Overview

Dataset statistics

Number of variables12
Number of observations1017
Missing cells1953
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.5 KiB
Average record size in memory98.1 B

Variable types

Text6
Categorical4
Numeric2

Dataset

Description키,분류,명칭,주소,행정 시,행정 구,행정 동,전화번호,홈페이지주소,HTML사용여부,X 좌표,Y 좌표
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-12957/S/1/datasetView.do

Alerts

HTML사용여부 has constant value ""Constant
행정 시 is highly overall correlated with X 좌표 and 3 other fieldsHigh correlation
행정 구 is highly overall correlated with 행정 시 and 1 other fieldsHigh correlation
행정 동 is highly overall correlated with 행정 시 and 1 other fieldsHigh correlation
X 좌표 is highly overall correlated with 행정 시High correlation
Y 좌표 is highly overall correlated with 행정 시High correlation
행정 구 is highly imbalanced (60.6%)Imbalance
주소 has 194 (19.1%) missing valuesMissing
전화번호 has 651 (64.0%) missing valuesMissing
홈페이지주소 has 694 (68.2%) missing valuesMissing
X 좌표 has 207 (20.4%) missing valuesMissing
Y 좌표 has 207 (20.4%) missing valuesMissing
Y 좌표 is highly skewed (γ1 = -20.10587948)Skewed
키 has unique valuesUnique

Reproduction

Analysis started2024-04-06 10:54:00.019908
Analysis finished2024-04-06 10:54:03.190194
Duration3.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

키
Text

UNIQUE 

Distinct1017
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-04-06T19:54:03.489443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12204
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1017 ?
Unique (%)100.0%

Sample

1st rowBE_IW10-0474
2nd rowBE_IW10-0475
3rd rowBE_IW10-0499
4th rowBE_IW10-0527
5th rowBE_IW10-0500
ValueCountFrequency (%)
be_iw10-0474 1
 
0.1%
be_iw10-0748 1
 
0.1%
be_iw10-0534 1
 
0.1%
be_iw10-0622 1
 
0.1%
be_iw10-0623 1
 
0.1%
be_iw10-0624 1
 
0.1%
be_iw10-0625 1
 
0.1%
be_iw10-0626 1
 
0.1%
be_iw10-0627 1
 
0.1%
be_iw10-0628 1
 
0.1%
Other values (1007) 1007
99.0%
2024-04-06T19:54:04.121949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2343
19.2%
1 1345
11.0%
B 1017
8.3%
E 1017
8.3%
_ 1017
8.3%
I 1017
8.3%
W 1017
8.3%
- 1017
8.3%
4 302
 
2.5%
7 302
 
2.5%
Other values (6) 1810
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6102
50.0%
Uppercase Letter 4068
33.3%
Connector Punctuation 1017
 
8.3%
Dash Punctuation 1017
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2343
38.4%
1 1345
22.0%
4 302
 
4.9%
7 302
 
4.9%
5 302
 
4.9%
2 302
 
4.9%
3 302
 
4.9%
6 302
 
4.9%
9 301
 
4.9%
8 301
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 1017
25.0%
E 1017
25.0%
I 1017
25.0%
W 1017
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1017
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1017
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8136
66.7%
Latin 4068
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2343
28.8%
1 1345
16.5%
_ 1017
12.5%
- 1017
12.5%
4 302
 
3.7%
7 302
 
3.7%
5 302
 
3.7%
2 302
 
3.7%
3 302
 
3.7%
6 302
 
3.7%
Other values (2) 602
 
7.4%
Latin
ValueCountFrequency (%)
B 1017
25.0%
E 1017
25.0%
I 1017
25.0%
W 1017
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2343
19.2%
1 1345
11.0%
B 1017
8.3%
E 1017
8.3%
_ 1017
8.3%
I 1017
8.3%
W 1017
8.3%
- 1017
8.3%
4 302
 
2.5%
7 302
 
2.5%
Other values (6) 1810
14.8%

분류
Text

Distinct53
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-04-06T19:54:04.509912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length15.854474
Min length5

Characters and Unicode

Total characters16124
Distinct characters110
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.2%

Sample

1st row문화재유산|문화재구분|가옥
2nd row문화재유산|문화재구분|가옥
3rd row문화재유산|문화재구분|누정
4th row문화재유산|문화재구분|예술가의집
5th row문화재유산|문화재구분|누정
ValueCountFrequency (%)
문화재유산|문화재구분|조형물 228
20.7%
문화재유산|문화재구분|민속자료 111
 
