```
import numpy as np
from PIL import Image
# Creating a new figure and setting up the resolution
fig = plt.figure(dpi=200)
# Change the coordinate system from scaler to polar
ax = fig.add_subplot(projection='polar')
# Generating the X and Y axis data points
r=[8,8,8,8,8,8,8,8,8]
theta = np.deg2rad(np.arange(45,406,45))
# plotting the polar coordinates on the system
ax.plot(theta,r, marker='x')
# Setting the axis limit
ax.set_ylim(0,12)
# Displaying the plot
plt.show()
```

The above code produces the image below. Given r and theta, create an x mark at each polar coordinate.

What I want is to put an image instead of the x mark at that x mark location. I can insert images using the add_axes method, but I cannot insert many images because I have to manually adjust the coordinates.

i’ve tried add_axes method of matplotlib, but the method takes ratio float of original plot. So i should manually adjust the location of the image.

result that i expect is described in below image. the x mark is replaced by an image.

enter image description here

### >Solution :

You don’t have to adjust the coordinates *manually*. You can get them with `get_data`

from Line2D object. Then use `add_artist`

to display your images:

```
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.image as image
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
# Creating a new figure and setting up the resolution
fig = plt.figure(dpi=200)
# Change the coordinate system from scaler to polar
ax = fig.add_subplot(projection='polar')
# Generating the X and Y axis data points
r=[8,8,8,8,8,8,8,8,8]
theta = np.deg2rad(np.arange(45,406,45))
# plotting the polar coordinates on the system
lines = ax.plot(theta,r, marker='x') # storing as 'lines'
im = image.imread("your_image.png")
imagebox = OffsetImage(im, zoom = 0.01) # adjust the zoom factor accordingly
data = lines[0].get_data()
for t, r in zip(data[0], data[1]):
ax.add_artist(AnnotationBbox(imagebox, (t, r), frameon = False))
# Setting the axis limit
ax.set_ylim(0,12)
# Displaying the plot
plt.show()
```