Overview

Dataset statistics

Number of variables9
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory76.7 B

Variable types

Text4
Categorical2
DateTime1
Numeric2

Dataset

Description충청남도 관광지 정보로 관광지명, 관광지 구분, 공공편익시설정보, 지정일자, 수용인원수, 관광지 소개에 대한 현황 정보입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=31&beforeMenuCd=DOM_000000201001001000&publicdatapk=15118669

Alerts

수용인원수 is highly overall correlated with 주차가능수High correlation
주차가능수 is highly overall correlated with 수용인원수 and 1 other fieldsHigh correlation
관광지구분 is highly overall correlated with 주차가능수High correlation
관광지구분 is highly imbalanced (59.2%)Imbalance

Reproduction

Analysis started2024-01-09 21:17:32.098221
Analysis finished2024-01-09 21:17:33.067283
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct45
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-01-10T06:17:33.193839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length6.4489796
Min length2

Characters and Unicode

Total characters316
Distinct characters108
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

Unique41 ?
Unique (%)83.7%

Sample

1st row천안종합휴양관광지
2nd row태조산관광지
3rd row마곡사관광지
4th row공주문화관광지
5th row구드래관광지
ValueCountFrequency (%)
관광지 4
 
6.9%
마곡사관광지 2
 
3.4%
아산온천관광지 2
 
3.4%
공주문화관광지 2
 
3.4%
남당 2
 
3.4%
관광단지 1
 
1.7%
천안종합휴양관광지 1
 
1.7%
왜목마을관광지 1
 
1.7%
삽교호 1
 
1.7%
마곡온천관광지 1
 
1.7%
Other values (41) 41
70.7%
2024-01-10T06:17:33.500171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
10.4%
29
 
9.2%
28
 
8.9%
10
 
3.2%
9
 
2.8%
9
 
2.8%
6
 
1.9%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (98) 177
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
96.5%
Space Separator 9
 
2.8%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
33
 
10.8%
29
 
9.5%
28
 
9.2%
10
 
3.3%
9
 
3.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
4
 
1.3%
Other values (95) 171
56.1%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
96.5%
Common 11
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
33
 
10.8%
29
 
9.5%
28
 
9.2%
10
 
3.3%
9
 
3.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
4
 
1.3%
Other values (95) 171
56.1%
Common
ValueCountFrequency (%)
9
81.8%
) 1
 
9.1%
( 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
96.5%
ASCII 11
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
33
 
10.8%
29
 
9.5%
28
 
9.2%
10
 
3.3%
9
 
3.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
4
 
1.3%
Other values (95) 171
56.1%
ASCII
ValueCountFrequency (%)
9
81.8%
) 1
 
9.1%
( 1
 
9.1%

관광지구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
관광지
45 
관광단지
 
4

Length

Max length4
Median length3
Mean length3.0816327
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 45
91.8%
관광단지 4
 
8.2%

Length

2024-01-10T06:17:33.609800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:17:33.694734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 45
91.8%
관광단지 4
 
8.2%
Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-01-10T06:17:33.862737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length28
Mean length16.081633
Min length3

Characters and Unicode

Total characters788
Distinct characters108
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

Unique35 ?
Unique (%)71.4%

Sample

1st row주차장
2nd row주차장
3rd row화장실+주차장
4th row화장실+주차장+관리사무소+관광안내소
5th row광장+선착장+조각공원
ValueCountFrequency (%)
주차장 19
 
18.3%
화장실 10
 
9.6%
관리사무소 5
 
4.8%
공연장 4
 
3.8%
공중화장실 3
 
2.9%
상하수도시설 3
 
2.9%
주차장+화장실 3
 
2.9%
사무실 2
 
1.9%
관광안내소+화장실+주차장 2
 
1.9%
전망대 2
 
1.9%
Other values (49) 51
49.0%
2024-01-10T06:17:34.157994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
13.1%
56
 
7.1%
+ 51
 
6.5%
46
 
5.8%
45
 
5.7%
42
 
5.3%
40
 
5.1%
38
 
4.8%
30
 
3.8%
21
 
2.7%
Other values (98) 316
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
79.6%
Space Separator 56
 
7.1%
Math Symbol 51
 
6.5%
Decimal Number 20
 
2.5%
Close Punctuation 17
 
2.2%
Open Punctuation 17
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
103
16.4%
46
 
7.3%
45
 
7.2%
42
 
6.7%
40
 
6.4%
38
 
6.1%
30
 
4.8%
21
 
3.3%
19
 
3.0%
19
 
3.0%
Other values (87) 224
35.7%
Decimal Number
ValueCountFrequency (%)
3 6
30.0%
1 6
30.0%
2 3
15.0%
5 2
 
