Overview

Dataset statistics

Number of variables20
Number of observations56
Missing cells191
Missing cells (%)17.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory167.4 B

Variable types

Text12
Categorical2
Numeric5
DateTime1

Dataset

Description관광지 정보 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6D55H4P620YMVJ36G63F21726511&infSeq=1

Alerts

위도 is highly overall correlated with 관광지구분 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 데이터기준일자High correlation
면적 is highly overall correlated with 수용인원수High correlation
수용인원수 is highly overall correlated with 면적 and 2 other fieldsHigh correlation
주차가능수 is highly overall correlated with 수용인원수 and 1 other fieldsHigh correlation
관광지구분 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
관광지구분 is highly imbalanced (87.1%)Imbalance
소재지도로명주소 has 9 (16.1%) missing valuesMissing
숙박시설정보 has 33 (58.9%) missing valuesMissing
운동및오락시설정보 has 40 (71.4%) missing valuesMissing
휴양및문화시설정보 has 22 (39.3%) missing valuesMissing
접객시설정보 has 45 (80.4%) missing valuesMissing
지원시설정보 has 42 (75.0%) missing valuesMissing
관광지명 has unique valuesUnique
주차가능수 has 7 (12.5%) zerosZeros

Reproduction

Analysis started2024-05-10 20:57:09.670366
Analysis finished2024-05-10 20:57:21.641375
Duration11.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:21.955617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.8035714
Min length3

Characters and Unicode

Total characters325
Distinct characters134
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row김포국제조각공원
2nd row고양관광정보센터
3rd row신륵사관광지
4th row동구릉
5th row고구려대장간마을
ValueCountFrequency (%)
김포평화누리길 3
 
4.8%
김포국제조각공원 1
 
1.6%
임진각관광지 1
 
1.6%
두물머리 1
 
1.6%
3코스 1
 
1.6%
김포함상공원 1
 
1.6%
중대물빛공원 1
 
1.6%
반월호수 1
 
1.6%
초막골 1
 
1.6%
생태공원 1
 
1.6%
Other values (51) 51
81.0%
2024-05-10T20:57:23.072076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
5.2%
14
 
4.3%
13
 
4.0%
10
 
3.1%
10
 
3.1%
9
 
2.8%
9
 
2.8%
9
 
2.8%
7
 
2.2%
7
 
2.2%
Other values (124) 220
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
96.3%
Space Separator 7
 
2.2%
Decimal Number 3
 
0.9%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
5.4%
14
 
4.5%
13
 
4.2%
10
 
3.2%
10
 
3.2%
9
 
2.9%
9
 
2.9%
9
 
2.9%
7
 
2.2%
7
 
2.2%
Other values (118) 208
66.5%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
2 1
33.3%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
96.3%
Common 12
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
5.4%
14
 
4.5%
13
 
4.2%
10
 
3.2%
10
 
3.2%
9
 
2.9%
9
 
2.9%
9
 
2.9%
7
 
2.2%
7
 
2.2%
Other values (118) 208
66.5%
Common
ValueCountFrequency (%)
7
58.3%
( 1
 
8.3%
3 1
 
8.3%
2 1
 
8.3%
1 1
 
8.3%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
96.3%
ASCII 12
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
 
5.4%
14
 
4.5%
13
 
4.2%
10
 
3.2%
10
 
3.2%
9
 
2.9%
9
 
2.9%
9
 
2.9%
7
 
2.2%
7
 
2.2%
Other values (118) 208
66.5%
ASCII
ValueCountFrequency (%)
7
58.3%
( 1
 
8.3%
3 1
 
8.3%
2 1
 
8.3%
1 1
 
8.3%
) 1
 
8.3%

관광지구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
관광지
55 
관광단지
 
1

Length

Max length4
Median length3
Mean length3.0178571
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 55
98.2%
관광단지 1
 
1.8%

Length

2024-05-10T20:57:23.444749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:57:23.665915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 55
98.2%
관광단지 1
 
1.8%
Distinct46
Distinct (%)97.9%
Missing9
Missing (%)16.1%
Memory size580.0 B
2024-05-10T20:57:24.080090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length19.914894
Min length14

Characters and Unicode

Total characters936
Distinct characters127
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st row경기도 김포시 월곶면 용강로13번길 38
2nd row경기도 고양시 일산동구 중앙로1271-1
3rd row경기도 여주시 신륵사길 73
4th row경기도 구리시 동구릉로 197
5th row경기도 구리시 우미내길 41
ValueCountFrequency (%)
경기도 45
 
20.8%
김포시 8
 
3.7%
광주시 7
 
3.2%
군포시 5
 
2.3%
양평군 4
 
1.9%
90 3
 
1.4%
월곶면 3
 
1.4%
하남시 3
 
1.4%
대곶면 3
 
1.4%
산수로 3
 
1.4%
Other values (117) 132
61.1%
2024-05-10T20:57:24.972339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
169
 
18.1%
49
 
5.2%
48
 
5.1%
47
 
5.0%
1 46
 
4.9%
39
 
4.2%
39
 
4.2%
21
 
2.2%
7 19
 
2.0%
19
 
2.0%
Other values (117) 440
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 586
62.6%
Decimal Number 171
 
18.3%
Space Separator 169
 
18.1%
Dash Punctuation 8
 
0.9%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
49
 
8.4%
48
 
8.2%
47
 
8.0%
39
 
6.7%
39
 
6.7%
21
 
3.6%
19
 
3.2%
16
 
2.7%
14
 
2.4%
13
 
2.2%
Other values (103) 281
48.0%
Decimal Number
ValueCountFrequency (%)
1 46
26.9%
7 19
11.1%
9 18
 
10.5%
3 17
 
9.9%
2 15
 
8.8%
0 14
 
8.2%
5 12
 
7.0%
4 12
 
7.0%
8 10
 
5.8%
6 8
 
4.7%
Space Separator
ValueCountFrequency (%)
169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 586
62.6%
Common 350
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
49
 
8.4%
48
 
8.2%
47
 
8.0%
39
 
6.7%
39
 
6.7%
21
 
3.6%
19
 
3.2%
16
 
2.7%
14
 
2.4%
13
 
2.2%
Other values (103) 281
48.0%
Common
ValueCountFrequency (%)
169
48.3%
1 46
 
13.1%
7 19
 
5.4%
9 18
 
5.1%
3 17
 
4.9%
2 15
 
4.3%
0 14
 
4.0%
5 12
 
3.4%
4 12
 
3.4%
8 10
 
2.9%
Other values (4) 18
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 586
62.6%
ASCII 350
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
169
48.3%
1 46
 
13.1%
7 19
 
5.4%
9 18
 
5.1%
3 17
 
4.9%
2 15
 
4.3%
0 14
 
4.0%
5 12
 
3.4%
4 12
 
3.4%
8 10
 
2.9%
Other values (4) 18
 
5.1%
Hangul
ValueCountFrequency (%)
49
 
8.4%
48
 
8.2%
47
 
8.0%
39
 
6.7%
39
 
6.7%
21
 
3.6%
19
 
3.2%
16
 
2.7%
14
 
2.4%
13
 
2.2%
Other values (103) 281
48.0%
Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:25.559254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length19.785714
Min length14

Characters and Unicode

Total characters1108
Distinct characters120
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st row경기도 김포시 월곶면 고막리 82-1
2nd row경기도 고양시 일산동구 장항동845
3rd row경기도 여주시 천송동 289-7
4th row경기도 구리시 인창동 66-1
5th row경기도 구리시 아천동 산45-1
ValueCountFrequency (%)
경기도 56
 
