Overview

Dataset statistics

Number of variables8
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory68.7 B

Variable types

Numeric2
Categorical3
Text3

Dataset

Description전북특별자치도내에 있는 테마길 현황(아름다운 순례길, 모악산 마실길, 서해안 해변 마실길, 마음이 머무는 길)전북특별자치도 내 테마길이 위치한 시군의 이름, 전북특별자치도 내에 있는 테마길의 길 이름
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055532/fileData.do

Alerts

자료출처 has constant value ""Constant
순번 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 순번High correlation
길명 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 18:44:11.165732
Analysis finished2024-03-14 18:44:13.345772
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T03:44:13.700759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2024-03-15T03:44:13.973990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Memory size512.0 B
완주군
9 
김제시
6 
익산시
4 
순창군
4 
진안군
4 
Other values (9)
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)6.2%

Sample

1st row전주시
2nd row완주군
3rd row완주군
4th row익산시
5th row익산시

Common Values

ValueCountFrequency (%)
완주군 9
18.8%
김제시 6
12.5%
익산시 4
8.3%
순창군 4
8.3%
진안군 4
8.3%
고창군 4
8.3%
전주시 3
 
6.2%
부안군 3
 
6.2%
군산시 3
 
6.2%
남원시 3
 
6.2%
Other values (4) 5
10.4%

Length

2024-03-15T03:44:14.316496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주군 9
18.8%
김제시 6
12.5%
익산시 4
8.3%
순창군 4
8.3%
진안군 4
8.3%
고창군 4
8.3%
전주시 3
 
6.2%
부안군 3
 
6.2%
군산시 3
 
6.2%
남원시 3
 
6.2%
Other values (4) 5
10.4%

길명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size512.0 B
마음이 머무는길
30 
아름다운 순례길
9 
모악산 마실길
7 
서해안 해변 마실길
 
2

Length

Max length10
Median length8
Mean length7.9375
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아름다운 순례길
2nd row아름다운 순례길
3rd row아름다운 순례길
4th row아름다운 순례길
5th row아름다운 순례길

Common Values

ValueCountFrequency (%)
마음이 머무는길 30
62.5%
아름다운 순례길 9
 
18.8%
모악산 마실길 7
 
14.6%
서해안 해변 마실길 2
 
4.2%

Length

2024-03-15T03:44:14.705445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:44:15.007817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마음이 30
30.6%
머무는길 30
30.6%
아름다운 9
 
9.2%
순례길 9
 
9.2%
마실길 9
 
9.2%
모악산 7
 
7.1%
서해안 2
 
2.0%
해변 2
 
2.0%

도로명주소
Text

Distinct42
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-03-15T03:44:16.224900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length15.895833
Min length13

Characters and Unicode

Total characters763
Distinct characters117
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

Unique36 ?
Unique (%)75.0%

Sample

1st row전주시 완산구 태조로 6
2nd row완주군 소양면 송광수만로 255-16
3rd row완주군 비봉면 천호성지길 124
4th row익산시 망성면 나바위길 77-4
5th row익산시 금마면 미륵사지로 362
ValueCountFrequency (%)
완주군 9
 
4.7%
김제시 6
 
3.1%
고창군 4
 
2.1%
구이면 4
 
2.1%
순창군 4
 
2.1%
진안군 4
 
2.1%
금산면 4
 
2.1%
익산시 4
 
2.1%
완산구 3
 
1.6%
군산시 3
 
1.6%
Other values (111) 147
76.6%
2024-03-15T03:44:17.879084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
18.9%
면 40
 
5.2%
군 31
 
4.1%
길 28
 
3.7%
1 28
 
3.7%
시 21
 
2.8%
산 20
 
2.6%
로 20
 
2.6%
4 18
 
2.4%
7 18
 
2.4%
Other values (107) 395
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
60.7%
Space Separator 144
 
18.9%
Decimal Number 141
 
18.5%
Dash Punctuation 15
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 40
 
