Annual death rates in people of different ages, by sex world

Author

math4mad

ref

ref :Annual death rates in people of different ages, by sex

Code

include("utils.jl")

[ Info: loading success

"Entity", "Code", "Year", "Central death rate - Type: period - Sex: female - Age: 0", "Central death rate - Type: period - Sex: male - Age: 0", "Central death rate - Type: period - Sex: female - Age: 10", "Central death rate - Type: period - Sex: male - Age: 10", "Central death rate - Type: period - Sex: female - Age: 15", "Central death rate - Type: period - Sex: male - Age: 15", "Central death rate - Type: period - Sex: female - Age: 25", "Central death rate - Type: period - Sex: male - Age: 25", "Central death rate - Type: period - Sex: female - Age: 45", "Central death rate - Type: period - Sex: male - Age: 45", "Central death rate - Type: period - Sex: female - Age: 65", "Central death rate - Type: period - Sex: male - Age: 65", "Central death rate - Type: period - Sex: female - Age: 80", "Central death rate - Type: period - Sex: male - Age: 80"]

2. load data->dataframe

Code

df=@pipe CSV.File("./data/annual-death-rates-in-different-age-groups-by-sex.csv")|>DataFrame

19922×17 DataFrame

19897 rows omitted

Row	Entity	Code	Year	Central death rate - Type: period - Sex: female - Age: 0	Central death rate - Type: period - Sex: male - Age: 0	Central death rate - Type: period - Sex: female - Age: 10	Central death rate - Type: period - Sex: male - Age: 10	Central death rate - Type: period - Sex: female - Age: 15	Central death rate - Type: period - Sex: male - Age: 15	Central death rate - Type: period - Sex: female - Age: 25	Central death rate - Type: period - Sex: male - Age: 25	Central death rate - Type: period - Sex: female - Age: 45	Central death rate - Type: period - Sex: male - Age: 45	Central death rate - Type: period - Sex: female - Age: 65	Central death rate - Type: period - Sex: male - Age: 65	Central death rate - Type: period - Sex: female - Age: 80	Central death rate - Type: period - Sex: male - Age: 80
	String	String15?	Int64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64
1	Afghanistan	AFG	1950	328.053	378.814	7.72991	6.52991	9.96758	8.11575	15.0426	14.8812	21.2739	27.5066	67.6107	77.0253	211.223	226.547
2	Afghanistan	AFG	1951	324.777	374.956	7.65714	6.47173	9.87427	8.0444	14.9049	14.7495	21.0961	27.2708	67.1116	76.5053	209.885	225.159
3	Afghanistan	AFG	1952	318.286	366.965	7.51281	6.3596	9.6892	7.90725	14.6317	14.4965	20.7428	26.8212	66.1187	75.5487	207.22	222.703
4	Afghanistan	AFG	1953	311.888	358.685	7.37038	6.25279	9.50655	7.77702	14.3619	14.2566	20.3934	26.3985	65.1349	74.6933	204.573	220.633
5	Afghanistan	AFG	1954	305.975	351.087	7.47033	6.32612	9.54872	7.80432	14.3075	14.1708	20.3094	26.2079	64.6866	74.327	202.837	219.442