21.1%
김포시 12
 
4.5%
광주시 7
 
2.6%
군포시 6
 
2.3%
월곶면 5
 
1.9%
연천군 5
 
1.9%
양평군 4
 
1.5%
대곶면 4
 
1.5%
하남시 4
 
1.5%
3
 
1.1%
Other values (141) 160
60.2%
2024-05-10T20:57:26.518508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
210
19.0%
57
 
5.1%
57
 
5.1%
56
 
5.1%
45
 
4.1%
39
 
3.5%
1 37
 
3.3%
- 30
 
2.7%
28
 
2.5%
27
 
2.4%
Other values (110) 522
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 679
61.3%
Space Separator 210
 
19.0%
Decimal Number 183
 
16.5%
Dash Punctuation 30
 
2.7%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
57
 
8.4%
57
 
8.4%
56
 
8.2%
45
 
6.6%
39
 
5.7%
28
 
4.1%
27
 
4.0%
22
 
3.2%
18
 
2.7%
17
 
2.5%
Other values (96) 313
46.1%
Decimal Number
ValueCountFrequency (%)
1 37
20.2%
5 26
14.2%
2 26
14.2%
3 20
10.9%
6 19
10.4%
4 16
8.7%
8 11
 
6.0%
7 11
 
6.0%
9 9
 
4.9%
0 8
 
4.4%
Space Separator
ValueCountFrequency (%)
210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 679
61.3%
Common 429
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
57
 
8.4%
57
 
8.4%
56
 
8.2%
45
 
6.6%
39
 
5.7%
28
 
4.1%
27
 
4.0%
22
 
3.2%
18
 
2.7%
17
 
2.5%
Other values (96) 313
46.1%
Common
ValueCountFrequency (%)
210
49.0%
1 37
 
8.6%
- 30
 
7.0%
5 26
 
6.1%
2 26
 
6.1%
3 20
 
4.7%
6 19
 
4.4%
4 16
 
3.7%
8 11
 
2.6%
7 11
 
2.6%
Other values (4) 23
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 679
61.3%
ASCII 429
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
210
49.0%
1 37
 
8.6%
- 30
 
7.0%
5 26
 
6.1%
2 26
 
6.1%
3 20
 
4.7%
6 19
 
4.4%
4 16
 
3.7%
8 11
 
2.6%
7 11
 
2.6%
Other values (4) 23
 
5.4%
Hangul
ValueCountFrequency (%)
57
 
8.4%
57
 
8.4%
56
 
8.2%
45
 
6.6%
39
 
5.7%
28
 
4.1%
27
 
4.0%
22
 
3.2%
18
 
2.7%
17
 
2.5%
Other values (96) 313
46.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.608356
Minimum36.914825
Maximum38.076726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-10T20:57:26.893792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.914825
5-th percentile37.296586
Q137.45057
median37.60343
Q337.739772
95-th percentile38.034045
Maximum38.076726
Range1.1619013
Interquartile range (IQR)0.2892022

Descriptive statistics

Standard deviation0.24064222
Coefficient of variation (CV)0.006398637
Kurtosis0.28080185
Mean37.608356
Median Absolute Deviation (MAD)0.14189733
Skewness0.048854726
Sum2106.0679
Variance0.057908678
MonotonicityNot monotonic
2024-05-10T20:57:27.482847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6506248 2
 
3.6%
37.72080378 1
 
1.8%
37.70077831 1
 
1.8%
37.40272258 1
 
1.8%
37.32458238 1
 
1.8%
37.35410097 1
 
1.8%
37.35543392 1
 
1.8%
37.35443607 1
 
1.8%
37.32136505 1
 
1.8%
37.2940666959 1
 
1.8%
Other values (45) 45
80.4%
ValueCountFrequency (%)
36.914825 1
1.8%
37.2591318929 1
1.8%
37.2940666959 1
1.8%
37.29742583 1
1.8%
37.32136505 1
1.8%
37.32458238 1
1.8%
37.33028283 1
1.8%
37.35028421 1
1.8%
37.35410097 1
1.8%
37.35443607 1
1.8%
ValueCountFrequency (%)
38.07672631 1
1.8%
38.072165 1
1.8%
38.065669 1
1.8%
38.02350322 1
1.8%
38.01564838 1
1.8%
38.00887699 1
1.8%
37.98583872 1
1.8%
37.94652177 1
1.8%
37.88953876 1
1.8%
37.75797919 1
1.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02204
Minimum126.53879
Maximum127.65994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-10T20:57:27.996746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53879
5-th percentile126.54488
Q1126.81471
median127.06016
Q3127.28238
95-th percentile127.44127
Maximum127.65994
Range1.1211502
Interquartile range (IQR)0.46767345

Descriptive statistics

Standard deviation0.30664955
Coefficient of variation (CV)0.0024141443
Kurtosis-0.9545864
Mean127.02204
Median Absolute Deviation (MAD)0.23736872
Skewness-0.054162935
Sum7113.2344
Variance0.094033944
MonotonicityNot monotonic
2024-05-10T20:57:28.654194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5387862 2
 
3.6%
126.552204 1
 
1.8%
126.6622045 1
 
1.8%
127.218054 1
 
1.8%
126.8899642 1
 
1.8%
126.9191417 1
 
1.8%
126.924967 1
 
1.8%
126.8967938 1
 
1.8%
126.8996775 1
 
1.8%
127.2021280298 1
 
1.8%
Other values (45) 45
80.4%
ValueCountFrequency (%)
126.5387862 2
3.6%
126.539261 1
1.8%
126.5467533 1
1.8%
126.5484911 1
1.8%
126.552204 1
1.8%
126.5533799 1
1.8%
126.5744366 1
1.8%
126.5942484 1
1.8%
126.6622045 1
1.8%
126.696212 1
1.8%
ValueCountFrequency (%)
127.6599364 1
1.8%
127.583066 1
1.8%
127.5331978 1
1.8%
127.410629 1
1.8%
127.409889 1
1.8%
127.3883989 1
1.8%
127.379521 1
1.8%
127.3347877 1
1.8%
127.3239608 1
1.8%
127.3174715 1
1.8%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean547531.53
Minimum180
Maximum12000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-10T20:57:29.021961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180
5-th percentile651
Q113644.5
median138445.5
Q3576413.75
95-th percentile1489868.5
Maximum12000000
Range11999820
Interquartile range (IQR)562769.25

Descriptive statistics

Standard deviation1632026.3
Coefficient of variation (CV)2.9806983
Kurtosis46.059593
Mean547531.53
Median Absolute Deviation (MAD)137315.62
Skewness6.5433394
Sum30661766
Variance2.6635098 × 1012
MonotonicityNot monotonic
2024-05-10T20:57:29.481378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15000.0 3
 
5.4%
651.0 2
 
3.6%
765.0 1
 
1.8%
9578.0 1
 
1.8%
12000000.0 1
 
1.8%
561500.0 1
 
1.8%
55795.0 1
 
1.8%
7369.0 1
 
1.8%
1477.76 1
 
1.8%
746000.0 1
 
1.8%
Other values (43) 43
76.8%
ValueCountFrequency (%)
180.0 1
1.8%
237.0 1
1.8%
651.0 2
3.6%
765.0 1
1.8%
782.0 1
1.8%
1477.76 1
1.8%
1732.0 1
1.8%
3328.0 1
1.8%
3339.0 1
1.8%
4928.0 1
1.8%
ValueCountFrequency (%)
12000000.0 1
1.8%
2472000.0 1
1.8%
1969675.0 1
1.8%
1329933.0 1
1.8%
990000.0 1
1.8%
947268.0 1
1.8%
778296.0 1
1.8%
746000.0 1
1.8%
708241.0 1
1.8%
700000.0 1
1.8%
Distinct32
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:29.855995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length24
Mean length13.196429
Min length3

Characters and Unicode

Total characters739
Distinct characters108
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

