Overview

Dataset statistics

Number of variables16
Number of observations358
Missing cells1891
Missing cells (%)33.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.7 KiB
Average record size in memory136.4 B

Variable types

Numeric4
Categorical4
Text3
DateTime2
Unsupported3

Dataset

Description게시판글 일련번호,메뉴 일련번호,글 제목,글 내용,조회수,최초등록일,최종등록일,첨부파일 일련번호,추천수 좋아요,게시판 사진 구분,공지사항 이미지,사진등록 일자,사진 이미지 x값,사진 이미지 Y 값,모바일 파일 이름,모바일 파일 URL
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15369/S/1/datasetView.do

Alerts

추천수 좋아요 has constant value ""Constant
메뉴 일련번호 is highly overall correlated with 게시판글 일련번호 and 5 other fieldsHigh correlation
사진등록 일자 is highly overall correlated with 게시판글 일련번호 and 3 other fieldsHigh correlation
게시판 사진 구분 is highly overall correlated with 조회수 and 3 other fieldsHigh correlation
게시판글 일련번호 is highly overall correlated with 메뉴 일련번호 and 1 other fieldsHigh correlation
조회수 is highly overall correlated with 메뉴 일련번호 and 2 other fieldsHigh correlation
사진 이미지 x값 is highly overall correlated with 메뉴 일련번호 and 1 other fieldsHigh correlation
사진 이미지 Y 값 is highly overall correlated with 메뉴 일련번호 and 2 other fieldsHigh correlation
최종등록일 has 223 (62.3%) missing valuesMissing
공지사항 이미지 has 358 (100.0%) missing valuesMissing
사진 이미지 x값 has 297 (83.0%) missing valuesMissing
사진 이미지 Y 값 has 297 (83.0%) missing valuesMissing
모바일 파일 이름 has 358 (100.0%) missing valuesMissing
모바일 파일 URL has 358 (100.0%) missing valuesMissing
게시판글 일련번호 has unique valuesUnique
최초등록일 has unique valuesUnique
첨부파일 일련번호 has unique valuesUnique
공지사항 이미지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
모바일 파일 이름 is an unsupported type, check if it needs cleaning or further analysisUnsupported
모바일 파일 URL is an unsupported type, check if it needs cleaning or further analysisUnsupported
조회수 has 223 (62.3%) zerosZeros

Reproduction

Analysis started2024-05-04 05:33:38.138430
Analysis finished2024-05-04 05:33:47.401938
Duration9.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

게시판글 일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1388.933
Minimum209
Maximum3458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-04T05:33:47.803632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum209
5-th percentile226.85
Q11073.25
median1162.5
Q31253.75
95-th percentile3440.15
Maximum3458
Range3249
Interquartile range (IQR)180.5

Descriptive statistics

Standard deviation1002.6012
Coefficient of variation (CV)0.72184993
Kurtosis0.22610446
Mean1388.933
Median Absolute Deviation (MAD)91
Skewness1.1776058
Sum497238
Variance1005209.1
MonotonicityStrictly increasing
2024-05-04T05:33:48.308127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209 1
 
0.3%
1209 1
 
0.3%
1230 1
 
0.3%
1229 1
 
0.3%
1228 1
 
0.3%
1227 1
 
0.3%
1226 1
 
0.3%
1225 1
 
0.3%
1224 1
 
0.3%
1222 1
 
0.3%
Other values (348) 348
97.2%
ValueCountFrequency (%)
209 1
0.3%
210 1
0.3%
211 1
0.3%
212 1
0.3%
213 1
0.3%
214 1
0.3%
215 1
0.3%
216 1
0.3%
217 1
0.3%
218 1
0.3%
ValueCountFrequency (%)
3458 1
0.3%
3457 1
0.3%
3456 1
0.3%
3455 1
0.3%
3454 1
0.3%
3453 1
0.3%
3452 1
0.3%
3451 1
0.3%
3450 1
0.3%
3449 1
0.3%

메뉴 일련번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
BBSMSTR_000000000081
314 
BBSMSTR_000000000045
44 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBBSMSTR_000000000081
2nd rowBBSMSTR_000000000081
3rd rowBBSMSTR_000000000081
4th rowBBSMSTR_000000000081
5th rowBBSMSTR_000000000081

