Overview

Dataset statistics

Number of variables8
Number of observations1430
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory90.9 KiB
Average record size in memory65.1 B

Variable types

Numeric1
Categorical1
Text6

Dataset

Description동해에 있는 선박에게 암초나 수심이 얕은 곳 등의 장애물의 존재나 항로를 표시하기 위하여 해저에 침추를 설치하여 해면상에 뜨게한 구조물의 정보를 담고 있다
Author해양수산부
URLhttps://www.data.go.kr/data/15113423/fileData.do

Alerts

공간정보일련번호(gid) is highly overall correlated with 자료출처명(mtr_ogn_nm)High correlation
자료출처명(mtr_ogn_nm) is highly overall correlated with 공간정보일련번호(gid)High correlation
공간정보일련번호(gid) has unique valuesUnique

Reproduction

Analysis started2024-05-18 08:47:07.879261
Analysis finished2024-05-18 08:47:14.376459
Duration6.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일련번호(gid)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1430
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean715.5
Minimum1
Maximum1430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.7 KiB
2024-05-18T17:47:14.642543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile72.45
Q1358.25
median715.5
Q31072.75
95-th percentile1358.55
Maximum1430
Range1429
Interquartile range (IQR)714.5

Descriptive statistics

Standard deviation412.94975
Coefficient of variation (CV)0.5771485
Kurtosis-1.2
Mean715.5
Median Absolute Deviation (MAD)357.5
Skewness0
Sum1023165
Variance170527.5
MonotonicityStrictly increasing
2024-05-18T17:47:15.225452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
941 1
 
0.1%
961 1
 
0.1%
960 1
 
0.1%
959 1
 
0.1%
958 1
 
0.1%
957 1
 
0.1%
956 1
 
0.1%
955 1
 
0.1%
954 1
 
0.1%
Other values (1420) 1420
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1430 1
0.1%
1429 1
0.1%
1428 1
0.1%
1427 1
0.1%
1426 1
0.1%
1425 1
0.1%
1424 1
0.1%
1423 1
0.1%
1422 1
0.1%
1421 1
0.1%

자료출처명(mtr_ogn_nm)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2015항행통보연보
250 
2013항행통보연보
204 
2017항행통보연보
193 
2016항행통보연보
177 
2014항행통보연보
165 
Other values (3)
441 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2012항행통보연보
2nd row2012항행통보연보
3rd row2012항행통보연보
4th row2012항행통보연보
5th row2012항행통보연보

Common Values

ValueCountFrequency (%)
2015항행통보연보 250
17.5%
2013항행통보연보 204
14.3%
2017항행통보연보 193
13.5%
2016항행통보연보 177
12.4%
2014항행통보연보 165
11.5%
2012항행통보연보 160
11.2%
2018항행통보연보 151
10.6%
2019항행통보연보 130
9.1%

Length

2024-05-18T17:47:15.800417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T17:47:16.313607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015항행통보연보 250
17.5%
2013항행통보연보 204
14.3%
2017항행통보연보 193
13.5%
2016항행통보연보 177
12.4%
2014항행통보연보 165
11.5%
2012항행통보연보 160
11.2%
2018항행통보연보 151
10.6%
2019항행통보연보 130
9.1%

자료출처상세(mtr_ogn_dtl)
Text

Distinct530
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:17.113292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length12.501399
Min length9

Characters and Unicode

Total characters17877
Distinct characters16
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)12.3%

Sample

1st row2012년2호33항
2nd row2012년2호33항
3rd row2012년2호33항
4th row2012년2호33항
5th row2012년3호50항
ValueCountFrequency (%)
2019년7호104항 21
 
1.5%
2013년50호894항(t 20
 
1.4%
2016년18호265항 16
 
1.1%
2013년25호467항(t 13
 
0.9%
2012년21호294항(t 12
 
0.8%
2014년30호540항 11
 
0.8%
2019년17호333항 11
 
0.8%
2014년38호750항(t 10
 
0.7%
2019년15호276항 10
 
0.7%
2015년22호277항 10
 
0.7%
Other values (520) 1296
90.6%
2024-05-18T17:47:18.466884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2550
14.3%
1 2266
12.7%
0 1878
10.5%
년 1430
8.0%
호 1430
8.0%
항 1421
7.9%
3 1144
 
6.4%
4 1091
 
6.1%
5 849
 
4.7%
8 787
 
4.4%
Other values (6) 3031
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12573
70.3%
Other Letter 4281
 
