For the below data
> head(df)
Date Longitude Latitude Elevation Max.Temperature Min.Temperature Precipitation Wind Relative.Humidity Solar RO
1 2014-07-01 77.1875 7.96184 -9999 27.725 26.673 16.115560560 8.395378 0.8132272 23.08192 Yes
2 2014-07-02 77.1875 7.96184 -9999 27.931 26.897 0.700378560 8.062267 0.8074675 21.48473 Yes
3 2014-07-03 77.1875 7.96184 -9999 28.179 26.686 0.000000000 9.465022 0.8107901 24.14900 No
4 2014-07-04 77.1875 7.96184 -9999 27.657 26.545 0.003433226 9.397203 0.8195020 23.42036 Yes
5 2014-07-05 77.1875 7.96184 -9999 27.157 26.490 1.541518560 8.903047 0.8385059 23.90545 Yes
6 2014-07-06 77.1875 7.96184 -9999 27.308 26.481 0.000000000 8.617348 0.8205267 23.96318 No
I have created an map using ggmap
> Precip_map<-get_map(location="india",maptype="satellite",zoom=12)
Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=india&zoom=12&size=640x640&scale=2&maptype=satellite&language=en-EN&sensor=false
> ggmap(Precip_map, extent = "device") + geom_point(aes(x = Longitude, y = Latitude), colour = "red",
+ alpha = 0.1, size = 2, data = df)
Warning message:
In loop_apply(n, do.ply) :
Removed 1106 rows containing missing values (geom_point).
drawn contour map
> ggmap(Precip_map, extent = "device") + geom_density2d(data = df,
+ aes(x = Longitude, y = Latitude), size = 0.3) + stat_density2d(data = df,
+ aes(x = Longitude, y = Latitude, fill = ..level.., alpha = ..level..), size = 0.01,
+ bins = 16, geom = "polygon") + scale_fill_gradient(low = "green", high = "red",
+ guide = FALSE) + scale_alpha(range = c(0, 0.3), guide = FALSE)
Error in if (any(h <= 0)) stop("bandwidths must be strictly positive") :
missing value where TRUE/FALSE needed
Error in if (any(h <= 0)) stop("bandwidths must be strictly positive") :
missing value where TRUE/FALSE needed
In addition: Warning message:
In loop_apply(n, do.ply) :
Removed 1106 rows containing non-finite values (stat_density2d).
Warning message:
In loop_apply(n, do.ply) :
Removed 1106 rows containing non-finite values (stat_density2d).
I dont know exactly where i am lacking.. i am new to this mapping.. please assist me. Also, I want to plot df$Precipitation in this contour map.
The lat, long
values are same across the entire dataset. Hence, the variance in both the lat
and long
direction is zero, so a bandwidth for the kernel density estimate (KDE) can't be calculated.
Hence, you are getting the error bandwidths must be strictly positive
.
For calculating 2-D KDEs, the variance in both x and y direction need to positive. You are getting the error twice as in your case variance in both directions are 0.
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