Overview

Dataset statistics

Number of variables17
Number of observations236
Missing cells15
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.7 KiB
Average record size in memory137.6 B

Variable types

Categorical12
Text2
Boolean2
DateTime1

Dataset

Description공간정보시스템 개방데이터 정보(레이어명, 레이어종류, 레이어유효축척, 레이어, 라벨색상, 선종류, 선색상, 주제도사용, 공개여부 등)
Author강원도 정선군
URLhttps://www.data.go.kr/data/15040128/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
라벨사용여부 is highly overall correlated with 그룹코드 and 6 other fieldsHigh correlation
주제도사용여부 is highly overall correlated with 그룹코드 and 8 other fieldsHigh correlation
선굵기 is highly overall correlated with 그룹코드 and 7 other fieldsHigh correlation
레이어종류 is highly overall correlated with 그룹코드 and 9 other fieldsHigh correlation
레이어 is highly overall correlated with 레이어종류 and 10 other fieldsHigh correlation
레이어유효축척 is highly overall correlated with 레이어종류 and 10 other fieldsHigh correlation
심볼유효축척 is highly overall correlated with 레이어유효축척 and 5 other fieldsHigh correlation
선종류 is highly overall correlated with 레이어종류 and 8 other fieldsHigh correlation
라벨사용컬럼 is highly overall correlated with 레이어종류 and 10 other fieldsHigh correlation
라벨유효축척 is highly overall correlated with 그룹코드 and 10 other fieldsHigh correlation
심볼크기 is highly overall correlated with 그룹코드 and 8 other fieldsHigh correlation
그룹코드 is highly overall correlated with 레이어종류 and 5 other fieldsHigh correlation
라벨색상 is highly overall correlated with 레이어종류 and 9 other fieldsHigh correlation
레이어종류 is highly imbalanced (76.8%)Imbalance
레이어유효축척 is highly imbalanced (77.3%)Imbalance
레이어 is highly imbalanced (77.3%)Imbalance
심볼크기 is highly imbalanced (55.4%)Imbalance
라벨사용여부 is highly imbalanced (82.9%)Imbalance
라벨사용컬럼 is highly imbalanced (77.8%)Imbalance
라벨유효축척 is highly imbalanced (77.8%)Imbalance
라벨색상 is highly imbalanced (76.0%)Imbalance
선종류 is highly imbalanced (79.1%)Imbalance
주제도사용여부 is highly imbalanced (51.2%)Imbalance
선색상 has 15 (6.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:24:15.346492
Analysis finished2023-12-12 20:24:17.009270
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

그룹코드
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
연속주제(국토)
30 
연속주제(지역)
28 
연속주제(환경)
26 
연속주제(산림)
19 
연속주제(도시)
16 
Other values (16)
117 

Length

Max length10
Median length8
Mean length8.029661
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연속주제(환경)
2nd row연속주제(환경)
3rd row연속주제(환경)
4th row연속주제(환경)
5th row연속주제(환경)

Common Values

ValueCountFrequency (%)
연속주제(국토) 30
12.7%
연속주제(지역) 28
11.9%
연속주제(환경) 26
11.0%
연속주제(산림) 19
 
8.1%
연속주제(도시) 16
 
6.8%
연속주제(교통) 15
 
6.4%
연속주제(공업) 14
 
5.9%
연속주제(교육문화) 12
 
5.1%
연속주제(농업) 8
 
3.4%
연속주제(조례) 8
 
3.4%
Other values (11) 60
25.4%

Length

2023-12-13T05:24:17.083558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연속주제(국토 30
12.7%
연속주제(지역 28
11.9%
연속주제(환경 26
11.0%
연속주제(산림 19
 
8.1%
연속주제(도시 16
 
6.8%
연속주제(교통 15
 
6.4%
연속주제(공업 14
 
5.9%
연속주제(교육문화 12
 
5.1%
연속주제(재난 8
 
3.4%
항공(위성)영상 8
 
3.4%
Other values (11) 60
25.4%

레이어명
Text

Distinct235
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T05:24:17.338152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length10.644068
Min length1

Characters and Unicode

Total characters2512
Distinct characters219
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

Unique234 ?
Unique (%)99.2%

Sample

1st row영산강수계/수변구역
2nd row하수도/배수구역
3rd row한강수계/수변구역
4th row폐기물처리시설설치지역
5th row야생동식물보호/용도구역
ValueCountFrequency (%)
산림/기타용도지역지구 2
 