23.9%
Open Punctuation 341
 
1.9%
Uppercase Letter 341
 
1.9%
Close Punctuation 341
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2550
20.3%
1 2266
18.0%
0 1878
14.9%
3 1144
9.1%
4 1091
8.7%
5 849
 
6.8%
8 787
 
6.3%
7 744
 
5.9%
6 730
 
5.8%
9 534
 
4.2%
Other Letter
ValueCountFrequency (%)
년 1430
33.4%
호 1430
33.4%
항 1421
33.2%
Open Punctuation
ValueCountFrequency (%)
( 341
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 341
100.0%
Close Punctuation
ValueCountFrequency (%)
) 341
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13255
74.1%
Hangul 4281
 
23.9%
Latin 341
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2550
19.2%
1 2266
17.1%
0 1878
14.2%
3 1144
8.6%
4 1091
8.2%
5 849
 
6.4%
8 787
 
5.9%
7 744
 
5.6%
6 730
 
5.5%
9 534
 
4.0%
Other values (2) 682
 
5.1%
Hangul
ValueCountFrequency (%)
년 1430
33.4%
호 1430
33.4%
항 1421
33.2%
Latin
ValueCountFrequency (%)
T 341
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13596
76.1%
Hangul 4281
 
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2550
18.8%
1 2266
16.7%
0 1878
13.8%
3 1144
8.4%
4 1091
8.0%
5 849
 
6.2%
8 787
 
5.8%
7 744
 
5.5%
6 730
 
5.4%
9 534
 
3.9%
Other values (3) 1023
7.5%
Hangul
ValueCountFrequency (%)
년 1430
33.4%
호 1430
33.4%
항 1421
33.2%

등부표위치명(lghtby_lc_nm)
Text

Distinct134
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:19.285912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.844755
Min length8

Characters and Unicode

Total characters15508
Distinct characters64
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)1.8%

Sample

1st row동해안 ～ 울산,울산항
2nd row동해안 ～ 울산,울산항
3rd row동해안 ～ 울산,울산항
4th row동해안 ～ 울산,울산항
5th row동해안 ～ 포항,구룡포
ValueCountFrequency (%)
부근 697
20.7%
동해안 587
17.4%
∼ 397
11.8%
～ 168
 
5.0%
울산항 151
 
4.5%
포항항 148
 
4.4%
동해안∼울산항부근 124
 
3.7%
동해안∼포항항부근 122
 
3.6%
동해안∼죽변항부근 57
 
1.7%
동해안∼동해,묵호항부근 41
 
1.2%
Other values (99) 882
26.1%
2024-05-18T17:47:20.672896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1944
12.5%
항 1697
10.9%
동 1539
9.9%
해 1534
9.9%
안 1422
9.2%
부 1416
9.1%
근 1385
8.9%
∼ 1099
7.1%
울 443
 
2.9%
포 436
 
2.8%
Other values (54) 2593
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11942
77.0%
Space Separator 1944
 
12.5%
Math Symbol 1430
 
9.2%
Other Punctuation 192
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
항 1697
14.2%
동 1539
12.9%
해 1534
12.8%
안 1422
11.9%
부 1416
11.9%
근 1385
11.6%
울 443
 
3.7%
포 436
 
3.7%
산 409
 
3.4%
릉 157
 
1.3%
Other values (48) 1504
12.6%
Math Symbol
ValueCountFrequency (%)
∼ 1099
76.9%
～ 170
 
11.9%
~ 161
 
11.3%
Other Punctuation
ValueCountFrequency (%)
, 184
95.8%
· 8
 
4.2%
Space Separator
ValueCountFrequency (%)
1944
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11942
77.0%
Common 3566
 
23.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
항 1697
14.2%
동 1539
12.9%
해 1534
12.8%
안 1422
11.9%
부 1416
11.9%
근 1385
11.6%
울 443
 
3.7%
포 436
 
3.7%
산 409
 
3.4%
릉 157
 
1.3%
Other values (48) 1504
12.6%
Common
ValueCountFrequency (%)
1944
54.5%
∼ 1099
30.8%
, 184
 
5.2%
～ 170
 
4.8%
~ 161
 
4.5%
· 8
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11942
77.0%
ASCII 2289
 
14.8%
Math Operators 1099
 
7.1%
None 178
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1944
84.9%
, 184
 
8.0%
~ 161
 
7.0%
Hangul
ValueCountFrequency (%)
항 1697
14.2%
동 1539
12.9%
해 1534
12.8%
안 1422
11.9%
부 1416
11.9%
근 1385
11.6%
울 443
 
