Overview

Dataset statistics

Number of variables11
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory92.9 B

Variable types

Numeric2
Categorical6
Text3

Dataset

DescriptionPRE위암_라이브러리_PRE_위암_환자_건강정보_메타정보( 제공 되어질 데이터 항목, 타입, 사이즈, 항목별건수등)를 제공
Author국립암센터
URLhttps://www.data.go.kr/data/15074140/fileData.do

Alerts

분류ID has constant value ""Constant
분류명 has constant value ""Constant
테이블ID has constant value ""Constant
테이블명 has constant value ""Constant
데이터타입 is highly overall correlated with 표시형식High correlation
표시형식 is highly overall correlated with 데이터타입High correlation
순번 has unique valuesUnique
컬럼ID has unique valuesUnique
컬럼명 has unique valuesUnique
컬럼설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:55:03.121878
Analysis finished2023-12-12 22:55:04.088175
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T07:55:04.156959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2023-12-13T07:55:04.278133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

분류ID
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
PT
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PT 45
100.0%

Length

2023-12-13T07:55:04.399690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:55:04.487048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pt 45
100.0%

분류명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
환자
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환자 45
100.0%

Length

2023-12-13T07:55:04.585228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:55:04.687054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환자 45
100.0%

테이블ID
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
PRE_GSTR_PT_HLNF
45 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PRE_GSTR_PT_HLNF 45
100.0%

Length

2023-12-13T07:55:04.783488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:55:05.183204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pre_gstr_pt_hlnf 45
100.0%

테이블명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
PRE_위암_환자_건강정보
45 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PRE_위암_환자_건강정보 45
100.0%

Length

2023-12-13T07:55:05.305321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:55:05.400253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pre_위암_환자_건강정보 45
100.0%

컬럼ID
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T07:55:05.595464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length18.6
Min length7

Characters and Unicode

Total characters837
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st rowCENTER_CD
2nd rowIRB_APRV_NO
3rd rowPT_SBST_NO
4th rowHLPT_ADM_YMD
5th rowHLPT_HLNF_SEQ
ValueCountFrequency (%)
center_cd 1
 
2.2%
hlpt_smok_strt_age 1
 
2.2%
hlpt_smok_dtrn_ycnt 1
 
2.2%
hlpt_nsmk_perd_ycnt 1
 
2.2%
hlpt_mhis_yn_clsf_cd 1
 
2.2%
hlpt_mhis_htn_yn_clsf_cd 1
 
2.2%
hlpt_mhis_dbt_yn_clsf_cd 1
 
2.2%
hlpt_mhis_tb_yn_clsf_cd 1
 
2.2%
hlpt_mhis_lvds_yn_clsf_cd 1
 
2.2%
hlpt_mhis_cncr_yn_clsf_cd 1
 
2.2%
Other values (35) 35
77.8%
2023-12-13T07:55:05.983731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 155
18.5%
T 77
9.2%
C 61
 
7.3%
H 61
 
7.3%
N 58
 
6.9%
D 58
 
6.9%
L 58
 
6.9%
S 48
 
5.7%
P 45
 
5.4%
M 31
 
3.7%
Other values (14) 185
22.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 682
81.5%
Connector Punctuation 155
 
18.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 77
11.3%
C 61
 
8.9%
H 61
 
8.9%
N 58
 
8.5%
D 58
 
8.5%
L 58
 
8.5%
S 48
 
7.0%
P 45
 
6.6%
M 31
 
4.5%
R 26
 
3.8%
Other values (13) 159
23.3%
Connector Punctuation
ValueCountFrequency (%)
_ 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 682
81.5%
Common 155
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 77
11.3%
C 61
 
8.9%
H 61
 
8.9%
N 58
 
8.5%
D 58
 
8.5%
L 58
 
8.5%
S 48
 
7.0%
P 45
 
6.6%
M 31
 
4.5%
R 26
 
3.8%
Other values (13) 159
23.3%
Common
ValueCountFrequency (%)
_ 155
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 155
18.5%
T 77
9.2%
C 61
 
7.3%
H 61
 
7.3%
N 58
 
6.9%
D 58
 
6.9%
L 58
 
6.9%
S 48
 
5.7%
P 45
 
5.4%
M 31
 
3.7%
Other values (14) 185
22.1%

컬럼명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T07:55:06.210464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length10.977778
Min length4