Unique21 ?
Unique (%)37.5%

Sample

1st row월곶면사무소
2nd row핸드폰충전 +컴퓨터 검색 + 우산대여서비스 + 휠체어대여 서비스 + 유모차대여서비스 + 휴계공간 + 공용화장실 + 정수기 +
3rd row관광안내소+주차장
4th row관리사무소+화장실+주차장
5th row관리사무소+화장실+주차장
ValueCountFrequency (%)
9
 
10.0%
화장실 7
 
7.8%
공중화장실 6
 
6.7%
주차장+화장실+공원 4
 
4.4%
월곶면사무소 4
 
4.4%
주차장+화장실 4
 
4.4%
해설안내소+화장실+주차장 3
 
3.3%
관리사무소+화장실+주차장 3
 
3.3%
관리사무소+주차장 3
 
3.3%
주차장 2
 
2.2%
Other values (37) 45
50.0%
2024-05-10T20:57:30.975828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 87
 
11.8%
79
 
10.7%
45
 
6.1%
42
 
5.7%
36
 
4.9%
34
 
4.6%
34
 
4.6%
30
 
4.1%
23
 
3.1%
23
 
3.1%
Other values (98) 306
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 596
80.6%
Math Symbol 87
 
11.8%
Space Separator 34
 
4.6%
Decimal Number 10
 
1.4%
Open Punctuation 5
 
0.7%
Close Punctuation 5
 
0.7%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
79
 
13.3%
45
 
7.6%
42
 
7.0%
36
 
6.0%
34
 
5.7%
30
 
5.0%
23
 
3.9%
23
 
3.9%
21
 
3.5%
17
 
2.9%
Other values (87) 246
41.3%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
2 2
20.0%
4 1
 
10.0%
3 1
 
10.0%
5 1
 
10.0%
6 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 87
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 596
80.6%
Common 143
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
79
 
13.3%
45
 
7.6%
42
 
7.0%
36
 
6.0%
34
 
5.7%
30
 
5.0%
23
 
3.9%
23
 
3.9%
21
 
3.5%
17
 
2.9%
Other values (87) 246
41.3%
Common
ValueCountFrequency (%)
+ 87
60.8%
34
 
23.8%
( 5
 
3.5%
) 5
 
3.5%
1 4
 
2.8%
, 2
 
1.4%
2 2
 
1.4%
4 1
 
0.7%
3 1
 
0.7%
5 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 596
80.6%
ASCII 143
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 87
60.8%
34
 
23.8%
( 5
 
3.5%
) 5
 
3.5%
1 4
 
2.8%
, 2
 
1.4%
2 2
 
1.4%
4 1
 
0.7%
3 1
 
0.7%
5 1
 
0.7%
Hangul
ValueCountFrequency (%)
79
 
13.3%
45
 
7.6%
42
 
7.0%
36
 
6.0%
34
 
5.7%
30
 
5.0%
23
 
3.9%
23
 
3.9%
21
 
3.5%
17
 
2.9%
Other values (87) 246
41.3%

숙박시설정보
Text

MISSING 

Distinct16
Distinct (%)69.6%
Missing33
Missing (%)58.9%
Memory size580.0 B
2024-05-10T20:57:31.456570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length22
Mean length16.130435
Min length1

Characters and Unicode

Total characters371
Distinct characters102
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

Unique12 ?
Unique (%)52.2%

Sample

1st row문수산농원펜션, 동막골캠프,문소골산장,김포관광농원,평화누리길게스트하우스
2nd rowN
3rd row관광호텔+여관+콘도
4th row펜션
5th row관광호텔 등
ValueCountFrequency (%)
관광호텔 7
 
11.5%
약암홍염천 5
 
8.2%
덕포진 5
 
8.2%
누리마을 5
 
8.2%
캠핑장 5
 
8.2%
펜션 3
 
4.9%
문수산농원펜션 2
 
3.3%
동막골캠프,문소골산장,김포관광농원,평화누리길게스트하우스 2
 
3.3%
n 2
 
3.3%
2
 
3.3%
Other values (22) 23
37.7%
2024-05-10T20:57:32.506690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
10.2%
, 14
 
3.8%
12
 
3.2%
10
 
2.7%
10
 
2.7%
10
 
2.7%
10
 
2.7%
+ 9
 
2.4%
9
 
2.4%
8
 
2.2%
Other values (92) 241
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
77.9%
Space Separator 38
 
10.2%
Other Punctuation 14
 
3.8%
Decimal Number 14
 
3.8%
Math Symbol 9
 
2.4%
Uppercase Letter 5
 
1.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
4.2%
10
 
3.5%
10
 
3.5%
10
 
3.5%
10
 
3.5%
9
 
3.1%
8
 
2.8%
8
 
2.8%
7
 
2.4%
6
 
2.1%
Other values (75) 199
68.9%
Decimal Number
ValueCountFrequency (%)
1 4
28.6%
6 2
14.3%
9 2
14.3%
4 2
14.3%
3 1
 
7.1%
2 1
 
7.1%
5 1
 
7.1%
8 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
N 2
40.0%
Z 1
20.0%
M 1
20.0%
D 1
20.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
77.9%
Common 77
 
20.8%
Latin 5
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
4.2%
10
 
3.5%
10
 
3.5%
10
 
3.5%
10
 
3.5%
9
 
3.1%
8
 
2.8%
8
 
2.8%
7
 
2.4%
6
 
2.1%
Other values (75) 199
68.9%
Common
ValueCountFrequency (%)
38
49.4%
, 14
 
18.2%
+ 9
 
11.7%
1 4
 
5.2%
6 2
 
2.6%
9 2
 
2.6%
4 2
 
2.6%
3 1
 
1.3%
2 1
 
1.3%
) 1
 
1.3%
Other values (3) 3
 
3.9%
Latin
ValueCountFrequency (%)
N 2
40.0%
Z 1
20.0%
M 1
20.0%
D 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
77.9%
ASCII 82
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
46.3%
, 14
 
17.1%
+ 9
 
11.0%
1 4
 
4.9%
6 2
 
2.4%
9 2
 
2.4%
4 2
 
2.4%
N 2
 
2.4%
3 1
 
1.2%
2 1
 
1.2%
Other values (7) 7
 
8.5%
Hangul
ValueCountFrequency (%)
12
 
4.2%
10
 
3.5%
10
 
3.5%
10
 
3.5%
10
 
3.5%
9
 
3.1%
8
 
2.8%
8
 
2.8%
7
 
2.4%
6
 
2.1%
Other values (75) 199
68.9%
Distinct16
Distinct (%)100.0%
Missing40
Missing (%)71.4%
Memory size580.0 B
2024-05-10T20:57:32.936044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length22
Mean length16.1875
Min length5

Characters and Unicode

Total characters259
Distinct characters111
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

Unique16 ?
Unique (%)100.0%

Sample

1st row버스킹존 + 한복체험실 + 민속놀이 체험존
2nd row물놀이장+오락장
3rd row수변데크+공원+바닥분수+벽천폭포 등
4th row인조잔디구장+풋살구장+농구장+인라인스케이트장+산책로+캐릭터공원+각종체육시설
5th row유원시설 등 계획
ValueCountFrequency (%)
3
 
8.6%
2
 
5.7%
민속놀이 2
 
5.7%
체험존 2
 
5.7%
버스킹존 1
 
2.9%
축구장 1
 
2.9%
다목적 1
 
2.9%
체육관+테니스장+족구장+농구장+체육시설+어린이 1
 
2.9%
물놀이시설 1
 
2.9%
조정호수 1
 
2.9%
Other values (20) 20
57.1%
2024-05-10T20:57:33.770073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 21
 
