ts.varp() | Teradata R Package - 17.00 - ts.varp() - Teradata R Package

Teradata® R Package User Guide

prodname
Teradata R Package
vrm_release
17.00
created_date
November 2020
category
User Guide
featnum
B700-4005-090K

The aggregate function ts.var() returns the population variance of values of the column grouped by time.

The variance of a population is a measure of dispersion from the mean of that population.

  • When there are fewer than two non-NULL data points in the population used for the computation, ts.varp() returns NULL/NA.
  • Nulls are not included in the result computation.
  • Division by zero results in NULL/NA value rather than an error.
  • ts.varp() can only be used if data represents entire population. Otherwise, Teradata recommends to use ts.var() to calculate sample variance.
Arguments:
  • value.expression: Specify the column for which population variance is to be computed.

Use ts.varp(distinct(column_name)) to exclude duplicate rows while calculating population variance.

Example 1: Calculate the population variance of values in the 'temperature' column of sequenced PTI table

  • Calculate the population variance.
    > df_seq_varp <- df_seq_grp %>% summarise(varp_temp = ts.varp(temperature))
  • Print the results.
    > df_seq_varp %>% arrange(TIMECODE_RANGE, buoyid, varp_temp)
    # Source:     lazy query [?? x 4]
    # Database:   [Teradata 16.20.50.01] [Teradata Native Driver 17.0.0.2]
    #   [TDAPUSER@<hostname>/TDAPUSERDB]
    # Ordered by: TIMECODE_RANGE, buoyid, varp_temp
      TIMECODE_RANGE                                    `GROUP BY TIME(MINUTES(~ buoyid varp_temp
      <chr>                                             <int64>                   <int>     <dbl>
    1 2014-01-06 08:00:00.000000+00:00,2014-01-06 08:3~ 35345                         0  2003.  
    2 2014-01-06 09:00:00.000000+00:00,2014-01-06 09:3~ 35347                         1    12.9 
    3 2014-01-06 10:00:00.000000+00:00,2014-01-06 10:3~ 35349                        44    30.7 
    4 2014-01-06 10:30:00.000000+00:00,2014-01-06 11:0~ 35350                        22     0   
    5 2014-01-06 10:30:00.000000+00:00,2014-01-06 11:0~ 35350                        44     0   
    6 2014-01-06 21:00:00.000000+00:00,2014-01-06 21:3~ 35371                         2     0.667

Example 2: Calculate the population variance of values in the 'temperature' column of non-PTI table

  • Calculate the population variance.
    > df_nonpti_varp <- df_nonpti %>% group_by_time(timebucket.duration = "10m", timecode.column = "TIMECODE") %>% summarise(varp_temp = ts.varp(temperature))
  • Print the results.
    > df_nonpti_varp %>% arrange(TIMECODE_RANGE, varp_temp)
    # Source:     lazy query [?? x 3]
    # Database:   [Teradata 16.20.50.01] [Teradata Native Driver 17.0.0.2]
    #   [TDAPUSER@<hostname>/TDAPUSERDB]
    # Ordered by: TIMECODE_RANGE, varp_temp
      TIMECODE_RANGE                                          `GROUP BY TIME(MINUTES(1~ varp_temp
      <chr>                                                   <int64>                       <dbl>
    1 2014-01-06 08:00:00.000000+00:00,2014-01-06 08:10:00.0~ 2314993                    1980.  
    2 2014-01-06 08:10:00.000000+00:00,2014-01-06 08:20:00.0~ 2314994                    2025   
    3 2014-01-06 09:00:00.000000+00:00,2014-01-06 09:10:00.0~ 2314999                      12.9 
    4 2014-01-06 10:00:00.000000+00:00,2014-01-06 10:10:00.0~ 2315005                      29.8 
    5 2014-01-06 10:10:00.000000+00:00,2014-01-06 10:20:00.0~ 2315006                       0   
    6 2014-01-06 10:30:00.000000+00:00,2014-01-06 10:40:00.0~ 2315008                       0   
    7 2014-01-06 10:50:00.000000+00:00,2014-01-06 11:00:00.0~ 2315010                       0   
    8 2014-01-06 21:00:00.000000+00:00,2014-01-06 21:10:00.0~ 2315071                       0.667