Characters and Unicode

Total characters494
Distinct characters80
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row센터코드
2nd rowIRB승인번호
3rd row환자대체번호
4th row건강환자입원일자
5th row건강환자건강정보순번
ValueCountFrequency (%)
센터코드 1
 
2.2%
건강환자흡연시작연령 1
 
2.2%
건강환자흡연기간년수 1
 
2.2%
건강환자금연시작시기년수 1
 
2.2%
건강환자병력여부구분코드 1
 
2.2%
건강환자병력고혈압여부구분코드 1
 
2.2%
건강환자병력당뇨여부구분코드 1
 
2.2%
건강환자병력결핵여부구분코드 1
 
2.2%
건강환자병력간질환여부구분코드 1
 
2.2%
건강환자병력암여부구분코드 1
 
2.2%
Other values (35) 35
77.8%
2023-12-13T07:55:06.594894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
환 45
 
9.1%
자 44
 
8.9%
강 42
 
8.5%
건 42
 
8.5%
코 22
 
4.5%
드 22
 
4.5%
병 15
 
3.0%
여 15
 
3.0%
력 15
 
3.0%
부 15
 
3.0%
Other values (70) 217
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
99.4%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
환 45
 
9.2%
자 44
 
9.0%
강 42
 
8.6%
건 42
 
8.6%
코 22
 
4.5%
드 22
 
4.5%
병 15
 
3.1%
여 15
 
3.1%
력 15
 
3.1%
부 15
 
3.1%
Other values (67) 214
43.6%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
R 1
33.3%
B 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
99.4%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
환 45
 
9.2%
자 44
 
9.0%
강 42
 
8.6%
건 42
 
8.6%
코 22
 
4.5%
드 22
 
4.5%
병 15
 
3.1%
여 15
 
3.1%
력 15
 
3.1%
부 15
 
3.1%
Other values (67) 214
43.6%
Latin
ValueCountFrequency (%)
I 1
33.3%
R 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
99.4%
ASCII 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
환 45
 
9.2%
자 44
 
9.0%
강 42
 
8.6%
건 42
 
8.6%
코 22
 
4.5%
드 22
 
4.5%
병 15
 
3.1%
여 15
 
3.1%
력 15
 
3.1%
부 15
 
3.1%
Other values (67) 214
43.6%
ASCII
ValueCountFrequency (%)
I 1
33.3%
R 1
33.3%
B 1
33.3%

데이터타입
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
VARCHAR(20)
19 
VARCHAR(100)
9 
CLOB
8 
VARCHAR(8)
2 
VARCHAR(200)
2 
Other values (5)
5 

Length

Max length12
Median length11
Mean length9.8
Min length4

Unique

Unique5 ?
Unique (%)11.1%

Sample

1st rowVARCHAR(20)
2nd rowVARCHAR(50)
3rd rowVARCHAR(10)
4th rowVARCHAR(8)
5th rowNUMBER(3)

Common Values

ValueCountFrequency (%)
VARCHAR(20) 19
42.2%
VARCHAR(100) 9
20.0%
CLOB 8
17.8%
VARCHAR(8) 2
 
4.4%
VARCHAR(200) 2
 
4.4%
VARCHAR(50) 1
 
2.2%
VARCHAR(10) 1
 
2.2%
NUMBER(3) 1
 
2.2%
NUMBER(4) 1
 
2.2%
DATETIME 1
 
2.2%

Length

2023-12-13T07:55:06.716356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:55:06.831386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
varchar(20 19
42.2%
varchar(100 9
20.0%
clob 8
17.8%
varchar(8 2
 
4.4%
varchar(200 2
 
4.4%
varchar(50 1
 
2.2%
varchar(10 1
 
2.2%
number(3 1
 
2.2%
number(4 1
 
2.2%
datetime 1
 
2.2%

컬럼설명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T07:55:07.101257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length41
Mean length32.622222
Min length12

Characters and Unicode

Total characters1468
Distinct characters163
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row센터코드 (5자리 : XXXXX) / 00030 : 국립암센터 예) 00030
2nd row센터별 기준에 따라 생성
3rd row개인고유번호(10자리) / 센터별 별도부여 예) RN12345678
4th row첫번째 간호 정보 작성시 입원한 일자 / YYYYMMDD 예)20200101
5th row건강환자입원일자별 순번
ValueCountFrequency (%)
98
22.0%
환자의 38
 
