Overview

Dataset statistics

Number of variables22
Number of observations924
Missing cells2640
Missing cells (%)13.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory163.5 KiB
Average record size in memory181.1 B

Variable types

Text14
Categorical2
Numeric5
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15021141/standard.do

Alerts

관광지구분 is highly imbalanced (79.3%)Imbalance
지원시설정보 is highly imbalanced (78.2%)Imbalance
소재지도로명주소 has 75 (8.1%) missing valuesMissing
소재지지번주소 has 145 (15.7%) missing valuesMissing
숙박시설정보 has 625 (67.6%) missing valuesMissing
운동및오락시설정보 has 644 (69.7%) missing valuesMissing
휴양및문화시설정보 has 482 (52.2%) missing valuesMissing
접객시설정보 has 669 (72.4%) missing valuesMissing
면적 has 20 (2.2%) zerosZeros
수용인원수 has 31 (3.4%) zerosZeros
주차가능수 has 109 (11.8%) zerosZeros

Reproduction

Analysis started2024-05-11 10:40:58.293987
Analysis finished2024-05-11 10:41:03.862194
Duration5.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지명
Text

Distinct815
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:04.287272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.8041126
Min length2

Characters and Unicode

Total characters6287
Distinct characters478
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique706 ?
Unique (%)76.4%

Sample

1st row일제 경성호국신사 계단(108계단)
2nd row찬바람재
3rd row옛 남영동 대공분실(민주인권기념관)
4th row옛 용산공설시장(현 남영아케이드)
5th row전쟁기념관
ValueCountFrequency (%)
관광지 14
 
1.2%
휴양마을 10
 
0.9%
농촌체험 10
 
0.9%
문경 7
 
0.6%
in 5
 
0.4%
부군당 5
 
0.4%
별밤미술관 5
 
0.4%
옛 5
 
0.4%
구 4
 
0.3%
서울 4
 
0.3%
Other values (939) 1094
94.1%
2024-05-11T10:41:05.743550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 305
 
4.9%
241
 
3.8%
지 220
 
3.5%
광 180
 
2.9%
원 130
 
2.1%
산 128
 
2.0%
사 109
 
1.7%
공 89
 
1.4%
대 88
 
1.4%
장 83
 
1.3%
Other values (468) 4714
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5922
94.2%
Space Separator 241
 
3.8%
Close Punctuation 27
 
0.4%
Decimal Number 27
 
0.4%
Open Punctuation 26
 
0.4%
Other Punctuation 17
 
0.3%
Lowercase Letter 15
 
0.2%
Uppercase Letter 10
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 305
 
5.2%
지 220
 
3.7%
광 180
 
3.0%
원 130
 
2.2%
산 128
 
2.2%
사 109
 
1.8%
공 89
 
1.5%
대 88
 
1.5%
장 83
 
1.4%
천 83
 
1.4%
Other values (438) 4507
76.1%
Decimal Number
ValueCountFrequency (%)
1 9
33.3%
0 4
14.8%
8 3
 
11.1%
2 3
 
11.1%
3 3
 
11.1%
4 2
 
7.4%
6 1
 
3.7%
7 1
 
3.7%
9 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
F 2
20.0%
B 1
10.0%
I 1
10.0%
N 1
10.0%
D 1
10.0%
Z 1
10.0%
M 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
i 6
40.0%
n 5
33.3%
e 2
 
13.3%
d 1
 
6.7%
a 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
& 11
64.7%
, 3
 
17.6%
. 2
 
11.8%
· 1
 
5.9%
Space Separator
ValueCountFrequency (%)
241
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5922
94.2%
Common 340
 
5.4%
Latin 25
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 305
 
5.2%
지 220
 
3.7%
광 180
 
3.0%
원 130
 
2.2%
산 128
 
2.2%
사 109
 
1.8%
공 89
 
1.5%
대 88
 
1.5%
장 83
 
1.4%
천 83
 
1.4%
Other values (438) 4507
76.1%
Common
ValueCountFrequency (%)
241
70.9%
) 27
 
7.9%
( 26
 
7.6%
& 11
 
3.2%
1 9
 
2.6%
0 4
 
1.2%
8 3
 
0.9%
2 3
 
0.9%
3 3
 
0.9%
, 3
 
0.9%
Other values (7) 10
 
2.9%
Latin
ValueCountFrequency (%)
i 6
24.0%
n 5
20.0%
S 2
 
8.0%
e 2
 
8.0%
F 2
 
8.0%
d 1
 
4.0%
B 1
 
4.0%
I 1
 
4.0%
a 1
 
4.0%
N 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5922
94.2%
ASCII 364
 
5.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 305
 
5.2%
지 220
 
3.7%
광 180
 
3.0%
원 130
 
2.2%
산 128
 
2.2%
사 109
 
1.8%
공 89
 
1.5%
대 88
 
1.5%
장 83
 
1.4%
천 83
 
1.4%
Other values (438) 4507
76.1%
ASCII
ValueCountFrequency (%)
241
66.2%
) 27
 
7.4%
( 26
 
7.1%
& 11
 
3.0%
1 9
 
2.5%
i 6
 
1.6%
n 5
 
1.4%
0 4
 
1.1%
8 3
 
0.8%
2 3
 
0.8%
Other values (19) 29
 
8.0%
None
ValueCountFrequency (%)
· 1
100.0%

관광지구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
관광지
894 
관광단지
 
30

Length

Max length4
Median length3
Mean length3.0324675
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 894
96.8%
관광단지 30
 
3.2%

Length

2024-05-11T10:41:06.220941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:41:06.687893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 894
96.8%
관광단지 30
 
3.2%

소재지도로명주소
Text

MISSING 

Distinct776
Distinct (%)91.4%
Missing75
Missing (%)8.1%
Memory size7.3 KiB
2024-05-11T10:41:07.418374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length20.792697
Min length14

Characters and Unicode

Total characters17653
Distinct characters373
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

Unique711 ?
Unique (%)83.7%

Sample

1st row서울특별시 용산구 신흥로22가길 33
2nd row서울특별시 용산구 녹사평대로 195
3rd row서울특별시 용산구 한강대로71길 37
4th row서울특별시 용산구 한강대로84길 7
5th row서울특별시 용산구 이태원로 29
ValueCountFrequency (%)
전라남도 174
 
4.4%
경상남도 100
 
2.5%
전라북도 84
 
2.1%
강원도 66
 
1.7%
부산광역시 64
 
1.6%
서울특별시 62
 
1.6%
경상북도 60
 
1.5%
곡성군 46
 
1.2%
경기도 45
 
1.1%
강원특별자치도 45
 
1.1%
Other values (1605) 3209
81.1%
2024-05-11T10:41:08.820435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3106
 
17.6%
도 720
 
4.1%
1 584
 
3.3%
로 564
 
3.2%
시 537
 
3.0%
면 425
 
2.4%
남 400
 
2.3%
2 395
 
2.2%
길 391
 
2.2%
군 352
 
2.0%
Other values (363) 10179
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11422
64.7%
Space Separator 3106
 
17.6%
Decimal Number 2824
 
16.0%
Dash Punctuation 185
 
1.0%
Open Punctuation 55
 
0.3%
Close Punctuation 55
 
0.3%
Uppercase Letter 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 720
 
6.3%
로 564
 
4.9%
시 537
 
4.7%
면 425
 
3.7%
남 400
 
3.5%
길 391
 
3.4%
군 352
 
3.1%
전 303
 
2.7%
산 302
 
2.6%
라 260
 
2.3%
Other values (344) 7168
62.8%
Decimal Number
ValueCountFrequency (%)
1 584
20.7%
2 395
14.0%
3 287
10.2%
4 256
9.1%
5 248
8.8%
6 237
8.4%
7 214
 
7.6%
8 205
 
7.3%
0 204
 
7.2%
9 194
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
E 1
25.0%
P 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
3106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11422
64.7%
Common 6227
35.3%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 720
 
6.3%
로 564
 
4.9%
시 537
 
4.7%
면 425
 
3.7%
남 400
 
3.5%
길 391
 
3.4%
군 352
 
3.1%
전 303
 
2.7%
산 302
 
2.6%
라 260
 
2.3%
Other values (344) 7168
62.8%
Common
ValueCountFrequency (%)
3106
49.9%
1 584
 
9.4%
2 395
 
6.3%
3 287
 
4.6%
4 256
 
4.1%
5 248
 
4.0%
6 237
 
3.8%
7 214
 
3.4%
8 205
 
3.3%
0 204
 
3.3%
Other values (5) 491
 
7.9%
Latin
ValueCountFrequency (%)
C 1
25.0%
E 1
25.0%
P 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11422
64.7%
ASCII 6231
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3106
49.8%
1 584
 
9.4%
2 395
 
6.3%
3 287
 
4.6%
4 256
 
4.1%
5 248
 
4.0%
6 237
 
3.8%
7 214
 
3.4%
8 205
 
3.3%
0 204
 
3.3%
Other values (9) 495
 
7.9%
Hangul
ValueCountFrequency (%)
도 720
 
6.3%
로 564
 
4.9%
시 537
 
4.7%
면 425
 
3.7%
남 400
 
3.5%
길 391
 
3.4%
군 352
 
3.1%
전 303
 
2.7%
산 302
 
2.6%
라 260
 
2.3%
Other values (344) 7168
62.8%

소재지지번주소
Text

MISSING 

Distinct736
Distinct (%)94.5%
Missing145
Missing (%)15.7%
Memory size7.3 KiB
2024-05-11T10:41:09.641998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length20.156611
Min length12

