Agricultural census data for the Island of Ireland

import os
import matplotlib.pyplot as plt
import pandas as pd
import geopandas as gpd

ROI data

bound_ie = gpd.read_file(
    os.path.join("data", "boundaries", "boundaries_all.gpkg"),
    layer="OSi_IE_electoral_divisions_2019",
)

bound_ie.head()

	ED_ID	ENGLISH	GAEILGE	CONTAE	COUNTY	PROVINCE	GUID	CENTROID_X	CENTROID_Y	AREA	ESRI_OID	Shape__Are	Shape__Len	geometry
0	267160	TURNAPIN	Turnapain	Baile Átha Cliath	DUBLIN	Leinster	2ae19629-1cea-13a3-e055-000000000001	717365.57	740807.88	943505.13	1	9.435051e+05	4732.251966	POLYGON ((717716.712 741601.510, 717759.461 74...
1	27045	DRUMLUMMAN	Droim Lomáin	An Cabhán	CAVAN	Ulster	2ae19629-1caa-13a3-e055-000000000001	638130.82	789588.69	17617760.82	2	1.761776e+07	21762.101454	POLYGON ((637756.185 787640.988, 637753.646 78...
2	117019	CASTLEFORE	Baile Choille Fóir	Liatroim	LEITRIM	Connacht	2ae19629-171c-13a3-e055-000000000001	606853.02	809670.32	14080012.63	3	1.408001e+07	21907.071044	POLYGON ((608196.069 807618.950, 608244.536 80...
3	37135	RAHONA	Ráth Úna	An Clár	CLARE	Munster	2ae19629-1fec-13a3-e055-000000000001	481634.87	649839.86	24664562.56	4	2.466456e+07	35830.867808	POLYGON ((484212.068 651795.629, 484231.866 65...
4	167021	CROSSAKEEL	Crosa Caoil	An Mhí	MEATH	Leinster	2ae19629-1861-13a3-e055-000000000001	662161.01	774125.96	20159197.51	5	2.015920e+07	34415.329703	POLYGON ((663308.409 776111.796, 663305.294 77...

bound_ie.shape

(3455, 14)

coa_ie = pd.read_csv(
    os.path.join("data", "agricultural_census", "CSO", "COA_2020.csv")
)

coa_ie.head()

	C03904V04656	electoral_division	total_cattle	total_sheep	total_grass_hectares
0	3576C59993454152E0530100007F0280	Brisha / Capard, Co.Laois, 08045/08046	1955	420	964.3
1	3576C59992AD4152E0530100007F0280	Firry / Newgrove, Co.Longford, 09024/09035	2164	675	965.4
2	2AE1962918C813A3E055000000000001	Fair Gate, Co.Louth, 10001	0	0	0.0
3	2AE19629193513A3E055000000000001	St. Laurence Gate, Co.Louth, 10002	0	0	0.0
4	2AE19629191E13A3E055000000000001	West Gate, Co.Louth, 10003	0	0	0.0

coa_ie.shape

(3409, 5)

bound_ie["C03904V04656"] = (
    bound_ie["GUID"].replace("-", "", regex=True).str.upper()
)

bound_ie.head()

