impact of eras.
LocalDate shields users from the concept of eras, by ensuring that getYear()
returns the proleptic year. That decision ensures that developers can think of
LocalDate instances as consisting of three fields - year, month-of-year and day-of-month.
By contrast, users of this interface must think of dates as consisting of four fields -
era, year-of-era, month-of-year and day-of-month. The extra era field is frequently
forgotten, yet it is of vital importance to dates in an arbitrary calendar system.
For example, in the Japanese calendar system, the era represents the reign of an Emperor.
Whenever one reign ends and another starts, the year-of-era is reset to one.
4) The only agreed international standard for passing a date between two systems is the ISO-8601 standard which requires the ISO calendar system. Using this interface throughout the application will inevitably lead to the requirement to pass the date across a network or component boundary, requiring an application specific protocol or format.
5) Long term persistence, such as a database, will almost always only accept dates in the ISO-8601 calendar system (or the related Julian-Gregorian). Passing around dates in other calendar systems increases the complications of interacting with persistence.
6) Most of the time, passing a ChronoLocalDate throughout an application is unnecessary, as discussed in the last section below.
False assumptions causing bugs in multi-calendar system code
As indicated above, there are many issues to consider when try to use and manipulate a date in an arbitrary calendar system. These are some of the key issues.
Code that queries the day-of-month and assumes that the value will never be more than 31 is invalid. Some calendar systems have more than 31 days in some months.
Code that adds 12 months to a date and assumes that a year has been added is invalid. Some calendar systems have a different number of months, such as 13 in the Coptic or Ethiopic.
Code that adds one month to a date and assumes that the month-of-year value will increase by one or wrap to the next year is invalid. Some calendar systems have a variable number of months in a year, such as the Hebrew.
Code that adds one month, then adds a second one month and assumes that the day-of-month will remain close to its original value is invalid. Some calendar systems have a large difference between the length of the longest month and the length of the shortest month. For example, the Coptic or Ethiopic have 12 months of 30 days and 1 month of 5 days.
Code that adds seven days and assumes that a week has been added is invalid. Some calendar systems have weeks of other than seven days, such as the French Revolutionary.
Code that assumes that because the year of date1
is greater than the year of date2
then date1
is after date2
is invalid. This is invalid for all calendar systems
when referring to the year-of-era, and especially untrue of the Japanese calendar system
where the year-of-era restarts with the reign of every new Emperor.
Code that treats month-of-year one and day-of-month one as the start of the year is invalid. Not all calendar systems start the year when the month value is one.
In general, manipulating a date, and even querying a date, is wide open to bugs when the calendar system is unknown at development time. This is why it is essential that code using this interface is subjected to additional code reviews. It is also why an architectural decision to avoid this interface type is usually the correct one.
Using LocalDate instead
The primary alternative to using this interface throughout your application is as follows.
- Declare all method signatures referring to dates in terms of LocalDate.
- Either store the chronology (calendar system) in the user profile or lookup the chronology from the user locale.
- Convert the ISO LocalDate to and from the user's preferred calendar system during printing and parsing.
This approach treats the problem of globalized calendar systems as a localization issue and confines it to the UI layer. This approach is in keeping with other localization issues in the java platform.
As discussed above, performing calculations on a date where the rules of the calendar system are pluggable requires skill and is not recommended.  For example, it is highly unlikely that the business rules of a library book rental scheme will allow rentals to be for one month, where meaning of the month is dependent on the user's preferred calendar system.
A key use case for calculations on a date in an arbitrary calendar system is producing a month-by-month calendar for display and user interaction. Again, this is a UI issue, and use of this interface solely within a few methods of the UI layer may be justified.
In any other part of the system, where a date must be manipulated in a calendar system other than ISO, the use case will generally specify the calendar system to use. For example, an application may need to calculate the next Islamic or Hebrew holiday which may require manipulating the date. This kind of use case can be handled as follows:
- start from the ISO LocalDate being passed to the method
- convert the date to the alternate calendar system, which for this use case is known rather than arbitrary
- perform the calculation
- convert back to LocalDate
Developers writing low-level frameworks or libraries should also avoid this interface. Instead, one of the two general purpose access interfaces should be used. Use TemporalAccessor if read-only access is required, or use Temporal if read-write access is required.
Specification for implementors
This interface must be implemented with care to ensure other classes operate correctly. All implementations that can be instantiated must be final, immutable and thread-safe. Subclasses should be Serializable wherever possible.
Additional calendar systems may be added to the system. See Chronology for more details.
In JDK 8, this is an interface with default methods. Since there are no default methods in JDK 7, an abstract class is used.
Method Summary
| Public Methods | ||
| public |
adjustInto(temporal: *): * |
|
| public |
format(formatter: DateTimeFormatter): String Formats this date using the specified formatter. |
|
| public |
isSupported(fieldOrUnit: *): * |
|
| public |
query(query: *): * |
Inherited Summary
| From class TemporalAccessor | ||
| public |
get(field: TemporalField): number Gets the value of the specified field as an |
|
| public |
getLong(field: *) |
|
| public |
isSupported(field: *) |
|
| public |
query(query: TemporalQuery): * Queries this date-time. |
|
| public |
range(field: TemporalField): ValueRange Gets the range of valid values for the specified field. |
| From class Temporal | ||
| public |
isSupported(fieldOrUnit: TemporalUnit): boolean Checks if the specified unit is supported. |
|
| public |
minus(amount: TemporalAmount | number, unit: TemporalUnit): Temporal function overloading for Temporal.plus |
|
| public |
plus(amount: TemporalAmount | number, unit: TemporalUnit): Temporal function overloading for Temporal.plus |
|
| public |
until(endTemporal: Temporal, unit: TemporalUnit): number Calculates the period between this temporal and another temporal in terms of the specified unit. |
|
| public |
with(adjusterOrField: TemporalAdjuster | TemporalField, newValue: number): Temporal function overloading for Temporal.with |
Public Methods
public format(formatter: DateTimeFormatter): String source
Formats this date using the specified formatter.
This date will be passed to the formatter to produce a string.
The default implementation must behave as follows:
return formatter.format(this);
Params:
| Name | Type | Attribute | Description |
| formatter | DateTimeFormatter | the formatter to use, not null |
Return:
| String | the formatted date string, not null |
Throw:
* |
DateTimeException if an error occurs during printing |
public isSupported(fieldOrUnit: *): * source
Checks if the specified unit is supported. This checks if the date-time can be queried for the specified unit. If false, then calling the plus and minus methods will throw an exception.
Specification for implementors
Implementations must check and handle all fields defined in ChronoUnit. If the field is supported, then true is returned, otherwise false
If the field is not a ChronoUnit, then the result of this method is obtained by invoking TemporalUnit.isSupportedBy(Temporal)
passing this as the argument.
Implementations must not alter this object.
Override:
Temporal#isSupportedParams:
| Name | Type | Attribute | Description |
| fieldOrUnit | * |
Return:
| * |
public query(query: *): * source
Queries this date-time.
This queries this date-time using the specified query strategy object.
Queries are a key tool for extracting information from date-times. They exists to externalize the process of querying, permitting different approaches, as per the strategy design pattern. Examples might be a query that checks if the date is the day before February 29th in a leap year, or calculates the number of days to your next birthday.
The most common query implementations are method references, such as LocalDate::from and ZoneId::from. Further implementations are on TemporalQueries. Queries may also be defined by applications.
Override:
TemporalAccessor#queryParams:
| Name | Type | Attribute | Description |
| query | * |
Return:
| * |


