Understanding Matplotlib Scatter
Our analysis in this article will concentrate on the Matplotlib scatter plot and its many features, such as customizing markers, colors, and labels, as well as displaying annotations and legends on the plot.
Table Of Content-
- Understanding Matplotlib Scatter:
- Matplotlib Scatter Plots – Create One:
- Now Compare Plots:
- Matplotlib Scatter Colors:
- Color Each Dot:
- Marker ColorMaps:
- How to Use ColorMap?:
- Accent:
- Accent_r:
- Blues:
- Blues_r:
- BrBG:
- BrBG_r:
- BuGn:
- BuGn_r:
- BuPu:
- BuPu_r:
- CMRmap:
- CMRmap_r:
- Dark2:
- Dark2_r:
- GnBu:
- GnBu_r:
- Greens:
- Greens_r:
- Greys:
- Greys_r:
- OrRd:
- OrRd_r:
- Oranges:
- Oranges_r:
- PRGn:
- PRGn_r:
- Paired:
- Paired_r:
- Pastel1:
- Pastel1_r:
- Pastel2:
- Pastel2_r:
- PiYG:
- PiYG_r:
- PuBu:
- PuBu_r:
- PuBuGn:
- PuBuGn_r:
- PuOr:
- PuRd_r:
- Purples:
- Purples_r:
- RdBu:
- RdBu_r:
- RdGy:
- RdGy_r:
- RdPu:
- RdPu_r:
- RdYlBu:
- RdYlBu_r:
- RdYlGn:
- RdYlGn_r:
- Reds:
- Reds_r:
Matplotlib Scatter Plots – Create One
To create a Matplotlib scatter plot, we use the scatter() function.
It is possible to plot one dot for each data point by calling the Matplotlib scatter() function.
The scatter() function takes two arrays of data as input:
- one for the x-values.
- one for the y-values.
Below are examples of how to create a simple Matplotlib scatter plots.
Generate a basic scatter graph:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([5, 34, 3, 2, 21, 13, 8])
random_num = npy.array([22,8,37,17,29,3,46])
pt.scatter(random_fibionacci, random_num)
pt.show()
Utilize the prime number array in the below example:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([74,3,61,22,5,39,16,41,19,35,51])
prime = npy.array([17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59])
pt.scatter(random_num, prime)
pt.show()
In the example above, there are 11 numbers that make up the Matplotlib scatter.
Random numbers are plotted along the X-axis.
Prime numbers are plotted on the Y-axis.
The scatter plot indicates that there is no clear connection between the random_num values and the prime values.
Now Compare Plots
In the Matplotlib scatter example above, there looks not to be a relationship between prime numbers and random numbers, but what if we display results from another day?
What else can we learn from the scatter plot?
Utilize the prime number array in the below example:
Example:
import matplotlib.pyplot as pt
import numpy as npy
#graph1
random_fibionacci = npy.array([5, 34, 3, 2, 21, 13, 8])
random_num = npy.array([22,8,37,17,29,3,46])
pt.scatter(random_fibionacci, random_num)
#graph2
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
pt.scatter(random_fibionacci, random_num)
pt.show()
Utilize the prime number array in the below example:
Example:
import matplotlib.pyplot as pt
import numpy as npy
#graph1
random_num = npy.array([74,3,61,22,5,39,16,41,19,35,51])
prime = npy.array([17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59])
pt.scatter(random_num, prime)
#graph2
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
pt.scatter(random_num, prime)
pt.show()
Reminder: The two graphs are displayed with two distinct colors, by default blue and orange. You will find out how to modify the colors after exploring Matplotlib scatter later in this chapter.
Matplotlib Scatter Colors
If you’re working with Matplotlib scatter, you can provide your own color through the color or c argument.
You can choose the color of the markers:
Example:
import matplotlib.pyplot as pt
import numpy as npy
#graph1
random_fibionacci = npy.array([5, 34, 3, 2, 21, 13, 8])
random_num = npy.array([22,8,37,17,29,3,46])
pt.scatter(random_fibionacci, random_num, color = 'Red')
#graph2
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
pt.scatter(random_fibionacci, random_num, color = 'PowderBlue')
pt.show()
In the following example first place the argument c then apply the different color in code form:
Example:
import matplotlib.pyplot as pt
import numpy as npy
#graph1
random_num = npy.array([74,3,61,22,5,39,16,41,19,35,51])
prime = npy.array([17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59])
pt.scatter(random_num, prime, c = '#d2a679')
#graph2
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
pt.scatter(random_num, prime, c = '#993366')
pt.show()
Color Each Dot
With Matplotlib scatter, you can also assign a particular color for each dot by utilizing an array of colors as a value for c argument:
Reminder: Utilizing the color argument will not work, only the c argument will.
