Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory52.4 B

Variable types

Categorical1
Text5

Dataset

Description안전한보행환경조성사업추진현황20147
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202076

Reproduction

Analysis started2024-03-14 00:10:15.002097
Analysis finished2024-03-14 00:10:15.406524
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도별
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2010
8 
2011
8 
2012
6 
2013
5 
2014
2 

Length

Max length4
Median length4
Mean length3.9
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row계
2nd row2010
3rd row2010
4th row2010
5th row2010

Common Values

ValueCountFrequency (%)
2010 8
26.7%
2011 8
26.7%
2012 6
20.0%
2013 5
16.7%
2014 2
 
6.7%
계 1
 
3.3%

Length

2024-03-14T09:10:15.470014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:10:15.579533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2010 8
26.7%
2011 8
26.7%
2012 6
20.0%
2013 5
16.7%
2014 2
 
6.7%
계 1
 
3.3%

사업명(2014.7.31일 기준)
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T09:10:15.733275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length16.466667
Min length1

Characters and Unicode

Total characters494
Distinct characters73
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

Unique22 ?
Unique (%)73.3%

Sample

1st row-
2nd row-
3rd row안전한 보행환경 조성사업(순창 농암)
4th row안전한 보행환경 조성사업(부안 모산)
5th row안전한 보행환경 조성사업(고창 선운)
ValueCountFrequency (%)
안전한 24
23.8%
보행환경 24
23.8%
6
 
5.9%
조성사업(익산 5
 
5.0%
조성사업(완주 4
 
4.0%
화산 2
 
2.0%
조성사업(정읍 2
 
2.0%
조성사업(남원 2
 
2.0%
조성사업(김제 2
 
2.0%
조성사업(순창 2
 
2.0%
Other values (28) 28
27.7%
2024-03-14T09:10:15.988864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
 
14.4%
안 26
 
5.3%
조 24
 
4.9%
경 24
 
4.9%
( 24
 
4.9%
업 24
 
4.9%
사 24
 
4.9%
성 24
 
4.9%
) 24
 
4.9%
환 24
 
4.9%
Other values (63) 205
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 365
73.9%
Space Separator 71
 
14.4%
Open Punctuation 24
 
4.9%
Close Punctuation 24
 
4.9%
Dash Punctuation 8
 
1.6%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 26
 
7.1%
조 24
 
6.6%
경 24
 
6.6%
업 24
 
6.6%
사 24
 
6.6%
성 24
 
6.6%
환 24
 
6.6%
행 24
 
6.6%
보 24
 
6.6%
한 24
 
6.6%
Other values (57) 123
33.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 365
73.9%
Common 129
 
26.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 26
 
7.1%
조 24
 
6.6%
경 24
 
6.6%
업 24
 
6.6%
사 24
 
6.6%
성 24
 
6.6%
환 24
 
6.6%
행 24
 
6.6%
보 24
 
6.6%
한 24
 
6.6%
Other values (57) 123
33.7%
Common
ValueCountFrequency (%)
71
55.0%
( 24
 
18.6%
) 24
 
18.6%
- 8
 
6.2%
1 1
 
0.8%
2 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 365
73.9%
ASCII 129
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
55.0%
( 24
 
18.6%
) 24
 
18.6%
- 8
 
6.2%
1 1
 
0.8%
2 1
 
0.8%
Hangul
ValueCountFrequency (%)
안 26
 
7.1%
조 24
 
6.6%
경 24
 
6.6%
업 24
 
6.6%
사 24
 
6.6%
성 24
 
6.6%
환 24
 
6.6%
행 24
 
6.6%
보 24
 
6.6%
한 24
 
6.6%
Other values (57) 123
33.7%

위 치
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T09:10:16.152048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.4666667
Min length3

Characters and Unicode

Total characters254
Distinct characters61
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

