Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory43.3 B

Variable types

Categorical3
Numeric2

Dataset

Description한국보훈복지의료공단 광주보훈병원에서 개방하는 연령대별 20대 상병 데이터로 연령대,순위,상병코드.상병명,건수 순으로 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15067147/fileData.do

Alerts

상병코드 is highly overall correlated with 상병명High correlation
상병명 is highly overall correlated with 상병코드High correlation
순위 is highly overall correlated with 건수High correlation
건수 is highly overall correlated with 순위High correlation

Reproduction

Analysis started2023-12-12 19:58:18.549667
Analysis finished2023-12-12 19:58:19.357866
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연령대
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
59세 이하
20 
60대
20 
70대
20 
80대
20 
90세 이상
20 

Length

Max length6
Median length3
Mean length4.2
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row59세 이하
2nd row59세 이하
3rd row59세 이하
4th row59세 이하
5th row59세 이하

Common Values

ValueCountFrequency (%)
59세 이하 20
20.0%
60대 20
20.0%
70대 20
20.0%
80대 20
20.0%
90세 이상 20
20.0%

Length

2023-12-13T04:58:19.431047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:58:19.532426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
59세 20
14.3%
이하 20
14.3%
60대 20
14.3%
70대 20
14.3%
80대 20
14.3%
90세 20
14.3%
이상 20
14.3%

순위
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.5
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T04:58:19.617782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q15.75
median10.5
Q315.25
95-th percentile19.05
Maximum20
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.7953308
Coefficient of variation (CV)0.55193626
Kurtosis-1.2060745
Mean10.5
Median Absolute Deviation (MAD)5
Skewness0
Sum1050
Variance33.585859
MonotonicityNot monotonic
2023-12-13T04:58:19.744857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 5
 
5.0%
12 5
 
5.0%
20 5
 
5.0%
19 5
 
5.0%
18 5
 
5.0%
17 5
 
5.0%
16 5
 
5.0%
15 5
 
5.0%
14 5
 
5.0%
13 5
 
5.0%
Other values (10) 50
50.0%
ValueCountFrequency (%)
1 5
5.0%
2 5
5.0%
3 5
5.0%
4 5
5.0%
5 5
5.0%
6 5
5.0%
7 5
5.0%
8 5
5.0%
9 5
5.0%
10 5
5.0%
ValueCountFrequency (%)
20 5
5.0%
19 5
5.0%
18 5
5.0%
17 5
5.0%
16 5
5.0%
15 5
5.0%
14 5
5.0%
13 5
5.0%
12 5
5.0%
11 5
5.0%

상병코드
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M48
 
5
E11
 
5
I10
 
5
I20
 
4
K21
 
4
Other values (39)
77 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st rowE30
2nd rowZ26
3rd rowE34
4th rowR52
5th rowJ00

Common Values

ValueCountFrequency (%)
M48 5
 
5.0%
E11 5
 
5.0%
I10 5
 
5.0%
I20 4
 
4.0%
K21 4
 
4.0%
M17 4
 
4.0%
K05 4
 
4.0%
I63 4
 
4.0%
N40 4
 
4.0%
N18 3
 
3.0%
Other values (34) 58
58.0%

Length

2023-12-13T04:58:19.912205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
m48 5
 
5.0%
i10 5
 
5.0%
e11 5
 
5.0%
i20 4
 
4.0%
k21 4
 
4.0%
m17 4
 
4.0%
k05 4
 
4.0%
i63 4
 
4.0%
n40 4
 
4.0%
r41 3
 
3.0%
Other values (34) 58
58.0%

상병명
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
기타 척추병증
 
5
인슐린-비의존 당뇨병
 
5
본태성(원발성) 고혈압
 
5
협심증
 
4
위-식도역류병
 
4
Other values (39)
77 

Length

Max length34
Median length20
Mean length11.66
Min length2

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st row달리 분류되지 않은 사춘기의 장애
2nd row기타 단일 감염성 질환에 대한 예방접종의 필요
3rd row기타 내분비장애
4th row달리 분류되지 않은 통증
5th row급성 코인두염 [감기]