3.7%
포 436
 
3.7%
산 409
 
3.4%
릉 157
 
1.3%
Other values (48) 1504
12.6%
Math Operators
ValueCountFrequency (%)
∼ 1099
100.0%
None
ValueCountFrequency (%)
～ 170
95.5%
· 8
 
4.5%

도분초위도(dms_la)
Text

Distinct766
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:21.599211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters15730
Distinct characters13
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

Unique340 ?
Unique (%)23.8%

Sample

1st row35-27-48.7N
2nd row35-27-54.4N
3rd row35-28-09.8N
4th row35-28-01.7N
5th row36-01-49.2N
ValueCountFrequency (%)
36-02-01.8n 8
 
0.6%
37-27-18.0n 7
 
0.5%
36-05-12.4n 6
 
0.4%
35-28-32.5n 6
 
0.4%
35-24-42.1n 6
 
0.4%
37-26-26.0n 6
 
0.4%
37-28-26.0n 6
 
0.4%
36-02-07.0n 6
 
0.4%
36-01-34.0n 6
 
0.4%
36-26-04.8n 5
 
0.3%
Other values (756) 1368
95.7%
2024-05-18T17:47:22.822843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2860
18.2%
3 2170
13.8%
. 1430
9.1%
N 1430
9.1%
0 1258
8.0%
5 1158
7.4%
2 1147
7.3%
1 903
 
5.7%
7 857
 
5.4%
6 816
 
5.2%
Other values (3) 1701
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10010
63.6%
Dash Punctuation 2860
 
18.2%
Other Punctuation 1430
 
9.1%
Uppercase Letter 1430
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2170
21.7%
0 1258
12.6%
5 1158
11.6%
2 1147
11.5%
1 903
9.0%
7 857
 
8.6%
6 816
 
8.2%
4 815
 
8.1%
8 500
 
5.0%
9 386
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 2860
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1430
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14300
90.9%
Latin 1430
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2860
20.0%
3 2170
15.2%
. 1430
10.0%
0 1258
8.8%
5 1158
8.1%
2 1147
8.0%
1 903
 
6.3%
7 857
 
6.0%
6 816
 
5.7%
4 815
 
5.7%
Other values (2) 886
 
6.2%
Latin
ValueCountFrequency (%)
N 1430
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2860
18.2%
3 2170
13.8%
. 1430
9.1%
N 1430
9.1%
0 1258
8.0%
5 1158
7.4%
2 1147
7.3%
1 903
 
5.7%
7 857
 
5.4%
6 816
 
5.2%
Other values (3) 1701
10.8%

도분초경도(dms_lo)
Text

Distinct761
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:23.717275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters17160
Distinct characters13
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

Unique343 ?
Unique (%)24.0%

Sample

1st row129-23-22.4E
2nd row129-23-11.4E
3rd row129-23-24.5E
4th row129-23-32.5E
5th row129-35-15.6E
ValueCountFrequency (%)
129-22-19.9e 10
 
0.7%
129-25-37.6e 8
 
0.6%
129-25-03.0e 7
 
0.5%
130-51-57.7e 7
 
0.5%
129-22-45.5e 7
 
0.5%
129-25-07.0e 6
 
0.4%
130-53-24.0e 6
 
0.4%
129-23-12.6e 6
 
0.4%
129-26-11.4e 6
 
0.4%
130-00-00.0e 6
 
0.4%
Other values (751) 1361
95.2%
2024-05-18T17:47:25.297955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3027
17.6%
- 2860
16.7%
1 2185
12.7%
9 1503
8.8%
. 1430
8.3%
E 1430
8.3%
0 946
 
5.5%
3 880
 
5.1%
5 876
 
5.1%
4 673
 
3.9%
Other values (3) 1350
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11440
66.7%
Dash Punctuation 2860
 
16.7%
Other Punctuation 1430
 
8.3%
Uppercase Letter 1430
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3027
26.5%
1 2185
19.1%
9 1503
13.1%
0 946
 
8.3%
3 880
 
7.7%
5 876
 
7.7%
4 673
 
5.9%
6 470
 
4.1%
8 460
 
4.0%
7 420
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 2860
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1430
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15730
91.7%
Latin 1430
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3027
19.2%
- 2860
18.2%
1 2185
13.9%
9 1503
9.6%
. 1430
9.1%
0 946
 