	ED_ID	ENGLISH	GAEILGE	CONTAE	COUNTY	PROVINCE	GUID	CENTROID_X	CENTROID_Y	AREA	ESRI_OID	Shape__Are	Shape__Len	geometry	C03904V04656
0	267160	TURNAPIN	Turnapain	Baile Átha Cliath	DUBLIN	Leinster	2ae19629-1cea-13a3-e055-000000000001	717365.57	740807.88	943505.13	1	9.435051e+05	4732.251966	POLYGON ((717716.712 741601.510, 717759.461 74...	2AE196291CEA13A3E055000000000001
1	27045	DRUMLUMMAN	Droim Lomáin	An Cabhán	CAVAN	Ulster	2ae19629-1caa-13a3-e055-000000000001	638130.82	789588.69	17617760.82	2	1.761776e+07	21762.101454	POLYGON ((637756.185 787640.988, 637753.646 78...	2AE196291CAA13A3E055000000000001
2	117019	CASTLEFORE	Baile Choille Fóir	Liatroim	LEITRIM	Connacht	2ae19629-171c-13a3-e055-000000000001	606853.02	809670.32	14080012.63	3	1.408001e+07	21907.071044	POLYGON ((608196.069 807618.950, 608244.536 80...	2AE19629171C13A3E055000000000001
3	37135	RAHONA	Ráth Úna	An Clár	CLARE	Munster	2ae19629-1fec-13a3-e055-000000000001	481634.87	649839.86	24664562.56	4	2.466456e+07	35830.867808	POLYGON ((484212.068 651795.629, 484231.866 65...	2AE196291FEC13A3E055000000000001
4	167021	CROSSAKEEL	Crosa Caoil	An Mhí	MEATH	Leinster	2ae19629-1861-13a3-e055-000000000001	662161.01	774125.96	20159197.51	5	2.015920e+07	34415.329703	POLYGON ((663308.409 776111.796, 663305.294 77...	2AE19629186113A3E055000000000001

# merge boundaries and census data
data_ie = pd.merge(bound_ie, coa_ie, on="C03904V04656", how="outer")

data_ie.shape

(3487, 19)

# find data rows without a geometry
data_na = data_ie[data_ie["geometry"].isnull()][
    [
        "C03904V04656",
        "electoral_division",
        "total_cattle",
        "total_sheep",
        "total_grass_hectares",
    ]
]