10.0%
8 1
 
5.0%
4 1
 
5.0%
6 1
 
5.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Math Symbol
ValueCountFrequency (%)
+ 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
79.6%
Common 161
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
103
16.4%
46
 
7.3%
45
 
7.2%
42
 
6.7%
40
 
6.4%
38
 
6.1%
30
 
4.8%
21
 
3.3%
19
 
3.0%
19
 
3.0%
Other values (87) 224
35.7%
Common
ValueCountFrequency (%)
56
34.8%
+ 51
31.7%
) 17
 
10.6%
( 17
 
10.6%
3 6
 
3.7%
1 6
 
3.7%
2 3
 
1.9%
5 2
 
1.2%
8 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
79.6%
ASCII 161
 
20.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
103
16.4%
46
 
7.3%
45
 
7.2%
42
 
6.7%
40
 
6.4%
38
 
6.1%
30
 
4.8%
21
 
3.3%
19
 
3.0%
19
 
3.0%
Other values (87) 224
35.7%
ASCII
ValueCountFrequency (%)
56
34.8%
+ 51
31.7%
) 17
 
10.6%
( 17
 
10.6%
3 6
 
3.7%
1 6
 
3.7%
2 3
 
1.9%
5 2
 
1.2%
8 1
 
0.6%
4 1
 
0.6%
Distinct38
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Memory size524.0 B
Minimum1900-01-01 00:00:00
Maximum2015-01-12 00:00:00
2024-01-10T06:17:34.277865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:17:34.419136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

수용인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96502.531
Minimum5
Maximum1000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-01-10T06:17:34.569118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile78
Q15000
median10000
Q345000
95-th percentile527493.6
Maximum1000000
Range999995
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation209798.62
Coefficient of variation (CV)2.174022
Kurtosis8.087047
Mean96502.531
Median Absolute Deviation (MAD)9200
Skewness2.8337274
Sum4728624
Variance4.4015461 × 1010
MonotonicityNot monotonic
2024-01-10T06:17:34.695969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
10000 8
 
16.3%
100000 5
 
10.2%
5000 4
 
8.2%
300000 2
 
4.1%
2000 1
 
2.0%
38869 1
 
2.0%
728808 1
 
2.0%
3000 1
 
2.0%
9076 1
 
2.0%
500000 1
 
2.0%
Other values (24) 24
49.0%
ValueCountFrequency (%)
5 1
2.0%
10 1
2.0%
30 1
2.0%
150 1
2.0%
280 1
2.0%
300 1
2.0%
400 1
2.0%
800 1
2.0%
1000 1
2.0%
1500 1
2.0%
ValueCountFrequency (%)
1000000 1
 
2.0%
728808 1
 
2.0%
540000 1
 
2.0%
508734 1
 
2.0%
500000 1
 
2.0%
300000 2
 
4.1%
100000 5
10.2%
45000 1
 
2.0%
38869 1
 
2.0%
30300 1
 
2.0%

주차가능수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1021.6531
Minimum2
Maximum24000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-01-10T06:17:34.797936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7
Q1150
median342
Q3700
95-th percentile2436.8
Maximum24000
Range23998
Interquartile range (IQR)550

Descriptive statistics

Standard deviation3414.1628
Coefficient of variation (CV)3.3418025
Kurtosis45.25209
Mean1021.6531
Median Absolute Deviation (MAD)213
Skewness6.6203621
Sum50061
Variance11656508
MonotonicityNot monotonic
2024-01-10T06:17:34.900218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
150 4
 
8.2%
300 4
 
8.2%
1000 3
 
6.1%
500 2
 
4.1%
408 2
 
4.1%
100 2
 
4.1%
200 2
 
4.1%
2 2
 
4.1%
350 2
 
4.1%
1334 1
 
2.0%
Other values (25) 25
51.0%
ValueCountFrequency (%)
2 2
4.1%
5 1
 
2.0%
10 1
 
2.0%
25 1
 
2.0%
35 1
 
2.0%
98 1
 
2.0%
100 2
4.1%
115 1
 
2.0%
150 4
8.2%
153 1
 
2.0%
ValueCountFrequency (%)
24000 1
 
2.0%
3093 1
 
2.0%
3000 1
 
2.0%
1592 1
 
2.0%
1381 1
 
2.0%
1334 1
 
2.0%
1137 1
 
2.0%
1086 1
 
2.0%
1000 3
6.1%
728 1
 
2.0%
Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-01-10T06:17:35.146935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length310
Median length54
Mean length66.265306
Min length10