Characters and Unicode

Total characters15702
Distinct characters286
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique696 ?
Unique (%)89.3%

Sample

1st row서울특별시 용산구 용산동2가 1-346
2nd row서울특별시 용산구 용산동2가 7-99
3rd row서울특별시 용산구 갈월동 98-8
4th row서울특별시 용산구 남영동 28-8
5th row서울특별시 용산구 용산동1가 8
ValueCountFrequency (%)
전라남도 177
 
4.9%
경상남도 92
 
2.5%
부산광역시 64
 
1.8%
강원도 63
 
1.7%
서울특별시 60
 
1.7%
경기도 55
 
1.5%
곡성군 54
 
1.5%
경상북도 47
 
1.3%
강원특별자치도 42
 
1.2%
용산구 42
 
1.2%
Other values (1558) 2939
80.9%
2024-05-11T10:41:11.138097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2856
 
18.2%
도 633
 
4.0%
1 576
 
3.7%
시 500
 
3.2%
리 492
 
3.1%
- 451
 
2.9%
동 398
 
2.5%
면 391
 
2.5%
산 376
 
2.4%
남 363
 
2.3%
Other values (276) 8666
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9651
61.5%
Space Separator 2856
 
18.2%
Decimal Number 2737
 
17.4%
Dash Punctuation 451
 
2.9%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 633
 
6.6%
시 500
 
5.2%
리 492
 
5.1%
동 398
 
4.1%
면 391
 
4.1%
산 376
 
3.9%
남 363
 
3.8%
군 320
 
3.3%
전 254
 
2.6%
구 229
 
2.4%
Other values (261) 5695
59.0%
Decimal Number
ValueCountFrequency (%)
1 576
21.0%
2 361
13.2%
5 288
10.5%
3 287
10.5%
4 271
9.9%
6 203
 
7.4%
7 194
 
7.1%
9 193
 
7.1%
0 192
 
7.0%
8 172
 
6.3%
Space Separator
ValueCountFrequency (%)
2856
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9651
61.5%
Common 6051
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 633
 
6.6%
시 500
 
5.2%
리 492
 
5.1%
동 398
 
4.1%
면 391
 
4.1%
산 376
 
3.9%
남 363
 
3.8%
군 320
 
3.3%
전 254
 
2.6%
구 229
 
2.4%
Other values (261) 5695
59.0%
Common
ValueCountFrequency (%)
2856
47.2%
1 576
 
9.5%
- 451
 
7.5%
2 361
 
6.0%
5 288
 
4.8%
3 287
 
4.7%
4 271
 
4.5%
6 203
 
3.4%
7 194
 
3.2%
9 193
 
3.2%
Other values (5) 371
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9651
61.5%
ASCII 6051
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2856
47.2%
1 576
 
9.5%
- 451
 
7.5%
2 361
 
6.0%
5 288
 
4.8%
3 287
 
4.7%
4 271
 
4.5%
6 203
 
3.4%
7 194
 
3.2%
9 193
 
3.2%
Other values (5) 371
 
6.1%
Hangul
ValueCountFrequency (%)
도 633
 
6.6%
시 500
 
5.2%
리 492
 
5.1%
동 398
 
4.1%
면 391
 
4.1%
산 376
 
3.9%
남 363
 
3.8%
군 320
 
3.3%
전 254
 
2.6%
구 229
 
2.4%
Other values (261) 5695
59.0%

위도
Real number (ℝ)

Distinct815
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.095549
Minimum33.233427
Maximum38.514386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-11T10:41:11.684584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.233427
5-th percentile34.783279
Q135.149124
median35.789877
Q337.350444
95-th percentile37.946124
Maximum38.514386
Range5.2809587
Interquartile range (IQR)2.2013204

Descriptive statistics

Standard deviation1.1446756
Coefficient of variation (CV)0.031712375
Kurtosis-0.97178249
Mean36.095549
Median Absolute Deviation (MAD)0.77727334
Skewness0.2910612
Sum33352.288
Variance1.3102822
MonotonicityNot monotonic
2024-05-11T10:41:12.272815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.98879491 6
 
0.6%
35.04638172 3
 
0.3%
35.13195828 3
 
0.3%
37.3765839984 2
 
0.2%
35.43111098 2
 
0.2%
37.92741327 2
 
0.2%
38.481345 2
 
0.2%
38.18542141 2
 
0.2%
38.05555608 2
 
0.2%
37.47034344 2
 
0.2%
Other values (805) 898
97.2%
ValueCountFrequency (%)
33.23342738 1
0.1%
33.23697818 1
0.1%
33.23799399 1
0.1%
33.2447447 1
0.1%
33.24474912 1
0.1%
33.2526783 1
0.1%
33.27159304 1
0.1%
33.3934958502 1
0.1%
33.44004881 1
0.1%
33.4443253 1
0.1%
ValueCountFrequency (%)
38.51438609 2
0.2%
38.481345 2
0.2%
38.47250515 2
0.2%
38.47218738 2
0.2%
38.33623615 2
0.2%
38.32452923 1
0.1%
38.31963688 1
0.1%
38.2900609 1
0.1%
38.28900491 1
0.1%
38.246783 1
0.1%

경도
Real number (ℝ)

Distinct813
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.71999
Minimum126.07251
Maximum129.56653
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-11T10:41:12.694227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.07251
5-th percentile126.52575
Q1127.00912
median127.47761
Q3128.5407
95-th percentile129.08306
Maximum129.56653
Range3.4940202
Interquartile range (IQR)1.5315804

Descriptive statistics

Standard deviation0.84900489
Coefficient of variation (CV)0.0066473926
Kurtosis-1.1718547
Mean127.71999
Median Absolute Deviation (MAD)0.65119914
Skewness0.28014778
Sum118013.27
Variance0.72080931
MonotonicityNot monotonic
2024-05-11T10:41:13.249178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.261342 6
 
0.6%
127.3863807 3
 
0.3%
128.9680068 3
 
0.3%
129.3079336 2
 
0.2%
128.435682 2
 
0.2%
127.2874037 2
 
0.2%
126.7405968 2
 
0.2%
128.5128997 2
 
0.2%
128.7948611 2
 
0.2%
128.6641979 2
 
0.2%
Other values (803) 898
97.2%
ValueCountFrequency (%)
126.0725117 1
0.1%
126.1169337 1
0.1%
126.1465709 1
0.1%
126.2310334 1
0.1%
126.2385968886 1
0.1%
126.2853294 2
0.2%
126.2999810075 1
0.1%
126.3041171 1
0.1%
126.3101147 1
0.1%
126.312306 1
0.1%
ValueCountFrequency (%)
129.5665319 1
0.1%
129.4190152574 1
0.1%
129.3794409 1
0.1%
129.3755938 1
0.1%
129.3591079 1
0.1%
129.3460154287 1
0.1%
129.343467 1
0.1%
129.3079336 2
0.2%
129.2869659 1
0.1%
129.2795067 1
0.1%

면적
Real number (ℝ)

ZEROS 

Distinct738
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean585651.15
Minimum0
Maximum47920000
Zeros20
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-11T10:41:13.784551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40
Q11862.25
median26603.5
Q3210278
95-th percentile2382454.9
Maximum47920000
Range47920000
Interquartile range (IQR)208415.75

Descriptive statistics

Standard deviation2780151.9
Coefficient of variation (CV)4.7471125
Kurtosis133.02885
Mean585651.15
Median Absolute Deviation (MAD)26522.118
Skewness10.290776
Sum5.4114166 × 108
Variance7.7292447 × 1012
MonotonicityNot monotonic
2024-05-11T10:41:14.350372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
2.2%
1.0 11
 
1.2%
10029.0 6
 
0.6%
10000.0 6
 
0.6%
3000.0 5
 
0.5%
130000.0 4
 
0.4%
40.0 4
 
0.4%
16000.0 4
 
0.4%
30.0 3
 
0.3%
150000.0 3
 
0.3%
Other values (728) 858
92.9%
ValueCountFrequency (%)
0.0 20
2.2%
1.0 11
1.2%
6.0 1
 
0.1%
10.9 1
 
0.1%
17.0 1
 
0.1%
20.0 1
 
0.1%
26.0 1
 
0.1%
28.8 1
 
0.1%
29.0 2
 
0.2%
29.26 1
 
0.1%
ValueCountFrequency (%)
47920000.0 1
0.1%
31400000.0 2
0.2%
19580000.0 2
0.2%
16900000.0 2
0.2%
16855179.0 1
0.1%
16219204.0 2
0.2%
12000000.0 1
0.1%
8980000.0 1
0.1%
8515243.0 1
0.1%
7052479.2 2
0.2%

공공편익시설정보
Text

Distinct367
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:14.807699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length85
Mean length12.386364
Min length1

Characters and Unicode

Total characters11445
Distinct characters335
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)26.1%

