# update marker sizes of a scatter plot

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There is a reason, however, that the size of markers is defined in this way. Because of the scaling of area as the square of width, doubling the width actually appears to increase the size by more than a factor 2 (in fact it increases it by a factor of 4). To see this consider the following two examples and the output they produce.

```# doubling the width of markers
x = [0, 2, 4, 6, 8, 10]
y = [0] * len(x)
s = [20 * 4 ** n
for n in range(len(x))
]
plt.scatter(x, y, s = s)
plt.show()```

Notice how the size increases very quickly. If instead we have

```# doubling the area of markers
x = [0, 2, 4, 6, 8, 10]
y = [0] * len(x)
s = [20 * 2 ** n
for n in range(len(x))
]
plt.scatter(x, y, s = s)
plt.show()```

```x = [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
s_exp = [20 * 2 ** n
for n in range(len(x))
]
s_square = [20 * n ** 2
for n in range(len(x))
]
s_linear = [20 * n
for n in range(len(x))
]
plt.scatter(x, [1] * len(x), s = s_exp, label = '\$s=2^n\$', lw = 1)
plt.scatter(x, [0] * len(x), s = s_square, label = '\$s=n^2\$')
plt.scatter(x, [-1] * len(x), s = s_linear, label = '\$s=n\$')
plt.ylim(-1.5, 1.5)
plt.legend(loc = 'center left', bbox_to_anchor = (1.1, 0.5), labelspacing = 3)
plt.show()```

```import matplotlib.pyplot as plt

fig, ax = plt.subplots()

ax.plot([0], [0], marker = "o", markersize = 10)
ax.plot([0.07, 0.93], [0, 0], linewidth = 10)
ax.scatter([1], [0], s = 100)

ax.plot([0], [1], marker = "o", markersize = 22)
ax.plot([0.14, 0.86], [1, 1], linewidth = 22)
ax.scatter([1], [1], s = 22 ** 2)

plt.show()```

It might be useful to be able to specify sizes in pixels instead of points. If the figure dpi is 72 as well, one point is one pixel. If the figure dpi is different (matplotlib default is `fig.dpi=100`),

`1 point == fig.dpi / 72. pixels`

```import matplotlib.pyplot as plt

for dpi in [72, 100, 144]:

fig, ax = plt.subplots(figsize = (1.5, 2), dpi = dpi)
ax.set_title("fig.dpi={}".format(dpi))

ax.set_ylim(-3, 3)
ax.set_xlim(-2, 2)

ax.scatter([0], [1], s = 10 ** 2,
marker = "s", linewidth = 0, label = "100 points^2")
ax.scatter([1], [1], s = (10 * 72. / fig.dpi) ** 2,
marker = "s", linewidth = 0, label = "100 pixels^2")

ax.legend(loc = 8, framealpha = 1, fontsize = 8)

fig.savefig("fig{}.png".format(dpi), bbox_inches = "tight")

plt.show()```

You can use markersize to specify the size of the circle in plot method

```import numpy as np
import matplotlib.pyplot as plt

x1 = np.random.randn(20)
x2 = np.random.randn(20)
plt.figure(1)
# you can specify the marker size two ways directly:
plt.plot(x1, 'bo', markersize = 20) # blue circle with size 10
plt.plot(x2, 'ro', ms = 10, ) # ms is just an alias
for markersize
plt.show()```

It is the area of the marker. I mean if you have `s1 = 1000` and then `s2 = 4000`, the relation between the radius of each circle is: `r_s2 = 2 * r_s1`. See the following plot:

```plt.scatter(2, 1, s = 4000, c = 'r')
plt.scatter(2, 1, s = 1000, c = 'b')
plt.scatter(2, 1, s = 10, c = 'g')```

I also attempted to use 'scatter' initially for this purpose. After quite a bit of wasted time - I settled on the following solution.

```import matplotlib.pyplot as plt
input_list = [{
'x': 100,
'y': 200,
'color': (0.1, 0.2, 0.3)
}]
output_list = []
for point in input_list:
output_list.append(plt.Circle((point['x'], point['y']), point['radius'], color = point['color'], fill = False))
ax = plt.gca(aspect = 'equal')
ax.cla()
ax.set_xlim((0, 1000))
ax.set_ylim((0, 1000))
for circle in output_list:

Suggestion : 2

In this Matplotlib Tutorial, we learned how to set size for markers in Scatter Plot.,To set specific size for markers in Scatter Plot in Matplotlib, pass required sizes for markers as list, to s parameter of scatter() function, where each size is applied to respective data point.,www.tutorialkart.com - ©Copyright - TutorialKart 2021,In the following example, we will draw a scatter plot with 6 (six) data points, and set specific size for the markers of these data points on the Scatter plot, with a list of numbers. Each number in the list is the size of the marker in Scatter plot.

The following is definition of `scatter()` function with `s` parameter, at third position, whose default value is `None`.

`matplotlib.pyplot.scatter(x, y, s = None, c = None, marker = None, cmap = None, norm = None, vmin = None, vmax = None, alpha = None, linewidths = None, *, edgecolors = None, plotnonfinite = False, data = None, ** kwargs)`

example.py

```import matplotlib.pyplot as plt

#data
x = [0, 1, 1, 2, 2, 3]
y = [0, 1, 2, 1, 2, 3]

#markers ' size
size = [40, 300, 125, 180, 72, 60]

#scatter plot
plt.scatter(x, y, s = size)

plt.show()```

Suggestion : 3

You can specify the marker size with the parameter s and the marker color with c in the plt.scatter() function.

You can specify the marker size with the parameter s and the marker color with c in the `plt.scatter()` function.

```import matplotlib.pyplot as plt
import matplotlib.colors

# Prepare a list of integers
val = [2, 3, 6, 9, 14]

# Prepare a list of sizes that increases with values in val
sizevalues = [i ** 2 * 50 + 50
for i in val
]

# Prepare a list of colors
plotcolor = ['red', 'orange', 'yellow', 'green', 'blue']

# Draw a scatter plot of val points with sizes in sizevalues and
# colors in plotcolor
plt.scatter(val, val, s = sizevalues, c = plotcolor)

# Set axis limits to show the markers completely
plt.xlim(0, 20)
plt.ylim(0, 20)

plt.show()```