Hi, I have two columns of data. They are over the same time period but column one generates data every 1000ms, and column 2 generates data every 500ms. How can i plot them on the same graph looking of equal length. The x-axis doesnt have to be "Time". Thank you.
plt.rcParams['figure.figsize'] = [40,20]
x = df['Time']
y1 = df['Engine RPM']
y2 = df['FMS RPM']
plt.plot(x,y1,color='r', label='column1',linewidth=2)
plt.plot(x,y2,color='b', label='column2',linewidth=2)
I can have both lines looking equal using the following code, but on seperate graphs.
x = np.linspace(0, 100,100)
x2 = np.linspace(0,200,200)
f, ((ax1, ax2)) = plt.subplots(2)
y1 = df['Engine RPM']
y2 = df1['FMS RPM']
ax1.plot(x,y1, label = 'column1')
ax2.plot(x2,y2, label = 'column2')
Try this:
x = np.linspace(0, 100,100)
x2 = np.linspace(0,200,200)
f, ax = plt.subplots(1,1)
ax2 = ax1.twiny()
ax.plot(x,y1,color='r', label='column1',linewidth=2)
ax2.plot(x,y2,color='b', label='column2',linewidth=2)
Related
Matrix values (zz) are not shown on the output. How can I fix this problem ?
fig = make_subplots(rows=1, cols=2)
# matrix
zz = [[0.1,0.2],
[0.2,0.3]]
#labels
names = ["No", "Yes"]
fig1 = ff.create_annotated_heatmap(zz, x = names, y = names)
fig2 = ff.create_annotated_heatmap(zz, x = names, y = names)
fig.add_trace(fig1.data[0], 1, 1)
fig.add_trace(fig2.data[0], 1, 2)
fig.show()
I want to combine a bar and line plot and label line plot.
This is what I got: plot
this is my code:
df %>%
ggplot(aes(reorder(NAME, pval),y = pval)) +
geom_col(aes(x = NAME, y = pval), size = 1, color = "royalblue", fill = "white") +
geom_line(aes(x = NAME, y = 10*Ratio), size = 1.5, color="#c4271b", group = 1) + geom_text(aes(label = Ratio))+coord_flip()
I want to label line plot, but the bar plot gets the labels?
My second question:
How to rearrange the y-axis from the largest -log(pvalue) to lowest one?
Any help will be really appreciated!
try set the x and y aes in geom_text() with the same in geom_line()
geom_text(aes(x = NAME, y = 10*Ratio, label = Ratio))
I have a Julia DataFrame where the first 4 columns are dimensions and the 5th one contains the actual data.
I would like to plot it using a subplots approach where the two main plot axis concern the first two dimensions and each subplot then is a contour plot over the remaining two dimensions.
I am almost there with the above code:
using DataFrames,Plots
# plotlyjs() # doesn't work with plotlyjs backend
pyplot()
X = [1,2,3,4]
Y = [0.1,0.15,0.2]
I = [2,4,6,8,10,12,14]
J = [10,20,30,40,50,60]
df = DataFrame(X=Int64[], Y=Float64[], I=Float64[], J=Float64[], V=Float64[] )
[push!(df,[x,y,i,j,(5*x+20*y+2)*(0.2*i^2+0.5*j^2+3*i*j+2*i^2*j+1)]) for x in X, y in Y, i in I, j in J]
minvalue = minimum(df[:V])
maxvalue = maximum(df[:V])
function toDict(df, dimCols, valueCol)
toReturn = Dict()
for r in eachrow(df)
keyValues = []
[push!(keyValues,r[d]) for d in dimCols]
toReturn[(keyValues...)] = r[valueCol]
end
return toReturn
end
dict = toDict(df, [:X,:Y,:I,:J], :V )
M = [dict[(x,y,i,j)] for j in J, i in I, y in Y, x in X ]
yL = length(Y)
xL = length(X)
plot(contour(M[:,:,3,1], ylabel="y = $(string(Y[3]))", zlims=(minvalue,maxvalue)), contour(M[:,:,3,2]), contour(M[:,:,3,3]), contour(M[:,:,3,4]),
contour(M[:,:,2,1], ylabel="y = $(string(Y[2]))", zlims=(minvalue,maxvalue)), contour(M[:,:,2,2]), contour(M[:,:,2,3]), contour(M[:,:,2,4]),
contour(M[:,:,1,1], ylabel="y = $(string(Y[1]))", xlabel="x = $(string(X[1]))"), contour(M[:,:,1,2], xlabel="x = $(string(X[2]))"), contour(M[:,:,1,3], xlabel="x = $(string(X[3]))"), contour(M[:,:,3,4], xlabel="x = $(string(X[4]))"),
layout=(yL,xL) )
This produces:
I remain however with the following concerns:
How do I automatize the creation of each subplot in the subplot call ? Do I need to write a macro ?