Sample

1st row승강기
2nd row승강기
3rd row화장실
4th row화장실
5th row화장실+주차장+물품보관함+수유실
ValueCountFrequency (%)
화장실 161
 
13.2%
주차장 86
 
7.0%
화장실+주차장 68
 
5.6%
주차장+화장실 59
 
4.8%
28
 
2.3%
관리사무소+화장실+주차장 24
 
2.0%
등 15
 
1.2%
공중화장실 12
 
1.0%
y 12
 
1.0%
전기시설 12
 
1.0%
Other values (466) 745
61.0%
2024-05-11T10:41:15.856146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1454
 
12.7%
+ 1454
 
12.7%
실 787
 
6.9%
화 706
 
6.2%
차 572
 
5.0%
주 568
 
5.0%
소 403
 
3.5%
관 315
 
2.8%
298
 
2.6%
사 245
 
2.1%
Other values (325) 4643
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8972
78.4%
Math Symbol 1455
 
12.7%
Space Separator 298
 
2.6%
Decimal Number 247
 
2.2%
Open Punctuation 188
 
1.6%
Close Punctuation 188
 
1.6%
Other Punctuation 59
 
0.5%
Uppercase Letter 33
 
0.3%
Dash Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1454
16.2%
실 787
 
8.8%
화 706
 
7.9%
차 572
 
6.4%
주 568
 
6.3%
소 403
 
4.5%
관 315
 
3.5%
사 245
 
2.7%
리 229
 
2.6%
무 211
 
2.4%
Other values (292) 3482
38.8%
Decimal Number
ValueCountFrequency (%)
1 83
33.6%
2 64
25.9%
3 34
13.8%
4 19
 
7.7%
5 16
 
6.5%
6 14
 
5.7%
7 6
 
2.4%
8 5
 
2.0%
9 5
 
2.0%
0 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
Y 12
36.4%
N 5
15.2%
T 3
 
9.1%
A 3
 
9.1%
M 3
 
9.1%
C 2
 
6.1%
F 2
 
6.1%
X 1
 
3.0%
L 1
 
3.0%
D 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 53
89.8%
. 3
 
5.1%
/ 2
 
3.4%
· 1
 
1.7%
Math Symbol
ValueCountFrequency (%)
+ 1454
99.9%
= 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
m 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 188
100.0%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8972
78.4%
Common 2438
 
21.3%
Latin 35
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1454
16.2%
실 787
 
8.8%
화 706
 
7.9%
차 572
 
6.4%
주 568
 
6.3%
소 403
 
4.5%
관 315
 
3.5%
사 245
 
2.7%
리 229
 
2.6%
무 211
 
2.4%
Other values (292) 3482
38.8%
Common
ValueCountFrequency (%)
+ 1454
59.6%
298
 
12.2%
( 188
 
7.7%
) 188
 
7.7%
1 83
 
3.4%
2 64
 
2.6%
, 53
 
2.2%
3 34
 
1.4%
4 19
 
0.8%
5 16
 
0.7%
Other values (11) 41
 
1.7%
Latin
ValueCountFrequency (%)
Y 12
34.3%
N 5
14.3%
T 3
 
8.6%
A 3
 
8.6%
M 3
 
8.6%
C 2
 
5.7%
F 2
 
5.7%
m 1
 
2.9%
X 1
 
2.9%
k 1
 
2.9%
Other values (2) 2
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8972
78.4%
ASCII 2471
 
21.6%
CJK Compat 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1454
16.2%
실 787
 
8.8%
화 706
 
7.9%
차 572
 
6.4%
주 568
 
6.3%
소 403
 
4.5%
관 315
 
3.5%
사 245
 
2.7%
리 229
 
2.6%
무 211
 
2.4%
Other values (292) 3482
38.8%
ASCII
ValueCountFrequency (%)
+ 1454
58.8%
298
 
12.1%
( 188
 
7.6%
) 188
 
7.6%
1 83
 
3.4%
2 64
 
2.6%
, 53
 
2.1%
3 34
 
1.4%
4 19
 
0.8%
5 16
 
0.6%
Other values (21) 74
 
3.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

숙박시설정보
Text

MISSING 

Distinct153
Distinct (%)51.2%
Missing625
Missing (%)67.6%
Memory size7.3 KiB
2024-05-11T10:41:16.635153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length8.7993311
Min length1

Characters and Unicode

Total characters2631
Distinct characters249
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)33.8%

Sample

1st row카라반 캠핑장
2nd row없음
3rd row카라반+글램핑+오토캠핑장
4th row없음
5th row문수산농원펜션, 동막골캠프,문소골산장,김포관광농원,평화누리길게스트하우스
ValueCountFrequency (%)
n 35
 
8.0%
관광호텔 25
 
5.7%
해당없음 10
 
2.3%
휴양콘도미니엄 10
 
2.3%
펜션 9
 
2.0%
등 9
 
2.0%
없음 9
 
2.0%
호텔 7
 
1.6%
캠핑장 7
 
1.6%
콘도+호텔 6
 
1.4%
Other values (203) 313
71.1%
2024-05-11T10:41:18.073088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 172
 
6.5%
141
 
5.4%
텔 128
 
4.9%
호 105
 
4.0%
관 61
 
2.3%
도 58
 
2.2%
콘 57
 
2.2%
션 48
 
1.8%
장 47
 
1.8%
광 46
 
1.7%
Other values (239) 1768
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2092
79.5%
Math Symbol 172
 
6.5%
Space Separator 141
 
5.4%
Decimal Number 101
 
3.8%
Uppercase Letter 38
 
1.4%
Other Punctuation 31
 
1.2%
Open Punctuation 24
 
0.9%
Close Punctuation 24
 
0.9%
Lowercase Letter 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 128
 
6.1%
호 105
 
5.0%
관 61
 
2.9%
도 58
 
2.8%
콘 57
 
2.7%
션 48
 
2.3%
장 47
 
2.2%
광 46
 
2.2%
펜 45
 
2.2%
박 40
 
1.9%
Other values (215) 1457
69.6%
Decimal Number
ValueCountFrequency (%)
1 25
24.8%
2 16
15.8%
3 12
11.9%
0 10
 
9.9%
9 7
 
6.9%
6 7
 
6.9%
8 7
 
6.9%
5 7
 
6.9%
7 6
 
5.9%
4 4
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
N 35
92.1%
D 1
 
2.6%
Z 1
 
2.6%
M 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 27
87.1%
· 2
 
6.5%
/ 2
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
o 4
50.0%
l 2
25.0%
p 2
25.0%
Math Symbol
ValueCountFrequency (%)
+ 172
100.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2092
79.5%
Common 493
 
18.7%
Latin 46
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 128
 
6.1%
호 105
 
5.0%
관 61
 
2.9%
도 58
 
2.8%
콘 57
 
2.7%
션 48
 
2.3%
장 47
 
2.2%
광 46
 
2.2%
펜 45
 
2.2%
박 40
 
1.9%
Other values (215) 1457
69.6%
Common
ValueCountFrequency (%)
+ 172
34.9%
141
28.6%
, 27
 
5.5%
1 25
 
5.1%
( 24
 
4.9%
) 24
 
4.9%
2 16
 
3.2%
3 12
 
2.4%
0 10
 
2.0%
9 7
 
1.4%
Other values (7) 35
 
7.1%
Latin
ValueCountFrequency (%)
N 35
76.1%
o 4
 
8.7%
l 2
 
4.3%
p 2
 
4.3%
D 1
 
2.2%
Z 1
 
2.2%
M 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2092
79.5%
ASCII 537
 
20.4%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 172
32.0%
141
26.3%
N 35
 
6.5%
, 27
 
5.0%
1 25
 
4.7%
( 24
 
4.5%
) 24
 
4.5%
2 16
 
3.0%
3 12
 
2.2%
0 10
 
1.9%
Other values (13) 51
 
9.5%
Hangul
ValueCountFrequency (%)
텔 128
 
6.1%
호 105
 
5.0%
관 61
 
2.9%
도 58
 
2.8%
콘 57
 
2.7%
션 48
 
2.3%
장 47
 
2.2%
광 46
 
2.2%
펜 45
 
2.2%
박 40
 
1.9%
Other values (215) 1457
69.6%
None
ValueCountFrequency (%)
· 2
100.0%

운동및오락시설정보
Text

MISSING 

Distinct182
Distinct (%)65.0%
Missing644
Missing (%)69.7%
Memory size7.3 KiB
2024-05-11T10:41:18.762825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length37
Mean length9.6357143
Min length1

Characters and Unicode

Total characters2698
Distinct characters352
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)50.0%

Sample

1st row가야무사어드벤처+익사이팅 사이클+익사이팅 타워
2nd row낙동강레일바이크
3rd row14종의 유기기구
4th row전통놀이체험
5th row다목적운동장+체력단련장+전통놀이광장
ValueCountFrequency (%)
n 24
 
6.6%
y 12
 
3.3%
등 12
 
3.3%
해당없음 10
 
2.7%
족구장 7
 
1.9%
스키장+골프장 6
 
1.6%
골프장 5
 
1.4%
다목적운동장 5
 
1.4%
골프장+스키장 4
 
1.1%
없음 4
 
1.1%
Other values (226) 276
75.6%
2024-05-11T10:41:19.934268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 241
 