6	Afghanistan	AFG	1955	298.864	342.552	7.08519	6.0428	9.14193	7.52088	13.824	13.7848	19.7027	25.5661	63.2202	72.9975	199.518	216.517
7	Afghanistan	AFG	1956	292.437	334.788	6.9579	5.95098	8.97388	7.40485	13.5696	13.5633	19.3775	25.173	62.3198	72.1939	197.145	214.542
8	Afghanistan	AFG	1957	285.96	327.082	6.80497	5.82437	8.78425	7.25426	13.2964	13.2944	19.0277	24.7002	61.3636	71.1901	194.668	212.095
9	Afghanistan	AFG	1958	279.403	319.298	6.66214	5.69684	8.60189	7.09851	13.0273	13.0086	18.6822	24.1954	60.4097	70.1002	192.166	209.401
10	Afghanistan	AFG	1959	273.273	312.183	6.52603	5.58004	8.42824	6.9558	12.7715	12.7468	18.3544	23.7325	59.5094	69.0955	189.867	206.911
11	Afghanistan	AFG	1960	267.463	305.598	6.40648	5.48074	8.27133	6.83256	12.5389	12.5175	18.0579	23.3241	58.6735	68.2023	187.792	204.59
12	Afghanistan	AFG	1961	261.854	298.886	6.26721	5.3612	8.09831	6.68825	12.2866	12.256	17.7335	22.8633	57.8106	67.1957	185.652	202.185
13	Afghanistan	AFG	1962	256.655	292.773	6.14919	5.26366	7.9478	6.56954	12.0652	12.0384	17.4491	22.4812	57.0294	66.3898	183.704	200.26
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
19911	Zimbabwe	ZWE	2010	53.9416	60.8736	1.63101	1.90256	2.49942	2.61754	8.802	8.97857	20.8596	27.2927	45.8422	52.5112	86.3175	114.257
19912	Zimbabwe	ZWE	2011	50.7671	57.5466	1.5059	1.7603	2.24074	2.40589	6.98757	7.8604	16.663	23.4714	41.1328	49.1328	85.6723	113.942
19913	Zimbabwe	ZWE	2012	45.8417	52.3628	1.2744	1.53946	1.90764	2.12629	5.97021	6.73963	14.7873	20.558	37.6887	46.8993	85.0377	113.63
19914	Zimbabwe	ZWE	2013	42.4171	48.8878	1.14827	1.36861	1.71382	1.9229	5.13833	5.92327	13.1951	18.2398	35.8164	45.3136	84.4419	113.357
19915	Zimbabwe	ZWE	2014	40.2433	46.6497	1.06513	1.26043	1.58333	1.78416	4.57123	5.31936	12.052	16.3566	34.5043	43.8205	83.7835	113.008
19916	Zimbabwe	ZWE	2015	39.3862	45.7603	1.03008	1.21829	1.51606	1.7263	4.23604	5.0488	11.3024	15.4633	33.6349	43.0445	83.1682	112.702
19917	Zimbabwe	ZWE	2016	37.7949	44.0875	0.97629	1.14752	1.43611	1.64832	3.93881	4.80345	10.7236	14.872	32.8932	42.7217	82.5508	112.388
19918	Zimbabwe	ZWE	2017	36.8661	43.1389	0.95685	1.12218	1.38986	1.61538	3.73174	4.70667	10.2912	14.6938	32.3443	42.7099	81.9914	112.102
19919	Zimbabwe	ZWE	2018	35.4646	41.6297	0.89795	1.04302	1.32043	1.53221	3.51856	4.42719	9.86634	13.892	31.726	42.13	81.3326	111.776
19920	Zimbabwe	ZWE	2019	35.3383	41.4167	0.93255	1.07613	1.32845	1.55651	3.48048	4.53653	9.78645	14.3989	31.6513	42.7631	80.8855	111.541
19921	Zimbabwe	ZWE	2020	34.9539	40.9834	0.87637	1.02782	1.20826	1.39351	3.11532	4.14614	9.38663	15.0135	33.6533	48.0212	82.9557	120.98
19922	Zimbabwe	ZWE	2021	34.9083	40.922	0.86883	1.02383	1.30698	1.58042	3.38878	4.70133	10.5541	17.1106	38.6799	56.6425	100.369	143.754

