I'm trying to plot a basis map for the Midwest region in R but the closest solution I've found is a stat_density2d
plot. Instead of plotting the frequencies I have a column of values called basis that are negative and positive and I'd like to reflect their distribution over a map as a heatmap. Is it possible? And are the non-ggmap solutions?
An example of what I want:
The data:
structure(list(crop_name = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
), .Label = c("beans", "corn", "hrw", "milo"), class = "factor"),
year = c(2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019), week = c(27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27), basis = c(-0.320000052452087, -0.289999842643738,
-0.399999976158142, -0.289999842643738, -0.349999785423279,
-0.249999865889549, -0.220000132918358, -0.309999823570251,
-0.309999823570251, 0.199999943375587, 0.150000229477882,
0.150000229477882, -0.399999976158142, -0.309999823570251,
-0.0500000566244125, -0.349999785423279, 0.0200001150369644,
0.0200001150369644, 0.0200001150369644, -0.349999785423279,
-0.0700000375509262, -0.349999785423279, -0.349999785423279,
-0.399999976158142, -0.399999976158142, -0.249999865889549,
-0.0999997705221176, -0.340000033378601, -0.249999865889549,
-0.249999865889549, -0.0999997705221176, -0.550000071525574,
-0.349999785423279, -0.109999999403954, -0.309999823570251,
-0.520000100135803, -0.449999928474426, -0.449999928474426,
-0.200000151991844, -0.360000014305115, -0.28000009059906,
-0.309999823570251, -0.0500000566244125, -0.0999997705221176,
-0.419999957084656, -0.419999957084656, -0.320000052452087,
-0.370000004768372, -0.309999823570251, -0.360000014305115,
-0.200000151991844, -0.109999999403954, -0.109999999403954,
-0.399999976158142, -0.0500000566244125, 1.33514404865309e-07,
-0.109999999403954, -0.320000052452087, -0.269999861717224,
0.0200001150369644, -0.320000052452087, -0.349999785423279,
-0.349999785423279, -0.349999785423279, -0.419999957084656,
-0.309999823570251, -0.370000004768372, -0.370000004768372,
-0.200000151991844, -0.0199998468160629, -0.0199998468160629,
-0.449999928474426, -0.149999961256981, -0.449999928474426,
0.0200001150369644, -0.249999865889549, -0.300000071525574,
-0.300000071525574, -0.249999865889549, -0.0799997895956039,
-0.0500000566244125, -0.349999785423279, -0.249999865889549,
0.199999943375587, -0.289999842643738, -0.0500000566244125,
-0.200000151991844, -0.200000151991844, -0.149999961256981,
-0.149999961256981, -0.249999865889549, -0.109999999403954,
-0.249999865889549, -0.0500000566244125, -0.0500000566244125,
0.0200001150369644, -0.449999928474426, 0.0099998852238059,
0.0499998480081558, -0.300000071525574, -0.389999985694885,
-0.300000071525574, -0.200000151991844, -0.140000209212303,
-0.449999928474426, -0.479999899864197, -0.479999899864197,
-0.0199998468160629, -0.0999997705221176, -0.0700000375509262,
1.33514404865309e-07, -0.0999997705221176, -0.0999997705221176,
-0.269999861717224, -0.269999861717224, -0.269999861717224,
0.199999943375587, -0.0500000566244125, -0.240000113844872,
-0.389999985694885, -0.309999823570251, 0.0499998480081558,
-0.399999976158142, -0.349999785423279, -0.449999928474426,
-0.449999928474426, -0.449999928474426, -0.449999928474426,
-0.28000009059906, -0.449999928474426, -0.349999785423279,
