I have a made a function which plots input variables against predicted variables.

dummy_data = pd.DataFrame(np.random.uniform(low=65.5,high=140.5,size=(50,4)), columns=list('ABCD'))
dummy_predicted = pd.DataFrame(np.random.uniform(low=15.5,high=17.5,size=(50,4)), columns=list('WXYZ'))

##Plot test input distriubtions
fig = plt.figure(figsize=(15,6))
n_rows = 1 
n_cols = 4
counter = 1
for i in dummy_data.keys():
    plt.subplot(n_rows, n_cols, counter)
    plt.scatter(dummy_data[i], dummy_predicted['Z'])

    plt.title(f'{i} vs Z')
    plt.xlabel(i)
    counter  = 1

plt.tight_layout() 
plt.show()

How do I create a 4 x 4 subplot of all combinations of 'ABCD' and 'WXYZ'? I can have any number of dummy_data and dummy_predicted columns so some dynamism would be useful.

CodePudding user response：

• Use

  CodePudding user response：

  just do a double for loop

  n_rows = len(dummy_data.columns)
  n_cols = len(dummy_predicted.columns)
  
  fig, axes = plt.subplots(n_rows, n_cols, figsize=(15,6))
  
  for row, data_col in enumerate(dummy_data):
      for col, pred_col in enumerate(dummy_predicted):
          ax = axes[row][col]
  
          ax.scatter(dummy_data[data_col], dummy_predicted[pred_col])
          
          ax.set_title(f'{data_col} vs {pred_col}')
  
          ax.set_xlabel(data_col)
  
  plt.tight_layout() 
  plt.show()
  

  Output: