Overview

Dataset statistics

Number of variables9
Number of observations2639
Missing cells33
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory193.4 KiB
Average record size in memory75.1 B

Variable types

Numeric3
Text3
Categorical3

Dataset

Description국립암센터에서 2022년도 10월7일까지 국가암정보센터의 메뉴정보 100대암정보(cancer_data)암종 및 세부메뉴정보
Author국립암센터
URLhttps://www.data.go.kr/data/15049622/fileData.do

Alerts

2차메뉴순번(SORT_CHAR) is highly overall correlated with 첨부파일명(FILE_NAME)High correlation
첨부파일명(FILE_NAME) is highly overall correlated with 상위메뉴아이디(CANCER_SEQ) and 4 other fieldsHigh correlation
사용여부(USER_GUBUN) is highly overall correlated with 1차메뉴순번(UC_ID) and 1 other fieldsHigh correlation
상위메뉴아이디(CANCER_SEQ) is highly overall correlated with 메뉴아이디(MENU_SEQ) and 1 other fieldsHigh correlation
메뉴아이디(MENU_SEQ) is highly overall correlated with 상위메뉴아이디(CANCER_SEQ) and 1 other fieldsHigh correlation
1차메뉴순번(UC_ID) is highly overall correlated with 사용여부(USER_GUBUN) and 1 other fieldsHigh correlation
사용여부(USER_GUBUN) is highly imbalanced (69.6%)Imbalance
첨부파일명(FILE_NAME) is highly imbalanced (99.5%)Imbalance
상위메뉴아이디(CANCER_SEQ) has 28 (1.1%) missing valuesMissing
1차메뉴순번(UC_ID) has 103 (3.9%) zerosZeros

Reproduction

Analysis started2023-12-12 03:49:35.263372
Analysis finished2023-12-12 03:49:38.008554
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상위메뉴아이디(CANCER_SEQ)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct107
Distinct (%)4.1%
Missing28
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean1361231.3
Minimum3293
Maximum8723941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2023-12-12T12:49:38.125548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3293
5-th percentile3413
Q13917
median4613
Q35261
95-th percentile8676000
Maximum8723941
Range8720648
Interquartile range (IQR)1344

Descriptive statistics

Standard deviation2935018.5
Coefficient of variation (CV)2.1561498
Kurtosis1.3723852
Mean1361231.3
Median Absolute Deviation (MAD)672
Skewness1.7986774
Sum3.5541749 × 109
Variance8.6143338 × 1012
MonotonicityNot monotonic
2023-12-12T12:49:38.331739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3317 27
 
1.0%
4877 27
 
1.0%
5213 26
 
1.0%
3917 26
 
1.0%
3869 26
 
1.0%
4757 26
 
1.0%
3797 26
 
1.0%
4925 26
 
1.0%
4997 26
 
1.0%
5045 26
 
1.0%
Other values (97) 2349
89.0%
(Missing) 28
 
1.1%
ValueCountFrequency (%)
3293 24
0.9%
3317 27
1.0%
3341 25
0.9%
3365 26
1.0%
3389 24
0.9%
3413 24
0.9%
3437 25
0.9%
3461 26
1.0%
3485 23
0.9%
3509 25
0.9%
ValueCountFrequency (%)
8723941 25
0.9%
8723940 25
0.9%
8723939 24
0.9%
8723938 23
0.9%
8687522 24
0.9%
8676000 24
0.9%
8467636 22
0.8%
7882456 24
0.9%
7880257 24
0.9%
7771357 24
0.9%

메뉴아이디(MENU_SEQ)
Real number (ℝ)

HIGH CORRELATION 

Distinct2638
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1912647.5
Minimum3293
Maximum20527147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2023-12-12T12:49:38.875668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3293
5-th percentile3431.85
Q13991.25
median4760.5
Q3308283.75
95-th percentile8687542.2
Maximum20527147
Range20523854
Interquartile range (IQR)304292.5

Descriptive statistics

Standard deviation4494746.3
Coefficient of variation (CV)2.3500128
Kurtosis8.0911306
Mean1912647.5
Median Absolute Deviation (MAD)892.5
Skewness2.8265402
Sum5.0455642 × 109
Variance2.0202744 × 1013
MonotonicityStrictly increasing
2023-12-12T12:49:39.030974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3293 1
 
