Gap between bars of the same year after each loop

I have a program/function that plots a graph like this -

What I am trying to do is stack the bars of the same year side by side, then leave some gap in between, and then stack the bars of another year side by side again. I am not able to solve this problem.

This is the code/function to plot the graph(for reference) -

def plot_monthly_multiple_store2():
    df = order_merged.multi_store_monthly_count([2020,2021], [1,2,3,4], ['Crizac','Ucol'])
    df['year'] = df['date_added'].dt.year
    df['month'] = df['date_added'].dt.month

    # Calculate count by year and month
    count_df = df.groupby(['year', 'month', 'store_type'])['order_id'].count().reset_index()

    # Pivot the count data by year and month
    pivot_df = pd.pivot_table(count_df, values='order_id', index=['year', 'month'], columns=['store_type'], fill_value=0)
    print(pivot_df,"\n")
    print(pivot_df.index.levels[1],"\n")
    print(pivot_df.index[:(len(pivot_df.index)//2)])
    # Plot the stacked bar chart
    fig, ax = plt.subplots(figsize=(10, 5))

    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd']

    width = 0.8 / len(pivot_df.index.levels[0])
    print(pivot_df.loc[2020,1])
    # print(pivot_df.loc[2021].index)
    
    for i, year in enumerate(pivot_df.index.levels[0]):
        x_pos = np.arange(len(pivot_df.loc[year].index)) + i*len(pivot_df.loc[year].index)
        print(x_pos,"\n")
        for j, store_type in enumerate(pivot_df.columns):
            ax.bar(x_pos, pivot_df.loc[year, store_type], width=width, align='edge', color=colors[j], alpha = 0.7, edgecolor='black', linewidth = 0.5, label=store_type if i==0 else None)
            
            for x, y in zip(x_pos, pivot_df.loc[year, store_type]):
                ax.text(x + width / 2, y, str(y), ha='center', va='bottom', fontsize=8)
    
    ax.set_xticks(np.arange(len(pivot_df.index)))
    ax.set_xticklabels([f"{calendar.month_abbr[month]}\n{year}" for year, month in pivot_df.index], fontsize=8)

    ax.set_xlabel('Year', fontsize=12)
    ax.set_ylabel('Count', fontsize=12)
    ax.set_title('Order Count by Month and Store Type', fontsize=14)

    ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))

    plt.tight_layout()
    plt.show()

I don't know the Pandas well, but I hope it helps.

from pandas import DataFrame as DF
import matplotlib.pyplot as plt
import pandas as pd

# creating dummy data
df = DF()
df['date'] = ['2020-01', '2020-02', '2020-03', '2020-04',
              '2021-01', '2021-02', '2021-03', '2021-04']

df['C'] = [10, 20, 30, 40,
           50, 60, 70, 80]

df['R'] = [100, 120, 130, 140,
           120, 150, 130, 150]

df['date'] = pd.to_datetime(df['date'])

gap = 5.0
x_labels = df['date'].dt.strftime('%b\n%Y')

df20 = df[df['date'].dt.year == 2020]
df21 = df[df['date'].dt.year == 2021]

x20 = df20['date'].dt.month
x21 = df21['date'].dt.month + gap

fig, ax = plt.subplots()
r1 = ax.bar(x20, df20['R'], align='edge', color='blue')
r2 = ax.bar(x20, df20['C'], align='edge', color='orange')

r3 = ax.bar(x21, df21['R'], align='edge', color='blue')
r4 = ax.bar(x21, df21['C'], align='edge', color='orange')

ax.set_xticks([*x20, *x21], x_labels)
ax.bar_label(r1)
ax.bar_label(r2)
ax.bar_label(r3)
ax.bar_label(r4)

My dummy data:

        date   C    R
0 2020-01-01  10  100
1 2020-02-01  20  120
2 2020-03-01  30  130
3 2020-04-01  40  140
4 2021-01-01  50  120
5 2021-02-01  60  150
6 2021-03-01  70  130
7 2021-04-01  80  150