My Thoughts
The first time that I’ve heard about Stream-graph was in 608 class where we were doing live coding demo to figure out how to use d3 to achieve plotting data in the webpage few days ago. I was confused at that time because compared to other intuitive graphs, stream-graph was not easy to interpret. I understand that different colors shown represented distinct categories. Then, what about the squiggly shape? What about the width of each category? Meanwhile, I also wondered why we need to use stream-graph and when the situation is where stream-graph has advantages over other plots and how to make a stream-graph in R.
By carrying these questions, I started doing some general research about it and find that it is nothing more than a basic stacked area chart, with fancier design and presentation. It shows the changes in a numeric variable against another numeric variable, in which I would say that it shows some relationships between x-axis and y-axis. Moreover, instead of study individual group using stream-graph, it is better to use it while studying relative proportions of the whole. According to data to viz, “it is very hard to substract the height of other groups at each time point”.
Make A Stream Graph
Data
only 1 missing value, it can be filtered out
## Country.Name Country.Code X1960 X1961
## Length:120 Length:120 Min. :1.201e+07 Min. :1.159e+07
## Class :character Class :character 1st Qu.:4.363e+08 1st Qu.:4.747e+08
## Mode :character Mode :character Median :2.724e+09 Median :2.667e+09
## Mean :7.738e+10 Mean :7.919e+10
## 3rd Qu.:2.926e+10 3rd Qu.:3.041e+10
## Max. :1.390e+12 Max. :1.440e+12
## NA's :1
## X1962 X1963 X1964
## Min. :1.254e+07 Min. :1.283e+07 Min. :1.342e+07
## 1st Qu.:4.716e+08 1st Qu.:5.082e+08 1st Qu.:5.418e+08
## Median :3.051e+09 Median :3.571e+09 Median :3.184e+09
## Mean :8.418e+10 Mean :9.092e+10 Mean :9.976e+10
## 3rd Qu.:3.295e+10 3rd Qu.:3.775e+10 3rd Qu.:3.687e+10
## Max. :1.550e+12 Max. :1.670e+12 Max. :1.820e+12
##
## X1965 X1966 X1967
## Min. :1.359e+07 Min. :1.447e+07 Min. :1.584e+07
## 1st Qu.:6.561e+08 1st Qu.:6.940e+08 1st Qu.:7.417e+08
## Median :3.590e+09 Median :4.231e+09 Median :4.194e+09
## Mean :1.092e+11 Mean :1.178e+11 Mean :1.245e+11
## 3rd Qu.:4.106e+10 3rd Qu.:4.430e+10 3rd Qu.:4.380e+10
## Max. :1.990e+12 Max. :2.160e+12 Max. :2.290e+12
##
## X1968 X1969 X1970
## Min. :1.460e+07 Min. :1.585e+07 Min. :1.630e+07
## 1st Qu.:7.689e+08 1st Qu.:7.863e+08 1st Qu.:8.549e+08
## Median :4.571e+09 Median :5.727e+09 Median :6.061e+09
## Mean :1.339e+11 Mean :1.481e+11 Mean :1.621e+11
## 3rd Qu.:4.683e+10 3rd Qu.:5.355e+10 3rd Qu.:6.300e+10
## Max. :2.480e+12 Max. :2.730e+12 Max. :2.990e+12
##
## X1971 X1972 X1973
## Min. :1.962e+07 Min. :2.294e+07 Min. :2.420e+07
## 1st Qu.:8.933e+08 1st Qu.:1.069e+09 1st Qu.:1.290e+09
## Median :6.511e+09 Median :6.548e+09 Median :8.058e+09
## Mean :1.780e+11 Mean :2.042e+11 Mean :2.501e+11
## 3rd Qu.:6.409e+10 3rd Qu.:7.239e+10 3rd Qu.:9.262e+10
