Quote
What does 4e+05 mean for example, how do I read it?
4e+05= 4x 105= 400 000
have a nice day
I wasnt going to play around with a letter, even if its the prosperous letter of "R".
A nice day to you too, kind sir!
Topic: Price zones (Read 1651 times)
dear sir if you don't know that how are you going to play around using R ?
4e+05= 4x 105= 400 000
have a nice day
I wasnt going to play around with a letter, even if its the prosperous letter of "R".
A nice day to you too, kind sir!
Quote
What does 4e+05 mean for example, how do I read it?
4e+05= 4x 105= 400 000
have a nice day
Yea its just automatic scientific notation that R does. Like I said I wouldn't really try to put stock in any of those specific number values for volume because the smoothing takes averages. It is more just relative volume.
Quote
What does 4e+05 mean for example, how do I read it?
4e+05= 4x 105= 400 000
have a nice day
@bitcoinbitcoin123: That looks...interesting!
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
The volume is USD, the x axis I didn't make specific so they could be general. They are just number of timepoints gathered from bitcoin charts (either days or minutes,respectively). The heatmap volume should just be read as normalized to max volume in the period plotted. The actual numbers are hard to compare due to the kernel smoothing.
Ok, thanks but also:
Quote
What does 4e+05 mean for example, how do I read it?
@bitcoinbitcoin123: That looks...interesting!
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
The volume is USD, the x axis I didn't make specific so they could be general. They are just number of timepoints gathered from bitcoin charts (either days or minutes,respectively). The heatmap volume should just be read as normalized to max volume in the period plotted. The actual numbers are hard to compare due to the kernel smoothing.
OK, here is how to make ferroh charts with R:
chart 1:
chart 2:
chart 3:
Code:
#install.packages("fields")
require(fields)
##Format data##
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
##Smoothing Kernel Settings##
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-1
lower.cutoff.multiplier<-.1
##Create Heatmap Matrix##
price.range<-round(seq(min(price),max(price),by=.01),2)
heatmap<-matrix(nrow=length(time),ncol=length(price.range))
for (i in 1:length(time)){
heatmap[i,which(price.range==price[i])]<-volume[i]
}
heatmap[which(is.na(heatmap))]<-0
##Smooth the heatmap##
smooth.heatmap<-image.smooth(heatmap, dx=time.resolution, dy=price.resolution, Nwidth=, Mwidth=,
theta=FWHM, kernel.function=dnorm, tol= 1.1, na.rm=TRUE)
##Heatmap Chart Settings###
max.smoothedvolume<-max(smooth.heatmap$z)
lower.cutoff<-lower.cutoff.multiplier*max.smoothedvolume
number.of.color.bins<-100
colors<-c("White",rev(rainbow(number.of.color.bins-1)))
##Make Chart##
image.plot(time, price.range, as.matrix(smooth.heatmap$z),
breaks= c(0,seq(lower.cutoff, max.smoothedvolume, length=number.of.color.bins)),
col=colors,
ylab="USD/BTC", xlab="Time"
)
lines(time, price, lwd=1)
require(fields)
##Format data##
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
##Smoothing Kernel Settings##
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-1
lower.cutoff.multiplier<-.1
##Create Heatmap Matrix##
price.range<-round(seq(min(price),max(price),by=.01),2)
heatmap<-matrix(nrow=length(time),ncol=length(price.range))
for (i in 1:length(time)){
heatmap[i,which(price.range==price[i])]<-volume[i]
}
heatmap[which(is.na(heatmap))]<-0
##Smooth the heatmap##
smooth.heatmap<-image.smooth(heatmap, dx=time.resolution, dy=price.resolution, Nwidth=, Mwidth=,
theta=FWHM, kernel.function=dnorm, tol= 1.1, na.rm=TRUE)
##Heatmap Chart Settings###
max.smoothedvolume<-max(smooth.heatmap$z)
lower.cutoff<-lower.cutoff.multiplier*max.smoothedvolume
number.of.color.bins<-100
colors<-c("White",rev(rainbow(number.of.color.bins-1)))
##Make Chart##
image.plot(time, price.range, as.matrix(smooth.heatmap$z),
breaks= c(0,seq(lower.cutoff, max.smoothedvolume, length=number.of.color.bins)),
col=colors,
ylab="USD/BTC", xlab="Time"
)
lines(time, price, lwd=1)
chart 1:
Code:
##Smoothing Kernel Settings##
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-1
lower.cutoff.multiplier<-.1
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-1
lower.cutoff.multiplier<-.1
chart 2:
Code:
##Smoothing Kernel Settings##
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.00000001
price.resolution<-1
lower.cutoff.multiplier<-.1
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.00000001
price.resolution<-1
lower.cutoff.multiplier<-.1
chart 3:
Code:
##Smoothing Kernel Settings##
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-.00000001
lower.cutoff.multiplier<-.1
FWHM<-1 #Set size of smoothing kernal (in pixels)
time.resolution<-.01
price.resolution<-.00000001
lower.cutoff.multiplier<-.1
@bitcoinbitcoin123: That looks...interesting!
