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pythonmatplotlibseaborndata-visualizationtimeserieschart

3D Plot of Multiple Time Series in Python


I've seen numerous examples of 3D plots using matplotlib/seaborn in Python but can't seem to get what I'm looking for; I have 50 or so timeseries that I would like to plot cleanly as in the following example below but with the name of the series on the axis; as an example I've marked in Goog, IBM, GE, Pepsi etc. Appreciate any pointers or examples. Thank you,

Example PLOT Click Here Please


Solution

  • Matplotlib has very rich gallery. I found this, you can only plot it once instead of animation. And manually put y-axis legend wherever you want.

    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib.animation as animation
    
    # Fixing random state for reproducibility
    np.random.seed(19680801)
    
    
    # Create new Figure with black background
    fig = plt.figure(figsize=(12, 8))
    
    # Add a subplot with no frame
    ax = plt.subplot(111, frameon=False)
    
    # Generate random data
    data = np.random.uniform(0, 1, (64, 75))
    X = np.linspace(-1, 1, data.shape[-1])
    G = 1.5 * np.exp(-4 * X ** 2)
    
    # Generate line plots
    lines = []
    for i in range(len(data)):
        # Small reduction of the X extents to get a cheap perspective effect
        xscale = 1 - i / 200.
        # Same for linewidth (thicker strokes on bottom)
        lw = 1.5 - i / 100.0
        line, = ax.plot(xscale * X, i + G * data[i], color="b", lw=lw)
        lines.append(line)
    
    # Set y limit (or first line is cropped because of thickness)
    ax.set_ylim(-1, 70)
    
    # No ticks
    ax.set_xticks([])
    ax.set_yticks([])
    
    # 2 part titles to get different font weights
    ax.text(0.5, 1.0, "MATPLOTLIB ", transform=ax.transAxes,
            ha="right", va="bottom", color="k",
            family="sans-serif", fontweight="light", fontsize=16)
    ax.text(0.5, 1.0, "UNCHAINED", transform=ax.transAxes,
            ha="left", va="bottom", color="k",
            family="sans-serif", fontweight="bold", fontsize=16)
    
    
    def update(*args):
        # Shift all data to the right
        data[:, 1:] = data[:, :-1]
    
        # Fill-in new values
        data[:, 0] = np.random.uniform(0, 1, len(data))
    
        # Update data
        for i in range(len(data)):
            lines[i].set_ydata(i + G * data[i])
    
        # Return modified artists
        return lines
    
    # Construct the animation, using the update function as the animation director.
    anim = animation.FuncAnimation(fig, update, interval=10)
    plt.show()
    

    enter image description here