Customize each marker color:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
mrx_colors = npy.array(["yellow","black","orange","purple","beige","gray","cyan","magenta"])
pt.scatter(random_fibionacci, random_num, c = mrx_colors)
pt.show()
Provide different colors for data points:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array(["Maroon","LightSalmon","MidnightBlue","yellow","cyan","magenta","PaleGreen","black","PeachPuff","purple","RebeccaPurple","Lime","gray"])
pt.scatter(random_num, prime, c = mrx_colors)
pt.show()
Marker ColorMaps
There are a variety of colormaps accessible in the Matplotlib module OR Matplotlib scatter.
When working with Matplotlib scatter, a colormap is similar to a list of colors with values ranging from 0 to 100.
Colormap example:
In this colormap, we can observe that it ranges from 0, which is a blue color, all the way upto 100, which is a yellow color, and this colormap is known as plasma.
How to Use ColorMap?
Matplotlib offers several built-in colormaps, including ‘plasma‘, which is one of them. The colormap can be provided with the keyword argument cmap.
Moreover, you have to generate an array with values (from 0 to 100), each value per scatter plot point in Matplotlib scatter.
In the scatter graph, construct a color array and provide a colormap:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
mrx_colors = npy.array([0,15,38,62,25,54,73,86])
pt.scatter(random_fibionacci, random_num, c = mrx_colors, cmap = 'plasma')
pt.show()
Implement the cmap argument then utilize the ‘plasma‘ colormap:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'plasma')
pt.show()
If you want to display the colormap in your graph, simply invoke the pt.colorbar() statement when you apply Matplotlib scatter:
Insert the ‘plasma’ colormap bar in the below example:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
mrx_colors = npy.array([0,15,38,62,25,54,73,86])
pt.scatter(random_fibionacci, random_num, c = mrx_colors, cmap = 'plasma')
pt.colorbar()
pt.show()
In the following example, display the ‘hsv‘ colormap by applying pt.colorbar():
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'hsv')
pt.colorbar()
pt.show()
The Matplotlib scatter package comes with a number of built-in colormaps that you can select from.
Here is a list of all 162 built-in colormaps in Matplotlib:
| Color Maps | Overview |
| Accent | A qualitative colormap with bright colors. |
| Accent_r | The reverse of the Accent colormap. |
| Blues | A sequential colormap that goes from light to dark blue. |
| Blues_r | The reverse of the Blues colormap. |
| BrBG | A diverging colormap that goes from brown to green to blue. |
| BrBG_r | The reverse of the BrBG colormap. |
| BuGn | A sequential colormap that goes from light blue to dark green. |
| BuGn_r | The reverse of the BuGn colormap. |
| BuPu | A sequential colormap that goes from light blue to dark purple. |
| BuPu_r | The reverse of the BuPu colormap. |
| CMRmap | A colormap that goes from black to red to yellow to white. |
| CMRmap_r | The reverse of the CMRmap colormap. |
| Dark2 | A qualitative colormap with dark colors. |
| Dark2_r | The reverse of the Dark2 colormap. |
| GnBu | A sequential colormap that goes from green to blue. |
| GnBu_r | The reverse of the GnBu colormap. |
| Greens | A sequential colormap that goes from light to dark green. |
| Greens_r | The reverse of the Greens colormap. |
| Greys | A sequential colormap that goes from black to white. |
| Greys_r | The reverse of the Greys colormap. |
| OrRd | A sequential colormap that goes from orange to red. |
| OrRd_r | The reverse of the OrRd colormap. |
| Oranges | A sequential colormap that goes from light orange to dark orange. |
| Oranges_r | The reverse of the Oranges colormap. |
| PRGn | A diverging colormap that goes from purple to green. |
| PRGn_r | The reverse of the PRGn colormap. |
| Paired | A qualitative colormap with paired colors. |
| Paired_r | The reverse of the Paired colormap. |
| Pastel1 | A qualitative colormap with pastel colors. |
| Pastel1_r | The reverse of the Pastel1 colormap. |
| Pastel2 | A qualitative colormap with pastel colors. |
| Pastel2_r | The reverse of the Pastel2 colormap. |
| PiYG | A diverging colormap that goes from pink to green. |
| PiYG_r | The reverse of the PiYG colormap. |
| PuBu | A sequential colormap that goes from purple to blue. |
| PuBuGn | A sequential colormap that goes from purple to blue to green. |
| PuBuGn_r | The reverse of the PuBuGn colormap. |
| PuBu_r | The reverse of the PuBu colormap. |
| PuOr | A diverging colormap that goes from purple to orange. |
| PuOr_r | The reverse of the PuOr colormap. |
| PuRd | A sequential colormap that goes from purple to red. |
