Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells43
Missing cells (%)0.1%
Duplicate rows37
Duplicate rows (%)0.4%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

Text3

Dataset

Description전라북도 임실군 공간정보시스템 내부 테이블 데이터로 관리번호(MNUM), 별칭(ALIAS), 비고(REMARK)가 포함된 메타데이터입니다.
Author전라북도 임실군
URLhttps://www.data.go.kr/data/15123553/fileData.do

Alerts

Dataset has 37 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 14:15:47.917884
Analysis finished2023-12-12 14:15:48.663197
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호(MNUM)
Text

Distinct9920
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:15:48.816912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length33
Mean length32.9972
Min length5

Characters and Unicode

Total characters329972
Distinct characters29
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

Unique9875 ?
Unique (%)98.8%

Sample

1st row47600004575020190016UJC2000878003
2nd row64500004575020120257UQC0010031000
3rd row47600004575020190016UJC2001018005
4th row47600004575020190016UJC2000934001
5th row64500004575020120257UQC0011893000
ValueCountFrequency (%)
64500004575020150060ujb1000001001 3
 
< 0.1%
16110004575020120027ujb1000001001 3
 
< 0.1%
16110004575020120027ujb1000001027 3
 
< 0.1%
16110004575020120027ujb1000001014 3
 
< 0.1%
16110004575020120027ujb1000001035 3
 
< 0.1%
64500004575020150064ujb1000001001 3
 
< 0.1%
16130004575020120027ujb1000001026 3
 
< 0.1%
64500004575020130040ujb4000001001 3
 
< 0.1%
64500004575020150111ujb1000001001 3
 
< 0.1%
16110004575020120027ujb1000001008 3
 
< 0.1%
Other values (9910) 9970
99.7%
2023-12-12T23:15:49.167993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 130134
39.4%
5 37706
 
11.4%
2 32848
 
10.0%
1 23461
 
7.1%
4 22926
 
6.9%
7 21504
 
6.5%
6 14354
 
4.4%
U 9999
 
3.0%
3 7668
 
2.3%
Q 6989
 
2.1%
Other values (19) 22383
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 299970
90.9%
Uppercase Letter 29997
 
9.1%
Other Letter 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 9999
33.3%
Q 6989
23.3%
B 5040
16.8%
C 3650
 
12.2%
J 1996
 
6.7%
M 674
 
2.2%
Z 598
 
2.0%
A 407
 
1.4%
I 283
 
0.9%
S 221
 
0.7%
Other values (4) 140
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 130134
43.4%
5 37706
 
12.6%
2 32848
 
11.0%
1 23461
 
7.8%
4 22926
 
7.6%
7 21504
 
7.2%
6 14354
 
4.8%
3 7668
 
2.6%
9 5394
 
1.8%
8 3975
 
1.3%
Other Letter
ValueCountFrequency (%)
소 1
20.0%
하 1
20.0%
천 1
20.0%
구 1
20.0%
역 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 299970
90.9%
Latin 29997
 
9.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 9999
33.3%
Q 6989
23.3%
B 5040
16.8%
C 3650
 
12.2%
J 1996
 
6.7%
M 674
 
2.2%
Z 598
 
2.0%
A 407
 
1.4%
I 283
 
0.9%
S 221
 
0.7%
Other values (4) 140
 
0.5%
Common
ValueCountFrequency (%)
0 130134
43.4%
5 37706
 
12.6%
2 32848
 
11.0%
1 23461
 
7.8%
4 22926
 
7.6%
7 21504
 
7.2%
6 14354
 
4.8%
3 7668
 
2.6%
9 5394
 
1.8%
8 3975
 
1.3%
Hangul
ValueCountFrequency (%)
소 1
20.0%
하 1
20.0%
천 1
20.0%
구 1
20.0%
역 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329967
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 130134
39.4%
5 37706
 
11.4%
2 32848
 
10.0%
1 23461
 
7.1%
4 22926
 
6.9%
7 21504
 
6.5%
6 14354
 
4.4%
U 9999
 
3.0%
3 7668
 
2.3%
Q 6989
 
2.1%
Other values (14) 22378
 
6.8%
Hangul
ValueCountFrequency (%)
소 1
20.0%
하 1
20.0%
천 1
20.0%
구 1
20.0%
역 1
20.0%

별칭(ALIAS)
Text

Distinct275
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:15:49.559493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length1
Mean length3.0519
Min length1

Characters and Unicode

Total characters30519
Distinct characters134
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)1.6%

Sample

1st row소하천예정지
2nd row
3rd row소하천예정지
4th row소하천예정지
5th row
ValueCountFrequency (%)
소하천예정지 1615
52.0%
소하천구역 258
 