## Max. :3.300e+12 Max. :3.800e+12 Max. :4.640e+12
##
## X1974 X1975 X1976
## Min. :3.151e+07 Min. :3.324e+07 Min. :3.010e+07
## 1st Qu.:1.636e+09 1st Qu.:2.108e+09 1st Qu.:2.355e+09
## Median :1.098e+10 Median :1.073e+10 Median :1.196e+10
## Mean :2.907e+11 Mean :3.232e+11 Mean :3.499e+11
## 3rd Qu.:1.210e+11 3rd Qu.:1.330e+11 3rd Qu.:1.330e+11
## Max. :5.350e+12 Max. :5.960e+12 Max. :6.480e+12
##
## X1977 X1978 X1979
## Min. :4.450e+07 Min. :4.943e+07 Min. :5.884e+07
## 1st Qu.:2.452e+09 1st Qu.:2.611e+09 1st Qu.:2.986e+09
## Median :1.429e+10 Median :1.617e+10 Median :2.045e+10
## Mean :3.952e+11 Mean :4.597e+11 Mean :5.341e+11
## 3rd Qu.:1.540e+11 3rd Qu.:1.645e+11 3rd Qu.:1.960e+11
## Max. :7.330e+12 Max. :8.630e+12 Max. :1.000e+13
##
## X1980 X1981 X1982
## Min. :6.846e+07 Min. :8.089e+07 Min. :8.602e+07
## 1st Qu.:3.717e+09 1st Qu.:3.365e+09 1st Qu.:3.272e+09
## Median :2.407e+10 Median :2.655e+10 Median :2.607e+10
## Mean :6.052e+11 Mean :6.383e+11 Mean :6.310e+11
## 3rd Qu.:2.338e+11 3rd Qu.:2.535e+11 3rd Qu.:2.590e+11
## Max. :1.130e+13 Max. :1.170e+13 Max. :1.160e+13
##
## X1983 X1984 X1985
## Min. :8.687e+07 Min. :9.860e+07 Min. :1.110e+08
## 1st Qu.:3.199e+09 1st Qu.:3.390e+09 1st Qu.:3.251e+09
## Median :2.400e+10 Median :2.266e+10 Median :2.470e+10
## Mean :6.379e+11 Mean :6.598e+11 Mean :6.962e+11
## 3rd Qu.:2.425e+11 3rd Qu.:2.600e+11 3rd Qu.:2.470e+11
## Max. :1.180e+13 Max. :1.220e+13 Max. :1.290e+13
##
## X1986 X1987 X1988
## Min. :1.307e+08 Min. :1.477e+08 Min. :1.727e+08
## 1st Qu.:3.793e+09 1st Qu.:3.710e+09 1st Qu.:3.833e+09
## Median :2.822e+10 Median :3.277e+10 Median :3.652e+10
## Mean :8.049e+11 Mean :9.059e+11 Mean :1.008e+12
## 3rd Qu.:2.550e+11 3rd Qu.:2.900e+11 3rd Qu.:2.980e+11
## Max. :1.520e+13 Max. :1.730e+13 Max. :1.930e+13
##
## X1989 X1990 X1991
## Min. :1.925e+08 Min. :2.173e+08 Min. :2.205e+08
## 1st Qu.:4.289e+09 1st Qu.:4.520e+09 1st Qu.:4.065e+09
## Median :3.904e+10 Median :4.202e+10 Median :4.567e+10
## Mean :1.049e+12 Mean :1.181e+12 Mean :1.229e+12
## 3rd Qu.:2.970e+11 3rd Qu.:3.375e+11 3rd Qu.:3.380e+11
## Max. :2.010e+13 Max. :2.270e+13 Max. :2.370e+13
##
## X1992 X1993 X1994
## Min. :2.421e+08 Min. :2.638e+08 Min. :2.894e+08
## 1st Qu.:4.320e+09 1st Qu.:4.597e+09 1st Qu.:4.547e+09
## Median :4.844e+10 Median :5.088e+10 Median :5.465e+10
## Mean :1.316e+12 Mean :1.347e+12 Mean :1.459e+12
## 3rd Qu.:3.578e+11 3rd Qu.:3.608e+11 3rd Qu.:3.922e+11
## Max. :2.540e+13 Max. :2.580e+13 Max. :2.790e+13
##
## X1995 X1996 X1997
## Min. :3.135e+08 Min. :3.315e+08 Min. :3.478e+08
## 1st Qu.:5.237e+09 1st Qu.:5.574e+09 1st Qu.:5.738e+09
## Median :6.489e+10 Median :6.956e+10 Median :7.264e+10
## Mean :1.624e+12 Mean :1.672e+12 Mean :1.676e+12
## 3rd Qu.:4.062e+11 3rd Qu.:4.425e+11 3rd Qu.:4.685e+11
## Max. :3.100e+13 Max. :3.170e+13 Max. :3.160e+13
##
## X1998 X1999 X2000
## Min. :3.736e+08 Min. :3.907e+08 Min. :3.963e+08
## 1st Qu.:6.173e+09 1st Qu.:5.870e+09 1st Qu.:6.148e+09