8.1%
19
 
7.3%
14
 
5.4%
9
 
3.5%
8
 
3.1%
7
 
2.7%
6
 
2.3%
6
 
2.3%
6
 
2.3%
6
 
2.3%
Other values (101) 157
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
79.9%
Math Symbol 21
 
8.1%
Space Separator 19
 
7.3%
Other Punctuation 4
 
1.5%
Open Punctuation 3
 
1.2%
Close Punctuation 3
 
1.2%
Uppercase Letter 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
6.8%
9
 
4.3%
8
 
3.9%
7
 
3.4%
6
 
2.9%
6
 
2.9%
6
 
2.9%
6
 
2.9%
5
 
2.4%
4
 
1.9%
Other values (94) 136
65.7%
Uppercase Letter
ValueCountFrequency (%)
V 1
50.0%
R 1
50.0%
Math Symbol
ValueCountFrequency (%)
+ 21
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
79.9%
Common 50
 
19.3%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
6.8%
9
 
4.3%
8
 
3.9%
7
 
3.4%
6
 
2.9%
6
 
2.9%
6
 
2.9%
6
 
2.9%
5
 
2.4%
4
 
1.9%
Other values (94) 136
65.7%
Common
ValueCountFrequency (%)
+ 21
42.0%
19
38.0%
, 4
 
8.0%
( 3
 
6.0%
) 3
 
6.0%
Latin
ValueCountFrequency (%)
V 1
50.0%
R 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
79.9%
ASCII 52
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 21
40.4%
19
36.5%
, 4
 
7.7%
( 3
 
5.8%
) 3
 
5.8%
V 1
 
1.9%
R 1
 
1.9%
Hangul
ValueCountFrequency (%)
14
 
6.8%
9
 
4.3%
8
 
3.9%
7
 
3.4%
6
 
2.9%
6
 
2.9%
6
 
2.9%
6
 
2.9%
5
 
2.4%
4
 
1.9%
Other values (94) 136
65.7%
Distinct33
Distinct (%)97.1%
Missing22
Missing (%)39.3%
Memory size580.0 B
2024-05-10T20:57:34.182988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length20
Mean length13.5
Min length3

Characters and Unicode

Total characters459
Distinct characters170
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)94.1%

Sample

1st row문수산삼림욕장
2nd row고양시 관광지 자료배포 및 행사 안내
3rd row청소년 수련실+야외음악당
4th row백자자료관
5th row행궁, 만해기념관 등
ValueCountFrequency (%)
7
 
8.6%
안내 3
 
3.7%
3
 
3.7%
야영장 2
 
2.5%
행사 2
 
2.5%
2
 
2.5%
문수산삼림욕장 2
 
2.5%
김포 1
 
1.2%
함상공원 1
 
1.2%
장작가마 1
 
1.2%
Other values (57) 57
70.4%
2024-05-10T20:57:35.003147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
10.2%
20
 
4.4%
, 17
 
3.7%
16
 
3.5%
+ 12
 
2.6%
7
 
1.5%
7
 
1.5%
7
 
1.5%
7
 
1.5%
7
 
1.5%
Other values (160) 312
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 378
82.4%
Space Separator 47
 
10.2%
Other Punctuation 18
 
3.9%
Math Symbol 12
 
2.6%
Decimal Number 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
 
5.3%
16
 
4.2%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
Other values (152) 287
75.9%
Decimal Number
ValueCountFrequency (%)
5 1
25.0%
2 1
25.0%
6 1
25.0%
3 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 17
94.4%
. 1
 
5.6%
Space Separator
ValueCountFrequency (%)
47
100.0%
Math Symbol
ValueCountFrequency (%)
+ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 378
82.4%
Common 81
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
 
5.3%
16
 
4.2%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
Other values (152) 287
75.9%
Common
ValueCountFrequency (%)
47
58.0%
, 17
 
21.0%
+ 12
 
14.8%
5 1
 
1.2%
2 1
 
1.2%
. 1
 
1.2%
6 1
 
1.2%
3 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 378
82.4%
ASCII 81
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
58.0%
, 17
 
21.0%
+ 12
 
14.8%
5 1
 
1.2%
2 1
 
1.2%
. 1
 
1.2%
6 1
 
1.2%
3 1
 
1.2%
Hangul
ValueCountFrequency (%)
20
 
5.3%
16
 
4.2%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
Other values (152) 287
75.9%

접객시설정보
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing45
Missing (%)80.4%
Memory size580.0 B
2024-05-10T20:57:35.378346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length20
Mean length15.272727
Min length2

Characters and Unicode

Total characters168
Distinct characters68
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row영상관25명 + 관광회의실 12명 + 북쉼터 15명 + 루프탑 30명 + 공유오피스 40명
2nd row관광식당
3rd row식당+카페 등 
4th row매점+식당 등 4개소 운영+상가 5개소 계획
5th row음식점 및 상가 2동 운영+3동 계획
ValueCountFrequency (%)
5
 
13.2%
20여명 2
 
5.3%
2
 
5.3%
음식점 2
 
5.3%
계획 2
 
5.3%
영상관25명 1
 
2.6%
5개소 1
 
2.6%
푸드코트+노천카페+이동판매대+와인판매대+기념품샵 1
 
2.6%
충의정 1
 
2.6%
대첩기념관 1
 
2.6%
Other values (20) 20
52.6%
2024-05-10T20:57:36.193158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
16.1%
+ 13
 
7.7%
7
 
4.2%
2 5
 
3.0%
5
 
3.0%
0 4
 
2.4%
4
 
2.4%
4
 
2.4%
3
 
1.8%
3
 
1.8%
Other values (58) 93
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
64.9%
Space Separator 28
 
16.7%
Decimal Number 18
 
10.7%
Math Symbol 13
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
6.4%
5
 
4.6%
4
 
3.7%
4
 
3.7%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
Other values (49) 71
65.1%
Decimal Number
ValueCountFrequency (%)
2 5
27.8%
0 4
22.2%
5 3
16.7%
3 2
 
11.1%
1 2
 
11.1%
4 2
 
11.1%
Space Separator
ValueCountFrequency (%)
27
96.4%
  1
 
3.6%
Math Symbol
ValueCountFrequency (%)
+ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
64.9%
Common 59
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
6.4%
5
 
4.6%
4
 
3.7%
4
 
3.7%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
Other values (49) 71
65.1%
Common
ValueCountFrequency (%)
27
45.8%
+ 13
22.0%
2 5
 
8.5%
0 4
 
6.8%
5 3
 
5.1%
3 2
 
3.4%
1 2
 
3.4%
4 2
 
3.4%
  1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
64.9%
ASCII 58
34.5%
None 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
46.6%
+ 13
22.4%
2 5
 
8.6%
0 4
 
6.9%
5 3
 
5.2%
3 2
 
3.4%
1 2
 
3.4%
4 2
 
3.4%
Hangul
ValueCountFrequency (%)
7
 
6.4%
5
 
4.6%
4
 
3.7%
4
 
3.7%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
3
 
2.8%
Other values (49) 71
65.1%
None
ValueCountFrequency (%)
  1
100.0%

지원시설정보
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing42
Missing (%)75.0%
Memory size580.0 B
2024-05-10T20:57:36.561668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length23.5
Mean length7
Min length2

Characters and Unicode

Total characters98
Distinct characters44
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

Unique5 ?
Unique (%)35.7%

Sample

1st row영상관+회의실+북쉼터+영상창작실+루프탑+관광기념품?? + 카페
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음
ValueCountFrequency (%)
해당없음 7
36.8%
없음 2
 
10.5%
2
 
10.5%
영상관+회의실+북쉼터+영상창작실+루프탑+관광기념품 1
 
5.3%
카페 1
 
5.3%
관리사무소 1
 
5.3%
김포시 1
 
5.3%
관광안내소 1
 
5.3%
방문자센터 1
 
5.3%
영상교육관 1
 
5.3%
2024-05-10T20:57:37.299979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
9.2%
9
 