10.1%
장소/위치|시설|민간시설|공연장 106
 
9.6%
문화재유산|문화재구분|조형물|표석|갤러리/미술관 72
 
6.5%
장소/위치|종로여행 63
 
5.7%
박물관 48
 
4.4%
장소/위치|시설|민간시설|문화관/박물관/기념관 43
 
3.9%
장소/위치|촬영장소 34
 
3.1%
문화재유산|문화재구분|궁궐 29
 
2.6%
문화재유산|문화재구분|종교문화재 27
 
2.5%
Other values (47) 341
30.9%
2024-04-06T19:54:05.101876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
| 2169
 
13.5%
화 1272
 
7.9%
문 1258
 
7.8%
재 1181
 
7.3%
산 586
 
3.6%
유 585
 
3.6%
/ 581
 
3.6%
구 571
 
3.5%
장 570
 
3.5%
분 569
 
3.5%
Other values (100) 6782
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13289
82.4%
Math Symbol 2169
 
13.5%
Other Punctuation 581
 
3.6%
Space Separator 85
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 1272
 
9.6%
문 1258
 
9.5%
재 1181
 
8.9%
산 586
 
4.4%
유 585
 
4.4%
구 571
 
4.3%
장 570
 
4.3%
분 569
 
4.3%
소 481
 
3.6%
물 437
 
3.3%
Other values (97) 5779
43.5%
Math Symbol
ValueCountFrequency (%)
| 2169
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 581
100.0%
Space Separator
ValueCountFrequency (%)
85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13289
82.4%
Common 2835
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 1272
 
9.6%
문 1258
 
9.5%
재 1181
 
8.9%
산 586
 
4.4%
유 585
 
4.4%
구 571
 
4.3%
장 570
 
4.3%
분 569
 
4.3%
소 481
 
3.6%
물 437
 
3.3%
Other values (97) 5779
43.5%
Common
ValueCountFrequency (%)
| 2169
76.5%
/ 581
 
20.5%
85
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13289
82.4%
ASCII 2835
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
| 2169
76.5%
/ 581
 
20.5%
85
 
3.0%
Hangul
ValueCountFrequency (%)
화 1272
 
9.6%
문 1258
 
9.5%
재 1181
 
8.9%
산 586
 
4.4%
유 585
 
4.4%
구 571
 
4.3%
장 570
 
4.3%
분 569
 
4.3%
소 481
 
3.6%
물 437
 
3.3%
Other values (97) 5779
43.5%

명칭
Text

Distinct959
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-04-06T19:54:05.724999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length9.8761062
Min length2

Characters and Unicode

Total characters10044
Distinct characters968
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique911 ?
Unique (%)89.6%

Sample

1st row해공 신익희 가옥
2nd row원서동 백홍범 가옥
3rd row백사 이항복 집터(필운대)
4th row한용운(韓龍雲, 1879-1944)家
5th row세검정 터
ValueCountFrequency (%)
터 82
 
4.0%
서울 40
 
1.9%
대사관 21
 
1.0%
드라마 19
 
0.9%
박물관 16
 
0.8%
가옥 16
 
0.8%
집터 15
 
0.7%
창덕궁 15
 
0.7%
mbc 14
 
0.7%
14
 
0.7%
Other values (1466) 1801
87.7%
2024-04-06T19:54:06.644217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1054
 
10.5%
) 248
 
2.5%
( 248
 
2.5%
관 233
 
2.3%
터 230
 
2.3%
동 145
 
1.4%
사 140
 
1.4%
대 117
 
1.2%
서 114
 
1.1%
문 111
 
1.1%
Other values (958) 7404
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7852
78.2%
Space Separator 1054
 
10.5%
Decimal Number 288
 
2.9%
Close Punctuation 286
 
2.8%
Open Punctuation 286
 
2.8%
Uppercase Letter 106
 
1.1%
Other Punctuation 104
 
1.0%
Connector Punctuation 16
 
0.2%
Lowercase Letter 16
 
0.2%
Math Symbol 14
 
0.1%
Other values (3) 22
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 233
 
3.0%
터 230
 
2.9%
동 145
 
1.8%
사 140
 
1.8%
대 117
 
1.5%
서 114
 
1.5%
문 111
 
1.4%
이 106
 
1.3%
화 99
 
1.3%
의 96
 
1.2%
Other values (904) 6461
82.3%
Uppercase Letter
ValueCountFrequency (%)
B 28
26.4%
S 26
24.5%
M 18
17.0%
C 18
17.0%
K 4
 