6.0%
3 880
 
5.6%
5 876
 
5.6%
4 673
 
4.3%
6 470
 
3.0%
Other values (2) 880
 
5.6%
Latin
ValueCountFrequency (%)
E 1430
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3027
17.6%
- 2860
16.7%
1 2185
12.7%
9 1503
8.8%
. 1430
8.3%
E 1430
8.3%
0 946
 
5.5%
3 880
 
5.1%
5 876
 
5.1%
4 673
 
3.9%
Other values (3) 1350
7.9%

등부표명(lghtby_nm)
Text

Distinct259
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:26.053524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length13.88951
Min length4

Characters and Unicode

Total characters19862
Distinct characters59
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)7.8%

Sample

1st rowFl(2)Y 6s(No.A)
2nd rowFl(2)Y 6s(No.B)
3rd rowFl(2)Y 6s(No.C)
4th rowFl(2)Y 6s(No.D)
5th rowFl(5)Y 20s(ODAS)
ValueCountFrequency (%)
y 355
 
14.5%
fl(4 235
 
9.6%
fl(4)y8s(no.a 159
 
6.5%
fl(4)y8s(no.b 139
 
5.7%
8s(no.a 101
 
4.1%
8s(no.b 84
 
3.4%
fl(4)y 81
 
3.3%
fl(4)y8s(no.c 65
 
2.7%
fl 54
 
2.2%
8s 41
 
1.7%
Other values (209) 1126
46.1%
2024-05-18T17:47:27.711030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 2574
13.0%
) 2574
13.0%
F 1423
 
7.2%
s 1407
 
7.1%
. 1255
 
6.3%
l 1249
 
6.3%
N 1248
 
6.3%
Y 1223
 
6.2%
o 1130
 
5.7%
1010
 
5.1%
Other values (49) 4769
24.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5573
28.1%
Lowercase Letter 3794
19.1%
Decimal Number 3057
15.4%
Open Punctuation 2574
13.0%
Close Punctuation 2574
13.0%
Other Punctuation 1257
 
6.3%
Space Separator 1010
 
5.1%
Other Letter 22
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 1423
25.5%
N 1248
22.4%
Y 1223
21.9%
A 451
 
8.1%
B 348
 
6.2%
O 185
 
3.3%
C 179
 
3.2%
D 171
 
3.1%
G 92
 
1.7%
R 66
 
1.2%
Other values (11) 187
 
3.4%
Other Letter
ValueCountFrequency (%)
항 3
13.6%
부 2
 
9.1%
표 2
 
9.1%
포 2
 
9.1%
등 2
 
9.1%
신 1
 
4.5%
제 1
 
4.5%
호 1
 
4.5%
양 1
 
4.5%
측 1
 
4.5%
Other values (6) 6
27.3%
Decimal Number
ValueCountFrequency (%)
4 1008
33.0%
8 912
29.8%
2 296
 
9.7%
6 234
 
7.7%
1 168
 
5.5%
5 132
 
4.3%
0 105
 
3.4%
3 100
 
3.3%
7 95
 
3.1%
9 7
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
s 1407
37.1%
l 1249
32.9%
o 1130
29.8%
u 7
 
0.2%
c 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 1255
99.8%
, 1
 
0.1%
" 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2574
100.0%
Space Separator
ValueCountFrequency (%)
1010
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10473
52.7%
Latin 9367
47.2%
Hangul 22
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 1423
15.2%
s 1407
15.0%
l 1249
13.3%
N 1248
13.3%
Y 1223
13.1%
o 1130
12.1%
A 451
 
4.8%
B 348
 
3.7%
O 185
 
2.0%
C 179
 
1.9%
Other values (16) 524
 
5.6%
Common
ValueCountFrequency (%)
( 2574
24.6%
) 2574
24.6%
. 1255
12.0%
1010
 
9.6%
4 1008
 
9.6%
8 912
 
8.7%
2 296
 
2.8%
6 234
 
2.2%
1 168
 
1.6%
5 132
 
1.3%
Other values (7) 310
 
3.0%
Hangul
ValueCountFrequency (%)
항 3
13.6%
부 2
 
9.1%
표 2
 
9.1%
포 2
 
9.1%
등 2
 
9.1%
신 1
 
4.5%
제 1
 
4.5%
호 1
 
4.5%
양 1
 
4.5%
측 1
 
4.5%
Other values (6) 6
27.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19840
99.9%
Hangul 22
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 2574
13.0%
) 2574
13.0%
F 1423
 
7.2%
s 1407
 
7.1%
. 1255
 
6.3%
l 1249
 
6.3%
N 1248
 
6.3%
Y 1223
 
6.2%
o 1130
 
5.7%
1010
 
5.1%
Other values (33) 4747
23.9%
Hangul
ValueCountFrequency (%)
항 3
13.6%
부 2
 
9.1%
표 2
 
9.1%
포 2
 
9.1%
등 2
 
9.1%
신 1
 
4.5%
제 1
 
4.5%
호 1
 
4.5%
양 1
 
4.5%
측 1
 
4.5%
Other values (6) 6
27.3%

비고내용(rm_cn)
Text

Distinct52
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size11.3 KiB
2024-05-18T17:47:28.387960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length2
Mean length2.7531469
Min length2

Characters and Unicode

Total characters3937
Distinct characters47
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)2.4%

Sample

1st row기재
2nd row기재
3rd row기재
4th row기재
5th row기재
ValueCountFrequency (%)
기재 505
34.6%
삭제 312
21.4%
이동전 211
14.5%
이동후 208
14.2%
정지 54
 
3.7%
복구 48
 
3.3%
변경전 15
 
1.0%
변경후 14
 
1.0%
변경(fl(2 7
 
0.5%
g 5
 
0.3%
Other values (48) 81
 
5.5%
2024-05-18T17:47:29.679877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 505
12.8%
재 505
12.8%
이 421
10.7%
동 421
10.7%
삭 312
 
7.9%
제 312
 
7.9%
전 233
 
5.9%
후 232
 
5.9%
) 108
 
2.7%
( 107
 
2.7%
Other values (37) 781
19.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3327
84.5%
Uppercase Letter 129
 
3.3%
Close Punctuation 108
 
2.7%
Open Punctuation 107
 
2.7%
Lowercase Letter 103
 
2.6%
Decimal Number 90
 
2.3%
Other Punctuation 43
 
1.1%
Space Separator 30
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 505
15.2%
재 505
15.2%
이 421
12.7%
동 421
12.7%
삭 312
9.4%
제 312
9.4%
전 233
7.0%
후 232
7.0%
정 94
 
2.8%
변 70
 
2.1%
Other values (6) 222
6.7%
Uppercase Letter
ValueCountFrequency (%)
N 43
33.3%
F 31
24.0%
Y 12
 
9.3%
G 11
 
8.5%
R 8
 
6.2%
A 8
 
6.2%
C 5
 
3.9%
B 2
 
1.6%
D 2
 
1.6%
E 2
 
1.6%
Other values (5) 5
 
3.9%
Decimal Number
ValueCountFrequency (%)
2 26
28.9%
6 20
22.2%
4 12
13.3%
8 11
12.2%
1 9
 
10.0%
3 5
 
5.6%
7 4
 
4.4%
5 2
 
2.2%
9 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
o 43
41.7%
s 30
29.1%
l 30
29.1%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Other Punctuation
ValueCountFrequency (%)
. 43
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3327
84.5%
Common 378
 
9.6%
Latin 232
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 43
18.5%
o 43
18.5%
F 31
13.4%
s 30
12.9%
l 30
12.9%
Y 12
 
5.2%
G 11
 
4.7%
R 8
 
3.4%
A 8
 
3.4%
C 5
 
2.2%
Other values (8) 11
 
4.7%
Hangul
ValueCountFrequency (%)
기 505
15.2%
재 505
15.2%
이 421
12.7%
동 421
12.7%
삭 312
9.4%
제 312
9.4%
전 233
7.0%
후 232
7.0%
정 94
 
2.8%
변 70
 
2.1%
Other values (6) 222
6.7%
Common
ValueCountFrequency (%)
) 108
28.6%
( 107
28.3%
. 43
 
11.4%
30
 
7.9%
2 26
 
6.9%
6 20
 
5.3%
4 12
 
3.2%
8 11
 
2.9%
1 9
 
2.4%
3 5
 
1.3%
Other values (3) 7
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3327
84.5%
ASCII 610
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 505
15.2%
재 505
15.2%
이 421
12.7%
동 421
12.7%
삭 312
9.4%
제 312
9.4%
전 233
7.0%
후 232
7.0%
정 94
 
2.8%
변 70
 
2.1%
Other values (6) 222
6.7%
ASCII
ValueCountFrequency (%)
) 108
17.7%
( 107
17.5%
N 43
 