8.6%
군 31
 
6.7%
길 28
 
6.0%
시 21
 
4.5%
산 20
 
4.3%
로 20
 
4.3%
주 14
 
3.0%
완 12
 
2.6%
금 12
 
2.6%
구 11
 
2.4%
Other values (95) 254
54.9%
Decimal Number
ValueCountFrequency (%)
1 28
19.9%
4 18
12.8%
7 18
12.8%
5 17
12.1%
2 12
8.5%
3 12
8.5%
6 11
 
7.8%
9 11
 
7.8%
0 8
 
5.7%
8 6
 
4.3%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
60.7%
Common 300
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 40
 
8.6%
군 31
 
6.7%
길 28
 
6.0%
시 21
 
4.5%
산 20
 
4.3%
로 20
 
4.3%
주 14
 
3.0%
완 12
 
2.6%
금 12
 
2.6%
구 11
 
2.4%
Other values (95) 254
54.9%
Common
ValueCountFrequency (%)
144
48.0%
1 28
 
9.3%
4 18
 
6.0%
7 18
 
6.0%
5 17
 
5.7%
- 15
 
5.0%
2 12
 
4.0%
3 12
 
4.0%
6 11
 
3.7%
9 11
 
3.7%
Other values (2) 14
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
60.7%
ASCII 300
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
48.0%
1 28
 
9.3%
4 18
 
6.0%
7 18
 
6.0%
5 17
 
5.7%
- 15
 
5.0%
2 12
 
4.0%
3 12
 
4.0%
6 11
 
3.7%
9 11
 
3.7%
Other values (2) 14
 
4.7%
Hangul
ValueCountFrequency (%)
면 40
 
8.6%
군 31
 
6.7%
길 28
 
6.0%
시 21
 
4.5%
산 20
 
4.3%
로 20
 
4.3%
주 14
 
3.0%
완 12
 
2.6%
금 12
 
2.6%
구 11
 
2.4%
Other values (95) 254
54.9%

시점위치
Text

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-03-15T03:44:18.771778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8.5
Mean length5.125
Min length2

Characters and Unicode

Total characters246
Distinct characters117
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

Unique40 ?
Unique (%)83.3%

Sample

1st row전주한옥마을
2nd row송광사
3rd row완주 천호
4th row나바위
5th row익산 미륵사지
ValueCountFrequency (%)
금구면사무소 2
 
3.7%
영모정 2
 
3.7%
도립미술관 2
 
3.7%
강경마을 2
 
3.7%
원덕현마을 1
 
1.9%
송광사 1
 
1.9%
주천면(치안센터 1
 
1.9%
전주한옥마을 1
 
1.9%
중평마을 1
 
1.9%
운봉읍(농협 1
 
1.9%
Other values (40) 40
74.1%
2024-03-15T03:44:20.468141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
을 10
 
4.1%
마 10
 
4.1%
사 7
 
2.8%
주 7
 
2.8%
6
 
2.4%
( 6
 
2.4%
) 6
 
2.4%
산 6
 
2.4%
구 6
 
2.4%
경 5
 
2.0%
Other values (107) 177
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
92.7%
Space Separator 6
 
2.4%
Open Punctuation 6
 
2.4%
Close Punctuation 6
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
을 10
 
4.4%
마 10
 
4.4%
사 7
 
3.1%
주 7
 
3.1%
산 6
 
2.6%
구 6
 
2.6%
경 5
 
2.2%
천 5
 
2.2%
금 5
 
2.2%
도 5
 
2.2%
Other values (104) 162
71.1%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 228
92.7%
Common 18
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
을 10
 
4.4%
마 10
 
4.4%
사 7
 
3.1%
주 7
 
3.1%
산 6
 
2.6%
구 6
 
2.6%
경 5
 
2.2%
천 5
 
2.2%
금 5
 
2.2%
도 5
 
2.2%
Other values (104) 162
71.1%
Common
ValueCountFrequency (%)
6
33.3%
( 6
33.3%
) 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 228
92.7%
ASCII 18
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
을 10
 