3.8%
Y 2
 
1.9%
A 2
 
1.9%
P 2
 
1.9%
H 1
 
0.9%
N 1
 
0.9%
Other values (4) 4
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 73
25.3%
2 64
22.2%
0 58
20.1%
3 26
 
9.0%
9 17
 
5.9%
8 13
 
4.5%
4 12
 
4.2%
5 9
 
3.1%
6 8
 
2.8%
7 8
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 37
35.6%
' 34
32.7%
/ 10
 
9.6%
. 9
 
8.7%
? 8
 
7.7%
& 2
 
1.9%
! 2
 
1.9%
: 1
 
1.0%
？ 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
18.8%
m 3
18.8%
k 2
12.5%
t 2
12.5%
e 2
12.5%
d 1
 
6.2%
l 1
 
6.2%
s 1
 
6.2%
p 1
 
6.2%
Math Symbol
ValueCountFrequency (%)
< 6
42.9%
> 6
42.9%
~ 2
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 248
86.7%
] 38
 
13.3%
Open Punctuation
ValueCountFrequency (%)
( 248
86.7%
[ 38
 
13.3%
Space Separator
ValueCountFrequency (%)
1054
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 6
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7104
70.7%
Common 2070
 
20.6%
Han 748
 
7.4%
Latin 122
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 233
 
3.3%
터 230
 
3.2%
동 145
 
2.0%
사 140
 
2.0%
대 117
 
1.6%
서 114
 
1.6%
문 111
 
1.6%
이 106
 
1.5%
화 99
 
1.4%
의 96
 
1.4%
Other values (536) 5713
80.4%
Han
ValueCountFrequency (%)
址 63
 
8.4%
家 17
 
2.3%
宮 15
 
2.0%
司 12
 
1.6%
漢 10
 
1.3%
城 9
 
1.2%
府 9
 
1.2%
署 9
 
1.2%
院 9
 
1.2%
寺 7
 
0.9%
Other values (358) 588
78.6%
Common
ValueCountFrequency (%)
1054
50.9%
) 248
 
12.0%
( 248
 
12.0%
1 73
 
3.5%
2 64
 
3.1%
0 58
 
2.8%
] 38
 
1.8%
[ 38
 
1.8%
, 37
 
1.8%
' 34
 
1.6%
Other values (21) 178
 
8.6%
Latin
ValueCountFrequency (%)
B 28
23.0%
S 26
21.3%
M 18
14.8%
C 18
14.8%
K 4
 
3.3%
a 3
 
2.5%
m 3
 
2.5%
Y 2
 
1.6%
k 2
 
1.6%
A 2
 
1.6%
Other values (13) 16
13.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7104
70.7%
ASCII 2182
 
21.7%
CJK 724
 
7.2%
CJK Compat Ideographs 24
 
0.2%
Punctuation 9
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1054
48.3%
) 248
 
11.4%
( 248
 
11.4%
1 73
 
3.3%
2 64
 
2.9%
0 58
 
2.7%
] 38
 
1.7%
[ 38
 
1.7%
, 37
 
1.7%
' 34
 
1.6%
Other values (41) 290
 
13.3%
Hangul
ValueCountFrequency (%)
관 233
 
3.3%
터 230
 
3.2%
동 145
 
2.0%
사 140
 
2.0%
대 117
 
1.6%
서 114
 
1.6%
문 111
 
1.6%
이 106
 
1.5%
화 99
 
1.4%
의 96
 
1.4%
Other values (536) 5713
80.4%
CJK
ValueCountFrequency (%)
址 63
 
8.7%
家 17
 
2.3%
宮 15
 
2.1%
司 12
 
1.7%
漢 10
 
1.4%
城 9
 
1.2%
府 9
 
1.2%
署 9
 
1.2%
院 9
 
1.2%
寺 7
 
1.0%
Other values (341) 564
77.9%
Punctuation
ValueCountFrequency (%)
‘ 6
66.7%
’ 3
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
李 5
20.8%
金 4
16.7%
里 1
 
4.2%
六 1
 
4.2%
禮 1
 
4.2%
女 1
 
4.2%
呂 1
 
4.2%
濾 1
 
4.2%
龜 1
 
4.2%
陸 1
 
4.2%
Other values (7) 7
29.2%
None
ValueCountFrequency (%)
？ 1
100.0%

주소
Text

MISSING 

Distinct713
Distinct (%)86.6%
Missing194
Missing (%)19.1%
Memory size8.1 KiB
2024-04-06T19:54:07.277663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33
Mean length18.839611
Min length3

Characters and Unicode

Total characters15505
Distinct characters239
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique639 ?
Unique (%)77.6%

