如何在 Python 中的单个 map 中显示两个不同的坐标数据框

Question

I am trying to visualise the movements of a fish within my study area. I have two different coordinate dataframes: the first Df1 contains the coordinates derived from the location of the fish at a given time, the second Df2 describes the positions of the submerged antennas used in the study necessary to locate the position of the fish.

Df1 =

FishTag       X         Y
32212   43.55154   -63.21155
32212   43.55896   -63.21458
32212   43.55157   -63.21785
32212   43.55452   -63.21154
32212   43.55122   -63.21455

Df2 =

Receiver    X         Y
1         47.55154   -68.21155
2         47.58622   -68.26332
3         47.57745   -68.96251
4         48.57455   -68.96521
5         48.57567   -69.94551
6         48.57759   -69.96251
7         48.54145   -69.95950

I created two distinct maps for each dataframe with .seaborn but i would like to overlap such maps to form a single map with all the informations!

import seaborn as sns

fig1, ax = plt.subplots()
fig1 = sns.scatterplot(Df1, x="Lat", y="Lon", ax=ax)
fig1.show()

fig2, ax = plt.subplots()
fig2 = sns.scatterplot(Df2, x="Lat", y="Lon", hue="Receiver", ax=ax)
fig2.show()

Both maps have the same coordinates scale!

Here an example of the expected output: the white circles are the receivers locations and the succession of red points are the positions of the animal.

Answer 1

Reuse Axes for both plot:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
sns.scatterplot(data=Df1, x='X', y='Y', ax=ax)
sns.scatterplot(data=Df2, x='X', y='Y', ax=ax)
plt.show()

Output: