jamesdamillington

import geopandas as gpd
import pandas as pd

england = pd.read_csv("https://raw.githubusercontent.com/jamesdamillington/spar/main/data/brexit/brexit_vote.csv",
                      index_col='Area_Code')

lads = gpd.read_file("https://raw.githubusercontent.com/jamesdamillington/spar/main/data/brexit/local_authority_districts.geojson").set_index('lad16cd')

Egdf = lads.merge(england, how='inner', 
                  left_index=True, right_index=True)

jamesdamillington

#import rquired packages
import pandas as pd
import geopandas as gpd
from shapely.geometry import Point

#read data and check column names (for coords)
df = pd.read_csv("data/StationLocationIGS.csv")
df.columns

#create geometry column from lat and long using shapely

jamesdamillington

#when saving GeoDataFrames as csv, high precision geometries can produce large files on disk
#reducing unnecessary precision can help reduce file size
#e.g. ONS digital vector boundary data converted from shp to gpd results in nano-metre precision!

import geopandas as gpd
from shapely.wkt import loads
from shapely.wkt import dumps

#set desired number of decimal places (e.g. see https://xkcd.com/2170/) 
precision = 0

jamesdamillington

#import relevant packages
import pandas as pd
import geopandas as gpd
from shapely.wkt import loads

#set variables for this particular data set
file_path = "data/mydata.csv"      #location of data
geom_col = 'geometry'              #name of column containing geometries
epsg_id = 27700                    #see https://epsg.io/
crs_str = "EPSG:" + str(epsg_id)   #concat

jamesdamillington

What can we do with a Gist?

Markdown

Here's a list

• of
• pointless
• stuff

Now go home