Termux is an Android terminal emulator and Linux environment app that works directly with no rooting or setup required. A minimal base system is installed automatically - additional packages are available using the APT package manager.
Secure. Access remote servers using the ssh client from OpenSSH. Termux combines standard packages with accurate terminal emulation in a beautiful open source solution.
Feature packed. Take your pick between Bash, fish or Zsh and nano, Emacs or Vim. Grep through your SMS inbox. Access API endpoints with curl and use rsync to store backups of your contact list on a remote server.
Customizable. Install what you want through the APT package management system known from Debian and Ubuntu GNU/Linux. Why not start with installing Git and syncing your dotfiles?
Explorable. Have you ever sat on a bus and wondered exactly which arguments tar accepts? Packages available in Termux are the same as those on Mac and Linux - install man pages on your phone and read them in one session while experimenting with them in another.
With batteries included. Can you imagine a more powerful yet elegant pocket calculator than a readline-powered Python console? Up-to-date versions of Perl, Python, Ruby and Node.js are all available.
Ready to scale up. Connect a Bluetooth keyboard and hook up your device to an external display if you need to - Termux supports keyboard shortcuts and has full mouse support.
Tinkerable. Develop by compiling Go, Rust, Swift, or C files with Clang and build your own projects with CMake and pkg-config. Both lldb/GDB and strace are available if you get stuck and need to debug.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 2
Dietary
Preheat the oven to 220C/425F/Gas 7.
Place the milk, vanilla pod, lemon zest and half of the sugar into a pan over a medium heat and bring to near boiling, then remove from the heat.
In a separate pan, melt the butter, then add the flour and stir to combine.
Strain the hot milk mixture then gradually add to the butter and flour mixture, stirring constantly, until thickened.
Meanwhile, using an electric whisk, beat the lemon juice and egg yolks together in a bowl, until very pale and fluffy, about 3-5 minutes.
Add the hot milk mixture and whisk well to combine as a smooth custard.
In a separate bowl, whisk together the whites and other half of the sugar, until stiff peaks form when the whisk is removed.
Fold a spoonful of the egg white mixture into the custard mixture, then gently fold in the remaining egg whites, until just combined.
Grease two ramekins with butter and sprinkle them with a little sugar to coat the insides.
Pour the soufflé mixture into both ramekins so that it comes almost to the top.
Run your thumb, or the handle of a teaspoon, around the edge to make a small indentation (this will help the soufflé to rise).
Place the ramekins onto a baking sheet and place into the oven to bake for 10-12 minutes, or until risen and light golden-brown.
For the sauce, place the sugar, rosewater, water and wine into a pan over a medium heat and bring to the boil. Reduce the heat and simmer for five minutes, or until thickened.
Add the raspberries and stir for one minute.
Blend the sauce with a hand-held blender then pass the sauce through a sieve.
Remove the souffés from the oven and place onto plates. Use a spoon to cut out a small hole in the top of each soufflé and pour in some of the raspberry sauce. Serve immediately.


