Plot with python

Matplotlib

• Build a figure

  fig = plt.figure()  # an empty figure with no Axes.
  

  or

  fig, ax = plt.subplots()  # Create a figure containing a single axes.
  

• Plot using plt.plot(), which automatically generates a figure and an axe with data on it.

  plt.plot([1, 2, 3, 4], [1, 4, 2, 3])  # Matplotlib plot.
  

• Plot using ax.plot(), which will plot data on the axe ax and the current figure.

  ax.plot([1, 2, 3, 4], [1, 4, 2, 3])  # Plot some data on the axes.
  

• Set legends

  plt.plot([1,2,3], label='cubic')
  plt.legend()
  

  or

  ax.plot([1, 2, 3], label='Inline label')
  ax.legend()
  

• Set title, x label, y label

  plt.xlabel('x label')
  plt.ylabel('y label')
  plt.title("Simple Plot")
  

  or

  ax.set_xlabel('x label')  # Add an x-label to the axes.
  ax.set_ylabel('y label')  # Add a y-label to the axes.
  ax.set_title("Simple Plot")  # Add a title to the axes.
  

• Subplots

  plt.figure(figsize=(9, 3))
  plt.subplot(131)
  plt.bar(names, values)
  plt.subplot(132)
  plt.scatter(names, values)
  plt.suptitle('Categorical Plotting')
  plt.show()
  

  or

  fig, axs = plt.subplots(2, 2)
  axs[0, 0].plot(x, y)
  axs[0, 0].set_title('Axis [0, 0]')
  axs[0, 1].plot(x, y, 'tab:orange')
  axs[0, 1].set_title('Axis [0, 1]')
  axs[1, 0].plot(x, -y, 'tab:green')
  axs[1, 0].set_title('Axis [1, 0]')
  axs[1, 1].plot(x, -y, 'tab:red')
  axs[1, 1].set_title('Axis [1, 1]')
  

• Customizing Figure Layouts Using GridSpec

  figure=plt.figure(figsize=figsize)
  spec=gridspec.GridSpec(ncols=2, nrows=2, figure=figure)
  for i in range(2):
    for j in range(2):
        ax=figure.add_subplot(spec[i,j])
        ax.set_xlabel('x')
        ax.set_ylabel('y')
        ax.plot(x,y,label='label')
        ax.legend()
  

  or

  fig2 = plt.figure(constrained_layout=True)
  spec2 = gridspec.GridSpec(ncols=2, nrows=2, figure=fig2)
  f2_ax1 = fig2.add_subplot(spec2[0, 0])
  f2_ax2 = fig2.add_subplot(spec2[0, 1])
  f2_ax3 = fig2.add_subplot(spec2[1, 0])
  f2_ax4 = fig2.add_subplot(spec2[1, 1])
  

• Hide x labels and tick labels for top plots and y ticks for right plots.

  for ax in axs.flat:
    ax.label_outer()
  

• Save Figure

  figure.savefig('fig.png',dpi=300)