-0.249999865889549, -0.249999865889549, -0.149999961256981,
-0.449999928474426, -0.109999999403954, -0.349999785423279,
-0.309999823570251, -0.0500000566244125, -0.0799997895956039,
-0.249999865889549, -0.28000009059906, -0.249999865889549,
-0.399999976158142, -0.200000151991844, -0.200000151991844,
-0.109999999403954, -0.169999942183495, -0.490000128746033,
-0.0500000566244125), loc_id = structure(c(1L, 467L, 506L,
453L, 349L, 564L, 4L, 582L, 116L, 438L, 139L, 135L, 636L,
407L, 627L, 493L, 142L, 142L, 388L, 508L, 7L, 615L, 615L,
616L, 616L, 567L, 628L, 469L, 144L, 144L, 417L, 147L, 148L,
149L, 588L, 150L, 509L, 152L, 85L, 9L, 420L, 408L, 154L,
155L, 156L, 156L, 454L, 455L, 10L, 11L, 470L, 338L, 338L,
637L, 629L, 12L, 546L, 456L, 14L, 595L, 457L, 385L, 385L,
385L, 159L, 424L, 494L, 495L, 565L, 163L, 163L, 362L, 554L,
165L, 16L, 568L, 590L, 591L, 394L, 511L, 630L, 617L, 18L,
323L, 614L, 171L, 172L, 172L, 596L, 120L, 377L, 547L, 578L,
175L, 175L, 87L, 513L, 440L, 20L, 569L, 375L, 21L, 514L,
473L, 618L, 179L, 179L, 597L, 181L, 182L, 121L, 185L, 107L,
378L, 378L, 378L, 361L, 516L, 351L, 458L, 409L, 25L, 517L,
122L, 489L, 188L, 465L, 108L, 27L, 189L, 496L, 192L, 555L,
194L, 363L, 342L, 497L, 459L, 197L, 29L, 390L, 30L, 556L,
32L, 428L, 598L, 343L, 199L, 200L, 201L), .Label = c("1569",
"1570", "1571", "1573", "1579", "1581", "1582", "1583", "1593",
"1595", "1598", "1601", "1602", "1603", "1608", "1611", "1617",
"1618", "1619", "1626", "1627", "1630", "1633", "1638", "1639",
"1640", "1644", "1651", "1652", "1653", "1654", "1655", "1658",
"1660", "1661", "1664", "1665", "1667", "1676", "1677", "1678",
"1679", "1681", "1683", "1687", "1689", "1693", "1695", "1697",
"1698", "1699", "1702", "1703", "1710", "1713", "1714", "1718",
"1721", "1725", "1727", "1728", "1729", "1732", "1733", "1740",
"1741", "1746", "1747", "1748", "1749", "1753", "1763", "1764",
"1771", "1773", "1774", "1776", "1778", "1785", "1786", "1788",
"1927", "1933", "1962", "1963", "1968", "1971", "1980", "1985",
"1989", "1990", "1993", "1998", "1999", "2000", "2014", "2018",
"2031", "2035", "2922", "2924", "2925", "2926", "2927", "2928",
"2929", "2930", "2931", "2932", "2933", "2935", "2936", "2938",
"2939", "2941", "2980", "2981", "2983", "2984", "2985", "2986",
"2987", "2992", "2993", "2994", "2996", "2997", "2998", "2999",
"3109", "3282", "4231", "4232", "4233", "4234", "4235", "4236",
"4237", "4238", "4239", "4240", "4241", "4242", "4244", "4245",
"4246", "4247", "4248", "4249", "4250", "4251", "4252", "4253",
"4254", "4255", "4256", "4257", "4258", "4260", "4261", "4262",
"4263", "4264", "4266", "4267", "4268", "4269", "4270", "4271",
"4272", "4273", "4274", "4275", "4277", "4278", "4279", "4280",
"4281", "4282", "4283", "4284", "4285", "4286", "4287", "4288",
"4289", "4290", "4291", "4294", "4295", "4296", "4297", "4298",
"4299", "4300", "4301", "4302", "4303", "4304", "4305", "4306",
"4307", "4308", "4309", "4310", "4311", "4312", "4313", "4314",
"4315", "4316", "4317", "4318", "4319", "4320", "4321", "4322",
"4323", "4324", "4325", "4326", "4327", "4328", "4329", "4330",
"4331", "4333", "4335", "4336", "4337", "4338", "4339", "4341",
"4342", "4343", "4344", "4345", "4346", "4347", "4348", "4349",
"4351", "4352", "4353", "4354", "4355&