Supplychain Tracking System
Secure Your Supplychain on Blockchain.
Owner: 0x39f60091825b96eddaA30C24A0e0bFa1A86f864c
Manufacturer: 0x6aF0Bc20D6Dc7ac5ecA4Ef96EfD08E19C7AcF91B
StockHolder:0xA9fD2B85207824bc994578585F0f739B51EE5256
Wholesaler:0x5143321B96121665E1C71D79a46b96DE0D388B61
Retailer:0xCb2d9A078bEd248D225EF3fCa8a717157A40158d
Customer:0xDa65aE48E1Ed31FaBDD786Da6Cf207c2E3bDA337
Create Asset:
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Track Asset Details:
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User
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Generous Portions: Bangkok ‘waitresses’ fined for very impractical uniforms (Video)
by Coconuts BangkokServers wearing nothing but bikini bottoms and an apron is apparently where Thailand draws the line when it comes to women’s attire.
Four promotional models or pretties were each fined THB2,000 (US$66) last night for wearing too little at a gig in Bangkok’s Bueng Kum district.
The four models, all between 24 and 34, were summoned to the local police station yesterday where they explained that they collectively received THB10,000 for serving tables 9pm to 11pm, according to multiple media reports. Before donning their skimpy outfits, they reportedly prepared backless bras to make sure they don’t accidentally flash anyone. The women said the outfits may have looked more inappropriate than they intended due to the sheer size of their actively moving breasts.
The curvaceous quartet gained attention when videos of them in their minimal uniforms went all over social media this past weekend. In the videos, the four models can be seen wearing nothing but hot pants or bikini bottoms under bright aprons. A large surface area of quite large breasts went uncovered by the aprons, which seemed barely able to hold them in. All four pretties readily said they were surgically augmented.
The four women and the restaurant’s owner were fined THB2,000 for public indecency.
Related:
Man who took dead model to his room arrested on sexual assault charges: police
Pretty Girls Taking Risks: Inside the world of Thailand’s models for hire


<while condition="expression" index="index_var_name" maxloops="max_loops"> body </while>
| Name | Required | Default | Description |
|---|---|---|---|
| condition | yes | Expression that is evaluated for every loop and if its value is true, the body is executed. | |
| index | no | Name of the index variable, initial value for the first loop is 1. | |
| maxloops | no | Limits number of iterations. There is no limit if it is not specified. |
See example from function processor.


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header
Kizito Akwotiga
Computer Enginering Student
<EMAIL_ADDRESS>I am Kizito Akwotiga, a second year computer engineering student at City University of New
York-QCC,
very much interested in software development and looking forward to bulding things for the web.
I find electrical circuits satisfying which led me to pursueing a degree in Engineering.
This is my very first portfolio and hopefully it will get better before SPS comes to an end.
I have worked with a group of software developers to create an E-Commerce website. As a
participant,
I sole handedly worked on the GUI of the login page and loved the outcome. You may visit the repository and leave any feed back.
You may connect with me on professional/social media:
github
LinkedIn
Instagram
The heart of Africa lies in it's people and it's wild life.
As this portfolio gets better, I will dedicate this space for the stories of the wild.
footer


Tic Tac Toe
Grid
3x3
4x4
5x5
6x6
7x7
8x8
9x9
10x10
11x11
12x12
13x13
14x14
15x15
16x16
Winner:
Player 1
0
Computer
0


Caixabank inks deal with Salesforce to bring CRM to digital banking
by Ruby HinchliffeSpain’s CaixaBank has signed an agreement with Salesforce to develop innovation projects which fuse customer relationship management (CRM) with the digital transformation phase taking hold of banking.
The two announced their partnership in San Francisco at Salesforce’s Dreamforce event, where CaixaBank’s digital business executive president Jordi Nicolau, and chief information officer (CIO) Pere Nebot, met co-CEO of Salesforce Keith Block, to finalise the plan.
As part of CaixaBank’s 2019-2020 strategic plan, employees will be able to use these co-developed CRM tools to respond to the bank’s customers. Salesforce will also become a member of the ‘la Caixa’ banking foundation which helps people struggling to integrate in the labour market.
Similarly, the agreement reads that CaixaBank – now holding 15.6 million customers – will be included in Salesforce’s international research and development (R&D) programme for financial services, which compromises of “a small group of banks experimenting with new ways of approaching customers”.
Read next: CaixaBank opens “urban oasis” for Barcelona customers


curl_free - reclaim memory that has been obtained through a libcurl call
#include <curl/curl.h> void *curl_free( char *ptr );
curl_free reclaims memory that has been obtained through a libcurl call. Use curl_free() instead of free() to avoid anomalies that can result from differences in memory man- agement between your application and libcurl.
curl_unescape(), curl_free()


