There's no need to manually set the colors. Instead, specify a grayscale colormap...

import numpy as np
import matplotlib.pyplot as plt

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

# Plot...
plt.scatter(x, y, c=y, s=500) # s is a size of marker 
plt.gray()

plt.show()

Or, if you'd prefer a wider range of colormaps, you can also specify the cmap kwarg to scatter. To use the reversed version of any of these, just specify the "_r" version of any of them. E.g. gray_r instead of gray. There are several different grayscale colormaps pre-made (e.g. gray, gist_yarg, binary, etc).

import matplotlib.pyplot as plt
import numpy as np

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

plt.scatter(x, y, c=y, s=500, cmap='gray')
plt.show()

You can also assign discrete colors to the points by passing an array to c= Like this:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

d = {"year"      : (1971, 1939, 1941, 1996, 1975),
     "length"    : ( 121,   71,    7,   70,   71),
     "Animation" : (   1,    1,    0,    1,    0)}

df = pd.DataFrame(d)
print(df)

colors = np.where(df["Animation"]==1,'y','k')
df.plot.scatter(x="year",y="length",c=colors)
plt.show()

This gives:

   Animation  length  year
0          1     121  1971
1          1      71  1939
2          0       7  1941
3          1      70  1996
4          0      71  1975