Color mapping with colorbar in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a scatter plot with colors mapped from the 'values' array.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(10)
y = np.random.rand(10)
values = np.linspace(0, 1, 10)

plt.scatter(x, y, c=[1])
plt.show()

Drag options to blanks, or click blank then click option'

Avalues

By

Cnp.arange(10)

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Using x or y instead of the values array for colors.

Not passing any array to the c parameter.

The c parameter in plt.scatter sets the colors of the points. We use the values array to map colors.

2fill in blank

medium

Complete the code to add a colorbar to the scatter plot.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(10)
y = np.random.rand(10)
values = np.linspace(0, 1, 10)

scatter = plt.scatter(x, y, c=values)
[1]
plt.show()

Drag options to blanks, or click blank then click option'

Aplt.colorbar(scatter)

Bplt.colorbar()

Cplt.colorbar(x)

Dplt.colorbar(y)

Attempts:

3 left

💡 Hint

Common Mistakes

Calling plt.colorbar() without arguments.

Passing x or y arrays to plt.colorbar().

To add a colorbar for a scatter plot, pass the scatter object to plt.colorbar().

3fill in blank

hard

Fix the error in the code to correctly map colors and add a colorbar.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(5)
y = np.random.rand(5)
values = np.array([10, 20, 30, 40, 50])

scatter = plt.scatter(x, y, c=[1])
plt.colorbar(scatter)
plt.show()

Drag options to blanks, or click blank then click option'

Ax

Bvalues

Cy

Dnp.arange(5)

Attempts:

3 left

💡 Hint

Common Mistakes

Using y or x instead of the values array for colors.

Not passing any array to the c parameter.

The c parameter should be the array of values to map colors, which is values.

4fill in blank

hard

Fill both blanks to create a scatter plot with a 'viridis' colormap and add a colorbar.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(8)
y = np.random.rand(8)
values = np.linspace(0, 1, 8)

scatter = plt.scatter(x, y, c=values, cmap=[1])
[2]
plt.show()

Drag options to blanks, or click blank then click option'

A'viridis'

Bplt.colorbar()

Cplt.colorbar(scatter)

D'plasma'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the wrong colormap name.

Calling plt.colorbar() without the scatter object.

Use cmap='viridis' to set the colormap. Pass the scatter object to plt.colorbar() to add the colorbar.

5fill in blank

hard

Fill all three blanks to create a scatter plot with a 'coolwarm' colormap, set the color limits from 0 to 1, and add a colorbar.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(6)
y = np.random.rand(6)
values = np.linspace(0, 1, 6)

scatter = plt.scatter(x, y, c=values, cmap=[1])
scatter.set_clim([2], [3])
plt.colorbar(scatter)
plt.show()

Drag options to blanks, or click blank then click option'

A'coolwarm'

B0

C1

D'viridis'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong colormap names.

Not setting color limits correctly.

Forgetting to add the colorbar.

Set cmap='coolwarm' for the colormap. Use scatter.set_clim(0, 1) to set color limits. Then add the colorbar.

Practice

1. What is the main purpose of adding a colorbar in a matplotlib plot with color mapping?

easy

A. To show the scale of colors representing data values

B. To change the plot title

C. To add grid lines to the plot

D. To save the plot as an image file

Solution

1. Step 1: Understand color mapping

   Color mapping assigns colors to data values to visualize differences.

2. Step 2: Role of colorbar

   The colorbar shows which colors correspond to which data values, acting as a legend.

3. Final Answer:

   To show the scale of colors representing data values -> Option A

4. Quick Check:

   Colorbar explains colors = B [OK]

Hint: Colorbar always explains color scale in plots [OK]

Common Mistakes:

• Thinking colorbar changes plot title
• Confusing colorbar with grid lines
• Assuming colorbar saves the plot

2. Which of the following is the correct way to add a colorbar to a scatter plot in matplotlib?

easy

A. plt.scatter(x, y); plt.colorbar(c=z)

B. plt.colorbar(); plt.scatter(x, y, c=z)

C. plt.scatter(x, y, c=z); plt.colorbar()

D. plt.scatter(x, y, c=z, colorbar=True)

Solution

1. Step 1: Plot with color mapping

   Use plt.scatter(x, y, c=z) to map colors to values z.