Common Values

ValueCountFrequency (%)
BBSMSTR_000000000081 314
87.7%
BBSMSTR_000000000045 44
 
12.3%

Length

2024-05-04T05:33:48.752069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:33:49.078142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbsmstr_000000000081 314
87.7%
bbsmstr_000000000045 44
 
12.3%

글 제목
Text

Distinct274
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-04T05:33:49.512632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length33
Mean length11.530726
Min length2

Characters and Unicode

Total characters4128
Distinct characters315
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)64.0%

Sample

1st row곡장에서 바라본 모습
2nd row돌고래 쉼터
3rd row백악쉼터 부근에서 바라본 모습
4th row백악마루 정상에서 바라본 모습
5th row숙정문
ValueCountFrequency (%)
성벽 63
 
6.2%
한양도성 38
 
3.8%
모습 33
 
3.3%
구간 27
 
2.7%
인왕산 27
 
2.7%
바라본 24
 
2.4%
야경 19
 
1.9%
전경 18
 
1.8%
정상 15
 
1.5%
숭례문 14
 
1.4%
Other values (398) 735
72.6%
2024-05-04T05:33:50.484556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
657
 
15.9%
성 155
 
3.8%
문 103
 
2.5%
서 97
 
2.3%
산 86
 
2.1%
도 71
 
1.7%
벽 69
 
1.7%
정 65
 
1.6%
바 64
 
1.6%
동 59
 
1.4%
Other values (305) 2702
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3166
76.7%
Space Separator 657
 
15.9%
Decimal Number 119
 
2.9%
Uppercase Letter 92
 
2.2%
Math Symbol 30
 
0.7%
Open Punctuation 21
 
0.5%
Close Punctuation 21
 
0.5%
Other Punctuation 17
 
0.4%
Dash Punctuation 4
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 155
 
4.9%
문 103
 
3.3%
서 97
 
3.1%
산 86
 
2.7%
도 71
 
2.2%
벽 69
 
2.2%
정 65
 
2.1%
바 64
 
2.0%
동 59
 
1.9%
인 59
 
1.9%
Other values (269) 2338
73.8%
Uppercase Letter
ValueCountFrequency (%)
E 14
15.2%
N 13
14.1%
R 11
12.0%
A 9
9.8%
T 6
 
6.5%
I 6
 
6.5%
G 5
 
5.4%
K 4
 
4.3%
O 4
 
4.3%
H 4
 
4.3%
Other values (6) 16
17.4%
Decimal Number
ValueCountFrequency (%)
1 30
25.2%
2 26
21.8%
0 19
16.0%
3 14
11.8%
7 9
 
7.6%
6 8
 
6.7%
5 4
 
3.4%
9 4
 
3.4%
4 3
 
2.5%
8 2
 
1.7%
Other Punctuation
ValueCountFrequency (%)
' 6
35.3%
. 5
29.4%
: 4
23.5%
, 2
 
11.8%
Space Separator
ValueCountFrequency (%)
657
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3166
76.7%
Common 870
 
21.1%
Latin 92
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 155
 
4.9%
문 103
 
3.3%
서 97
 
3.1%
산 86
 
2.7%
도 71
 
2.2%
벽 69
 
2.2%
정 65
 
2.1%
바 64
 
2.0%
동 59
 
1.9%
인 59
 
1.9%
Other values (269) 2338
73.8%
Common
ValueCountFrequency (%)
657
75.5%
~ 30
 
3.4%
1 30
 
3.4%
2 26
 
3.0%
( 21
 
2.4%
) 21
 
2.4%
0 19
 
2.2%
3 14
 
1.6%
7 9
 
1.0%
6 8
 
0.9%
Other values (10) 35
 
4.0%
Latin
ValueCountFrequency (%)
E 14
15.2%
N 13
14.1%
R 11
12.0%
A 9
9.8%
T 6
 
6.5%
I 6
 
6.5%
G 5
 
5.4%
K 4
 
4.3%
O 4
 
4.3%
H 4
 
4.3%
Other values (6) 16
17.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3166
76.7%
ASCII 962
 
