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gp_sya_rgn.csv

Patients registered at a GP practice

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gss_code	gss_name	geography	measure	extract_date	sex	age_0	age_1	age_2	age_3	age_4	age_5	age_6	age_7	age_8	age_9	age_10	age_11	age_12	age_13	age_14	age_15	age_16	age_17	age_18	age_19	age_20	age_21	age_22	age_23	age_24	age_25	age_26	age_27	age_28	age_29	age_30	age_31	age_32	age_33	age_34	age_35	age_36	age_37	age_38	age_39	age_40	age_41	age_42	age_43	age_44	age_45	age_46	age_47	age_48	age_49	age_50	age_51	age_52	age_53	age_54	age_55	age_56	age_57	age_58	age_59	age_60	age_61	age_62	age_63	age_64	age_65	age_66	age_67	age_68	age_69	age_70	age_71	age_72	age_73	age_74	age_75	age_76	age_77	age_78	age_79	age_80	age_81	age_82	age_83	age_84	age_85	age_86	age_87	age_88	age_89	age_90	age_91	age_92	age_93	age_94	age_95
E12000001	North East	RGN23	gp_count	2014-10-01	female	12627.3	14236.4	15127.4	15212.8	15125.3	14833.9	15339	14615.2	14718.1	14271.4	14012.3	13575.5	13221	13327.9	13705.2	14231.5	14719.4	15399.6	15417.4	17387.5	18469.2	18818.3	19219	19495.7	19365.2	17905.5	18473.7	18315.3	18012.1	17916.3	17290.5	17113.4	17068.1	17240.4	17457.9	16824.3	15233.2	14283.6	15330.8	15179.7	15884.8	16509.1	17738	19182.6	18547.8	18748.9	18793.2	19477.5	19668.3	20126.3	20142	20124.7	19745.1	19281.4	18627	18628.6	18702.1	17887.9	17204	16372.1	16192.1	16300.5	15754.1	15801.6	15859.6	16227.2	16888.2	18729.4	15133.2	13429.5	13554.1	12184.5	11293.3	10639.7	11296.7	11222.9	11212.9	10712.4	9861	9585.7	8760.6	8270.8	8050.1	7675.8	7201.9	6263.4	5597.7	4859.4	4459.6	3920	3291.6	2781.2	2370.7	1998.6	1700.8	3024
E12000001	North East	RGN23	gp_count	2015-01-01	female	12431.7	14145	15014.8	15156.9	15313.4	14856.6	15273.7	14815.8	14756.5	14374.6	14029.9	13756.7	13328.3	13243	13618	14183.6	14589.3	15169.4	16375.5	17592.5	18552.4	18896.6	19243.1	19609.7	19698.7	17989.6	18397.3	18401.4	18214.4	17836.6	17482.4	17032.3	17169.9	17111.1	17571.3	17175.7	15639	14309	15147.7	15198.4	15591.7	16402.4	17317.7	18945.4	18839.9	18598	18776.8	19331.8	19516.5	20096.5	20233.7	20183	19701.8	19380	18853.2	18483.4	18831.5	18091.6	17410.4	16572.5	16167.4	16304.1	15915.1	15635.8	15765	16179.9	16708	18159.7	16361.1	13066.3	14104.6	12307.8	11564.9	10613.1	11058.7	11156	11187.6	10754.7	9979.8	9592.8	8888	8135.5	8059.3	7574.6	7284.4	6217.5	5718.6	4732.3	4544.2	3838.3	3349.9	2716.2	2327	1999.2	1639	3167.6
E12000001	North East	RGN23	gp_count	2015-04-01	female	12425.4	14125.7	14790.6	15334.6	15293.1	15023.8	14998.9	15155.1	14638.9	14434.3	14213.2	13988.8	13286.8	13157.9	13537.6	14177.2	14396.5	15055.5	16208.9	17226.7	18528.8	18918.9	19030.3	19651.1	19722.3	18019.2	18151.1	18750.3	18042.5	17989.1	17633.3	17198.4	17031.9	17110.5	17401.4	17377.5	16042.6	14496.1	14671.9	15415.6	15482.7	16167	16941.9	18586.9	18989	18414.4	18989.3	18996	19613.5	19959.1	20109.9	20195.9	19847.1	19594.3	18902.8	18505.5	18684	18398.7	17417.3	16818.7	16265.1	16270.8	15894.9	15649.8	15668.4	16221.4	16325.3	17594.5	17674.4	13362.8	13900.6	12569.3	11677.6	10796.5	10739.9	11128.2	10998.7	10949.6	10015.5	9490.8	8865.6	8248.5	7940.8	7488.7	7247.4	6226.3	5665.3	4740.7	4396.8	3810.9	3294.5	2683	2285.1	1933.8	1518.4	3150.3
E12000001	North East	RGN23	gp_count	2015-07-01	female	12427.6	14084	14658.4	15191.2	15365.4	15132.2	14851.1	15365.6	14651.9	14688.4	14181.7	13997.4	13490.8	13122.9	13458.3	13982.9	14349.9	14903.9	15908	16897.3	18270.5	19067.1	18725.1	19538.6	19658.7	18052.9	18092.8	18621.9	18134.7	18114.4	17838.3	17181.5	17237	17106.7	17184	17393.7	16583.1	14874	14338.7	15426.6	15438.1	15883.3	16775.9	18128.2	19181.3	18430.3	18745.5	18986.2	19559.5	19791.3	20117.3	20072.5	20051.9	19651.8	19032.4	18569	18646.7	18554.7	17608.8	16933.8	16264.9	16220.1	16070.9	15607.8	15650.6	16091.6	16178.7	17098.3	18462.8	13933.4	13403.2	13087.5	11833	11066	10417.2	11090.2	10934.6	10880.8	10192.3	9367.1	9126.9	8275.5	7850.2	7587.4	7117.9	6485.3	5611.6	4870.6	4294.5	3804.6	3302.7	2749.8	2225.8	1916.6	1514.5	3271.4