9.2%
7
 
7.1%
+ 7
 
7.1%
7
 
7.1%
6
 
6.1%
5
 
5.1%
3
 
3.1%
3
 
3.1%
2
 
2.0%
Other values (34) 40
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
85.7%
Math Symbol 7
 
7.1%
Space Separator 5
 
5.1%
Other Punctuation 2
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9
 
10.7%
9
 
10.7%
7
 
8.3%
7
 
8.3%
6
 
7.1%
3
 
3.6%
3
 
3.6%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (31) 34
40.5%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
85.7%
Common 14
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9
 
10.7%
9
 
10.7%
7
 
8.3%
7
 
8.3%
6
 
7.1%
3
 
3.6%
3
 
3.6%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (31) 34
40.5%
Common
ValueCountFrequency (%)
+ 7
50.0%
5
35.7%
? 2
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
85.7%
ASCII 14
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9
 
10.7%
9
 
10.7%
7
 
8.3%
7
 
8.3%
6
 
7.1%
3
 
3.6%
3
 
3.6%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (31) 34
40.5%
ASCII
ValueCountFrequency (%)
+ 7
50.0%
5
35.7%
? 2
 
14.3%
Distinct40
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum1963-01-21 00:00:00
Maximum2021-05-12 00:00:00
2024-05-10T20:57:37.679000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:38.030949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

수용인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39442.857
Minimum20
Maximum900000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-10T20:57:38.395932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile70
Q1300
median3000
Q310000
95-th percentile137500
Maximum900000
Range899980
Interquartile range (IQR)9700

Descriptive statistics

Standard deviation139452.85
Coefficient of variation (CV)3.5355665
Kurtosis28.759478
Mean39442.857
Median Absolute Deviation (MAD)2850
Skewness5.1625131
Sum2208800
Variance1.9447096 × 1010
MonotonicityNot monotonic
2024-05-10T20:57:38.899853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10000 8
 
14.3%
500 5
 
8.9%
3000 4
 
7.1%
300 3
 
5.4%
3514 3
 
5.4%
100 3
 
5.4%
5000 3
 
5.4%
200 2
 
3.6%
100000 2
 
3.6%
70 2
 
3.6%
Other values (19) 21
37.5%
ValueCountFrequency (%)
20 1
 
1.8%
40 1
 
1.8%
70 2
 
3.6%
80 1
 
1.8%
100 3
5.4%
122 1
 
1.8%
150 2
 
3.6%
200 2
 
3.6%
300 3
5.4%
500 5
8.9%
ValueCountFrequency (%)
900000 1
 
1.8%
500000 1
 
1.8%
250000 1
 
1.8%
100000 2
 
3.6%
81546 1
 
1.8%
60000 1
 
1.8%
50000 1
 
1.8%
20000 1
 
1.8%
10000 8
14.3%
7800 1
 
1.8%

주차가능수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean553.23214
Minimum0
Maximum10400
Zeros7
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-10T20:57:39.302944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.75
median104.5
Q3486.5
95-th percentile2268.25
Maximum10400
Range10400
Interquartile range (IQR)462.75

Descriptive statistics

Standard deviation1502.2567
Coefficient of variation (CV)2.7154183
Kurtosis34.703642
Mean553.23214
Median Absolute Deviation (MAD)104.5
Skewness5.5227192
Sum30981
Variance2256775.1
MonotonicityNot monotonic
2024-05-10T20:57:39.693733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 7
 
12.5%
100 5
 
8.9%
50 3
 
5.4%
10 3
 
5.4%
567 2
 
3.6%
500 2
 
3.6%
20 2
 
3.6%
45 1
 
1.8%
2091 1
 
1.8%
85 1
 
1.8%
Other values (29) 29
51.8%
ValueCountFrequency (%)
0 7
12.5%
5 1
 
1.8%
10 3
5.4%
11 1
 
1.8%
20 2
 
3.6%
25 1
 
1.8%
35 1
 
1.8%
45 1
 
1.8%
50 3
5.4%
56 1
 
1.8%
ValueCountFrequency (%)
10400 1
1.8%
3500 1
1.8%
2800 1
1.8%
2091 1
1.8%
1830 1
1.8%
945 1
1.8%
899 1
1.8%
807 1
1.8%
724 1
1.8%
567 2
3.6%
Distinct54
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:40.238034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length455
Median length86
Mean length82.785714
Min length5

Characters and Unicode

Total characters4636
Distinct characters484
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)94.6%

Sample

1st row통일을 주제로 조성된 테마공원으로 세계적인 조각의 작품 30여점이 전시되어 있다. 산책로를 따라 조각작품이 전시되어 있어 산림욕을 즐기면서 조각작품을 감상할 수 있다.
2nd row고양시 관광지 자료 배포 및 시티투어 안내
3rd row시원한 남한강을 따라 자전거도로, 각종 체육시설과 여주박물관, 도자세상, 농특산물 판매장이 있으며, 매년 여주도자기축제와 오곡나루축제가 이곳에서 개최되고 있다. 특히 남한강을 가르는 황포돛배(Yellow Sail boat)와 수상레저를 즐길 수 있는 가족 연인들의 나들이 공간이다
4th row유네스코 세계유산이자 사적 제193호로 지정된 「구리 동구릉(東九陵)」은 ‘도성(都城)의 동(東)쪽에 있는 아홉(九) 기의 왕릉’이라 하여 동구릉이라 붙여짐
5th row국내유일의 고구려 박물관으로 아차산에서 출토된 유물을 전시하고 있으며 고구려모습을 보여주는 야외전시관을 운영
ValueCountFrequency (%)
있다 24
 
2.4%
있는 18
 
1.8%
13
 
1.3%
10
 
1.0%
있으며 7
 
0.7%
다양한 6
 
0.6%
조성되어 6
 
0.6%
6
 
0.6%
갖춘 4
 
0.4%
등이 4
 
0.4%
Other values (811) 918
90.4%
2024-05-10T20:57:41.275674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
963
 
20.8%
98
 
2.1%
72
 
1.6%
66
 
1.4%
65
 
1.4%
, 63
 
1.4%
62
 
1.3%
60
 
1.3%
59
 
1.3%
58
 
1.3%
Other values (474) 3070
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3342
72.1%
Space Separator 963
 
20.8%
Decimal Number 138
 
3.0%
Other Punctuation 119
 
2.6%
Lowercase Letter 27
 
0.6%
Close Punctuation 15
 
0.3%
Open Punctuation 15
 
0.3%
Math Symbol 11
 
0.2%
Uppercase Letter 3
 
0.1%
Final Punctuation 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
98
 
2.9%
72
 
2.2%
66
 
2.0%
65
 
1.9%
62
 
1.9%
60
 
1.8%
59
 
1.8%
58
 
1.7%
51
 
1.5%
48
 
1.4%
Other values (438) 2703
80.9%
Decimal Number
ValueCountFrequency (%)
1 24
17.4%
0 23
16.7%
2 18
13.0%
9 16
11.6%
6 12
8.7%
3 11
8.0%
4 10
7.2%
5 9
 
6.5%
8 8
 
5.8%
7 7
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
m 9
33.3%
k 6
22.2%
l 3
 
11.1%
a 2
 
7.4%
o 2
 
7.4%
i 1
 
3.7%
w 1
 
3.7%
e 1
 
3.7%
b 1
 
3.7%
t 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 63
52.9%
. 51
42.9%
: 3
 
2.5%
· 2
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
Y 1
33.3%
D 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 14
93.3%
1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 14
93.3%
1
 
