I am wanting to plot many datasets on one plot in python. Currently, I have hardcoded 20 of the datasets for the sake of testing my plot. Here is the shortened code below:

import numpy as np
import matplotlib as plt

N_steps = 1000
N_plot = 20
xorb_list = np.empty((N_plot, N_steps))
yorb_list = np.empty((N_plot, N_steps))
xobs = np.empty((N_plot, N_steps))
yobs = np.empty((N_plot, N_steps))
zobs = np.empty((N_plot, N_steps))


for i in range(N_plot):
   for k in range(N_steps):
        xorb_list[i][k] = r[k] * cm_to_arcsec * cos_theta[k]
        yorb_list[i][k] = r[k] * cm_to_arcsec * sin_theta[k]
        xobs[i][k] = r[k] * (cos_lon * cos_w_plus_nu[k] - sin_lon * sin_w_plus_nu[k] * cos_i)
        yobs[i][k] = r[k] * (sin_lon * cos_w_plus_nu[k] + cos_lon * sin_w_plus_nu[k] * cos_i)
        zobs[i][k] = r[k] * sin_i * sin_w_plus_nu[k]

# Plotting the observed orbits

fig1 = plt.figure(1)
ax1 = fig1.add_subplot()
ax1.set_aspect(1)
ax1.set_title("Observed Stellar Orbits")

ax1.plot(xobs[0], yobs[0])
ax1.plot(xobs[1], yobs[1])
ax1.plot(xobs[2], yobs[2])
ax1.plot(xobs[3], yobs[3])
ax1.plot(xobs[4], yobs[4])
ax1.plot(xobs[5], yobs[5])
ax1.plot(xobs[6], yobs[6])
ax1.plot(xobs[7], yobs[7])
ax1.plot(xobs[8], yobs[8])
ax1.plot(xobs[9], yobs[9])
ax1.plot(xobs[10], yobs[10])
ax1.plot(xobs[11], yobs[11])
ax1.plot(xobs[12], yobs[12])
ax1.plot(xobs[13], yobs[13])
ax1.plot(xobs[14], yobs[14])
ax1.plot(xobs[15], yobs[15])
ax1.plot(xobs[16], yobs[16])
ax1.plot(xobs[17], yobs[17])
ax1.plot(xobs[18], yobs[18])
ax1.plot(xobs[19], yobs[19])

plt.show()

The total number of datasets will be around 100, which will not be fun to hardcode. Is there some way to generate these datasets for any arbitrary number of sets?

>Solution :

You can loop through your dataframe by its length. Then, place plt.show() outside the for loop like:

for x in range(len(xobs)): 
    ax1.plot(xobs[x], yobs[x])
plt.show()