23.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
657
68.3%
~ 30
 
3.1%
1 30
 
3.1%
2 26
 
2.7%
( 21
 
2.2%
) 21
 
2.2%
0 19
 
2.0%
E 14
 
1.5%
3 14
 
1.5%
N 13
 
1.4%
Other values (26) 117
 
12.2%
Hangul
ValueCountFrequency (%)
성 155
 
4.9%
문 103
 
3.3%
서 97
 
3.1%
산 86
 
2.7%
도 71
 
2.2%
벽 69
 
2.2%
정 65
 
2.1%
바 64
 
2.0%
동 59
 
1.9%
인 59
 
1.9%
Other values (269) 2338
73.8%

글 내용
Text

Distinct278
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-04T05:33:51.244390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length281
Mean length47.76257
Min length2

Characters and Unicode

Total characters17099
Distinct characters486
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique237 ?
Unique (%)66.2%

Sample

1st row백악구간 곡장에서 바라본 성 안쪽 모습과 서울 전경 입니다.
2nd row백악구간 돌고래 쉼터에서 바라본 모습
3rd row<p>백악쉼터 부근 나무계단길에서 바라본 모습입니다.</p>
4th row백악구간 정상 백악마루에 오르면 큰 바위가 있습니다.
5th row<p>4대문 중 북대문인 숙정문입니다.</p>
ValueCountFrequency (%)
0pt 71
 
3.3%
성벽 58
 
2.7%
p 40
 
1.8%
31
 
1.4%
한양도성 27
 
1.2%
인왕산 25
 
1.2%
바라본 25
 
1.2%
구간<br 25
 
1.2%
p>&nbsp;</p 24
 
1.1%
mso-pagination 22
 
1.0%
Other values (938) 1823
84.0%
2024-05-04T05:33:52.680914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1818
 
10.6%
p 575
 
3.4%
s 528
 
3.1%
< 483
 
2.8%
> 477
 
2.8%
n 451
 
2.6%
- 434
 
2.5%
t 433
 
2.5%
; 332
 
1.9%
a 325
 
1.9%
Other values (476) 11243
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5591
32.7%
Lowercase Letter 4434
25.9%
Space Separator 1818
 
10.6%
Other Punctuation 1423
 
8.3%
Uppercase Letter 1423
 
8.3%
Math Symbol 1132
 
6.6%
Decimal Number 674
 
3.9%
Dash Punctuation 434
 
2.5%
Connector Punctuation 63
 
0.4%
Close Punctuation 47
 
0.3%
Other values (4) 60
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 207
 
3.7%
서 142
 
2.5%
다 127
 
2.3%
도 125
 
2.2%
문 121
 
2.2%
한 113
 
2.0%
니 106
 
1.9%
의 104
 
1.9%
산 103
 
1.8%
에 100
 
1.8%
Other values (392) 4343
77.7%
Uppercase Letter
ValueCountFrequency (%)
P 298
20.9%
T 151
10.6%
E 127
8.9%
A 110
 
7.7%
N 92
 
6.5%
S 88
 
6.2%
I 74
 
5.2%
F 68
 
4.8%
O 58
 
4.1%
C 47
 
3.3%
Other values (15) 310
21.8%
Lowercase Letter
ValueCountFrequency (%)
p 575
13.0%
s 528
11.9%
n 451
10.2%
t 433
9.8%
a 325
 
7.3%
b 267
 
6.0%
o 236
 
5.3%
e 208
 
4.7%
l 205
 
4.6%
i 183
 
4.1%
Other values (14) 1023
23.1%
Other Punctuation
ValueCountFrequency (%)
; 332
23.3%
/ 230
16.2%
' 224
15.7%
& 209
14.7%
: 199
14.0%
. 166
11.7%
% 18
 
1.3%
, 17
 
1.2%
? 15
 
1.1%
! 12
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 235
34.9%
1 121
18.0%
2 90
 