| PuRd_r | The reverse of the PuRd colormap. |
| Purples | A sequential colormap that goes from light to dark purple. |
| Purples_r | The reverse of the Purples colormap. |
| RdBu | A diverging colormap that goes from red to blue. |
| RdBu_r | The reverse of the RdBu colormap. |
| RdGy | A diverging colormap that goes from red to white to blue. |
| RdGy_r | The reverse of the RdGy colormap. |
| RdPu | A sequential colormap that goes from red to purple. |
| RdPu_r | The reverse of the RdPu colormap. |
| RdYlBu | A diverging colormap that goes from red to yellow to blue. |
| RdYlBu_r | The reverse of the RdYlBu colormap. |
| RdYlGn | A diverging colormap that goes from red to yellow to green. |
| RdYlGn_r | The reverse of the RdYlGn colormap. |
| Reds | A sequential colormap that goes from light to dark red. |
| Reds_r | The reverse of the Reds colormap. |
| Set1 | A qualitative colormap with distinct colors. |
| Set1_r | The reverse of the Set1 colormap. |
| Set2 | A qualitative colormap with distinct colors. |
| Set2_r | The reverse of the Set2 colormap. |
| Set3 | A qualitative colormap with distinct colors. |
| Set3_r | The reverse of the Set3 colormap. |
| Spectral | A diverging colormap that goes from red to yellow to green to blue. |
| Spectral_r | The reverse of the Spectral colormap. |
| Wistia | A sequential colormap that goes from light yellow to dark yellow. |
| Wistia_r | The reverse of the Wistia colormap. |
| YlGn | A sequential colormap that goes from light yellow to dark green. |
| YlGnBu | A sequential colormap that goes from light yellow to blue to dark green. |
| YlGnBu_r | The reverse of the YlGnBu colormap. |
| YlGn_r | The reverse of the YlGn colormap. |
| YlOrBr | A sequential colormap that goes from light yellow to dark brown. |
| YlOrBr_r | The reverse of the YlOrBr colormap. |
| YlOrRd | A sequential colormap that goes from light yellow to dark red. |
| YlOrRd_r | The reverse of the YlOrRd colormap. |
| afmhot | A sequential colormap that goes from black to red to yellow to white. |
| afmhot_r | The reverse of the afmhot colormap. |
| autumn | A sequential colormap that goes from red to yellow to brown. |
| autumn_r | The reverse of the autumn colormap. |
| binary | A colormap that goes from black to white. |
| binary_r | The reverse of the binary colormap. |
| bone | A sequential colormap that goes from black to white with a blue tint. |
| bone_r | The reverse of the bone colormap. |
| brg | A colormap that goes from blue to red to green. |
| brg_r | The reverse of the brg colormap. |
| bwr | A diverging colormap that goes from blue to white to red. |
| bwr_r | The reverse of the bwr colormap. |
| cividis | A sequential colormap that goes from blue to yellow to green. |
| cividis_r | The reverse of the cividis colormap. |
| cool | A sequential colormap that goes from cyan to magenta. |
| cool_r | The reverse of the cool colormap. |
| coolwarm | A diverging colormap that goes from blue to white to red. |
| coolwarm_r | The reverse of the coolwarm colormap. |
| copper | A sequential colormap that goes from black to brown. |
| copper_r | The reverse of the copper colormap. |
| cubehelix | A sequential colormap that goes from black to red to yellow to white. |
| cubehelix_r | The reverse of the cubeh. |
| flag | A colormap that goes from red to white to blue. |
| flag_r | The reverse of the flag colormap. |
| gist_earth | A sequential colormap that goes from brown to green to blue. |
| gist_earth_r | The reverse of the gist_earth colormap. |
| gist_gray | A sequential colormap that goes from black to white. |
| gist_gray_r | The reverse of the gist_gray colormap. |
| gist_heat | A sequential colormap that goes from black to yellow to red. |
| gist_heat_r | The reverse of the gist_heat colormap. |
| gist_ncar | A qualitative colormap with distinct colors. |
| gist_ncar_r | The reverse of the gist_ncar colormap. |
| gist_rainbow | A qualitative colormap with distinct colors. |
| gist_rainbow_r | The reverse of the gist_rainbow colormap. |
| gist_stern | A sequential colormap that goes from blue to white to red. |
| gist_stern_r | The reverse of the gist_stern colormap. |
| gist_yarg | A sequential colormap that goes from black to white with a blue tint. |
| gist_yarg_r | The reverse of the gist_yarg colormap. |
| gnuplot | A sequential colormap that goes from yellow to red to purple. |
| gnuplot2 | A sequential colormap that goes from blue to green to yellow to red to purple. |
| gnuplot2_r | The reverse of the gnuplot2 colormap. |
| gnuplot_r | The reverse of the gnuplot colormap. |
| gray | A sequential colormap that goes from black to white. |
| gray_r | The reverse of the gray colormap. |
| hot | A sequential colormap that goes from black to red to yellow to white. |
