Python - TypeError: expecting string or bytes object

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Based on the export data noted above, the problem you are experiencing is due to the fact that the data in one row is not the same type as the data in subsequent rows. In your case, in one row you have the value '04/02/13' (as a string) and in the next row you have the value 0 (as an integer). You will need to make sure that the data type is consistent for the column across all rows.

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theprowler
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theprowler

Updated on June 09, 2022

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  • theprowler
    theprowler almost 2 years

    After much research I cannot figure out why I receive this error in my code.

    I'm trying to export a Pandas Dataframe to my Oracle table. I have successfully done this hundreds of times on other data tables but this one keeps producing errors.

    Here is my Dataframe, which I read in with pd.read_excel and appended three of my own columns with simple df['column_name'] = variable commands:

    S USTAINABLE H ARVEST S ECTOR| QUOTA LISTING APRIL 16 2013 Unnamed: 1  \
    1                                                DATE           TRADE ID   
    2                                            04/02/13             130014   
    3                                                   0                  0   
    4                                                   0                  0   
    5                                                   0                  0   
    6                                 FY13 QUOTA – TO BUY                  0   
    7                                                DATE           TRADE ID   
    8                                             3/26/13             130006   
    9                                              4/9/13             130012   
    10                                            3/26/13             130007   
    11                                            3/26/13             130001   
    12                                            3/26/13             130009   
    13                                             4/9/13             130013   
    14                                            3/26/13             130010   
    15                                            3/26/13             130008   
    16                                            3/26/13             130011   
    17                                                  1                  0   
    
             Unnamed: 2     Unnamed: 3                     Unnamed: 4 email_year  \
    1   AVAILABLE STOCK         AMOUNT                      BUY PRICE       2013   
    2        WINTER SNE          12000            TRADE IN RETURN FOR       2013   
    3                 0              0                   HADDOCK GOM,       2013   
    4                 0              0             YELLOWTAIL GOM, OR       2013   
    5                 0              0                 WITCH - OFFERS       2013   
    6                 0              0                              0       2013   
    7     DESIRED STOCK         AMOUNT                      BUY PRICE       2013   
    8           COD GBE            ANY                         OFFERS       2013   
    9           COD GBW  UP TO 100,000                            0.3       2013   
    10          COD GBW            ANY                         OFFERS       2013   
    11          COD GOM        INQUIRE                            1.5       2013   
    12        WINTER GB            ANY                         OFFERS       2013   
    13       WINTER SNE  UP TO 100,000                            0.3       2013   
    14       WINTER SNE            ANY                         OFFERS       2013   
    15    YELLOWTAIL GB            ANY                         OFFERS       2013   
    16   YELLOWTAIL GOM            ANY  TRADE FOR GB STOCKS -\nOFFERS       2013   
    17                0              0                              0       2013   
    
       email_month email_day  
    1            4        16  
    2            4        16  
    3            4        16  
    4            4        16  
    5            4        16  
    6            4        16  
    7            4        16  
    8            4        16  
    9            4        16  
    10           4        16  
    11           4        16  
    12           4        16  
    13           4        16  
    14           4        16  
    15           4        16  
    16           4        16  
    17           4        16  
    

    My code fails on the export line cursor.executemany(sql_query, exported_data) with the error:

    Traceback (most recent call last):
      File "Z:\Code\successful_excel_pdf_code.py", line 74, in <module>
        cursor.executemany(sql_query, exported_data)
    TypeError: expecting string or bytes object
    

    Here is my relevant code:

    df = pd.read_excel(file_path)
    
    
    df = df.fillna(0)
    df = df.ix[1:]
    
    
    cursor = con.cursor()
    exported_data = [tuple(x) for x in df.values]
    #exported_data = [str(x) for x in df.values]
    #print("exported_data:", exported_data)
    
    sql_query = ("INSERT INTO FISHTABLE(date_posted, stock_id, species, pounds, advertised_price, email_year, email_month, email_day, sector_name, ask)" "VALUES(:1, :2, :3, :4, :5, :6, :7, :8, 'Sustainable Harvest Sector', '1')")
    
    cursor.executemany(sql_query, exported_data)
    
    con.commit() #commit to database
    
    cursor.close()
    con.close()
    

    Here is a printout of exported_data:

    [('DATE', 'TRADE ID', 'AVAILABLE STOCK', 'AMOUNT', 'BUY PRICE', '2013', '4', '16'), ('04/02/13', 130014, 'WINTER SNE', 12000, 'TRADE IN RETURN FOR', '2013', '4', '16'), (0, 0, 0, 0, 'HADDOCK GOM,', '2013', '4', '16'), (0, 0, 0, 0, 'YELLOWTAIL GOM, OR', '2013', '4', '16'), (0, 0, 0, 0, 'WITCH - OFFERS', '2013', '4', '16'), ('FY13 QUOTA – TO BUY', 0, 0, 0, 0, '2013', '4', '16'), ('DATE', 'TRADE ID', 'DESIRED STOCK', 'AMOUNT', 'BUY PRICE', '2013', '4', '16'), ('3/26/13', 130006, 'COD GBE', 'ANY', 'OFFERS', '2013', '4', '16'), ('4/9/13', 130012, 'COD GBW', 'UP TO 100,000', 0.3, '2013', '4', '16'), ('3/26/13', 130007, 'COD GBW', 'ANY', 'OFFERS', '2013', '4', '16'), ('3/26/13', 130001, 'COD GOM', 'INQUIRE', 1.5, '2013', '4', '16'), ('3/26/13', 130009, 'WINTER GB', 'ANY', 'OFFERS', '2013', '4', '16'), ('4/9/13', 130013, 'WINTER SNE', 'UP TO 100,000', 0.3, '2013', '4', '16'), ('3/26/13', 130010, 'WINTER SNE', 'ANY', 'OFFERS', '2013', '4', '16'), ('3/26/13', 130008, 'YELLOWTAIL GB', 'ANY', 'OFFERS', '2013', '4', '16'), ('3/26/13', 130011, 'YELLOWTAIL GOM', 'ANY', 'TRADE FOR GB STOCKS -\nOFFERS', '2013', '4', '16'), (1, 0, 0, 0, 0, '2013', '4', '16')]

    1) I thought the error could be from a lot of NaNs being scattered throughout the Dataframe, so I replaced them with 0's and it still fails.

    2) I then thought the error could be from trying to export the first couple rows which held no valuable information, so I deleted the first row with df = df.ix[1:] but it still fails.

    3) I also thought it could be failing because of the values in my email_year/month/day columns, so I changed them all to strings before putting them into my Dataframe, but it still fails.

    4) I tried changing the exported_data command to a str instead of a tuple but that only changed the error to cx_Oracle.DatabaseError: ORA-01036: illegal variable name/number. Also, it has always worked fine as a tuple when exporting other Dataframes.

    5) I thought the error could be from my Oracle columns not allowing either numbers or letters, but they are all set to all VarChar2 so that isn't the cause of the error either.

    I'd appreciated any help solving this, thanks.

  • theprowler
    theprowler about 7 years
    Ohh ok that makes enough sense... is there an easy enough way to do that? To change all datatypes of a Dataframe to the same one?
  • theprowler
    theprowler about 7 years
    So I figured it out and was able to change all the values to strings. Who knows why creating the Dataframe made some values strings and others integers. But thanks a ton for pointing out what was wrong with it, now I can proceed with exporting a ton of data
  • John Prawyn
    John Prawyn over 3 years
    Data type should be consistent across all rows is important.