13.4%
5 52
 
7.7%
4 49
 
7.3%
3 45
 
6.7%
9 32
 
4.7%
6 22
 
3.3%
8 15
 
2.2%
7 13
 
1.9%
Math Symbol
ValueCountFrequency (%)
< 483
42.7%
> 477
42.1%
= 147
 
13.0%
~ 25
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 45
95.7%
》 2
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 44
95.7%
《 2
 
4.3%
Space Separator
ValueCountFrequency (%)
1818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 434
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 63
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 10
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5857
34.3%
Common 5651
33.0%
Hangul 5591
32.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 207
 
3.7%
서 142
 
2.5%
다 127
 
2.3%
도 125
 
2.2%
문 121
 
2.2%
한 113
 
2.0%
니 106
 
1.9%
의 104
 
1.9%
산 103
 
1.8%
에 100
 
1.8%
Other values (392) 4343
77.7%
Latin
ValueCountFrequency (%)
p 575
 
9.8%
s 528
 
9.0%
n 451
 
7.7%
t 433
 
7.4%
a 325
 
5.5%
P 298
 
5.1%
b 267
 
4.6%
o 236
 
4.0%
e 208
 
3.6%
l 205
 
3.5%
Other values (39) 2331
39.8%
Common
ValueCountFrequency (%)
1818
32.2%
< 483
 
8.5%
> 477
 
8.4%
- 434
 
7.7%
; 332
 
5.9%
0 235
 
4.2%
/ 230
 
4.1%
' 224
 
4.0%
& 209
 
3.7%
: 199
 
3.5%
Other values (25) 1010
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11499
67.2%
Hangul 5591
32.7%
None 5
 
< 0.1%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1818
 
15.8%
p 575
 
5.0%
s 528
 
4.6%
< 483
 
4.2%
> 477
 
4.1%
n 451
 
3.9%
- 434
 
3.8%
t 433
 
3.8%
; 332
 
2.9%
a 325
 
2.8%
Other values (69) 5643
49.1%
Hangul
ValueCountFrequency (%)
성 207
 
3.7%
서 142
 
2.5%
다 127
 
2.3%
도 125
 
2.2%
문 121
 
2.2%
한 113
 
2.0%
니 106
 
1.9%
의 104
 
1.9%
산 103
 
1.8%
에 100
 
1.8%
Other values (392) 4343
77.7%
None
ValueCountFrequency (%)
》 2
40.0%
《 2
40.0%
？ 1
20.0%
Punctuation
ValueCountFrequency (%)
‘ 2
50.0%
’ 2
50.0%

조회수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.505587
Minimum0
Maximum5179
Zeros223
Zeros (%)62.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-04T05:33:53.221095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile487.7
Maximum5179
Range5179
Interquartile range (IQR)1

Descriptive statistics

Standard deviation336.25495
Coefficient of variation (CV)4.7024991
Kurtosis151.21086
Mean71.505587
Median Absolute Deviation (MAD)0
Skewness10.712209
Sum25599
Variance113067.39
MonotonicityNot monotonic
2024-05-04T05:33:53.873010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 223
62.3%
1 49
 
13.7%
2 30
 
8.4%
4 4
 
1.1%
6 3
 
0.8%
5 2
 
0.6%
3 2
 
0.6%
481 2
 
0.6%
566 1
 
0.3%
56 1
 
0.3%
Other values (41) 41
 
11.5%
ValueCountFrequency (%)
0 223
62.3%
1 49
 
13.7%
2 30
 
8.4%
3 2
 
0.6%
4 4
 
1.1%
5 2
 
0.6%
6 3
 
0.8%
7 1
 
0.3%
20 1
 
0.3%
34 1
 
0.3%
ValueCountFrequency (%)
5179 1
0.3%
1434 1
0.3%
1293 1
0.3%
1145 1
0.3%
1067 1
0.3%
1052 1
0.3%
1033 1
0.3%
888 1
0.3%
811 1
0.3%
800 1
0.3%

최초등록일
Date

UNIQUE 

Distinct358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2014-03-12 15:21:38
Maximum2020-06-12 13:28:47
2024-05-04T05:33:54.307932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:54.814145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종등록일
Date