< 0.1%
5258 1
 
< 0.1%
5260 1
 
< 0.1%
5261 1
 
< 0.1%
5262 1
 
< 0.1%
5263 1
 
< 0.1%
5264 1
 
< 0.1%
5265 1
 
< 0.1%
5266 1
 
< 0.1%
5267 1
 
< 0.1%
Other values (2628) 2628
99.6%
ValueCountFrequency (%)
3293 1
< 0.1%
3295 1
< 0.1%
3296 1
< 0.1%
3297 1
< 0.1%
3298 1
< 0.1%
3299 1
< 0.1%
3300 1
< 0.1%
3301 1
< 0.1%
3302 1
< 0.1%
3303 1
< 0.1%
ValueCountFrequency (%)
20527147 1
< 0.1%
20527146 1
< 0.1%
20527145 1
< 0.1%
20527144 1
< 0.1%
20527143 1
< 0.1%
20527142 1
< 0.1%
20527141 1
< 0.1%
20527140 1
< 0.1%
20527139 1
< 0.1%
20527138 1
< 0.1%

메뉴명(MENU_NAME)
Text

Distinct144
Distinct (%)5.5%
Missing1
Missing (%)< 0.1%
Memory size20.7 KiB
2023-12-12T12:49:39.232240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length4.1974981
Min length2

Characters and Unicode

Total characters11073
Distinct characters184
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)4.3%

Sample

1st row간내 담도암
2nd row암이란
3rd row발생부위
4th row정의 및 종류
5th row관련통계
ValueCountFrequency (%)
및 208
 
6.5%
치료 108
 
3.4%
요약설명 107
 
3.4%
진단방법 107
 
3.4%
치료방법 107
 
3.4%
식생활 107
 
3.4%
일상생활 107
 
3.4%
생활가이드 107
 
3.4%
진단 107
 
3.4%
위험요인 107
 
3.4%
Other values (148) 2004
63.1%
2023-12-12T12:49:39.585972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
538
 
4.9%
진 504
 
4.6%
생 436
 
3.9%
방 431
 
3.9%
료 427
 
3.9%
치 425
 
3.8%
법 406
 
3.7%
단 397
 
3.6%
활 327
 
3.0%
이 325
 
2.9%
Other values (174) 6857
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10515
95.0%
Space Separator 538
 
4.9%
Lowercase Letter 8
 
0.1%
Uppercase Letter 4
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 504
 
4.8%
생 436
 
4.1%
방 431
 
4.1%
료 427
 
4.1%
치 425
 
4.0%
법 406
 
3.9%
단 397
 
3.8%
활 327
 
3.1%
이 325
 
3.1%
상 316
 
3.0%
Other values (162) 6521
62.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
25.0%
P 1
25.0%
B 1
25.0%
V 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
t 4
50.0%
s 2
25.0%
e 2
25.0%
Space Separator
ValueCountFrequency (%)
538
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10515
95.0%
Common 546
 
4.9%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 504
 
4.8%
생 436
 
4.1%
방 431
 
4.1%
료 427
 
4.1%
치 425
 
4.0%
법 406
 
3.9%
단 397
 
3.8%
활 327
 
3.1%
이 325
 
3.1%
상 316
 
3.0%
Other values (162) 6521
62.0%
Latin
ValueCountFrequency (%)
t 4
33.3%
s 2
16.7%
e 2
16.7%
H 1
 
8.3%
P 1
 
8.3%
B 1
 
8.3%
V 1
 
8.3%
Common
ValueCountFrequency (%)
538
98.5%
( 3
 
0.5%
) 3
 
0.5%
· 1
 
0.2%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10515
95.0%
ASCII 557
 
5.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
538
96.6%
t 4
 
0.7%
( 3
 
0.5%
) 3
 
0.5%
s 2
 
0.4%
e 2
 
0.4%
- 1
 
0.2%
H 1
 
0.2%
P 1
 
0.2%
B 1
 
0.2%
Hangul
ValueCountFrequency (%)
진 504
 
4.8%
생 436
 
4.1%
방 431
 
4.1%
료 427
 
4.1%
치 425
 
4.0%
법 406
 
3.9%
단 397
 
3.8%
활 327
 
3.1%
이 325
 
3.1%
상 316
 
3.0%
Other values (162) 6521
62.0%
None
ValueCountFrequency (%)
· 1
100.0%

1차메뉴순번(UC_ID)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.9006823
Minimum0
Maximum7
Zeros103
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2023-12-12T12:49:39.722954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q35
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6918438
Coefficient of variation (CV)0.43373022
Kurtosis-0.65693987
Mean3.9006823
Median Absolute Deviation (MAD)1
Skewness-0.40222133
Sum10290
Variance2.8623355
MonotonicityNot monotonic
2023-12-12T12:49:39.856520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
6 541
20.5%
5 528
20.0%
4 502
19.0%
3 424
16.1%
2 410
15.5%
0 103
 
