Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory64.7 B

Variable types

Categorical2
Text1
Numeric4

Dataset

Description건강보험 입원환자 통계 / 진료일자 기준(심사분은 각 진료년+4개월) (예) 진료년월: 2020.1월~12월, 심사년월: 2020.1월~2021.4월 / 보험자: 건강보험 / 입원환자(입원명세서) 중 일반, 소아, 신생아 중환자실 입원료 대상(중환자실 전담의 및 격리관리료 포함X)
URLhttps://www.data.go.kr/data/15052314/fileData.do

Alerts

진료년도 has constant value ""Constant
환자수 is highly overall correlated with 명세서청구건수 and 2 other fieldsHigh correlation
명세서청구건수 is highly overall correlated with 환자수 and 2 other fieldsHigh correlation
총사용량(중환자실입원일수) is highly overall correlated with 환자수 and 2 other fieldsHigh correlation
진료행위청구금액 is highly overall correlated with 환자수 and 2 other fieldsHigh correlation
환자수 has unique valuesUnique
명세서청구건수 has unique valuesUnique
총사용량(중환자실입원일수) has unique valuesUnique
진료행위청구금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:31:31.570438
Analysis finished2023-12-12 08:31:33.666105
Duration2.1 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

2023-12-12T17:31:33.754720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:31:33.877440image/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

2023-12-12T17:31:33.998615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:31:34.105174image/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
2023-12-12T17:31:34.277820image/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%
2023-12-12T17:31:34.703995image/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%
Mean8435.7222
Minimum340
Maximum24624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T17:31:34.872859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum340
5-th percentile451.5
Q11367
median6297.5
Q314602.5
95-th percentile20627.5
Maximum24624
Range24284
Interquartile range (IQR)13235.5

Descriptive statistics

Standard deviation7763.404
Coefficient of variation (CV)0.92030104
Kurtosis-1.0577639
Mean8435.7222
Median Absolute Deviation (MAD)5285.5
Skewness0.60694857
Sum303686
Variance60270441
MonotonicityNot monotonic
2023-12-12T17:31:35.048029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
10706 1
 
2.8%
340 1
 
2.8%
700 1
 
2.8%
919 1
 
2.8%
1178 1
 
2.8%
1430 1
 
2.8%
1864 1
 
2.8%
2770 1
 
2.8%
3876 1
 
2.8%
5645 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
340 1
2.8%
438 1
2.8%
456 1
2.8%
522 1
2.8%
700 1
2.8%
738 1
2.8%
919 1
2.8%
1105 1
2.8%
1178 1
2.8%
1430 1
2.8%
ValueCountFrequency (%)
24624 1
2.8%
20860 1
2.8%
20550 1
2.8%
20468 1
2.8%
20275 1
2.8%
20105 1
2.8%
19398 1
2.8%
15870 1
2.8%
14745 1
2.8%
14555 1
2.8%

명세서청구건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10132.694
Minimum386
Maximum28731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T17:31:35.211960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum386
5-th percentile553.75
Q11536.75
median7073.5
Q318089
95-th percentile24253.25
Maximum28731
Range28345
Interquartile range (IQR)16552.25

Descriptive statistics

Standard deviation9299.2231
Coefficient of variation (CV)0.91774436
Kurtosis-1.2569477
Mean10132.694
Median Absolute Deviation (MAD)6250
Skewness0.51891575
Sum364777
Variance86475551
MonotonicityNot monotonic
2023-12-12T17:31:35.386751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
19399 1
 
2.8%
386 1
 
2.8%
794 1
 
2.8%
1041 1
 
2.8%
1344 1
 
2.8%
1601 1
 
2.8%
2096 1
 
2.8%
3100 1
 
2.8%
4390 1
 
2.8%
6349 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
386 1
2.8%
532 1
2.8%
561 1
2.8%
625 1
2.8%
794 1
2.8%
853 1
2.8%
1041 1
2.8%
1243 1
2.8%
1344 1
2.8%
1601 1
2.8%
ValueCountFrequency (%)
28731 1
2.8%
24614 1
2.8%
24133 1
2.8%
24121 1
2.8%
23798 1
2.8%
23413 1
2.8%
22862 1
2.8%
19399 1
2.8%
18704 1
2.8%
17884 1
2.8%

총사용량(중환자실입원일수)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71228.181
Minimum1962
Maximum363835.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T17:31:35.529824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1962
5-th percentile3394.375
Q17648.25
median33792.75
Q3117126.38
95-th percentile216962.12
Maximum363835.5
Range361873.5
Interquartile range (IQR)109478.12

Descriptive statistics

Standard deviation86548.373
Coefficient of variation (CV)1.2150861
Kurtosis3.3225432
Mean71228.181
Median Absolute Deviation (MAD)29844.75
Skewness1.7587725
Sum2564214.5
Variance7.4906208 × 109
MonotonicityNot monotonic
2023-12-12T17:31:35.687011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
363835.5 1
 