Characters and Unicode

Total characters3247
Distinct characters422
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row중부권 최대의 온천관광지로 워터파크 휴양콘도 천안예술의 전당이 있음.
2nd row유량동 태조산 아래에 자리잡힌 넓은 공원으로 천안시민들의 문화ㆍ휴식 공간
3rd row천년고찰 마곡사 관광지
4th row백제역사 유적관광지
5th row백마강과 함께 가족단위 공원 심터 및 생활체육을 즐길수 있는 웰빙관광지
ValueCountFrequency (%)
13
 
1.7%
있음 9
 
1.2%
9
 
1.2%
있는 8
 
1.1%
8
 
1.1%
7
 
0.9%
있으며 6
 
0.8%
온천 6
 
0.8%
가족단위 5
 
0.7%
선생의 5
 
0.7%
Other values (578) 685
90.0%
2024-01-10T06:17:35.528174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
712
 
21.9%
64
 
2.0%
54
 
1.7%
54
 
1.7%
47
 
1.4%
44
 
1.4%
41
 
1.3%
40
 
1.2%
40
 
1.2%
38
 
1.2%
Other values (412) 2113
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2382
73.4%
Space Separator 712
 
21.9%
Decimal Number 85
 
2.6%
Other Punctuation 31
 
1.0%
Lowercase Letter 13
 
0.4%
Dash Punctuation 6
 
0.2%
Uppercase Letter 5
 
0.2%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
64
 
2.7%
54
 
2.3%
54
 
2.3%
47
 
2.0%
44
 
1.8%
41
 
1.7%
40
 
1.7%
40
 
1.7%
38
 
1.6%
35
 
1.5%
Other values (383) 1925
80.8%
Decimal Number
ValueCountFrequency (%)
1 20
23.5%
9 16
18.8%
2 12
14.1%
0 12
14.1%
3 6
 
7.1%
4 5
 
5.9%
7 5
 
5.9%
6 3
 
3.5%
5 3
 
3.5%
8 3
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
m 5
38.5%
k 3
23.1%
a 3
23.1%
h 1
 
7.7%
i 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
D 1
20.0%
C 1
20.0%
N 1
20.0%
S 1
20.0%
O 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 28
90.3%
· 2
 
6.5%
1
 
3.2%
Space Separator
ValueCountFrequency (%)
712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2382
73.4%
Common 847
 
26.1%
Latin 18
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
64
 
2.7%
54
 
2.3%
54
 
2.3%
47
 
2.0%
44
 
1.8%
41
 
1.7%
40
 
1.7%
40
 
1.7%
38
 
1.6%
35
 
1.5%
Other values (383) 1925
80.8%
Common
ValueCountFrequency (%)
712
84.1%
. 28
 
3.3%
1 20
 
2.4%
9 16
 
1.9%
2 12
 
1.4%
0 12
 
1.4%
3 6
 
0.7%
- 6
 
0.7%
4 5
 
0.6%
7 5
 
0.6%
Other values (9) 25
 
3.0%
Latin
ValueCountFrequency (%)
m 5
27.8%
k 3
16.7%
a 3
16.7%
h 1
 
5.6%
D 1
 
5.6%
C 1
 
5.6%
N 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
O 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2381
73.3%
ASCII 860
 
26.5%
Geometric Shapes 2
 
0.1%
None 2
 
0.1%
Punctuation 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
712
82.8%
. 28
 
3.3%
1 20
 
2.3%
9 16
 
1.9%
2 12
 
1.4%
0 12
 
1.4%
3 6
 
0.7%
- 6
 
0.7%
m 5
 
0.6%
4 5
 
0.6%
Other values (16) 38
 
4.4%
Hangul
ValueCountFrequency (%)
64
 
2.7%
54
 
2.3%
54
 
2.3%
47
 
2.0%
44
 
1.8%
41
 
1.7%
40
 
1.7%
40
 
1.7%
38
 
1.6%
35
 
1.5%
Other values (382) 1924
80.8%
Geometric Shapes
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
· 2
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-01-10T06:17:35.713213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.877551
Min length9

Characters and Unicode

Total characters582
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

Unique23 ?
Unique (%)46.9%

Sample

1st row041-906-7000
2nd row041-550-2520
3rd row1899-0088
4th row1899-0088
5th row041-830-2222
ValueCountFrequency (%)
042-840-2402 5
 