3.9%
1 101
 
3.8%
7 29
 
1.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 103
 
3.9%
1 101
 
3.8%
2 410
15.5%
3 424
16.1%
4 502
19.0%
5 528
20.0%
6 541
20.5%
7 29
 
1.1%
ValueCountFrequency (%)
7 29
 
1.1%
6 541
20.5%
5 528
20.0%
4 502
19.0%
3 424
16.1%
2 410
15.5%
1 101
 
3.8%
0 103
 
3.9%

2차메뉴순번(SORT_CHAR)
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
A
745 
AB
698 
AC
527 
AD
452 
AE
198 
Other values (14)
 
19

Length

Max length4
Median length2
Mean length1.718454
Min length1

Unique

Unique13 ?
Unique (%)0.5%

Sample

1st rowA
2nd rowA
3rd rowAB
4th rowAC
5th rowAD

Common Values

ValueCountFrequency (%)
A 745
28.2%
AB 698
26.4%
AC 527
20.0%
AD 452
17.1%
AE 198
 
7.5%
AF 6
 
0.2%
AJ 1
 
< 0.1%
AG 1
 
< 0.1%
AH 1
 
< 0.1%
AI 1
 
< 0.1%
Other values (9) 9
 
0.3%

Length

2023-12-12T12:49:40.056329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a 745
28.2%
ab 698
26.4%
ac 527
20.0%
ad 452
17.1%
ae 198
 
7.5%
af 6
 
0.2%
ap 1
 
< 0.1%
am 1
 
< 0.1%
ar 1
 
< 0.1%
aq 1
 
< 0.1%
Other values (9) 9
 
0.3%

사용여부(USER_GUBUN)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
S
2367 
H
271 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0011368
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
S 2367
89.7%
H 271
 
10.3%
<NA> 1
 
< 0.1%

Length

2023-12-12T12:49:40.234310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:40.387564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 2367
89.7%
h 271
 
10.3%
na 1
 
< 0.1%

첨부파일명(FILE_NAME)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
\N
2638 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0007579
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row\N
2nd row\N
3rd row\N
4th row\N
5th row\N

Common Values

ValueCountFrequency (%)
\N 2638
> 99.9%
<NA> 1
 
< 0.1%

Length

2023-12-12T12:49:40.559097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:40.691976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 2638
> 99.9%
na 1
 
< 0.1%

작성일(REG_DATE)
Text

Distinct134
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Memory size20.7 KiB
2023-12-12T12:49:41.080064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length17.698256
Min length2

Characters and Unicode

Total characters46688
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.7%

Sample

1st row2012-08-23 00:00:00
2nd row2012-08-23 15:45:53
3rd row2012-08-23 15:45:53
4th row2012-08-23 15:45:54
5th row2012-08-23 15:45:54
ValueCountFrequency (%)
2012-08-23 1861
36.7%
n 202
 
4.0%
2014-10-10 115
 
2.3%
00:00:00 96
 
1.9%
2019-08-01 50
 
1.0%
2014-11-12 46
 
0.9%
2014-10-21 46
 
0.9%
2019-08-06 25
 
0.5%
12:04:14 25
 
0.5%
09:06:11 25
 
0.5%
Other values (144) 2583
50.9%
2023-12-12T12:49:41.850598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7431
15.9%
0 7270
15.6%
1 7031
15.1%
- 4872
10.4%
: 4872
10.4%
3 2965
 
6.4%
8 2559
 
5.5%
2436
 
5.2%
5 2227
 
4.8%
6 1753
 
3.8%
Other values (5) 3272
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34104
73.0%
Other Punctuation 5074
 
