fetchone Method (Python)

.fetchone(). Fetches the next row (case) from the active dataset. The result is a single tuple or the Python data type None after the last row has been read. A value of None is also returned at a split boundary. In this case, a subsequent call to fetchone will retrieve the first case of the next split group.

  • This method is available in read or write mode.
  • Each element in the returned tuple contains the data value for a specific variable. The order of variable values in the tuple is the order specified by the variable index values in the optional argument n to the Cursor class, or file order if n is omitted. For example, if n=[5,2,7] the first tuple element is the value of the variable with index value 5, the second is the variable with index value 2, and the third is the variable with index value 7.
  • String values are right-padded to the defined width of the string variable.
  • System-missing values are always converted to the Python data type None.
  • By default, user-missing values are converted to the Python data type None. You can use the SetUserMissingInclude method to specify that user-missing values be treated as valid.
  • Values of variables with time formats are returned as integers representing the number of seconds from midnight.
  • By default, values of variables with date or datetime formats are returned as integers representing the number of seconds from October 14, 1582. You can specify to convert values of those variables to Python datetime.datetime objects with the cvtDates argument to the spss.Cursor function. See the topic spss.Cursor Class (Python) for more information.
  • If a weight variable has been defined for the active dataset, then cases with zero, negative, or missing values for the weighting variable are skipped when fetching data with fetchone, fetchall, or fetchmany. If you need to retrieve all cases when weighting is in effect, then you can use the Dataset class.
  • The fetchone, fetchall, and fetchmany methods honor case filters specified with the FILTER or USE commands.
DATA LIST FREE /var1 var2 var3.
BEGIN DATA
1 2 3
4 5 6
END DATA.
BEGIN PROGRAM.
import spss
dataCursor=spss.Cursor()
firstRow=dataCursor.fetchone()
secondRow=dataCursor.fetchone()
thirdRow=dataCursor.fetchone()
print("First row: ",firstRow)
print("Second row ",secondRow)
print("Third row...there is NO third row: ",thirdRow)
dataCursor.close()
END PROGRAM.

Result

First row:  (1.0, 2.0, 3.0)
Second row  (4.0, 5.0, 6.0)
Third row...there is NO third row:  None