Rum is any distilled spirit created from sugarcane. The vast majority of rums are produced from molasses, the by-product of refining sugarcane into raw sugar. The minority, principally Brazilian cachaça and French rhum agricole, are produced from the juice of sugarcane after it’s pressed. Molasses can be used to make light, soft rums (as Cuba and Puerto Rico are known for) or dark, pungent rums ( Jamaica’s reputation was made by this style), as well as everything in between.
The variables that can differentiate one style from another include such obvious matters as the time in oak and the type of oak (or other woods, in the case of Brazilian cachaça), whether pot stills or continuous stills are employed, whether flavors or spices are added, and perhaps less obviously, whether molasses, cane syrup or the freshly extracted juice of the cane is used to create a fermentation.
Techniques and styles vary not only from country to country, but often within countries. Jamaica is known for dark and heavy rums. But in fact, the most popular rum in Jamaica is a white rum with a high proof, 126 degrees, called Wray & Nephew.
In the rundown that follows, you’ll note that the decision to use molasses, cane juice or syrup might be the most important factor in the style of the rum.
Rum is made anywhere sugarcane is grown and in many other countries besides. You don’t need to grow cane to make rum. Two hundred and fifty years ago, rum was widely produced in both England and New England, all from molasses imported from the Caribbean. Even today, much of the molasses that Caribbean and other countries utilize for rum production is supplied by Brazil.
Most consumers believe that rum is solely a product of the Caribbean, and indeed most of the famous names in rum are island based. But quality rums are produced on every continent (well, okay, not Antarctica) and in a myriad of styles. Moreover, the sugarcane plant doesn’t originate in the Caribbean, as most believe, but hails from somewhere in the Far East, perhaps Indonesia. A distilled spirit from sugarcane may have been the basis for what is the earliest known large- scale distilling; it took place in what is now modern-day Pakistan over 2,500 years ago.
Cachaça is made from sugarcane juice and comes only from Brazil, the world’s largest sugarcane producer. It is bottled from between 38 percent to 51 percent alcohol and is produced by as many as 30,000 small distillers. An incredible 98 percent of all cachaça is consumed in Brazil. Cachaça comes in a trio of classifications: unaged (1 year in wood), aged (2 to 12 years in wood), and yellow (immature spirits that have caramel or wood extracts added so they can appear older).
The rum we know today probably has its origins in desperation. Early Spanish and Portuguese settlers in Central and South America, as well as the Caribbean, had no wine and needed alcohol. We don’t exactly know how and when, but they were creating a rudimentary distillate from molasses within a few decades of their arrival in the New World. Once again, there is no “aha!” moment to declare New World rum’s time of birth. But the pangs are evident in the names chosen to depict the fiery spirit: “kill-devil,”,“demon rum,” “rumbullion” and “rumbustion,” the latter two terms used to connote mayhem.
The popular image of pirate juice is closer to the truth than any other popular image. Rums were distilled from molasses that might have been left to spoil for weeks, and then fermented. Straight from the still, these rums were either consumed on the spot or went into barrels and on to ships. The barrels were probably empty before a few weeks had passed.
From the sixteenth to the eighteenth centuries, lots of rum was being distilled in New England and particularly in or near Boston and coastal Connecticut. Ships laden with sugarcane, only recently arrived from the Caribbean or America’s Southeast, wouldn’t transport sugarcane back to England. Instead they would drop their loads in New England and take back a far more concentrated form of sugarcane: raw sugar.
With all the leftover molasses, the early American colonials made their own kind of rum, but it too must have tasted like the same hot liquid that the pirates were drinking. Meanwhile, back in the mother country, connoisseurs of Punch were developing a taste for rum and initiating the process that led to the taming of this fiery spirit. To soften rum’s heat, you either need a careful fermentation (that wasn’t happening centuries ago), a selective distillation (nobody’s throwing out perfectly good pirate juice), filtration (that’s a late nineteenth century innovation) or long barrel aging.
Originally, no one was willing to wait for rum to age in barrel long enough for the spirit to soften. That would change: as one English epicure noted in 1737, “in order to make Rum palatable to any Person of nice Taste, it must be carefully kept in a good Cellar for several years.”
That aged rum was becoming increasingly available. In Barbados in the seventeenth century, so much rum was being produced that plenty of it was available for sale elsewhere. Some of those barrels took enough time to transport that the rum they contained took on the elements of well-aged rum: honey, caramel and vanilla, as well as a gentler nature. Barbados rum was famous enough that George Washington insisted on a barrel for his inauguration, and it was highly prized on the London docks.
Other islands saw similar growth in reputation. Jamaican distillers started their fermentations with molasses from a previous fermentation, to more rapidly initiate the fermentation in a batch of fresh molasses. Those rums were far funkier in aroma, and the Jamaicans, too, learned to age them in barrel as long as possible to soften the weirdness. In some cases they added spices and flavorings, and most islands did the same for at least some of their rums.
The Demerara river region of British Guyana was noted for its Jamaican-style rums as well. It didn’t hurt that the Royal Navy was issuing its sailors a daily dram of old rum, blended from Jamaican and Demerara sources, a practice that didn’t end until 1970.
The French Islands used only cane juice since Napoleon owned sugar beet factories in France capable of producing raw sugar. With no home market for refined sugar, the French Islands were free to use the juice itself. As a result the rum produced on the French Islands (Martinique, Guadalupe, Marie Galante) as well as on former French possessions such as Haiti is something different from other rums. Cane juice rums can be more herbal and vegetal, but also more tropical in fruit character. Today, not all rhums (that’s how the French spell it) are made from cane juice, but the best are. They’re referred to as rhum agricole, or “agricultural rum” (as opposed to rhum industriel, or “industrial rum,” which is made from molasses).
By the late nineteenth century, Cuba had emerged as a sugar producing dynamo (as usual, made possible either by slave labor or slavery like conditions) and all that leftover molasses had to be used. Don Facundo de Bacardì began filtering his rums through charcoal, as vodka producers were famously doing, and thereby created a gentler rum. Later, he and his competitors employed continuous stills to make something closer to vodka.
After the Cuban Revolution, the Bacardi family escaped to Puerto Rico. Today, the rules of Puerto Rican rum production demand that no rum can be distilled below 160-proof. For some, that means the rums are more boring and have less of the character of traditional rum. To many, lighter, gentler rum is exactly what they want. As with all things about flavor, preference is personal.
Meanwhile, in Cuba, rum production continued with the flagship export brand (to everywhere but the U.S.) assuming the old pre-Revolutionary brand of Havana Club and retaining the richer, more fullflavored character of pre-Revolutionary Cuban rums.
But rum’s resurgence may be tied to its distinctive flavors rather than to its ability to seem like vodka. The cocktails that have epitomized rum drinks: Rum and Coke, Piña Colada, Daiquiri and such might be ideal for the neutral-style of rum. But the two drinks that have brought rum back to the cool side of the pool are the Caipirinha and the Mojito. Both demand that bartenders re-learn the old-fashioned practice of muddling.
Certainly, one of the largest selling and most important segments of rum is the flavored rum category. Rums such as Malibu (created in Barbados in 1980), Cruzan and Captain Morgan have revolutionized and revitalized the industry. Most popular flavors include coconut, mango, passion fruit, spiced, vanilla, citrus and others.
And a Caipirinha requires cachaça, a Brazilian rum made only from cane juice and often aged in unusual indigenous woods like freijo, cedar, imburana, cherry and jequitiba. Those barrels smell as unusual as they sound, but the exotic, tropical, herbal aromas of cachaça add funk and excitement to the smell of a great Caipirinha.
As usual, the best way to find flavor and identify differences is to put several rums next to each other. But the amazing variety of rums means that three aren’t enough. Instead, place one rum from each of the dominant styles next to each other: spiced, flavored, Jamaican, Puerto Rican, cachaça, Barbados, and Martinique (to name only a few). Smell, taste and compare them. Now add in some of the others that are out there—and see if they seem similar to one of the dominant styles. Try several brands all in the same style—differences can be strong here too.
Rum should be clean and dry and not bitter and not sweet, unless it is a sweetened and flavored type.


