Year         Month   Day      Qty           Amount     Item   Customer
0     2003         9       1         30.0         220.80     N2719  3110361
1     2003         9       1          1.0          75.17     X1046  3126034
2     2003         9       1        240.0         379.20     D5853  0008933
3     2003         9       1       2112.0        2787.84     D5851  0008933
4     2003         9       1       3312.0        4371.84     D5851  0008933
...
...
<2.7M rows>

df.set_index(['Item', 'Customer', 'Year', 'Month', 'Day'], inplace=True, drop=True)
df.sortlevel(inplace=True)

Item      Customer     Year   Month   Day   Qty      Amount
X1046     3126034      2003   9       1     1.0      75.17
                       < ...  other transactions for X1046/3126034 item/customer combination ...>
          3126035      2005   1       2     50.0     500.00
                        < ...  other transactions for X1046/3126035 item/customer combination ...>
      < ... 48 other customers for X1046 ...>

N2719     3110361      2003    9      1     30.0      220.80
                       < ...  other transactions for N2719/3110361 item/customer combination ...>
          3110362      2004    9      10     9.0     823.00
                       < ...  other transactions for N2719/3110362 item/customer combination ...>
      < ... 198 other customers for N2719 ... >
< ... 6998 other items ... >

item_by_customers = df.reset_index().groupby('Item')['Customer'].nunique().sort_values(ascending=False)

Item
N2719    200
X1046     50
<... 6998 other rows ...>

sorted_data = df.set_index(item_by_customers.index)
< ... gives me ValueError: Length mismatch: Expected axis has 2.7M elements, new values have 7000 elements ...>

sorted_data = df.reindex(index=item_by_customers.index, columns=['Item'])
< ... gives me Exception: cannot handle a non-unique multi-index! ...>

Item      Customer     Year   Month   Day   Qty      Amount
N2719     3110361      2003    9      1     30.0      220.80
                       < ...  other transactions for N2719/3110361 item/customer combination ...>
          3110362      2004    9      10     9.0     823.00
                       < ...  other transactions for N2719/3110362 item/customer combination ...>
      < ... 198 other customers for N2719 ... >

X1046     3126034      2003   9       1     1.0      75.17
                       < ...  other transactions for X1046/3126034 item/customer combination ...>
          3126035      2005   1       2     50.0     500.00
                        < ...  other transactions for X1046/3126035 item/customer combination ...>
      < ... 48 other customers for X1046 ...>

< ... 6998 other items ... >

i = df.groupby('Item').Customer.transform('nunique').mul(-1).argsort()
df.iloc[i]