8.9%
장 215
 
8.0%
86
 
3.2%
이 85
 
3.2%
체 54
 
2.0%
스 50
 
1.9%
시 49
 
1.8%
프 46
 
1.7%
구 44
 
1.6%
험 41
 
1.5%
Other values (342) 1787
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2236
82.9%
Math Symbol 241
 
8.9%
Space Separator 86
 
3.2%
Uppercase Letter 57
 
2.1%
Decimal Number 31
 
1.1%
Other Punctuation 14
 
0.5%
Open Punctuation 10
 
0.4%
Close Punctuation 10
 
0.4%
Lowercase Letter 10
 
0.4%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 215
 
9.6%
이 85
 
3.8%
체 54
 
2.4%
스 50
 
2.2%
시 49
 
2.2%
프 46
 
2.1%
구 44
 
2.0%
험 41
 
1.8%
골 40
 
1.8%
놀 37
 
1.7%
Other values (305) 1575
70.4%
Uppercase Letter
ValueCountFrequency (%)
N 24
42.1%
Y 12
21.1%
R 5
 
8.8%
V 4
 
7.0%
X 3
 
5.3%
B 2
 
3.5%
S 1
 
1.8%
M 1
 
1.8%
T 1
 
1.8%
E 1
 
1.8%
Other values (3) 3
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 14
45.2%
3 5
 
16.1%
2 4
 
12.9%
4 2
 
6.5%
8 2
 
6.5%
6 2
 
6.5%
9 1
 
3.2%
7 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
a 2
20.0%
c 1
10.0%
p 1
10.0%
l 1
10.0%
k 1
10.0%
b 1
10.0%
i 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 12
85.7%
※ 1
 
7.1%
: 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
+ 241
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2236
82.9%
Common 395
 
14.6%
Latin 67
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 215
 
9.6%
이 85
 
3.8%
체 54
 
2.4%
스 50
 
2.2%
시 49
 
2.2%
프 46
 
2.1%
구 44
 
2.0%
험 41
 
1.8%
골 40
 
1.8%
놀 37
 
1.7%
Other values (305) 1575
70.4%
Latin
ValueCountFrequency (%)
N 24
35.8%
Y 12
17.9%
R 5
 
7.5%
V 4
 
6.0%
X 3
 
4.5%
e 2
 
3.0%
B 2
 
3.0%
a 2
 
3.0%
c 1
 
1.5%
p 1
 
1.5%
Other values (11) 11
16.4%
Common
ValueCountFrequency (%)
+ 241
61.0%
86
 
21.8%
1 14
 
3.5%
, 12
 
3.0%
( 10
 
2.5%
) 10
 
2.5%
3 5
 
1.3%
2 4
 
1.0%
- 3
 
0.8%
4 2
 
0.5%
Other values (6) 8
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2236
82.9%
ASCII 461
 
17.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 241
52.3%
86
 
18.7%
N 24
 
5.2%
1 14
 
3.0%
Y 12
 
2.6%
, 12
 
2.6%
( 10
 
2.2%
) 10
 
2.2%
3 5
 
1.1%
R 5
 
1.1%
Other values (26) 42
 
9.1%
Hangul
ValueCountFrequency (%)
장 215
 
9.6%
이 85
 
3.8%
체 54
 
2.4%
스 50
 
2.2%
시 49
 
2.2%
프 46
 
2.1%
구 44
 
2.0%
험 41
 
1.8%
골 40
 
1.8%
놀 37
 
1.7%
Other values (305) 1575
70.4%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

휴양및문화시설정보
Text

MISSING 

Distinct284
Distinct (%)64.3%
Missing482
Missing (%)52.2%
Memory size7.3 KiB
2024-05-11T10:41:20.411247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length41
Mean length12.411765
Min length1

Characters and Unicode

Total characters5486
Distinct characters415
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

Unique202 ?
Unique (%)45.7%

Sample

1st row철광산공연장
2nd row와인동굴+철교전망대
3rd row전시동+관측동
4th row문수산삼림욕장
5th row한옥마을,문화원,카페,공방,꽃집,
ValueCountFrequency (%)
등 27
 
4.5%
n 15
 
2.5%
야영장 15
 
2.5%
y 12
 
2.0%
전시실 11
 
1.8%
및 10
 
1.7%
박물관 9
 
1.5%
주차장+화장실 8
 
1.3%
전시관 8
 
1.3%
주차장 6
 
1.0%
Other values (355) 478
79.8%
2024-05-11T10:41:21.741110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 552
 
10.1%
장 256
 
4.7%
관 209
 
3.8%
158
 
2.9%
원 113
 
2.1%
전 111
 
2.0%
시 107
 
2.0%
공 95
 
1.7%
야 76
 
1.4%
물 76
 
1.4%
Other values (405) 3733
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4628
84.4%
Math Symbol 552
 
10.1%
Space Separator 158
 
2.9%
Decimal Number 34
 
0.6%
Uppercase Letter 32
 
0.6%
Other Punctuation 31
 
0.6%
Close Punctuation 26
 
0.5%
Open Punctuation 25
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 256
 
5.5%
관 209
 
4.5%
원 113
 
2.4%
전 111
 
2.4%
시 107
 
2.3%
공 95
 
2.1%
야 76
 
1.6%
물 76
 
1.6%
화 66
 
1.4%
수 61
 
1.3%
Other values (381) 3458
74.7%
Decimal Number
ValueCountFrequency (%)
2 9
26.5%
1 9
26.5%
3 3
 
8.8%
6 3
 
8.8%
5 3
 
8.8%
0 3
 
8.8%
9 2
 
5.9%
4 1
 
2.9%
7 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 15
46.9%
Y 12
37.5%
K 1
 
3.1%
B 1
 
3.1%
J 1
 
3.1%
I 1
 
3.1%
C 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 27
87.1%
/ 2
 
6.5%
※ 1
 
3.2%
. 1
 
3.2%
Math Symbol
ValueCountFrequency (%)
+ 552
100.0%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4628
84.4%
Common 826
 
15.1%
Latin 32
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 256
 
5.5%
관 209
 
4.5%
원 113
 
2.4%
전 111
 
2.4%
시 107
 
2.3%
공 95
 
2.1%
야 76
 
1.6%
물 76
 
1.6%
화 66
 
1.4%
수 61
 
1.3%
Other values (381) 3458
74.7%
Common
ValueCountFrequency (%)
+ 552
66.8%
158
 
19.1%
, 27
 
3.3%
) 26
 
3.1%
( 25
 
3.0%
2 9
 
1.1%
1 9
 
1.1%
3 3
 
0.4%
6 3
 
0.4%
5 3
 
0.4%
Other values (7) 11
 
1.3%
Latin
ValueCountFrequency (%)
N 15
46.9%
Y 12
37.5%
K 1
 
3.1%
B 1
 
3.1%
J 1
 
3.1%
I 1
 
3.1%
C 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4628
84.4%
ASCII 857
 
15.6%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 552
64.4%
158
 
18.4%
, 27
 
3.2%
) 26
 
3.0%
( 25
 
2.9%
N 15
 
1.8%
Y 12
 
1.4%
2 9
 
1.1%
1 9
 
1.1%
3 3
 
0.4%
Other values (13) 21
 
2.5%
Hangul
ValueCountFrequency (%)
장 256
 
5.5%
관 209
 
4.5%
원 113
 
2.4%
전 111
 
2.4%
시 107
 
2.3%
공 95
 
2.1%
야 76
 
1.6%
물 76
 
1.6%
화 66
 
1.4%
수 61
 
1.3%
Other values (381) 3458
74.7%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

접객시설정보
Text

MISSING 

Distinct112
Distinct (%)43.9%
Missing669
Missing (%)72.4%
Memory size7.3 KiB
2024-05-11T10:41:22.319127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length24
Mean length6.7058824
Min length1

Characters and Unicode

Total characters1710
Distinct characters218
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

Unique65 ?
Unique (%)25.5%

Sample

1st row열차카페
2nd row음식점
3rd row다목적홀+공연장+카페
4th rowN
5th rowN
ValueCountFrequency (%)
n 23
 
7.2%
안내소 21
 
6.6%
관광식당 15
 
4.7%
음식점 8
 
2.5%
주차장+화장실 8
 
2.5%
등 8
 
2.5%
카페 7
 
2.2%
관리사무소 7
 
2.2%
카페테리아 6
 
1.9%
주차장 6
 
1.9%
Other values (135) 211
65.9%
2024-05-11T10:41:23.464228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 123
 
7.2%
장 73
 
4.3%
관 67
 
3.9%
65
 
3.8%
소 55
 
3.2%
식 45
 
2.6%
실 40
 
2.3%
당 39
 
2.3%
카 38
 
2.2%
안 37
 
2.2%
Other values (208) 1128
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1412
82.6%
Math Symbol 124
 
7.3%
Space Separator 65
 
3.8%
Decimal Number 40
 
2.3%
Uppercase Letter 24
 
1.4%
Close Punctuation 21
 
1.2%
Open Punctuation 21
 
1.2%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 73
 
5.2%
관 67
 
4.7%
소 55
 
3.9%
식 45
 
3.2%
실 40
 
2.8%
당 39
 
2.8%
카 38
 
2.7%
안 37
 
2.6%
내 37
 
2.6%
페 35
 
2.5%
Other values (191) 946
67.0%
Decimal Number
ValueCountFrequency (%)
2 9
22.5%
1 7
17.5%
3 6
15.0%
5 6
15.0%
0 5
12.5%
4 4
10.0%
7 1
 
