matplotlib subplotting issue

Unfortunately, reading the source code of trendln, they directly use plt.plot for everything, so it's not easy to do this. You have to change the source code yourself. You can see where the source is located:

>>> import trendln
>>> trendln.__file__
'/home/username/.local/lib/python3.8/site-packages/trendln/__init__.py'
>>> 

Then you can directly modify the plot_support_resistance function to the following. I basically make it take an axs and plot there instead of plt; there were also a few other changes to be made:

def plot_support_resistance(axs, hist, xformatter = None, numbest = 2, fromwindows = True,
                            pctbound=0.1, extmethod = METHOD_NUMDIFF, method=METHOD_NSQUREDLOGN,
                            window=125, errpct = 0.005, hough_scale=0.01, hough_prob_iter=10, sortError=False, accuracy=1):
    import matplotlib.pyplot as plt
    import matplotlib.ticker as ticker
    ret = calc_support_resistance(hist, extmethod, method, window, errpct, hough_scale, hough_prob_iter, sortError, accuracy)
    # plt.clf()
    # plt.subplot(111)

    if len(ret) == 2:
        minimaIdxs, pmin, mintrend, minwindows = ret[0]
        maximaIdxs, pmax, maxtrend, maxwindows = ret[1]
        if type(hist) is tuple and len(hist) == 2 and check_num_alike(hist[0]) and check_num_alike(hist[1]):
            len_h = len(hist[0])
            min_h, max_h = min(min(hist[0]), min(hist[1])), max(max(hist[0]), max(hist[1]))
            disp = [(hist[0], minimaIdxs, pmin, 'yo', 'Avg. Support', 'y--'), (hist[1], maximaIdxs, pmax, 'bo', 'Avg. Resistance', 'b--')]
            dispwin = [(hist[0], minwindows, 'Support', 'g--'), (hist[1], maxwindows, 'Resistance', 'r--')]
            disptrend = [(hist[0], mintrend, 'Support', 'g--'), (hist[1], maxtrend, 'Resistance', 'r--')]
            axs.plot(range(len_h), hist[0], 'k--', label='Low Price')
            axs.plot(range(len_h), hist[1], 'm--', label='High Price')
        else:
            len_h = len(hist)
            min_h, max_h = min(hist), max(hist)
            disp = [(hist, minimaIdxs, pmin, 'yo', 'Avg. Support', 'y--'), (hist, maximaIdxs, pmax, 'bo', 'Avg. Resistance', 'b--')]
            dispwin = [(hist, minwindows, 'Support', 'g--'), (hist, maxwindows, 'Resistance', 'r--')]
            disptrend = [(hist, mintrend, 'Support', 'g--'), (hist, maxtrend, 'Resistance', 'r--')]
            axs.plot(range(len_h), hist, 'k--', label='Close Price')
    else:
        minimaIdxs, pmin, mintrend, minwindows = ([], [], [], []) if hist[0] is None else ret
        maximaIdxs, pmax, maxtrend, maxwindows = ([], [], [], []) if hist[1] is None else ret
        len_h = len(hist[1 if hist[0] is None else 0])
        min_h, max_h = min(hist[1 if hist[0] is None else 0]), max(hist[1 if hist[0] is None else 0])
        disp = [(hist[1], maximaIdxs, pmax, 'bo', 'Avg. Resistance', 'b--') if hist[0] is None else (hist[0], minimaIdxs, pmin, 'yo', 'Avg. Support', 'y--')]
        dispwin = [(hist[1], maxwindows, 'Resistance', 'r--') if hist[0] is None else (hist[0], minwindows, 'Support', 'g--')]
        disptrend = [(hist[1], maxtrend, 'Resistance', 'r--') if hist[0] is None else (hist[0], mintrend, 'Support', 'g--')]
        axs.plot(range(len_h), hist[1 if hist[0] is None else 0], 'k--', label= ('High' if hist[0] is None else 'Low') + ' Price')
    for h, idxs, pm, clrp, lbl, clrl in disp:
        axs.plot(idxs, [h[x] for x in idxs], clrp)
        axs.plot([0, len_h-1],[pm[1],pm[0] * (len_h-1) + pm[1]],clrl, label=lbl)
    def add_trend(h, trend, lbl, clr, bFirst):
        for ln in trend[:numbest]:
            maxx = ln[0][-1]+1
            while maxx < len_h:
                ypred = ln[1][0] * maxx + ln[1][1]
                if (h[maxx] > ypred and h[maxx-1] < ypred or h[maxx] < ypred and h[maxx-1] > ypred or
                    ypred > max_h + (max_h-min_h)*pctbound or ypred < min_h - (max_h-min_h)*pctbound): break
                maxx += 1
            x_vals = np.array((ln[0][0], maxx)) # plt.gca().get_xlim())
            y_vals = ln[1][0] * x_vals + ln[1][1]
            if bFirst:
                axs.plot([ln[0][0], maxx], y_vals, clr, label=lbl)
                bFirst = False
            else: axs.plot([ln[0][0], maxx], y_vals, clr)
        return bFirst
    if fromwindows:
        for h, windows, lbl, clr in dispwin:
            bFirst = True
            for trend in windows:
                bFirst = add_trend(h, trend, lbl, clr, bFirst)
    else:
        for h, trend, lbl, clr in disptrend:
            add_trend(h, trend, lbl, clr, True)
    # axs.title('Prices with Support/Resistance Trend Lines')
    #axs.xlabel('Date')
    #axs.ylabel('Price')
    axs.legend()
    #plt.gca()
    axs.xaxis.set_major_locator(ticker.MaxNLocator(6))
    #plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
    #if not xformatter is None: plt.gca().xaxis.set_major_formatter(xformatter)
    #plt.setp(plt.gca().get_xticklabels(), rotation=30, ha='right')
    #plt.gca().set_position([0, 0, 1, 1])
    #plt.savefig(os.path.join(curdir, 'data', 'suppres.svg'), format='svg', bbox_inches = 'tight')
    #plt.show()
    return None#plt.gcf()

Now that that is taken care of, you can pass one of the axs to draw things:

import matplotlib.pyplot as plt
import trendln
import yfinance as yf

fig, axs = plt.subplots(2, 2, figsize = (20,10))
axs[0, 1].plot([0, 1], [3, 4])

tick = yf.Ticker('^GSPC') # S&P500
hist = tick.history(period="max", rounding=True)

f = trendln.plot_support_resistance(axs[0, 0], hist[-1000:].Close, accuracy = 2)

plt.show()

I get:

I hope this helps. You probably were looking for another option, but because of the hard coding they use, it's not easy. I also tried copying the axs that plt draws to instead of modifying the source code, but it didn't work.