MISSING 

Distinct135
Distinct (%)100.0%
Missing223
Missing (%)62.3%
Memory size2.9 KiB
Minimum2014-03-12 15:41:12
Maximum2021-11-03 11:27:54
2024-05-04T05:33:55.452377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:56.077859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

첨부파일 일련번호
Text

UNIQUE 

Distinct358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-04T05:33:56.658035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7160
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique358 ?
Unique (%)100.0%

Sample

1st rowFILE_000000000003736
2nd rowFILE_000000000003737
3rd rowFILE_000000000003738
4th rowFILE_000000000003739
5th rowFILE_000000000003740
ValueCountFrequency (%)
file_000000000003736 1
 
0.3%
file_000000000005899 1
 
0.3%
file_000000000005920 1
 
0.3%
file_000000000005919 1
 
0.3%
file_000000000005918 1
 
0.3%
file_000000000005917 1
 
0.3%
file_000000000005916 1
 
0.3%
file_000000000005914 1
 
0.3%
file_000000000005913 1
 
0.3%
file_000000000005912 1
 
0.3%
Other values (348) 348
97.2%
2024-05-04T05:33:57.677530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4005
55.9%
5 363
 
5.1%
F 358
 
5.0%
I 358
 
5.0%
L 358
 
5.0%
E 358
 
5.0%
_ 358
 
5.0%
7 205
 
2.9%
8 181
 
2.5%
9 131
 
1.8%
Other values (5) 485
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5370
75.0%
Uppercase Letter 1432
 
20.0%
Connector Punctuation 358
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4005
74.6%
5 363
 
6.8%
7 205
 
3.8%
8 181
 
3.4%
9 131
 
2.4%
4 125
 
2.3%
3 109
 
2.0%
6 102
 
1.9%
2 79
 
1.5%
1 70
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
F 358
25.0%
I 358
25.0%
L 358
25.0%
E 358
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 358
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5728
80.0%
Latin 1432
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4005
69.9%
5 363
 
6.3%
_ 358
 
6.2%
7 205
 
3.6%
8 181
 
3.2%
9 131
 
2.3%
4 125
 
2.2%
3 109
 
1.9%
6 102
 
1.8%
2 79
 
1.4%
Latin
ValueCountFrequency (%)
F 358
25.0%
I 358
25.0%
L 358
25.0%
E 358
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4005
55.9%
5 363
 
5.1%
F 358
 
5.0%
I 358
 
5.0%
L 358
 
5.0%
E 358
 
5.0%
_ 358
 
5.0%
7 205
 
2.9%
8 181
 
2.5%
9 131
 
1.8%
Other values (5) 485
 
6.8%

추천수 좋아요
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
358 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 358
100.0%

Length

2024-05-04T05:33:58.117022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:33:58.576938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
100.0%

게시판 사진 구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
인왕
100 
<NA>
60 
남산
50 
백악
49 
낙산
43 
Other values (2)
56 

Length

Max length4
Median length2
Mean length2.3351955
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인왕 100
27.9%
<NA> 60
16.8%
남산 50
14.0%
백악 49
13.7%
낙산 43
12.0%
흥인 30
 
8.4%
숭례 26
 
7.3%

Length

2024-05-04T05:33:59.063279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:33:59.523780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인왕 100
27.9%
na 60
16.8%
남산 50
14.0%
백악 49
13.7%
낙산 43
12.0%
흥인 30
 
8.4%
숭례 26
 
7.3%

공지사항 이미지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing358
Missing (%)100.0%
Memory size3.3 KiB

사진등록 일자
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2016.11
55 
2016.10
51 
<NA>
50 
2016.6
49 
2016.7
28 
Other values (24)
125 

Length

Max length13
Median length12
Mean length6.9804469
Min length4

Unique

Unique6 ?
Unique (%)1.7%

Sample

1st row2013년 10월 21일
2nd row2013년 10월 21일
3rd row2013년 10월 21일
4th row2013년 10월 21일
5th row2013년 10월 21일

Common Values

ValueCountFrequency (%)
2016.11 55
15.4%
2016.10 51
14.2%
<NA> 50
14.0%
2016.6 49
13.7%
2016.7 28
7.8%
2019.8 15
 