data_na

	C03904V04656	electoral_division	total_cattle	total_sheep	total_grass_hectares
3455	3576C59993454152E0530100007F0280	Brisha / Capard, Co.Laois, 08045/08046	1955.0	420.0	964.3
3456	3576C59992AD4152E0530100007F0280	Firry / Newgrove, Co.Longford, 09024/09035	2164.0	675.0	965.4
3457	3576C59993334152E0530100007F0280	Esker / Ballaghassaan, Co.Offaly, 12043/12034	3830.0	923.0	1792.4
3458	3576C599940F4152E0530100007F0280	Ballinalack / Lackan, Co.Westmeath, 13054/13085	2685.0	2311.0	1748.1
3459	3576C59994FC4152E0530100007F0280	Noughaval / Castletown, Co.Clare, 16014/16008	4311.0	940.0	4445.3
3460	3576C59994AA4152E0530100007F0280	Glenroe / Ballyeighter, Co.Clare, 16020/16017	2379.0	808.0	2450.5
3461	3576C59996354152E0530100007F0280	Corlea / Cahermurphy, Co.Clare, 16128/16123	689.0	0.0	1051.5
3462	3576C59995BD4152E0530100007F0280	Inishcaltra North / Inishcaltra South, Co.Clar...	2114.0	0.0	1094.7
3463	3576C599953E4152E0530100007F0280	Bantry Rural / Whiddy, Co.Cork, 18033/18046	3387.0	2596.0	2411.1
3464	3576C59996CB4152E0530100007F0280	Ceannúigh / Máistir Gaoithe, Co.Kerry, 19009/1...	1579.0	7615.0	4068.3
3465	3576C599971F4152E0530100007F0280	Doire Ianna / Cloon, Co.Kerry, 19014/19011	1045.0	21522.0	7209.8
3466	3576C59998334152E0530100007F0280	Greenhall / Lackagh, Co.Tipperary, 22037/22045	2385.0	1159.0	1750.6
3467	3576C59999824152E0530100007F0280	Kilsheelan / Killaloan, Co.Tipperary, 23137/23136	3739.0	359.0	1728.7
3468	3576C59997034152E0530100007F0280	Ballybeg South / Ballynaneashagh, Co.Waterford...	0.0	0.0	0.0
3469	3576C59999FD4152E0530100007F0280	Derrycunlagh / Derrylea, Co.Galway, 27027/27028	518.0	5186.0	3120.8
3470	3576C5999B294152E0530100007F0280	Marblehill / Loughatorick, Co.Galway, 27129/27126	1597.0	393.0	1719.3
3471	3576C5999B084152E0530100007F0280	Greaghglass / Stralongford, Co.Leitrim, 28007/...	880.0	3391.0	1690.7
3472	3576C5999AA84152E0530100007F0280	Drumreilly West / Drumreilly East, Co.Leitrim,...	766.0	5527.0	1905.9
3473	3576C5999AEA4152E0530100007F0280	Aghalateeve / Aghanlish, Co.Leitrim, 28027/28028	274.0	10020.0	1944.0
3474	3576C5999AEB4152E0530100007F0280	Aghavoghill / Melvin, Co.Leitrim, 28029/28032	480.0	7953.0	1761.0
3475	3576C5999B174152E0530100007F0280	Garvagh / Arigna, Co.Leitrim, 28041/28034	408.0	1882.0	950.9
3476	3576C5999AEE4152E0530100007F0280	Glenco / Sheskin, Co.Mayo, 29058/29065	646.0	8044.0	3702.6
3477	3576C5999BB44152E0530100007F0280	Owennadornaun / Bundorragha, Co.Mayo, 29150/29130	181.0	10308.0	1234.6
3478	3576C5999B404152E0530100007F0280	Lisgarve / Mantua, Co.Roscommon, 30046/30048	2714.0	1296.0	1859.9
3479	3576C5999B934152E0530100007F0280	Lough Allen / Altagowlan, Co.Roscommon, 30047/...	424.0	1537.0	892.9
3480	3576C5999C054152E0530100007F0280	Templeboy South / Mullagheruse, Co.Sligo, 3103...	1211.0	8563.0	3810.5
3481	3576C5999C464152E0530100007F0280	Branchfield / Carrownaskeagh, Co.Sligo, 31067/...	806.0	4551.0	1568.1
3482	3576C5999C144152E0530100007F0280	Loughill / Cloonacool, Co.Sligo, 31078/31071	737.0	10066.0	3307.2
3483	3576C5999C884152E0530100007F0280	Pedara Vohers / Tircahan, Co.Cavan, 32025/32028	940.0	2752.0	1531.2
3484	3576C59999EE4152E0530100007F0280	Templeport / Benbrack, Co.Cavan, 32027/32018	1146.0	3741.0	1843.6
3485	3576C5999CF04152E0530100007F0280	Dunmakeever / Derrynananta, Co.Cavan, 32084/32082	833.0	11142.0	2750.4
3486	3576C5999C9C4152E0530100007F0280	Killinagh / Teebane, Co.Cavan, 32086/32087	422.0	3844.0	1424.1

data_na.shape

(32, 5)

# manual merging
data_na_left = data_na.copy()
data_na_right = data_na.copy()

data_na_left["ENGLISH"] = data_na_left["electoral_division"].str.split(
    expand=True, pat=" / "
)[0]

data_na_left["COUNTY"] = (
    data_na_left["electoral_division"]
    .str.split(expand=True, pat=" / ")[1]
    .str.split(expand=True, pat=",")[1]
    .str.split(expand=True, pat=" Co.")
)[1]

data_na_left.head()

	C03904V04656	electoral_division	total_cattle	total_sheep	total_grass_hectares	ENGLISH	COUNTY
3455	3576C59993454152E0530100007F0280	Brisha / Capard, Co.Laois, 08045/08046	1955.0	420.0	964.3	Brisha	Laois
3456	3576C59992AD4152E0530100007F0280	Firry / Newgrove, Co.Longford, 09024/09035	2164.0	675.0	965.4	Firry	Longford
3457	3576C59993334152E0530100007F0280	Esker / Ballaghassaan, Co.Offaly, 12043/12034	3830.0	923.0	1792.4	Esker	Offaly
3458	3576C599940F4152E0530100007F0280	Ballinalack / Lackan, Co.Westmeath, 13054/13085	2685.0	2311.0	1748.1	Ballinalack	Westmeath
3459	3576C59994FC4152E0530100007F0280	Noughaval / Castletown, Co.Clare, 16014/16008	4311.0	940.0	4445.3	Noughaval	Clare

data_na_right["ENGLISH"] = (
    data_na_right["electoral_division"]
    .str.split(expand=True, pat="/")[1]
    .str.split(expand=True, pat=", ")[0]
)

data_na_right["COUNTY"] = (
    data_na_right["electoral_division"]
    .str.split(expand=True, pat=" / ")[1]
    .str.split(expand=True, pat=",")[1]
    .str.split(expand=True, pat=" Co.")
)[1]

data_na_right.head()