4.4%
마 10
 
4.4%
사 7
 
3.1%
주 7
 
3.1%
산 6
 
2.6%
구 6
 
2.6%
경 5
 
2.2%
천 5
 
2.2%
금 5
 
2.2%
도 5
 
2.2%
Other values (104) 162
71.1%
ASCII
ValueCountFrequency (%)
6
33.3%
( 6
33.3%
) 6
33.3%

명칭
Text

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-03-15T03:44:21.866782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.2291667
Min length2

Characters and Unicode

Total characters251
Distinct characters100
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

Unique41 ?
Unique (%)85.4%

Sample

1st row한옥마을
2nd row송광사
3rd row천호
4th row나바위
5th row미륵사지
ValueCountFrequency (%)
완주군 3
 
4.4%
구간 3
 
4.4%
전주시 2
 
2.9%
금구 2
 
2.9%
김제시 2
 
2.9%
고종시 2
 
2.9%
마실길1 2
 
2.9%
마실길2 2
 
2.9%
신시도 2
 
2.9%
둘레길 2
 
2.9%
Other values (45) 46
67.6%
2024-03-15T03:44:23.180229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 26
 
10.4%
20
 
8.0%
마 10
 
4.0%
시 8
 
3.2%
주 7
 
2.8%
구 7
 
2.8%
실 6
 
2.4%
고 5
 
2.0%
금 5
 
2.0%
천 5
 
2.0%
Other values (90) 152
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
87.3%
Space Separator 20
 
8.0%
Decimal Number 8
 
3.2%
Math Symbol 3
 
1.2%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 26
 
11.9%
마 10
 
4.6%
시 8
 
3.7%
주 7
 
3.2%
구 7
 
3.2%
실 6
 
2.7%
고 5
 
2.3%
금 5
 
2.3%
천 5
 
2.3%
군 5
 
2.3%
Other values (84) 135
61.6%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 3
37.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
87.3%
Common 32
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 26
 
11.9%
마 10
 
4.6%
시 8
 
3.7%
주 7
 
3.2%
구 7
 
3.2%
실 6
 
2.7%
고 5
 
2.3%
금 5
 
2.3%
천 5
 
2.3%
군 5
 
2.3%
Other values (84) 135
61.6%
Common
ValueCountFrequency (%)
20
62.5%
2 4
 
12.5%
1 3
 
9.4%
~ 3
 
9.4%
- 1
 
3.1%
3 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
87.3%
ASCII 32
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 26
 
11.9%
마 10
 
4.6%
시 8
 
3.7%
주 7
 
3.2%
구 7
 
3.2%
실 6
 
2.7%
고 5
 
2.3%
금 5
 
2.3%
천 5
 
2.3%
군 5
 
2.3%
Other values (84) 135
61.6%
ASCII
ValueCountFrequency (%)
20
62.5%
2 4
 
12.5%
1 3
 
9.4%
~ 3
 
9.4%
- 1
 
3.1%
3 1
 
3.1%

거리(km)
Real number (ℝ)

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.554375
Minimum0.6
Maximum55.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T03:44:23.516644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile2.14
Q17.075
median13
Q323.925
95-th percentile42.065
Maximum55.3
Range54.7
Interquartile range (IQR)16.85

Descriptive statistics

Standard deviation12.555489
Coefficient of variation (CV)0.75843932
Kurtosis1.5037742
Mean16.554375
Median Absolute Deviation (MAD)7.75
Skewness1.2110959
Sum794.61
Variance157.6403
MonotonicityNot monotonic
2024-03-15T03:44:23.917941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3.8 2
 
4.2%
26.5 2
 
4.2%
19.7 2
 
4.2%
4.0 2
 
4.2%
28.0 1
 
2.1%
42.1 1
 
2.1%
11.5 1
 
2.1%
6.5 1
 
2.1%
10.2 1
 
2.1%
19.48 1
 
2.1%
Other values (34) 34
70.8%
ValueCountFrequency (%)
0.6 1
2.1%
1.5 1
2.1%
2.0 1
2.1%
2.4 1
2.1%
3.8 2
4.2%
4.0 2
4.2%
4.5 1
2.1%
5.5 1
2.1%
6.5 1
2.1%
7.0 1
2.1%
ValueCountFrequency (%)
55.3 1
2.1%
50.0 1
2.1%
42.1 1
2.1%
42.0 1
2.1%
29.3 1
2.1%
28.0 1
2.1%
27.5 1
2.1%
26.5 2
4.2%
26.0 1
2.1%
25.5 1
2.1%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size512.0 B
관광총괄과
48 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광총괄과 48
100.0%