7.0%
o 43
 
7.0%
. 43
 
7.0%
F 31
 
5.1%
s 30
 
4.9%
30
 
4.9%
l 30
 
4.9%
2 26
 
4.3%
Other values (21) 119
19.5%

Interactions

2024-05-18T17:47:13.107372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T17:47:30.049505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)자료출처명(mtr_ogn_nm)비고내용(rm_cn)
공간정보일련번호(gid)1.0000.9560.446
자료출처명(mtr_ogn_nm)0.9561.0000.310
비고내용(rm_cn)0.4460.3101.000
2024-05-18T17:47:30.441503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)자료출처명(mtr_ogn_nm)
공간정보일련번호(gid)1.0000.864
자료출처명(mtr_ogn_nm)0.8641.000

Missing values

2024-05-18T17:47:13.572092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T17:47:14.065606image/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

공간정보일련번호(gid)자료출처명(mtr_ogn_nm)자료출처상세(mtr_ogn_dtl)등부표위치명(lghtby_lc_nm)도분초위도(dms_la)도분초경도(dms_lo)등부표명(lghtby_nm)비고내용(rm_cn)
012012항행통보연보2012년2호33항동해안 ～ 울산,울산항35-27-48.7N129-23-22.4EFl(2)Y 6s(No.A)기재
122012항행통보연보2012년2호33항동해안 ～ 울산,울산항35-27-54.4N129-23-11.4EFl(2)Y 6s(No.B)기재
232012항행통보연보2012년2호33항동해안 ～ 울산,울산항35-28-09.8N129-23-24.5EFl(2)Y 6s(No.C)기재
342012항행통보연보2012년2호33항동해안 ～ 울산,울산항35-28-01.7N129-23-32.5EFl(2)Y 6s(No.D)기재
452012항행통보연보2012년3호50항동해안 ～ 포항,구룡포36-01-49.2N129-35-15.6EFl(5)Y 20s(ODAS)기재
562012항행통보연보2012년4호62항동해안 ～ 울주,온산35-26-05.6N129-22-23.2EFl(3)Y 7s삭제
672012항행통보연보2012년8호108항동해안 ～ 울산항 부근35-27-05.4N129-21-03.6EFlY 4s(No.B)변경(FlY 4s(No.A))
782012항행통보연보2012년8호108항동해안 ～ 울산항 부근35-27-09.3N129-21-00.9EFlY 4s(No.C)변경(FlY 4s(No.B))
892012항행통보연보2012년8호108항동해안 ～ 울산항 부근35-27-01.2N129-21-15.2EFl(3)Y 7s(No.A)기재
9102012항행통보연보2012년8호116항동해안 ～ 울산항 부근35-29-42.4N129-23-19.5EFl(4)Y 8s(No.A)삭제
공간정보일련번호(gid)자료출처명(mtr_ogn_nm)자료출처상세(mtr_ogn_dtl)등부표위치명(lghtby_lc_nm)도분초위도(dms_la)도분초경도(dms_lo)등부표명(lghtby_nm)비고내용(rm_cn)
142014212019항행통보연보2019년15호276항동해안~울산항 부근35-25-17.6N129-22-43.6EF1(4)Y8s(NO.D)이동전
142114222019항행통보연보2019년15호276항동해안~울산항 부근35-25-11.3N129-22-47.2EF1(4)Y8s(NO.D)이동후
142214232019항행통보연보2019년15호276항동해안~울산항 부근35-25-02.8N129-23-12.6EF1(4)Y8s(NO.F)이동전
142314242019항행통보연보2019년15호276항동해안~울산항 부근35-24-50.0N129-23-12.6EF1(4)Y8s(NO.F)이동후
142414252019항행통보연보2019년15호276항동해안~울산항 부근35-24-46.3N129-23-12.6EF1(4)Y8s(NO.G)이동전
142514262019항행통보연보2019년15호276항동해안~울산항 부근35-24-22.5N129-23-12.4EF1(4)Y8s(NO.G)이동후
142614272019항행통보연보2019년17호334항동해안~구룡포항 부근35-52-51.5N129-31-45.0EF1(4)Y8s(NO.C)이동전
142714282019항행통보연보2019년17호334항동해안~구룡포항 부근35-52-47.3N129-31-45.6EF1(4)Y8s(NO.C)이동후
142814292019항행통보연보2019년50호1173항동해안~동해, 묵호항 부근37-29-39.9N129-08-56.5EF1(4)Y8s(NO.E)변경전
142914302019항행통보연보2019년50호1173항동해안~동해, 묵호항 부근37-29-50.2N129-09-01.2EF1(2)R6s(NO.E)변경후