10.9%
Dash Punctuation 4872
 
10.4%
Space Separator 2436
 
5.2%
Uppercase Letter 202
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7431
21.8%
0 7270
21.3%
1 7031
20.6%
3 2965
 
8.7%
8 2559
 
7.5%
5 2227
 
6.5%
6 1753
 
5.1%
4 1636
 
4.8%
9 701
 
2.1%
7 531
 
1.6%
Other Punctuation
ValueCountFrequency (%)
: 4872
96.0%
\ 202
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 4872
100.0%
Space Separator
ValueCountFrequency (%)
2436
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46486
99.6%
Latin 202
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 7431
16.0%
0 7270
15.6%
1 7031
15.1%
- 4872
10.5%
: 4872
10.5%
3 2965
 
6.4%
8 2559
 
5.5%
2436
 
5.2%
5 2227
 
4.8%
6 1753
 
3.8%
Other values (4) 3070
6.6%
Latin
ValueCountFrequency (%)
N 202
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7431
15.9%
0 7270
15.6%
1 7031
15.1%
- 4872
10.4%
: 4872
10.4%
3 2965
 
6.4%
8 2559
 
5.5%
2436
 
5.2%
5 2227
 
4.8%
6 1753
 
3.8%
Other values (5) 3272
7.0%

최종업데이트일(FINAL_PUBLISHING_DATE)
Text

Distinct338
Distinct (%)12.8%
Missing1
Missing (%)< 0.1%
Memory size20.7 KiB
2023-12-12T12:49:42.186994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length16.712282
Min length2

Characters and Unicode

Total characters44087
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)10.1%

Sample

1st row2013-02-01 00:00:00
2nd row2013-02-01 00:00:00
3rd row2017-01-23 00:00:00
4th row2017-01-23 00:00:00
5th row2022-02-07 00:00:00
ValueCountFrequency (%)
00:00:00 2037
41.4%
2013-02-01 872
17.7%
n 355
 
7.2%
2016-01-08 58
 
1.2%
2019-08-07 57
 
1.2%
2021-01-05 52
 
1.1%
2022-02-07 51
 
1.0%
2021-01-29 43
 
0.9%
2021-01-07 41
 
0.8%
2013-12-12 39
 
0.8%
Other values (375) 1316
26.7%
2023-12-12T12:49:42.638560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18471
41.9%
2 4630
 
10.5%
- 4566
 
10.4%
: 4566
 
10.4%
1 4565
 
10.4%
2283
 
5.2%
3 1384
 
3.1%
9 632
 
1.4%
4 599
 
1.4%
7 457
 
1.0%
Other values (5) 1934
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31962
72.5%
Other Punctuation 4921
 
11.2%
Dash Punctuation 4566
 
10.4%
Space Separator 2283
 
5.2%
Uppercase Letter 355
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18471
57.8%
2 4630
 
14.5%
1 4565
 
14.3%
3 1384
 
4.3%
9 632
 
2.0%
4 599
 
1.9%
7 457
 
1.4%
8 453
 
1.4%
5 389
 
1.2%
6 382
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 4566
92.8%
\ 355
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 4566
100.0%
Space Separator
ValueCountFrequency (%)
2283
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 355
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43732
99.2%
Latin 355
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18471
42.2%
2 4630
 
10.6%
- 4566
 
10.4%
: 4566
 
10.4%
1 4565
 
10.4%
2283
 
5.2%
3 1384
 
3.2%
9 632
 
1.4%
4 599
 
1.4%
7 457
 
1.0%
Other values (4) 1579
 
3.6%
Latin
ValueCountFrequency (%)
N 355
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44087
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18471
41.9%
2 4630
 