| hot_r | The reverse of the hot colormap. |
| hsv | A colormap that goes from red to yellow to green to blue to purple to red. |
| hsv_r | The reverse of the hsv colormap. |
| inferno | A sequential colormap that goes from black to yellow to red to purple. |
| inferno_r | The reverse of the inferno colormap. |
| jet | A colormap that goes from blue to green to yellow to red. |
| jet_r | The reverse of the jet colormap. |
| magma | A sequential colormap that goes from black to purple to pink to yellow. |
| magma_r | The reverse of the magma colormap. |
| nipy_spectral | A diverging colormap that goes from blue to white to red to yellow to green. |
| nipy_spectral_r | The reverse of the nipy_spectral colormap. |
| ocean | A sequential colormap that goes from black to blue to white. |
| ocean_r | The reverse of the ocean colormap. |
| pink | A sequential colormap that goes from black to pink. |
| pink_r | The reverse of the pink colormap. |
| plasma | A sequential colormap that goes from blue to green to yellow to pink. |
| plasma_r | The reverse of the plasma colormap. |
| prism | A qualitative colormap with distinct colors. |
| prism_r | The reverse of the prism colormap. |
| rainbow | A qualitative colormap with distinct colors. |
| rainbow_r | The reverse of the rainbow colormap. |
| seismic | A diverging colormap that goes from blue to white to red. |
| seismic_r | The reverse of the seismic colormap. |
| spring | A sequential colormap that goes from magenta to yellow. |
| spring_r | The reverse of the spring colormap. |
| summer | A sequential colormap that goes from green to yellow. |
| summer_r | The reverse of the summer colormap. |
| tab10 | A qualitative colormap with 10 distinct colors. |
| tab10_r | The reverse of the tab10 colormap. |
| tab20 | A qualitative colormap with 20 distinct colors. |
| tab20_r | The reverse of the tab20 colormap. |
| tab20b | A qualitative colormap with 20 distinct colors, emphasizing the middle range. |
| tab20b_r | The reverse of the tab20b colormap. |
| tab20c | A qualitative colormap with 20 distinct colors, emphasizing the extremes. |
| tab20c_r | The reverse of the tab20c colormap. |
| terrain | A sequential colormap that goes from green to brown to gray. |
| terrain_r | The reverse of the terrain colormap. |
| twilight | A sequential colormap that goes from blue to green to yellow to orange to red. |
| twilight_r | The reverse of the twilight colormap. |
| twilight_shifted | A sequential colormap that goes from green to blue to purple to pink to orange. |
| twilight_shifted_r | The reverse of the twilight_shifted colormap. |
| viridis | A sequential colormap that goes from blue to green to yellow. |
| viridis_r | The reverse of the viridis colormap. |
Accent
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Accent')
pt.colorbar()
pt.show()
Accent_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Accent_r')
pt.colorbar()
pt.show()
Blues
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Blues')
pt.colorbar()
pt.show()
Blues_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Blues_r')
pt.colorbar()
pt.show()
BrBG
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BrBG')
pt.colorbar()
pt.show()
BrBG_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BrBG_r')
pt.colorbar()
pt.show()
BuGn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BuGn')
pt.colorbar()
pt.show()
BuGn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BuGn_r')
pt.colorbar()
pt.show()
BuPu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BuPu')
pt.colorbar()
pt.show()
BuPu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'BuPu_r')
pt.colorbar()
pt.show()
CMRmap
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'CMRmap')
pt.colorbar()
pt.show()
CMRmap_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'CMRmap_r')
pt.colorbar()
pt.show()
Dark2
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Dark2')
pt.colorbar()
pt.show()
Dark2_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Dark2_r')
pt.colorbar()
pt.show()
GnBu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'GnBu')
pt.colorbar()
pt.show()
GnBu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'GnBu_r')
pt.colorbar()
pt.show()
Greens
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Greens')
pt.colorbar()
pt.show()
Greens_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Greens_r')
pt.colorbar()
pt.show()
Greys
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Greys')
pt.colorbar()
pt.show()
Greys_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Greys_r')
pt.colorbar()
pt.show()
OrRd
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'OrRd')
pt.colorbar()
pt.show()
OrRd_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'OrRd_r')
