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# PUBLG100: Introduction to Quantitative Methods
#
# Week 1 Solutions: Introduction to Quantitative Analysis
#
#

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rm( list = ls() )

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getwd()

## ----eval=FALSE----------------------------------------------------------
## setwd("N:/PUBLG100")

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# assign the 5 elements to a
a <- c( 2, 4, 6, 8, 10)
# check what a contains
a

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a <- a[- length(a)]
a

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# create a again
a <- c( 2, 4, 6, 8, 10,4)
# delete last element
a <- head(a, -1)
# see what a contains now
a

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# assign the values to the matrix
m <- matrix( c( 3, 6, 9, 2, 3, 5, 54, 48, 42), 3, 3, byrow = T)
# print the contents of m to the screen (check what m contains)
m

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# assing the values to the matrix
m <- rbind( c(3, 6, 9), c(2, 3, 5), c(54, 48, 42))
# check what m contains
m

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# assign a 1 to row 1 and column 1 of m
m[1, 1] <- 1
# assign a 1 to row 2 and column 2 of m
m[2, 2] <- 1
# assign a 1 to row 3 and column 3 of m
m[3, 3] <- 1
# check what m contains
m

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# assigning the values from Exercise 7 to m again
m <- rbind( c(3, 6, 9), c(2, 3, 5), c(54, 48, 42))
# assigning a 1 to each element on the diagonal of m
diag(m) <- 1
# checking what m contains
m

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# assign the csv file to df
df <- read.csv("http://uclspp.github.io/PUBLG100/data/polity.csv")

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# assign(overwrite) df to df but only those rows where 
# the variable year is equal to 1991
df <- df[ df$year == 1991, ]
# look at the first 6 rows of data set df
head(df)

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# summary() returns summary statistics
# the $ indicates that you want to access something in data set df
# in this case the variable democ
summary( df$democ)
# table() produces a frequency table
table(df$democ)

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# assign (overwrite in this case) df with df but only those rows (observations)
# of df where democracy is greater or equal to zero
df <- df[ df$democ >= 0, ]

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hist( df$democ)