6.7%
Space Separator
ValueCountFrequency (%)
963
100.0%
Math Symbol
ValueCountFrequency (%)
+ 11
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3335
71.9%
Common 1264
 
27.3%
Latin 30
 
0.6%
Han 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
98
 
2.9%
72
 
2.2%
66
 
2.0%
65
 
1.9%
62
 
1.9%
60
 
1.8%
59
 
1.8%
58
 
1.7%
51
 
1.5%
48
 
1.4%
Other values (433) 2696
80.8%
Common
ValueCountFrequency (%)
963
76.2%
, 63
 
5.0%
. 51
 
4.0%
1 24
 
1.9%
0 23
 
1.8%
2 18
 
1.4%
9 16
 
1.3%
) 14
 
1.1%
( 14
 
1.1%
6 12
 
0.9%
Other values (13) 66
 
5.2%
Latin
ValueCountFrequency (%)
m 9
30.0%
k 6
20.0%
l 3
 
10.0%
a 2
 
6.7%
o 2
 
6.7%
i 1
 
3.3%
S 1
 
3.3%
w 1
 
3.3%
e 1
 
3.3%
Y 1
 
3.3%
Other values (3) 3
 
10.0%
Han
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3333
71.9%
ASCII 1288
 
27.8%
CJK 7
 
0.2%
None 4
 
0.1%
Compat Jamo 2
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
963
74.8%
, 63
 
4.9%
. 51
 
4.0%
1 24
 
1.9%
0 23
 
1.8%
2 18
 
1.4%
9 16
 
1.2%
) 14
 
1.1%
( 14
 
1.1%
6 12
 
0.9%
Other values (21) 90
 
7.0%
Hangul
ValueCountFrequency (%)
98
 
2.9%
72
 
2.2%
66
 
2.0%
65
 
2.0%
62
 
1.9%
60
 
1.8%
59
 
1.8%
58
 
1.7%
51
 
1.5%
48
 
1.4%
Other values (432) 2694
80.8%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
· 2
50.0%
1
25.0%
1
25.0%
CJK
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct43
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:41.767069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.089286
Min length12

Characters and Unicode

Total characters677
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

Unique32 ?
Unique (%)57.1%

Sample

1st row031-984-5167
2nd row031-905-8396
3rd row031-887-2070
4th row031-563-2909
5th row031-550-8355
ValueCountFrequency (%)
031-392-3000 3
 
5.4%
031-980-5108 3
 
5.4%
031-538-3363 2
 
3.6%
031-790-5971 2
 
3.6%
031-580-2518 2
 
3.6%
031-324-2117 2
 
3.6%
031-980-2483 2
 
3.6%
031-839-2144 2
 
3.6%
031-760-3763 2
 
3.6%
031-799-1500 2
 
3.6%
Other values (33) 34
60.7%
2024-05-10T20:57:42.730957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 118
17.4%
- 112
16.5%
3 93
13.7%
1 82
12.1%
8 59
8.7%
9 47
 
6.9%
5 41
 
6.1%
7 40
 
5.9%
2 34
 
5.0%
6 27
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 565
83.5%
Dash Punctuation 112
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
20.9%
3 93
16.5%
1 82
14.5%
8 59
10.4%
9 47
 
8.3%
5 41
 
7.3%
7 40
 
7.1%
2 34
 
6.0%
6 27
 
4.8%
4 24
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 118
17.4%
- 112
16.5%
3 93
13.7%
1 82
12.1%
8 59
8.7%
9 47
 
6.9%
5 41
 
6.1%
7 40
 
5.9%
2 34
 
5.0%
6 27
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 118
17.4%
- 112
16.5%
3 93
13.7%
1 82
12.1%
8 59
8.7%
9 47
 
6.9%
5 41
 
6.1%
7 40
 
5.9%
2 34
 
5.0%
6 27
 
4.0%
Distinct30
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-10T20:57:43.185639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14.5
Mean length9.0714286
Min length3

Characters and Unicode

Total characters508
Distinct characters72
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)33.9%

Sample

1st row김포문화재단
2nd row경기도 고양시청 관광과
3rd row경기도 여주시청
4th row문화재청
5th row경기도 구리시청
ValueCountFrequency (%)
경기도 34
31.8%
김포시청 7
 
6.5%
관광과 6
 
5.6%
군포시청 5
 
4.7%
경기도연천군청 5
 
4.7%
양평군청 4
 
3.7%
김포문화재단 3
 
2.8%
광주시청 3
 
2.8%
공원정책과 3
 
2.8%
하남시청 3
 
2.8%
Other values (27) 34
31.8%
2024-05-10T20:57:44.027425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
10.0%
44
 
8.7%
41
 
8.1%
40
 
7.9%
40
 
7.9%
33
 
6.5%
18
 
3.5%
16
 
3.1%
15
 
3.0%
14
 
2.8%
Other values (62) 196
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 456
89.8%
Space Separator 51
 
10.0%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
44
 
9.6%
41
 
9.0%
40
 
8.8%
40
 
8.8%
33
 
7.2%
18
 
3.9%
16
 
3.5%
15
 
3.3%
14
 
3.1%
13
 
2.9%
Other values (60) 182
39.9%
Space Separator
ValueCountFrequency (%)
51
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 457
90.0%
Common 51
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
44
 
9.6%
41
 
9.0%
40
 
8.8%
40
 
8.8%
33
 
7.2%
18
 
3.9%
16
 
3.5%
15
 
3.3%
14
 
3.1%
13
 
2.8%
Other values (61) 183
40.0%
Common
ValueCountFrequency (%)
51
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 456
89.8%
ASCII 51
 
10.0%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
100.0%
Hangul
ValueCountFrequency (%)
44
 
9.6%
41
 
9.0%
40
 
8.8%
40
 
8.8%
33
 
7.2%
18
 
3.9%
16
 
3.5%
15
 
3.3%
14
 
3.1%
13
 
2.9%
Other values (60) 182
39.9%
None
ValueCountFrequency (%)
1
100.0%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-09-19
12 
2022-11-01
2023-12-15
2023-07-03
2023-05-24
Other values (12)
22 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique5 ?
Unique (%)8.9%

Sample

1st row2023-09-19
2nd row2023-07-09
3rd row2023-11-15
4th row2023-05-27
5th row2023-05-27

Common Values

ValueCountFrequency (%)
2023-09-19 12
21.4%
2022-11-01 7
12.5%
2023-12-15 6
10.7%
2023-07-03 5
8.9%
2023-05-24 4
 
7.1%
2023-12-01 4
 
7.1%
2023-05-10 3
 
5.4%
2024-02-08 2
 
3.6%
2023-04-20 2
 
3.6%
2023-07-06 2
 
3.6%
Other values (7) 9
16.1%

Length

2024-05-10T20:57:44.354075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-09-19 12
21.4%
2022-11-01 7
12.5%
2023-12-15 6
10.7%
2023-07-03 5
8.9%
2023-05-24 4
 