4.2%
2014.11 11
 
3.1%
2019.11 10
 
2.8%
2019.10 10
 
2.8%
2012.09 10
 
2.8%
Other values (19) 69
19.3%

Length

2024-05-04T05:34:00.085926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2016.11 55
12.7%
2016.10 51
11.8%
na 50
11.5%
2016.6 49
11.3%
10월 38
8.8%
2013년 37
8.5%
2016.7 28
 
6.5%
2019.8 15
 
3.5%
2014.11 11
 
2.5%
2019.11 10
 
2.3%
Other values (21) 90
20.7%

사진 이미지 x값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51
Distinct (%)83.6%
Missing297
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean341.70492
Minimum36
Maximum544
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-04T05:34:00.469493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile82
Q1195
median412
Q3504
95-th percentile538
Maximum544
Range508
Interquartile range (IQR)309

Descriptive statistics

Standard deviation169.66323
Coefficient of variation (CV)0.49651972
Kurtosis-1.4566887
Mean341.70492
Median Absolute Deviation (MAD)120
Skewness-0.33672855
Sum20844
Variance28785.611
MonotonicityNot monotonic
2024-05-04T05:34:00.986136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449 3
 
0.8%
195 2
 
0.6%
204 2
 
0.6%
542 2
 
0.6%
454 2
 
0.6%
521 2
 
0.6%
504 2
 
0.6%
455 2
 
0.6%
448 2
 
0.6%
84 1
 
0.3%
Other values (41) 41
 
11.5%
(Missing) 297
83.0%
ValueCountFrequency (%)
36 1
0.3%
44 1
0.3%
45 1
0.3%
82 1
0.3%
84 1
0.3%
89 1
0.3%
101 1
0.3%
120 1
0.3%
121 1
0.3%
137 1
0.3%
ValueCountFrequency (%)
544 1
0.3%
542 2
0.6%
538 1
0.3%
533 1
0.3%
532 1
0.3%
530 1
0.3%
529 1
0.3%
521 2
0.6%
516 1
0.3%
515 1
0.3%

사진 이미지 Y 값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct55
Distinct (%)90.2%
Missing297
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean279.2459
Minimum-8
Maximum703
Zeros1
Zeros (%)0.3%
Negative1
Negative (%)0.3%
Memory size3.3 KiB
2024-05-04T05:34:01.549154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8
5-th percentile18
Q1109
median254
Q3425
95-th percentile650
Maximum703
Range711
Interquartile range (IQR)316

Descriptive statistics

Standard deviation206.81551
Coefficient of variation (CV)0.74062147
Kurtosis-0.98676144
Mean279.2459
Median Absolute Deviation (MAD)148
Skewness0.44027996
Sum17034
Variance42772.655
MonotonicityNot monotonic
2024-05-04T05:34:02.129947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
109 3
 
0.8%
470 2
 
0.6%
425 2
 
0.6%
113 2
 
0.6%
110 2
 
0.6%
228 1
 
0.3%
216 1
 
0.3%
277 1
 
0.3%
155 1
 
0.3%
172 1
 
0.3%
Other values (45) 45
 
12.6%
(Missing) 297
83.0%
ValueCountFrequency (%)
-8 1
0.3%
0 1
0.3%
4 1
0.3%
18 1
0.3%
19 1
0.3%
35 1
0.3%
45 1
0.3%
50 1
0.3%
53 1
0.3%
54 1
0.3%
ValueCountFrequency (%)
703 1
0.3%
673 1
0.3%
666 1
0.3%
650 1
0.3%
628 1
0.3%
602 1
0.3%
597 1
0.3%
581 1
0.3%
532 1
0.3%
528 1
0.3%

모바일 파일 이름
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing358
Missing (%)100.0%
Memory size3.3 KiB

모바일 파일 URL
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing358
Missing (%)100.0%
Memory size3.3 KiB