8.5%
무응답 18
 
4.0%
y 15
 
3.4%
여 15
 
3.4%
n 15
 
3.4%
부 15
 
3.4%
m 15
 
3.4%
예 14
 
3.1%
기타 9
 
2.0%
Other values (129) 193
43.4%
2023-12-13T07:55:07.512142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
400
27.2%
: 56
 
3.8%
자 47
 
3.2%
/ 45
 
3.1%
환 44
 
3.0%
의 38
 
2.6%
0 36
 
2.5%
부 32
 
2.2%
여 31
 
2.1%
, 30
 
2.0%
Other values (153) 709
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 654
44.6%
Space Separator 400
27.2%
Other Punctuation 132
 
9.0%
Decimal Number 104
 
7.1%
Lowercase Letter 80
 
5.4%
Uppercase Letter 75
 
5.1%
Close Punctuation 19
 
1.3%
Open Punctuation 3
 
0.2%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 47
 
7.2%
환 44
 
6.7%
의 38
 
5.8%
부 32
 
4.9%
여 31
 
4.7%
무 19
 
2.9%
답 18
 
2.8%
응 18
 
2.8%
기 17
 
2.6%
주 16
 
2.4%
Other values (110) 374
57.2%
Lowercase Letter
ValueCountFrequency (%)
e 26
32.5%
t 19
23.8%
r 10
 
12.5%
x 8
 
10.0%
f 8
 
10.0%
m 2
 
2.5%
c 1
 
1.2%
u 1
 
1.2%
n 1
 
1.2%
i 1
 
1.2%
Other values (3) 3
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
Y 23
30.7%
M 19
25.3%
N 16
21.3%
D 5
 
6.7%
X 5
 
6.7%
E 1
 
1.3%
F 1
 
1.3%
A 1
 
1.3%
U 1
 
1.3%
T 1
 
1.3%
Other values (2) 2
 
2.7%
Decimal Number
ValueCountFrequency (%)
0 36
34.6%
9 15
14.4%
1 12
 
11.5%
2 11
 
10.6%
5 9
 
8.7%
3 6
 
5.8%
8 5
 
4.8%
4 4
 
3.8%
7 3
 
2.9%
6 3
 
2.9%
Other Punctuation
ValueCountFrequency (%)
: 56
42.4%
/ 45
34.1%
, 30
22.7%
. 1
 
0.8%
Space Separator
ValueCountFrequency (%)
400
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 659
44.9%
Hangul 654
44.6%
Latin 155
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 47
 
7.2%
환 44
 
6.7%
의 38
 
5.8%
부 32
 
4.9%
여 31
 
4.7%
무 19
 
2.9%
답 18
 
2.8%
응 18
 
2.8%
기 17
 
2.6%
주 16
 
2.4%
Other values (110) 374
57.2%
Latin
ValueCountFrequency (%)
e 26
16.8%
Y 23
14.8%
t 19
12.3%
M 19
12.3%
N 16
10.3%
r 10
 
6.5%
x 8
 
5.2%
f 8
 
5.2%
D 5
 
3.2%
X 5
 
3.2%
Other values (15) 16
10.3%
Common
ValueCountFrequency (%)
400
60.7%
: 56
 
8.5%
/ 45
 
6.8%
0 36
 
5.5%
, 30
 
4.6%
) 19
 
2.9%
9 15
 
2.3%
1 12
 
1.8%
2 11
 
1.7%
5 9
 
1.4%
Other values (8) 26
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 814
55.4%
Hangul 654
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
400
49.1%
: 56
 
6.9%
/ 45
 
5.5%
0 36
 
4.4%
, 30
 
3.7%
e 26
 
3.2%
Y 23
 
2.8%
) 19
 
2.3%
t 19
 
2.3%
M 19
 
2.3%
Other values (33) 141
 
17.3%
Hangul
ValueCountFrequency (%)
자 47
 
7.2%
환 44
 
6.7%
의 38
 
5.8%
부 32
 
4.9%
여 31
 
4.7%
무 19
 
2.9%
답 18
 
2.8%
응 18
 
2.8%
기 17
 
2.6%
주 16
 
2.4%
Other values (110) 374
57.2%

컬럼데이터수
Real number (ℝ)