10.2%
041-350-3592 3
 
6.1%
041-830-2222 3
 
6.1%
041-350-3601 3
 
6.1%
041-950-4018 2
 
4.1%
041-830-2214 2
 
4.1%
1899-0088 2
 
4.1%
041-339-7303 2
 
4.1%
041-521-5159 2
 
4.1%
041-540-2822 2
 
4.1%
Other values (23) 23
46.9%
2024-01-10T06:17:36.024135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 115
19.8%
- 96
16.5%
4 78
13.4%
1 66
11.3%
2 57
9.8%
8 41
 
7.0%
3 38
 
6.5%
5 30
 
5.2%
9 26
 
4.5%
6 22
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 486
83.5%
Dash Punctuation 96
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 115
23.7%
4 78
16.0%
1 66
13.6%
2 57
11.7%
8 41
 
8.4%
3 38
 
7.8%
5 30
 
6.2%
9 26
 
5.3%
6 22
 
4.5%
7 13
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 582
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 115
19.8%
- 96
16.5%
4 78
13.4%
1 66
11.3%
2 57
9.8%
8 41
 
7.0%
3 38
 
6.5%
5 30
 
5.2%
9 26
 
4.5%
6 22
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 115
19.8%
- 96
16.5%
4 78
13.4%
1 66
11.3%
2 57
9.8%
8 41
 
7.0%
3 38
 
6.5%
5 30
 
5.2%
9 26
 
4.5%
6 22
 
3.8%

관리기관명
Categorical

Distinct19
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
충청남도 당진시청
충청남도 부여군청
충청남도 계룡시
충청남도 서산시청
충청남도 공주시청
Other values (14)
25 

Length

Max length10
Median length9
Mean length8.5714286
Min length3

Unique

Unique7 ?
Unique (%)14.3%

Sample

1st row소노벨 천안
2nd row천안시시설관리공단
3rd row공주시
4th row공주시
5th row충청남도 부여군청

Common Values

ValueCountFrequency (%)
충청남도 당진시청 6
12.2%
충청남도 부여군청 5
10.2%
충청남도 계룡시 5
10.2%
충청남도 서산시청 4
 
8.2%
충청남도 공주시청 4
 
8.2%
충청남도 예산군청 4
 
8.2%
충청남도 천안시청 3
 
6.1%
충청남도 서천군청 3
 
6.1%
충청남도 홍성군청 2
 
4.1%
충청남도 아산시청 2
 
4.1%
Other values (9) 11
22.4%

Length

2024-01-10T06:17:36.143377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청남도 42
44.7%
당진시청 6
 
6.4%
부여군청 5
 
5.3%
계룡시 5
 
5.3%
예산군청 4
 
4.3%
아산시청 4
 
4.3%
공주시청 4
 
4.3%
서산시청 4
 
4.3%
천안시청 3
 
3.2%
서천군청 3
 
3.2%
Other values (11) 14
 
14.9%

Interactions

2024-01-10T06:17:32.777364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:17:32.654597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:17:32.840396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:17:32.714230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:17:36.221655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지명관광지구분공공편익시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명
관광지명1.0001.0000.9550.9851.0001.0000.9930.3170.937
관광지구분1.0001.0000.4171.0000.5450.4341.0000.0000.242
공공편익시설정보0.9550.4171.0000.9700.9170.0000.9790.9360.955
지정일자0.9851.0000.9701.0000.7000.0000.9730.7420.958
수용인원수1.0000.5450.9170.7001.0000.9191.0000.0000.000
주차가능수1.0000.4340.0000.0000.9191.0001.0000.6050.000
관광지소개0.9931.0000.9790.9731.0001.0001.0000.9451.000
관리기관전화번호0.3170.0000.9360.7420.0000.6050.9451.0001.000
관리기관명0.9370.2420.9550.9580.0000.0001.0001.0001.000
2024-01-10T06:17:36.324036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명관광지구분
관리기관명1.0000.148
관광지구분0.1481.000
2024-01-10T06:17:36.388120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용인원수주차가능수관광지구분관리기관명
수용인원수1.0000.5100.3750.000
주차가능수0.5101.0000.6680.000
관광지구분0.3750.6681.0000.148
관리기관명0.0000.0000.1481.000

Missing values

2024-01-10T06:17:32.923923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:17:33.027088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