## Median :6.718e+10 Median :6.907e+10 Median :7.994e+10
## Mean :1.668e+12 Mean :1.729e+12 Mean :1.800e+12
## 3rd Qu.:4.452e+11 3rd Qu.:4.860e+11 3rd Qu.:5.460e+11
## Max. :3.150e+13 Max. :3.270e+13 Max. :3.380e+13
##
## X2001 X2002 X2003
## Min. :4.300e+08 Min. :4.619e+08 Min. :4.699e+08
## 1st Qu.:6.251e+09 1st Qu.:6.176e+09 1st Qu.:7.285e+09
## Median :7.648e+10 Median :8.211e+10 Median :8.940e+10
## Mean :1.793e+12 Mean :1.862e+12 Mean :2.088e+12
## 3rd Qu.:5.412e+11 3rd Qu.:5.902e+11 3rd Qu.:6.588e+11
## Max. :3.360e+13 Max. :3.490e+13 Max. :3.910e+13
##
## X2004 X2005 X2006
## Min. :5.069e+08 Min. :5.472e+08 Min. :6.109e+08
## 1st Qu.:8.564e+09 1st Qu.:9.574e+09 1st Qu.:1.029e+10
## Median :1.036e+11 Median :1.215e+11 Median :1.430e+11
## Mean :2.360e+12 Mean :2.580e+12 Mean :2.825e+12
## 3rd Qu.:7.640e+11 3rd Qu.:8.792e+11 3rd Qu.:9.938e+11
## Max. :4.410e+13 Max. :4.780e+13 Max. :5.180e+13
##
## X2007 X2008 X2009
## Min. :6.844e+08 Min. :6.954e+08 Min. :6.749e+08
## 1st Qu.:1.218e+10 1st Qu.:1.377e+10 1st Qu.:1.267e+10
## Median :1.650e+11 Median :1.810e+11 Median :1.740e+11
## Mean :3.215e+12 Mean :3.567e+12 Mean :3.426e+12
## 3rd Qu.:1.182e+12 3rd Qu.:1.270e+12 3rd Qu.:1.250e+12
## Max. :5.830e+13 Max. :6.400e+13 Max. :6.070e+13
##
## X2010 X2011 X2012
## Min. :6.812e+08 Min. :6.761e+08 Min. :6.929e+08
## 1st Qu.:1.434e+10 1st Qu.:1.776e+10 1st Qu.:1.769e+10
## Median :2.135e+11 Median :2.365e+11 Median :2.250e+11
## Mean :3.811e+12 Mean :4.266e+12 Mean :4.404e+12
## 3rd Qu.:1.440e+12 3rd Qu.:1.610e+12 3rd Qu.:1.680e+12
## Max. :6.650e+13 Max. :7.370e+13 Max. :7.530e+13
##
## X2013 X2014 X2015
## Min. :7.212e+08 Min. :7.277e+08 Min. :7.554e+08
## 1st Qu.:1.878e+10 1st Qu.:1.959e+10 1st Qu.:1.942e+10
## Median :2.345e+11 Median :2.395e+11 Median :2.165e+11
## Mean :4.565e+12 Mean :4.712e+12 Mean :4.499e+12
## 3rd Qu.:1.790e+12 3rd Qu.:1.850e+12 3rd Qu.:1.680e+12
## Max. :7.740e+13 Max. :7.960e+13 Max. :7.510e+13
##
## X2016 X2017 X2018
## Min. :7.744e+08 Min. :7.922e+08 Min. :8.113e+08
## 1st Qu.:2.071e+10 1st Qu.:2.204e+10 1st Qu.:2.354e+10
## Median :2.310e+11 Median :2.525e+11 Median :2.750e+11
## Mean :4.565e+12 Mean :4.886e+12 Mean :5.207e+12
## 3rd Qu.:1.560e+12 3rd Qu.:1.670e+12 3rd Qu.:1.750e+12
## Max. :7.630e+13 Max. :8.120e+13 Max. :8.630e+13
##
## X2019 X2020
## Min. :8.250e+08 Min. :8.075e+08
## 1st Qu.:2.328e+10 1st Qu.:2.052e+10
## Median :2.740e+11 Median :2.580e+11
## Mean :5.303e+12 Mean :5.147e+12
## 3rd Qu.:1.800e+12 3rd Qu.:1.702e+12
## Max. :8.760e+13 Max. :8.470e+13
## Data Before Reshape
## Country.Name Country.Code X1960 X1961 X1962
## 1 Africa Eastern and Southern AFE 19313106302 19723488057 21493920015
## 2 Africa Western and Central AFW 10404280784 11128050589 11943353288
## 3 Australia AUS 18606786874 19683055213 19922723709
## 4 Austria AUT 6592693841 7311749633 7756110210
## 5 Burundi BDI 195999990 202999992 213500006
## 6 Belgium BEL 11658722591 12400145222 13264015675
## X1963 X1964 