Distinct20
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4229.6222
Minimum7
Maximum5632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T07:55:07.631626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile303.8
Q13025
median5632
Q35632
95-th percentile5632
Maximum5632
Range5625
Interquartile range (IQR)2607

Descriptive statistics

Standard deviation1867.0768
Coefficient of variation (CV)0.44142873
Kurtosis-0.39242211
Mean4229.6222
Median Absolute Deviation (MAD)0
Skewness-0.96539089
Sum190333
Variance3485975.7
MonotonicityNot monotonic
2023-12-13T07:55:07.739283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
5632 23
51.1%
5377 2
 
4.4%
3087 2
 
4.4%
5588 2
 
4.4%
3105 1
 
2.2%
3236 1
 
2.2%
2198 1
 
2.2%
179 1
 
2.2%
651 1
 
2.2%
1427 1
 
2.2%
Other values (10) 10
22.2%
ValueCountFrequency (%)
7 1
2.2%
179 1
2.2%
217 1
2.2%
651 1
2.2%
1058 1
2.2%
1427 1
2.2%
2198 1
2.2%
2532 1
2.2%
2904 1
2.2%
2990 1
2.2%
ValueCountFrequency (%)
5632 23
51.1%
5588 2
 
4.4%
5377 2
 
4.4%
3236 1
 
2.2%
3124 1
 
2.2%
3105 1
 
2.2%
3087 2
 
4.4%
3031 1
 
2.2%
3025 1
 
2.2%
3009 1
 
2.2%

표시형식
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
Y 여 | N 부 | M 무응답
15 
텍스트
12 
Free 텍스트
8 
YYYYMMDD
2 
숫자
2 
Other values (6)
6 

Length

Max length81
Median length71
Mean length13.688889
Min length2

Unique

Unique6 ?
Unique (%)13.3%

Sample

1st row문자(5) : XXXXX
2nd row텍스트
3rd row문자(10) : XXXXXXXXXX
4th rowYYYYMMDD
5th row숫자

Common Values

ValueCountFrequency (%)
Y 여 | N 부 | M 무응답 15
33.3%
텍스트 12
26.7%
Free 텍스트 8
17.8%
YYYYMMDD 2
 
4.4%
숫자 2
 
4.4%
문자(5) : XXXXX 1
 
2.2%
문자(10) : XXXXXXXXXX 1
 
2.2%
01 한글해독불가 | 02 초졸이하 | 03 중졸 | 04 고졸 | 05 대졸 | 06 대학원이상 | 98 무응답 | 99 기타 1
 
2.2%
01 회사원 | 02 전문직 | 03 주부 | 04 학생 | 05 군인 | 06 무직 | 07 자유업 | 08 교사 | 98 무응답 | 99 기타 1
 
2.2%
01 맥주 | 02 소주 | 03 양주 | 98 무응답 | 99 기타 1
 
2.2%

Length

2023-12-13T07:55:07.860636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
52
23.0%
텍스트 20
 
8.8%
무응답 18
 
8.0%
y 15
 
6.6%
m 15
 
6.6%
여 15
 
6.6%
부 15
 
6.6%
n 15
 
6.6%
free 8
 
3.5%
99 3
 
1.3%
Other values (35) 50
22.1%

Interactions

2023-12-13T07:55:03.664917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:55:03.516215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:55:03.738205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:55:03.596110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:55:07.956994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번컬럼ID컬럼명데이터타입컬럼설명컬럼데이터수표시형식
순번1.0001.0001.0000.6101.0000.5020.570
컬럼ID1.0001.0001.0001.0001.0001.0001.000
컬럼명1.0001.0001.0001.0001.0001.0001.000
데이터타입0.6101.0001.0001.0001.0000.4610.933
컬럼설명1.0001.0001.0001.0001.0001.0001.000
컬럼데이터수0.5021.0001.0000.4611.0001.0000.384
표시형식0.5701.0001.0000.9331.0000.3841.000
2023-12-13T07:55:08.059109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표시형식데이터타입
표시형식1.0000.743
데이터타입0.7431.000
2023-12-13T07:55:08.137450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번컬럼데이터수데이터타입표시형식
순번1.000-0.0350.2290.283
컬럼데이터수-0.0351.0000.2340.174
데이터타입0.2290.2341.0000.743
표시형식0.2830.1740.7431.000