Unique25 ?
Unique (%)83.3%

Sample

1st row25개소
2nd row7개소
3rd row순창 복흥
4th row부안 부안
5th row고창 부안
ValueCountFrequency (%)
익산 7
 
12.5%
완주 4
 
7.1%
부안 3
 
5.4%
금마(지722 3
 
5.4%
김제 2
 
3.6%
7개소 2
 
3.6%
남원 2
 
3.6%
순창 2
 
3.6%
정읍 2
 
3.6%
임실 1
 
1.8%
Other values (28) 28
50.0%
2024-03-14T09:10:16.417051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
10.2%
지 19
 
7.5%
( 18
 
7.1%
7 18
 
7.1%
) 18
 
7.1%
산 15
 
5.9%
2 9
 
3.5%
4 8
 
3.1%
주 7
 
2.8%
1 7
 
2.8%
Other values (51) 109
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131
51.6%
Decimal Number 60
23.6%
Space Separator 26
 
10.2%
Open Punctuation 18
 
7.1%
Close Punctuation 18
 
7.1%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 19
 
14.5%
산 15
 
11.5%
주 7
 
5.3%
익 7
 
5.3%
소 6
 
4.6%
개 6
 
4.6%
안 4
 
3.1%
완 4
 
3.1%
창 3
 
2.3%
금 3
 
2.3%
Other values (37) 57
43.5%
Decimal Number
ValueCountFrequency (%)
7 18
30.0%
2 9
15.0%
4 8
13.3%
1 7
 
11.7%
6 5
 
8.3%
5 4
 
6.7%
3 3
 
5.0%
0 2
 
3.3%
9 2
 
3.3%
8 2
 
3.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131
51.6%
Common 123
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 19
 
14.5%
산 15
 
11.5%
주 7
 
5.3%
익 7
 
5.3%
소 6
 
4.6%
개 6
 
4.6%
안 4
 
3.1%
완 4
 
3.1%
창 3
 
2.3%
금 3
 
2.3%
Other values (37) 57
43.5%
Common
ValueCountFrequency (%)
26
21.1%
( 18
14.6%
7 18
14.6%
) 18
14.6%
2 9
 
7.3%
4 8
 
6.5%
1 7
 
5.7%
6 5
 
4.1%
5 4
 
3.3%
3 3
 
2.4%
Other values (4) 7
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
51.6%
ASCII 123
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
21.1%
( 18
14.6%
7 18
14.6%
) 18
14.6%
2 9
 
7.3%
4 8
 
6.5%
1 7
 
5.7%
6 5
 
4.1%
5 4
 
3.3%
3 3
 
2.4%
Other values (4) 7
 
5.7%
Hangul
ValueCountFrequency (%)
지 19
 
14.5%
산 15
 
11.5%
주 7
 
5.3%
익 7
 
5.3%
소 6
 
4.6%
개 6
 
4.6%
안 4
 
3.1%
완 4
 
3.1%
창 3
 
2.3%
금 3
 
2.3%
Other values (37) 57
43.5%

사업량(km)
Text

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T09:10:16.562718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.2666667
Min length5

Characters and Unicode

Total characters158
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)60.0%

Sample

1st rowL=13.4
2nd rowL=4.3
3rd rowL=0.73
4th rowL=0.78
5th rowL=0.51
ValueCountFrequency (%)
l=0.4 5
16.7%
l=0.5 4
 
13.3%
l=0.3 3
 
10.0%
l=4.3 1
 
3.3%
l=0.2 1
 
3.3%
l=1.3 1
 
3.3%
l=0.8 1
 
3.3%
l=1.2 1
 
3.3%
l=3.4 1
 
3.3%
l=0.1 1
 
3.3%
Other values (11) 11
36.7%
2024-03-14T09:10:16.825380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
L 30
19.0%
= 30
19.0%
. 30
19.0%
0 24
15.2%
4 11
 