I would like each subplot to have the same limits in the z axis, but zlims seems not to work. Is zlims not yet supported ?
How do I hide the legend on the z axis on each subplot and plot it instead apart (best would be on the right side of the main/total plot) ?
EDIT:
For the first point I don't need a macro, I can create the subplots in a for loop, add them in a array and pass the array to the plot() call using the ellipsis operator:
plots = []
for y in length(Y):-1:1
for x in 1:length(X)
xlabel = y == 1 ? "x = $(string(X[x]))" : ""
ylabel = x==1 ? "y = $(string(Y[y]))" : ""
println("$y - $x")
plot = contour(I,J,M[:,:,y,x], xlabel=xlabel, ylabel=ylabel, zlims=(minvalue,maxvalue))
push!(plots,plot)
end
end
plot(plots..., layout=(yL,xL))
I have created the best fit lines for the dataset using the following code:
fig, ax = plt.subplots()
for dd,KK in DATASET.groupby('Z'):
fit = polyfit(x,y,3)
fit_fn = poly1d(fit)
ax.plot(KK['x'],KK['y'],'o',KK['x'], fit_fn(KK['x']),'k',linewidth=4)
ax.set_xlabel('x')
ax.set_ylabel('y')
The graph displays the best fit line for each group of Z. I want print the equation of the best fit line on top of the line.Please suggest what can i do out here
So you need to write some function that convert a poly parameters array to a latex string, here is an example:
import pylab as pl
import numpy as np
x = np.random.randn(100)
y = 1 + 2 * x + 3 * x * x + np.random.randn(100) * 2
poly = pl.polyfit(x, y, 2)
def poly2latex(poly, variable="x", width=2):
t = ["{0:0.{width}f}"]
t.append(t[-1] + " {variable}")
t.append(t[-1] + "^{1}")
def f():
for i, v in enumerate(reversed(poly)):
idx = i if i < 2 else 2
yield t[idx].format(v, i, variable=variable, width=width)
return "${}$".format("+".join(f()))
pl.plot(x, y, "o", alpha=0.4)
x2 = np.linspace(-2, 2, 100)
y2 = np.polyval(poly, x2)
pl.plot(x2, y2, lw=2, color="r")
pl.text(x2[5], y2[5], poly2latex(poly), fontsize=16)
Here is the output:
Here's a one liner.
If fit is the poly1d object, while plotting the fitted line, just use label argument as bellow,
label='y=${}$'.format(''.join(['{}x^{}'.format(('{:.2f}'.format(j) if j<0 else '+{:.2f}'.format(j)),(len(fit.coef)-i-1)) for i,j in enumerate(fit.coef)]))
I have two time series (ts-variables) with different time length. It’s yearly data and they are stored as separate ts.objects. The first series starts in 1936 and the other starts in 1943 and both ends in 2012. Problem: I cannot find the R-script (commands) for plotting these series in one, single, nice figure which includes all observations. Great if someone can help.
Regards
If the data are on a comparable scale then you just need to set the x-axis limits to the range of the entire data, e.g.
set.seed(2) ## reproducible
dat1 <- data.frame(Year = seq(1936, 2012, by = 1), Y = runif(77))
dat2 <- data.frame(Year = seq(1943, 2012, by = 1), Y = runif(70))
ylim <- range(dat1$Y, dat2$Y)
xlim <- range(dat1$Year, dat2$Year)
plot(Y ~ Year, data = dat1, type = "l", col = "red", xlim = xlim,
ylim = ylim)
lines(Y ~ Year, data = dat2, type = "l", col = "blue")
I'll leave you to prettify the plot.
Just noticed you said ts variables, so the following will work too
ts1 <- ts(runif(77), start = 1936, freq = 1)
ts2 <- ts(runif(70), start = 1943, freq = 1)
xlim <- c(1936, 2012)
ylim <- range(ts1, ts2)
plot(ts1, ylim = ylim, xlim = xlim, col = "red")
lines(ts2, col = "blue")
With your data, replace runif(n) with the real data for the two time series.