How do you fix this error. Or is there another way to plot six confidence ellipse in 3x2 grid of plots using subplot (IN PYTHON) Create a 3 x 2 grid of plots (using the subplot command from matplotlib), where the first column of plots shows the 3 water-based pairs and the secondcolumn shows the 3 methanol-based pairs. Each plot will look like your plot for Exercise 1 above: it should include the scattered points as well as confidenceellipses for fermented and unfermented. Each subplot should have its own axis labels and title.In order to keep your code from exploding, you should create a function whose inputs are two columns of data, which produces the plot corresponding to thosetwo features. You will then call this function 6 times to produce the 6 subplots.import matplotlib.pyplot as pltxf= df_fer [['TPC-MEOH']]yf= df_fer[['TEAC-MEOH']]xnf = df_nf[[ TPC-MEOH']]ynf = df_nf[['TEAC-MEOH']]#Answer to Exercise 4 hereimport numpy as np # 'np' is the prefix that will identify nump packagesfrom source.ellipses import confidence_ellipse # for representing the correlation (for def draw_confidence_ellipse2(xf, yf,xfa = np.array(xf).flatten()yfa= np.array(yf).flatten()xnfa = np.array(xnf).flatten()ynfa = np.array(ynf).flatten()ax = plt.subplots()plt.scatter(xfa, yfa, s-6, color = 'blue')confidence_ellipse (xfa, yfa, ax, n_std=1, label='FR', edgecolor='blue', linestyle='--')plt.scatter (xnfa, ynfa, s-6, color = 'orange')confidence_ellipse (xnfa, ynfa, ax, n_std=1, label='NF', edgecolor="orange', linestyle='--')ax.set_title('title', fontsize =16, fontweight = "bold")ax.set_xlabel('x1', fontweight ='bold', fontsize =16)ax.set_ylabel('yl', fontweight ='bold', fontsize =16)ax.legend (prop={"size":14})f_tpc_m= df_fer [['TPC-MEOH']]f_teac_m= df_fer [['TEAC-MEOH']]f_frap_m= df_fer [['FRAP-MECH']] f_tpc_n = df_fer[['TPC-MECH']]f_teac_n = df_fer [['TEAC-MEOH"]]f_frap_m= df_fer [['FRAP-MECH']]f_tpc_h= df_fer[['TPC-H20']]f_teac_h= df_fer[['TEAC-H20']]f_frap_h= df_fer[['FRAP-H20']]nf_tpc_n = df_nf[['TPC-MECH']]nf_teac_n = df_nf[['TEAC-MECH']]nf_frap_m= df_nf[['FRAP-MECH']]nf_tpc_h= df_nf[['TPC-H20']]nf_teac_h= df_nf[['TEAC-H20']]nf_frap_h= df_nf[['FRAP-H20']]fig, ax = plt.subplots(3, 2, figsize=(24, 24))draw_confidence_ellipse2(f_tpc_h, f_teac_h, nf_tpc_h, nf_teac_h, 2, ax[0,0], "TPC", "TEAC", "TPC-H20 vs TEAC-H20")draw_confidence_ellipse2(f_tpc_h, f_frap_h, nf_tpc_h, nf_frap_h, 2, ax[1,0], "TPC", "FRAP", "TPC-H20 vs FRAP-H20")draw_confidence_ellipse2(f_frap_h, f_teac_h, nf_frap_h, nf_teac_h, 2, ax[2,0], "FRAP", "TEAC", "FRAP-H20 vs TEAC-H20")draw_confidence_ellipse2(f_tpc_m,draw_confidence_ellipse2(f_tpc_m,draw_confidence_ellipse2(f_frap_n,4f_teac_m, nf_tpc_m, nf_teac_m, 2, ax[0,1], "TPC", "TEAC", "TPC-MEOH vs TEAC-MEOH")f_frap_m, nf_tpc_m, nf_frap_m, 2, ax[1,1], "TPC", "FRAP", "TPC-MEOH vs FRAP-MEOH")f_teac_m, nf_frap_n, nf_teac_m, 2, ax[2,1], "FRAP", "TEAC", "FRAP-MEOH vs TEAC-MEOH"AttributeErrorInput In [26], in ()plt.subplots()Traceback (most recent call last)10 ax12 plt.scatter(xfa, yfa, s=6, color = 'blue')--- 13 confidence_ellipse(xfa, yfa, ax, n_std=1, label='FR", edgecolor='blue', linestyle='--')15 plt.scatter(xnfa, ynfa, s=6, color="orange")16 confidence_ellipse(xnfa, ynfa, ax, n_std=1, label='NF", edgecolor='orange', linestyle='--')File -\source\ellipses.py:58, in confidence_ellipse(x, y, ax, n_std, facecolor, **kwargs)51 mean y = np.mean(y)53 transf = transforms.Affine2D() \54.rotate_deg (45) \55.scale(scale_x, scale_y) \.translate(mean_x, nean_y)56-- 58 ellipse.set_transform(transf + ax. transData)59 return ax.add_patch(ellipse)AttributeError: 'tuple' object has no attribute 'transData'