7.1%
2023-12-01 4
 
7.1%
2023-05-10 3
 
5.4%
2023-07-09 2
 
3.6%
2023-05-27 2
 
3.6%
2023-04-20 2
 
3.6%
Other values (7) 9
16.1%

Interactions

2024-05-10T20:57:18.785433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:13.747164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:14.822660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:16.113719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:17.376611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:19.059587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:13.984578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:15.020639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:16.351984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:17.684425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:19.316469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:14.244600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:15.304253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:16.652430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:17.948372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:19.555884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:14.445400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:15.616478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:16.898661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:18.221782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:19.798453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:14.629269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:15.883507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:17.141921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:18.498389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:57:44.591908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지명관광지구분소재지도로명주소소재지지번주소위도경도면적공공편익시설정보숙박시설정보운동및오락시설정보휴양및문화시설정보접객시설정보지원시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명데이터기준일자
관광지명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
관광지구분1.0001.0001.0001.0001.0000.0000.0001.0001.0001.0001.0001.0001.0000.0000.5560.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9801.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9910.9901.0001.000
위도1.0001.0001.0001.0001.0000.5030.4180.9550.9641.0000.9541.0000.7310.6290.5640.5400.9800.9370.9600.939
경도1.0000.0001.0001.0000.5031.0000.0850.9150.9491.0001.0001.0000.8120.9180.0000.5340.9470.9690.9270.875
면적1.0000.0001.0001.0000.4180.0851.0000.5541.0001.0001.0001.000NaN0.0000.3760.3761.0000.5800.8670.763
공공편익시설정보1.0001.0001.0001.0000.9550.9150.5541.0000.9711.0001.0001.0001.0000.9510.0000.9310.0000.9720.9710.996
숙박시설정보1.0001.0001.0001.0000.9640.9491.0000.9711.0001.0001.0001.0000.8970.5650.6871.0000.9610.8790.9440.973
운동및오락시설정보1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
휴양및문화시설정보1.0001.0001.0001.0000.9541.0001.0001.0001.0001.0001.0001.0001.0000.9630.0001.0000.9770.9660.9891.000
접객시설정보1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.000
지원시설정보1.0001.0001.0001.0000.7310.812NaN1.0000.8971.0001.0001.0001.0000.9471.000NaN1.0001.0000.8901.000
지정일자1.0000.0001.0001.0000.6290.9180.0000.9510.5651.0000.9631.0000.9471.0000.0001.0001.0000.9720.8760.957
수용인원수1.0000.5561.0001.0000.5640.0000.3760.0000.6871.0000.0001.0001.0000.0001.0000.0001.0000.0000.0000.498
주차가능수1.0000.0001.0001.0000.5400.5340.3760.9311.0001.0001.000NaNNaN1.0000.0001.0001.0000.7810.9660.812
관광지소개1.0001.0001.0000.9910.9800.9471.0000.0000.9611.0000.9771.0001.0001.0001.0001.0001.0001.0001.0001.000
관리기관전화번호1.0001.0000.9800.9900.9370.9690.5800.9720.8791.0000.9661.0001.0000.9720.0000.7811.0001.0000.9981.000
관리기관명1.0001.0001.0001.0000.9600.9270.8670.9710.9441.0000.9891.0000.8900.8760.0000.9661.0000.9981.0001.000
데이터기준일자1.0001.0001.0001.0000.9390.8750.7630.9960.9731.0001.0001.0001.0000.9570.4980.8121.0001.0001.0001.000
2024-05-10T20:57:45.034183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자관광지구분
데이터기준일자1.0000.850
관광지구분0.8501.000
2024-05-10T20:57:45.284553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적수용인원수주차가능수관광지구분데이터기준일자
위도1.000-0.224-0.061-0.165-0.1970.9330.681
경도-0.2241.0000.4030.2760.4150.0000.541
면적-0.0610.4031.0000.7530.4970.0000.471
수용인원수-0.1650.2760.7531.0000.5050.6530.237
주차가능수-0.1970.4150.4970.5051.0000.0000.513
관광지구분0.9330.0000.0000.6530.0001.0000.850
데이터기준일자0.6810.5410.4710.2370.5130.8501.000

Missing values

2024-05-10T20:57:20.196284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:57:20.967259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-10T20:57:21.426078image/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