2.5%
6 1
 
2.5%
8 1
 
2.5%
Math Symbol
ValueCountFrequency (%)
+ 123
99.2%
~ 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N 23
95.8%
D 1
 
4.2%
Space Separator
ValueCountFrequency (%)
65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1412
82.6%
Common 274
 
16.0%
Latin 24
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 73
 
5.2%
관 67
 
4.7%
소 55
 
3.9%
식 45
 
3.2%
실 40
 
2.8%
당 39
 
2.8%
카 38
 
2.7%
안 37
 
2.6%
내 37
 
2.6%
페 35
 
2.5%
Other values (191) 946
67.0%
Common
ValueCountFrequency (%)
+ 123
44.9%
65
23.7%
) 21
 
7.7%
( 21
 
7.7%
2 9
 
3.3%
1 7
 
2.6%
3 6
 
2.2%
5 6
 
2.2%
0 5
 
1.8%
4 4
 
1.5%
Other values (5) 7
 
2.6%
Latin
ValueCountFrequency (%)
N 23
95.8%
D 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1412
82.6%
ASCII 298
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 123
41.3%
65
21.8%
N 23
 
7.7%
) 21
 
7.0%
( 21
 
7.0%
2 9
 
3.0%
1 7
 
2.3%
3 6
 
2.0%
5 6
 
2.0%
0 5
 
1.7%
Other values (7) 12
 
4.0%
Hangul
ValueCountFrequency (%)
장 73
 
5.2%
관 67
 
4.7%
소 55
 
3.9%
식 45
 
3.2%
실 40
 
2.8%
당 39
 
2.8%
카 38
 
2.7%
안 37
 
2.6%
내 37
 
2.6%
페 35
 
2.5%
Other values (191) 946
67.0%

지원시설정보
Categorical

IMBALANCE 

Distinct49
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
<NA>
798 
관리사무소
 
14
Y
 
12
홈페이지 운영
 
11
해당없음
 
11
Other values (44)
 
78

Length

Max length34
Median length4
Mean length4.2380952
Min length1

Unique

Unique33 ?
Unique (%)3.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 798
86.4%
관리사무소 14
 
1.5%
Y 12
 
1.3%
홈페이지 운영 11
 
1.2%
해당없음 11
 
1.2%
없음 10
 
1.1%
관리사무실 8
 
0.9%
전용숙소 7
 
0.8%
무료 4
 
0.4%
사무실 3
 
0.3%
Other values (39) 46
 
5.0%

Length

2024-05-11T10:41:23.906856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 798
83.9%
관리사무소 14
 
1.5%
y 12
 
1.3%
홈페이지 11
 
1.2%
운영 11
 
1.2%
해당없음 11
 
1.2%
없음 10
 
1.1%
관리사무실 8
 
0.8%
전용숙소 7
 
0.7%
관광안내소 6
 
0.6%
Other values (51) 63
 
6.6%

지정일자
Text

Distinct587
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:24.667672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters9240
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)47.9%

Sample

1st row1905-04-26
2nd row2000-12-15
3rd row2024-12-01
4th row1920-01-01
5th row1994-06-10
ValueCountFrequency (%)
2021-06-16 38
 
4.1%
2021-09-01 32
 
3.5%
1979-12-03 19
 
2.1%
2019-01-01 12
 
1.3%
2020-07-07 11
 
1.2%
2000-01-01 10
 
1.1%
2017-03-14 8
 
0.9%
1900-01-01 8
 
0.9%
1963-01-21 8
 
0.9%
2016-03-21 7
 
0.8%
Other values (577) 771
83.4%
2024-05-11T10:41:26.005874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2216
24.0%
- 1848
20.0%
1 1701
18.4%
2 1247
13.5%
9 667
 
7.2%
7 319
 
3.5%
6 306
 
3.3%
8 275
 
3.0%
3 267
 
2.9%
5 207
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7392
80.0%
Dash Punctuation 1848
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2216
30.0%
1 1701
23.0%
2 1247
16.9%
9 667
 
9.0%
7 319
 
4.3%
6 306
 
4.1%
8 275
 
3.7%
3 267
 
3.6%
5 207
 
2.8%
4 187
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1848
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2216
24.0%
- 1848
20.0%
1 1701
18.4%
2 1247
13.5%
9 667
 
7.2%
7 319
 
3.5%
6 306
 
3.3%
8 275
 
3.0%
3 267
 
2.9%
5 207
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2216
24.0%
- 1848
20.0%
1 1701
18.4%
2 1247
13.5%
9 667
 
7.2%
7 319
 
3.5%
6 306
 
3.3%
8 275
 
3.0%
3 267
 
2.9%
5 207
 
2.2%

수용인원수
Real number (ℝ)

ZEROS 

Distinct143
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16069.999
Minimum0
Maximum1000000
Zeros31
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-11T10:41:26.584978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.75
Q1147.75
median870
Q35000
95-th percentile50000
Maximum1000000
Range1000000
Interquartile range (IQR)4852.25

Descriptive statistics

Standard deviation78034.056
Coefficient of variation (CV)4.8558843
Kurtosis84.745449
Mean16069.999
Median Absolute Deviation (MAD)820
Skewness8.6953582
Sum14848679
Variance6.0893138 × 109
MonotonicityNot monotonic
2024-05-11T10:41:27.413735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000 101
 
10.9%
10000 84
 
9.1%
100 76
 
8.2%
500 55
 
6.0%
200 51
 
5.5%
3000 43
 
4.7%
5000 38
 
4.1%
300 33
 
3.6%
0 31
 
3.4%
50 28
 
3.0%
Other values (133) 384
41.6%
ValueCountFrequency (%)
0 31
3.4%
1 1
 
0.1%
2 1
 
0.1%
5 4
 
0.4%
10 10
 
1.1%
15 6
 
0.6%
20 19
2.1%
25 1
 
0.1%
26 1
 
0.1%
30 16
1.7%
ValueCountFrequency (%)
1000000 1
 
0.1%
900000 1
 
0.1%
800000 2
0.2%
700000 2
0.2%
500000 4
0.4%
300000 2
0.2%
250000 2
0.2%
200000 2
0.2%
166200 2
0.2%
147272 1
 
0.1%

주차가능수
Real number (ℝ)

ZEROS 

Distinct236
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343.67424
Minimum0
Maximum24000
Zeros109
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-11T10:41:28.180796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median100
Q3300
95-th percentile1280.85
Maximum24000
Range24000
Interquartile range (IQR)280

Descriptive statistics

Standard deviation1098.8193
Coefficient of variation (CV)3.1972698
Kurtosis252.9681
Mean343.67424
Median Absolute Deviation (MAD)94
Skewness13.530921
Sum317555
Variance1207403.8
MonotonicityNot monotonic
2024-05-11T10:41:28.864673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 109
 
11.8%
100 81
 
8.8%
50 60
 
6.5%
20 39
 
4.2%
10 37
 
4.0%
1000 34
 
3.7%
30 27
 
2.9%
150 26
 
2.8%
200 26
 
2.8%
40 24
 
2.6%
Other values (226) 461
49.9%
ValueCountFrequency (%)
0 109
11.8%
1 1
 
0.1%
2 9
 
1.0%
3 1
 
0.1%
4 4
 
0.4%
5 15
 
1.6%
6 3
 
0.3%
7 2
 
0.2%
8 1
 
0.1%
9 4
 
0.4%
ValueCountFrequency (%)
24000 1
0.1%
10400 1
0.1%
10000 2
0.2%
5000 1
0.1%
3530 1
0.1%
3500 1
0.1%
3400 1
0.1%
3209 1
0.1%
3000 2
0.2%
2837 2
0.2%

관광지소개
Text

Distinct786
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:29.770485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1000
Median length271
Mean length100.62987
Min length1

Characters and Unicode

Total characters92982
Distinct characters1135
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique674 ?
Unique (%)72.9%

Sample

1st row일제강점기 경성호국신사에 참배하기 위해 오르던 진입로로, 완공까지 한국인들의 재산과 노동력이 동원되었다. 일제 말기 식민지 한국이 처했던 비극의 역사를 선명하게 보여주는 장소이다.
2nd row예전부터 겨울철 찬바람이 매섭게 몰아친다 하여 찬바람재 또는 한풍재라고도 불리던 곳이다. 현재는 이 일대를 푸른 풀이 무성한 들판이라는 뜻의 녹사평이라고 부르고 있다.
3rd row1970~80년대 민주주의를 억압하며 악명을 떨쳤던 남영동 대공분실은 1976년 지상5층 규모로 신축되어 치안본부 대공과 대공분실로 사용되었다. 2023년경 민주주의와 인권의 가치를 수호하는 민주인권기념관으로 정식 개관할 예정이다.
4th row1922년 일제가 설치한 시장으로 지금은 남영아케이드로 불리고 있다.
5th row1994년 용산에 건립된 전쟁기념관은 외침을 극복하고 국민의 생명과 재산을 지켜온 대외항쟁사와 민족의 자주독립을 지켜온 국난극복사 등 전쟁에 관한 자료를 수집,보존하고, 전쟁의 교훈을 통해 전쟁을 예방하여 조국의 평화적 통일을 이룩하는데 이바지하기 위해 세워졌다.
ValueCountFrequency (%)
수 304
 
