Overview

Dataset statistics

Number of variables4
Number of observations55
Missing cells79
Missing cells (%)35.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory34.4 B

Variable types

Text2
Unsupported1
Categorical1

Dataset

Description예향천리마실길주요노선201511
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202557

Alerts

예향천리 마실길 조성현황(2015.11) has 38 (69.1%) missing valuesMissing
Unnamed: 1 has 2 (3.6%) missing valuesMissing
Unnamed: 2 has 39 (70.9%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:16:02.089570
Analysis finished2024-03-14 02:16:02.446109
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예향천리 마실길 조성현황(2015.11)
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing38
Missing (%)69.1%
Memory size572.0 B
2024-03-14T11:16:02.541816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length4.5294118
Min length3

Characters and Unicode

Total characters77
Distinct characters39
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row(단위 : km, 백만원)
2nd row시․ 군
3rd row 14개 시군
4th row전주시
5th row군산시
ValueCountFrequency (%)
단위 1
 
4.5%
1
 
4.5%
완주군 1
 
4.5%
고창군 1
 
4.5%
순창군 1
 
4.5%
임실군 1
 
4.5%
장수군 1
 
4.5%
무주군 1
 
4.5%
진안군 1
 
4.5%
김제시 1
 
4.5%
Other values (12) 12
54.5%
2024-03-14T11:16:02.814296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
20.8%
군 11
 
14.3%
시 8
 
10.4%
주 3
 
3.9%
산 2
 
2.6%
안 2
 
2.6%
창 2
 
2.6%
원 2
 
2.6%
․ 1
 
1.3%
김 1
 
1.3%
Other values (29) 29
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
67.5%
Space Separator 16
 
20.8%
Other Punctuation 3
 
3.9%
Decimal Number 2
 
2.6%
Lowercase Letter 2
 
2.6%
Open Punctuation 1
 
1.3%
Close Punctuation 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 11
21.2%
시 8
15.4%
주 3
 
5.8%
산 2
 
3.8%
안 2
 
3.8%
창 2
 
3.8%
원 2
 
3.8%
김 1
 
1.9%
제 1
 
1.9%
진 1
 
1.9%
Other values (19) 19
36.5%
Other Punctuation
ValueCountFrequency (%)
․ 1
33.3%
, 1
33.3%
: 1
33.3%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
1 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
67.5%
Common 23
29.9%
Latin 2
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 11
21.2%
시 8
15.4%
주 3
 
5.8%
산 2
 
3.8%
안 2
 
3.8%
창 2
 
3.8%
원 2
 
3.8%
김 1
 
1.9%
제 1
 
1.9%
진 1
 
1.9%
Other values (19) 19
36.5%
Common
ValueCountFrequency (%)
16
69.6%
․ 1
 
4.3%
( 1
 
4.3%
4 1
 
4.3%
1 1
 
4.3%
) 1
 
4.3%
, 1
 
4.3%
: 1
 
4.3%
Latin
ValueCountFrequency (%)
m 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
67.5%
ASCII 24
31.2%
Punctuation 1
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
66.7%
( 1
 
4.2%
4 1
 
4.2%
1 1
 
4.2%
) 1
 
4.2%
, 1
 
4.2%
m 1
 
4.2%
k 1
 
4.2%
: 1
 
4.2%
Hangul
ValueCountFrequency (%)
군 11
21.2%
시 8
15.4%
주 3
 
5.8%
산 2
 
3.8%
안 2
 
3.8%
창 2
 
3.8%
원 2
 
3.8%
김 1
 
1.9%
제 1
 
1.9%
진 1
 
1.9%
Other values (19) 19
36.5%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%

Unnamed: 1
Text

MISSING 

Distinct51
Distinct (%)96.2%
Missing2
Missing (%)3.6%
Memory size572.0 B
2024-03-14T11:16:02.978800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length11.981132
Min length4

Characters and Unicode

Total characters635
Distinct characters160
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)94.3%

Sample

1st row주 요 노 선
2nd row∘모악산마실길
3rd row(원당마을 →체련공원 → 독배마을)
4th row∘천년전주마실길
5th row(아태무형→다가공원→전통문화센터)
ValueCountFrequency (%)
→ 7
 
8.8%
∘모악산마실길 3
 
3.8%
∘명품길 2
 
2.5%
원덕현 2
 
2.5%
∘예향천리순창마실길 2
 
2.5%
굴암→ 1
 
1.2%
마암마을 1
 
1.2%
서면마을→안성면→ 1
 
1.2%
∘예향천리백두대산마실길 1
 
1.2%
잠두마을 1
 
1.2%
Other values (59) 59
73.8%
2024-03-14T11:16:03.269025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
→ 49
 