X1965 X1966 X1967 X1968
## 1 25733212134 23527443251 26810567154 29152157362 30173172663 32877055829
## 2 12676515454 13838577015 14862472886 15832846881 14426432397 14880350847
## 3 21539926084 23801097547 25977153097 27309889125 30444618658 32716989584
## 4 8374175258 9169983886 9994070616 10887682273 11579431669 12440625313
## 5 232749998 260750008 158994963 165444571 178297143 183200000
## 6 14260017387 15960106681 17371457608 18651883472 19992040788 21376353113
## X1969 X1970 X1971 X1972 X1973 X1974
## 1 37744346869 40315782854 44476662703 48301485014 62983498805 78250886611
## 2 16882094303 23504608015 20832819361 25264956496 31273822294 44214489606
## 3 36686079068 41337215814 45222309329 52051401869 63844971172 88981577008
## 4 13582798556 15373005557 17858486067 22059612477 29515467707 35189299912
## 5 190205714 242732571 252842286 246804571 304339840 345263492
## 6 23710735895 26706196047 29821661870 37209418019 47743801490 56033077879
## X1975 X1976 X1977 X1978 X1979 X1980
## 1 83435565923 83210426602 94988948105 106000000000 124000000000 157000000000
## 2 51444737234 62129396933 65315014927 71199715512 88628410997 112000000000
## 3 97333060221 105000000000 110000000000 119000000000 135000000000 150000000000
## 4 40059206763 42959976222 51545758888 62052259073 73937296963 82058912997
## 5 420986667 448412754 547535556 610225556 782496667 919726667
## 6 65678189097 71113882968 82839905459 101000000000 116000000000 127000000000
## X1981 X1982 X1983 X1984 X1985 X1986
## 1 160000000000 155000000000 160000000000 146000000000 130000000000 147000000000
## 2 211000000000 187000000000 138000000000 114000000000 117000000000 107000000000
## 3 177000000000 194000000000 177000000000 194000000000 181000000000 182000000000
## 4 71034228443 71275287570 72121016547 67985344887 69386774408 99036164939
## 5 969046667 1013222222 1082926304 987143931 1149979286 1201725497
## 6 105000000000 92095926188 87184239053 83349530159 86268264148 120000000000
## X1987 X1988 X1989 X1990 X1991 X1992
## 1 180000000000 189000000000 195000000000 212000000000 221000000000 220000000000
## 2 110000000000 109000000000 102000000000 122000000000 117000000000 118000000000
## 3 189000000000 236000000000 300000000000 311000000000 326000000000 325000000000
## 4 124000000000 133000000000 133000000000 166000000000 174000000000 195000000000
## 5 1131466494 1082403219 1113924130 1132101253 1167398478 1083037671
## 6 149000000000 162000000000 164000000000 205000000000 211000000000 235000000000
## X1993 X1994 X1995 X1996 X1997 X1998
## 1 234000000000 239000000000 270000000000 268000000000 282000000000 266000000000
## 2 98826405551 86281770253 108000000000 126000000000 127000000000 130000000000
## 3 312000000000 323000000000 368000000000 401000000000 435000000000 399000000000
## 4 190000000000 204000000000 241000000000 237000000000 213000000000 218000000000
## 5 938632612 925030590 1000428394 869033856 972896268 893770806
## 6 225000000000 245000000000 288000000000 