scatter

I am having trouble making a scatter plot that has from a date array and a bunch of PM 2.5 values. My lists would look like the following: dates = ['2015-12-20','2015-09-12'] PM_25 = [80, 55] import pandas as pd dates = ['2015-12-20','2015-09-12'] PM_25 = [80, 55] dates = [pd.to_datetime(d) for d in dates] plt.scatter(dates, PM_25, s =100, c = 'red') s sets the size c sets the color There are a whole bunch of other args as well: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter If a plot with data that contains dates, you can use plot_date Similar to the plot() command,

I have a 1D-array representation of a 2D array: below is a 6x6 example: [00000012300456700890100234500000] => [------] [|0123|] [|4567|] [|8901|] [|2345|] [------] A typical size will be 514*514 elements (512 + 2 halo cells). I have to distribute the data among, say, four processors: Rank 0: Rank 1: Rank 2: Rank 3: [----] [----] [|456] [567|] [|012] [123|] [|890] [901|] [|456] [567|] [|234] [345|] [|890] [901|] [----] [----] that is, in a way that the rightmost section of the data that goes to rank 0 also has to go to the left section of the data going to rank 1, and so on with all other pairs

I would like to change the color of dots in top left part of the scatterplot. I wrote a macro, no errors occurred but the color did not change :/ Sub Kolorowanie() ActiveSheet.ChartObjects("Chart 1").Activate a = ActiveChart.SeriesCollection(1).Values b = ActiveChart.SeriesCollection(1).XValues For i = LBound(a) To UBound(a) If a(i) < 0 And b(i) > 0 Then ActiveSheet.ChartObjects("Chart 1").Activate ActiveChart.SeriesCollection(1).Select ActiveChart.SeriesCollection(1).Points(i).Select With Selection.Format.Fill .Visible = msoTrue .ForeColor.RGB = RGB(255, 0, 0) .Solid End With Else End If Next

I am trying to modify the color/thickness of a specific gridline in a 3D matplotlib scatter plot, in this case I want the -30 z axis grid line to be black, bold, or thickened so it stands out amongst the other gridlines. Here is the basic code seen from the mplot3d scatter plot tutorial: import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt def randrange(n, vmin, vmax): return (vmax-vmin)*np.random.rand(n) + vmin fig = plt.figure() ax = fig.add_subplot(111, projection='3d') n = 100 for c, m, zl, zh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]: xs =

I am basically plotting several million data points with help of scatterplot. here I am doing scatter(x(1:end-1), y(1:end-1),5, z) Now is possible to select a particular area in the plot...and find out the values. I dont know if you will understand my question or not. As an alternative is it possible to reduce the datapoints from the beginning itself, so that those dont come in my calculation. I am using following to read the data fid = fopen('cr.txt'); A = textscan(fid, '%f %f %f %f %f %*f %*f %*f %*f %*f %*s %*s %*s') ; %read the file a = A{1}; e = A{2}; c = A{3}; x = A{4}; y = A{5}; here x

I want to plot the location of some disks generated randomly on a scatter plot, and see whether the disks are 'connected' to each other. For this, I need to set the radius of each disk fixed/linked to the axis scale. The 's' parameter in the plt.scatter function uses points, so the size is not fixed relative to the axis. If I dynamically zoom into the plot, the scatter marker size remains constant on the plot and does not scale up with the axis. How do I set the radius so they have a definite value (relative to the axis)? Schorsch Instead of using plt.scatter , I suggest using patches.Circle