7.7%
35
 
5.5%
마 35
 
5.5%
) 27
 
4.3%
길 27
 
4.3%
( 27
 
4.3%
∘ 26
 
4.1%
을 18
 
2.8%
산 16
 
2.5%
실 14
 
2.2%
Other values (150) 361
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
73.5%
Math Symbol 77
 
12.1%
Space Separator 35
 
5.5%
Close Punctuation 27
 
4.3%
Open Punctuation 27
 
4.3%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 35
 
7.5%
길 27
 
5.8%
을 18
 
3.9%
산 16
 
3.4%
실 14
 
3.0%
수 11
 
2.4%
원 11
 
2.4%
리 11
 
2.4%
사 10
 
2.1%
천 9
 
1.9%
Other values (142) 305
65.3%
Math Symbol
ValueCountFrequency (%)
→ 49
63.6%
∘ 26
33.8%
~ 2
 
2.6%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 467
73.5%
Common 168
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 35
 
7.5%
길 27
 
5.8%
을 18
 
3.9%
산 16
 
3.4%
실 14
 
3.0%
수 11
 
2.4%
원 11
 
2.4%
리 11
 
2.4%
사 10
 
2.1%
천 9
 
1.9%
Other values (142) 305
65.3%
Common
ValueCountFrequency (%)
→ 49
29.2%
35
20.8%
) 27
16.1%
( 27
16.1%
∘ 26
15.5%
~ 2
 
1.2%
4 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 467
73.5%
ASCII 93
 
14.6%
Arrows 49
 
7.7%
Math Operators 26
 
4.1%

Most frequent character per block

Arrows
ValueCountFrequency (%)
→ 49
100.0%
ASCII
ValueCountFrequency (%)
35
37.6%
) 27
29.0%
( 27
29.0%
~ 2
 
2.2%
4 1
 
1.1%
1 1
 
1.1%
Hangul
ValueCountFrequency (%)
마 35
 
7.5%
길 27
 
5.8%
을 18
 
3.9%
산 16
 
3.4%
실 14
 
3.0%
수 11
 
2.4%
원 11
 
2.4%
리 11
 
2.4%
사 10
 
2.1%
천 9
 
1.9%
Other values (142) 305
65.3%
Math Operators
ValueCountFrequency (%)
∘ 26
100.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)70.9%
Memory size572.0 B

Unnamed: 3
Categorical

Distinct4
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
39 
‘10~’11
14 
조성연도
 
1
‘10
 
1

Length

Max length7
Median length4
Mean length4.7454545
Min length3

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st row<NA>
2nd row조성연도
3rd row‘10~’11
4th row‘10~’11
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 39
70.9%
‘10~’11 14
 
25.5%
조성연도 1
 
1.8%
‘10 1
 
1.8%

Length

2024-03-14T11:16:03.442411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:16:03.534232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
70.9%
‘10~’11 14
 
25.5%
조성연도 1
 
1.8%
‘10 1
 
1.8%

Correlations

2024-03-14T11:16:03.588350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예향천리 마실길 조성현황(2015.11)Unnamed: 1Unnamed: 3
예향천리 마실길 조성현황(2015.11)1.0001.0001.000
Unnamed: 11.0001.0001.000
Unnamed: 31.0001.0001.000

Missing values

2024-03-14T11:16:02.245950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:16:02.319053image/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.
2024-03-14T11:16:02.398700image/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

예향천리 마실길 조성현황(2015.11)Unnamed: 1Unnamed: 2Unnamed: 3
0(단위 : km, 백만원)<NA>NaN<NA>
1시․ 군주 요 노 선연장조성연도
214개 시군<NA>800‘10~’11
3전주시∘모악산마실길39‘10~’11
4<NA>(원당마을 →체련공원 → 독배마을)NaN<NA>
5<NA>∘천년전주마실길NaN<NA>
6<NA>(아태무형→다가공원→전통문화센터)NaN<NA>
7군산시∘군산마실길38‘10~’11
8<NA>(군산저수지→백석제 → 은파호수공원)NaN<NA>
9<NA>∘선유도길NaN<NA>
예향천리 마실길 조성현황(2015.11)Unnamed: 1Unnamed: 2Unnamed: 3
45순창군∘예향천리순창마실길 1코스26‘10~’11
46<NA>(입석마을→도왕마을→강경마을)NaN<NA>
47<NA>∘예향천리순창마실길 4코스NaN<NA>
48<NA>(내월초→도왕마을→강경마을)NaN<NA>
49고창군∘역사길94‘10~’11
50<NA>(무장읍성→천수정→사신원)NaN<NA>
51<NA>∘수변길NaN<NA>
52<NA>(석남리→용대저수지→두암저수지)NaN<NA>
53부안군∘부안마실길115‘10~’11
54<NA>(새만금전시관 →줄포 부안자연생태공원)NaN<NA>