Code

cats=names(df)
rename!(df,  "Central death rate - Type: period - Sex: female - Age: 0"=>:female_age0, 
             "Central death rate - Type: period - Sex: male - Age: 0"=>:male_age0, 
             "Central death rate - Type: period - Sex: female - Age: 10"=>:female_age10, 
             "Central death rate - Type: period - Sex: male - Age: 10"=>:male_age10, 
             "Central death rate - Type: period - Sex: female - Age: 15"=>:female_age15, 
             "Central death rate - Type: period - Sex: male - Age: 15"=>:male_age15, 
             "Central death rate - Type: period - Sex: female - Age: 25"=>:female_age25, 
             "Central death rate - Type: period - Sex: male - Age: 25"=>:male_age25, 
             "Central death rate - Type: period - Sex: female - Age: 45"=>:female_age45, 
             "Central death rate - Type: period - Sex: male - Age: 45"=>:male_age45,
              "Central death rate - Type: period - Sex: female - Age: 65"=>:female_age65, 
              "Central death rate - Type: period - Sex: male - Age: 65"=>:male_age65, 
              "Central death rate - Type: period - Sex: female - Age: 80"=>:female_age80, 
              "Central death rate - Type: period - Sex: male - Age: 80" =>:male_age80 
)

19922×17 DataFrame

19897 rows omitted

Row	Entity	Code	Year	female_age0	male_age0	female_age10	male_age10	female_age15	male_age15	female_age25	male_age25	female_age45	male_age45	female_age65	male_age65	female_age80	male_age80
	String	String15?	Int64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64	Float64
1	Afghanistan	AFG	1950	328.053	378.814	7.72991	6.52991	9.96758	8.11575	15.0426	14.8812	21.2739	27.5066	67.6107	77.0253	211.223	226.547
2	Afghanistan	AFG	1951	324.777	374.956	7.65714	6.47173	9.87427	8.0444	14.9049	14.7495	21.0961	27.2708	67.1116	76.5053	209.885	225.159
3	Afghanistan	AFG	1952	318.286	366.965	7.51281	6.3596	9.6892	7.90725	14.6317	14.4965	20.7428	26.8212	66.1187	75.5487	207.22	222.703
4	Afghanistan	AFG	1953	311.888	358.685	7.37038	6.25279	9.50655	7.77702	14.3619	14.2566	20.3934	26.3985	65.1349	74.6933	204.573	220.633
5	Afghanistan	AFG	1954	305.975	351.087	7.47033	6.32612	9.54872	7.80432	14.3075	14.1708	20.3094	26.2079	64.6866	74.327	202.837	219.442
6	Afghanistan	AFG	1955	298.864	342.552	7.08519	6.0428	9.14193	7.52088	13.824	13.7848	19.7027	25.5661	63.2202	72.9975	199.518	216.517
7	Afghanistan	AFG	1956	292.437	334.788	6.9579	5.95098	8.97388	7.40485	13.5696	13.5633	19.3775	25.173	62.3198	72.1939	197.145	214.542
8	Afghanistan	AFG	1957	285.96	327.082	6.80497	5.82437	8.78425	7.25426	13.2964	13.2944	19.0277	24.7002	61.3636	71.1901	194.668	212.095
9	Afghanistan	AFG	1958	279.403	319.298	6.66214	5.69684	8.60189	7.09851	13.0273	13.0086	18.6822	24.1954	60.4097	70.1002	192.166	209.401
10	Afghanistan	AFG	1959	273.273	312.183	6.52603	5.58004	8.42824	6.9558	12.7715	12.7468	18.3544	23.7325	59.5094	69.0955	189.867	206.911
11	Afghanistan	AFG	1960	267.463	305.598	6.40648	5.48074	8.27133	6.83256	12.5389	12.5175	18.0579	23.3241	58.6735	68.2023	187.792	204.59
12	Afghanistan	AFG	1961	261.854	298.886	6.26721	5.3612	8.09831	6.68825	12.2866	12.256	17.7335	22.8633	57.8106	67.1957	185.652	202.185
13	Afghanistan	AFG	1962	256.655	292.773	6.14919	5.26366	7.9478	6.56954	12.0652	12.0384	17.4491	22.4812	57.0294	66.3898	183.704	200.26
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
19911	Zimbabwe	ZWE	2010	53.9416	60.8736	1.63101	1.90256	2.49942	2.61754	8.802	8.97857	20.8596	27.2927	45.8422	52.5112	86.3175	114.257
19912	Zimbabwe	ZWE	2011	50.7671	57.5466	1.5059	1.7603	2.24074	2.40589	6.98757	7.8604	16.663	23.4714	41.1328	49.1328	85.6723	113.942
19913	Zimbabwe	ZWE	2012	45.8417	52.3628	1.2744	1.53946	1.90764	2.12629	5.97021	6.73963	14.7873	20.558	37.6887	46.8993	85.0377	113.63
19914	Zimbabwe	ZWE	2013	42.4171	48.8878	1.14827	1.36861	1.71382	1.9229	5.13833	5.92327	13.1951	18.2398	35.8164	45.3136	84.4419	113.357
19915	Zimbabwe	ZWE	2014	40.2433	46.6497	1.06513	1.26043	1.58333	1.78416	4.57123	5.31936	12.052	16.3566	34.5043	43.8205	83.7835	113.008
19916	Zimbabwe	ZWE	2015	39.3862	45.7603	1.03008	1.21829	1.51606	1.7263	4.23604	5.0488	11.3024	15.4633	33.6349	43.0445	83.1682	112.702
19917	Zimbabwe	ZWE	2016	37.7949	44.0875	0.97629	1.14752	1.43611	1.64832	3.93881	4.80345	10.7236	14.872	32.8932	42.7217	82.5508	112.388
19918	Zimbabwe	ZWE	2017	36.8661	43.1389	0.95685	1.12218	1.38986	1.61538	3.73174	4.70667	10.2912	14.6938	32.3443	42.7099	81.9914	112.102
19919	Zimbabwe	ZWE	2018	35.4646	41.6297	0.89795	1.04302	1.32043	1.53221	3.51856	4.42719	9.86634	13.892	31.726	42.13	81.3326	111.776
19920	Zimbabwe	ZWE	2019	35.3383	41.4167	0.93255	1.07613	1.32845	1.55651	3.48048	4.53653	9.78645	14.3989	31.6513	42.7631	80.8855	111.541
19921	Zimbabwe	ZWE	2020	34.9539	40.9834	0.87637	1.02782	1.20826	1.39351	3.11532	4.14614	9.38663	15.0135	33.6533	48.0212	82.9557	120.98
19922	Zimbabwe	ZWE	2021	34.9083	40.922	0.86883	1.02383	1.30698	1.58042	3.38878	4.70133	10.5541	17.1106	38.6799	56.6425	100.369	143.754

