pandas-to-animation.py

# create figure form matplotlib.pyplot
fig = plt.figure()

# make global min/max for the whole array,
# so colour scale will be consistent between the frames
data_min = np.nanmin(full_data_panel.values)
data_max = np.nanmax(full_data_panel.values)

# create iterator
data_frames_iterator = full_data_panel.iteritems()

def update_frame(i):
    plt.clf()
    key, heatmap_data = next(data_frames_iterator)
    # make it latitude-sorted (top > bottom == north > south)
    heatmap_data.sort_index(inplace=True, ascending=False)
    # use seaborn for a little better looking heatmap (matplotlib-based)
    ax = sns.heatmap(
        heatmap_data,
        annot=False,
        vmin=data_min,
        vmax=data_max,
        cmap='jet',
        linewidths=.5,
        xticklabels=5,
        yticklabels=10
    )

# write animation frames
anim = FuncAnimation(fig, update_frame, frames=len(full_data_panel)-1, interval=500)
anim.save('test.gif', writer='imagemagick')