pt.colorbar()
pt.show()
Oranges
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Oranges')
pt.colorbar()
pt.show()
Oranges_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Oranges_r')
pt.colorbar()
pt.show()
PRGn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PRGn')
pt.colorbar()
pt.show()
PRGn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PRGn_r')
pt.colorbar()
pt.show()
Paired
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Paired')
pt.colorbar()
pt.show()
Paired_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Paired_r')
pt.colorbar()
pt.show()
Pastel1
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Pastel1')
pt.colorbar()
pt.show()
Pastel1_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Pastel1_r')
pt.colorbar()
pt.show()
Pastel2
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Pastel2')
pt.colorbar()
pt.show()
Pastel2_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Pastel2_r')
pt.colorbar()
pt.show()
PiYG
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PiYG')
pt.colorbar()
pt.show()
PiYG_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PiYG_r')
pt.colorbar()
pt.show()
PuBu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuBu')
pt.colorbar()
pt.show()
PuBu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuBu_r')
pt.colorbar()
pt.show()
PuBuGn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuBuGn')
pt.colorbar()
pt.show()
PuBuGn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuBuGn_r')
pt.colorbar()
pt.show()
PuOr
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuOr')
pt.colorbar()
pt.show()
PuRd_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'PuRd_r')
pt.colorbar()
pt.show()
Purples
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Purples')
pt.colorbar()
pt.show()
Purples_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Purples_r')
pt.colorbar()
pt.show()
RdBu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdBu')
pt.colorbar()
pt.show()
RdBu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdBu_r')
pt.colorbar()
pt.show()
RdGy
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdGy')
pt.colorbar()
pt.show()
RdGy_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdGy_r')
pt.colorbar()
pt.show()
RdPu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdPu')
pt.colorbar()
pt.show()
RdPu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdPu_r')
pt.colorbar()
pt.show()
RdYlBu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdYlBu')
pt.colorbar()
pt.show()
RdYlBu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdYlBu_r')
pt.colorbar()
pt.show()
RdYlGn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdYlGn')
pt.colorbar()
pt.show()
RdYlGn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'RdYlGn_r')
pt.colorbar()
pt.show()
Reds
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Reds')
pt.colorbar()
pt.show()
Reds_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Reds_r')
pt.colorbar()
pt.show()
Set1
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set1')
pt.colorbar()
pt.show()
Set1_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set1_r')
pt.colorbar()
pt.show()
Set2
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set2')
pt.colorbar()
pt.show()
Set2_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set2_r')
pt.colorbar()
pt.show()
Set3
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set3')
pt.colorbar()
pt.show()
Set3_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Set3_r')
pt.colorbar()
pt.show()
Spectral
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Spectral')
pt.colorbar()
pt.show()
Spectral_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Spectral_r')
pt.colorbar()
pt.show()
Wistia
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Wistia')
pt.colorbar()
pt.show()
Wistia_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Wistia_r')
pt.colorbar()
pt.show()
YlGn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlGn')
pt.colorbar()
pt.show()
YlGn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlGn_r')
pt.colorbar()
pt.show()
YlGnBu
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlGnBu')
pt.colorbar()
pt.show()
YlGnBu_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlGnBu_r')
pt.colorbar()
pt.show()
YlOrBr
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlOrBr')
pt.colorbar()
pt.show()
YlOrBr_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlOrBr_r')
pt.colorbar()
pt.show()
YlOrRd
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlOrRd')
pt.colorbar()
pt.show()
YlOrRd_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'YlOrRd_r')
pt.colorbar()
pt.show()
afmhot
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'afmhot')
pt.colorbar()
