Overview

Dataset statistics

Number of variables5
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.2 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-13006/F/1/datasetView.do

Alerts

NO is highly overall correlated with 구분High correlation
구분 is highly overall correlated with NOHigh correlation
NO has unique valuesUnique
이미지명 has unique valuesUnique
이미지URL has unique valuesUnique

Reproduction

Analysis started2023-12-11 10:17:51.160732
Analysis finished2023-12-11 10:17:51.629043
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-11T19:17:51.687225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.81944
Coefficient of variation (CV)0.57706181
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.667
MonotonicityStrictly increasing
2023-12-11T19:17:51.799225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
673 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
667 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%
995 1
0.1%
994 1
0.1%
993 1
0.1%
992 1
0.1%
991 1
0.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
장소
847 
행사
153 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장소 847
84.7%
행사 153
 
15.3%

Length

2023-12-11T19:17:51.900366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T19:17:51.975718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장소 847
84.7%
행사 153
 
15.3%

컨텐츠명
Text

Distinct78
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-11T19:17:52.168190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.801
Min length2

Characters and Unicode

Total characters5801
Distinct characters162
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st rowN서울타워 남산공원
2nd rowN서울타워 남산공원
3rd rowN서울타워 남산공원
4th rowN서울타워 남산공원
5th rowN서울타워 남산공원
ValueCountFrequency (%)
서울숲 43
 
3.5%
남산공원 40
 
3.2%
한양도성 40
 
3.2%
n서울타워 40
 
3.2%
석촌호수 37
 
3.0%
여의도공원 35
 
2.8%
국립현대미술관 31
 
2.5%
경복궁 31
 
2.5%
서울억새축제 30
 
2.4%
창경궁 30
 
2.4%
Other values (80) 882
71.2%
2023-12-11T19:17:52.502726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
322
 
5.6%
서 230
 
4.0%
울 174
 
3.0%
원 151
 
2.6%
경 142
 
2.4%
공 136
 
2.3%
궁 136
 
2.3%
대 132
 
2.3%
동 128
 
2.2%
관 121
 
2.1%
Other values (152) 4129
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5120
88.3%
Space Separator 322
 
5.6%
Uppercase Letter 178
 
3.1%
Open Punctuation 52
 
0.9%
Close Punctuation 52
 
0.9%
Decimal Number 44
 
0.8%
Lowercase Letter 33
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 230
 
4.5%
울 174
 
3.4%
원 151
 
2.9%
경 142
 
2.8%
공 136
 
2.7%
궁 136
 
2.7%
대 132
 
2.6%
동 128
 
2.5%
관 121
 
2.4%
수 111
 
2.2%
Other values (132) 3659
71.5%
Uppercase Letter
ValueCountFrequency (%)
C 46
25.8%
N 40
22.5%
M 38
21.3%
D 38
21.3%
I 8
 
4.5%
F 8
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 15
34.1%
5 7
15.9%
1 7
15.9%
0 7
15.9%
6 4
 
9.1%
3 4
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
c 9
27.3%
b 9
27.3%
m 6
18.2%
s 6
18.2%
j 3
 
9.1%
Space Separator
ValueCountFrequency (%)
322
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5120
88.3%
Common 470
 
8.1%
Latin 211
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 230
 
4.5%
울 174
 
3.4%
원 151
 
2.9%
경 142
 
2.8%
공 136
 
2.7%
궁 136
 
2.7%
대 132
 
2.6%
동 128
 
2.5%
관 121
 
2.4%
수 111
 
2.2%
Other values (132) 3659
71.5%
Latin
ValueCountFrequency (%)
C 46
21.8%
N 40
19.0%
M 38
18.0%
D 38
18.0%
c 9
 
4.3%
b 9
 
4.3%
I 8
 
3.8%
F 8
 
3.8%
m 6
 
2.8%
s 6
 
2.8%
Common
ValueCountFrequency (%)
322
68.5%
( 52
 
11.1%
) 52
 
11.1%
2 15
 
3.2%
5 7
 
1.5%
1 7
 
1.5%
0 7
 
1.5%
6 4
 
0.9%
3 4
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5120
88.3%
ASCII 681
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
322
47.3%
( 52
 
