Poverty Probability Index (PPI) lookup table for Rwanda
Format
A data frame with 11 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
Examples
# Access Rwanda PPI table
ppiRWA2016
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 0 0 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0
#> 1 1 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0
#> 2 2 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0
#> 3 3 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0
#> 4 4 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0
#> 5 5 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0
#> 6 6 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0
#> 7 7 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0
#> 8 8 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0
#> 9 9 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0
#> 10 10 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0
#> 11 11 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0
#> 12 12 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0
#> 13 13 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0
#> 14 14 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0
#> 15 15 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0
#> 16 16 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0
#> 17 17 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0
#> 18 18 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0
#> 19 19 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0
#> 20 20 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0
#> 21 21 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0
#> 22 22 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0
#> 23 23 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0
#> 24 24 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0
#> 25 25 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0
#> 26 26 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0
#> 27 27 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0
#> 28 28 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0
#> 29 29 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0
#> 30 30 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0
#> 31 31 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0
#> 32 32 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0
#> 33 33 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0
#> 34 34 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0
#> 35 35 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0
#> 36 36 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0
#> 37 37 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0
#> 38 38 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0
#> 39 39 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0
#> 40 40 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9
#> 41 41 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9
#> 42 42 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9
#> 43 43 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9
#> 44 44 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9
#> 45 45 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9
#> 46 46 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9
#> 47 47 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9
#> 48 48 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9
#> 49 49 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9
#> 50 50 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9
#> 51 51 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9
#> 52 52 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9
#> 53 53 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9
#> 54 54 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9
#> 55 55 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6
#> 56 56 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6
#> 57 57 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6
#> 58 58 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6
#> 59 59 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6
#> 60 60 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8
#> 61 61 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8
#> 62 62 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8
#> 63 63 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8
#> 64 64 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8
#> 65 65 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2
#> 66 66 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2
#> 67 67 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2
#> 68 68 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2
#> 69 69 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2
#> 70 70 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3
#> 71 71 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3
#> 72 72 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3
#> 73 73 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3
#> 74 74 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3
#> 75 75 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7
#> 76 76 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7
#> 77 77 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7
#> 78 78 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7
#> 79 79 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7
#> 80 80 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1
#> 81 81 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1
#> 82 82 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1
#> 83 83 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1
#> 84 84 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1
#> 85 85 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6
#> 86 86 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6
#> 87 87 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6
#> 88 88 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6
#> 89 89 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.9 45.6
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.9 45.6
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.9 45.6
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.9 45.6
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.9 45.6
#> 95 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
#> 96 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
#> 97 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
#> 98 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
#> 99 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
#> 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.6
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiRWA2016[ppiRWA2016$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 50 50 2.7 11 30.5 56.3 2 21.2 61.5 77.2 95.7 99.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiRWA2016, score == ppiScore)
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 50 50 2.7 11 30.5 56.3 2 21.2 61.5 77.2 95.7 99.9
# 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
ppiRWA2016[ppiRWA2016$score == ppiScore, "nl100"]
#> [1] 11