Df has columns Client, Product, StartDate, EndDate.

# Create a new empty DataFrame to store the expanded date ranges
expanded_df = pd.DataFrame(columns=df.columns)


# Iterate over each row in the original DataFrame
for _, row in df.iterrows():
    # Get the start and end date for the row
    start_date = row['StartDate']
    end_date = row['EndDate']
    
    # Generate a date range from the start date to the end date (inclusive)
    date_range = pd.date_range(start=start_date, end=end_date, inclusive='both')
    
    # Create a new DataFrame with the expanded date range for the row
    row_df = pd.DataFrame([[row['Client'], row['Product'], start_date, end_date, d] for d in date_range], 
                          columns=df.columns)
    
    # Append the row DataFrame to the expanded DataFrame
    expanded_df = expanded_df.append(row_df, ignore_index=True)

# Output the expanded DataFrame
print(expanded_df)

Fix the error
AssertionError                            Traceback (most recent call last)
File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\internals\construction.py:969, in _finalize_columns_and_data(content, columns, dtype)
    968 try:
--> 969     columns = _validate_or_indexify_columns(contents, columns)
    970 except AssertionError as err:
    971     # GH#26429 do not raise user-facing AssertionError

File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\internals\construction.py:1017, in _validate_or_indexify_columns(content, columns)
   1015 if not is_mi_list and len(columns) != len(content):  # pragma: no cover
   1016     # caller's responsibility to check for this...
-> 1017     raise AssertionError(
   1018         f"{len(columns)} columns passed, passed data had "
   1019         f"{len(content)} columns"
   1020     )
   1021 elif is_mi_list:
   1022 
   1023     # check if nested list column, length of each sub-list should be equal

AssertionError: 4 columns passed, passed data had 5 columns

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
Cell In[29], line 15
     12 date_range = pd.date_range(start=start_date, end=end_date, inclusive='right')
     14 # Create a new DataFrame with the expanded date range for the row
---> 15 row_df = pd.DataFrame([[row['Client'], row['Product'], start_date, end_date, d] for d in date_range], 
     16                       columns=df.columns)
     18 # Append the row DataFrame to the expanded DataFrame
     19 expanded_df = expanded_df.append(row_df, ignore_index=True)

File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\frame.py:746, in DataFrame.__init__(self, data, index, columns, dtype, copy)
    744     if columns is not None:
    745         columns = ensure_index(columns)
--> 746     arrays, columns, index = nested_data_to_arrays(
    747         # error: Argument 3 to "nested_data_to_arrays" has incompatible
    748         # type "Optional[Collection[Any]]"; expected "Optional[Index]"
    749         data,
    750         columns,
    751         index,  # type: ignore[arg-type]
    752         dtype,
    753     )
    754     mgr = arrays_to_mgr(
    755         arrays,
    756         columns,
   (...)
    759         typ=manager,
    760     )
    761 else:

File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\internals\construction.py:510, in nested_data_to_arrays(data, columns, index, dtype)
    507 if is_named_tuple(data[0]) and columns is None:
    508     columns = ensure_index(data[0]._fields)
--> 510 arrays, columns = to_arrays(data, columns, dtype=dtype)
    511 columns = ensure_index(columns)
    513 if index is None:

File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\internals\construction.py:875, in to_arrays(data, columns, dtype)
    872     data = [tuple(x) for x in data]
    873     arr = _list_to_arrays(data)
--> 875 content, columns = _finalize_columns_and_data(arr, columns, dtype)
    876 return content, columns

File ~\AppData\Local\anaconda3\Lib\site-packages\pandas\core\internals\construction.py:972, in _finalize_columns_and_data(content, columns, dtype)
    969     columns = _validate_or_indexify_columns(contents, columns)
    970 except AssertionError as err:
    971     # GH#26429 do not raise user-facing AssertionError
--> 972     raise ValueError(err) from err
    974 if len(contents) and contents[0].dtype == np.object_:
    975     contents = _convert_object_array(contents, dtype=dtype)

ValueError: 4 columns passed, passed data had 5 columns