관광지명관광지구분공공편익시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명
0천안종합휴양관광지관광지주차장1996-07-025000500중부권 최대의 온천관광지로 워터파크 휴양콘도 천안예술의 전당이 있음.041-906-7000소노벨 천안
1태조산관광지관광지주차장1985-07-2410000300유량동 태조산 아래에 자리잡힌 넓은 공원으로 천안시민들의 문화ㆍ휴식 공간041-550-2520천안시시설관리공단
2마곡사관광지관광지화장실+주차장1994-03-305000100천년고찰 마곡사 관광지1899-0088공주시
3공주문화관광지관광지화장실+주차장+관리사무소+관광안내소2007-09-275000100백제역사 유적관광지1899-0088공주시
4구드래관광지관광지광장+선착장+조각공원1969-01-2145000300백마강과 함께 가족단위 공원 심터 및 생활체육을 즐길수 있는 웰빙관광지041-830-2222충청남도 부여군청
5서동요역사관광지관광지관리사무소+주차장+화장실2008-11-20400150역사문화환경을 구축하여 부여 대표 관광명소041-830-2222충청남도 부여군청
6백제문화관광단지관광단지주차장+화장실2015-01-121000003000고유의 교육적 가치 제고 및 관광 지역경제 활성화를 위한 슈요자 중심의 체류형 종합 관광단지041-830-2222충청남도 부여군청
7서산류방택천문기상과학관관광지사무실 화장실 주차장1900-01-0128025천상열차분야지도를 제작한 충남 서산 출신 고려말 천문학자 류방택 선생의 뜻을 기려 설립된 과학관041-661-8009충청남도 서산시청
8서산버드랜드관광지화장실(5동) 주차장 안내소(4개소)2013-11-0110000200철새도래시기에는 천수만에 도래하는 철새들을 탐조투어를 통해 볼 수 있고 특별프로그램 기간에는 각종 체험행사 등을 경험할 수 있으며 4D 영상 등의 볼거리가 있음.041-661-8046충청남도 서산시청
9용현자연휴양림관광지관리사무소 화장실 주차장2000-06-1280098용현계곡 한가운데 자리해 심산유곡의 경치를 자랑하는 산림휴양의 적지041-664-1978국립자연휴양림관리소
관광지명관광지구분공공편익시설정보지정일자수용인원수주차가능수관광지소개관리기관전화번호관리기관명
39춘장대관광지종합안내소+주차장+화장실+취사장1977-04-21100000300국내 유일의 해송림 해수욕장으로 캠핑장과 조개잡이 체험등 다양한 즐길거리와 인근 동백정 마량항등 볼거리도 풍부041-950-4018충청남도 서천군청
40신정호국민관광지관광지관리사무소화장실주차장변전실1971-05-202000670신정호는 담수면적이 92ha이며 농업용수 공급을 목적으로 1926년에 만들어진 인공호수이다.041-540-8725충남 아산시청
41아산온천관광지관광지관리사무소화장실주차장일반광장1991-03-1515003501987년에 발견되어 1991년에 관광지로 지정된 아산온천은 2001년 테마 온천 시설인 아산스파비스가 개장된 이후로 인기가 높다. 약알칼리성 온천으로 20여종의 인체에 유익한 성분이 다량 함유되어 있다.041-540-2689충남 아산시청
42덕산온천관광단지관광단지관광안내소+화장실(2동)+주차장1981-09-221000003501917년 처음으로 탕을 이용한 온천으로 개장됐으며 49도씨 이상의 천연중탄산나트륨 온천수로 전국 최고의 온천수로 인정받고 있다.041-339-7303충청남도 예산군청
43예당국민관광지관광지관리사무소+화장실(6동)+주차장1986-05-0220000185예당호를 배경으로 예당호 출렁다리 예당호 조각공원 느린호수길 캠핑장 야영장이 조성되어 있어 가족단위 휴양객이 즐길수 있는 관광지041-339-8282충청남도 예산군청
44이심원충신정려현판관광지주차장1995-03-0652효령대군의 증손인 이심원선생의 충직함을 기리기 위한 현판042-840-2402충청남도 계룡시
45신원재관광지주차장2002-01-10305사계 김장생 선생의 9번째 아들인 김비 선생의 재실042-840-2402충청남도 계룡시
46사계고택관광지관리사무소+화장실(1동)+주차장2013-11-1115010조선중기 유학의 대가 사계김장생 선생의고택042-840-2402충청남도 계룡시
47모원재관광지화장실(1동)+주차장1989-04-2030035사계 김장생 선생의 5대 선친인 김국광의 재실042-840-2402충청남도 계룡시
48염선재관광지주차장1990-09-27102사계 김장생 선생의 계배 순천김씨의 재실042-840-2402충청남도 계룡시