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
Would you mind helping me to read your scale correctly?
What does 4e+05 mean for example, how do I read it?
Is the volume displayed in USD (currency) or BTC?
How do I read your x-axis? Are those intervals weeks?
Would you mind adding dates to the x-axis?
This one may be better for intraday. Data is the last two days minute weighted price. Ferrohs is better but Im not sure how to accomplish that.
Code:
#install.packages(ggplot2) #only run the first time
require(ggplot2)
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
smoothing.bw<-5
smoothed.volume <- ksmooth(time, volume, "normal", bandwidth=smoothing.bw)$y
colors = c("Black",rev(rainbow(100)))
btcdata <- data.frame (time, price, volume, smoothed.volume)
# labeling positions
label <- seq(0,nrow(btcdata),by=50)
position <- seq(0,nrow(btcdata),by=50)
ggplot(btcdata,aes(x=time, colour= smoothed.volume)) +
geom_line(aes(y=price), size=.01, colour= "black") +
scale_colour_gradientn(colours = colors , guide= "colourbar") +
geom_point(aes(y=price, size=3*smoothed.volume/max(smoothed.volume))) +
scale_x_continuous(breaks=position,labels=label) +
opts(title = paste("Volume Smoothing Bandwidth=",smoothing.bw))+
opts(legend.position="none")
require(ggplot2)
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
smoothing.bw<-5
smoothed.volume <- ksmooth(time, volume, "normal", bandwidth=smoothing.bw)$y
colors = c("Black",rev(rainbow(100)))
btcdata <- data.frame (time, price, volume, smoothed.volume)
# labeling positions
label <- seq(0,nrow(btcdata),by=50)
position <- seq(0,nrow(btcdata),by=50)
ggplot(btcdata,aes(x=time, colour= smoothed.volume)) +
geom_line(aes(y=price), size=.01, colour= "black") +
scale_colour_gradientn(colours = colors , guide= "colourbar") +
geom_point(aes(y=price, size=3*smoothed.volume/max(smoothed.volume))) +
scale_x_continuous(breaks=position,labels=label) +
opts(title = paste("Volume Smoothing Bandwidth=",smoothing.bw))+
opts(legend.position="none")
That Ferroh chart is a good one. Here is a similar chart in R (not as pretty but more customizable).
First import data somehow. Here I just copy pasted from bitcoincharts.com into excel, then made a column of all commas to the right of each. Then I copied pasted that into a R script. There are better ways but I did this for now...
Code for making the chart:
First import data somehow. Here I just copy pasted from bitcoincharts.com into excel, then made a column of all commas to the right of each. Then I copied pasted that into a R script. There are better ways but I did this for now...