2. Step 2: Add colorbar after plotting

   Call plt.colorbar() after the scatter plot to add the color scale.

3. Final Answer:

   plt.scatter(x, y, c=z); plt.colorbar() -> Option C

4. Quick Check:

   Plot first, then colorbar [OK]

Hint: Call plt.colorbar() after plotting with color data [OK]

Common Mistakes:

• Calling plt.colorbar() before plotting
• Passing colorbar as a parameter to scatter
• Trying to pass c=z inside plt.colorbar()

3. What will the following code display?

import matplotlib.pyplot as plt
import numpy as np
x = np.arange(5)
y = np.arange(5)
z = x * y
plt.scatter(x, y, c=z)
plt.colorbar()
plt.show()

medium

A. A scatter plot with points colored from 0 to 16 and a colorbar showing this range

B. A scatter plot with all points in the same color and no colorbar

C. A line plot connecting points with a colorbar

D. An error because colorbar needs a colormap argument

Solution

1. Step 1: Understand data and color mapping

   x and y are arrays 0 to 4, z is their product (0,1,4,9,16).

2. Step 2: Scatter plot with color mapping and colorbar

   Points colored by z values, colorbar shows color scale from min to max z.

3. Final Answer:

   A scatter plot with points colored from 0 to 16 and a colorbar showing this range -> Option A

4. Quick Check:

   Color mapped scatter with colorbar = D [OK]

Hint: Colorbar shows range of c= values in scatter [OK]

Common Mistakes:

• Thinking colorbar is missing
• Expecting a line plot instead of scatter
• Believing colorbar needs explicit colormap argument

4. Identify the error in this code snippet that tries to add a colorbar:

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5, 6]
plt.scatter(x, y)
plt.colorbar()
plt.show()

medium

A. Error because plt.show() is missing

B. No error; code runs fine and shows colorbar

C. Error because plt.colorbar() must be called before scatter

D. Error because scatter plot has no color mapping (c parameter missing)

Solution

1. Step 1: Check scatter plot parameters

   Scatter plot lacks c= parameter, so no color mapping exists.

2. Step 2: Understand colorbar requirement

   Colorbar needs a mappable object with colors; without c=, colorbar cannot be created.

3. Final Answer:

   Error because scatter plot has no color mapping (c parameter missing) -> Option D

4. Quick Check:

   Colorbar needs color data = A [OK]

Hint: Colorbar requires color mapping (c=) in plot [OK]

Common Mistakes:

• Calling colorbar before plotting
• Forgetting plt.show() (though optional)
• Assuming colorbar works without color data

5. You want to create a heatmap using imshow with a colorbar that shows values from 0 to 1. Which code snippet correctly sets the color limits and adds the colorbar?

hard

A. plt.imshow(data); plt.colorbar(vmin=0, vmax=1)

B. plt.imshow(data, vmin=0, vmax=1); plt.colorbar()

C. plt.imshow(data, colorbar=True, vmin=0, vmax=1)

D. plt.imshow(data); plt.colorbar(); plt.clim(0, 1)

Solution

1. Step 1: Set color limits in imshow

   Use vmin=0 and vmax=1 in imshow to fix color scale range.

2. Step 2: Add colorbar without extra arguments

   Call plt.colorbar() after plotting to add the colorbar matching the scale.

3. Final Answer:

   plt.imshow(data, vmin=0, vmax=1); plt.colorbar() -> Option B

4. Quick Check:

   Set vmin/vmax in imshow, then colorbar [OK]

Hint: Set vmin/vmax in imshow, then call plt.colorbar() [OK]

Common Mistakes:

• Passing vmin/vmax to plt.colorbar() instead of imshow
• Using colorbar=True inside imshow (not valid)
• Calling plt.clim() after colorbar (wrong order)