Interactions

2024-05-04T05:33:44.605500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:40.564360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:42.200012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:43.321875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:44.980608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:40.882350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:42.452678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:43.626451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:45.342992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:41.214958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:42.691554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:43.924150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:45.658702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:41.708828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:42.935759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:33:44.274478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T05:34:02.564186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시판글 일련번호메뉴 일련번호조회수게시판 사진 구분사진등록 일자사진 이미지 x값사진 이미지 Y 값
게시판글 일련번호1.0000.7090.5420.6530.9820.8030.911
메뉴 일련번호0.7091.0000.781NaNNaNNaNNaN
조회수0.5420.7811.000NaNNaNNaNNaN
게시판 사진 구분0.653NaNNaN1.0000.7970.8130.892
사진등록 일자0.982NaNNaN0.7971.0000.7280.874
사진 이미지 x값0.803NaNNaN0.8130.7281.0000.877
사진 이미지 Y 값0.911NaNNaN0.8920.8740.8771.000
2024-05-04T05:34:02.978219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴 일련번호사진등록 일자게시판 사진 구분
메뉴 일련번호1.0001.0001.000
사진등록 일자1.0001.0000.495
게시판 사진 구분1.0000.4951.000
2024-05-04T05:34:03.321641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시판글 일련번호조회수사진 이미지 x값사진 이미지 Y 값메뉴 일련번호게시판 사진 구분사진등록 일자
게시판글 일련번호1.000-0.166-0.0720.0160.5190.4810.810
조회수-0.1661.000-0.071-0.3200.5711.0001.000
사진 이미지 x값-0.072-0.0711.0000.2081.0000.5780.379
사진 이미지 Y 값0.016-0.3200.2081.0001.0000.7070.578
메뉴 일련번호0.5190.5711.0001.0001.0001.0001.000
게시판 사진 구분0.4811.0000.5780.7071.0001.0000.495
사진등록 일자0.8101.0000.3790.5781.0000.4951.000

Missing values

2024-05-04T05:33:46.171774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T05:33:46.809977image/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.
2024-05-04T05:33:47.208189image/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