pt.show()
afmhot_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'afmhot_r')
pt.colorbar()
pt.show()
Autumn
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'autumn')
pt.colorbar()
pt.show()
Autumn_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'autumn_r')
pt.colorbar()
pt.show()
Binary
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'binary')
pt.colorbar()
pt.show()
Binary_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'binary_r')
pt.colorbar()
pt.show()
Bone
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'bone')
pt.colorbar()
pt.show()
Bone_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'bone_r')
pt.colorbar()
pt.show()
Brg
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'brg')
pt.colorbar()
pt.show()
Brg_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'brg_r')
pt.colorbar()
pt.show()
Bwr
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'bwr')
pt.colorbar()
pt.show()
Bwr_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'bwr_r')
pt.colorbar()
pt.show()
Cividis
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cividis')
pt.colorbar()
pt.show()
Cividis_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cividis_r')
pt.colorbar()
pt.show()
Cool
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cool')
pt.colorbar()
pt.show()
Cool_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cool_r')
pt.colorbar()
pt.show()
Coolwarm
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'coolwarm')
pt.colorbar()
pt.show()
Coolwarm_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'coolwarm_r')
pt.colorbar()
pt.show()
Copper
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'copper')
pt.colorbar()
pt.show()
Copper_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'copper_r')
pt.colorbar()
pt.show()
Cubehelix
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cubehelix')
pt.colorbar()
pt.show()
Cubehelix_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'cubehelix_r')
pt.colorbar()
pt.show()
Flag
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'flag')
pt.colorbar()
pt.show()
Flag_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'flag_r')
pt.colorbar()
pt.show()
Gist_earth
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_earth')
pt.colorbar()
pt.show()
Gist_earth_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_earth_r')
pt.colorbar()
pt.show()
Gist_gray
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_gray')
pt.colorbar()
pt.show()
Gist_gray_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_gray_r')
pt.colorbar()
pt.show()
Gist_heat
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_heat')
pt.colorbar()
pt.show()
Gist_heat_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_heat_r')
pt.colorbar()
pt.show()
Gist_ncar
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_ncar')
pt.colorbar()
pt.show()
Gist_ncar_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_ncar_r')
pt.colorbar()
pt.show()
Gist_rainbow
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_rainbow')
pt.colorbar()
pt.show()
Gist_rainbow_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_rainbow_r')
pt.colorbar()
pt.show()
Gist_stern
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_stern')
pt.colorbar()
pt.show()
Gist_stern_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_stern_r')
pt.colorbar()
pt.show()
Gist_yarg
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_yarg')
pt.colorbar()
pt.show()
Gist_yarg_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gist_yarg_r')
pt.colorbar()
pt.show()
Gnuplot
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gnuplot')
pt.colorbar()
pt.show()
Gnuplot_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gnuplot_r')
pt.colorbar()
pt.show()
Gnuplot2
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gnuplot2')
pt.colorbar()
pt.show()
Gnuplot2_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gnuplot2_r')
pt.colorbar()
pt.show()
Gray
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gray')
pt.colorbar()
pt.show()
Gray_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'gray_r')
pt.colorbar()
pt.show()
Hot
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'hot')
pt.colorbar()
pt.show()
Hot_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'hot_r')
pt.colorbar()
pt.show()
Hsv
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'hsv')
pt.colorbar()
pt.show()
Hsv_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'hsv_r')
pt.colorbar()
pt.show()
Inferno
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'inferno')
pt.colorbar()
pt.show()
Inferno_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'inferno_r')
pt.colorbar()
pt.show()
Jet
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'jet')
pt.colorbar()
pt.show()
