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How can I remove borders/frames of subplots while plotting xarray dataset using imshow of matplotlib in Python?

I have a netCDF file downloaded from the NASA website called gistemp1200_GHCNv4_ERSSTv5.nc.gz

I open the data using xarray that contains temperature anomaly data.

import xarray as xr
file = "../data/gistemp1200_GHCNv4_ERSSTv5.nc"
xr_df = xr.open_dataset(file)

xr_df_annual = xr_df.resample(time = "Y").mean()

anomaly = xr_df_annual["tempanomaly"]

anomaly looks as follows: enter image description here

It contains annual temperature anomaly value relative to certain time period.

I want to plot the annual temperature values for four years in the form of subplots. I use the following code:

fig, axs = plt.subplots(2, 2, figsize = (10, 10))

fig.suptitle("Temperature anomaly in the end of last four decades\n relative to 1951-1980")

def get_plot(year, i, j, k):
 
    ax = fig.add_subplot(2, 2, k, 
                         projection = ccrs.PlateCarree())
    
    ax.add_feature(NaturalEarthFeature('cultural', 'admin_0_countries', '10m'),
                       facecolor='none', edgecolor='black')

    ax.set_extent([-150, 150, -55, 85])
    
    xr_df_sub = anomaly.loc[f"{year}-12-31"]
    
    ax.set_title(f"{year}")
    
    ax.set_axis_off()
    
    xr.plot.imshow(xr_df_sub,
                  ax = ax,
                  add_labels = False,
                  vmin = -4, vmax = 4,
                  cmap = "coolwarm",
                   add_colorbar = False,
                  interpolation = "bicubic")
    
    
axs[0, 0] = get_plot(1990, 0, 0, 1)

axs[0, 1] = get_plot(2000, 0, 1, 2)

axs[1, 0] = get_plot(2010, 0, 1, 3)


axs[1, 1] = get_plot(2020, 0, 1, 4)

# add colorbar
cax = fig.add_axes([0.92, 0.15, 0.01, 0.7]) #[left, bottom, width, height]
sm = plt.cm.ScalarMappable(cmap='coolwarm',
                           norm=plt.Normalize(vmin= -4, vmax= 4))

# fake up the array of the scalar mappable.
sm._A = []
lgd=fig.colorbar(sm, cax=cax, extend = "both"
                 ).set_label("°C", rotation=0,y=1.1, labelpad= -35)


plt.show()

I created a function called get_plot(year, i, j, k) for each subplot. i, j refer to row and column number and k refer to the index number of the subplot. The function to plot the temperature anomaly for given year.

I got a plot as shown below: enter image description here

This is the desired plot, however, I am getting outer black frames for each subplot, which I want to remove. I used following code:

ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

However, it does not change anything. I also tried

fig.patch.set_visible(False)

It also does not change anything.

How can I remove the outer borders with 0 to 1 in x-axis and y-axis for each subplot? Also, I'd like to get advice on bringing subplots closer to each other?

Solution

  • Based on suggestion of Dahn, I figured out that I had used plt.subplot() and again used fig.add_subplot() twice.

    I solved the problem as follows:

    fig = plt.figure(figsize = (10, 10))

    fig.suptitle("Temperature anomaly in the end of last four decades\n relative to 1951-1980", y = 0.8)

    plt.subplots_adjust(bottom = 0.3, top = 0.7, wspace=0.1, hspace= 0.25)

    def get_plot(year, i, j, k):
 
    ax = fig.add_subplot(2, 2, k, 
                         projection = ccrs.PlateCarree())
    
    ax.add_feature(NaturalEarthFeature('cultural', 'admin_0_countries', '10m'),
                       facecolor='none', edgecolor='black')

    ax.set_extent([-150, 150, -55, 85])
    
    xr_df_sub = anomaly.loc[f"{year}-12-31"]
    
    ax.set_title(f"{year}")
    
    ax.axis("off")
    
    ax = xr.plot.imshow(xr_df_sub,

              add_labels = True,
              vmin = -4, vmax = 4,
              cmap = "coolwarm",
               add_colorbar = False,
              interpolation = "bicubic",
              )
    
    return ax
    
ax[0, 0] = get_plot(1990, 0, 0, 1)

ax[0, 1] = get_plot(2000, 0, 1, 2)

ax[1, 0] = get_plot(2010, 0, 1, 3)


ax[1, 1] = get_plot(2020, 0, 1, 4)

# add colorbar
cax = fig.add_axes([0.92, 0.3, 0.02, 0.5]) #[left, bottom, width, height]
sm = plt.cm.ScalarMappable(cmap='coolwarm',
                           norm=plt.Normalize(vmin= -4, vmax= 4))

# fake up the array of the scalar mappable.
sm._A = []
lgd=fig.colorbar(sm, cax=cax, extend = "both"
                 ).set_label("°C", rotation=0,y=1.1, labelpad= -35)

plt.show()

    I got the required plot as shown below: enter image description here