8.3%
상대제한_100m 182
 
5.9%
섬진강 82
 
2.6%
하천구역 82
 
2.6%
상대제한_350m 56
 
1.8%
상대제한_1000m 45
 
1.4%
상대제한_500m 39
 
1.3%
오수 36
 
1.2%
임실 25
 
0.8%
Other values (256) 685
22.1%
2023-12-12T23:15:50.118558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7319
24.0%
천 1988
 
6.5%
하 1964
 
6.4%
소 1935
 
6.3%
지 1929
 
6.3%
정 1632
 
5.3%
예 1623
 
5.3%
0 1620
 
5.3%
대 835
 
2.7%
_ 824
 
2.7%
Other values (124) 8850
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17959
58.8%
Space Separator 7319
24.0%
Decimal Number 2852
 
9.3%
Connector Punctuation 824
 
2.7%
Lowercase Letter 739
 
2.4%
Open Punctuation 256
 
0.8%
Close Punctuation 256
 
0.8%
Other Punctuation 226
 
0.7%
Dash Punctuation 85
 
0.3%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 1988
11.1%
하 1964
10.9%
소 1935
10.8%
지 1929
10.7%
정 1632
9.1%
예 1623
9.0%
대 835
 
4.6%
제 772
 
4.3%
상 760
 
4.2%
한 748
 
4.2%
Other values (105) 3773
21.0%
Decimal Number
ValueCountFrequency (%)
0 1620
56.8%
1 444
 
15.6%
2 248
 
8.7%
5 232
 
8.1%
3 172
 
6.0%
7 58
 
2.0%
4 47
 
1.6%
9 19
 
0.7%
6 8
 
0.3%
8 4
 
0.1%
Space Separator
ValueCountFrequency (%)
7319
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 824
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 739
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17959
58.8%
Common 11819
38.7%
Latin 741
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 1988
11.1%
하 1964
10.9%
소 1935
10.8%
지 1929
10.7%
정 1632
9.1%
예 1623
9.0%
대 835
 
4.6%
제 772
 
4.3%
상 760
 
4.2%
한 748
 
4.2%
Other values (105) 3773
21.0%
Common
ValueCountFrequency (%)
7319
61.9%
0 1620
 
13.7%
_ 824
 
7.0%
1 444
 
3.8%
( 256
 
2.2%
) 256
 
2.2%
2 248
 
2.1%
5 232
 
2.0%
/ 226
 
1.9%
3 172
 
1.5%
Other values (7) 222
 
1.9%
Latin
ValueCountFrequency (%)
m 739
99.7%
M 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17959
58.8%
ASCII 12560
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7319
58.3%
0 1620
 
12.9%
_ 824
 
6.6%
m 739
 
5.9%
1 444
 
3.5%
( 256
 
2.0%
) 256
 
2.0%
2 248
 
2.0%
5 232
 
1.8%
/ 226
 
1.8%
Other values (9) 396
 
3.2%
Hangul
ValueCountFrequency (%)
천 1988
11.1%
하 1964
10.9%
소 1935
10.8%
지 1929
10.7%
정 1632
9.1%
예 1623
9.0%
대 835
 
4.6%
제 772
 
4.3%
상 760
 
4.2%
한 748
 
4.2%
Other values (105) 3773
21.0%

비고(REMARK)
Text

Distinct541
Distinct (%)5.4%
Missing43
Missing (%)0.4%
Memory size156.2 KiB
2023-12-12T23:15:50.449115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length40
Mean length5.5234508
Min length1

Characters and Unicode

Total characters54997
Distinct characters247
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)1.9%

Sample

1st row독주골천
2nd row농림지역
3rd row원천
4th row산바천
5th row농림지역
ValueCountFrequency (%)
보전관리지역 3243
33.9%
농림지역 1728
18.0%
생산관리지역 1136
 
11.9%
계획관리지역 537
 
5.6%
상대제한_100m 182
 
1.9%
상대제한_350m 56
 
0.6%
지방도(745 48
 
0.5%
상대제한_1000m 45
 
0.5%
상대제한_500m 39
 
0.4%
율치천 35
 
0.4%
Other values (530) 2526
26.4%
2023-12-12T23:15:50.943520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 7030
 
12.8%
역 6812
 
12.4%
관 4950
 
9.0%
리 4940
 
9.0%
전 3322
 
6.0%
보 3281
 
6.0%
천 1917
 
3.5%
농 1742
 
3.2%
림 1729
 
3.1%
0 1650
 
3.0%
Other values (237) 17624
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48411
88.0%
Decimal Number 3258
 
