将 geopandas 行复制到空白 geopandas 行

Question

我有一个要从 geopandas 数据框中提取的邮政编码列表。我能够成功地检测到带有邮政编码列表 (rfp) 的行，但是无法创建新的 geopandas DataFrame，只复制新行。

我尝试追加，iloc

是否有更简单的方法来完成此操作？

i =0
while i < len(rfp):
    for index, row in countries.iterrows():
            if rfp[i] == row['CFSAUID']:
                #print(index, row)
                print(index, row['CFSAUID'], countries.iloc[index])
                #data=data.append[countries.iloc[index]] 
    #print(rfp[i])
    i = i + 1
data.head()

Answer 1

您似乎无缘无故地使 pandas / geopandas 过滤器功能过于复杂
已获取所有美国邮政编码几何图形
使用 loc[]
已将几何简化为质心以便能够在此答案中显示输出

import geopandas as gpd
gdf = gpd.read_file("https://www2.census.gov/geo/tiger/TIGER2021/ZCTA520/tl_2021_us_zcta520.zip")

zipcode = ['41714', '47994', '40502', '46550', '46385', '46731', '46170',
       '40071', '46049', '46985', '46256', '41603', '40511', '41005',
       '46808', '41006', '47338', '46118', '40003', '41179']


gdf2 = gdf.loc[gdf["ZCTA5CE20"].isin(zipcode)].copy()
gdf2["geometry"] = gdf2["geometry"].centroid
gdf2

	ZCTA5CE20	GEOID20	CLASSFP20	MTFCC20	FUNCSTAT20	ALAND20	AWATER20	INTPTLAT20	INTPTLON20	geometry
17	46118	46118	B5	G6350	S	141161691	408941	39.6587	-86.5313	POINT (-86.52394789855478 39.65319687881211)
19	46256	46256	B5	G6350	S	28865547	2051373	39.9084	-86.0131	POINT (-86.0114959356422 39.90683668248156)
36	46731	46731	B5	G6350	S	40833756	74360	40.7935	-85.0996	POINT (-85.10270347937339 40.79753662311887)
66	46985	46985	B5	G6350	S	170789205	115396	40.9595	-86.5805	POINT (-86.58222146640128 40.95485185925257)
67	47994	47994	B5	G6350	S	56334635	0	40.1823	-87.0823	POINT (-87.0823111593409 40.18233088778645)
75	40071	40071	B5	G6350	S	314120461	3703551	38.0429	-85.3788	POINT (-85.37070453567415 38.04328301537532)
76	41005	41005	B5	G6350	S	135617739	97008	39.0068	-84.7601	POINT (-84.7653976667778 39.00706909605251)
81	40511	40511	B5	G6350	S	222838540	808726	38.141	-84.4616	POINT (-84.47394279725246 38.13277356826288)
83	40502	40502	B5	G6350	S	18509366	699624	38.011	-84.4832	POINT (-84.48188158114969 38.01371604197583)
86	40003	40003	B5	G6350	S	112166630	1151993	38.2767	-85.0438	POINT (-85.04368804019533 38.26863127746849)
92	41006	41006	B5	G6350	S	143721210	2283721	38.7844	-84.3456	POINT (-84.34296186884575 38.78473023614392)
100	41179	41179	B5	G6350	S	877946552	2573419	38.535	-83.3701	POINT (-83.38987423897763 38.52484654452977)
108	41603	41603	B5	G6350	S	36349511	116254	37.5715	-82.7046	POINT (-82.68704929399041 37.55933118794476)
140	41714	41714	B5	G6350	S	31218191	51291	37.1632	-83.5058	POINT (-83.50751835227443 37.16518559160255)
142	46385	46385	B5	G6350	S	209128553	1458064	41.4644	-87.1241	POINT (-87.12395316038518 41.46394402403933)
146	46550	46550	B5	G6350	S	185523489	140699	41.4469	-86.0006	POINT (-86.00026862329979 41.4470028890462)
156	46049	46049	B5	G6350	S	67941709	6187	40.295	-86.2218	POINT (-86.22160670624778 40.29760037111507)
163	46808	46808	B5	G6350	S	27442493	192647	41.0978	-85.1771	POINT (-85.17619884243086 41.0988556047745)
176	47338	47338	B5	G6350	S	77579648	653392	40.3424	-85.3374	POINT (-85.33974232857304 40.34362126071514)
188	46170	46170	B5	G6350	S	521838	0	39.5716	-86.8627	POINT (-86.86265114552866 39.57162423401216)

将 geopandas 行复制到空白 geopandas 行

copy geopandas rows to a blank geopandas row

python

dataframe

pandas

geopandas