1.5%
있는 288
 
1.4%
있다 276
 
1.3%
등 133
 
0.6%
있으며 90
 
0.4%
있어 88
 
0.4%
및 87
 
0.4%
다양한 84
 
0.4%
아름다운 60
 
0.3%
그 54
 
0.3%
Other values (10746) 19387
93.0%
2024-05-11T10:41:31.419807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19955
 
21.5%
이 1996
 
2.1%
다 1457
 
1.6%
의 1409
 
1.5%
는 1279
 
1.4%
을 1265
 
1.4%
로 1154
 
1.2%
에 1118
 
1.2%
있 1064
 
1.1%
. 1048
 
1.1%
Other values (1125) 61237
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67367
72.5%
Space Separator 19955
 
21.5%
Decimal Number 2424
 
2.6%
Other Punctuation 2159
 
2.3%
Open Punctuation 231
 
0.2%
Lowercase Letter 229
 
0.2%
Close Punctuation 227
 
0.2%
Math Symbol 159
 
0.2%
Uppercase Letter 81
 
0.1%
Final Punctuation 62
 
0.1%
Other values (4) 88
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1996
 
3.0%
다 1457
 
2.2%
의 1409
 
2.1%
는 1279
 
1.9%
을 1265
 
1.9%
로 1154
 
1.7%
에 1118
 
1.7%
있 1064
 
1.6%
한 1026
 
1.5%
고 964
 
1.4%
Other values (1046) 54635
81.1%
Uppercase Letter
ValueCountFrequency (%)
Y 13
16.0%
D 8
 
9.9%
R 7
 
8.6%
M 7
 
8.6%
A 5
 
6.2%
C 5
 
6.2%
E 4
 
4.9%
B 4
 
4.9%
K 4
 
4.9%
G 3
 
3.7%
Other values (10) 21
25.9%
Lowercase Letter
ValueCountFrequency (%)
m 142
62.0%
k 47
 
20.5%
a 7
 
3.1%
l 5
 
2.2%
b 5
 
2.2%
i 4
 
1.7%
h 4
 
1.7%
o 3
 
1.3%
e 3
 
1.3%
c 3
 
1.3%
Other values (5) 6
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 469
19.3%
0 464
19.1%
2 313
12.9%
9 218
9.0%
3 183
 
7.5%
5 180
 
7.4%
4 165
 
6.8%
8 160
 
6.6%
6 137
 
5.7%
7 135
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 1048
48.5%
, 1033
47.8%
· 40
 
1.9%
， 16
 
0.7%
: 10
 
0.5%
/ 9
 
0.4%
* 3
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 132
83.0%
~ 19
 
11.9%
= 3
 
1.9%
∼ 3
 
1.9%
< 1
 
0.6%
> 1
 
0.6%
Other Symbol
ValueCountFrequency (%)
㎡ 17
45.9%
㎞ 8
21.6%
㎢ 7
18.9%
℃ 3
 
8.1%
▶ 1
 
2.7%
㈜ 1
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 201
88.5%
] 11
 
4.8%
」 10
 
4.4%
』 5
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 201
87.0%
「 14
 
6.1%
[ 11
 
4.8%
『 5
 
2.2%
Final Punctuation
ValueCountFrequency (%)
’ 58
93.5%
” 4
 
6.5%
Initial Punctuation
ValueCountFrequency (%)
‘ 36
92.3%
“ 3
 
7.7%
Space Separator
ValueCountFrequency (%)
19955
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67166
72.2%
Common 25304
 
27.2%
Latin 310
 
0.3%
Han 202
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1996
 
3.0%
다 1457
 
2.2%
의 1409
 
2.1%
는 1279
 
1.9%
을 1265
 
1.9%
로 1154
 
1.7%
에 1118
 
1.7%
있 1064
 
1.6%
한 1026
 
1.5%
고 964
 
1.4%
Other values (918) 54434
81.0%
Han
ValueCountFrequency (%)
山 18
 
8.9%
東 5
 
2.5%
輿 4
 
2.0%
寺 4
 
2.0%
故 3
 
1.5%
馬 3
 
1.5%
出 3
 
1.5%
田 3
 
1.5%
園 3
 
1.5%
地 3
 
1.5%
Other values (119) 153
75.7%
Common
ValueCountFrequency (%)
19955
78.9%
. 1048
 
4.1%
, 1033
 
4.1%
1 469
 
1.9%
0 464
 
1.8%
2 313
 
1.2%
9 218
 
0.9%
) 201
 
0.8%
( 201
 
0.8%
3 183
 
0.7%
Other values (33) 1219
 
4.8%
Latin
ValueCountFrequency (%)
m 142
45.8%
k 47
 
15.2%
Y 13
 
4.2%
D 8
 
2.6%
R 7
 
2.3%
a 7
 
2.3%
M 7
 
2.3%
l 5
 
1.6%
A 5
 
1.6%
b 5
 
1.6%
Other values (25) 64
20.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67162
72.2%
ASCII 25384
 
27.3%
CJK 195
 
0.2%
Punctuation 101
 
0.1%
None 91
 
0.1%
CJK Compat 32
 
< 0.1%
CJK Compat Ideographs 7
 
< 0.1%
Math Operators 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19955
78.6%
. 1048
 
4.1%
, 1033
 
4.1%
1 469
 
1.8%
0 464
 
1.8%
2 313
 
1.2%
9 218
 
0.9%
) 201
 
0.8%
( 201
 
0.8%
3 183
 
0.7%
Other values (52) 1299
 
5.1%
Hangul
ValueCountFrequency (%)
이 1996
 
3.0%
다 1457
 
2.2%
의 1409
 
2.1%
는 1279
 
1.9%
을 1265
 
1.9%
로 1154
 
1.7%
에 1118
 
1.7%
있 1064
 
1.6%
한 1026
 
1.5%
고 964
 
1.4%
Other values (916) 54430
81.0%
Punctuation
ValueCountFrequency (%)
’ 58
57.4%
‘ 36
35.6%
” 4
 
4.0%
“ 3
 
3.0%
None
ValueCountFrequency (%)
· 40
44.0%
， 16
 
17.6%
「 14
 
15.4%
」 10
 
11.0%
』 5
 
5.5%
『 5
 
5.5%
㈜ 1
 
1.1%
CJK
ValueCountFrequency (%)
山 18
 
9.2%
東 5
 
2.6%
輿 4
 
2.1%
寺 4
 
2.1%
故 3
 
1.5%
馬 3
 
1.5%
出 3
 
1.5%
田 3
 
1.5%
園 3
 
1.5%
地 3
 
1.5%
Other values (115) 146
74.9%
CJK Compat
ValueCountFrequency (%)
㎡ 17
53.1%
㎞ 8
25.0%
㎢ 7
21.9%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
凌 2
28.6%
樂 2
28.6%
金 2
28.6%
六 1
14.3%
Geometric Shapes
ValueCountFrequency (%)
▶ 1
100.0%

관리기관전화번호
Text

Distinct612
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:32.116888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.96645
Min length9

Characters and Unicode

Total characters11057
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique470 ?
Unique (%)50.9%

Sample

1st row02-2199-7240
2nd row02-2199-7240
3rd row031-361-9576
4th row02-2199-7240
5th row02-709-3114
ValueCountFrequency (%)
02-2199-7240 23
 
2.5%
033-330-2742 16
 
1.7%
051-519-4081 10
 
1.1%
033-640-5685 10
 
1.1%
033-570-3547 8
 
0.9%
055-880-2381 8
 
0.9%
053-665-2344 8
 
0.9%
063-0859-5827 8
 
0.9%
051-440-4815 8
 
0.9%
055-359-5639 8
 
0.9%
Other values (602) 817
88.4%
2024-05-11T10:41:33.179789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1855
16.8%
- 1837
16.6%
3 1253
11.3%
5 986
8.9%
2 914
8.3%
6 914
8.3%
4 828
7.5%
1 825
7.5%
7 593
 
5.4%
8 580
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9220
83.4%
Dash Punctuation 1837
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1855
20.1%
3 1253
13.6%
5 986
10.7%
2 914
9.9%
6 914
9.9%
4 828
9.0%
1 825
8.9%
7 593
 
6.4%
8 580
 
6.3%
9 472
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1837
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11057
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1855
16.8%
- 1837
16.6%
3 1253
11.3%
5 986
8.9%
2 914
8.3%
6 914
8.3%
4 828
7.5%
1 825
7.5%
7 593
 
5.4%
8 580
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1855
16.8%
- 1837
16.6%
3 1253
11.3%
5 986
8.9%
2 914
8.3%
6 914
8.3%
4 828
7.5%
1 825
7.5%
7 593
 
5.4%
8 580
 
5.2%

관리기관명
Text

Distinct345
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:33.957332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length9.8484848
Min length1

Characters and Unicode

Total characters9100
Distinct characters283
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