Sample

1st row서울특별시 종로구 효자동 164-2
2nd row서울특별시 종로구 원서동 9-5
3rd row서울특별시 종로구 필운동 산1-2
4th row서울특별시 종로구 계동 43
5th row서울특별시 종로구 신영동 168-6
ValueCountFrequency (%)
종로구 796
22.9%
서울특별시 531
 
15.3%
서울시 187
 
5.4%
동숭동 80
 
2.3%
세종로 43
 
1.2%
관훈동 35
 
1.0%
일반 33
 
1.0%
와룡동 32
 
0.9%
평창동 28
 
0.8%
부암동 23
 
0.7%
Other values (806) 1683
48.5%
2024-04-06T19:54:08.230758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2685
17.3%
로 946
 
6.1%
종 895
 
5.8%
구 816
 
5.3%
1 797
 
5.1%
서 768
 
5.0%
동 753
 
4.9%
울 749
 
4.8%
시 726
 
4.7%
별 534
 
3.4%
Other values (229) 5836
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9543
61.5%
Space Separator 2685
 
17.3%
Decimal Number 2648
 
17.1%
Dash Punctuation 522
 
3.4%
Uppercase Letter 43
 
0.3%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%
Other Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 946
 
9.9%
종 895
 
9.4%
구 816
 
8.6%
서 768
 
8.0%
동 753
 
7.9%
울 749
 
7.8%
시 726
 
7.6%
별 534
 
5.6%
특 533
 
5.6%
지 256
 
2.7%
Other values (196) 2567
26.9%
Uppercase Letter
ValueCountFrequency (%)
B 12
27.9%
F 5
11.6%
E 4
 
9.3%
S 3
 
7.0%
D 3
 
7.0%
A 2
 
4.7%
O 2
 
4.7%
L 2
 
4.7%
C 2
 
4.7%
M 2
 
4.7%
Other values (5) 6
14.0%
Decimal Number
ValueCountFrequency (%)
1 797
30.1%
2 376
14.2%
3 253
 
9.6%
4 217
 
8.2%
8 197
 
7.4%
5 191
 
7.2%
7 173
 
6.5%
0 155
 
5.9%
9 146
 
5.5%
6 143
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 9
50.0%
. 3
 
16.7%
? 3
 
16.7%
/ 3
 
16.7%
Space Separator
ValueCountFrequency (%)
2685
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 522
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9543
61.5%
Common 5919
38.2%
Latin 43
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 946
 
9.9%
종 895
 
9.4%
구 816
 
8.6%
서 768
 
8.0%
동 753
 
7.9%
울 749
 
7.8%
시 726
 
7.6%
별 534
 
5.6%
특 533
 
5.6%
지 256
 
2.7%
Other values (196) 2567
26.9%
Common
ValueCountFrequency (%)
2685
45.4%
1 797
 
13.5%
- 522
 
8.8%
2 376
 
6.4%
3 253
 
4.3%
4 217
 
3.7%
8 197
 
3.3%
5 191
 
3.2%
7 173
 
2.9%
0 155
 
2.6%
Other values (8) 353
 
6.0%
Latin
ValueCountFrequency (%)
B 12
27.9%
F 5
11.6%
E 4
 
9.3%
S 3
 
7.0%
D 3
 
7.0%
A 2
 
4.7%
O 2
 
4.7%
L 2
 
4.7%
C 2
 
4.7%
M 2
 
4.7%
Other values (5) 6
14.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9543
61.5%
ASCII 5962
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2685
45.0%
1 797
 
13.4%
- 522
 
8.8%
2 376
 
6.3%
3 253
 
4.2%
4 217
 
3.6%
8 197
 
3.3%
5 191
 
3.2%
7 173
 
2.9%
0 155
 
2.6%
Other values (23) 396
 
6.6%
Hangul
ValueCountFrequency (%)
로 946
 
9.9%
종 895
 
9.4%
구 816
 
8.6%
서 768
 
8.0%
동 753
 
7.9%
울 749
 
7.8%
시 726
 
7.6%
별 534
 
5.6%
특 533
 
5.6%
지 256
 
2.7%
Other values (196) 2567
26.9%

행정 시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
서울특별시
821 
<NA>
196 

Length

Max length5
Median length5
Mean length4.8072763
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 821
80.7%
<NA> 196
 
19.3%

Length

2024-04-06T19:54:08.454744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:54:08.649523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 821
80.7%
na 196
 
19.3%

행정 구
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
종로구
811 
<NA>
196 
중구
 
9
용산구
 
1

Length

Max length4
Median length3
Mean length3.1838741
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 811
79.7%
<NA> 196
 