Code:
imported.data<-cbind(
weighted.price<-c(
0.05 ,
0.07 ,
0.09 ,
0.08 ,
0.07 ,
0.06 ,
0.06 ,
0.05 ,
0.05 ,
0.05 ,
0.06 ,
0.06 ,
0.07 ,
0.07 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.06 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.06 ,
0.07 ,
0.07 ,
0.07 ,
0.07 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.06 ,
0.08 ,
0.09 ,
0.1 ,
0.1 ,
0.09 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.1 ,
0.11 ,
0.11 ,
0.11 ,
0.15 ,
0.16 ,
0.18 ,
0.19 ,
0.19 ,
0.19 ,
0.19 ,
0.19 ,
0.19 ,
0.19 ,
0.21 ,
0.24 ,
0.29 ,
0.36 ,
0.32 ,
0.27 ,
0.2 ,
0.22 ,
0.26 ,
0.29 ,
0.28 ,
0.27 ,
0.25 ,
0.26 ,
0.27 ,
0.27 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.28 ,
0.25 ,
0.21 ,
0.21 ,
0.24 ,
0.25 ,
0.23 ,
0.21 ,
0.2 ,
0.22 ,
0.23 ,
0.21 ,
0.19 ,
0.22 ,
0.21 ,
0.22 ,
0.23 ,
0.24 ,
0.25 ,
0.25 ,
0.25 ,
0.24 ,
0.26 ,
0.25 ,
0.25 ,
0.25 ,
0.25 ,
0.25 ,
0.25 ,
0.26 ,
0.27 ,
0.29 ,
0.3 ,
0.29 ,
0.3 ,
0.3 ,
0.3 ,
0.29 ,
0.3 ,
0.3 ,
0.31 ,
0.31 ,
0.32 ,
0.32 ,
0.32 ,
0.34 ,
0.36 ,
0.39 ,
0.39 ,
0.39 ,
0.35 ,
0.32 ,
0.31 ,
0.35 ,
0.4 ,
0.43 ,
0.44 ,
0.41 ,
0.42 ,
0.41 ,
0.44 ,
0.43 ,
0.44 ,
0.46 ,
0.51 ,
0.74 ,
0.73 ,
0.71 ,
0.8 ,
0.86 ,
0.87 ,
0.86 ,
0.9 ,
0.96 ,
0.96 ,
0.99 ,
1.06 ,
1.05 ,
1.06 ,
1.05 ,
1.04 ,
1.04 ,
0.89 ,
0.91 ,
0.85 ,
0.84 ,
0.88 ,
0.9 ,
0.95 ,
0.96 ,
0.94 ,
0.93 ,
0.88 ,
0.95 ,
0.92 ,
0.92 ,
0.91 ,
0.88 ,
0.85 ,
0.89 ,
0.87 ,
0.85 ,
0.89 ,
0.89 ,
0.9 ,
0.9 ,
0.89 ,
0.88 ,
0.85 ,
0.84 ,
0.77 ,
0.76 ,
0.77 ,
0.75 ,
0.78 ,
0.83 ,
0.88 ,
0.88 ,
0.87 ,
0.83 ,
0.81 ,
0.79 ,
0.79 ,
0.79 ,
0.78 ,
0.79 ,
0.78 ,
0.69 ,
0.67 ,
0.72 ,
0.75 ,
0.76 ,
0.74 ,
0.74 ,
0.77 ,
0.85 ,
0.93 ,
0.95 ,
1 ,
1.04 ,
1.08 ,
1.15 ,
1.18 ,
1.16 ,
1.18 ,
1.29 ,
1.55 ,
1.67 ,
1.58 ,
1.67 ,
1.89 ,
2.03 ,
2.59 ,
3.29 ,
3.14 ,
3.24 ,
3.32 ,
3.44 ,
3.41 ,
3.48 ,
3.61 ,
3.77 ,
3.8 ,
4.74 ,
5.35 ,
5.83 ,
7.48 ,
7.86 ,
6.74 ,
7.77 ,
7.52 ,
7.14 ,
6.96 ,
6.28 ,
5.97 ,
6.47 ,
7.1 ,
7.23 ,
7.98 ,
8.55 ,
8.67 ,
8.45 ,
8.3 ,
8.72 ,
8.88 ,
9.21 ,
10.11 ,
13.08 ,
16.41 ,
17.32 ,
18.46 ,
19.9 ,
27.25 ,
29.58 ,
24.67 ,
17.61 ,
16.21 ,
20.11 ,
19.25 ,
19.68 ,
18.86 ,
15.51 ,
16.04 ,
17.77 ,
15.59 ,
17.01 ,
16.93 ,
16.88 ,
16.51 ,
15.9 ,
15.53 ,
15.48 ,
14.48 ,
12.8 ,
14.8 ,
15.16 ,
14.35 ,
14.39 ,
15.08 ,
14.37 ,
14.15 ,
14.03 ,
13.93 ,
13.9 ,
13.62 ,
13.34 ,
13.03 ,
14.04 ,
13.69 ,
13.66 ,
13.65 ,
13.64 ,
13.86 ,
14.2 ,
13.91 ,
13.96 ,
13.61 ,
13.51 ,
13.53 ,
13.52 ,
13.17 ,
12.39 ,
10.45 ,
10.58 ,
10.27 ,
7.82 ,
7.72 ,
7.74 ,
9.72 ,
10 ,
9.47 ,
9.32 ,
9.8 ,
10.61 ,
11.3 ,
11.05 ,
10.88 ,
10.9 ,
11.4 ,
11.49 ,
11.38 ,
11.03 ,
11.03 ,
10.94 ,
10.01 ,
8.65 ,
8.63 ,
8.97 ,
8.93 ,
8.78 ,
8.35 ,
