---
title: "2018 By-Election Results"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: fill
social: [ "twitter", "facebook", "menu"]
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(highcharter)
library(ggvis)
```
```{r}
Candidate <- data.frame(Candidate=c("COLE, Josiah Marvin (CDC)","GBILAH, Fairnoh Theo (VOLT)","KOLLIE, Prince Togar (UPP)","TOKPA, Henrique Flomo (IND)","ZARWOLO, Orando Koimene (ALP)"),Votes=c(20982,5556,1346,27806,3504))%>%
# Calculate -- and format -- the percentage for each channel
mutate(Bar_Percentage = sprintf("%.1f%%", 100*(Votes / sum(.$Votes))))
```
Bong County
============================
Column {data-width=550}
-----------------------------------------------------------------------
### 502 Polling Place(s) of Total 502 Polling Places ( 100.00% )
```{r}
kable(Candidate, align=c('l','r','r'))
```
### 502 Polling Place(s) of Total 502 Polling Places ( 100.00% )
```{r}
library(ggplot2)
# Basic barplot
p <-ggplot(data = Candidate, aes(x=Candidate, y=Votes)) +
geom_bar(stat="identity")
# Horizontal bar plot
p + coord_flip()+
theme(axis.text.y = element_text(size = 13, color = "black")) # THE 'OVERRIDE' LINE
```
```{r}
Candidates <- data.frame(Candidates =c("BENSON, Jr., Bernard DJ Blue(IND)","FRANCIS,Josephine George (UP)","JOSEPH, Saah Hardy (CDC)","KARNGAR, Finley Y. (VCP)","KESHEN, Mark Austin (IND)","KOLUBAH, Yekeh Yarpahworluo (IND)","TIPAYSON, Michael Doe (UPP)"),Votes = c(14074,5978,37141,684,6640,1593,1198)) %>%
# Calculate -- and format -- the percentage for each channel
mutate(Bar_Percentage = sprintf("%.1f%%", 100*(Votes / sum(.$Votes))))
```
Montserrado County
============================
Column {data-width=550}
-----------------------------------------------------------------------
### 947 Polling Place(s) of Total 1790 Polling Places ( 52.91% )
```{r}
kable(Candidates, align=c('l','r','r'))
```
### 947 Polling Place(s) of Total 1790 Polling Places ( 52.91% )
```{r}
# Basic barplot
p2<-ggplot(data = Candidates, aes(x=Candidates, y=Votes)) +
geom_bar(stat="identity")
# Horizontal bar plot
p2 + coord_flip()+
theme(axis.text.y = element_text(size = 13, color = "black")) # THE 'OVERRIDE' LINE
```
Statement by Cllr. Jerome G. Korkoya
=========================================
Chairman, National Elections Commission (NEC)
On the Announcement of Progressive Results of the
July 31, 2018 Senatorial By-elections in
Montserrado and Bong Counties
NEC Conference Hall, 9thStreet, Sinkor
**Introduction**
Ladies and gentlemen of the press, you are welcome to this second day of announcement of results for the Senatorial By-elections in Bong and Montserrado Counties. In today's press briefing, we will announce 502 of 502 or 100% of polling places in Bong County and 947 of 1,790 or 52.91% of polling places in Montserrado County. Today's announcement includes the final results from Bong County.
We had planned to announce results from all polling places in the two counties today but the change of venue from the Samuel Kanyon Doe Sports Complex to our Conference Hall for the tallying of votes in Montserrado County has impacted our ability to do so. At the S.K.D Sports Complex, we have space to erect eleven work stations whereas our conference Hall can accommodate a maximum of six work stations. Be that as it may, we are hopeful of announcing final results from Montserado County on tomorrow, August 3, 2018.
**Complaint/Dispute Resolution**
As stated yesterday, the NEC has not received any complaint on the conduct of the Senatorial By-elections or the tally process. With that said, we will now proceed to announce the second day results of the Senatorial By-elections.
**Reading of Results and Declaration of Winner in Bong County**
Based on the results just read and in keeping with Section 2.9(g) of the New Elections Laws of Liberia, I, on behalf of the Board of Commissioners of the National Elections Commission do hereby declare Dr. Henrique Flomo Tokpa as the winner of the July 31, 2018 Senatorial By-election in Bong County. Senator elect Tokpa will be certificated within the time frame provided for by law.
Updated results are available on the NEC website at [www.necliberia.org.](http://www.necliberia.org/others.php?&7d5f44532cbfc489b8db9e12e44eb820=MTAzNQ%3D%3D)
I thank you.
