Overview

Dataset statistics

Number of variables7
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory63.0 B

Variable types

Categorical1
Text3
DateTime2
Numeric1

Dataset

Description충청북도내 관광지 정보에 대한 데이터로 시군, 관광지명, 위치, 최초지정일, 최종변경일, 면적(㎡), 주요 관광자원 등과 같은 정보를 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/3067368/fileData.do

Alerts

관광지명 has unique valuesUnique
최종변경일 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:11:27.224375
Analysis finished2023-12-12 15:11:27.775767
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Categorical

Distinct8
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size308.0 B
제천시
충주시
단양군
보은군
영동군
Other values (3)

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row충주시
2nd row충주시
3rd row충주시
4th row충주시
5th row제천시

Common Values

ValueCountFrequency (%)
제천시 7
31.8%
충주시 4
18.2%
단양군 3
13.6%
보은군 2
 
9.1%
영동군 2
 
9.1%
괴산군 2
 
9.1%
옥천군 1
 
4.5%
음성군 1
 
4.5%

Length

2023-12-13T00:11:27.827170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:11:27.930387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제천시 7
31.8%
충주시 4
18.2%
단양군 3
13.6%
보은군 2
 
9.1%
영동군 2
 
9.1%
괴산군 2
 
9.1%
옥천군 1
 
4.5%
음성군 1
 
4.5%

관광지명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T00:11:28.100231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.6363636
Min length2

Characters and Unicode

Total characters80
Distinct characters56
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row세계무술공원
2nd row충주호체험
3rd row능암온천
4th row충온온천
5th row교리
ValueCountFrequency (%)
세계무술공원 1
 
4.0%
속리산레저 1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
다리안 1
 
4.0%
무극전적 1
 
4.0%
수옥정 1
 
4.0%
괴강 1
 
4.0%
송호 1
 
4.0%
Other values (15) 15
60.0%
2023-12-13T00:11:28.423219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
6.2%
5
 
6.2%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
2
 
2.5%
2
 
2.5%
2
 
2.5%
Other values (46) 49
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
92.5%
Space Separator 3
 
3.8%
Uppercase Letter 3
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
6.8%
5
 
6.8%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (42) 44
59.5%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
B 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
92.5%
Common 3
 
3.8%
Latin 3
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
6.8%
5
 
6.8%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (42) 44
59.5%
Latin
ValueCountFrequency (%)
K 1
33.3%
B 1
33.3%
S 1
33.3%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
92.5%
ASCII 6
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
 
6.8%
5
 
6.8%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (42) 44
59.5%
ASCII
ValueCountFrequency (%)
3
50.0%
K 1
 
16.7%
B 1
 
16.7%
S 1
 
16.7%

위치
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T00:11:28.621596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.7272727
Min length3

Characters and Unicode

Total characters148
Distinct characters50
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

Unique18 ?
Unique (%)81.8%

Sample

1st row금릉동
2nd row가금면 탑평리
3rd row앙성면 능암리
4th row앙성면 돈산리
5th row청풍면 교리
ValueCountFrequency (%)
청풍면 3
 
7.0%
단양읍 2
 
4.7%
교리 2
 
4.7%
앙성면 2
 
4.7%
천동리 2
 
4.7%
수산면 2
 
4.7%
금성면 2
 
4.7%
원풍리 1
 
2.3%
송호리 1
 
2.3%
괴산읍 1
 
2.3%
Other values (25) 25
58.1%
2023-12-13T00:11:28.955590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
14.9%
22
14.9%
16
 
10.8%
7
 
4.7%
6
 
4.1%
5
 
3.4%
5
 
3.4%
4
 
2.7%
4
 
2.7%
3
 
2.0%
Other values (40) 54
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
85.1%
Space Separator 22
 
14.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
22
17.5%
16
 
12.7%
7
 
5.6%
6
 
4.8%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
3
 
2.4%
3
 
2.4%
Other values (39) 51
40.5%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
85.1%
Common 22
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
17.5%
16
 
12.7%
7
 
5.6%
6
 
4.8%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
3
 
2.4%
3
 
2.4%
Other values (39) 51
40.5%
Common
ValueCountFrequency (%)
22
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
85.1%
ASCII 22
 
14.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
100.0%
Hangul
ValueCountFrequency (%)
22
17.5%
16
 
12.7%
7
 
5.6%
6
 
4.8%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
3
 
2.4%
3
 
2.4%
Other values (39) 51
40.5%
Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum1969-01-21 00:00:00
Maximum2010-10-08 00:00:00
2023-12-13T00:11:29.077929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:29.198340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

최종변경일
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2007-06-22 00:00:00
Maximum2022-08-12 00:00:00
2023-12-13T00:11:29.374322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:29.499355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265924.36
Minimum18499
Maximum1750523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T00:11:29.624802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18499
5-th percentile92767.1
Q1131594.75
median176721
Q3235053.5
95-th percentile602001.4
Maximum1750523
Range1732024
Interquartile range (IQR)103458.75

Descriptive statistics

Standard deviation352305.24
Coefficient of variation (CV)1.3248325
Kurtosis16.609137
Mean265924.36
Median Absolute Deviation (MAD)52418
Skewness3.9176406
Sum5850336
Variance1.2411898 × 1011
MonotonicityNot monotonic
2023-12-13T00:11:29.766048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
617325 1
 
4.5%
130191 1
 
4.5%
97576 1
 
4.5%
120982 1
 
4.5%
154737 1
 
4.5%
18499 1
 
4.5%
225818 1
 
4.5%
238132 1
 
4.5%
284000 1
 
4.5%
1750523 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
18499 1
4.5%
92514 1
4.5%
97576 1
4.5%
100272 1
4.5%
120982 1
4.5%
130191 1
4.5%
135806 1
4.5%
136818 1
4.5%
146276 1
4.5%
147440 1
4.5%
ValueCountFrequency (%)
1750523 1
4.5%
617325 1
4.5%
310853 1
4.5%
296700 1
4.5%
284000 1
4.5%
238132 1
4.5%
225818 1
4.5%
224825 1
4.5%
223134 1
4.5%
199210 1
4.5%
Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T00:11:29.998200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length18.727273
Min length2

Characters and Unicode

Total characters412
Distinct characters136
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)63.6%

Sample

1st row충주호, 탄금호, 중앙탑, 중원고구려비, 탄금대
2nd row충주호, 탄금호, 중앙탑, 중원고구려비, 탄금대
3rd row탄산온천
4th row탄산온천
5th row청풍리조트
ValueCountFrequency (%)
3
 
3.9%
충주호 2
 
2.6%
삼년산성 2
 
2.6%
괴산댐 2
 
2.6%
옛길 2
 
2.6%
산막이 2
 
2.6%
화양구곡 2
 
2.6%
선유구곡 2
 
2.6%
쌍곡구곡 2
 
2.6%
탄산온천 2
 
2.6%
Other values (45) 55
72.4%
2023-12-13T00:11:30.414926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
13.3%
, 49
 
11.9%
16
 
3.9%
12
 
2.9%
9
 
2.2%
8
 
1.9%
6
 
1.5%
6
 
1.5%
6
 
1.5%
5
 
1.2%
Other values (126) 240
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
74.0%
Space Separator 55
 
13.3%
Other Punctuation 50
 
12.1%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16
 
5.2%
12
 
3.9%
9
 
3.0%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (121) 227
74.4%
Other Punctuation
ValueCountFrequency (%)
, 49
98.0%
. 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
74.0%
Common 105
 
25.5%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16
 
5.2%
12
 
3.9%
9
 
3.0%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (121) 227
74.4%
Common
ValueCountFrequency (%)
55
52.4%
, 49
46.7%
. 1
 
1.0%
Latin
ValueCountFrequency (%)
E 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
74.0%
ASCII 107
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
51.4%
, 49
45.8%
E 1
 
0.9%
. 1
 
0.9%
S 1
 
0.9%
Hangul
ValueCountFrequency (%)
16
 
5.2%
12
 
3.9%
9
 
3.0%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (121) 227
74.4%

Interactions

2023-12-13T00:11:27.535084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:11:30.519867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군관광지명위치최초지정일최종변경일면적(제곱미터)주요 관광자원
시군1.0001.0001.0001.0001.0000.6001.000
관광지명1.0001.0001.0001.0001.0001.0001.000
위치1.0001.0001.0000.9821.0000.9560.967
최초지정일1.0001.0000.9821.0001.0001.0000.979
최종변경일1.0001.0001.0001.0001.0001.0001.000
면적(제곱미터)0.6001.0000.9561.0001.0001.0000.699
주요 관광자원1.0001.0000.9670.9791.0000.6991.000
2023-12-13T00:11:30.636392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)시군
면적(제곱미터)1.0000.354
시군0.3541.000

Missing values

2023-12-13T00:11:27.637669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:11:27.734736image/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

시군관광지명위치최초지정일최종변경일면적(제곱미터)주요 관광자원
0충주시세계무술공원금릉동1980-10-302016-12-09617325충주호, 탄금호, 중앙탑, 중원고구려비, 탄금대
1충주시충주호체험가금면 탑평리2004-08-132016-07-08223134충주호, 탄금호, 중앙탑, 중원고구려비, 탄금대
2충주시능암온천앙성면 능암리1989-12-142016-06-10199210탄산온천
3충주시충온온천앙성면 돈산리1989-12-142011-02-18224825탄산온천
4제천시교리청풍면 교리1989-12-282020-08-14310853청풍리조트
5제천시능강수산면 능강리1997-06-272008-04-18136818E.S리조트
6제천시금월봉금성면 월굴리1998-05-292016-03-2592514콘도, 수석공원, 수상레저시설
7제천시계산청풍면 계산리1998-07-242018-01-24135806펜션,조각공원,눈썰매장,모노레일
8제천시제천온천수산면 내리2002-01-162011-01-16296700온천
9제천시만남의광장청풍면 교리2004-08-272012-12-27147440번지점프, 인공암벽, 휴게소, 야생화원
시군관광지명위치최초지정일최종변경일면적(제곱미터)주요 관광자원
12보은군속리산레저속리산면 상판리1996-10-042007-06-22130191속리산국립공원, 법주사, 구병산, 삼년산성
13옥천군장계안내면 장계리1986-06-072010-05-04198705향토전시관, 육영수생가, 정지용 생가 및 문학관
14영동군레인보우힐링영동읍 매천리2010-10-082022-08-121750523과일나라테마공원, 와인터널,와인연구소,복합문화예술회관
15영동군송호양산면 송호리1977-10-312013-10-21284000금강수변, 솔밭 및 양산팔경
16괴산군괴강괴산읍 검승리2000-12-272007-08-03238132쌍곡구곡, 선유구곡, 화양구곡, 산막이 옛길, 괴산댐, 충민사
17괴산군수옥정연풍면 원풍리1995-12-082021-12-17225818쌍곡구곡, 선유구곡, 화양구곡, 산막이 옛길, 괴산댐, 조령산 휴양림
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