Investments

AMPD
Tomorrow: ZYNGA: Options.

Songs

Plastic NYC

Broken Boy Meets Broken Girl

Poor Black Kid Meets the Police

Thank You Pat

Heart Love Heart Break

R Code Snippets

Summarizing Mathematically a Data Frame

summary(data[monthIsMay == TRUE,])

Reading a CSV File into a data Frame:

data <- read.csv("hw1_data.csv")

data[1:2,]

Adding all Rows based on a Column Condition:

aggregateEmissionsValuesByYearDataSet <- aggregate(Emissions ~ year, data = NEI, FUN = sum)

Histogram:


hist(dailyStepData$Steps, xlab = "Number of Steps", ylab = "Number of Days", main = "Histogram of Number of Steps Daily")

Using rbinom:

rbinom(1,5,1/6)    ### rbinom(number of experiments, number of observations per experiment, probability of success)

isNaOzone = is.na(ozone)

summary(data)

over31Ozone = data$Ozone > 31

data2 <- data[over31Ozone == TRUE,]

data4 <- data[monthIsJune == TRUE]

mdhIsNa[is.na(mdhIsNa)] <- FALSE

Plotting a Simple Graph with a AB Line:

with(aggregateEmissionsValuesByYearDataSet, plot(year, Emissions), main = "Total Emissions by Year", pch = 20)
model <- lm(Emissions ~ year, aggregateEmissionsValuesByYearDataSet)
abline(model, lwd = 2)

Printing a Plot to a PNG File:

png(file = "myplot.png", bg = "transparent")
plot(1:10)
rect(1, 5, 3, 7, col = "white")
dev.off()

Getting the Sum of the Columns:

colSums(x[c(4,9)])

Plotting: Printing A Plot with Five Panels for Months using ggplot2:

airquality = transform(airquality, Month = factor(Month))
qplot(Wind, Ozone, data = airquality, facets = . ~ Month)

Building a Matrix in R:

B = matrix(c(2, 4, 3, 1, 5, 7, 6, 5, 9), nrow=3, ncol=3)

Reading RDS Files:

NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")

Processing Fixed Width Columns:

x <- read.fwf(
    file="fwff.txt",
    skip=4,
    widths=c(12, 7,4, 9,4, 9,4, 9,4))

Setting an Objects Column Names from a data table:

colnames(x_test_data) <- x_test_data_titles[,2]

Getting the Adjoining Values From Two Columns:

both <- intersect(eduData$CountryCode, gdpData$CountryCode)

Downloading a file from a URL:

download.file(fileURL, destfile="idahoHousing.csv", method="curl")

Merging Data Frame:

completeDataSet <- merge(gdpData,eduData,by="CountryCode")

Stripping Characters from a Vector:

group <- c("12357e", "12575e", "197e18", "e18947") 

v <- gsub("e", "", group)

Setting Column Names:

names(gdpData) <- c("CountryCode", "CountryNumberCode", "V3", "FullCountryName", "GDP", "V6", "V7", "V8", "V9", "V10")

Removing All Variables from the Current Environment Except Functions:

rm(list = setdiff(ls(), lsf.str()))

Ordering a Data Frame:

completeOrderedDataSet <- completeDataSet[with(completeDataSet, order(GDPRank, decreasing = FALSE)), ]

Downloading a JPEG:

fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fjeff.jpg"
download.file(fileURL, destfile="instructorPhoto.jpg", method="curl")
install.packages("jpeg")
install(jpeg)
img <- readJPEG("instructorPhoto.jpg", native = TRUE)

Getting a Quantile from an Image:

quantile(img, c(0.3, 0.8), type = 1)

Installing a Package:

install.packages("xlsx")

Using XML/RCurl to extract data

install.packages("RCurl")
library(RCurl)
xData <- getURL(fileURL)
doc <- xmlParse(xData)
rootNode <- xmlRoot(doc)
xpathSApply(rootNode, "//zipcode", xmlValue)
zips <- xpathSApply(rootNode, "//zipcode", xmlValue)
zips[zips == "21231"]

Unzipping a zip file:

unzip("galaxyProject1.zip");

Changing the Working Directory:

setwd("./UCI HAR Dataset");

Setting Working Directory:

getwd();

Listing all the Files in a Directory:

list.files()

Clearing all data from the terminal:

cat("\014")

Removing Variables From Environment:

remove(activity_labels_data, subject_test_data, test_table1, x_test_data, x_test_data_titles, y_test_data)

Subsetting a Data Frame:

stateTFSubset = outcome$State == state
stateSubset = outcome[stateTFSubset == TRUE,]
LAAutoTFDataSet = carNEIDataSet$fips == "06037"