관광지명관광지구분소재지도로명주소소재지지번주소위도경도면적공공편익시설정보숙박시설정보운동및오락시설정보휴양및문화시설정보접객시설정보지원시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명데이터기준일자
0김포국제조각공원관광지경기도 김포시 월곶면 용강로13번길 38경기도 김포시 월곶면 고막리 82-137.720804126.552204765.0월곶면사무소문수산농원펜션, 동막골캠프,문소골산장,김포관광농원,평화누리길게스트하우스<NA>문수산삼림욕장<NA><NA>1998-01-01150221통일을 주제로 조성된 테마공원으로 세계적인 조각의 작품 30여점이 전시되어 있다. 산책로를 따라 조각작품이 전시되어 있어 산림욕을 즐기면서 조각작품을 감상할 수 있다.031-984-5167김포문화재단2023-09-19
1고양관광정보센터관광지경기도 고양시 일산동구 중앙로1271-1경기도 고양시 일산동구 장항동84537.659487126.7726991732.0핸드폰충전 +컴퓨터 검색 + 우산대여서비스 + 휠체어대여 서비스 + 유모차대여서비스 + 휴계공간 + 공용화장실 + 정수기 +N버스킹존 + 한복체험실 + 민속놀이 체험존고양시 관광지 자료배포 및 행사 안내영상관25명 + 관광회의실 12명 + 북쉼터 15명 + 루프탑 30명 + 공유오피스 40명영상관+회의실+북쉼터+영상창작실+루프탑+관광기념품?? + 카페2020-11-151220고양시 관광지 자료 배포 및 시티투어 안내031-905-8396경기도 고양시청 관광과2023-07-09
2신륵사관광지관광지경기도 여주시 신륵사길 73경기도 여주시 천송동 289-737.297426127.659936947268.0관광안내소+주차장관광호텔+여관+콘도물놀이장+오락장청소년 수련실+야외음악당<NA><NA>1978-02-1140701830시원한 남한강을 따라 자전거도로, 각종 체육시설과 여주박물관, 도자세상, 농특산물 판매장이 있으며, 매년 여주도자기축제와 오곡나루축제가 이곳에서 개최되고 있다. 특히 남한강을 가르는 황포돛배(Yellow Sail boat)와 수상레저를 즐길 수 있는 가족 연인들의 나들이 공간이다031-887-2070경기도 여주시청2023-11-15
3동구릉관광지경기도 구리시 동구릉로 197경기도 구리시 인창동 66-137.617129127.1363341969675.0관리사무소+화장실+주차장<NA><NA><NA><NA><NA>1970-05-265000109유네스코 세계유산이자 사적 제193호로 지정된 「구리 동구릉(東九陵)」은 ‘도성(都城)의 동(東)쪽에 있는 아홉(九) 기의 왕릉’이라 하여 동구릉이라 붙여짐031-563-2909문화재청2023-05-27
4고구려대장간마을관광지경기도 구리시 우미내길 41경기도 구리시 아천동 산45-137.560808127.1109494928.0관리사무소+화장실+주차장<NA><NA><NA><NA><NA>2008-04-25200100국내유일의 고구려 박물관으로 아차산에서 출토된 유물을 전시하고 있으며 고구려모습을 보여주는 야외전시관을 운영031-550-8355경기도 구리시청2023-05-27
5분원백자자료관관광지경기도 광주시 남종면 산수로 1642-1경기도 광주시 남종면 분원리 116번지37.496257127.3034493339.0주차장+화장실<NA><NA>백자자료관<NA>해당없음2007-01-243000조선시대 관영사기의 변천과 도자기역사의 발자취 감상031-799-1500경기도자박물관2022-11-01
6남한산성관광지경기도 광주시 남한산성면 남한산성로 731경기도 광주시 남한산성면 산성리 158-1번지37.476696127.188417526476.0주차장+화장실펜션<NA>행궁, 만해기념관 등관광식당해당없음2007-01-2410000945역사와 문화, 4계절의 아름다움을 감상할 수 있는 곳031-8008-5155남한산성세계문화유산센터2022-11-01
7천진암관광지경기도 광주시 퇴촌면 천진암로 1203경기도 광주시 퇴촌면 우산리 500번지37.423573127.388399990000.0주차장+화장실<NA><NA>천주교박물관<NA>해당없음2007-01-2410000100천학 강학회를 통해 신앙의 차원인 천주교로 발전시킨 성지031-764-5953재단법인 천주교수원교구유지재단2022-11-01
8경안천습지생태공원관광지경기도 광주시 퇴촌면 산수로 1159경기도 광주시 퇴촌면 정지리 456-4번지37.4592127.305117162000.0주차장+화장실<NA><NA>조류관찰, 자연학습의 장<NA>해당없음2007-01-2410000115다양한 수생식물 등 조류관찰과 자연학습의 장031-760-3763광주시청 공원정책과2022-11-01
9팔당물안개공원관광지경기도 광주시 남종면 산수로 1897경기도 광주시 남종면 귀여리 267-10번지37.509563127.317461708241.0주차장+화장실+공원<NA><NA>시민의 숲, 희망의 숲, 코스모스길 등<NA>해당없음2018-01-3110000300시민의 숲, 희망의 숲, 코스모스길, 자전거길이 잘 조성된 공원031-760-4483광주시청 공원정책과2022-11-01
관광지명관광지구분소재지도로명주소소재지지번주소위도경도면적공공편익시설정보숙박시설정보운동및오락시설정보휴양및문화시설정보접객시설정보지원시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명데이터기준일자
46유니온파크관광지경기도 하남시 미사대로 710경기도 하남시 신장동 2737.546548127.22050379057.0도로+주차장+관리사무소+화장실<NA>다목적 체육관+테니스장+족구장+농구장+체육시설+어린이 물놀이시설유니온타워+야외무대<NA><NA>2015-06-01500237기존의 노후화 된 소각장, 재활용선별장, 음식물처리장, 중계펌프장 등의 시설 개선과 미사지구와 같은 택지개발사업 등으로 환경기초시설 확충이 요구됨에 따라 국내최초로 지하에 폐기물처리시설과 하수처리시설을 함께 설치한 신개념 환경기초시설이다. 지하에는 소각처리시설, 재활용선별시설, 음식물자원화시설, 하수처리시설 등이 설치되어 있고, 지상에는 잔디광장, 어린이물놀이시설, 다목적체육관, 야외체육시설 등 다양한 주민친화시설이 있는 하남유니온파크와 한강·검단산 등 하남의 아름다운 경관을 한눈에 조망할 수 있는 하남유니온타워(105m)가 설치되어있다.031-790-6255경기도 하남시청 체육진흥과2023-12-01
47광주향교관광지경기도 하남시 대성로 126-13경기도 하남시 교산동 227-337.522076127.1984187127.0공중화장실<NA><NA><NA><NA><NA>1983-09-1910045고려, 조선시대의 교육기관으로 유학을 가르치고 인재를 양성하던 곳031-790-5971경기도 하남시청 문화정책과2023-12-01
48이성산성관광지<NA>경기도 하남시 춘궁동 산 3637.525307127.184778128891.0주차장+화장실+공원<NA><NA><NA><NA><NA>2000-09-163000356세기 중반경에 신라가 쌓은 것으로 추정되는 신라시대 산성031-790-5971경기도 하남시청 문화정책과2023-12-01
49미사경정공원관광지경기도 하남시 미사대로 505경기도 하남시 신장동 281번지37.553308127.2131671329933.0조정호수+축구장+족구장+매점+자전거대여 등<NA>조정호수, 축구장, 족구장, 매점, 자전거대여 등<NA><NA><NA>1980-01-0110000350086아시안게임 및 88 서울 올림픽 당시 조정, 카누경기를 위해 만들어진 공원으로 조정호수를 중심으로 축구장, 족구장 등 스포츠시설을 비롯하여 매점, 자전거 대여 등 편의시설과 놀이시설을 갖춘 시민들의 여가선용 장소임031-790-8883한국체육산업개발주식회사2023-12-01
50수동관광지관광지경기도 남양주시 수동면 비룡로 1635경기도 남양주시 수동면 내방리 25437.757979127.27536225000.0몽골문화촌<NA><NA><NA><NA><NA>1983-10-11100119몽골문화촌031-559-8018경기도 남양주시청2023-05-11
51행주산성관광지경기도 고양시 덕양구 행주로 15번길 89경기도 고양시 덕양구 행주외동11637.596108126.828712347670.0휠체어대여 서비스+ 유모차대여서비스 + 교통약자 차량 지원+ 공중화장실 +N민속놀이 체험존행주산성 문화재 관광 안내 책자 및 행사 안내대첩기념관 20여명 + 충의정 20여명영상교육관 + 대첩기념관1963-01-212000230행주산성 사적 제 56호(행주대첩비 + 충훈정+충장사+대첩기념관+대첩비각+충의정+덕양정+진강정)031-8075-4642경기도 고양시청 관광과2023-07-09
52광명동굴관광지경기도 광명시 가학로 85번길 142경기도 광명시 가학동 2737.424679126.863432782.0주차장+화장실+매표소+방문자센터<NA>VR체험관+공포체험관라스코전시관+예술의전당+미디어타워푸드코트+노천카페+이동판매대+와인판매대+기념품샵<NA>2011-09-1140008991912년 일제가 자원수탈을 목적으로 개발을 시작한 광명동굴(구.시흥광산)은 일제강점기 징용과 수탈의 현장이자 해방 후 근대화ㆍ산업화의 흔적을 고스란히 간직한 산업유산이다. 1972년 폐광된 후 40여 년간 새우젓 창고로 쓰이며 잠들어 있던 광명동굴을 2011년 광명시가 매입하여 역사ㆍ문화 관광명소로 탈바꿈시켰다. 광명동굴은 산업유산으로서의 가치와 문화적 가치가 결합된 대한민국 최고의 동굴테마파크라는 평가를 받고 있으며 연간 100만 명 이상의 관광객이 찾는 세계가 놀란 폐광의 기적을 이루었다.070-4277-8902경기도 광명도시공사2023-06-27
53산정호수관광지경기도 포천시 영북면 산정호수로411번길 5 일원경기도 포천시 영북면 산정리 451-3일원38.065669127.315722644500.0관리사무실+화장실+주차장<NA><NA><NA><NA><NA>1977-03-3020000500백운산에서 흘러내린 맑은 물이 계곡을 이룬곳으로 경관이 수려함031-538-3363경기도 포천시청 관광사업과2023-07-06
54용문산 관광지관광지경기도 양평군 용문면 용문산로 641경기도 양평군 용문면 신점리 525-2번지37.545296127.583066382233.0관리사무소+관광안내소+ 주차장+ 공중화장실콘도+ 펜션청춘뮤지엄야영장+ 친환경농업박물관야외공연장<NA>1971-05-205000807관광지를 품에 안고 있는 용문산의 웅장한 산세와 기암괴석이 만들어 낸 절경은 금강산을 방불케 한다.031-770-2491경기도 양평군청2023-05-24
55아트빌리지(한옥마을)관광지경기도 김포시 모담공원로 170경기도 김포시 운양동 1325-137.646632126.69621280000.0화장실, 주차장전통한옥숙박시설전통놀이체험한옥마을,문화원,카페,공방,꽃집,음식점<NA>2018-03-031000142김포시 운양동 모담산 자락에 안겨 있는 김포아트빌리지는 모담산이 주는 소담한 자연의 아름다움이 느껴지는 자연친화적 문화 · 예술 공간으로서, 다양한 문화예술을 창작하고 체험할 수 있는 예술 공방, 전통한옥숙박체험관이 있고 지역문화예술 단체의 창작 활동 공간인 아트센터에는, 다목적홀, 전시관이 있으며 또한 천여 명의 관객을 수용할 수 있는 자연과 어우러지는 야외공연장으로 구성되어 있습니다.031-996-6836김포문화재단2023-09-19