7.0%
3 10
 
6.3%
1 9
 
5.7%
5 5
 
3.2%
8 3
 
1.9%
7 3
 
1.9%
Other values (2) 3
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
43.0%
Uppercase Letter 30
19.0%
Math Symbol 30
19.0%
Other Punctuation 30
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24
35.3%
4 11
16.2%
3 10
14.7%
1 9
 
13.2%
5 5
 
7.4%
8 3
 
4.4%
7 3
 
4.4%
2 2
 
2.9%
9 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
L 30
100.0%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Other Punctuation
ValueCountFrequency (%)
. 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
81.0%
Latin 30
 
19.0%

Most frequent character per script

Common
ValueCountFrequency (%)
= 30
23.4%
. 30
23.4%
0 24
18.8%
4 11
 
8.6%
3 10
 
7.8%
1 9
 
7.0%
5 5
 
3.9%
8 3
 
2.3%
7 3
 
2.3%
2 2
 
1.6%
Latin
ValueCountFrequency (%)
L 30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L 30
19.0%
= 30
19.0%
. 30
19.0%
0 24
15.2%
4 11
 
7.0%
3 10
 
6.3%
1 9
 
5.7%
5 5
 
3.2%
8 3
 
1.9%
7 3
 
1.9%
Other values (2) 3
 
1.9%

사업기간
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T09:10:16.959582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length12.166667
Min length1

Characters and Unicode

Total characters365
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)43.3%

Sample

1st row-
2nd row-
3rd row2010.05~2010.12
4th row2010.05~2010.11
5th row2010.05~2010.12
ValueCountFrequency (%)
6
20.0%
2010.05~2010.12 3
 
10.0%
2011.06~2012.02 3
 
10.0%
2012.05~2013.01 3
 
10.0%
2012.10~2013.01 2
 
6.7%
2013.01~2013.1 1
 
3.3%
2012.03~2012.07 1
 
3.3%
2013.10~2013.12 1
 
3.3%
2013.01~2013.12 1
 
3.3%
2013.01~2013.08 1
 
3.3%
Other values (8) 8
26.7%
2024-03-14T09:10:17.217895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
27.7%
1 78
21.4%
2 71
19.5%
. 48
13.2%
~ 24
 
6.6%
3 14
 
3.8%
5 7
 
1.9%
6 7
 
1.9%
- 6
 
1.6%
7 4
 
1.1%
Other values (3) 5
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 287
78.6%
Other Punctuation 48
 
13.2%
Math Symbol 24
 
6.6%
Dash Punctuation 6
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
35.2%
1 78
27.2%
2 71
24.7%
3 14
 
4.9%
5 7
 
2.4%
6 7
 
2.4%
7 4
 
1.4%
9 2
 
0.7%
4 2
 
0.7%
8 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 101
27.7%
1 78
21.4%
2 71
19.5%
. 48
13.2%
~ 24
 
6.6%
3 14
 
3.8%
5 7
 
1.9%
6 7
 
1.9%
- 6
 
1.6%
7 4
 
1.1%
Other values (3) 5
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
27.7%
1 78
21.4%
2 71
19.5%
. 48
13.2%
~ 24
 
6.6%
3 14
 
3.8%
5 7
 
1.9%
6 7
 
1.9%
- 6
 
1.6%
7 4
 
1.1%
Other values (3) 5
 
1.4%

사업비(백만원)
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T09:10:17.350756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1
Min length2

Characters and Unicode

Total characters93
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

Unique18 ?
Unique (%)60.0%

Sample

1st row8,790
2nd row2,800
3rd row190
4th row430
5th row340
ValueCountFrequency (%)
90 4
 
13.3%
340 2
 
6.7%
800 2
 
6.7%
290 2
 
6.7%
430 2
 
6.7%
600 1
 
3.3%
8,790 1
 
3.3%
230 1
 
3.3%
280 1
 
3.3%
355 1
 
3.3%
Other values (13) 13
43.3%
2024-03-14T09:10:17.600735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35
37.6%
9 9
 