19.3%
중구 9
 
0.9%
용산구 1
 
0.1%

Length

2024-04-06T19:54:08.833083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:54:09.025482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 811
79.7%
na 196
 
19.3%
중구 9
 
0.9%
용산구 1
 
0.1%

행정 동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
종로1.2.3.4가동
218 
<NA>
196 
이화동
113 
사직동
85 
가회동
71 
Other values (18)
334 

Length

Max length11
Median length7
Mean length5.0943953
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row청운효자동
2nd row가회동
3rd row사직동
4th row가회동
5th row부암동

Common Values

ValueCountFrequency (%)
종로1.2.3.4가동 218
21.4%
<NA> 196
19.3%
이화동 113
11.1%
사직동 85
 
8.4%
가회동 71
 
7.0%
혜화동 67
 
6.6%
삼청동 65
 
6.4%
청운효자동 63
 
6.2%
부암동 41
 
4.0%
평창동 37
 
3.6%
Other values (13) 61
 
6.0%

Length

2024-04-06T19:54:09.241254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로1.2.3.4가동 218
21.4%
na 196
19.3%
이화동 113
11.1%
사직동 85
 
8.4%
가회동 71
 
7.0%
혜화동 67
 
6.6%
삼청동 65
 
6.4%
청운효자동 63
 
6.2%
부암동 41
 
4.0%
평창동 37
 
3.6%
Other values (13) 61
 
6.0%

전화번호
Text

MISSING 

Distinct313
Distinct (%)85.5%
Missing651
Missing (%)64.0%
Memory size8.1 KiB
2024-04-06T19:54:09.611451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length11
Mean length11.734973
Min length6

Characters and Unicode

Total characters4295
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)74.6%

Sample

1st row02-3217-6484
2nd row02-394-6411
3rd row02-379-3182
4th row02-2075-0114
5th row02-399-1114
ValueCountFrequency (%)
02-766-6494 4
 
1.1%
02-766-3315 3
 
0.8%
02-396-9277 3
 
0.8%
02-3673-2778 3
 
0.8%
02-2148-4171 3
 
0.8%
02-766-6000 3
 
0.8%
02-766-0272 3
 
0.8%
02-741-5978 3
 
0.8%
02-2148-4175 3
 
0.8%
02-730-1610 3
 
0.8%
Other values (307) 343
91.7%
2024-04-06T19:54:10.282978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 735
17.1%
0 678
15.8%
2 619
14.4%
7 504
11.7%
3 359
8.4%
6 267
 
6.2%
4 267
 
6.2%
1 267
 
6.2%
5 200
 
4.7%
8 170
 
4.0%
Other values (5) 229
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3494
81.4%
Dash Punctuation 735
 
17.1%
Math Symbol 37
 
0.9%
Other Punctuation 16
 
0.4%
Space Separator 13
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 678
19.4%
2 619
17.7%
7 504
14.4%
3 359
10.3%
6 267
 
7.6%
4 267
 
7.6%
1 267
 
7.6%
5 200
 
5.7%
8 170
 
4.9%
9 163
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 15
93.8%
? 1
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 735
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4295
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 735
17.1%
0 678
15.8%
2 619
14.4%
7 504
11.7%
3 359
8.4%
6 267
 
6.2%
4 267
 
6.2%
1 267
 
6.2%
5 200
 
4.7%
8 170
 
4.0%
Other values (5) 229
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 735
17.1%
0 678
15.8%
2 619
14.4%
7 504
11.7%
3 359
8.4%
6 267
 
6.2%
4 267
 
6.2%
1 267
 
6.2%
5 200
 
4.7%
8 170
 
4.0%
Other values (5) 229
 
5.3%

홈페이지주소
Text

MISSING 

Distinct268
Distinct (%)83.0%
Missing694
Missing (%)68.2%
Memory size8.1 KiB
2024-04-06T19:54:10.692409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length121
Median length64
Mean length29.495356
Min length11

Characters and Unicode

Total characters9527
Distinct characters64
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

Unique225 ?
Unique (%)69.7%

Sample

1st rowhttp://www.kimchongyung.com
2nd rowhttp://www.hjmuseum.or.kr/museum/main.asp
3rd rowhttp://yisunshinstory.or.kr
4th rowhttp://www.much.go.kr
5th rowhttp://www.daelimmuseum.org/index.do
ValueCountFrequency (%)
http://www.ijongno.co.kr 5
 
