fix / -> 7

@@ -2,6 +2,7 @@ import re
 import random
 import locale
 import numpy as np
+from datetime import datetime
 from pandas._libs import tslib
 from pandas._libs.tslibs.nattype import NaTType
 from pandas.core.indexes.datetimes import DatetimeIndex
@@ -255,7 +256,7 @@ class BSWorkbook(Workbook):
         date_col = date_col + 1
         for date_tuple_src in ws.iter_cols(min_col=date_col, max_col=date_col, min_row=min_row, values_only=True):
             date_tuple = [date[:10] if isinstance(date, str) else date for date in date_tuple_src]
-            dt_array, tz_parsed = tslib.array_to_datetime(
+            dt_array, _ = tslib.array_to_datetime(
                 np.array(date_tuple, copy=False, dtype=np.object_),
                 errors="coerce",
                 utc=False,
@@ -265,6 +266,22 @@ class BSWorkbook(Workbook):
             )
             dti = DatetimeIndex(dt_array, tz=None, name=None)
 
+            rebuid = False
+            for idx, d in enumerate(dti):
+                try:
+                    if isinstance(d, NaTType) and isinstance(date_tuple[idx], str):
+                        match_obj = re.match(r'(\d{4})[7/](\d{2})[7/](\d{2})', date_tuple[idx])
+                        if match_obj:
+                            dt_array[idx] = np.datetime64(datetime(int(match_obj.group(1)),
+                                                                   int(match_obj.group(2)),
+                                                                   int(match_obj.group(3))))
+                            rebuid = True
+                except Exception as e:
+                    continue
+                    
+            if rebuid:
+                dti = DatetimeIndex(dt_array, tz=None, name=None)
+
             month_list, idx_list = self.month_split(dti, date_list, date_statistics)
 
             if len(month_list) == 0: