I'm using Core Plot to draw graphs in my app.
I just encountered a problem:
I have dates on the X-Axis and I use a custom labeling policy.
If I only have a few records everything works fine
If I have many records all the labels are near and not useful :-(
So the question is: How can I decide which values display and which not to always have 10 labels, separated one from the other.
Divide the number of points by the number of labels you want and round up. For example, if you have 25 data points and want roughly 10 labels, label every third data point. You'll end up with 9 evenly spaced labels.
Related
My pandas dataset has velocity curves for different trials of an experiment and for different conditions ('shifts'). I want to plot the velocity lines for each trial in the same facet per condition, but without specifying that I want the trials to influence a style they are just plotted in one continuous line, where the end of the first is connected to the start of the second line, and so on. This also means I can't use alpha values to see where the velocity curves are most dense, because it's just one big line. Is there a way to separate them?
this is what it looks like without separation
this is what it's supposed to look like, just not with different hues for each line
This is the code I used for the second example
grid = sns.FacetGrid(half_second_df, col='shift', hue='trial', col_wrap=3)
grid.map(plt.plot, 't_rel_sacc', 'yaw_velo', linewidth=0.5, alpha=0.3)
I want to plot 5 different data frames in 1 plot. Containing the same measurement but done at different times. The plot should share the x-Axis for all measurement.
First thing i did was to calculate the time between the measurement points. It differs between 5-10 ms but sometimes also big gaps of 200 ms.
Then i calculated the running sum over this column. Then i set this column as the index (dtype "timedelta64[ns]")
Now i want to plot those 5 times.series in one plot which share the x-Axis (as time in ms)
But i don´t now how because they have almost no common index together. The plot should have one common x-Axis from 0-3 seconds containing the 5 measurements.
Thank you!
2 Example DataFrames:
example for measuremt01
example for measuremt02
Is it possible to have 2 category axis(x -axis) values one with bar and other with line and one measure for both? If possible please let me know how to achieve it.
Thanks
Niki
Multiple Y-axis are possible, but you can only have one X-axis per chart. That said, you can have an X-axis with multiple dimensions on it (e.g. City and State).
Each measure will be plotted (aggregated) according to the dimensions added to the X-axis.
You cannot have different visualisations for the same measure on the same chart (e.g. a column and a line for the same measure), unless you have a chart with 2 Y-axis. Whether this would be a good visualisation of your data is a different matter.
I have a lineplot with 2 lines on it...they're two separate channels from the same data set. Would love to just label each one - the "labels" options are all about giving a number for each point on your plot, and that is simply not helpful.
Would love to know how to do any (really, all, but I just need to do one to be happy) of these:
plot each against its own y axis and be able to sensibly label that axis with units (and color the numbers to correspond to the data it correlates to)
put a legend on it. I can't figure out how to use lineLegend
just put any kind of (singular) label in the vicinity of the lines.
I'm stuck with the following problem and I hope I can explain it coherent.
So, I have a number (about 10) of descrete positions on a coordinate system.
Now, I want to analyse data from a program where user could label each point as somethingA and somethingB.
I extracted the data points for each class. So I have about 60 points for the somethingA class and a little bit less for the other class. One class stands for good points and one for bad points. I want to find the positions which have the most good/bad labels. I do that with machine learning algorithms, I just want to visualize this with plots.
I now want to plot those points. So I make one plot per class. But since in every class every point occurs at least once, the two plots would look exactly the same.
But, the amount of occurences has a different distribution thoughout the positions.
Maybe point A has 20 occurences in class A and 1 in class B, both plots would look the same.
So, my question is: How can I take the number of occurences for points into account when plotting scatters in Matplotlib?
Either with different colors (like a heatmap?) maybe with a cool legend.
Or with different sizes (e.g. higher amount = bigger cirlce).
Any help would be appreciated!
I don't know if this helps you but I have had a problem where I wanted a scatterplot to reflect both positions as well as two variables that were attributed to the data points.
Since size and color in the scatter function do not allow variables themselves, meaning one has to specify color code and size in the usual way, meaning sth like
ax.scatter(..., c=whatEverFunction, s=numberOfOccurences, ...)
did not work for me.
what I did was to bin the values of the two variables I wanted to visualize. In my case the variable nodeMass and another variable.
for i in range(Number):
mask[i] = False
if(lowerBound1<variableOne[i]<upperBound1):
mask[i] = True & pmask[i]
if len(positionX[mask])>0:
ax.scatter(positionX[mask], positionY[mask], positionZ[mask],C='#424242',s=10, edgecolors='none')
for i in range(Number):
mask[i] = False
if(lowerBound2<variableOne[i]<upperBound2):
mask[i] = True & pmask[i]
if len(positionX[mask])>0:
ax.scatter(positionX[mask], positionY[mask], positionZ[mask],c='#9E0050',s=25,edgecolors='none')
I know it is not very elegant but it worked for me. I had to make as many for loops as I had bins in my variables. With if-querys and the masks I could at least avoid redundant or 'unreadable' plots.