10.5%
- 4566
 
10.4%
: 4566
 
10.4%
1 4565
 
10.4%
2283
 
5.2%
3 1384
 
3.1%
9 632
 
1.4%
4 599
 
1.4%
7 457
 
1.0%
Other values (5) 1934
 
4.4%

Interactions

2023-12-12T12:49:36.892907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:35.964294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:36.483040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:37.048114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:36.092715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:36.615732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:37.207997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:36.255349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:36.747983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:49:42.756216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상위메뉴아이디(CANCER_SEQ)메뉴아이디(MENU_SEQ)1차메뉴순번(UC_ID)2차메뉴순번(SORT_CHAR)사용여부(USER_GUBUN)
상위메뉴아이디(CANCER_SEQ)1.0000.9400.0000.0000.073
메뉴아이디(MENU_SEQ)0.9401.0000.0000.3680.075
1차메뉴순번(UC_ID)0.0000.0001.0000.5230.671
2차메뉴순번(SORT_CHAR)0.0000.3680.5231.0000.407
사용여부(USER_GUBUN)0.0730.0750.6710.4071.000
2023-12-12T12:49:42.896530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차메뉴순번(SORT_CHAR)첨부파일명(FILE_NAME)사용여부(USER_GUBUN)
2차메뉴순번(SORT_CHAR)1.0001.0000.320
첨부파일명(FILE_NAME)1.0001.0001.000
사용여부(USER_GUBUN)0.3201.0001.000
2023-12-12T12:49:43.017103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상위메뉴아이디(CANCER_SEQ)메뉴아이디(MENU_SEQ)1차메뉴순번(UC_ID)2차메뉴순번(SORT_CHAR)사용여부(USER_GUBUN)첨부파일명(FILE_NAME)
상위메뉴아이디(CANCER_SEQ)1.0000.883-0.0400.0000.0891.000
메뉴아이디(MENU_SEQ)0.8831.0000.1160.1730.0801.000
1차메뉴순번(UC_ID)-0.0400.1161.0000.2500.5101.000
2차메뉴순번(SORT_CHAR)0.0000.1730.2501.0000.3201.000
사용여부(USER_GUBUN)0.0890.0800.5100.3201.0001.000
첨부파일명(FILE_NAME)1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T12:49:37.426792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:49:37.601634image/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.
2023-12-12T12:49:37.827821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

상위메뉴아이디(CANCER_SEQ)메뉴아이디(MENU_SEQ)메뉴명(MENU_NAME)1차메뉴순번(UC_ID)2차메뉴순번(SORT_CHAR)사용여부(USER_GUBUN)첨부파일명(FILE_NAME)작성일(REG_DATE)최종업데이트일(FINAL_PUBLISHING_DATE)
032933293간내 담도암0AS\N2012-08-23 00:00:002013-02-01 00:00:00
132933295암이란3AS\N2012-08-23 15:45:532013-02-01 00:00:00
232933296발생부위3ABS\N2012-08-23 15:45:532017-01-23 00:00:00
332933297정의 및 종류3ACS\N2012-08-23 15:45:542017-01-23 00:00:00
432933298관련통계3ADS\N2012-08-23 15:45:542022-02-07 00:00:00
532933299예방4AS\N2012-08-23 15:45:542013-02-01 00:00:00
632933300위험요인4ABS\N2012-08-23 15:45:542017-01-23 00:00:00
732933301예방법4ACS\N2012-08-23 15:45:542017-01-23 00:00:00
832933302조기검진4ADS\N2012-08-23 15:45:542017-01-23 00:00:00
932933303진단5AS\N2012-08-23 15:45:542013-02-01 00:00:00
상위메뉴아이디(CANCER_SEQ)메뉴아이디(MENU_SEQ)메뉴명(MENU_NAME)1차메뉴순번(UC_ID)2차메뉴순번(SORT_CHAR)사용여부(USER_GUBUN)첨부파일명(FILE_NAME)작성일(REG_DATE)최종업데이트일(FINAL_PUBLISHING_DATE)
2629406120527139치료6AS\N2019-08-07 08:35:532019-08-07 00:00:00
2630406120527140치료방법6ALS\N2019-08-07 08:36:062019-08-07 00:00:00
2631406120527141치료의 부작용6AMS\N2019-08-07 08:36:182019-08-07 09:14:59
2632406120527142재발 및 전이6ANS\N2019-08-07 08:36:312019-08-07 09:15:36
2633406120527143치료현황6AOS\N2019-08-07 08:36:512019-08-07 09:19:02
2634406120527144생활가이드7AS\N2019-08-07 08:37:092019-08-07 00:00:00
2635406120527145일상생활7APS\N2019-08-07 08:37:232019-08-07 16:29:59
2636406120527146식생활7AQS\N2019-08-07 08:37:362019-08-07 09:36:23
2637406120527147특수기구7ARS\N2019-08-07 08:37:482019-08-07 09:35:54
2638<NA><NA><NA><NA><NA><NA><NA><NA><NA>