게시판글 일련번호메뉴 일련번호글 제목글 내용조회수최초등록일최종등록일첨부파일 일련번호추천수 좋아요게시판 사진 구분공지사항 이미지사진등록 일자사진 이미지 x값사진 이미지 Y 값모바일 파일 이름모바일 파일 URL
0209BBSMSTR_000000000081곡장에서 바라본 모습백악구간 곡장에서 바라본 성 안쪽 모습과 서울 전경 입니다.62014-03-12 15:21:38.02014-06-13 16:53:51.0FILE_0000000000037360백악<NA>2013년 10월 21일213-8<NA><NA>
1210BBSMSTR_000000000081돌고래 쉼터백악구간 돌고래 쉼터에서 바라본 모습72014-03-12 15:27:58.02014-06-13 16:53:27.0FILE_0000000000037370백악<NA>2013년 10월 21일15850<NA><NA>
2211BBSMSTR_000000000081백악쉼터 부근에서 바라본 모습<p>백악쉼터 부근 나무계단길에서 바라본 모습입니다.</p>62014-03-12 15:36:14.02014-06-13 16:53:11.0FILE_0000000000037380백악<NA>2013년 10월 21일16445<NA><NA>
3212BBSMSTR_000000000081백악마루 정상에서 바라본 모습백악구간 정상 백악마루에 오르면 큰 바위가 있습니다.22014-03-12 15:39:37.02014-06-13 16:52:45.0FILE_0000000000037390백악<NA>2013년 10월 21일17953<NA><NA>
4213BBSMSTR_000000000081숙정문<p>4대문 중 북대문인 숙정문입니다.</p>12014-03-12 15:41:10.02014-03-12 15:41:12.0FILE_0000000000037400백악<NA>2013년 10월 21일2544<NA><NA>
5214BBSMSTR_000000000081우수조망명소에서 바라본 모습백악구간 우수조망명소에서 바라본 서울 전경 입니다.12014-03-12 15:42:08.02014-06-13 16:52:12.0FILE_0000000000037410백악<NA>2013년 10월 21일31257<NA><NA>
6215BBSMSTR_000000000081창의문4소문중 북서쪽에 위치한 창의문 입니다.02014-03-12 15:42:53.0<NA>FILE_0000000000037420백악<NA>2013년 10월 21일12154<NA><NA>
7216BBSMSTR_000000000081청운대~암문사이 바깥쪽 모습<p>백악구간 청운대에서 바깥쪽에서 암문 사이 모습입니다.</p>12014-03-12 16:38:01.02014-06-13 16:51:35.0FILE_0000000000037430백악<NA>2013년 10월 21일19519<NA><NA>
8217BBSMSTR_000000000081혜화문방향에서 낙산구간 초입 야경 모습<p>혜화문방향에서 낙산구간 초입은 밤에도 볼 수 있도록 조명들이 잘&nbsp; 설치 되어있습니다.&nbsp;</p>22014-03-12 16:40:58.02014-06-13 16:51:10.0FILE_0000000000037440낙산<NA>2013년 10월 22일495146<NA><NA>
9218BBSMSTR_000000000081낙산정상 및 낙산공원 모습<p>낙산구간은 낙산공원과 같이 조성되어 있어서 편하게&nbsp;탐방하시기 좋습니다.&nbsp;</p>22014-03-12 16:43:41.02014-06-13 16:50:46.0FILE_0000000000037450낙산<NA>2013년 10월 22일521254<NA><NA>
게시판글 일련번호메뉴 일련번호글 제목글 내용조회수최초등록일최종등록일첨부파일 일련번호추천수 좋아요게시판 사진 구분공지사항 이미지사진등록 일자사진 이미지 x값사진 이미지 Y 값모바일 파일 이름모바일 파일 URL
3483449BBSMSTR_000000000081서울로7017에서 바라본 숭례문서울로7017에서 바라본 숭례문<br>12020-06-12 13:22:37.02020-06-12 13:22:38.0FILE_0000000000075780숭례<NA>2019.8<NA><NA><NA><NA>
3493450BBSMSTR_000000000081인왕산 전경인왕산 전경<br>02020-06-12 13:23:33.0<NA>FILE_0000000000075790인왕<NA>2019.10<NA><NA><NA><NA>
3503451BBSMSTR_000000000081월암공원~인왕 곡성 구간&nbsp;월암공원~인왕 곡성 구간<br>12020-06-12 13:24:12.02020-06-17 16:17:19.0FILE_0000000000075800인왕<NA>2019.11<NA><NA><NA><NA>
3513452BBSMSTR_000000000081월암공원~인왕 곡성 구간&nbsp;월암공원~인왕 곡성 구간<br>02020-06-12 13:24:59.0<NA>FILE_0000000000075810인왕<NA>2019.9<NA><NA><NA><NA>
3523453BBSMSTR_000000000081인왕산 범바위&nbsp;인왕산 범바위<br>02020-06-12 13:25:40.0<NA>FILE_0000000000075820인왕<NA>2019.9<NA><NA><NA><NA>
3533454BBSMSTR_000000000081범바위~인왕산 정상 구간범바위~인왕산 정상 구간<br>12020-06-12 13:26:16.02020-06-12 13:26:17.0FILE_0000000000075830인왕<NA>2019.9<NA><NA><NA><NA>
3543455BBSMSTR_000000000081범바위~인왕산 정상 구간범바위~인왕산 정상 구간<br>02020-06-12 13:26:56.0<NA>FILE_0000000000075840인왕<NA>2019.9<NA><NA><NA><NA>
3553456BBSMSTR_000000000081인왕산 정상에서 바라본 서울 도심인왕산 정상에서 바라본 서울 도심<br>02020-06-12 13:27:34.0<NA>FILE_0000000000075850인왕<NA>2019.11<NA><NA><NA><NA>
3563457BBSMSTR_000000000081기차바위에서 바라본 인왕산과 서울 도심기차바위에서 바라본 인왕산과 서울 도심<br>02020-06-12 13:28:11.0<NA>FILE_0000000000075860인왕<NA>2019.11<NA><NA><NA><NA>
3573458BBSMSTR_000000000081인왕산 정상~창의문 구간&nbsp;인왕산 정상~창의문 구간<br>02020-06-12 13:28:47.0<NA>FILE_0000000000075870인왕<NA>2019.9<NA><NA><NA><NA>