7.6%
) 52
 
7.6%
C 46
 
6.8%
N 40
 
5.9%
M 38
 
5.6%
D 38
 
5.6%
2 15
 
2.2%
c 9
 
1.3%
b 9
 
1.3%
Other values (10) 60
 
8.8%
Hangul
ValueCountFrequency (%)
서 230
 
4.5%
울 174
 
3.4%
원 151
 
2.9%
경 142
 
2.8%
공 136
 
2.7%
궁 136
 
2.7%
대 132
 
2.6%
동 128
 
2.5%
관 121
 
2.4%
수 111
 
2.2%
Other values (132) 3659
71.5%

이미지명
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-11T19:17:52.725299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length26.53
Min length10

Characters and Unicode

Total characters26530
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowNSeoulTower_Namsan_Park_01.jpg
2nd rowNSeoulTower_Namsan_Park_02.jpg
3rd rowNSeoulTower_Namsan_Park_03.jpg
4th rowNSeoulTower_Namsan_Park_04.jpg
5th rowNSeoulTower_Namsan_Park_05.jpg
ValueCountFrequency (%)
moonlight_tour_at 19
 
1.9%
seokchon_lake(33).jpg 1
 
0.1%
seokchon_lake(22).jpg 1
 
0.1%
world_food_street(14).jpg 1
 
0.1%
seokchon_lake(23).jpg 1
 
0.1%
seokchon_lake(24).jpg 1
 
0.1%
seokchon_lake(25).jpg 1
 
0.1%
seokchon_lake(26).jpg 1
 
0.1%
seokchon_lake(27).jpg 1
 
0.1%
seokchon_lake(28).jpg 1
 
0.1%
Other values (991) 991
97.3%
2023-12-11T19:17:53.126965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 2218
 
8.4%
a 1805
 
6.8%
o 1635
 
6.2%
e 1547
 
5.8%
g 1452
 
5.5%
n 1398
 
5.3%
. 1000
 
3.8%
u 844
 
3.2%
l 820
 
3.1%
i 806
 
3.0%
Other values (54) 13005
49.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16368
61.7%
Uppercase Letter 4174
 
15.7%
Connector Punctuation 2218
 
8.4%
Decimal Number 1761
 
6.6%
Other Punctuation 1000
 
3.8%
Open Punctuation 495
 
1.9%
Close Punctuation 495
 
1.9%
Space Separator 19
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1805
11.0%
o 1635
 
10.0%
e 1547
 
9.5%
g 1452
 
8.9%
n 1398
 
8.5%
u 844
 
5.2%
l 820
 
5.0%
i 806
 
4.9%
r 794
 
4.9%
t 783
 
4.8%
Other values (16) 4484
27.4%
Uppercase Letter
ValueCountFrequency (%)
P 805
19.3%
G 639
15.3%
J 530
12.7%
S 432
10.3%
M 236
 
5.7%
C 232
 
5.6%
F 196
 
4.7%
N 191
 
4.6%
D 149
 
3.6%
R 132
 
3.2%
Other values (13) 632
15.1%
Decimal Number
ValueCountFrequency (%)
1 415
23.6%
0 301
17.1%
2 264
15.0%
3 169
9.6%
5 126
 
7.2%
4 123
 
7.0%
6 110
 
6.2%
7 93
 
5.3%
8 83
 
4.7%
9 77
 
4.4%
Connector Punctuation
ValueCountFrequency (%)
_ 2218
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%
Open Punctuation
ValueCountFrequency (%)
( 495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 495
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20542
77.4%
Common 5988
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1805
 
8.8%
o 1635
 
8.0%
e 1547
 
7.5%
g 1452
 
7.1%
n 1398
 
6.8%
u 844
 
4.1%
l 820
 
4.0%
i 806
 
3.9%
P 805
 
3.9%
r 794
 
3.9%
Other values (39) 8636
42.0%
Common
ValueCountFrequency (%)
_ 2218
37.0%
. 1000
16.7%
( 495
 
8.3%
) 495
 
8.3%
1 415
 
6.9%
0 301
 
5.0%
2 264
 
4.4%
3 169
 
2.8%
5 126
 
2.1%
4 123
 
2.1%
Other values (5) 382
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 2218
 
8.4%
a 1805
 
6.8%
o 1635
 
6.2%
e 1547
 
5.8%
g 1452
 
5.5%
n 1398
 
5.3%
. 1000
 
3.8%
u 844
 
3.2%
l 820
 
3.1%
i 806
 
3.0%
Other values (54) 13005
49.0%

이미지URL
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-11T19:17:53.326006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length115
Median length100
Mean length81.63
Min length62

Characters and Unicode

Total characters81630
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowhttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_01.jpg
2nd rowhttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_02.jpg
3rd rowhttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_03.jpg
4th rowhttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_04.jpg
5th rowhttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_05.jpg
ValueCountFrequency (%)
http://www.visitseoul.net/file_save/art_img/gallery/moonlight_tour_at 19
 
