I have a rather large geojson file which is converted from some National Weather Service data. I've trimmed it down to this sample here:
{
"properties": {
"name": "day1otlk"
},
"type": "FeatureCollection",
"features": [
{
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-122.71424459627099,
40.229695635383166
],
[
-122.62484780364827,
40.53410620541074
],
[
-122.71424459627099,
40.229695635383166
]
]
]
},
"properties": {
"Name": "General Thunder",
"stroke-opacity": 1,
"stroke-width": 4,
"name": "General Thunder",
"fill": "#c0e8c0",
"fill-opacity": 0.75,
"stroke": "#ffffff",
"timeSpan": {
"end": "2017-03-30T12:00:00Z",
"begin": "2017-03-29T20:00:00Z"
}
},
"type": "Feature"
},
{
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-108.65861565996833,
32.91391108773154
],
[
-108.63932601964923,
32.95521185698698
],
[
-108.65861565996833,
32.91391108773154
]
]
]
},
"properties": {
"Name": "General Thunder",
"stroke-opacity": 1,
"stroke-width": 4,
"name": "General Thunder",
"fill": "#c0e8c0",
"fill-opacity": 0.75,
"stroke": "#ffffff",
"timeSpan": {
"end": "2017-03-30T12:00:00Z",
"begin": "2017-03-29T20:00:00Z"
}
},
"type": "Feature"
},
{
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-92.67280213157608,
38.47870651780003
],
[
-92.62448390998837,
38.45534960370862
],
[
-92.59475154780039,
38.493327413824595
],
[
-92.64308574626148,
38.51669676139087
],
[
-92.67280213157608,
38.47870651780003
]
]
]
},
"properties": {
"Name": "10 %",
"stroke-opacity": 1,
"stroke-width": 4,
"name": "10 %",
"fill": "#8b4726",
"fill-opacity": 0.89,
"stroke": "#ffffff",
"timeSpan": {
"end": "2017-03-30T12:00:00Z",
"begin": "2017-03-29T20:00:00Z"
}
},
"type": "Feature"
},
{
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-92.67280213157608,
38.47870651780003
],
[
-92.62448390998837,
38.45534960370862
],
[
-92.59475154780039,
38.493327413824595
],
[
-92.64308574626148,
38.51669676139087
],
[
-92.67280213157608,
38.47870651780003
]
]
]
},
"properties": {
"Name": "10 %",
"stroke-opacity": 1,
"stroke-width": 4,
"name": "20 %",
"fill": "#8b4726",
"fill-opacity": 0.89,
"stroke": "#ffffff",
"timeSpan": {
"end": "2017-03-30T12:00:00Z",
"begin": "2017-03-29T20:00:00Z"
}
},
"type": "Feature"
},
{
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-97.09845994557838,
38.43843745045377
],
[
-97.07114801649661,
38.47751978088534
],
[
-97.09845994557838,
38.43843745045377
]
]
]
},
"properties": {
"Name": "5 %",
"stroke-opacity": 1,
"stroke-width": 4,
"name": "5 %",
"fill": "#b47f00",
"fill-opacity": 0.89,
"stroke": "#ffffff",
"timeSpan": {
"end": "2017-03-30T12:00:00Z",
"begin": "2017-03-29T20:00:00Z"
}
},
"type": "Feature"
}
]
}
I'm looking to remove the elements where name has a % in it. I don't want those coordinates or anything included.
Here's my code:
import json
with open('test.geojson') as data_file:
data = json.load(data_file)
for element in data["features"]:
if '%' in element["properties"]["name"]:
del element["type"]
del element["properties"] # Deletes the properties
del element["geometry"] # Deletes the coords
with open('test_output.geojson', 'w') as data_file:
data = json.dump(data, data_file)
This works well enough to remove the element's sub keys, but I'm left with output that looks like:
{}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}
I've also tried to use
for element in data["features"]:
if '%' in element["properties"]["name"]:
data["features"].remove(element)
but that seems to delete only the last element in the sample group, which is the 5 % group. It should be removing the 10 %, 20 % and the 5 % groups.
Is there a way to remove the element from data["features"] if name has a % in it all together so I'm left with clean json output? In this sample data, the only data["features"] I should have left are the General Thunder and no empty brackets.
The issue with using del element["type"], del element["properties"] and del element["geometry"] is that it only removes those items from properties dict of that element. Not the element itself.
For your 2nd item, when you're iterating over a list like in for element in data["features"]:, it's not good to modify a list or object while iterating over it (which is what's happening with data["features"].remove(element)). Also, list.remove() removes an item with that value. So element gets used in a value context, not as that element.
It's better to create a new list and then assign that. What you could do is:
new_features = []
for element in data["features"]:
if '%' not in element["properties"]["name"]: # note the 'not'
new_features.append(element) # new_features has the one's you want
# and then re-assign features to the list with the elements you want
data["features"] = new_features