8.22 ,
8.44 ,
8.53 ,
8.17 ,
7.62 ,
6.73 ,
7.03 ,
6.8 ,
5.31 ,
5.03 ,
6.07 ,
6.04 ,
5.84 ,
5.56 ,
4.98 ,
4.82 ,
4.81 ,
5.14 ,
5.29 ,
6.11 ,
5.63 ,
5.54 ,
5.61 ,
5.45 ,
5.41 ,
4.96 ,
4.92 ,
4.77 ,
4.74 ,
5.02 ,
5.05 ,
4.98 ,
4.97 ,
4.96 ,
4.9 ,
4.69 ,
4.29 ,
4.03 ,
4.19 ,
4.1 ,
3.95 ,
4.07 ,
4.08 ,
4.01 ,
3.89 ,
3.64 ,
2.85 ,
2.62 ,
2.28 ,
2.31 ,
2.54 ,
3.01 ,
3.08 ,
2.81 ,
2.74 ,
2.75 ,
2.92 ,
3.11 ,
3.54 ,
3.38 ,
3.19 ,
3.19 ,
3.23 ,
3.21 ,
3.13 ,
3.01 ,
2.96 ,
3 ,
3.09 ,
3 ,
2.87 ,
2.97 ,
3.06 ,
3 ,
2.51 ,
2.3 ,
2.46 ,
2.23 ,
2.14 ,
2.17 ,
2.28 ,
2.23 ,
2.31 ,
2.32 ,
2.42 ,
2.47 ,
2.48 ,
2.46 ,
2.51 ,
2.79 ,
2.91 ,
3.05 ,
3.1 ,
2.93 ,
2.75 ,
2.87 ,
2.98 ,
3 ,
2.95 ,
2.99 ,
3.04 ,
3.2 ,
3.18 ,
3.21 ,
3.12 ,
3.17 ,
3.18 ,
3.19 ,
3.2 ,
3.41 ,
3.97 ,
3.93 ,
3.79 ,
3.9 ,
3.92 ,
4.14 ,
4.04 ,
4.03 ,
4.14 ,
4.22 ,
4.19 ,
4.6 ,
5.1 ,
5.21 ,
4.95 ,
5.25 ,
6.2 ,
6.79 ,
6.72 ,
7.05 ,
6.47 ,
6.4 ,
6.81 ,
6.74 ,
6.61 ,
6.59 ,
6.9 ,
6.83 ,
6.04 ,
5.98 ,
6.18 ,
6.44 ,
6.29 ,
6.29 ,
6.31 ,
6.3 ,
5.88 ,
5.59 ,
5.29 ,
5.57 ,
5.48 ,
5.51 ,
5.53 ,
5.82 ,
6.03 ,
5.92 ,
5.92 ,
5.68 ,
5.55 ,
5.62 ,
5.64 ,
5.75 ,
5.88 ,
5.7 ,
5.6 ,
5.34 ,
4.7 ,
4.58 ,
4.19 ,
4.46 ,
4.27 ,
4.35 ,
4.37 ,
4.31 ,
4.44 ,
4.82 ,
4.98 ,
4.88 ,
4.96 ,
4.95 ,
4.87 ,
4.86 ,
4.94 ,
4.69 ,
4.68 ,
4.81 ,
4.95 ,
4.98 ,
4.93 ,
4.87 ,
4.9 ,
4.82 ,
4.91 ,
4.91 ,
5.16 ,
5.37 ,
5.33 ,
5.35 ,
5.32 ,
5.26 ,
4.88 ,
4.79 ,
4.82 ,
4.76 ,
4.7 ,
4.65 ,
4.5 ,
4.65 ,
4.67 ,
4.79 ,
4.77 ,
4.8 ,
4.89 ,
4.79 ,
4.94 ,
4.9 ,
4.93 ,
4.91 ,
4.94 ,
4.8 ,
4.72 ,
4.78 ,
4.83 ,
4.89 ,
4.89 ,
4.86 ,
4.98 ,
4.92 ,
4.95 ,
4.96 ,
5.08 ,
5.15 ,
5.23 ,
5.27 ,
5.18 ,
5.12 ,
5.07 ,
5.13 ,
5.08 ,
5.08 ,
4.96 ,
4.94 ,
4.94 ,
4.96 ,
5.08 ,
5.09 ,
5.12 ,
5.07 ,
5.05 ,
5.04 ,
5.03 ,
5.05 ,
4.96 ,
4.93 ,
4.95 ,
4.96 ,
4.99 ,
5.01 ,
5.07 ,
5.08 ,
5.1 ,
5.11 ,
5.12 ,
5.1 ,
5.08 ,
5.13 ,
5.12 ,
5.13 ,
5.12 ,
5.12 ,
5.13 ,
5.11 ,
5.14 ,
5.16 ,
5.24 ,
5.24 ,
5.22 ,
5.23 ,
5.39 ,
5.44 ,
5.5 ,
5.62 ,
5.57 ,
5.49 ,
5.51 ,
5.6 ,
5.86 ,
5.9 ,
6.12 ,
6.46 ,
6.33 ,
6.27 ,
6.44 ,
6.61 ,
6.69 ,
6.58 ,
6.5 ,
6.41 ,
6.32 ,
6.4 ,
6.53 ,
6.59 ,
6.63 ,
6.66 ,
6.6 ,
6.71 ,
6.55 ,
6.51 ,
6.65 ,
6.64 ,
6.77 ,
6.79 ,
6.9 ,
7.1 ,
7.11 ,
7.3 ,
7.63 ,
7.6 ,
7.58 ,
8.08 ,
8.34 ,
9.02 ,
9.09 ,
8.2 ,
8.88 ,
8.62 ,
8.46 ,
8.63 ,
8.59 ,
8.77 ,
8.89 ,
8.86 ,
8.77 ,
8.95 ,
9.24 ,
9.43 ,
10.13 ,
10.73 ,
11 ,
10.63 ,
10.9 ,
10.85 ,
11.04 ,
11.33 ,
11.41 ,
11.5 ,
11.64 ,
11.79 ,
12.09 ,
12.61 ,
13.23 ,
13.26 ,
11.87 ,
9.09 ,
9.53 ,
10.03 ,
9.86 ,
10 ,
10.27 ,
10.45 ,
10.55 ,
11.18 ,
10.9 ,
10.84 ,
10.76 ,
10.18 ,
10 ,
10.05 ,
10.35 ,
10.3 ,
10.75 ,
10.94 ,
11.1 ,
10.98 ,
11.05 ,
11.04 ,
11.11 ,
11.21 ,
