09 csv to points

Converting CSV to points

Uncomment the following line to install leafmap if needed.

In [1]:

# !pip install leafmap

# !pip install leafmap

This notebook example requires the ipyleaflet plotting backend. Folium is not supported.

In [2]:

import os
import leafmap.leafmap as leafmap

import os import leafmap.leafmap as leafmap

Read a CSV as a Pandas DataFrame.

In [3]:

in_csv = 'https://raw.githubusercontent.com/giswqs/data/main/world/world_cities.csv'

in_csv = 'https://raw.githubusercontent.com/giswqs/data/main/world/world_cities.csv'

In [4]:

df = leafmap.csv_to_pandas(in_csv)
df

df = leafmap.csv_to_pandas(in_csv) df

Out[4]:

	id	name	country	latitude	longitude	population
0	1	Bombo	UGA	0.58330	32.53330	75000
1	2	Fort Portal	UGA	0.67100	30.27500	42670
2	3	Potenza	ITA	40.64200	15.79900	69060
3	4	Campobasso	ITA	41.56300	14.65600	50762
4	5	Aosta	ITA	45.73700	7.31500	34062
...	...	...	...	...	...	...
1244	1245	Rio de Janeiro	BRA	-22.92502	-43.22502	11748000
1245	1246	Sao Paulo	BRA	-23.55868	-46.62502	18845000
1246	1247	Sydney	AUS	-33.92001	151.18518	4630000
1247	1248	Singapore	SGP	1.29303	103.85582	5183700
1248	1249	Hong Kong	CHN	22.30498	114.18501	7206000

1249 rows × 6 columns

Create a point layer from a CSV file containing lat/long information.

In [5]:

Map = leafmap.Map()
Map.add_xy_data(in_csv, x="longitude", y="latitude", layer_name="World Cities")
Map

Map = leafmap.Map() Map.add_xy_data(in_csv, x="longitude", y="latitude", layer_name="World Cities") Map

Set the output directory.

In [6]:

out_dir = os.path.expanduser('~/Downloads')
if not os.path.exists(out_dir):
    os.makedirs(out_dir)
out_shp = os.path.join(out_dir, 'world_cities.shp')

out_dir = os.path.expanduser('~/Downloads') if not os.path.exists(out_dir): os.makedirs(out_dir) out_shp = os.path.join(out_dir, 'world_cities.shp')

Convert a CSV file containing lat/long information to a shapefile.

In [7]:

leafmap.csv_to_shp(in_csv, out_shp)

leafmap.csv_to_shp(in_csv, out_shp)

Downloading https://raw.githubusercontent.com/giswqs/data/main/world/world_cities.csv ...
Data downloaded to: /home/runner/Downloads/world_cities.csv

In [8]:

out_geojson = os.path.join(out_dir, 'world_cities.geojson')
leafmap.csv_to_geojson(in_csv, out_geojson)

out_geojson = os.path.join(out_dir, 'world_cities.geojson') leafmap.csv_to_geojson(in_csv, out_geojson)

Convert a CSV file containing lat/long information to a GeoPandas GeoDataFrame.

In [9]:

# gdf = leafmap.csv_to_gdf(in_csv)
# gdf

# gdf = leafmap.csv_to_gdf(in_csv) # gdf

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Last update: 2022-03-14