	C03904V04656	electoral_division	total_cattle	total_sheep	total_grass_hectares	ENGLISH	COUNTY
3455	3576C59993454152E0530100007F0280	Brisha / Capard, Co.Laois, 08045/08046	1955.0	420.0	964.3	Capard	Laois
3456	3576C59992AD4152E0530100007F0280	Firry / Newgrove, Co.Longford, 09024/09035	2164.0	675.0	965.4	Newgrove	Longford
3457	3576C59993334152E0530100007F0280	Esker / Ballaghassaan, Co.Offaly, 12043/12034	3830.0	923.0	1792.4	Ballaghassaan	Offaly
3458	3576C599940F4152E0530100007F0280	Ballinalack / Lackan, Co.Westmeath, 13054/13085	2685.0	2311.0	1748.1	Lackan	Westmeath
3459	3576C59994FC4152E0530100007F0280	Noughaval / Castletown, Co.Clare, 16014/16008	4311.0	940.0	4445.3	Castletown	Clare

data_na = pd.concat([data_na_left, data_na_right])

data_na.shape

(64, 7)

# strip whitespace
data_na["ENGLISH"] = data_na["ENGLISH"].str.upper().str.strip()
data_na["COUNTY"] = data_na["COUNTY"].str.upper().str.strip()

data_na.head()

	C03904V04656	electoral_division	total_cattle	total_sheep	total_grass_hectares	ENGLISH	COUNTY
3455	3576C59993454152E0530100007F0280	Brisha / Capard, Co.Laois, 08045/08046	1955.0	420.0	964.3	BRISHA	LAOIS
3456	3576C59992AD4152E0530100007F0280	Firry / Newgrove, Co.Longford, 09024/09035	2164.0	675.0	965.4	FIRRY	LONGFORD
3457	3576C59993334152E0530100007F0280	Esker / Ballaghassaan, Co.Offaly, 12043/12034	3830.0	923.0	1792.4	ESKER	OFFALY
3458	3576C599940F4152E0530100007F0280	Ballinalack / Lackan, Co.Westmeath, 13054/13085	2685.0	2311.0	1748.1	BALLINALACK	WESTMEATH
3459	3576C59994FC4152E0530100007F0280	Noughaval / Castletown, Co.Clare, 16014/16008	4311.0	940.0	4445.3	NOUGHAVAL	CLARE

# manually change names to English
names = {
    "CEANNÚIGH": "CANUIG",
    "DOIRE IANNA": "DERRIANA",
    "AGHAVOGHILL": "AGHAVOGHIL",
    "LOUGHILL": "LOUGHIL",
    "MÁISTIR GAOITHE": "MASTERGEEHY",
}
data_na.replace({"ENGLISH": names}, inplace=True)

# drop these entries from the original dataframe
coa_ie = coa_ie[~coa_ie["C03904V04656"].isin(list(data_na["C03904V04656"]))]

coa_ie.shape

(3377, 5)

# merge boundaries and census data again
data_ie = pd.merge(bound_ie, coa_ie, on="C03904V04656", how="outer")

data_ie.shape

(3455, 19)

data_ie = pd.merge(data_ie, data_na, how="outer", on=["ENGLISH", "COUNTY"])

data_ie.head()