|
RUNTIME-TERROR
|
#include <string>
#include <SDL.h>
#include <SDL_mixer.h>
#include <map>
#include <utility>
#include <SDL_ttf.h>
#include <api/LevelData.hpp>
Go to the source code of this file.
Classes | |
| class | ResourceManager |
| This class handles all the requests by the game objects that involve external resource acquisition. More... | |


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• New tokens Providers
• Changes in 0.17.0
• What's next?
Here we are with another feature-packed update!
The feedback issue had some success. Thanks to Gerrit-K suggestion we have now replaced the old Default - VCS Provider with a Recently used one and a VCS one.
The Recently used Provider reads tokens from the recent commit messages cache, and if it
doesn't find enough tokens it falls back to the active VCS repositories filtering the commits made by yourself.
The VCS Provider reads tokens strictly from VCS repositories, without any filter so that you can
pick whatever a friend or colleague wrote down.
Don't worry about performance as what's needed is cached at the appropriate time to offer a snappy completion experience. Beware reading from VCS repositories is still experimental, so if you encounter issues you're able to disable it by unchecking the
com.github.lppedd.cc.providers.vcs
Registry key.
Be sure to keep the feedbacks coming by commenting
on the GitHub issue,
or by contacting me at lp.edoardo(at)gmail.com
Other than the new Providers, this release brings small features, a couple of fixes,
and as always an extensive refactoring of the codebase.
Following is a short summary, but you can look at all the commits
here.
Features:
• implemented two new tokens Providers that are able to offer Recently used tokens and VCS-extracted tokens.
• cleaned-up the commit message even when template completion is canceled (deliberately or by accident).
• included by default the Refs
footer type.
Fixes:
• deduplicated completion popup's items based on Providers ordering.
• removed a memory leak when the Providers settings panel was opened without first going through the main panel.
• correctly scaled the What's New dialog tabs and icon when a user changes scaling value while the dialog is displayed.
• correctly calculated the checkbox column width on row insertion when the Co-authors table is empty.
Refactorings:
• updated the UI style of the Co-authors table to reflect the changes made in 0.16.0.
• improved the SVG icons.
As stated in the previous release changelog, I'm focusing mainly on the features we already have. However I'd like to provide a way to disable a Provider as currently this is impossible, if not by disabling plugins in case of third-party ones. And obviously I'll continue cleaning-up the code and fixing issues if required!
Thanks to ymind for keeping the Chinese translation updated and for answering my questions. And thanks to every user.


