Poverty Probability Index (PPI) lookup table for South Africa
Source:R/00_south_africa.R
ppiZAF2009.RdPoverty Probability Index (PPI) lookup table for South Africa
Format
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
nu100National upper poverty line (100%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
Examples
# Access South Africa PPI table
ppiZAF2009
#> score nl100 nlFood extreme nu100 ppp125 ppp250 ppp400
#> 0 0 98.0 92.8 78.9 100.0 76.3 95.9 100.0
#> 1 1 98.0 92.8 78.9 100.0 76.3 95.9 100.0
#> 2 2 98.0 92.8 78.9 100.0 76.3 95.9 100.0
#> 3 3 98.0 92.8 78.9 100.0 76.3 95.9 100.0
#> 4 4 98.0 92.8 78.9 100.0 76.3 95.9 100.0
#> 5 5 95.1 87.8 77.5 100.0 55.6 92.9 97.6
#> 6 6 95.1 87.8 77.5 100.0 55.6 92.9 97.6
#> 7 7 95.1 87.8 77.5 100.0 55.6 92.9 97.6
#> 8 8 95.1 87.8 77.5 100.0 55.6 92.9 97.6
#> 9 9 95.1 87.8 77.5 100.0 55.6 92.9 97.6
#> 10 10 96.3 77.0 54.7 99.6 40.5 92.5 99.1
#> 11 11 96.3 77.0 54.7 99.6 40.5 92.5 99.1
#> 12 12 96.3 77.0 54.7 99.6 40.5 92.5 99.1
#> 13 13 96.3 77.0 54.7 99.6 40.5 92.5 99.1
#> 14 14 96.3 77.0 54.7 99.6 40.5 92.5 99.1
#> 15 15 91.8 69.3 51.4 98.6 30.2 82.9 96.7
#> 16 16 91.8 69.3 51.4 98.6 30.2 82.9 96.7
#> 17 17 91.8 69.3 51.4 98.6 30.2 82.9 96.7
#> 18 18 91.8 69.3 51.4 98.6 30.2 82.9 96.7
#> 19 19 91.8 69.3 51.4 98.6 30.2 82.9 96.7
#> 20 20 81.9 50.9 37.9 97.2 21.6 70.1 94.7
#> 21 21 81.9 50.9 37.9 97.2 21.6 70.1 94.7
#> 22 22 81.9 50.9 37.9 97.2 21.6 70.1 94.7
#> 23 23 81.9 50.9 37.9 97.2 21.6 70.1 94.7
#> 24 24 81.9 50.9 37.9 97.2 21.6 70.1 94.7
#> 25 25 72.9 38.3 29.5 93.8 12.6 60.2 89.6
#> 26 26 72.9 38.3 29.5 93.8 12.6 60.2 89.6
#> 27 27 72.9 38.3 29.5 93.8 12.6 60.2 89.6
#> 28 28 72.9 38.3 29.5 93.8 12.6 60.2 89.6
#> 29 29 72.9 38.3 29.5 93.8 12.6 60.2 89.6
#> 30 30 64.2 24.8 18.6 92.6 5.1 45.4 81.6
#> 31 31 64.2 24.8 18.6 92.6 5.1 45.4 81.6
#> 32 32 64.2 24.8 18.6 92.6 5.1 45.4 81.6
#> 33 33 64.2 24.8 18.6 92.6 5.1 45.4 81.6
#> 34 34 64.2 24.8 18.6 92.6 5.1 45.4 81.6
#> 35 35 39.3 15.5 12.6 77.2 4.4 28.5 58.4
#> 36 36 39.3 15.5 12.6 77.2 4.4 28.5 58.4
#> 37 37 39.3 15.5 12.6 77.2 4.4 28.5 58.4
#> 38 38 39.3 15.5 12.6 77.2 4.4 28.5 58.4
#> 39 39 39.3 15.5 12.6 77.2 4.4 28.5 58.4
#> 40 40 29.6 10.3 7.1 73.8 2.0 20.3 47.9
#> 41 41 29.6 10.3 7.1 73.8 2.0 20.3 47.9
#> 42 42 29.6 10.3 7.1 73.8 2.0 20.3 47.9
#> 43 43 29.6 10.3 7.1 73.8 2.0 20.3 47.9
#> 44 44 29.6 10.3 7.1 73.8 2.0 20.3 47.9
#> 45 45 18.0 4.8 3.2 53.9 1.0 10.4 36.1
#> 46 46 18.0 4.8 3.2 53.9 1.0 10.4 36.1
#> 47 47 18.0 4.8 3.2 53.9 1.0 10.4 36.1