5.9%
Connector Punctuation 904
 
1.6%
Lowercase Letter 739
 
1.3%
Space Separator 614
 
1.1%
Open Punctuation 354
 
0.6%
Close Punctuation 354
 
0.6%
Other Punctuation 227
 
0.4%
Dash Punctuation 121
 
0.2%
Math Symbol 7
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 7030
14.5%
역 6812
14.1%
관 4950
10.2%
리 4940
10.2%
전 3322
 
6.9%
보 3281
 
6.8%
천 1917
 
4.0%
농 1742
 
3.6%
림 1729
 
3.6%
산 1223
 
2.5%
Other values (213) 11465
23.7%
Decimal Number
ValueCountFrequency (%)
0 1650
50.6%
1 558
 
17.1%
2 296
 
9.1%
5 280
 
8.6%
3 181
 
5.6%
7 131
 
4.0%
4 115
 
3.5%
9 38
 
1.2%
8 5
 
0.2%
6 4
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 353
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 353
99.7%
] 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
= 6
85.7%
~ 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 3
50.0%
B 3
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 904
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 739
100.0%
Space Separator
ValueCountFrequency (%)
614
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48411
88.0%
Common 5841
 
10.6%
Latin 745
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 7030
14.5%
역 6812
14.1%
관 4950
10.2%
리 4940
10.2%
전 3322
 
6.9%
보 3281
 
6.8%
천 1917
 
4.0%
농 1742
 
3.6%
림 1729
 
3.6%
산 1223
 
2.5%
Other values (213) 11465
23.7%
Common
ValueCountFrequency (%)
0 1650
28.2%
_ 904
15.5%
614
 
10.5%
1 558
 
9.6%
( 353
 
6.0%
) 353
 
6.0%
2 296
 
5.1%
5 280
 
4.8%
/ 227
 
3.9%
3 181
 
3.1%
Other values (11) 425
 
7.3%
Latin
ValueCountFrequency (%)
m 739
99.2%
L 3
 
0.4%
B 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48411
88.0%
ASCII 6586
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 7030
14.5%
역 6812
14.1%
관 4950
10.2%
리 4940
10.2%
전 3322
 
6.9%
보 3281
 
6.8%
천 1917
 
4.0%
농 1742
 
3.6%
림 1729
 
3.6%
산 1223
 
2.5%
Other values (213) 11465
23.7%
ASCII
ValueCountFrequency (%)
0 1650
25.1%
_ 904
13.7%
m 739
11.2%
614
 
9.3%
1 558
 
8.5%
( 353
 
5.4%
) 353
 
5.4%
2 296
 
4.5%
5 280
 
4.3%
/ 227
 
3.4%
Other values (14) 612
 
9.3%

Missing values

2023-12-12T23:15:48.557802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:15:48.627783image/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

관리번호(MNUM)별칭(ALIAS)비고(REMARK)
115147600004575020190016UJC2000878003소하천예정지독주골천
790364500004575020120257UQC0010031000농림지역
194347600004575020190016UJC2001018005소하천예정지원천
142147600004575020190016UJC2000934001소하천예정지산바천
967764500004575020120257UQC0011893000농림지역
701564500004575020120257UQB3002540000보전관리지역
500564500004575020120257UQB3000499000보전관리지역
118947600004575020190016UJC2000887006소하천예정지두만천
543664500004575020120257UQB3000933000보전관리지역
173547600004575020190016UJC2000981003소하천예정지신기천
관리번호(MNUM)별칭(ALIAS)비고(REMARK)
111847600004575020190016UJC2000874017소하천예정지도봉천
664964500004575020120257UQB3002171000보전관리지역
714364500004575020120257UQB3002672000보전관리지역
317264500004575020120257UQB1000425000계획관리지역
967964500004575020120257UQC0011895000농림지역
594064500004575020120257UQB3001455000보전관리지역
700964500004575020120257UQB3002534000보전관리지역
710264500004575020120257UQB3002630000보전관리지역
125547600004575020190016UJC2000903003소하천예정지매산천
950164500004575020120257UQC0011689000농림지역

Duplicate rows

Most frequently occurring

관리번호(MNUM)별칭(ALIAS)비고(REMARK)# duplicates
015000004575020060001UQM11000010012
116110004575020120026UJB4000001001섬진강홍수관리구역2
216110004575020120026UJB4000001002섬진강홍수관리구역2
316110004575020120026UJB4000001003섬진강홍수관리구역2
416110004575020120026UJB4000001004섬진강홍수관리구역2
516110004575020120027UJB1000001001섬진강 하천구역2
616110004575020120027UJB1000001002섬진강 하천구역2
716110004575020120027UJB1000001003섬진강하천구역2
816110004575020120027UJB1000001005섬진강하천구역2
916110004575020120027UJB1000001006섬진강 하천구역2