	ED_ID	ENGLISH	GAEILGE	CONTAE	COUNTY	PROVINCE	GUID	CENTROID_X	CENTROID_Y	AREA	...	C03904V04656_x	electoral_division_x	total_cattle_x	total_sheep_x	total_grass_hectares_x	C03904V04656_y	electoral_division_y	total_cattle_y	total_sheep_y	total_grass_hectares_y
0	267160	TURNAPIN	Turnapain	Baile Átha Cliath	DUBLIN	Leinster	2ae19629-1cea-13a3-e055-000000000001	717365.57	740807.88	943505.13	...	2AE196291CEA13A3E055000000000001	Turnapin, Co.Dublin, 04042	0.0	0.0	0.0	NaN	NaN	NaN	NaN	NaN
1	27045	DRUMLUMMAN	Droim Lomáin	An Cabhán	CAVAN	Ulster	2ae19629-1caa-13a3-e055-000000000001	638130.82	789588.69	17617760.82	...	2AE196291CAA13A3E055000000000001	Drumlumman, Co.Cavan, 32089	2673.0	231.0	1249.1	NaN	NaN	NaN	NaN	NaN
2	117019	CASTLEFORE	Baile Choille Fóir	Liatroim	LEITRIM	Connacht	2ae19629-171c-13a3-e055-000000000001	606853.02	809670.32	14080012.63	...	2AE19629171C13A3E055000000000001	Castlefore, Co.Leitrim, 28063	630.0	0.0	805.9	NaN	NaN	NaN	NaN	NaN
3	37135	RAHONA	Ráth Úna	An Clár	CLARE	Munster	2ae19629-1fec-13a3-e055-000000000001	481634.87	649839.86	24664562.56	...	2AE196291FEC13A3E055000000000001	Rahona, Co.Clare, 16101	2369.0	0.0	1349.9	NaN	NaN	NaN	NaN	NaN
4	167021	CROSSAKEEL	Crosa Caoil	An Mhí	MEATH	Leinster	2ae19629-1861-13a3-e055-000000000001	662161.01	774125.96	20159197.51	...	2AE19629186113A3E055000000000001	Crossakeel, Co.Meath, 11061	4826.0	671.0	2014.1	NaN	NaN	NaN	NaN	NaN

5 rows × 24 columns

# finishing merges
data_ie.fillna(0, inplace=True)

data_ie["total_cattle"] = data_ie["total_cattle_x"] + data_ie["total_cattle_y"]
data_ie["total_sheep"] = data_ie["total_sheep_x"] + data_ie["total_sheep_y"]
data_ie["total_grass_hectares"] = (
    data_ie["total_grass_hectares_x"] + data_ie["total_grass_hectares_y"]
)

data_ie.replace({"electoral_division_x": {0.0: ""}}, inplace=True)
data_ie.replace({"electoral_division_y": {0.0: ""}}, inplace=True)

data_ie["electoral_division"] = data_ie["electoral_division_x"].astype(
    str
) + data_ie["electoral_division_y"].astype(str)

# drop unnecessary columns
data_ie.drop(
    columns=[
        "C03904V04656_x",
        "electoral_division_x",
        "total_cattle_x",
        "total_sheep_x",
        "total_grass_hectares_x",
        "C03904V04656_y",
        "electoral_division_y",
        "total_cattle_y",
        "total_sheep_y",
        "total_grass_hectares_y",
    ],
    inplace=True,
)

data_ie.head()