9.7%
4 8
 
8.6%
3 8
 
8.6%
2 8
 
8.6%
8 6
 
6.5%
1 6
 
6.5%
, 4
 
4.3%
7 3
 
3.2%
6 3
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
95.7%
Other Punctuation 4
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
39.3%
9 9
 
10.1%
4 8
 
9.0%
3 8
 
9.0%
2 8
 
9.0%
8 6
 
6.7%
1 6
 
6.7%
7 3
 
3.4%
6 3
 
3.4%
5 3
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35
37.6%
9 9
 
9.7%
4 8
 
8.6%
3 8
 
8.6%
2 8
 
8.6%
8 6
 
6.5%
1 6
 
6.5%
, 4
 
4.3%
7 3
 
3.2%
6 3
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35
37.6%
9 9
 
9.7%
4 8
 
8.6%
3 8
 
8.6%
2 8
 
8.6%
8 6
 
6.5%
1 6
 
6.5%
, 4
 
4.3%
7 3
 
3.2%
6 3
 
3.2%

Correlations

2024-03-14T09:10:17.695002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도별사업명(2014.7.31일 기준)위 치사업량(km)사업기간사업비(백만원)
년도별1.0000.0000.0000.7710.7760.000
사업명(2014.7.31일 기준)0.0001.0000.9470.0000.9970.747
위 치0.0000.9471.0000.9040.8010.985
사업량(km)0.7710.0000.9041.0000.0000.891
사업기간0.7760.9970.8010.0001.0000.000
사업비(백만원)0.0000.7470.9850.8910.0001.000

Missing values

2024-03-14T09:10:15.253472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:10:15.356733image/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

년도별사업명(2014.7.31일 기준)위 치사업량(km)사업기간사업비(백만원)
0계-25개소L=13.4-8,790
12010-7개소L=4.3-2,800
22010안전한 보행환경 조성사업(순창 농암)순창 복흥L=0.732010.05~2010.12190
32010안전한 보행환경 조성사업(부안 모산)부안 부안L=0.782010.05~2010.11430
42010안전한 보행환경 조성사업(고창 선운)고창 부안L=0.512010.05~2010.12340
52010안전한 보행환경 조성사업(정읍 운학)정읍 영원L=0.312010.05~2010.12170
62010안전한 보행환경 조성사업(익산 동촌)익산 여산, 익산 낭산L=1.412010.06~2010.12920
72010안전한 보행환경 조성사업(진안 주천)진안 주천L=0.072010.06~2010.09140
82010안전한 보행환경 조성사업(김제 구월)김제 구월(지714)L=0.442010.06~2011.07610
92011-7개소L=3.8-3,000
년도별사업명(2014.7.31일 기준)위 치사업량(km)사업기간사업비(백만원)
202012안전한 보행환경 조성사업(김제 청하)김제 청하(지711)L=0.82012.05~2013.01430
212012안전한 보행환경 조성사업(순창 복흥)순창 복흥(지897)L=0.52012.10~2013.01280
222012안전한 보행환경 조성사업(완주 화산)완주 화산(지643)L=0.42012.10~2013.01290
232013-4개소L=1.3-800
242013안전한 보행환경 조성사업(익산 석천)익산 낭산(지718)L=0.42013.01~2013.1340
252013안전한 보행환경 조성사업(정읍 두지)정읍 두지(지736)L=0.22013.01~2013.0880
262013안전한 보행환경 조성사업(완주 어우)완주 고산(지741)L=0.32013.01~2013.12290
272013안전한 보행환경 조성사업(익산 금마-1공구)익산 금마(지722)L=0.42013.10~2013.1290
282014-1개소L=0.3-90
292014안전한 보행환경 조성사업(익산 금마-2공구)익산 금마(지722)L=0.32014.01~2014.0790