279000000000 253000000000 259000000000
## X1999 X2000 X2001 X2002 X2003 X2004
## 1 262000000000 284000000000 259000000000 265000000000 353000000000 439000000000
## 2 138000000000 140000000000 148000000000 177000000000 205000000000 254000000000
## 3 389000000000 416000000000 379000000000 395000000000 467000000000 614000000000
## 4 217000000000 197000000000 197000000000 213000000000 262000000000 301000000000
## 5 808077223 870486066 876794723 825394490 784654424 915257323
## 6 258000000000 236000000000 237000000000 257000000000 317000000000 369000000000
## X2005 X2006 X2007 X2008 X2009 X2010
## 1 512000000000 576000000000 661000000000 7.080000e+11 713000000000 8.470000e+11
## 2 311000000000 393000000000 462000000000 5.660000e+11 507000000000 5.920000e+11
## 3 695000000000 748000000000 854000000000 1.060000e+12 928000000000 1.150000e+12
## 4 316000000000 336000000000 389000000000 4.300000e+11 400000000000 3.920000e+11
## 5 1117113046 1273375020 1356199365 1.611836e+09 1781455092 2.032135e+09
## 6 386000000000 408000000000 470000000000 5.150000e+11 481000000000 4.810000e+11
## X2011 X2012 X2013 X2014 X2015 X2016
## 1 9.430000e+11 9.510000e+11 9.640000e+11 9.850000e+11 9.200000e+11 8.730000e+11
## 2 6.710000e+11 7.280000e+11 8.210000e+11 8.650000e+11 7.610000e+11 6.910000e+11
## 3 1.400000e+12 1.550000e+12 1.580000e+12 1.470000e+12 1.350000e+12 1.210000e+12
## 4 4.310000e+11 4.090000e+11 4.300000e+11 4.420000e+11 3.820000e+11 3.960000e+11
## 5 2.235821e+09 2.333308e+09 2.451625e+09 2.705783e+09 3.104395e+09 2.732809e+09
## 6 5.230000e+11 4.960000e+11 5.220000e+11 5.350000e+11 4.620000e+11 4.760000e+11
## X2017 X2018 X2019 X2020
## 1 9.85000e+11 1.010000e+12 1.010000e+12 9.210000e+11
## 2 6.84000e+11 7.420000e+11 7.950000e+11 7.850000e+11
## 3 1.33000e+12 1.430000e+12 1.390000e+12 1.330000e+12
## 4 4.16000e+11 4.550000e+11 4.450000e+11 4.330000e+11
## 5 2.74818e+09 2.668496e+09 2.631434e+09 2.841786e+09
## 6 5.02000e+11 5.430000e+11 5.350000e+11 5.220000e+11Data After Reshape
## Country.Name Country.Code year gdp
## 1 Africa Eastern and Southern AFE 1960 19313106302
## 2 Africa Western and Central AFW 1960 10404280784
## 3 Australia AUS 1960 18606786874
## 4 Austria AUT 1960 6592693841
## 5 Burundi BDI 1960 195999990
## 6 Belgium BEL 1960 11658722591Plot Top 5 Countries
Plot Top 5 countries in Proportion(gdp)
Conclusion
Most of value in reality is not negative, therefore, setting stream-graph type into “mirror”(default) is not desirable in this case, “ridge” will be preferred because its lower bound is 0 and upper bound is unlimited. In graph “gdp growth aross years in listed countries”, United State still shows the largest gdp growth; China does not have any records in the data showing growth of GDP, or its GDP is super low. However, the proportional graph is just for me to show how the proportional stream-graph looks like. It is misleading and confusing around 1960 in the plot, So I will not draw any conclusions on this plot.