1.5%
http://www.arkoartcenter.or.kr 3
 
0.9%
http://www.medicalmuseum.org 3
 
0.9%
http://www.sejongpac.or.kr 3
 
0.9%
http://www.hansangsoo.com 3
 
0.9%
http://www.wjmuseum.com 3
 
0.9%
http://www.kokdumuseum.com 3
 
0.9%
http://www.zipul.co.kr 3
 
0.9%
http://www.mokkumto.com 3
 
0.9%
http://bukchon.seoul.go.kr 3
 
0.9%
Other values (257) 292
90.1%
2024-04-06T19:54:11.331316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 838
 
8.8%
/ 831
 
8.7%
w 795
 
8.3%
t 791
 
8.3%
o 598
 
6.3%
r 460
 
4.8%
m 441
 
4.6%
h 420
 
4.4%
a 409
 
4.3%
e 387
 
4.1%
Other values (54) 3557
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7271
76.3%
Other Punctuation 1988
 
20.9%
Decimal Number 151
 
1.6%
Uppercase Letter 31
 
0.3%
Math Symbol 28
 
0.3%
Connector Punctuation 26
 
0.3%
Space Separator 17
 
0.2%
Dash Punctuation 10
 
0.1%
Other Letter 5
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 795
 
10.9%
t 791
 
10.9%
o 598
 
8.2%
r 460
 
6.3%
m 441
 
6.1%
h 420
 
5.8%
a 409
 
5.6%
e 387
 
5.3%
p 381
 
5.2%
c 345
 
4.7%
Other values (16) 2244
30.9%
Uppercase Letter
ValueCountFrequency (%)
C 8
25.8%
L 5
16.1%
S 3
 
9.7%
H 3
 
9.7%
N 2
 
6.5%
G 2
 
6.5%
M 2
 
6.5%
B 1
 
3.2%
V 1
 
3.2%
T 1
 
3.2%
Other values (3) 3
 
9.7%
Decimal Number
ValueCountFrequency (%)
0 56
37.1%
1 26
17.2%
2 15
 
9.9%
6 12
 
7.9%
4 10
 
6.6%
5 10
 
6.6%
7 8
 
5.3%
9 7
 
4.6%
3 6
 
4.0%
8 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 838
42.2%
/ 831
41.8%
: 292
 
14.7%
& 15
 
0.8%
? 12
 
0.6%
Other Letter
ValueCountFrequency (%)
켓 1
20.0%
티 1
20.0%
로 1
20.0%
학 1
20.0%
대 1
20.0%
Math Symbol
ValueCountFrequency (%)
= 27
96.4%
~ 1
 
3.6%
Connector Punctuation
ValueCountFrequency (%)
_ 26
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7302
76.6%
Common 2220
 
23.3%
Hangul 5
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 795
 
10.9%
t 791
 
10.8%
o 598
 
8.2%
r 460
 
6.3%
m 441
 
6.0%
h 420
 
5.8%
a 409
 
5.6%
e 387
 
5.3%
p 381
 
5.2%
c 345
 
4.7%
Other values (29) 2275
31.2%
Common
ValueCountFrequency (%)
. 838
37.7%
/ 831
37.4%
: 292
 
13.2%
0 56
 
2.5%
= 27
 
1.2%
1 26
 
1.2%
_ 26
 
1.2%
17
 
0.8%
2 15
 
0.7%
& 15
 
0.7%
Other values (10) 77
 
3.5%
Hangul
ValueCountFrequency (%)
켓 1
20.0%
티 1
20.0%
로 1
20.0%
학 1
20.0%
대 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9522
99.9%
Hangul 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 838
 
8.8%
/ 831
 
8.7%
w 795
 
8.3%
t 791
 
8.3%
o 598
 
6.3%
r 460
 
4.8%
m 441
 
4.6%
h 420
 
4.4%
a 409
 
4.3%
e 387
 
4.1%
Other values (49) 3552
37.3%
Hangul
ValueCountFrequency (%)
켓 1
20.0%
티 1
20.0%
로 1
20.0%
학 1
20.0%
대 1
20.0%

HTML사용여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Y
1017 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 1017
100.0%

Length

2024-04-06T19:54:11.573733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:54:11.722457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 1017
100.0%

X 좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct560
Distinct (%)69.1%
Missing207
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean126.98635
Minimum126.95502
Maximum127.27336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-04-06T19:54:11.897310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95502
5-th percentile126.96292
Q1126.97677
median126.98524
Q3126.99891
95-th percentile127.00493
Maximum127.27336
Range0.3183397
Interquartile range (IQR)0.0221404

Descriptive statistics

Standard deviation0.017113246
Coefficient of variation (CV)0.00013476446
Kurtosis96.530878
Mean126.98635
Median Absolute Deviation (MAD)0.0101675
Skewness5.8053225
Sum102858.94
Variance0.00029286319
MonotonicityNot monotonic
2024-04-06T19:54:12.144562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9913206 14
 
1.4%
126.979642 14
 
1.4%
126.9767743 11
 
1.1%
126.9950431 10
 
1.0%
127.0037106 7
 
0.7%
126.9580981 7
 
0.7%
126.9864633 6
 
0.6%
126.9769632 5
 
0.5%
126.9895626 5
 
0.5%
126.9823368 5
 
0.5%
Other values (550) 726
71.4%
(Missing) 207
 
20.4%
ValueCountFrequency (%)
126.9550229 1
 
0.1%
126.955532 1
 
0.1%
126.9556779 1
 
0.1%
126.9556804 2
 
0.2%
126.9560406 2
 
0.2%
126.9562643 1
 
0.1%
126.956449 1
 
0.1%
126.9570008 1
 
0.1%
126.9574 1
 
0.1%
126.9580981 7
0.7%
ValueCountFrequency (%)
127.2733626 1
 
0.1%
127.0187664 1
 
0.1%
127.0183336 4
0.4%
127.0176267 1
 
0.1%
127.0173078 1
 
0.1%
127.0167666 1
 
0.1%
127.0162555 1
 
0.1%
127.0154862 1
 
0.1%
127.014448 1
 
0.1%
127.0141832 1
 
0.1%

Y 좌표
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct560
Distinct (%)69.1%
Missing207
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean37.579837
Minimum37.015224
Maximum37.631481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-04-06T19:54:12.348757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.015224
5-th percentile37.569884
Q137.573901
median37.579719
Q337.583683
95-th percentile37.601344
Maximum37.631481
Range0.6162566
Interquartile range (IQR)0.009782

Descriptive statistics

Standard deviation0.022238075
Coefficient of variation (CV)0.00059175548
Kurtosis514.82002
Mean37.579837
Median Absolute Deviation (MAD)0.0050142
Skewness-20.105879
Sum30439.668
Variance0.00049453197
MonotonicityNot monotonic
2024-04-06T19:54:12.529680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5827758 14
 
1.4%
37.573033 14
 
1.4%
37.5866061 11
 
1.1%
37.5805909 10
 
1.0%
37.5836832 7
 
0.7%
37.5760084 7
 
0.7%
37.5843579 6
 
0.6%
37.5705897 5
 
0.5%
37.5807844 5
 
0.5%
37.5739012 5
 
0.5%
Other values (550) 726
71.4%
(Missing) 207
 
20.4%
ValueCountFrequency (%)
37.0152241 1
0.1%
37.5343949 1
0.1%
37.5599933 1
0.1%
37.562758 1
0.1%
37.5627724 1
0.1%
37.564438 1
0.1%
37.56661 1
0.1%
37.5673135 1
0.1%
37.5675045 2
0.2%
37.567967 1
0.1%
ValueCountFrequency (%)
37.6314807 1
0.1%
37.6312731 1
0.1%
37.6269949 2
0.2%
37.6238013 1
0.1%
37.6227107 1
0.1%
37.6179 1
0.1%
37.6143517 1
0.1%
37.6143202 1
0.1%
37.6134542 1
0.1%
37.6130429 2
0.2%

Interactions

2024-04-06T19:54:01.989374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:54:01.599018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:54:02.180386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:54:01.790586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:54:12.657979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류행정 구행정 동X 좌표Y 좌표
분류1.0000.4290.7760.5660.283
행정 구0.4291.0001.0000.0000.644
행정 동0.7761.0001.0000.7450.554
X 좌표0.5660.0000.7451.0000.676
Y 좌표0.2830.6440.5540.6761.000
2024-04-06T19:54:12.818382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정 시행정 구행정 동
행정 시1.0001.0001.000
행정 구1.0001.0000.988
행정 동1.0000.9881.000
2024-04-06T19:54:12.970268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X 좌표Y 좌표행정 시행정 구행정 동
X 좌표1.000-0.0411.0000.0000.497
Y 좌표-0.0411.0001.0000.3070.343
행정 시1.0001.0001.0001.0001.000
행정 구0.0000.3071.0001.0000.988
행정 동0.4970.3431.0000.9881.000

Missing values

2024-04-06T19:54:02.416712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:54:02.742823image/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.
2024-04-06T19:54:02.997323image/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

