ggplot2 - Disease Maps by using R -


My data set here is attached to .csv file in some body RG to help me create disease maps using GG Plot 2 Could. << >> Observed latitude longitude Jarawala Town 183 34.584 31.33429 73.419487 Sumanandi Town 59 5.6 9 27 31.06 9 531 72.9361303 Tandiala Town 28 2.8326 31.0316667 73.1316667 Jhumra Town 23 1.0923 31.5666667 73.1833333 Madinah Town 127 21.95 31.4178652 73.120208 Iqbal Town 40 6.9147 31.4932177 73.1051778 Jinnah Town 43 16.89 31.4144303 73.0768364 Lyallpur Town 97 38.121 31.4401011 73.0680131

As long as I generally agree that "there is no free code writing service", this problem is very simple, and it shows how much I have also known intensity of complex visibility in an R in R. It is very difficult to start in R. That's why I have suggested that you use this as a starting point , study code, read the documentation on various functions, and make it automatically Expand.

  Library (Rg) # readOGR For (...) Library (ArcolterBuver) for # brewer.pal (...) Library (ggplot2) setwd ("& lt; Your file with directory"; pak & lt; - readOGR (dsn = "Map" of map of Pakistan & lt; - pak [pak $ NAME_3 == "Faisalabad",] # Remove Faisalabad area centroids & lt; - data.frame (coordinates (map)) Label (centroids) & lt; -c ("long", "latitude") centroids $ name & lt; - map @ data $ NAME_3 # label (s) pallet #Low-Orange-Red Color Palette GG Plot (Map) + GOM_path (AES (X = Long, Y = LAT, Group = Group)) + GOM_text (Data = Sentiments, AES (X = Long, Y = LET, label = name)) + GOM_point (data = data, AES (x = longitude, y = latitude, size = observation, color = observation)) + scale_color_gradient (low = window) [5], high = palette [9]) + scale_size (guide = "none") + theme_bw () + coord_fixed ()   

explanation < P> All your data are from the Faisalabad area in Pakistan, as far as I can tell. First we need a map of Pakistan. It is available from many sources, but I like the outstanding website, where you can download Pakistan size e, of course, is in a zip archive, so you have to open the files in a directory ("all your files Along with the directory "as noted in the code). There is a workflow from:

  1. Read the file size: pak & lt; - readOGR (...) 2. Remove the appropriate area: map & lt; - pak [...] Remove the area name and centroid (for the label) 4. Generate color palette: palette and lieutenant; - Brewer Poll (...) 5. Presenting the map, placing points.  Edit  It has been brought to my attention that GADM has a direct interface in R, which avoids downloading and removing shapes manually . This package is  raster .  
  # setwd ("Directory with all your files"; ##) pak & lt; - readOGR (dsn = "# map of Pakistan, admin level 3.       

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