11.34 ,
11.58 ,
11.71 ,
11.88 ,
11.9 ,
12.06 ,
12.41 ,
12.48 ,
12.27 ,
12.22 ,
12 ,
12.12 ,
12.11 ,
12.23 ,
12.32 ,
12.35 ,
12.4 ,
12.38 ,
12.39 ,
12.63 ,
12.84 ,
12.88 ,
12.75 ,
12.58 ,
12.01 ,
11.26 ,
11.97 ,
12.02 ,
12.03 ,
12.05 ,
11.96 ,
11.84 ,
11.72 ,
11.79 ,
11.88 ,
11.88 ,
11.76 ,
11.72 ,
11.68 ,
11.7 ,
11.73 ,
11.68 ,
11.03 ,
10.31 ,
10.38 ,
10.57 ,
10.65 ,
10.75 ,
11.02 ,
10.93 ,
10.58 ,
10.54 ,
10.67 ,
10.73 ,
10.8 ,
10.98 ,
10.92 ,
10.86 ,
10.85 ,
10.81 ,
10.99 ,
11 ,
10.95 ,
11.08 ,
11.49 ,
11.65
),
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),
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933.23 ,
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863.02 ,
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418.8 ,
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217005.56 ,
465280.45 ,
217804.23 ,
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286978.88 ,
257213.27 ,
123756.04 ,
425223.11 ,
497668.82 ,
297644.88 ,
471834.37 ,
499441.51 ,
121635.99 ,
204616.5 ,
835550.27 ,
1757815.81 ,
955210.08 ,
438703.58 ,
1267523.74 ,
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259113.81 ,
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353506.54 ,
555883.85 ,
283993.34 ,
237223.99 ,
143179.47 ,
100508.03 ,
458873.3 ,
648746.34 ,
647522.58 ,
1283817.64 ,
661588.16 ,
575464.3 ,
714863.7 ,
562801.91 ,
451978.45 ,
345666.89 ,
1153809.11 ,
725605.06 ,
250620.15 ,
353092.67 ,
637059.69 ,
532302.32 ,
725834.14 ,
1277714.19 ,
2930580.33 ,
1045361.51 ,
2170411.03 ,
1835053.01 ,
722740.27 ,
665544.84 ,
560012.6 ,
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420388.01 ,
277773.75 ,
1957673.34 ,
598168.05 ,
581687.69 ,
332208.84 ,
690452.97 ,
233777.63 ,
251932.43 ,
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359404.18 ,
653374.16 ,
733288.22 ,
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155002.6 ,
467067.67 ,
721708.44 ,
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494030.03 ,
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272640.88 ,
259113.16 ,
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279843.08 ,
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258957.79 ,
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178761.66 ,
233650.36 ,
291515.94 ,
348474.7 ,
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669422.19 ,
160662.83
)
)
Code for making the chart:
Code:
#install.packages("ggplot2") #only run the first time
require(ggplot2)
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
smoothing.bw<-7 # Set volume smoothing bandwidth (here 1 week)
