percentiles_descriptive.py

# prtint min, max, median, first quartile, third quartile and random quartile
# using .quartile()
for i in num_col:
    print(f'Min: {train[i].quantile(0)} First Quartile: {train[i].quantile(0.25)}' 
          f'Median: {train[i].quantile(0.5)} Third Quartile: {train[i].quantile(0.75)}' 
          f'Max: {train[i].quantile(0)} Random Quartile(90%): {train[i].quantile(0.9)}')

# quartile for categorical variables
def percentile(n):
    def percentile_(x):
        return np.percentile(x, n)
    percentile_.__name__ = 'percentile_%s' % n
    return percentile_
  
print(train[['Item_MRP',
             'Outlet_Type']].groupby(['Outlet_Type']).agg({'Item_MRP':['min','max', percentile(25)]}))

# Here is code to create a box plot for the Item_MRP column.
train.boxplot(column="Item_MRP",
               return_type='axes',
               figsize=(8,8))

plt.text(x=0.74, y=185.64, s="3rd Quartile")
plt.text(x=0.8, y=140.99, s="Median")
plt.text(x=0.75, y=93.82, s="1st Quartile")
plt.text(x=0.9, y=31.29, s="Min")
plt.text(x=0.9, y=266.88, s="Max")
plt.text(x=0.6, y=140, s="IQR", rotation=90, size=40)
plt.show()