I have a list of pandas DataFrames with 2 columns each. So far I have a function that, when given an index i, it takes the frame corresponding to index i and plots a graph of data from the first column against the data of the second column.
list = [f0,f1,f2,f3,f4,f5,f6,f7,f8,f9]
def getGraph(i):
frame = list[i]
frame.plot(x = "firstColumn",y = "secondColumn")
return 0
My question now is, how do I make this iterate over the list of frames and animate the graphs displaying each one for 0.3 seconds in succession.
Preferably, I would like to use the FuncAnimation class in the animation library which does the heavy lifting and optimizations for you.
Set animate function and init to axes, figure and line:
from matplotlib import pyplot as plt
from matplotlib import animation
import pandas as pd
f0 = pd.DataFrame({'firstColumn': [1,2,3,4,5], 'secondColumn': [1,2,3,4,5]})
f1 = pd.DataFrame({'firstColumn': [5,4,3,2,1], 'secondColumn': [1,2,3,4,5]})
f2 = pd.DataFrame({'firstColumn': [5,4,3.5,2,1], 'secondColumn': [5,4,3,2,1]})
# make a global variable to store dataframes
global mylist
mylist=[f0,f1,f2]
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 5), ylim=(0, 5))
line, = ax.plot([], [], lw=2)
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function of dataframes' list
def animate(i):
line.set_data(mylist[i]['firstColumn'], mylist[i]['secondColumn'])
return line,
# call the animator, animate every 300 ms
# set number of frames to the length of your list of dataframes
anim = animation.FuncAnimation(fig, animate, frames=len(mylist), init_func=init, interval=300, blit=True)
plt.show()
For more info look for the tutorial: https://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
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