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xmodaler.datasets¶
-
class
xmodaler.datasets.
DatasetFromList
(lst: list, copy: bool = True, serialize: bool = True)[source]¶ Bases:
torch.utils.data.dataset.Dataset
Wrap a list to a torch Dataset. It produces elements of the list as data.
-
__init__
(lst: list, copy: bool = True, serialize: bool = True)[source]¶ - Parameters
lst (list) – a list which contains elements to produce.
copy (bool) – whether to deepcopy the element when producing it, so that the result can be modified in place without affecting the source in the list.
serialize (bool) – whether to hold memory using serialized objects, when enabled, data loader workers can use shared RAM from master process instead of making a copy.
-
-
class
xmodaler.datasets.
MapDataset
(dataset, map_func)[source]¶ Bases:
torch.utils.data.dataset.Dataset
Map a function over the elements in a dataset.
- Parameters
dataset – a dataset where map function is applied.
map_func – a callable which maps the element in dataset. map_func is responsible for error handling, when error happens, it needs to return None so the MapDataset will randomly use other elements from the dataset.
-
class
xmodaler.datasets.
MSCoCoDataset
(stage: str, anno_file: str, seq_per_img: int, max_feat_num: int, max_seq_len: int, feats_folder: str)[source]¶ Bases:
object
-
class
xmodaler.datasets.
ConceptualCaptionsDataset
(stage: str, anno_file: str, max_seq_length: int, max_feat_num: int, feats_folder: str, images_ids_file: str, tokenizer)[source]¶ Bases:
object
-
class
xmodaler.datasets.
VQADataset
(stage: str, anno_folder: str, ans2label_path: str, label2ans_path: str, feats_folder: str, max_feat_num: int, max_seq_len: int, tokenizer)[source]¶ Bases:
object
-
class
xmodaler.datasets.
Flickr30kDataset
(stage: str, anno_folder: str, anno_file: str, feats_folder: str, max_feat_num: int, max_seq_len: int, tokenizer)[source]¶ Bases:
object
-
class
xmodaler.datasets.
MSVDDataset
(stage: str, anno_file: str, seq_per_img: int, max_feat_num: int, max_seq_len: int, feats_folder: str)[source]¶ Bases:
object
-
class
xmodaler.datasets.
MSRVTTDataset
(stage: str, anno_file: str, seq_per_img: int, max_feat_num: int, max_seq_len: int, feats_folder: str)[source]¶ Bases:
object


Below, each text box can have one pattern per line.
Unless otherwise specified, each line can either be:
- A simple text match on the URL, starting from the beginning of the domain.
- A regular expression, marked with a backtick (`) at the begginning of the line (backtick is placed after a negating '-', if used).
Global Options
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Title Use Overrides
Each line enables using the title, or prefix with - to disable use of title.
Fragment Use Overrides
Each line enables including fragments, or prefix with - to ignore fragments.
URL Tranforms
One "pattern`replacement[`flags]" per line. Separate with a backtick.
Try URL Conversions
Try out how URL transforms and fragment overrides affect any URL.
Enter a URL and hit Convert to see how it will be represented
when compared against other URL representations.


--- layout: post title: Ringing Rocks comments: true share: true category: personal images: # - preview: https://farm6.staticflickr.com/5679/21966688314_daf0c2e69e_s.jpg # feature: https://farm6.staticflickr.com/5679/21966688314_d642b1ef51_h.jpg # - preview: https://farm1.staticflickr.com/738/22401482840_206954ec4e_s.jpg # feature: https://farm1.staticflickr.com/738/22401482840_2b88cdcaba_h.jpg #song: https://embed.spotify.com/?uri=spotify%3Atrack%3A2CG5jX3RQYLaLHJ7O1FI56 excerpt: ---
Post about Ringing Rocks trail.