Getting the Cummulative Variance From PCA with Carat:

adData = data.frame(diagnosis,predictors)
inTrain = createDataPartition(adData$diagnosis, p = 3/4)[[1]]
training = adData[ inTrain,]
testing = adData[-inTrain,]

training2 <- training[, c(1, 58:69)]

preProc <- preProcess(training2[,-1], method = "pca", pcaComp = 10)

stds <- preProc$std

stds[1]^2 / sum(stds^2) + stds[2]^2 / sum(stds^2) + stds[3]^2 / sum(stds^2) + stds[4]^2 / sum(stds^2) + stds[5]^2 / sum(stds^2) + stds[6]^2 / sum(stds^2) + stds[7]^2 / sum(stds^2) + stds[8]^2 / sum(stds^2) + stds[9]^2 / sum(stds^2)

Getting the Accuracy of a PCA based Prediction:

testing2 <- testing[, c(1, 58:69)]
testPC <- predict(preProc, testing2[,-1])
confusionMatrix(testing2$diagnosis, predict(modelFit, testPC))

Getting the Cummulative Variance From PCA with prcomp:

training2prcomp <- prcomp(training2)

summary(training2prcomp)

Replacing Factors with Numbers:

training2$diagnosis <- ifelse(training2$diagnosis == "Impaired", 2, 1)

Running an R Script:

source("run_analysis.R")

getting the first to rows from a column and the 1st, 2nd, 3rd, 4th, and 5th columns with the titles:

complete_table[1:2, c(1:2, 3:5), with=FALSE]

Replacing All Values in a Table (numeric but it shouldn't matter) with Corresponding Text Values from another Table:

labeled_table2[, activity_code:=activity_labels_data[activity_code,2]]

Printing a Specific Set of Values from a Table:

labeled_table[1:10,c(1:2), with=FALSE]

Plotting a Variable in qplot against it's index:

qplot(seq_along(CompressiveStrength), CompressiveStrength, data = training)

Plotting a Variable in qplot with Colors against it's index:

cutCoarseAggregate <- cut2(training$CoarseAggregate, g=4)
qplot(seq_along(CompressiveStrength), CompressiveStrength, color= cutCoarseAggregate,data = training)

How to combine two different tables data (not based on a key):

DT1<-data.table(col1=sample(letters,5,replace=TRUE),col2=sample(LETTERS[1:5],5,replace=TRUE),col3=sample(1:2,5,replace=TRUE))
DT2<-data.table(col4=sample(1:3,10,replace=TRUE),col5=sample(LETTERS[1:5],10,replace=TRUE),col6=sample(1:100,10,replace=TRUE))
(DT1)
(DT2)

Goals

Nov. 8th.

1.  Debug script
2.  Get breakfast Sandwich VC to work
3.  Add logos
4.  Submit App

Nov. 9th

1.  Get CarMath Layout to work.
2.  Build the back end piece with the calculation.

iOS Development: Moving a TabBar to the Bottom of a Screen Regardless of Size

-(void)viewDidLayoutSubviews

{

    

    UIScreen* screen = [[UIScreen screens] objectAtIndex:0];

    

    CGRect screenBounds = screen.bounds;

    

    self.tabBar.frame = CGRectMake(0,  screenBounds.size.height - self.tabBar.frame.size.height, self.tabBar.frame.size.width, self.tabBar.frame.size.height);

    

    [self.view addSubview:tabBar];

    

}

iPhone: Building a View Dynamically Using Screen Size as the Parameter

  if ((int)[[UIScreen mainScreen] bounds].size.height == 568)

    {

        // This is iPhone 5 screen

        NSLog(@"iPhone 5: viewDidAppear: picker");

        

        labelRect = CGRectMake(20.0, 79.0, 167.0, 21.0);

        address1Label = [[UILabel alloc] initWithFrame:labelRect];

        address1Label.text = @"Address 1";

        

        [self.view addSubview:address1Label];

     }

else 

{

        

        // This is iPhone 4/4s screen

        NSLog(@"iPhone 4: viewDidAppear: picker");

        

        labelRect = CGRectMake(20.0, 79.0, 280.0, 30.0);

        address1TextField = [[UITextField alloc] initWithFrame:labelRect];

        address1TextField.returnKeyType=UIReturnKeyDone;

        [address1TextField addTarget:self action:@selector(hideKeyBoard:)

                    forControlEvents:UIControlEventEditingDidEndOnExit];

        address1TextField.placeholder = @" Address 1";

}

Work and Photo Album

select tbh.brokerageName, tbh.corpCRDNumber, count(tb.crdNumber) as brokerCount
from tblBrokerageHouses tbh inner join tblBrokers tb on tbh.corpCRDNumber = tb.corpCRDNumber group by tbh.corpCRDNumber order by brokerCount desc;

Stopped at: NYLIFE SECURITIES LLC

http://bb-women.net/sexiest-selfies-of-2014-photo-album