Length

2024-03-15T03:44:24.253499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:44:24.499577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 48
100.0%

Interactions

2024-03-15T03:44:12.346496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:44:11.870400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:44:12.585761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:44:12.110468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:44:24.603369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명길명도로명주소시점위치명칭거리(km)
순번1.0000.8560.9160.9460.9490.9370.592
시군명0.8561.0000.6461.0001.0000.9900.421
길명0.9160.6461.0000.9641.0001.0000.851
도로명주소0.9461.0000.9641.0001.0000.9760.521
시점위치0.9491.0001.0001.0001.0000.9890.000
명칭0.9370.9901.0000.9760.9891.0000.927
거리(km)0.5920.4210.8510.5210.0000.9271.000
2024-03-15T03:44:24.906949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명길명
시군명1.0000.367
길명0.3671.000
2024-03-15T03:44:25.140718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번거리(km)시군명길명
순번1.000-0.4800.5360.752
거리(km)-0.4801.0000.1660.500
시군명0.5360.1661.0000.367
길명0.7520.5000.3671.000

Missing values

2024-03-15T03:44:12.933035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:44:13.260001image/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

순번시군명길명도로명주소시점위치명칭거리(km)자료출처
01전주시아름다운 순례길전주시 완산구 태조로 6전주한옥마을한옥마을28.0관광총괄과
12완주군아름다운 순례길완주군 소양면 송광수만로 255-16송광사송광사26.5관광총괄과
23완주군아름다운 순례길완주군 비봉면 천호성지길 124완주 천호천호26.5관광총괄과
34익산시아름다운 순례길익산시 망성면 나바위길 77-4나바위나바위27.5관광총괄과
45익산시아름다운 순례길익산시 금마면 미륵사지로 362익산 미륵사지미륵사지29.3관광총괄과
56완주군아름다운 순례길완주군 이서면 초남신기길 23-24초남이초남이24.0관광총괄과
67김제시아름다운 순례길김제시 금산면 모악15길 1김제 금산사금산사19.7관광총괄과
78김제시아름다운 순례길김제시 금산면 수류로 643수류수류21.0관광총괄과
89완주군아름다운 순례길완주군 구이면 모악산길 91전주 모악산모악산19.7관광총괄과
910순창군모악산 마실길순창군 동계면 추동길 90-3추동마을입구(경계)전주시12.3관광총괄과
순번시군명길명도로명주소시점위치명칭거리(km)자료출처
3839장수군마음이 머무는길장수군 장수읍 덕산로 795용림제마루한 길12.5관광총괄과
3940임실군마음이 머무는길임실군 운암면 학암2길 30학암마을옥정호 마실길17.64관광총괄과
4041순창군마음이 머무는길순창군 적성면 강경길 159-4강경마을마실길14.0관광총괄과
4142순창군마음이 머무는길순창군 적성면 강경길 159-4강경마을마실길24.5관광총괄과
4243순창군마음이 머무는길순창군 적성면 강경길 76-165드무소골마실길33.8관광총괄과
4344고창군마음이 머무는길고창군 고창읍 고인돌공원길 74고인돌박물관고인돌길8.3관광총괄과
4445고창군마음이 머무는길고창군 아산면 운곡로 82장살비재복분자-풍천장어길7.7관광총괄과
4546고창군마음이 머무는길고창군 부안면 연기길 21산림경영모델숲질마재길11.3관광총괄과
4647고창군마음이 머무는길고창군 부안면 연기길 17풍천(강나루식당)보은길12.7관광총괄과
4748부안군마음이 머무는길부안군 진서면 내소사로 187일주문내소사 전나무숲길0.6관광총괄과