2.8%
1962.0 1
 
2.8%
3464.5 1
 
2.8%
4967.0 1
 
2.8%
6587.0 1
 
2.8%
8002.0 1
 
2.8%
9095.0 1
 
2.8%
13640.0 1
 
2.8%
22148.0 1
 
2.8%
30272.0 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1962.0 1
2.8%
3184.0 1
2.8%
3464.5 1
2.8%
3881.0 1
2.8%
4015.0 1
2.8%
4967.0 1
2.8%
5297.0 1
2.8%
6076.5 1
2.8%
6587.0 1
2.8%
8002.0 1
2.8%
ValueCountFrequency (%)
363835.5 1
2.8%
303028.0 1
2.8%
188273.5 1
2.8%
165774.0 1
2.8%
159813.5 1
2.8%
151334.5 1
2.8%
136422.5 1
2.8%
135993.5 1
2.8%
128017.5 1
2.8%
113496.0 1
2.8%

진료행위청구금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2834836 × 1010
Minimum8.5814239 × 108
Maximum1.2007071 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T17:31:35.853193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.5814239 × 108
5-th percentile1.3530881 × 109
Q12.8223219 × 109
median1.1682346 × 1010
Q33.7622723 × 1010
95-th percentile6.3062881 × 1010
Maximum1.2007071 × 1011
Range1.1921256 × 1011
Interquartile range (IQR)3.4800401 × 1010

Descriptive statistics

Standard deviation2.7501174 × 1010
Coefficient of variation (CV)1.2043517
Kurtosis4.4354101
Mean2.2834836 × 1010
Median Absolute Deviation (MAD)9.9883435 × 109
Skewness1.95031
Sum8.220541 × 1011
Variance7.5631455 × 1020
MonotonicityNot monotonic
2023-12-12T17:31:36.049124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
120070706760 1
 
2.8%
858142390 1
 
2.8%
1343910625 1
 
2.8%
1857137690 1
 
2.8%
2382292200 1
 
2.8%
2968998450 1
 
2.8%
3275444610 1
 
2.8%
4844004440 1
 
2.8%
7897648290 1
 
2.8%
10532172140 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
858142390 1
2.8%
1343910625 1
2.8%
1356147290 1
2.8%
1685953450 1
2.8%
1702050770 1
2.8%
1857137690 1
2.8%
2055042080 1
2.8%
2255489105 1
2.8%
2382292200 1
2.8%
2968998450 1
2.8%
ValueCountFrequency (%)
120070706760 1
2.8%
100139476900 1
2.8%
50704015600 1
2.8%
49485486435 1
2.8%
47599886280 1
2.8%
45197640175 1
2.8%
43942583865 1
2.8%
43396920995 1
2.8%
39240294050 1
2.8%
37083532190 1
2.8%

Interactions

2023-12-12T17:31:32.948663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:31.772879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.120284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.553185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:33.052594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:31.870328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.226718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.645135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:33.167294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:31.949520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.328184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.746438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:33.296322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.037963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.431680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:31:32.841091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:31:36.172795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군환자수명세서청구건수총사용량(중환자실입원일수)진료행위청구금액
성별1.0000.0000.0000.0000.0000.000
연령군0.0001.0000.5880.5290.6130.501
환자수0.0000.5881.0000.9800.8800.861
명세서청구건수0.0000.5290.9801.0000.8890.816
총사용량(중환자실입원일수)0.0000.6130.8800.8891.0000.952
진료행위청구금액0.0000.5010.8610.8160.9521.000
2023-12-12T17:31:36.312261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자수명세서청구건수총사용량(중환자실입원일수)진료행위청구금액성별
환자수1.0000.9900.9360.9360.000
명세서청구건수0.9901.0000.9690.9700.000
총사용량(중환자실입원일수)0.9360.9691.0000.9980.000
진료행위청구금액0.9360.9700.9981.0000.000
성별0.0000.0000.0000.0001.000

Missing values

2023-12-12T17:31:33.450400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:31:33.605907image/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

진료년도성별연령군환자수명세서청구건수총사용량(중환자실입원일수)진료행위청구금액
02022남01_0~4세1070619399363835.5120070706760
12022남02_5~9세4385323184.01356147290
22022남03_10~14세5226253881.01685953450
32022남04_15~19세7388535297.02055042080
42022남05_20~24세110512436076.52255489105
52022남06_25~29세156117408923.03213693900
62022남07_30~34세1968220011127.54038161415
72022남08_35~39세2896326516435.55866228995
82022남09_40~44세4857550926584.09271829100
92022남10_45~49세7074796038600.513117057895
진료년도성별연령군환자수명세서청구건수총사용량(중환자실입원일수)진료행위청구금액
262022여09_40~44세2770310013640.04844004440
272022여10_45~49세3876439022148.07897648290
282022여11_50~54세5645634930272.010532172140
292022여12_55~59세6950779837313.512832518990
302022여13_60~64세100501134555598.019250981860
312022여14_65~69세114301307066872.522847738100
322022여15_70~74세130521505282630.527412514535
332022여16_75~79세1587018704112313.034979685865
342022여17_80~84세2027523798151334.543942583865
352022여18_85세 이상2462428731188273.547599886280