Question

How do you fix this error. Or is there another way to plot six confidence ellipse in 3x2 grid of plots using subplot (IN PYTHON) Create a 3 x 2 grid of plots (using the subplot command from matplotlib), where the first column of plots shows the 3 water-based pairs and the secondcolumn shows the 3 methanol-based pairs. Each plot will look like your plot for Exercise 1 above: it should include the scattered points as well as confidenceellipses for fermented and unfermented. Each subplot should have its own axis labels and title.In order to keep your code from exploding, you should create a function whose inputs are two columns of data, which produces the plot corresponding to thosetwo features. You will then call this function 6 times to produce the 6 subplots.import matplotlib.pyplot as pltxf= df_fer [['TPC-MEOH']]yf= df_fer[['TEAC-MEOH']]xnf = df_nf[[ TPC-MEOH']]ynf = df_nf[['TEAC-MEOH']]#Answer to Exercise 4 hereimport numpy as np # 'np' is the prefix that will identify nump packagesfrom source.ellipses import confidence_ellipse # for representing the correlation (for def draw_confidence_ellipse2(xf, yf,xfa = np.array(xf).flatten()yfa= np.array(yf).flatten()xnfa = np.array(xnf).flatten()ynfa = np.array(ynf).flatten()ax = plt.subplots()plt.scatter(xfa, yfa, s-6, color = 'blue')confidence_ellipse (xfa, yfa, ax, n_std=1, label='FR', edgecolor='blue', linestyle='--')plt.scatter (xnfa, ynfa, s-6, color = 'orange')confidence_ellipse (xnfa, ynfa, ax, n_std=1, label='NF', edgecolor=&#34;orange', linestyle='--')ax.set_title('title', fontsize =16, fontweight = &#34;bold&#34;)ax.set_xlabel('x1', fontweight ='bold', fontsize =16)ax.set_ylabel('yl', fontweight ='bold', fontsize =16)ax.legend (prop={&#34;size&#34;:14})f_tpc_m= df_fer [['TPC-MEOH']]f_teac_m= df_fer [['TEAC-MEOH']]f_frap_m= df_fer [['FRAP-MECH']] f_tpc_n = df_fer[['TPC-MECH']]f_teac_n = df_fer [['TEAC-MEOH&#34;]]f_frap_m= df_fer [['FRAP-MECH']]f_tpc_h= df_fer[['TPC-H20']]f_teac_h= df_fer[['TEAC-H20']]f_frap_h= df_fer[['FRAP-H20']]nf_tpc_n = df_nf[['TPC-MECH']]nf_teac_n = df_nf[['TEAC-MECH']]nf_frap_m= df_nf[['FRAP-MECH']]nf_tpc_h= df_nf[['TPC-H20']]nf_teac_h= df_nf[['TEAC-H20']]nf_frap_h= df_nf[['FRAP-H20']]fig, ax = plt.subplots(3, 2, figsize=(24, 24))draw_confidence_ellipse2(f_tpc_h, f_teac_h, nf_tpc_h, nf_teac_h, 2, ax[0,0], &#34;TPC&#34;, &#34;TEAC&#34;, &#34;TPC-H20 vs TEAC-H20&#34;)draw_confidence_ellipse2(f_tpc_h, f_frap_h, nf_tpc_h, nf_frap_h, 2, ax[1,0], &#34;TPC&#34;, &#34;FRAP&#34;, &#34;TPC-H20 vs FRAP-H20&#34;)draw_confidence_ellipse2(f_frap_h, f_teac_h, nf_frap_h, nf_teac_h, 2, ax[2,0], &#34;FRAP&#34;, &#34;TEAC&#34;, &#34;FRAP-H20 vs TEAC-H20&#34;)draw_confidence_ellipse2(f_tpc_m,draw_confidence_ellipse2(f_tpc_m,draw_confidence_ellipse2(f_frap_n,4f_teac_m, nf_tpc_m, nf_teac_m, 2, ax[0,1], &#34;TPC&#34;, &#34;TEAC&#34;, &#34;TPC-MEOH vs TEAC-MEOH&#34;)f_frap_m, nf_tpc_m, nf_frap_m, 2, ax[1,1], &#34;TPC&#34;, &#34;FRAP&#34;, &#34;TPC-MEOH vs FRAP-MEOH&#34;)f_teac_m, nf_frap_n, nf_teac_m, 2, ax[2,1], &#34;FRAP&#34;, &#34;TEAC&#34;, &#34;FRAP-MEOH vs TEAC-MEOH&#34;AttributeErrorInput In [26], in ()plt.subplots()Traceback (most recent call last)10 ax12 plt.scatter(xfa, yfa, s=6, color = 'blue')---> 13 confidence_ellipse(xfa, yfa, ax, n_std=1, label='FR&#34;, edgecolor='blue', linestyle='--')15 plt.scatter(xnfa, ynfa, s=6, color=&#34;orange&#34;)16 confidence_ellipse(xnfa, ynfa, ax, n_std=1, label='NF&#34;, edgecolor='orange', linestyle='--')File -\source\ellipses.py:58, in confidence_ellipse(x, y, ax, n_std, facecolor, **kwargs)51 mean y = np.mean(y)53 transf = transforms.Affine2D() \54.rotate_deg (45) \55.scale(scale_x, scale_y) \.translate(mean_x, nean_y)56--> 58 ellipse.set_transform(transf + ax. transData)59 return ax.add_patch(ellipse)AttributeError: 'tuple' object has no attribute 'transData'

Accepted Answer

error 404