1.9%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(33).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(22).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/world_food_street(14).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(23).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(24).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(25).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(26).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(27).jpg 1
 
0.1%
http://www.visitseoul.net/file_save/art_img/gallery/2016/seokchon_lake(28).jpg 1
 
0.1%
Other values (991) 991
97.3%
2023-12-11T19:17:53.661098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 6700
 
8.2%
e 6547
 
8.0%
t 5783
 
7.1%
l 4820
 
5.9%
i 4806
 
5.9%
a 4805
 
5.9%
_ 4218
 
5.2%
s 3482
 
4.3%
g 3452
 
4.2%
w 3169
 
3.9%
Other values (56) 33848
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57368
70.3%
Other Punctuation 10700
 
13.1%
Connector Punctuation 4218
 
5.2%
Uppercase Letter 4174
 
5.1%
Decimal Number 4161
 
5.1%
Close Punctuation 495
 
0.6%
Open Punctuation 495
 
0.6%
Space Separator 19
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6547
11.4%
t 5783
 
10.1%
l 4820
 
8.4%
i 4806
 
8.4%
a 4805
 
8.4%
s 3482
 
6.1%
g 3452
 
6.0%
w 3169
 
5.5%
r 2794
 
4.9%
o 2635
 
4.6%
Other values (16) 15075
26.3%
Uppercase Letter
ValueCountFrequency (%)
P 805
19.3%
G 639
15.3%
J 530
12.7%
S 432
10.3%
M 236
 
5.7%
C 232
 
5.6%
F 196
 
4.7%
N 191
 
4.6%
D 149
 
3.6%
R 132
 
3.2%
Other values (13) 632
15.1%
Decimal Number
ValueCountFrequency (%)
0 1001
24.1%
1 915
22.0%
2 764
18.4%
6 610
14.7%
9 277
 
6.7%
3 169
 
4.1%
5 126
 
3.0%
4 123
 
3.0%
7 93
 
2.2%
8 83
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 6700
62.6%
. 3000
28.0%
: 1000
 
9.3%
Connector Punctuation
ValueCountFrequency (%)
_ 4218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 495
100.0%
Open Punctuation
ValueCountFrequency (%)
( 495
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 61542
75.4%
Common 20088
 
24.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6547
 
10.6%
t 5783
 
9.4%
l 4820
 
7.8%
i 4806
 
7.8%
a 4805
 
7.8%
s 3482
 
5.7%
g 3452
 
5.6%
w 3169
 
5.1%
r 2794
 
4.5%
o 2635
 
4.3%
Other values (39) 19249
31.3%
Common
ValueCountFrequency (%)
/ 6700
33.4%
_ 4218
21.0%
. 3000
14.9%
0 1001
 
5.0%
: 1000
 
5.0%
1 915
 
4.6%
2 764
 
3.8%
6 610
 
3.0%
) 495
 
2.5%
( 495
 
2.5%
Other values (7) 890
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 6700
 
8.2%
e 6547
 
8.0%
t 5783
 
7.1%
l 4820
 
5.9%
i 4806
 
5.9%
a 4805
 
5.9%
_ 4218
 
5.2%
s 3482
 
4.3%
g 3452
 
4.2%
w 3169
 
3.9%
Other values (56) 33848
41.5%

Interactions

2023-12-11T19:17:51.430636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T19:17:53.738848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NO구분컨텐츠명
NO1.0000.9380.999
구분0.9381.0001.000
컨텐츠명0.9991.0001.000
2023-12-11T19:17:53.814952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NO구분
NO1.0000.787
구분0.7871.000

Missing values

2023-12-11T19:17:51.533224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T19:17:51.601698image/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

NO구분컨텐츠명이미지명이미지URL
01장소N서울타워 남산공원NSeoulTower_Namsan_Park_01.jpghttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_01.jpg
12장소N서울타워 남산공원NSeoulTower_Namsan_Park_02.jpghttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_02.jpg
23장소N서울타워 남산공원NSeoulTower_Namsan_Park_03.jpghttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_03.jpg
34장소N서울타워 남산공원NSeoulTower_Namsan_Park_04.jpghttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_04.jpg
45장소N서울타워 남산공원NSeoulTower_Namsan_Park_05.jpghttp://www.visitseoul.net/file_save/art_img/gallery/NSeoulTower_Namsan_Park_05.jpg
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