Jet_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'jet_r')
pt.colorbar()
pt.show()
Magma
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'magma')
pt.colorbar()
pt.show()
Magma_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'magma_r')
pt.colorbar()
pt.show()
Nipy_spectral
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'nipy_spectral')
pt.colorbar()
pt.show()
Nipy_spectral_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'Accent_r')
pt.colorbar()
pt.show()
Ocean
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'ocean')
pt.colorbar()
pt.show()
Ocean_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'ocean_r')
pt.colorbar()
pt.show()
Pink
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'pink')
pt.colorbar()
pt.show()
Pink_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'pink_r')
pt.colorbar()
pt.show()
Plasma
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'plasma')
pt.colorbar()
pt.show()
Plasma_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'plasma_r')
pt.colorbar()
pt.show()
Prism
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'prism')
pt.colorbar()
pt.show()
Prism_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'prism_r')
pt.colorbar()
pt.show()
Rainbow
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'rainbow')
pt.colorbar()
pt.show()
Rainbow_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'rainbow_r')
pt.colorbar()
pt.show()
Seismic
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'seismic')
pt.colorbar()
pt.show()
Seismic_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'seismic_r')
pt.colorbar()
pt.show()
Spring
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'spring')
pt.colorbar()
pt.show()
Spring_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'spring_r')
pt.colorbar()
pt.show()
Summer
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'summer')
pt.colorbar()
pt.show()
Summer_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'summer_r')
pt.colorbar()
pt.show()
Tab10
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab10')
pt.colorbar()
pt.show()
Tab10_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab10_r')
pt.colorbar()
pt.show()
Tab20
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20')
pt.colorbar()
pt.show()
Tab20_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20_r')
pt.colorbar()
pt.show()
Tab20b
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20b')
pt.colorbar()
pt.show()
Tab20b_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20b_r')
pt.colorbar()
pt.show()
Tab20c
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20c')
pt.colorbar()
pt.show()
Tab20c_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'tab20c_r')
pt.colorbar()
pt.show()
Terrain
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'terrain')
pt.colorbar()
pt.show()
Terrain_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'terrain_r')
pt.colorbar()
pt.show()
Twilight
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'twilight')
pt.colorbar()
pt.show()
Twilight_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'twilight_r')
pt.colorbar()
pt.show()
Twilight_shifted
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'twilight_shifted')
pt.colorbar()
pt.show()
Twilight_shifted_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'twilight_shifted_r')
pt.colorbar()
pt.show()
Viridis
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'viridis')
pt.colorbar()
pt.show()
Viridis_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'viridis_r')
pt.colorbar()
pt.show()
Winter
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'winter')
pt.colorbar()
pt.show()
Winter_r
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
pt.scatter(random_num, prime, c = mrx_colors, cmap = 'winter_r')
pt.colorbar()
pt.show()
Size
With Matplotlib scatter, you can customize the size of the points with the s argument.
Similarly to colors, ensure that the arrays for x and y axis are the identical size:
According to your need customize the size of the following markers:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
mrx_colors = npy.array([0,15,38,62,25,54,73,86])
mrx_sizes = npy.array([90,150,230,33,410,550,320,170])
pt.scatter(random_fibionacci, random_num, c = mrx_colors, s = mrx_sizes, cmap = 'cividis')
pt.colorbar()
pt.show()
First assign different sizes to markers and also insert the ‘inferno’ color map:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
mrx_sizes = npy.array([800,650,270,190,360,580,80,120,444,55,710,410,230])
pt.scatter(random_num, prime, c = mrx_colors, s = mrx_sizes, cmap = 'inferno')
pt.colorbar()
pt.show()
Alpha
With Matplotlib scatter, you can modify the transparency of the points by changing the alpha parameter values.