Interactive Data Visualization
====================================
Column {data-width=350}
----------------------------
### County: Bong
```{r}
p1 <- Candidate %>%
group_by(Candidate) %>%
plot_ly(x = ~Candidate,
y = ~Votes,
color = "blue",
type = 'bar') %>%
layout(xaxis = list(title = "Name of Candidate"),
yaxis = list(title = 'Total Votes Obtained'))
p1
```
Column {data-width=350}
----------------------------
### County: Montserrado
```{r}
p1 <- Candidates %>%
group_by(Candidates) %>%
plot_ly(x = ~Candidates,
y = ~Votes,
color = "blue",
type = 'bar') %>%
layout(xaxis = list(title = "Name"),
yaxis = list(title = 'Total Votes Obtained'))
p1
```
Public Sentiments
=================================
```{r}
y <- c('It was necessary for
Hon. Saah Joseph to contest
the Senatorial seat.',
'Hon. Saah Joseph winning
the Senatorial seat
will encourage more legislators
to work in the interest of their constituents.',
'The poor turn out does not mean that
the Ruling Party is under performing.',
'More people are likely to cross carpet
to the Ruling Party.')
x1 <- c(21, 24, 27, 29)
x2 <-c(30, 31, 26, 24)
x3 <- c(21, 19, 23, 15)
x4 <- c(16, 15, 11, 18)
x5 <- c(12, 11, 13, 14)
data <- data.frame(y, x1, x2, x3, x4, x5)
top_labels <- c('Strongly
agree', 'Agree', 'Neutral', 'Disagree', 'Strongly
disagree')
p <- plot_ly(data, x = ~x1, y = ~y, type = 'bar', orientation = 'h',
marker = list(color = 'rgba(38, 24, 74, 0.8)',
line = list(color = 'rgb(248, 248, 249)', width = 1))) %>%
add_trace(x = ~x2, marker = list(color = 'rgba(71, 58, 131, 0.8)')) %>%
add_trace(x = ~x3, marker = list(color = 'rgba(122, 120, 168, 0.8)')) %>%
add_trace(x = ~x4, marker = list(color = 'rgba(164, 163, 204, 0.85)')) %>%
add_trace(x = ~x5, marker = list(color = 'rgba(190, 192, 213, 1)')) %>%
layout(xaxis = list(title = "",
showgrid = FALSE,
showline = FALSE,
showticklabels = FALSE,
zeroline = FALSE,
domain = c(0.15, 1)),
yaxis = list(title = "",
showgrid = FALSE,
showline = FALSE,
showticklabels = FALSE,
zeroline = FALSE),
barmode = 'stack',
paper_bgcolor = 'rgb(248, 248, 255)', plot_bgcolor = 'rgb(248, 248, 255)',
margin = list(l = 120, r = 10, t = 140, b = 80),
showlegend = FALSE) %>%
# labeling the y-axis
add_annotations(xref = 'paper', yref = 'y', x = 0.14, y = y,
xanchor = 'right',
text = y,
font = list(family = 'Arial', size = 12,
color = 'rgb(67, 67, 67)'),
showarrow = FALSE, align = 'right') %>%
# labeling the percentages of each bar (x_axis)
add_annotations(xref = 'x', yref = 'y',
x = x1 / 2, y = y,
text = paste(data[,"x1"], '%'),
font = list(family = 'Arial', size = 12,
color = 'rgb(248, 248, 255)'),
showarrow = FALSE) %>%
add_annotations(xref = 'x', yref = 'y',
x = x1 + x2 / 2, y = y,
text = paste(data[,"x2"], '%'),
font = list(family = 'Arial', size = 12,
color = 'rgb(248, 248, 255)'),
showarrow = FALSE) %>%
add_annotations(xref = 'x', yref = 'y',
x = x1 + x2 + x3 / 2, y = y,
text = paste(data[,"x3"], '%'),
font = list(family = 'Arial', size = 12,
color = 'rgb(248, 248, 255)'),
showarrow = FALSE) %>%
add_annotations(xref = 'x', yref = 'y',
x = x1 + x2 + x3 + x4 / 2, y = y,
text = paste(data[,"x4"], '%'),
font = list(family = 'Arial', size = 12,
color = 'rgb(248, 248, 255)'),
showarrow = FALSE) %>%
add_annotations(xref = 'x', yref = 'y',
x = x1 + x2 + x3 + x4 + x5 / 2, y = y,
text = paste(data[,"x5"], '%'),
font = list(family = 'Arial', size = 12,
color = 'rgb(248, 248, 255)'),
showarrow = FALSE) %>%
# labeling the first Likert scale (on the top)
add_annotations(xref = 'x', yref = 'paper',
x = c(21 / 2, 21 + 30 / 2, 21 + 30 + 21 / 2, 21 + 30 + 21 + 16 / 2,
21 + 30 + 21 + 16 + 12 / 2),
y = 1.15,
text = top_labels,
font = list(family = 'Arial', size = 12,
color = 'rgb(67, 67, 67)'),
showarrow = FALSE)
p
```