	ED_ID	ENGLISH	GAEILGE	CONTAE	COUNTY	PROVINCE	GUID	CENTROID_X	CENTROID_Y	AREA	ESRI_OID	Shape__Are	Shape__Len	geometry	total_cattle	total_sheep	total_grass_hectares	electoral_division
0	267160	TURNAPIN	Turnapain	Baile Átha Cliath	DUBLIN	Leinster	2ae19629-1cea-13a3-e055-000000000001	717365.57	740807.88	943505.13	1	9.435051e+05	4732.251966	POLYGON ((717716.712 741601.510, 717759.461 74...	0.0	0.0	0.0	Turnapin, Co.Dublin, 04042
1	27045	DRUMLUMMAN	Droim Lomáin	An Cabhán	CAVAN	Ulster	2ae19629-1caa-13a3-e055-000000000001	638130.82	789588.69	17617760.82	2	1.761776e+07	21762.101454	POLYGON ((637756.185 787640.988, 637753.646 78...	2673.0	231.0	1249.1	Drumlumman, Co.Cavan, 32089
2	117019	CASTLEFORE	Baile Choille Fóir	Liatroim	LEITRIM	Connacht	2ae19629-171c-13a3-e055-000000000001	606853.02	809670.32	14080012.63	3	1.408001e+07	21907.071044	POLYGON ((608196.069 807618.950, 608244.536 80...	630.0	0.0	805.9	Castlefore, Co.Leitrim, 28063
3	37135	RAHONA	Ráth Úna	An Clár	CLARE	Munster	2ae19629-1fec-13a3-e055-000000000001	481634.87	649839.86	24664562.56	4	2.466456e+07	35830.867808	POLYGON ((484212.068 651795.629, 484231.866 65...	2369.0	0.0	1349.9	Rahona, Co.Clare, 16101
4	167021	CROSSAKEEL	Crosa Caoil	An Mhí	MEATH	Leinster	2ae19629-1861-13a3-e055-000000000001	662161.01	774125.96	20159197.51	5	2.015920e+07	34415.329703	POLYGON ((663308.409 776111.796, 663305.294 77...	4826.0	671.0	2014.1	Crossakeel, Co.Meath, 11061

data_ie.shape

(3455, 18)

fig, axs = plt.subplots(1, 3, figsize=(15, 15))
cols = [
    ("total_cattle", "Total cattle"),
    ("total_sheep", "Total sheep"),
    ("total_grass_hectares", "Total grassland (hectares)"),
]
for i, ax in enumerate(axs.flat):
    data_ie.plot(
        column=cols[i][0],
        ax=ax,
        cmap="Spectral_r",
        scheme="equal_interval",
        edgecolor="darkslategrey",
        linewidth=0.2,
        legend=True,
        legend_kwds={
            "loc": "upper left",
            "fmt": "{:.0f}",
            "title": cols[i][1],
        },
    )
    # ax.ticklabel_format(style="scientific", scilimits=[-4, 4])
    ax.tick_params(labelbottom=False, labelleft=False)
    for legend_handle in ax.get_legend().legend_handles:
        legend_handle.set_markeredgewidth(0.2)
        legend_handle.set_markeredgecolor("darkslategrey")
plt.tight_layout()
plt.show()

NI data

bound_ni = gpd.read_file(
    os.path.join("data", "boundaries", "boundaries_all.gpkg"),
    layer="ONS_NI_wards_12_2022_2157",
)

bound_ni.head()

	OBJECTID	WD22CD	WD22NM	WD22NMW	LAD22CD	LAD22NM	BNG_E	BNG_N	LONG	LAT	GlobalID	SHAPE_Leng	SHAPE_Area	geometry
0	6905	N08000101	Abbey	None	N09000001	Antrim and Newtownabbey	148871	538433	-5.89564	54.677608	{5BDA2CD0-D7CB-4D6B-90EB-75F8A1FFD7A4}	5291.934708	9.102273e+05	POLYGON ((736083.766 883168.756, 736079.853 88...
1	6906	N08000102	Aldergrove	None	N09000001	Antrim and Newtownabbey	123312	535417	-6.28810	54.637211	{EF80E5AC-3B27-4D56-9BB3-0CBFE94D7642}	66396.070829	1.562231e+08	POLYGON ((716585.770 885559.814, 716589.067 88...
2	6907	N08000103	Antrim Centre	None	N09000001	Antrim and Newtownabbey	126897	544127	-6.24085	54.717220	{2900E2DF-24DB-45B8-8266-663DDF1D3BDF}	17140.311467	1.062755e+07	POLYGON ((713846.305 888779.215, 713856.936 88...
3	6908	N08000104	Ballyclare East	None	N09000001	Antrim and Newtownabbey	142993	547438	-5.99452	54.755379	{ED83EA03-CE92-4D89-B5C4-BEB02CD9A528}	8186.240587	1.828746e+06	POLYGON ((728893.847 890935.685, 728892.974 89...
4	6909	N08000105	Ballyclare West	None	N09000001	Antrim and Newtownabbey	141887	547417	-6.01165	54.754620	{0835C4C3-E634-4DEC-B0BE-3A67BFF613C7}	8307.724846	1.782133e+06	POLYGON ((728672.484 892458.897, 728669.323 89...

