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Thursday, November 28, 2024
Price range of different flats and apartments in Phase 7 and 8 in Bahria Town, Rawalpindi/Islamabad
Bahria Town is one of the most well-known areas in Rawalpindi/Islamabad.
It may have several investment options. Considering flats in the area of Phase
7 and Phase 8, they can be of different types, including Studio apartments, 1
Bed, 2 Bed, and 3 Bed flats.
Studio flats are one bed flats with a room and attached bathroom.
One bed flat has one bedroom with attached bathroom and TV launch and balcony. Two
bed means two bedrooms with TV launch attached. Three bed means three bedrooms
with TV launch attached and washroom with bedrooms.
Considering cash payments, Studio apartments are available
in the price range of 25 lacs to 50 lacs depending on the location, floor,
building, availability of lift, beauty, and furnished or non-furnished. These apartments
after purchase can also be set on Airbnb. The rent of these apartments can be
over 20,000. One bed flats are available in the price range of 35 lacs to 150
lacs. The rent of these apartments can be over 35,000. Two bed flats are
available in the price range of 45 lacs to 200 lacs. The rent of these apartments
can be over 50,000. Three bed flats are available in the price range of 75 lacs
to 300 lacs. The rent of these apartments can be over 75,000. There is about
20% ROI on these investments.
Source:
Property Naama - Flats In Bahria Town Rawalpindi | 25 Lac
Say 2 Crore Tak | 1, 2 & 3 Bedroom Ready & Installments - https://www.youtube.com/watch?v=qyKG8x8z51o
Wednesday, November 27, 2024
Day 12 and Last Day: 30-days to learn rgl, plotly, and gganimate - Create a Time-Based 3D Animation Using rgl and gganimate
N.B.: This is the last of learning a combination of rgl, plotly, and gganimate, as it becomes difficult to combine all these at this time.
Step 1: Install Required Packages
Before starting, ensure the following packages are installed:
install.packages
(c("rgl",
"ggplot2",
"gganimate",
"ggimage"))
Step 2: Generate 3D Frames Using rgl
1. Setup the Environment: Create a 3D scatter plot
that rotates over time.
library
(rgl
)
# Create a 3D scatter plot
n
<- 100
# Number of points
x
<- rnorm
(n
)
y
<- rnorm
(n
)
z
<- rnorm
(n
)
col
<- rainbow
(n
)
open3d
()
# Initialize the 3D plot
plot3d
(x
, y
, z
, col
= col
, size
=
5)
2. Rotate and Save Frames: Capture frames by
rotating the plot over time and saving each frame as an image.
frames_dir
<-
"frames"
dir.create
(frames_dir
, showWarnings
=
FALSE)
# Create a directory for frames
# Generate and save frames
for
(i
in
1:100)
{
view3d
(userMatrix
= rotationMatrix
(pi
* i
/
50,
0,
1,
0))
# Rotate around Y-axis
snapshot3d
(file.path
(frames_dir
, paste0
("frame_", sprintf
("%03d", i
),
".png")))
}
Step 3: Animate Frames Using gganimate
1. Prepare Frame Data: Load the saved frames and
prepare a data frame for animation.
library
(ggplot2
)
library
(gganimate
)
library
(ggimage
)
# List saved frames
frame_paths
<- list.files
(frames_dir
, full.names
=
TRUE)
# Create a data frame
frame_df
<- data.frame
(
frame
= frame_paths
,
time
=
1:length(frame_paths
),
# Time points for animation
x
=
0,
# Placeholder for x-coordinate
y
=
0
# Placeholder for y-coordinate
)
2. Build the Animation: Use gganimate
to create the animation from
the frames.
animation
<- ggplot
(frame_df
, aes
(x
= x
, y
= y
, image
= frame
))
+
geom_image
(size
=
1)
+
# Add images to the plot
transition_time
(time
)
+
# Transition over the time variable
enter_fade
()
+
# Fade-in effect
exit_fade
()
+
# Fade-out effect
theme_void
()
# Remove unnecessary plot elements
3. Save the Animation: Export the animation as a
GIF.
anim_save
("3d_time_animation.gif", animation
)
Step 4: Review and Debug
- Check the
saved animation in your working directory (
3d_time_animation.gif
). - If the
animation doesn’t look smooth, adjust the number of frames or transition
settings.