Similarly to colors, ensure that the array for dimensions has the identical length as the arrays for the x- and y-axis:
Modify the opacity of the markers:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_fibionacci = npy.array([13, 5, 2, 8, 21, 34, 3, 1])
random_num = npy.array([10,87,54,33,47,21,13, 5])
mrx_colors = npy.array([0,15,38,62,25,54,73,86])
mrx_sizes = npy.array([90,150,230,33,410,550,320,170])
pt.scatter(random_fibionacci, random_num, c = mrx_colors, s = mrx_sizes, cmap = 'nipy_spectral', apha = 0.8)
pt.colorbar()
pt.show()
Utilize the ‘ocean’ colormap and change the opacity of the points:
Example:
import matplotlib.pyplot as pt
import numpy as npy
random_num = npy.array([5,39,16,7,41,9,35,51,3,61,2,24,1])
prime = npy.array([31, 37, 19, 43, 47, 53, 23, 62, 29, 41, 16, 59, 17])
mrx_colors = npy.array([20,73,51,13,82,69,29,33,71,44,5,49,99])
mrx_sizes = npy.array([800,650,270,190,360,580,80,120,444,55,710,410,230])
pt.scatter(random_num, prime, c = mrx_colors, s = mrx_sizes, cmap = 'ocean', alpha = 0.3)
pt.colorbar()
pt.show()
Combine Color Size and Alpha
Utilizing 100 x-points, y-points, colors, and sizes, generate random arrays:
Example:
import matplotlib.pyplot as pt
import numpy as npy
mrx = npy.random.randint(100, size=(50))
ample = npy.random.randint(100, size=(50))
mrx_colors = npy.random.randint(100, size=(50))
mrx_sizes = 30 * npy.random.randint(100, size=(50))
pt.scatter(mrx, ample, c=mrx_colors, s=mrx_sizes, alpha=0.7, cmap='terrain')
pt.colorbar()
pt.show()
Apply size = 200 in the below four arrays and also utilize the gist_ncar colormap:
Example:
import matplotlib.pyplot as pt
import numpy as npy
mrx =npy.random.randint(300, size=(200))
ample = npy.random.randint(300, size=(200))
mrx_colors = npy.random.randint(100, size=(200))
mrx_sizes = 10 * npy.random.randint(100, size=(200))
pt.scatter(mrx, ample, c=mrx_colors, s=mrx_sizes, alpha=0.9, cmap='gist_ncar')
pt.colorbar()
pt.show()
Example Explanation
The above example utilizes Matplotlib library to create a scatter plot. The code can be summarized as follows:
- Matplotlib library is imported with an alias “pt“.
- A NumPy array “mrx” is generated containing 200 random integers from 0 to 299.
- Another NumPy array “ample” is generated containing 200 random integers from 0 to 299.
- A third NumPy array “mrx_colors” is generated containing 200 random integers from 0 to 99 which will be used to determine colors for the scatter plot points.
- A fourth NumPy array “mrx_sizes” is generated containing 200 random integers from 0 to 999 which will be used to determine the size of the scatter plot points.
- The “scatter” function from Matplotlib is used to create a scatter plot. The function takes several parameters including x and y coordinates of the points, the color map to be used, the size of each point, and the transparency of each point.
- A color bar is added to the plot using the “colorbar” function.
- The plot is displayed using the “show” function.
Matplotlib Scatter Benefits
Scatter plots have the following benefits:
- Matplotlib scatter plots are great for displaying how two variables are related to each other, which helps to identify patterns or trends in data.
- Matplotlib scatter plots can be customized in many ways, such as changing the color, shape, size, and transparency of points. This provides a more informative and visually appealing visualization.
- Matplotlib scatter plots can be used to visualize the distribution of data points, especially when there are a large number of points. This is useful in detecting any outliers or patterns in the data.
- Creating scatter plots with Matplotlib in Python is relatively simple, making it a popular choice for data visualization. It is also a well-known library with ample resources for learning and troubleshooting.
- Matplotlib scatter plots can be made interactive by using other libraries such as Plotly, Bokeh or mpld3, allowing users to zoom in, hover over data points, and access additional information.
- Matplotlib scatter plots can be easily shared and displayed on different operating systems and devices, as Matplotlib is a cross-platform library.
Conclusion
Matplotlib scatter plots offer a flexible and adaptable approach for displaying the correlation between two variables and the distribution of data points. Due to its simplicity, cross-platform adaptability, and capacity for interactivity, Matplotlib has become a widely-used data visualization tool in Python. Whether you are new to the field or an experienced data analyst, acquiring expertise in creating scatter plots using Matplotlib is a valuable asset for your toolkit.
We value your feedback.
+1
+1
+1
+1
+1
+1
+1