Code

female_data=@chain df begin
   @filter(Year==2021)
   @select(1,3:17)
   @select(startswith("female"))
   @summarize(female_age0=mean(female_age0),female_age10=mean(female_age10),female_age15=mean(female_age15),female_age25=mean(female_age25),    female_age45=mean(female_age45),female_age65=mean(female_age65),female_age80=mean(female_age80))
end

1×7 DataFrame

Row	female_age0	female_age10	female_age15	female_age25	female_age45	female_age65	female_age80
	Float64	Float64	Float64	Float64	Float64	Float64	Float64
1	16.8304	0.426706	0.564174	1.06755	3.32511	18.0247	77.9603

Code

male_data=@chain df begin
   @filter(Year==2021)
   @select(1,3:17)
   @select(startswith("male"))
   @summarize(male_age0=mean(male_age0),male_age10=mean(male_age10),male_age15=mean(male_age15),male_age25=mean(male_age25),male_age45=mean(male_age45),male_age65=mean(male_age65),male_age80=mean(male_age80))
end

1×7 DataFrame

Row	male_age0	male_age10	male_age15	male_age25	male_age45	male_age65	male_age80
	Float64	Float64	Float64	Float64	Float64	Float64	Float64
1	20.0176	0.504313	0.759778	1.84672	5.45103	29.892	109.894