키분류명칭주소행정 시행정 구행정 동전화번호홈페이지주소HTML사용여부X 좌표Y 좌표
0BE_IW10-0474문화재유산|문화재구분|가옥해공 신익희 가옥서울특별시 종로구 효자동 164-2서울특별시종로구청운효자동<NA><NA>Y126.97232437.581993
1BE_IW10-0475문화재유산|문화재구분|가옥원서동 백홍범 가옥서울특별시 종로구 원서동 9-5서울특별시종로구가회동<NA><NA>Y126.98848837.583711
2BE_IW10-0499문화재유산|문화재구분|누정백사 이항복 집터(필운대)서울특별시 종로구 필운동 산1-2서울특별시종로구사직동<NA><NA>Y126.96630837.578115
3BE_IW10-0527문화재유산|문화재구분|예술가의집한용운(韓龍雲, 1879-1944)家서울특별시 종로구 계동 43서울특별시종로구가회동<NA><NA>Y126.98703537.581515
4BE_IW10-0500문화재유산|문화재구분|누정세검정 터서울특별시 종로구 신영동 168-6서울특별시종로구부암동<NA><NA>Y126.96027437.600817
5BE_IW10-0501문화재유산|문화재구분|누정보신각 터서울특별시 종로구 관철동 45-5서울특별시종로구종로1.2.3.4가동<NA><NA>Y126.98358437.569842
6BE_IW10-0502문화재유산|문화재구분|누정황학정서울특별시 종로구 사직동 산1-1서울특별시종로구사직동<NA><NA>Y126.96853737.57649
7BE_IW10-0503문화재유산|문화재구분|누정안평대군 이용 집터서울특별시 종로구 부암동 319-4서울특별시종로구부암동<NA><NA>Y126.96284137.591618
8BE_IW10-0504문화재유산|문화재구분|누정침류각서울특별시 종로구 세종로 1서울특별시종로구청운효자동<NA><NA>Y126.97677437.586606
9BE_IW10-0514문화재유산|문화재구분|예술가의집시인 윤동주가 하숙하던 집종로구 누상동 9번지서울특별시종로구청운효자동<NA><NA>Y126.96567937.581451
키분류명칭주소행정 시행정 구행정 동전화번호홈페이지주소HTML사용여부X 좌표Y 좌표
1007BE_IW10-1000장소/위치|종로여행|박물관투어|가회동 박물관명인박물관서울특별시 종로구 가회동 208-7서울특별시종로구가회동02-766-0272http://www.myeonginmuseum.com/Y126.98520137.580179
1008BE_IW10-1001대학로 명소|마로니에공원마로니에공원서울특별시 종로구 동숭동 1-124서울특별시종로구이화동02-2148-1114http://www.visitseoul.net/kr/article/article.do?_method=view&m=0004003002017&p=03&art_id=501&lang=krY127.00272737.580522
1009BE_IW10-0955장소/위치|종로여행이화동(타임머신 타고 추억여행길) _ 약 2시간 30분<NA><NA><NA><NA><NA><NA>Y<NA><NA>
1010BE_IW10-0956장소/위치|종로여행북촌한옥마을(북촌코스/가회동코스/계동코스) _ 택1<NA><NA><NA><NA><NA><NA>Y<NA><NA>
1011BE_IW10-1002대학로 명소|낙산공원낙산공원서울특별시 종로구 낙산길 54서울특별시종로구이화동02-743-7985http://www.visitseoul.net/kr/article/article.do?_method=view&m=0004003002017&p=kr&art_id=751&lang=kr&tab=mapY127.00727537.580454
1012BE_IW10-1003대학로 명소|이화동 벽화마을이화동 벽화마을이화동서울특별시종로구이화동<NA><NA>Y127.00433837.577008
1013BE_IW10-0957장소/위치|시설|민간시설|종로문화원종로문화원서울특별시 종로구 중학동 24서울특별시종로구종로1.2.3.4가동02-2148-4087~8<NA>Y126.98031637.576093
1014BE_IW10-0958장소/위치|시설|민간시설|세종문화회관세종문화회관서울시 종로구 세종로 81-3서울특별시종로구사직동02-399-1111http://www.sejongpac.or.kr/Y126.97607537.572231
1015BE_IW10-1004대학로 박물관 / 갤러리|대학로 박물관쇳대박물관종로구 이화장길 100서울특별시종로구이화동02-766-6494http://lockmuseum.co.kr/Y127.00462637.579811
1016BE_IW10-1005대학로 박물관 / 갤러리|대학로 박물관짚풀생활사박물관종로구 성균관로4길 45서울특별시종로구혜화동02-743-8787http://www.zipul.co.krY126.99986137.584911