I have csv data containing latitude and longitude. I wish to create a 'heatmap' whereby some placemarks are certain colours based on values corresponding to each lat+long point in the csv.
import simplekml
import csv
kml = simplekml.Kml()
kml.document.name = "Test"
with open('final.csv', 'rb') as f:
reader = csv.reader(f)
first_row = reader.next() # removes csv header string
long = col[1]
lat = col[2]
for col in reader:
pnt = kml.newpoint()
pnt.name = 'test-name'
pnt.coords = [(long, lat, 10000)]
pnt.description = col[0] # timestamp data
pnt.style.labelstyle.color = 'ff0000ff'
kml.save("test.kml")
This script creates a kml file that on inspection with google earth presents the data points but I want some kind of graphical input too.
It doesn't seem like simplekml package supports such things.. Any advice on what python package is best to get a 'heatmap' or something along those lines? Or even I can add kml elements directly in the script but the documentation it seems is rather limited for the solutions I require.
Thanks
Sounds like you're looking to create a "thematic map", not a "heatmap".
Looks like you're using pnt.style.labelstyle.color = ... to add colors. LabelStyle refers to the text labels associated with icons, not the icons themselves. What you probably want is to refer to differently colored icons based on your attribute values. You should be able to do that with: pnt.style.iconstyle.icon.href = .... Either specify a colored icon image, or use a white image and apply a color with style.iconstyle.color = ....
Best practice for KML would be to set up several shared styles, one for each icon color, and then apply the relevant style to each point with pnt.style = ....
Implementation details are in the simplekml documentation.
Related
I have a VTK file that correctly populates the data in ParaView:
However, when I open that same file with VTK's Python API, I cannot for the life of me seem to find these same labeled datasets. Here's what I've tried:
import vtk
from vtk.numpy_interface import dataset_adapter as dsa
reader = vtk.vtkUnstructuredGridReader()
reader.SetFileName('test.vtk')
reader.Update()
adapter = dsa.WrapDataObject(reader.GetOutput())
print(adapter.PointData.keys()) # ['hu', 'disp']
print(adapter.CellData.keys()) # []
print(adapter.FieldData.keys()) # []
So, it seems that ParaView is able to identify the other datasets beyond just 'hu' and 'disp', but I cannot seem to find them in the corresponding Python object.
I'm assuming it's there somewhere. Anyone know why they, e.g., 'meanstress', don't appear as keys?
You need to ask the reader to read all the data.
reader.ReadAllScalarsOn()
reader.ReadAllVectorsOn()
...
Dependending of wich kind of data you are trying to load.
(scalars, vector, tensor ... See for the whole list: https://vtk.org/doc/nightly/html/classvtkDataReader.html#a831f470c6fbfc6e7209a1243ccb546e2 )
I'm using the altair python library to create html files with vega-lite specifications. I'm encountering a problem where color is not being displayed in my plot. Here is the code:
import altair as alt
import pandas
data = 'Test.csv' #this contains three columns: Rating, Frequency, and typ, where 'typ' is either E or O.
a = alt.Chart(data).mark_bar().encode(
alt.X('Rating', type = 'ordinal'),
alt.Y('Frequency',type = 'quantitative'),
alt.Color('typ', type = 'nominal')
)
a.save('altairtest.html')
I get a graph without colors, and the legend comes up as 'typ' but only with blue, and text reading "undefined.
I am currently working locally on a SimpleHttpsServer. Could this be the reason why? For my purposes it is easier this way than using jupyter. Thanks
This usually indicates that there is an issue in your data file. I can reproduce your issue with a Data.csv file that looks like this:
Rating,Frequency, typ
0,1,O
1,2,E
Then the resulting chart looks like this:
Notice the space before typ in the header: spaces are important in CSV files: this means your column is named " typ" not "typ".
If you remove the space from the header in the CSV file, the same code gives you this:
Rating,Frequency,typ
0,1,O
1,2,E
Make certain your fields exactly match your data columns, and your chart should work as expected.
I'm trying to do some work on a complex Excel Workbook which has a large number of variables which have been created and used using the Name Box feature. See picture attached for example/detail.
I'd like to store or change DeathRate or maybe read all the Name Boxes and create a dictionary between names and locations of the cell from outside Excel.
I'm using the win32com library in Python but I guess I could switch to another Excel reader as long as it copes with XLSX files.
Has someone come across this before?
Found the solution, see code below:
import os
from win32com.client import Dispatch #win32com is based around cells beginning at one.
app_xl = Dispatch("Excel.Application")
WORKING_DIR = os.getcwd()
excelPath = WORKING_DIR + "\SampleModel.xls"
wb = app_xl.Workbooks.Open(excelPath)
# Get Named Boxes
name_box_list = [x for x in app_xl.ActiveWorkbook.Names]
name_box_map = {x.Name:x.Value for x in name_box_list}
print name_box_list
print name_box_map
# Change Named Boxes
name_box_list[0].Name = u'NewName'
name_box_list[0].Value = u'=model!$B$5'
name_box_map = {x.Name:x.Value for x in name_box_list}
This should be very simple:
I have an Excel table with pollution detection sites, and their corresponding Latitudes and Longitudes. I want to create a point shapefile for this table.
I have written a script to create the file, but cannot figure out how to create the points in it:
#Creates Observation Site Shapefile
import arcpy
import fileinput
import string
import os
from arcpy import env
env.workspace = "F:\GEOG 487B\Project"
env.overwriteOutput = True
outpath = env.workspace
newfc = "sites.shp"
infile = "site_loc.xls"
arcpy.CreateFeatureclass_management(outpath, newfc, "Point")
The shapefile is created, but the attribute table is empty. How can I get ArcMap to recognize my Latutude and Longitude columns?
The table is very simple:
Column A = Site ID#, B = Latitude, C = Longitude
Thanks!!
I know there is a library which can read/write shape files. I've used it to read in National Weather Service Shapefiles in the past.
http://code.google.com/p/pyshp/
From the examples on that webpage, writing points into a shape file looks fairly easy.
My answer is probably late, but you can use Make XY Event Layer and then save the output layer to a shapefile or feature class with e.g. Copy Features.
You can also do this without Python by right-clicking your xls sheet in ArcCatalog > Create feature class from XY table.
import shapefile
r = shapefile.Reader("C:\Users\Me\Desktop\py\mis.dbf")
That is as far as I get, must be something simple I don't know about. I have already spent a embarrassing amount of time on this little thing. Could one of you more knowlegeable ones tell me what I missed?
It looks like you're good to go unless you're getting an error that you didn't mention.
First of all you're looking at the dbf file which contains the shapefile attributes (similar to a spreadsheet). But that doesn't matter because the Reader ignores extensions and will try to find the .shp and .shx files as well containing the geometry and geometry record index as well.
If you're just interested in the attributes try the following after you above example:
# Print the dbf field names
print [f[0] for f in r.fields]
# Print the first record:
print r.record(0)
# Loop through all the records using an interator:
for rec in r.iterRecords(): print rec