#> 48 48 18.0 4.8 3.2 53.9 1.0 10.4 36.1
#> 49 49 18.0 4.8 3.2 53.9 1.0 10.4 36.1
#> 50 50 5.4 1.1 1.0 27.9 0.4 2.6 13.7
#> 51 51 5.4 1.1 1.0 27.9 0.4 2.6 13.7
#> 52 52 5.4 1.1 1.0 27.9 0.4 2.6 13.7
#> 53 53 5.4 1.1 1.0 27.9 0.4 2.6 13.7
#> 54 54 5.4 1.1 1.0 27.9 0.4 2.6 13.7
#> 55 55 4.2 0.1 0.1 24.3 0.0 1.1 10.4
#> 56 56 4.2 0.1 0.1 24.3 0.0 1.1 10.4
#> 57 57 4.2 0.1 0.1 24.3 0.0 1.1 10.4
#> 58 58 4.2 0.1 0.1 24.3 0.0 1.1 10.4
#> 59 59 4.2 0.1 0.1 24.3 0.0 1.1 10.4
#> 60 60 0.9 0.4 0.4 11.0 0.0 0.4 5.0
#> 61 61 0.9 0.4 0.4 11.0 0.0 0.4 5.0
#> 62 62 0.9 0.4 0.4 11.0 0.0 0.4 5.0
#> 63 63 0.9 0.4 0.4 11.0 0.0 0.4 5.0
#> 64 64 0.9 0.4 0.4 11.0 0.0 0.4 5.0
#> 65 65 0.1 0.0 0.0 4.7 0.0 0.1 0.4
#> 66 66 0.1 0.0 0.0 4.7 0.0 0.1 0.4
#> 67 67 0.1 0.0 0.0 4.7 0.0 0.1 0.4
#> 68 68 0.1 0.0 0.0 4.7 0.0 0.1 0.4
#> 69 69 0.1 0.0 0.0 4.7 0.0 0.1 0.4
#> 70 70 0.0 0.0 0.0 1.4 0.0 0.0 0.0
#> 71 71 0.0 0.0 0.0 1.4 0.0 0.0 0.0
#> 72 72 0.0 0.0 0.0 1.4 0.0 0.0 0.0
#> 73 73 0.0 0.0 0.0 1.4 0.0 0.0 0.0
#> 74 74 0.0 0.0 0.0 1.4 0.0 0.0 0.0
#> 75 75 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 76 76 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 77 77 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 78 78 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 79 79 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 80 80 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 81 81 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 82 82 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 83 83 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 84 84 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 95 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 96 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 97 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 98 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 99 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiZAF2009[ppiZAF2009$score == ppiScore, ]
#> score nl100 nlFood extreme nu100 ppp125 ppp250 ppp400
#> 50 50 5.4 1.1 1 27.9 0.4 2.6 13.7
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiZAF2009, score == ppiScore)
#> score nl100 nlFood extreme nu100 ppp125 ppp250 ppp400
#> 50 50 5.4 1.1 1 27.9 0.4 2.6 13.7
# Given a specific PPI score (from 0 - 100), get a poverty probability
# based on a specific poverty definition. In this example, the national
# poverty line definition
ppiScore <- 50
ppiZAF2009[ppiZAF2009$score == ppiScore, "nl100"]
#> [1] 5.4