Unique178 ?
Unique (%)19.3%

Sample

1st row서울특별시 용산구청 문화체육과
2nd row서울특별시 용산구청 문화체육과
3rd row민주화운동기념사업회
4th row서울특별시 용산구청 문화체육과
5th row전쟁기념사업회
ValueCountFrequency (%)
전라남도 146
 
7.8%
경상남도 93
 
5.0%
전라북도 66
 
3.5%
강원도 59
 
3.2%
곡성군청 55
 
2.9%
문화체육과 48
 
2.6%
부산광역시 47
 
2.5%
경상북도 46
 
2.5%
경기도 46
 
2.5%
강원특별자치도 44
 
2.4%
Other values (362) 1218
65.2%
2024-05-11T10:41:35.004220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
944
 
10.4%
청 728
 
8.0%
도 609
 
6.7%
시 462
 
5.1%
군 344
 
3.8%
남 302
 
3.3%
광 245
 
2.7%
전 234
 
2.6%
라 218
 
2.4%
경 218
 
2.4%
Other values (273) 4796
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8103
89.0%
Space Separator 944
 
10.4%
Uppercase Letter 12
 
0.1%
Open Punctuation 11
 
0.1%
Close Punctuation 11
 
0.1%
Other Symbol 10
 
0.1%
Decimal Number 7
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 728
 
9.0%
도 609
 
7.5%
시 462
 
5.7%
군 344
 
4.2%
남 302
 
3.7%
광 245
 
3.0%
전 234
 
2.9%
라 218
 
2.7%
경 218
 
2.7%
과 177
 
2.2%
Other values (263) 4566
56.3%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
1 2
28.6%
2 2
28.6%
Uppercase Letter
ValueCountFrequency (%)
Y 7
58.3%
N 5
41.7%
Space Separator
ValueCountFrequency (%)
944
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8113
89.2%
Common 975
 
10.7%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 728
 
9.0%
도 609
 
7.5%
시 462
 
5.7%
군 344
 
4.2%
남 302
 
3.7%
광 245
 
3.0%
전 234
 
2.9%
라 218
 
2.7%
경 218
 
2.7%
과 177
 
2.2%
Other values (264) 4576
56.4%
Common
ValueCountFrequency (%)
944
96.8%
( 11
 
1.1%
) 11
 
1.1%
0 3
 
0.3%
1 2
 
0.2%
+ 2
 
0.2%
2 2
 
0.2%
Latin
ValueCountFrequency (%)
Y 7
58.3%
N 5
41.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8103
89.0%
ASCII 987
 
10.8%
None 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
944
95.6%
( 11
 
1.1%
) 11
 
1.1%
Y 7
 
0.7%
N 5
 
0.5%
0 3
 
0.3%
1 2
 
0.2%
+ 2
 
0.2%
2 2
 
0.2%
Hangul
ValueCountFrequency (%)
청 728
 
9.0%
도 609
 
7.5%
시 462
 
5.7%
군 344
 
4.2%
남 302
 
3.7%
광 245
 
3.0%
전 234
 
2.9%
라 218
 
2.7%
경 218
 
2.7%
과 177
 
2.2%
Other values (263) 4566
56.3%
None
ValueCountFrequency (%)
㈜ 10
100.0%

데이터기준일자
Date

Distinct133
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
Minimum2020-06-16 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T10:41:35.633155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:41:36.073441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Text

Distinct186
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:36.765153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters6468
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)5.1%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000
ValueCountFrequency (%)
4860000 55
 
6.0%
3020000 42
 
4.5%
5370000 28
 
3.0%
4840000 26
 
2.8%
4830000 23
 
2.5%
4820000 22
 
2.4%
4721000 19
 
2.1%
4720000 19
 
2.1%
3630000 14
 
1.5%
4800000 13
 
1.4%
Other values (176) 663
71.8%
2024-05-11T10:41:37.674711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3769
58.3%
4 672
 
10.4%
3 442
 
6.8%
5 355
 
5.5%
2 306
 
4.7%
8 255
 
3.9%
1 230
 
3.6%
7 185
 
2.9%
6 175
 
2.7%
9 78
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6467
> 99.9%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3769
58.3%
4 672
 
10.4%
3 442
 
6.8%
5 355
 
5.5%
2 306
 
4.7%
8 255
 
3.9%
1 230
 
3.6%
7 185
 
2.9%
6 175
 
2.7%
9 78
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6467
> 99.9%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3769
58.3%
4 672
 
10.4%
3 442
 
6.8%
5 355
 
5.5%
2 306
 
4.7%
8 255
 
3.9%
1 230
 
3.6%
7 185
 
2.9%
6 175
 
2.7%
9 78
 
1.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3769
58.3%
4 672
 
10.4%
3 442
 
6.8%
5 355
 
5.5%
2 306
 
4.7%
8 255
 
3.9%
1 230
 
3.6%
7 185
 
2.9%
6 175
 
2.7%
9 78
 
1.2%

제공기관명
Text

Distinct186
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-11T10:41:38.228156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.3722944
Min length5

Characters and Unicode

Total characters7736
Distinct characters125
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)5.1%

Sample

1st row서울특별시 용산구
2nd row서울특별시 용산구
3rd row서울특별시 용산구
4th row서울특별시 용산구
5th row서울특별시 용산구
ValueCountFrequency (%)
전라남도 194
 
10.6%
경상남도 111
 
6.0%
서울특별시 66
 
3.6%
경기도 65
 
3.5%
부산광역시 64
 
3.5%
강원도 63
 
3.4%
경상북도 59
 
3.2%
강원특별자치도 56
 
3.1%
곡성군 55
 
3.0%
전북특별자치도 50
 
2.7%
Other values (160) 1052
57.3%
2024-05-11T10:41:39.293800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
911
 
11.8%
도 741
 
9.6%
시 571
 
7.4%
군 381
 
4.9%
남 375
 
4.8%
전 309
 
4.0%
경 251
 
3.2%
라 244
 
3.2%
구 206
 
2.7%
북 200
 
2.6%
Other values (115) 3547
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6825
88.2%
Space Separator 911
 
11.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 741
 
10.9%
시 571
 
8.4%
군 381
 
5.6%
남 375
 
5.5%
전 309
 
4.5%
경 251
 
3.7%
라 244
 
3.6%
구 206
 
3.0%
북 200
 
2.9%
광 194
 
2.8%
Other values (114) 3353
49.1%
Space Separator
ValueCountFrequency (%)
911
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6825
88.2%
Common 911
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 741
 
10.9%
시 571
 
8.4%
군 381
 
5.6%
남 375
 
5.5%
전 309
 
4.5%
경 251
 
3.7%
라 244
 
3.6%
구 206
 
3.0%
북 200
 
2.9%
광 194
 
2.8%
Other values (114) 3353
49.1%
Common
ValueCountFrequency (%)
911
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6825
88.2%
ASCII 911
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
911
100.0%
Hangul
ValueCountFrequency (%)
도 741
 