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codeMelon.com is a non-profit site exploring new features in CSS3, HTML5 and jQuery. You can view its content in recent versions of Chrome, Safari or Firefox.
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I am currently Assistant Professor of Computer Science at the Faculty of the Electrical Engineering of the Universidade Federal de Uberlândia, in Brazil.
In 2017, I received my PhD in Computer Science from the University of Campinas supervised by prof. Guilherme P. Telles and Simon Gog. My PhD thesis has been awarded as one of the best in the year by the Brazilian Computer Society and recieved the Honorable Mention in the CAPES award 2018.
From 2017 to 2019 I held a postdoc at the University of São Paulo and I have been Visiting Scientist at the BioAlgo group of the Consiglio Nazionale delle Ricerche, in Italy.
My research interest is the design of algorithms data structures for solving theoretical and applied problems in Bioinformatics, Information Retrieval, and related areas.
Office: Room 3N 314
FEELT - UFU
Uberlândia, MG
Brazil
E-mail: louza@ufu.br


Post 6 - On Primitives
You may be sitting there going "What is a primitive?"
I'M GLAD YOU ASKED
Well, for the purposes of this blog post, it is one thing that Ruby and Javascript have definitely not got in common. There ARE NO PRIMITIVES in Ruby, where everything is an object and the whole language is meant to be easy for us to read and write. How many times in the past did we read something like "Everything in Ruby is an object!" I feel like that should be a footnote to the entire post, so maybe it will be...
In contrast, only objects are objects in Javascript. The rest are whatcha call Primitives.
There are exactly five types of primitives, and they are...(I'm gonna assume that if you have made it this far, you might know a little bit about what is going on)
Undefined
Null
Boolean
String
Number
So what does it mean?Well, not a lot in practice. You can often coerce a property to a primitive and thus make an object, but in practice it is wasteful and often useless. The major advantage of using objects over primitives is that you can assign properties, but that could just lead to confusion.
Any-who, as useless as allllll this information may have been, I think there is merit in understanding as much as possible about the language we are learning.


Guardiola fearful over Aguero injury
The striker was forced off in the second half against Chelsea.
Pep Guardiola fears Manchester City’s come-from-behind victory over Chelsea may have come at a cost after striker Sergio Aguero limped off in the second half.
The Argentinian was replaced by Gabriel Jesus with 13 minutes left, one of three enforced changes for City on a night when first-half goals from Kevin De Bruyne and Riyad Mahrez gave them a 2-1 win after N’Golo Kante put Chelsea in front.
Aguero’s problem comes ahead of Tuesday’s Champions League match against Shakhtar Donetsk, and with trips to Newcastle and Burnley on the horizon before the Manchester derby on December 7.
“We will see tomorrow but it doesn’t look good,” Guardiola said of Aguero. “I think it’s muscular…
“He thought it was a kick but maybe he stretched it a bit.”
Aguero came off after City had already lost Spanish midfield duo Rodri and David Silva to cramping problems which looked less serious.
“Rodri has been one month without playing many games and David, he needs rhythm and these games are so demanding,” Guardiola said.
It certainly looked a demanding match as two teams with problems at the back decided attack was the best form of defence.
The result was at times a pulsating encounter, edged by City as they moved back above Chelsea and into third place.
Chelsea showed the confidence of a team who had won six in a row in the Premier League coming into this match, while City demonstrated the desire of a side desperate to bounce back from their defeat at Anfield a fortnight ago.
The visitors drew first blood when Kante burst through City’s defence, in which Fernandinho partnered John Stones, to slip the ball beyond Ederson after 21 minutes, and the hosts needed a deflection on De Bruyne’s shot to level eight minutes later.
Mahrez then produced a moment of real quality just before the break, cutting inside from the right, ghosting between Emerson and Mateo Kovacic before firing between Fikayo Tomori’s legs and in.
At the time it seemed unlikely to be the winning goal – Aguero would hit the crossbar while shots whistled narrowly wide at both ends and Raheem Sterling had a stoppage-time effort scrubbed out for a tight offside – but City held out for victory.
“We won against a top side,” Guardiola said. “Chelsea over the last 20 years have always been a good team but Frank is a courageous manager.”
That courage was shown in the amount of time Chelsea had City on the back foot. The visitors limited City to 46.7 per cent possession, the lowest total of any Guardiola-managed side in his 381 top-flight matches to date, but ultimately could not make it count.
“It was not the critical factor,” said Lampard. “Coming into the game, with our recent form and how we’ve been developing quickly, I wanted to come and be brave on the ball and off the ball.
“In the first half you saw all of that and at 1-0 we had relative control of the game, but that never lasts.
“There were a lot of positives but we lost the games. It shows at this level it’s the finer details in both boxes that decide it.
“These teams, Liverpool and City, have been getting results for a long time because these finer details, maybe they get them right.
“I don’t think you can come away from that game and say it was anything other than two really strong teams going against each other.
“One wins it because of a deflected goal and a really good goal, and the rest was in the balance.”