Key Notes
- Custom Rotation: You can modify the
view3d()
function to rotate around different axes or add zoom effects. - Image Quality: Ensure the
rgl
frames are saved with high resolution for better animation quality. - Animation Effects: Experiment with different
gganimate
effects likeease_aes()
or transitions (transition_states()
).
Tuesday, November 26, 2024
Day 11: 30-days to learn rgl, plotly, and gganimate - Learn How to Save rgl 3D Frames and Stitch Them Into an Animation With gganimate
Step 1: Set Up the Environment
1. Install Required Packages
Ensure you have the following packages installed:
install.packages
(c("rgl",
"gganimate",
"magick"))
The magick
package will handle image processing for stitching frames.
2. Load the Libraries
Load the necessary libraries:
library
(rgl
)
library
(magick
)
library
(gganimate
)
Step 2: Create an rgl 3D Plot
1. Generate Data for 3D Visualization
Create a 3D dataset for plotting:
set.seed
(123)
x
<- rnorm
(100)
y
<- rnorm
(100)
z
<- rnorm
(100)
colors
<- rainbow
(100)
# Create a 3D scatter plot
plot3d
(x
, y
, z
, col
= colors
, size
=
5, type
=
"s")
2. Set Up Rotation or Camera Movements
Define the rotation sequence or camera viewpoints:
n_frames
<- 36
# Number of frames
angles
<- seq
(0,
360, length.out
= n_frames
)
Step 3: Save rgl Frames
1. Create a Temporary Directory for Frames
Create a directory to save the images:
dir.create
("rgl_frames")
2. Save Each Frame
Loop through the angles and save an image for each:
for
(i
in
seq_along(angles
))
{
rgl.viewpoint
(theta
= angles
[i
], phi
=
30, fov
=
60)
snapshot3d
(sprintf
("rgl_frames/frame_%03d.png", i
))
}
Step 4: Combine Frames Into an Animation
1. Use magick to Stitch Images
Load and combine the images:
frames
<- list.files
("rgl_frames", full.names
=
TRUE, pattern
=
"png")
animation
<- image_read
(frames
)
%>%
image_animate
(fps
=
10)
# Set frames per second
2. Save the Animation
Save the animation as a GIF:
image_write
(animation
,
"rgl_animation.gif")
Step 5: (Optional) Combine With gganimate
1. Create a Data Frame for gganimate
If you want to integrate gganimate
,
create a dataset representing each frame's data:
animation_data
<- data.frame
(
x
=
rep(x
, n_frames
),
y
=
rep(y
, n_frames
),
z
=
rep(z
, n_frames
),
frame
=
rep(1:n_frames
, each
=
length(x
))
)
2. Visualize With ggplot2 and gganimate
Use ggplot2
to create a
dynamic scatter plot:
library
(ggplot2
)
ggplot
(animation_data
, aes
(x
= x
, y
= y
, color
= z
, frame
= frame
))
+
geom_point
()
+
transition_manual
(frame
)
+
theme_minimal
()
Step 6: Clean Up
1. Remove Temporary Files
Delete the directory containing frames:
unlink
("rgl_frames", recursive
=
TRUE)
2. Review the Final Animation
Check the GIF and tweak the settings (e.g., angles, FPS) if needed.
Prices of 5 marla plots in some of the well-known areas in and near Islamabad, Pakistan
There are different societies in Islamabad and Rawalpindi,
Pakistan. It needs to be considered that if someone wants to make big
investments, they have to listen about mature housing societies. Nevertheless,
considering prices of different societies, in the Blue World City, which is the
last housing city, if we go through the motorway side, the cost of a 5 marla
plot is in the range of 15 to 18 lacs. In the Silver City Housing society, the
cost of a 5 marla plot is in the range of 20 lacs to 24 lacs. In the Capital Smart
City, the price is in the range of 30 lacs to 34 lacs. In the Faisal Town Phase
II, prices are in the range of 22 lacs to 25 lacs. In the Top City, prices are
in the range of 62 lacs to 80 lacs. In the Faisal Town Phase I, prices are in
the range of 90 lacs to 1 crore. In the I-14 sector, prices are in the range of
1.25 crores; in I-15, prices are in the range of 70 lacs, and in I-16, prices
are in the range of 85 lacs. In the G15 sector, prices of 7 marla plots are in
the range of 1.75 crores. In G-13 and G-14, prices of 5 marla plots are in the
range of 2.25 crores to 2.50 crores. In the Park View City, prices are in the
range of 50 lacs to 65 lacs and above 1 crore. In Bahria Enclave, prices are in
the range of 65 lacs to 95 lacs. In D-12, costliest plots are available that
are in the range of 3 crores to 3.5 crores.