smoothed.volume <- ksmooth(time, volume, "normal", bandwidth=smoothing.bw)$y #Calculate smoothed volume
colors = c("Black", rev(rainbow(100)), "Red") # Set heat colors
btcdata <- data.frame (time, price, volume, smoothed.volume)
# Set x axis labels
label <- seq(0,nrow(btcdata),by=50)
position <- seq(0,nrow(btcdata),by=50)
ggplot(btcdata,aes(x=time, colour= smoothed.volume)) +
scale_colour_gradientn(colours = colors , guide= "colourbar") +
geom_line(aes(y=price), size=2) + # plot the line
scale_x_continuous(breaks=position,labels=label) +
opts(title = paste("Volume Smoothing Bandwidth=",smoothing.bw))
require(ggplot2)
price <- imported.data[,1] # for line plot
volume <- imported.data[,2] # for line color heatmap
time <- 1:length(price) # X axis
smoothing.bw<-7 # Set volume smoothing bandwidth (here 1 week)
smoothed.volume <- ksmooth(time, volume, "normal", bandwidth=smoothing.bw)$y #Calculate smoothed volume
colors = c("Black", rev(rainbow(100)), "Red") # Set heat colors
btcdata <- data.frame (time, price, volume, smoothed.volume)
# Set x axis labels
label <- seq(0,nrow(btcdata),by=50)
position <- seq(0,nrow(btcdata),by=50)
ggplot(btcdata,aes(x=time, colour= smoothed.volume)) +
scale_colour_gradientn(colours = colors , guide= "colourbar") +
geom_line(aes(y=price), size=2) + # plot the line
scale_x_continuous(breaks=position,labels=label) +
opts(title = paste("Volume Smoothing Bandwidth=",smoothing.bw))
supports/resistances usually form around areas of high volume spent. Ferroh's chart provides a very handy tool to identify those zone:
https://ferroh.com/charts
Maybe that can help you improve your chart further.
for the volume is do use the SC feature for volume bar chart, here http://twitpic.com/be1d0r/full a example, this chart does have 10 000 volume per bar, I pick 10k per bar because is the minimum volume to get a decent move in price above daily ATR https://ferroh.com/charts
Maybe that can help you improve your chart further.
supports/resistances usually form around areas of high volume spent. Ferroh's chart provides a very handy tool to identify those zone:
https://ferroh.com/charts
Maybe that can help you improve your chart further.
https://ferroh.com/charts
Maybe that can help you improve your chart further.
Hello /spec/ I know that some people use this strategy on their trading, they use past price action to see where is likely to a reversal, resistance or support
This is my poor attempt to mark some of this zones http://twitpic.com/bdukku/full on a daily chart
This is my poor attempt to mark some of this zones http://twitpic.com/bdukku/full on a daily chart
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