10.9%
시 571
 
8.4%
군 381
 
5.6%
남 375
 
5.5%
전 309
 
4.5%
경 251
 
3.7%
라 244
 
3.6%
구 206
 
3.0%
북 200
 
2.9%
광 194
 
2.8%
Other values (114) 3353
49.1%

Sample

관광지명관광지구분소재지도로명주소소재지지번주소위도경도면적공공편익시설정보숙박시설정보운동및오락시설정보휴양및문화시설정보접객시설정보지원시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
0일제 경성호국신사 계단(108계단)관광지서울특별시 용산구 신흥로22가길 33서울특별시 용산구 용산동2가 1-34637.546023126.982542237.2승강기<NA><NA><NA><NA><NA>1905-04-26200일제강점기 경성호국신사에 참배하기 위해 오르던 진입로로, 완공까지 한국인들의 재산과 노동력이 동원되었다. 일제 말기 식민지 한국이 처했던 비극의 역사를 선명하게 보여주는 장소이다.02-2199-7240서울특별시 용산구청 문화체육과2022-12-073020000서울특별시 용산구
1찬바람재관광지서울특별시 용산구 녹사평대로 195서울특별시 용산구 용산동2가 7-9937.534815126.987014646.6승강기<NA><NA><NA><NA><NA>2000-12-15500예전부터 겨울철 찬바람이 매섭게 몰아친다 하여 찬바람재 또는 한풍재라고도 불리던 곳이다. 현재는 이 일대를 푸른 풀이 무성한 들판이라는 뜻의 녹사평이라고 부르고 있다.02-2199-7240서울특별시 용산구청 문화체육과2022-12-073020000서울특별시 용산구
2옛 남영동 대공분실(민주인권기념관)관광지서울특별시 용산구 한강대로71길 37서울특별시 용산구 갈월동 98-837.541012126.9716346391.0화장실<NA><NA><NA><NA><NA>2024-12-0143001970~80년대 민주주의를 억압하며 악명을 떨쳤던 남영동 대공분실은 1976년 지상5층 규모로 신축되어 치안본부 대공과 대공분실로 사용되었다. 2023년경 민주주의와 인권의 가치를 수호하는 민주인권기념관으로 정식 개관할 예정이다.031-361-9576민주화운동기념사업회2022-12-073020000서울특별시 용산구
3옛 용산공설시장(현 남영아케이드)관광지서울특별시 용산구 한강대로84길 7서울특별시 용산구 남영동 28-837.543723126.9729241449.0화장실<NA><NA><NA><NA><NA>1920-01-0110001922년 일제가 설치한 시장으로 지금은 남영아케이드로 불리고 있다.02-2199-7240서울특별시 용산구청 문화체육과2022-12-073020000서울특별시 용산구
4전쟁기념관관광지서울특별시 용산구 이태원로 29서울특별시 용산구 용산동1가 837.537314126.978466112887.2화장실+주차장+물품보관함+수유실<NA><NA><NA><NA><NA>1994-06-1075001501994년 용산에 건립된 전쟁기념관은 외침을 극복하고 국민의 생명과 재산을 지켜온 대외항쟁사와 민족의 자주독립을 지켜온 국난극복사 등 전쟁에 관한 자료를 수집,보존하고, 전쟁의 교훈을 통해 전쟁을 예방하여 조국의 평화적 통일을 이룩하는데 이바지하기 위해 세워졌다.02-709-3114전쟁기념사업회2022-12-073020000서울특별시 용산구
5당고개 순교성지관광지서울특별시 용산구 청파로 139-26서울특별시 용산구 신계동 5637.53559126.9669631752.0화장실<NA><NA><NA><NA><NA>1986-01-0112010이 일대는 조선후기에 처형장으로도 이용되었는데, 1839년 기해박해 당시 천주교 신자 10여명이 순교한 곳이다. 지금은 기해박해 당시 천주교 순교자들을 기리기 위해 당고개 순교성지가 들어서 있다.02-711-0933당고개 순교성지2022-12-073020000서울특별시 용산구
6옛 풍국제과 공장관광지서울특별시 용산구 백범로90다길 13서울특별시 용산구 문배동 30-1037.535672126.9695133086.0화장실+주차장<NA><NA><NA><NA><NA>1930-01-0120070풍국제과는 일제강점기 용산에 본사와 생산공장을 두었던 제과업체로 1934년 지금의 위치에 설립하였다. 해방 이후 풍국제과는 정부에 귀속되었다가 1956년 이양구가 인수해 동양제과공업 주식회사를 설립했다. 그 후 사업확장과 함께 2001년 제과업을 중심으로 하는 오리온 그룹이 동양그룹계열에서 분리되어 오늘날의 ㈜오리온이 되었다.02-710-6000오리온2022-12-073020000서울특별시 용산구
7용산신학교관광지서울특별시 용산구 원효로19길 49서울특별시 용산구 원효로4가 1-137.534209126.954593690.0주차장+쉼터+화장실<NA><NA><NA><NA><NA>2012-06-2050101892년에 세워졌으며, 프랑스인 코스트 신부가 설계, 감독 했다. 한국 최초의 신학교 건물이다.02-701-5501성심수녀회2022-12-073020000서울특별시 용산구
8서울 원효로 예수성심당관광지서울특별시 용산구 원효로19길 49서울특별시 용산구 원효로4가 1-137.534209126.954593709.0주차장<NA><NA><NA><NA><NA>2012-06-2050101902년에 세워졌으며, 프랑스인 코스트 신부가 설계, 감독 했다. 19세기 말의 성당 건축을 상징적으로 보여준다.02-701-5501성심수녀회2022-12-073020000서울특별시 용산구
9구 용산 수위관측소관광지<NA>서울특별시 용산구 청암동 169-137.533956126.94713210.9쉼터<NA><NA><NA><NA><NA>2002-02-0510한강변에서는 최초로, 전국에서는 아홉번째로 건립된 자기 관측소로서 조위와 홍수위를 관측할 목적으로 건립되었다.02-2199-7240서울특별시 용산구청 문화체육과2022-12-073020000서울특별시 용산구
관광지명관광지구분소재지도로명주소소재지지번주소위도경도면적공공편익시설정보숙박시설정보운동및오락시설정보휴양및문화시설정보접객시설정보지원시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
914계산관광지관광지<NA>충청북도 제천시 청풍면 계산리 9-437.017861128.130911135806.0주차장+도로+배수지오수처리장펜션운동장+눈썰매장조경휴게소+바비큐장+전망대<NA>완충녹지+원형보존녹지1998-07-24205760수상레저 및 수상마리나 등 수상연계관광 인프라 조성 및 비봉산모노레일 등과 연계 관광 인프라조성 목적 관광지043-641-6694충청북도 제천시청2023-10-114400000충청북도 제천시
915만남의광장관광지충청북도 제천시 청풍면 청풍호로50길 6충청북도 제천시 청풍면 교리 14737.010834128.181189147440.0도로+광장+공용주차장+매표소(매점)+화장실<NA>번지점프장+인공암벽장+종합관리동만남의광장+휴게쉼터+야생화원<NA><NA>2003-02-1322339264청풍호반 주변 관광시설과 연계한 핵심 관광거점으로 각종 관광시설이 집중된 제천관광의 중심지043-641-6694충청북도 제천시청2023-10-114400000충청북도 제천시
916제천 성내관광지관광지충청북도 제천시 금성면 청풍호로 1482충청북도 제천시 금성면 성내리 산12-237.033664128.175173111060.0도로+광장+주차장+관리동+화장실<NA><NA>촬영장+휴게쉼터<NA>전문음식점+기념품(토산품점)+녹지2004-08-27168270청풍호반의 뛰어난 장소적 특성을 활용한 문화영상 테마지구로 한류와 연계 국내외 영상테마 관광지043-641-6694충청북도 제천시청2023-10-114400000충청북도 제천시
917제천온천관광지관광지<NA>충청북도 제천시 수산면 내리 산2436.921834128.181971296700.0관리사무소+도로+주차장+오수처리장+배수지휴양콘도미니엄<NA>한방온천장(워터파크포함)+조경휴게지<NA>상가+완충녹지+원형보존녹지2002-01-16449540청풍호반, 월악산등과 연계한 핵심 처류거점으로 한방도시 컨셉과 연계한 한방온천장으로 조성계획 관광지043-641-6694충청북도 제천시청2023-10-114400000충청북도 제천시
918교리관광지관광지충청북도 제천시 청풍면 청풍호로 1798충청북도 제천시 청풍면 교리 225-137.016567128.176853316900.0오수정화조+정배수장+소각장+공중화장실+주차장+도로청풍레이크호텔+청풍힐호텔+민박촌다목적운동장+구기장+놀이동산+미니골프장조경휴게소+녹지공원+다목적광장+격납고<NA>관리원 숙소+하천+유보지+녹지1989-12-2848015200청풍호반 주변 관광시설과 연계한 핵심 체류 거점으로 청풍권 최고의 리조트 관광지043-641-6694충청북도 제천시청2023-10-114400000충청북도 제천시
919팔봉산관광지관광지강원특별자치도 홍천군 서면 한치골길 1124<NA>37.703098127.695183386977.0관리사무소+화장실+주차장<NA>풋살장캠핑장+공연장향토식당관리사무실1980-05-2810001508개의 암봉과 홍천강이 어우러진 아름다운 명산033-430-2471강원특별자치도 홍천군청2023-10-054251000강원특별자치도 홍천군
920소노벨비발디파크관광단지강원특별자치도 홍천군 서면 한치골길 262<NA>37.652337127.6873357052479.2관리사무소+화장실+주차장휴양콘도미니엄골프장+스키장+승마장오션월드관광공연장+식당 등직원전용 숙소2008-11-21200002000휴양과 레저, 골프 및 스키 등 국내 최대규모의 관광휴양단지033-430-2471강원특별자치도 홍천군청2023-10-054251000강원특별자치도 홍천군
921오전약수관광지관광지경상북도 봉화군 물야면 문수로 1541경상북도 봉화군 물야면 오전리 95-3537.012095128.745721137000.0관리사무소+화장실+상하수도시설+주차장<NA><NA><NA>관광식당<NA>1986-12-302000500심산계곡에 자리잡은 약수탕은 선달산, 옥석산 아래 깊은 계곡에 위치하고 있고, 약수는 예부터 위장병과 피부병에 효험이 있다.054-679-6353경상북도 봉화군청2023-09-045240000경상북도 봉화군
922다덕약수관광지관광지경상북도 봉화군 봉성면 다덕로 873경상북도 봉화군 봉성면 우곡리 505-536.914122128.82732388720.0관리사무소+화장실+주차장<NA><NA><NA>관광식당<NA>2008-12-30500120옛날 스무나무 아래 약수가 있어 이를 마시고 위장병과 피부병에 효험이 있어 많은 사람이 이 약수를 마시고 덕을 보았다 하여 다덕약수라고 불리움054-679-6353경상북도 봉화군청2023-09-045240000경상북도 봉화군
923다도박물관관광지경기도 김포시 월곶면 애기봉로275번길 187-49경기도 김포시 월곶면 개곡리 83237.737504126.574437180.0월곶면사무소약암홍염천 관광호텔, 덕포진 누리마을 캠핑장<NA><NA><NA><NA>2001-01-0115050지상3층 규모로 다도전시장과 조각공원, 다도체험장, 연못, 정자, 투호장 등 부대시설과 잔디광장을 갖춘 복합예술 공간으로 자연을 벗삼아 다도 및 전통예절, 민속놀이 체험을 할 수있다.031-998-1000경기도 김포시청2023-09-194090000경기도 김포시