Missing values

2023-12-13T07:55:03.843280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:55:04.034667image/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

순번분류ID분류명테이블ID테이블명컬럼ID컬럼명데이터타입컬럼설명컬럼데이터수표시형식
01PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보CENTER_CD센터코드VARCHAR(20)센터코드 (5자리 : XXXXX) / 00030 : 국립암센터 예) 000305632문자(5) : XXXXX
12PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보IRB_APRV_NOIRB승인번호VARCHAR(50)센터별 기준에 따라 생성5632텍스트
23PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보PT_SBST_NO환자대체번호VARCHAR(10)개인고유번호(10자리) / 센터별 별도부여 예) RN123456785632문자(10) : XXXXXXXXXX
34PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_ADM_YMD건강환자입원일자VARCHAR(8)첫번째 간호 정보 작성시 입원한 일자 / YYYYMMDD 예)202001015632YYYYMMDD
45PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_HLNF_SEQ건강환자건강정보순번NUMBER(3)건강환자입원일자별 순번5632숫자
56PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_RCRD_YMD건강환자기록일자VARCHAR(8)기타건강정보 기록일자 / YYYYMMDD 예)202001015632YYYYMMDD
67PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_IADM_AGE건강환자입원시연령NUMBER(4)첫번째 수술 당시 환자 나이 / 정수 예) 455632숫자
78PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_EDU_DGRE_CD건강환자교육정도코드VARCHAR(20)환자의 교육정도코드 / 01 한글해독불가 02 초졸이하 03 중졸 04 고졸 05 대졸 06 대학원이상 98 무응답 99 기타558801 한글해독불가 | 02 초졸이하 | 03 중졸 | 04 고졸 | 05 대졸 | 06 대학원이상 | 98 무응답 | 99 기타
89PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_EDU_DGRE_NM건강환자교육정도명VARCHAR(100)환자의 교육정도코드명 / 예) 대졸5588텍스트
910PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_EDU_DGRE_CD_ETC_CONT건강환자교육정도코드기타내용CLOB환자교육정도코드가 기타 : 99 일 경우 환자의 기타 교육정도 상세내용 / free text7Free 텍스트
순번분류ID분류명테이블ID테이블명컬럼ID컬럼명데이터타입컬럼설명컬럼데이터수표시형식
3536PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_CADS_YN_CLSF_CD건강환자병력심장질환여부구분코드VARCHAR(20)환자의 심장질환여부 / Y : 여, N : 부, M : 무응답5632Y 여 | N 부 | M 무응답
3637PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_ETC_YN_CLSF_CD건강환자병력기타여부구분코드VARCHAR(20)환자의 기타병력여부 / Y : 여, N : 부, M : 무응답5632Y 여 | N 부 | M 무응답
3738PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_HTN_CONT건강환자병력고혈압내용CLOB환자의 고혈압 상세내용 / free text1427Free 텍스트
3839PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_DBT_CONT건강환자병력당뇨내용CLOB환자의 당뇨 상세내용 / free text651Free 텍스트
3940PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_CADS_CONT건강환자병력심장질환내용CLOB환자의 심장질환 상세내용 / free text179Free 텍스트
4041PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MHIS_ETC_CONT건강환자병력기타내용CLOB환자의 기타병력 상세내용 / free text2198Free 텍스트
4142PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MAIN_SYM_YN_CLSF_CD건강환자주증상여부구분코드VARCHAR(20)환자의 입원 시 주증상여부 / Y : 여, N : 부, M : 무응답5632Y 여 | N 부 | M 무응답
4243PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_MAIN_SYM_CONT건강환자주증상내용CLOB환자의 입원 시 주증상 상세내용 / free text3236Free 텍스트
4344PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보HLPT_OHAD_HSTR_YN_CLSF_CD건강환자타병원진단후전원여부구분코드VARCHAR(20)환자의 타병원 진단 후 전원여부 / Y : 여, N : 부, M : 무응답5632Y 여 | N 부 | M 무응답
4445PT환자PRE_GSTR_PT_HLNFPRE_위암_환자_건강정보CRTN_DT생성일시DATETIME생성일시 DEFAULT current_timestamp()5632YYYY-MM-DD HH:MI:SS