Individual alpha values in scatter plot

You can use the color argument and a colormap with alpha. cmap linearly increases the alpha value from 0 to 1.

import numpy as np
import matplotlib.pylab as plt
from matplotlib import colors

c='C0'

xs = np.arange(10)

fig, ax = plt.subplots(1, 1)
cmap = colors.LinearSegmentedColormap.from_list(
        'incr_alpha', [(0, (*colors.to_rgb(c),0)), (1, c)])
ax.scatter(xs, xs, c=xs, cmap=cmap, ec=None, s=10**2)

plt.show()

New solution with matplotlib >= 3.4

Since matplotlib 3.4, alpha supports an iterable of multiple values: https://matplotlib.org/stable/users/prev_whats_new/whats_new_3.4.0.html#transparency-alpha-can-be-set-as-an-array-in-collections

import numpy as np
import matplotlib.pylab as plt

x = np.arange(10)
y = np.arange(10)

alphas = np.linspace(0.1, 1, 10)

plt.scatter(x, y, alpha=alphas)
plt.show()

Old solution for matplotlib < 3.4

tcaswell's suggestion is correct, you can do it like this:

import numpy as np
import matplotlib.pylab as plt

x = np.arange(10)
y = np.arange(10)

alphas = np.linspace(0.1, 1, 10)
rgba_colors = np.zeros((10,4))
# for red the first column needs to be one
rgba_colors[:,0] = 1.0
# the fourth column needs to be your alphas
rgba_colors[:, 3] = alphas

plt.scatter(x, y, color=rgba_colors)
plt.show()