The administrative information of the current AAS.
An AAS Reference to the Asset represented by the created AAS. This parameter can be a AASReferenceObject or an array of Key creating a path to the pointed Asset.
The browsename for the created Object.
An AAS Reference to another AAS the created AAS is derived from.
A description of the Asset Administration Shell.
The Identifier for the Asset Administration Shell to be created. The Constructor can be obtained from the property CoreServer.coreaas.
The node id for the created Object.
Generated using TypeDoc
An object containing all the parameters for the creation of an instance of the AASType ObjectType.
example:
{ browseName: "SampleAAS", description: [ new LocalizedText({locale: "en", text: "Festo Controller"}), new LocalizedText({locale: "de", text: "Festo Controller"}) ], identification: new Identifier({ id: "www.admin-shell.io/aas-sample/1.0", idType: IdentifierType.URI }), assetRef: [new Key({ idType: KeyType.URI, local: true, type: KeyElements.Asset, value: "http://pk.festo.com/3S7PLFDRS35" })], derivedFromRef: [ new Key({ idType: KeyType.IRDI, local: false, type: KeyElements.AssetAdministrationShell, value: "AAA#1234-454#123456789" }) ], administration: admin }


| Vendor Name: | PromoMedia Group Inc. |
|---|---|
| Reference Number: | 06002-00-0093 |
| Contract Date: | 2015-01-12 |
| Description of Work: | 0301 - Advertising Services |
| Delivery Date: | 2015-03-31 |
| Contract Value: | $19,475.55 |
| Comments: | This contract was sole-sourced. This contract includes one or more amendments. |


Class: ActiveSupport::Notifications::Fanout::Handle
| Relationships & Source Files | |
| Inherits: | Object |
| Defined in: | activesupport/lib/active_support/notifications/fanout.rb |
Overview
A Handle
is used to record the start and finish time of event.
Both #start and #finish must each be called exactly once.
Where possible, it’s best to use the block form: ActiveSupport::Notifications.instrument. Handle
is a low-level API intended for cases where the block form can’t be used.
handle = ActiveSupport::Notifications.instrumenter.build_handle("my.event", {})
begin
handle.start
# work to be instrumented
ensure
handle.finish
end
Class Method Summary
- .new(notifier, name, id, payload) ⇒ Handle constructor Internal use only
Instance Method Summary
- #finish
- #start
- #ensure_state!(expected) private
- #finish_with_values(name, id, payload) Internal use only
Constructor Details
.new(notifier, name, id, payload) ⇒ Handle
This method is for internal use only.
# File 'activesupport/lib/active_support/notifications/fanout.rb', line 228
def initialize(notifier, name, id, payload) # :nodoc: @name = name @id = id @payload = payload @groups = notifier.groups_for(name).map do |group_klass, grouped_listeners| group_klass.new(grouped_listeners, name, id, payload) end @state = :initialized end
Instance Method Details
#ensure_state!(expected) (private)
[ GitHub ]#finish
[ GitHub ]# File 'activesupport/lib/active_support/notifications/fanout.rb', line 247
def finish finish_with_values(@name, @id, @payload) end
#finish_with_values(name, id, payload)
This method is for internal use only.
[ GitHub ]
# File 'activesupport/lib/active_support/notifications/fanout.rb', line 251
def finish_with_values(name, id, payload) # :nodoc: ensure_state! :started @state = :finished @groups.each do |group| group.finish(name, id, payload) end end
#start
[ GitHub ]# File 'activesupport/lib/active_support/notifications/fanout.rb', line 238
def start ensure_state! :initialized @state = :started @groups.each do |group| group.start(@name, @id, @payload) end end


5.3. Conditional Expressions
CASE
The standard SQL CASE expression has two forms. The “simple” form searches each value expression from left to right until it finds one that equals expression:
CASE expression
WHEN value THEN result
[ WHEN ... ]
[ ELSE result ]
END
The result for the matching value is returned. If no match is found, the result from the ELSE clause is returned if it exists, otherwise null is returned. Example:
SELECT a,
CASE a
WHEN 1 THEN 'one'
WHEN 2 THEN 'two'
ELSE 'many'
END
The “searched” form evaluates each boolean condition from left to right until one is true and returns the matching result:
CASE
WHEN condition THEN result
[ WHEN ... ]
[ ELSE result ]
END
If no conditions are true, the result from the ELSE clause is returned if it exists, otherwise null is returned. Example:
SELECT a, b,
CASE
WHEN a = 1 THEN 'aaa'
WHEN b = 2 THEN 'bbb'
ELSE 'ccc'
END
IF
The IF function is actually a language construct that is equivalent to the following CASE expression:
CASE WHEN condition THEN true_value [ ELSE false_value ] END
- if(condition, true_value)
Evaluates and returns true_value if condition is true, otherwise null is returned and true_value is not evaluated.
- if(condition, true_value, false_value)
Evaluates and returns true_value if condition is true, otherwise evaluates and returns false_value.
COALESCE
- coalesce(value[, ...])
Returns the first non-null value in the argument list. Like a CASE expression, arguments are only evaluated if necessary.
NULLIF
- nullif(value1, value2)
Returns null if value1 equals value2, otherwise returns value1.


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