bound_ni.shape

(462, 14)

coa_ni = pd.read_csv(
    os.path.join(
        "data", "agricultural_census", "DAERA", "daera_agricultural_census.csv"
    )
)

coa_ni.head()

	ward_2014_code	ward_2014_name	year	total_grass_hectares	total_cattle	total_sheep
0	N08000101	Abbey (Antrim and Newtownabbey)	2018	3	3	3
1	N08000102	Aldergrove	2018	5676	10784	15053
2	N08000103	Antrim Centre	2018	3	3	3
3	N08000104	Ballyclare East	2018	3	3	3
4	N08000105	Ballyclare West	2018	148	207	152

coa_ni.shape

(462, 6)

coa_ni.rename(columns={"ward_2014_code": "WD22CD"}, inplace=True)

data_ni = pd.merge(bound_ni, coa_ni, on=["WD22CD"])

data_ni.head()

	OBJECTID	WD22CD	WD22NM	WD22NMW	LAD22CD	LAD22NM	BNG_E	BNG_N	LONG	LAT	GlobalID	SHAPE_Leng	SHAPE_Area	geometry	ward_2014_name	year	total_grass_hectares	total_cattle	total_sheep
0	6905	N08000101	Abbey	None	N09000001	Antrim and Newtownabbey	148871	538433	-5.89564	54.677608	{5BDA2CD0-D7CB-4D6B-90EB-75F8A1FFD7A4}	5291.934708	9.102273e+05	POLYGON ((736083.766 883168.756, 736079.853 88...	Abbey (Antrim and Newtownabbey)	2018	3	3	3
1	6906	N08000102	Aldergrove	None	N09000001	Antrim and Newtownabbey	123312	535417	-6.28810	54.637211	{EF80E5AC-3B27-4D56-9BB3-0CBFE94D7642}	66396.070829	1.562231e+08	POLYGON ((716585.770 885559.814, 716589.067 88...	Aldergrove	2018	5676	10784	15053
2	6907	N08000103	Antrim Centre	None	N09000001	Antrim and Newtownabbey	126897	544127	-6.24085	54.717220	{2900E2DF-24DB-45B8-8266-663DDF1D3BDF}	17140.311467	1.062755e+07	POLYGON ((713846.305 888779.215, 713856.936 88...	Antrim Centre	2018	3	3	3
3	6908	N08000104	Ballyclare East	None	N09000001	Antrim and Newtownabbey	142993	547438	-5.99452	54.755379	{ED83EA03-CE92-4D89-B5C4-BEB02CD9A528}	8186.240587	1.828746e+06	POLYGON ((728893.847 890935.685, 728892.974 89...	Ballyclare East	2018	3	3	3
4	6909	N08000105	Ballyclare West	None	N09000001	Antrim and Newtownabbey	141887	547417	-6.01165	54.754620	{0835C4C3-E634-4DEC-B0BE-3A67BFF613C7}	8307.724846	1.782133e+06	POLYGON ((728672.484 892458.897, 728669.323 89...	Ballyclare West	2018	148	207	152

data_ni.shape

(462, 19)

fig, axs = plt.subplots(1, 3, figsize=(15, 15), sharey=True)
cols = [
    ("total_cattle", "Total cattle"),
    ("total_sheep", "Total sheep"),
    ("total_grass_hectares", "Total grassland (hectares)"),
]
for i, ax in enumerate(axs.flat):
    data_ni.plot(
        column=cols[i][0],
        ax=ax,
        cmap="Spectral_r",
        scheme="equal_interval",
        edgecolor="darkslategrey",
        linewidth=0.2,
        legend=True,
        legend_kwds={
            "loc": "upper left",
            "fmt": "{:.0f}",
            "title": cols[i][1],
        },
    )
    # ax.ticklabel_format(style="scientific", scilimits=[-4, 4])
    ax.tick_params(labelbottom=False, labelleft=False)
    for legend_handle in ax.get_legend().legend_handles:
        legend_handle.set_markeredgewidth(0.2)
        legend_handle.set_markeredgecolor("darkslategrey")
plt.tight_layout()
plt.show()