These properties have no installment plans.
Source:
Gondal Group of Marketing Islamabad - Top 10 Best Housing
Societies in Islamabad | 5 Marla Possession Plot Price Comparison in Islamabad
- https://www.youtube.com/watch?v=tktrkw5uvP0
Monday, November 25, 2024
Day 10: 30-days to learn rgl, plotly, and gganimate - Create an Animated Scatter Plot with gganimate and Enhance it with Plotly Hover Details
Step 1: Install and Load Required Libraries
Ensure you have all the necessary libraries installed. Use the following
code:
# Install required packages
install.packages
(c("ggplot2",
"gganimate",
"plotly"))
# Load the libraries
library
(ggplot2
)
library
(gganimate
)
library
(plotly
)
Step 2: Prepare the Dataset
Use a time-series dataset or create a sample dataset for the scatter plot.
For this example:
# Create a sample dataset
set.seed
(123)
data
<- data.frame
(
Time
=
rep(1:10, each
=
10),
X
= runif
(100,
min
=
1,
max
=
100),
Y
= runif
(100,
min
=
1,
max
=
100),
Category
=
rep(letters[1:10], times
=
10)
)
Step 3: Create the Static ggplot
Set up the scatter plot with ggplot2
:
# Create the base plot
static_plot
<- ggplot
(data
, aes
(x
= X
, y
= Y
, color
= Category
, frame
= Time
))
+
geom_point
(size
=
3)
+
labs
(title
=
"Scatter Plot Over Time", x
=
"X-Axis", y
=
"Y-Axis")
+
theme_minimal
()
Step 4: Animate the Plot with gganimate
Use transition_time
to
animate the plot over the Time
variable:
# Animate the scatter plot
animated_plot
<- static_plot
+
transition_time
(Time
)
+
labs
(subtitle
=
'Time: {frame_time}')
# Render the animation (optional, for preview)
animate
(animated_plot
, nframes
=
100, fps
=
10)
Step 5: Export Animation Frames
Save animation frames for converting to Plotly:
# Save each frame
animation_frames
<- animate
(animated_plot
, renderer
= file_renderer
(dir
=
"frames", overwrite
=
TRUE))
Step 6: Convert ggplot to Plotly for Interactivity
Add Plotly's hover functionality to the ggplot-based animation:
# Convert the static ggplot to a plotly object
plotly_plot
<- ggplotly
(static_plot
, tooltip
=
c("Category",
"X",
"Y"))
# Add animation controls
plotly_plot
<- plotly_plot
%>%
animation_opts
(frame
=
1000, redraw
=
TRUE)
%>%
animation_slider
(currentvalue
=
list(prefix
=
"Time: "))
Step 7: Combine gganimate and Plotly
Overlay gganimate
animations on the interactive Plotly scatter plot:
# Generate the final interactive plot
final_plot
<- plot_ly
(
data
= data
,
x
=
~X
,
y
=
~Y
,
color
=
~Category
,
frame
=
~Time
,
text
=
~paste
("Category:", Category
,
"<br>X:",
round(X
,
2),
"<br>Y:",
round(Y
,
2)),
hoverinfo
=
"text",
type
=
'scatter',
mode
=
'markers'
)
%>%
layout
(
title
=
"Interactive Scatter Plot with Animation",
xaxis
=
list(title
=
"X-Axis"),
yaxis
=
list(title
=
"Y-Axis")
)
Step 8: Preview and Save
Render and view the interactive plot:
# Render the interactive animated plot
final_plot
# Save the plot as an HTML file
htmlwidgets
::saveWidget
(final_plot
,
"animated_scatter_plot.html")
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