Data as a function of time

npl.py

import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import pandas as pd
dat=pd.read_csv("Gban_data.csv")
def randrange(n, vmin, vmax):
    return (vmax-vmin)*np.random.rand(n) + vmin

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x=dat.Field
y1=dat.Intensity1;z1=0
y2=dat.Intensity2;z2=10
y3=dat.Intensity3;z3=20
### Un comment below 3 lines if you want plot with points not with lines
#ax.scatter(x,[0]*len(dat.Field) ,y1, c='r', marker='^')
#ax.scatter(x,[10]*len(dat.Field),y2 , c='g', marker='o')
#ax.scatter(x,[20]*len(dat.Field),y3 , c='b', marker='*')
ax.plot(x,[z1]*len(dat.Field) ,y1, c='r'  )
ax.plot(x,[z2]*len(dat.Field),y2 , c='g' )
ax.plot(x,[z3]*len(dat.Field),y3 , c='b' )
ax.set_xlabel('Field')
ax.set_ylabel('Time ')
ax.set_zlabel('Intensity')
plt.savefig('example01.pdf') 
plt.show()