Merge

# subset data
data_ie = data_ie[
    [
        "ENGLISH",
        "COUNTY",
        "PROVINCE",
        "GUID",
        "total_cattle",
        "total_sheep",
        "total_grass_hectares",
        "electoral_division",
        "geometry",
    ]
]

data_ni = data_ni[
    [
        "WD22CD",
        "WD22NM",
        "ward_2014_name",
        "total_cattle",
        "total_sheep",
        "total_grass_hectares",
        "geometry",
    ]
]

data_ie[["total_cattle", "total_sheep", "total_grass_hectares"]] = data_ie[
    ["total_cattle", "total_sheep", "total_grass_hectares"]
].astype(float)
data_ni[["total_cattle", "total_sheep", "total_grass_hectares"]] = data_ni[
    ["total_cattle", "total_sheep", "total_grass_hectares"]
].astype(float)

/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/geopandas/geodataframe.py:1472: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super().__setitem__(key, value)
/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/geopandas/geodataframe.py:1472: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super().__setitem__(key, value)

data_ni["ENGLISH"] = data_ni["WD22NM"].str.upper()
data_ni["PROVINCE"] = "Ulster"

/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/geopandas/geodataframe.py:1472: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super().__setitem__(key, value)
/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/geopandas/geodataframe.py:1472: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  super().__setitem__(key, value)

data = pd.merge(data_ie, data_ni, how="outer")

fig, axs = plt.subplots(1, 3, figsize=(15, 15), sharey=True)
cols = [
    ("total_cattle", "Total cattle"),
    ("total_sheep", "Total sheep"),
    ("total_grass_hectares", "Total grassland (hectares)"),
]
for i, ax in enumerate(axs.flat):
    data.plot(
        column=cols[i][0],
        ax=ax,
        cmap="Spectral_r",
        scheme="equal_interval",
        edgecolor="darkslategrey",
        linewidth=0.2,
        legend=True,
        legend_kwds={
            "loc": "upper left",
            "fmt": "{:.0f}",
            "title": cols[i][1],
        },
    )
    # ax.ticklabel_format(style="scientific", scilimits=[-4, 4])
    ax.tick_params(labelbottom=False, labelleft=False)
    for legend_handle in ax.get_legend().legend_handles:
        legend_handle.set_markeredgewidth(0.2)
        legend_handle.set_markeredgecolor("darkslategrey")
plt.tight_layout()
plt.show()

Stocking rate

data.loc[data["total_grass_hectares"] == 0.0, "stocking_rate"] = 0.0
data.loc[data["total_grass_hectares"] > 0.0, "stocking_rate"] = (
    data["total_cattle"] * 0.8 + data["total_sheep"] * 0.1
) / data["total_grass_hectares"]

data["stocking_rate"].max()

5.627624825011666

data["stocking_rate"].min()

0.0

axs = data.plot(
    column="stocking_rate",
    cmap="Spectral_r",
    scheme="equal_interval",
    edgecolor="darkslategrey",
    linewidth=0.2,
    figsize=(7.5, 7.5),
    legend=True,
    legend_kwds={
        "loc": "upper left",
        "fmt": "{:.2f}",
        "title": "Stocking rate",
    },
)
plt.ticklabel_format(style="scientific", scilimits=[-4, 4])
for legend_handle in axs.get_legend().legend_handles:
    legend_handle.set_markeredgewidth(0.2)
    legend_handle.set_markeredgecolor("darkslategrey")
axs.tick_params(labelbottom=False, labelleft=False)
plt.tight_layout()
plt.show()

data.to_file(
    os.path.join("data", "agricultural_census", "agricultural_census.gpkg"),
    layer="stocking_rate",
)