how to animate a scatterplot of pandas data with matplotlib

Question

I'm currently trying to animate a scatterplot of monthly data saved in a pandas dataframe. So far I made loop, which generates one single plot after another. Now I would like to join them in a single gif (or mp4 I don't care). Is there an easy way to make use of mathplotlibs animation function? I can't get my head around, how to loop sliced data through FuncAnimation. So far I did this:

time = df.monat.unique()
for i in time:
    dft = df[(df.monat == i) & (df.xcol < 4000)]
    plt.scatter(x=dft['xcol'],
            y=dft['ycol'],
            s=dft['scol'] / 25,
            c=dft['clr'],
            linewidth=0,
            alpha=0.8)
    plt.title('Title ' + str(i), fontsize=10)
    plt.xlabel('x label', fontsize=9)
    plt.ylabel('y label', fontsize=9)
    legend1_line2d = list()
    for val in clrdict.values():
        legend1_line2d.append(mlines.Line2D([0], [0],
            linestyle='none',
            marker='o',
            alpha=0.6,
            markersize=6,
            markeredgecolor=None,
            markeredgewidth=0,
            markerfacecolor=val))
    legend1 = plt.legend(legend1_line2d,
             names,
             frameon=False,
             numpoints=1,
             fontsize=8,
             loc='upper right') 
    plt.show()

Answer 1

I figured it out by myself:

Generate an empty plot (fig). Like before all unique time-values are stored in a series(time). A simple counter (i) helps generating the correct slice of the data (dft) for each month (df.monat == a value from the series 'time') within the update-function. The update-function is called times the value of the frame-parameter in the anim.FuncAnimation (frames=len(time)).

Hope, this will be helpful for somebody else (most of the explanations for the matplotlib FuncAnimation I've found worked with random numbers - not with specific pandas columns):

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import matplotlib.animation as anim

...

time = df.monat.unique()    
fig = plt.figure()
i = 1

def update(i):
        plt.clf()
        dft = df[(df.monat == time[i]) & (df.xcol < 4000)]
        plt.scatter(x=dft['xcol'],
                    y=dft['ycol'],
                    s=dft['scol'] / 25,
                    c=dft['clr'],
                    linewidth=0,
                    alpha=0.8)
        plt.title('Title ' + str(time[i]), fontsize=10)
        plt.xlabel('x label', fontsize=9)
        plt.ylabel('y label', fontsize=9)
        plt.xlim(0, 900)  # fixed dimensions x
        plt.ylim(-5, 100) # fixed dimensions y 
        legend1_line2d = list()
        for val in clrdict.values():
            legend1_line2d.append(mlines.Line2D([0], [0],
                    linestyle='none',
                    marker='o',
                    alpha=0.6,
                    markersize=6,
                    markeredgecolor=None,
                    markeredgewidth=0,
                    markerfacecolor=val))
        legend1 = plt.legend(legend1_line2d,
                    names,
                    frameon=False,
                    numpoints=1,
                    fontsize=8,
                    loc='upper right')
        i += 1

ani = anim.FuncAnimation(fig, update, frames=len(time), interval=500)
# plt.show() # this will show the ani over and over
ani.save("test.mp4", dpi=200, fps=1, codec="libx264", bitrate=5000, extra_args=['-pix_fmt', 'yuv420p'])