Right now im struggling with plotting the graph that should be showing the peaks of my dataset, but it looks like the find_peaks function is cutting off every datapoint that doesnt fit into to the peak detection. Does anybody know how i can still plot the graphs by maybe replacing the datapoints that dont fit with zeros or is there any other possibility?

I am getting the following Error Message: "ValueError: x and y must have same first dimension, but have shapes (800,) and (105,)"

def plot():
    i = 1
    d_time, d_x, d_y, d_z = [], [], [], []
    columns = ["Time", "y", "x", "z"]
    df = pd.read_csv("mydata.csv", usecols=columns)
    for zeile in df.Time:
        if i % 30 == 0:
            d_time.append(df.Time[i])
            d_x.append(df.x[i])
            d_y.append(df.y[i])
            d_z.append(df.z[i])
            i  = 1
        elif i > 24000:
            break
        else:
            i  = 1

    fig = plt.figure(dpi=64, figsize=(100, 60))

    p_z, _ = scipy.signal.find_peaks(d_z, 0, distance=5)

    plt.plot(d_time, d_z, c='red', label="Z-Achse")
    plt.plot(d_time, p_z, "x", c='blue', label="Peaks Z-Achse")

    plt.title("Peak Detection", fontsize=16)
    plt.xlabel('t(s)', fontsize=16)

    fig.autofmt_xdate()
    plt.ylabel("a(m/s²)", fontsize=16)
    plt.tick_params(axis='both', which='major')

    plt.legend()
    plt.show()


plot()

Link to Mydata.csv: