Overview

Dataset statistics

Number of variables8
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory73.7 B

Variable types

Categorical2
Text1
Numeric5

Dataset

Description건강보험 입원환자 통계 / 진료일자 기준(심사분은 각 진료년+4개월) (예) 진료년월: 2022.1월~12월, 심사년월: 2022.1월~2023.4월 / 보험자: 건강보험 / 입원환자(입원명세서) 대상
URLhttps://www.data.go.kr/data/15052315/fileData.do

Alerts

진료년도 has constant value ""Constant
환자수 is highly overall correlated with 명세서청구건수 and 3 other fieldsHigh correlation
명세서청구건수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
입원일수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
요양급여비용총액 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
보험자부담금 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
환자수 has unique valuesUnique
명세서청구건수 has unique valuesUnique
입원일수 has unique valuesUnique
요양급여비용총액 has unique valuesUnique
보험자부담금 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:33:40.900429
Analysis finished2023-12-12 14:33:44.092067
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2022
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 36
100.0%

Length

2023-12-12T23:33:44.158863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:33:44.256539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 36
100.0%

성별
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
남
18 
여
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row남
3rd row남
4th row남
5th row남

Common Values

ValueCountFrequency (%)
남 18
50.0%
여 18
50.0%

Length

2023-12-12T23:33:44.364317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:33:44.479365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 18
50.0%
여 18
50.0%

연령군
Text

Distinct18
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T23:33:44.654326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.7777778
Min length7

Characters and Unicode

Total characters316
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_0~4세
2nd row02_5~9세
3rd row03_10~14세
4th row04_15~19세
5th row05_20~24세
ValueCountFrequency (%)
01_0~4세 2
 
5.3%
11_50~54세 2
 
5.3%
18_85세 2
 
5.3%
17_80~84세 2
 
5.3%
16_75~79세 2
 
5.3%
15_70~74세 2
 
5.3%
14_65~69세 2
 
5.3%
13_60~64세 2
 
5.3%
12_55~59세 2
 
5.3%
10_45~49세 2
 
5.3%
Other values (9) 18
47.4%
2023-12-12T23:33:45.042821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
12.0%
_ 36
11.4%
세 36
11.4%
~ 34
10.8%
1 30
9.5%
4 30
9.5%
5 30
9.5%
9 18
5.7%
2 12
 
3.8%
3 12
 
3.8%
Other values (6) 40
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
64.6%
Other Letter 40
 
12.7%
Connector Punctuation 36
 
11.4%
Math Symbol 34
 
10.8%
Space Separator 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
18.6%
1 30
14.7%
4 30
14.7%
5 30
14.7%
9 18
8.8%
2 12
 
5.9%
3 12
 
5.9%
6 12
 
5.9%
7 12
 
5.9%
8 10
 
4.9%
Other Letter
ValueCountFrequency (%)
세 36
90.0%
이 2
 
5.0%
상 2
 
5.0%
Connector Punctuation
ValueCountFrequency (%)
_ 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
87.3%
Hangul 40
 
12.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
13.8%
_ 36
13.0%
~ 34
12.3%
1 30
10.9%
4 30
10.9%
5 30
10.9%
9 18
6.5%
2 12
 
4.3%
3 12
 
4.3%
6 12
 
4.3%
Other values (3) 24
8.7%
Hangul
ValueCountFrequency (%)
세 36
90.0%
이 2
 
5.0%
상 2
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
87.3%
Hangul 40
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
13.8%
_ 36
13.0%
~ 34
12.3%
1 30
10.9%
4 30
10.9%
5 30
10.9%
9 18
6.5%
2 12
 
4.3%
3 12
 
4.3%
6 12
 
4.3%
Other values (3) 24
8.7%
Hangul
ValueCountFrequency (%)
세 36
90.0%
이 2
 
5.0%
상 2
 
5.0%

환자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196182.61
Minimum53353
Maximum368315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:33:45.188198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53353
5-th percentile71884.25
Q1132562.25
median205903.5
Q3244365.75
95-th percentile323105.5
Maximum368315
Range314962
Interquartile range (IQR)111803.5

Descriptive statistics

Standard deviation82296.017
Coefficient of variation (CV)0.41948681
Kurtosis-0.80836037
Mean196182.61
Median Absolute Deviation (MAD)61228
Skewness0.023348311
Sum7062574
Variance6.7726345 × 109
MonotonicityNot monotonic
2023-12-12T23:33:45.327498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
214833 1
 
2.8%
72785 1
 
2.8%
69182 1
 
2.8%
110563 1
 
2.8%
172320 1
 
2.8%
246873 1
 
2.8%
220072 1
 
2.8%
215867 1
 
2.8%
229459 1
 
2.8%
289459 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
53353 1
2.8%
69182 1
2.8%
72785 1
2.8%
76987 1
2.8%
89568 1
2.8%
93718 1
2.8%
106290 1
2.8%
110563 1
2.8%
123242 1
2.8%
135669 1
2.8%
ValueCountFrequency (%)
368315 1
2.8%
331015 1
2.8%
320469 1
2.8%
301112 1
2.8%
291799 1
2.8%
289459 1
2.8%
270036 1
2.8%
264189 1
2.8%
246873 1
2.8%
243530 1
2.8%

명세서청구건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean491009.42
Minimum90249
Maximum1651082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:33:45.462254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90249
5-th percentile121808
Q1209635.5
median459721.5
Q3683710.5
95-th percentile921907.25
Maximum1651082
Range1560833
Interquartile range (IQR)474075

Descriptive statistics

Standard deviation331541.74
Coefficient of variation (CV)0.67522482
Kurtosis2.8116645
Mean491009.42
Median Absolute Deviation (MAD)250790.5
Skewness1.2935085
Sum17676339
Variance1.0991993 × 1011
MonotonicityNot monotonic
2023-12-12T23:33:45.603935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
540514 1
 
2.8%
129494 1
 
2.8%
112031 1
 
2.8%
164534 1
 
2.8%
251494 1
 
2.8%
353389 1
 
2.8%
341606 1
 
2.8%
377679 1
 
2.8%
450434 1
 
2.8%
607547 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
90249 1
2.8%
112031 1
2.8%
125067 1
2.8%
129494 1
2.8%
145235 1
2.8%
162240 1
2.8%
164534 1
2.8%
181917 1
2.8%
207522 1
2.8%
210340 1
2.8%
ValueCountFrequency (%)
1651082 1
2.8%
1105301 1
2.8%
860776 1
2.8%
824785 1
2.8%
808187 1
2.8%
784651 1
2.8%
782444 1
2.8%
727392 1
2.8%
723534 1
2.8%
670436 1
2.8%

입원일수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3836545.6
Minimum382682
Maximum22252614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:33:45.747238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum382682
5-th percentile484920.25
Q11057809
median2218455.5
Q35945821.5
95-th percentile9624586.5
Maximum22252614
Range21869932
Interquartile range (IQR)4888012.5

Descriptive statistics

Standard deviation4262198.8
Coefficient of variation (CV)1.110947
Kurtosis9.5203479
Mean3836545.6
Median Absolute Deviation (MAD)1710027.5
Skewness2.6730757
Sum1.3811564 × 108
Variance1.8166339 × 1013
MonotonicityNot monotonic
2023-12-12T23:33:45.867392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2196852 1
 
2.8%
419254 1
 
2.8%
509746 1
 
2.8%
696149 1
 
2.8%
1088015 1
 
2.8%
1640659 1
 
2.8%
1640569 1
 
2.8%
1832672 1
 
2.8%
2374418 1
 
2.8%
3429909 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
382682 1
2.8%
419254 1
2.8%
506809 1
2.8%
507110 1
2.8%
509746 1
2.8%
696149 1
2.8%
715467 1
2.8%
1006038 1
2.8%
1040880 1
2.8%
1063452 1
2.8%
ValueCountFrequency (%)
22252614 1
2.8%
13160469 1
2.8%
8445959 1
2.8%
6364767 1
2.8%
6268785 1
2.8%
6119942 1
2.8%
6095272 1
2.8%
6057019 1
2.8%
6013983 1
2.8%
5923101 1
2.8%

요양급여비용총액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8246281 × 1011
Minimum1.2080592 × 1011
Maximum2.886534 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:33:45.989720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2080592 × 1011
5-th percentile1.4197107 × 1011
Q13.2854627 × 1011
median7.0541766 × 1011
Q31.6992007 × 1012
95-th percentile2.087441 × 1012
Maximum2.886534 × 1012
Range2.765728 × 1012
Interquartile range (IQR)1.3706544 × 1012

Descriptive statistics

Standard deviation7.498648 × 1011
Coefficient of variation (CV)0.76325006
Kurtosis-0.55903528
Mean9.8246281 × 1011
Median Absolute Deviation (MAD)4.9403668 × 1011
Skewness0.66239985
Sum3.5368661 × 1013
Variance5.6229722 × 1023
MonotonicityNot monotonic
2023-12-12T23:33:46.119155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
669185479140 1
 
2.8%
121507772990 1
 
2.8%
148792163300 1
 
2.8%
220076585260 1
 
2.8%
374312978310 1
 
2.8%
605052539030 1
 
2.8%
592760894990 1
 
2.8%
632826982450 1
 
2.8%
775361897280 1
 
2.8%
1046696085160 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
120805920590 1
2.8%
121507772990 1
2.8%
148792163300 1
2.8%
149559584250 1
2.8%
159377136430 1
2.8%
219648649800 1
2.8%
220076585260 1
2.8%
275057143370 1
2.8%
311955146840 1
2.8%
334076643390 1
2.8%
ValueCountFrequency (%)
2886533950220 1
2.8%
2295072677450 1
2.8%
2018230410850 1
2.8%
1979755610490 1
2.8%
1923608668780 1
2.8%
1901523995270 1
2.8%
1746922785220 1
2.8%
1745842341680 1
2.8%
1726196807200 1
2.8%
1690201992070 1
2.8%

보험자부담금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.183001 × 1011
Minimum1.1109726 × 1011
Maximum2.2663826 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:33:46.245820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1109726 × 1011
5-th percentile1.2042388 × 1011
Q12.6556789 × 1011
median6.271434 × 1011
Q31.4057645 × 1012
95-th percentile1.7449952 × 1012
Maximum2.2663826 × 1012
Range2.1552854 × 1012
Interquartile range (IQR)1.1401967 × 1012

Descriptive statistics

Standard deviation6.0964306 × 1011
Coefficient of variation (CV)0.7450116
Kurtosis-0.82258016
Mean8.183001 × 1011
Median Absolute Deviation (MAD)4.463171 × 1011
Skewness0.57647973
Sum2.9458804 × 1013
Variance3.7166466 × 1023
MonotonicityNot monotonic
2023-12-12T23:33:46.365990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
639389391710 1
 
2.8%
111984573750 1
 
2.8%
123236982060 1
 
2.8%
179673300160 1
 
2.8%
316435942460 1
 
2.8%
530131352490 1
 
2.8%
510775130430 1
 
2.8%
529656044350 1
 
2.8%
647186708050 1
 
2.8%
871840065300 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
111097256710 1
2.8%
111984573750 1
2.8%
123236982060 1
2.8%
137994432240 1
2.8%
146636573220 1
2.8%
179673300160 1
2.8%
181979309530 1
2.8%
220070869150 1
2.8%
251208192600 1
2.8%
270354449360 1
2.8%
ValueCountFrequency (%)
2266382642350 1
2.8%
1847135484700 1
2.8%
1710948434990 1
2.8%
1671990494140 1
2.8%
1606476625630 1
2.8%
1569856305940 1
2.8%
1464729028340 1
2.8%
1437799321720 1
2.8%
1426507489030 1
2.8%
1398850231030 1
2.8%

Interactions

2023-12-12T23:33:43.432926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.126020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.558092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.102117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.943458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.523810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.198909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.673646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.215864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.044740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.627746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.281455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.772807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.306374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.161592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.700255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.355636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.884611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.392090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.261644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.791415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.462255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:41.988177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:42.544892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:33:43.349903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:33:46.452822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군환자수명세서청구건수입원일수요양급여비용총액보험자부담금
성별1.0000.0000.2060.0000.0000.0000.000
연령군0.0001.0000.0000.8200.8960.9020.908
환자수0.2060.0001.0000.4730.0000.2740.616
명세서청구건수0.0000.8200.4731.0000.8810.8990.918
입원일수0.0000.8960.0000.8811.0000.9650.935
요양급여비용총액0.0000.9020.2740.8990.9651.0000.959
보험자부담금0.0000.9080.6160.9180.9350.9591.000
2023-12-12T23:33:46.574108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자수명세서청구건수입원일수요양급여비용총액보험자부담금성별
환자수1.0000.8380.7030.8070.8050.175
명세서청구건수0.8381.0000.9510.9750.9790.000
입원일수0.7030.9511.0000.9680.9690.000
요양급여비용총액0.8070.9750.9681.0000.9960.000
보험자부담금0.8050.9790.9690.9961.0000.000
성별0.1750.0000.0000.0000.0001.000

Missing values

2023-12-12T23:33:43.909548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:33:44.045403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

진료년도성별연령군환자수명세서청구건수입원일수요양급여비용총액보험자부담금
02022남01_0~4세2148335405142196852669185479140639389391710
12022남02_5~9세89568162240507110149559584250137994432240
22022남03_10~14세76987125067506809159377136430146636573220
32022남04_15~19세93718145235715467219648649800181979309530
42022남05_20~24세1232421819171006038275057143370220070869150
52022남06_25~29세1366582075221040880311955146840251208192600
62022남07_30~34세1356692103401063452334076643390270354449360
72022남08_35~39세1475802390501278160410440543180334161015000
82022남09_40~44세1816963087581777091585184945420480246391040
92022남10_45~49세1951493608692240059741649841360614897415860
진료년도성별연령군환자수명세서청구건수입원일수요양급여비용총액보험자부담금
262022여09_40~44세2158673776791832672632826982450529656044350
272022여10_45~49세2294594504342374418775361897280647186708050
282022여11_50~54세28945960754734299091046696085160871840065300
292022여12_55~59세301112663374415054712077220057801002686343220
302022여13_60~64세368315860776583836316902019920701398850231030
312022여14_65~69세320469782444585565017261968072001426507489030
322022여15_70~74세264189727392626878517458423416801437799321720
332022여16_75~79세236288824785844595919236086687801569856305940
342022여17_80~84세23223311053011316046922950726774501847135484700
352022여18_85세 이상24176116510822225261428865339502202266382642350