Common Values

ValueCountFrequency (%)
기타 척추병증 5
 
5.0%
인슐린-비의존 당뇨병 5
 
5.0%
본태성(원발성) 고혈압 5
 
5.0%
협심증 4
 
4.0%
위-식도역류병 4
 
4.0%
윤충증 4
 
4.0%
치은염(잇몸염)및 치주 질환 4
 
4.0%
뇌경색증 4
 
4.0%
전립선증식증 4
 
4.0%
만성 콩팥(신장)기능상실 3
 
3.0%
Other values (34) 58
58.0%

Length

2023-12-13T04:58:20.056500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 29
 
9.8%
기타 25
 
8.4%
질환 8
 
2.7%
징후 6
 
2.0%
만성 6
 
2.0%
증상 6
 
2.0%
당뇨병 5
 
1.7%
척추병증 5
 
1.7%
인슐린-비의존 5
 
1.7%
고혈압 5
 
1.7%
Other values (90) 196
66.2%

건수
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2233.64
Minimum200
Maximum16831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T04:58:20.183951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile263.95
Q1626.75
median988.5
Q32449
95-th percentile9543.75
Maximum16831
Range16631
Interquartile range (IQR)1822.25

Descriptive statistics

Standard deviation3101.5805
Coefficient of variation (CV)1.3885767
Kurtosis9.542134
Mean2233.64
Median Absolute Deviation (MAD)579
Skewness2.9586771
Sum223364
Variance9619801.5
MonotonicityNot monotonic
2023-12-13T04:58:20.329006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1308 2
 
2.0%
16491 1
 
1.0%
2446 1
 
1.0%
832 1
 
1.0%
959 1
 
1.0%
967 1
 
1.0%
1010 1
 
1.0%
1032 1
 
1.0%
1052 1
 
1.0%
1285 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
200 1
1.0%
209 1
1.0%
214 1
1.0%
254 1
1.0%
263 1
1.0%
264 1
1.0%
276 1
1.0%
286 1
1.0%
291 1
1.0%
322 1
1.0%
ValueCountFrequency (%)
16831 1
1.0%
16491 1
1.0%
10910 1
1.0%
10906 1
1.0%
10470 1
1.0%
9495 1
1.0%
8994 1
1.0%
7483 1
1.0%
5679 1
1.0%
4733 1
1.0%

Interactions

2023-12-13T04:58:18.991956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:58:18.791182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:58:19.095968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:58:18.886092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:58:20.423567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대순위상병코드상병명건수
연령대1.0000.0000.0000.0000.528
순위0.0001.0000.7760.7760.465
상병코드0.0000.7761.0001.0000.000
상병명0.0000.7761.0001.0000.000
건수0.5280.4650.0000.0001.000
2023-12-13T04:58:20.520495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대상병코드상병명
연령대1.0000.0000.000
상병코드0.0001.0001.000
상병명0.0001.0001.000
2023-12-13T04:58:20.625396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위건수연령대상병코드상병명
순위1.000-0.5650.0000.3060.306
건수-0.5651.0000.3540.0000.000
연령대0.0000.3541.0000.0000.000
상병코드0.3060.0000.0001.0001.000
상병명0.3060.0000.0001.0001.000

Missing values

2023-12-13T04:58:19.220216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:58:19.318348image/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

연령대순위상병코드상병명건수
059세 이하1E30달리 분류되지 않은 사춘기의 장애16491
159세 이하2Z26기타 단일 감염성 질환에 대한 예방접종의 필요5679
259세 이하3E34기타 내분비장애2132
359세 이하4R52달리 분류되지 않은 통증2023
459세 이하5J00급성 코인두염 [감기]1657
559세 이하6I10본태성(원발성) 고혈압1308
659세 이하7E11인슐린-비의존 당뇨병1127
759세 이하8Z49투석을 포함한 치료를 위하여 보건서비스와 접하고 있는 사람1070
859세 이하9M51기타 추간판장애960
959세 이하10Z11감염성 및 기생충성 질환에 대한 특수선별검사935
연령대순위상병코드상병명건수
9090세 이상11C61전립선의 악성 신생물322
9190세 이상12R63음식 및 수액섭취에 관계된 증상 및 징후291
9290세 이상13N18만성 콩팥(신장)기능상실286
9390세 이상14I48심방세동 및 조동276
9490세 이상15R41인지기능 및 자각에 관한 기타 증상 및 징후264
9590세 이상16F03상세불명의 치매263
9690세 이상17F51비기질적 수면 장애254
9790세 이상18R42현기 및 어지러움214
9890세 이상19D75혈액 및 조혈기관의 기타 질환209
9990세 이상20K21위-식도역류병200