0.8%
항만과그주변지역/항만재개발사업구역 1
 
0.4%
습지보전/습지보호지역 1
 
0.4%
농어촌정비/농어촌정비 1
 
0.4%
교차로 1
 
0.4%
도로구간 1
 
0.4%
실폭도로 1
 
0.4%
네이버영상 1
 
0.4%
보금자리주택/용도지구 1
 
0.4%
속초시조례/도시계획 1
 
0.4%
Other values (225) 225
95.3%
2023-12-13T05:24:17.804407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 203
 
8.1%
지 187
 
7.4%
역 145
 
5.8%
구 114
 
4.5%
도 114
 
4.5%
용 67
 
2.7%
시 47
 
1.9%
계 46
 
1.8%
기 43
 
1.7%
보 39
 
1.6%
Other values (209) 1507
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2284
90.9%
Other Punctuation 203
 
8.1%
Decimal Number 23
 
0.9%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 187
 
8.2%
역 145
 
6.3%
구 114
 
5.0%
도 114
 
5.0%
용 67
 
2.9%
시 47
 
2.1%
계 46
 
2.0%
기 43
 
1.9%
보 39
 
1.7%
획 38
 
1.7%
Other values (200) 1444
63.2%
Decimal Number
ValueCountFrequency (%)
1 9
39.1%
0 6
26.1%
2 5
21.7%
5 1
 
4.3%
3 1
 
4.3%
7 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/ 203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2284
90.9%
Common 228
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 187
 
8.2%
역 145
 
6.3%
구 114
 
5.0%
도 114
 
5.0%
용 67
 
2.9%
시 47
 
2.1%
계 46
 
2.0%
기 43
 
1.9%
보 39
 
1.7%
획 38
 
1.7%
Other values (200) 1444
63.2%
Common
ValueCountFrequency (%)
/ 203
89.0%
1 9
 
3.9%
0 6
 
2.6%
2 5
 
2.2%
5 1
 
0.4%
3 1
 
0.4%
( 1
 
0.4%
) 1
 
0.4%
7 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2284
90.9%
ASCII 228
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 203
89.0%
1 9
 
3.9%
0 6
 
2.6%
2 5
 
2.2%
5 1
 
0.4%
3 1
 
0.4%
( 1
 
0.4%
) 1
 
0.4%
7 1
 
0.4%
Hangul
ValueCountFrequency (%)
지 187
 
8.2%
역 145
 
6.3%
구 114
 
5.0%
도 114
 
5.0%
용 67
 
2.9%
시 47
 
2.1%
계 46
 
2.0%
기 43
 
1.9%
보 39
 
1.7%
획 38
 
1.7%
Other values (200) 1444
63.2%

레이어종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
MA
219 
ST
 
8
SP
 
8
ML
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
MA 219
92.8%
ST 8
 
3.4%
SP 8
 
3.4%
ML 1
 
0.4%

Length

2023-12-13T05:24:17.995726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:18.120177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ma 219
92.8%
st 8
 
3.4%
sp 8
 
3.4%
ml 1
 
0.4%

레이어유효축척
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
500,100,000
210 
50,080,000,000
 
4
5,008,000,000
 
4
500,800,000
 
4
5,005,000
 
3
Other values (10)
 
11

Length

Max length14
Median length11
Mean length11.033898
Min length8

Unique

Unique9 ?
Unique (%)3.8%

Sample

1st row500,100,000
2nd row500,100,000
3rd row500,100,000
4th row500,100,000
5th row500,100,000

Common Values

ValueCountFrequency (%)
500,100,000 210
89.0%
50,080,000,000 4
 
1.7%
5,008,000,000 4
 
1.7%
500,800,000 4
 
1.7%
5,005,000 3
 
1.3%
50,010,000 2
 
0.8%
10,080,000,000 1
 
0.4%
100,250,000 1
 
0.4%
0,250000 1
 
0.4%
0,100000 1
 
0.4%
Other values (5) 5
 
2.1%

Length

2023-12-13T05:24:18.260440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
500,100,000 210
89.0%
50,080,000,000 4
 
1.7%
5,008,000,000 4
 
1.7%
500,800,000 4
 
1.7%
5,005,000 3
 
1.3%
50,010,000 2
 
0.8%
10,080,000,000 1
 
0.4%
100,250,000 1
 
0.4%
0,250000 1
 
0.4%
0,100000 1
 
0.4%
Other values (5) 5
 
2.1%

레이어
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
500,100,000
210 
50,080,000,000
 
4
5,008,000,000
 
4
500,800,000
 
4
5,005,000
 
3
Other values (10)
 
11

Length

Max length14
Median length11
Mean length11.033898
Min length8

Unique

Unique9 ?
Unique (%)3.8%

Sample

1st row500,100,000
2nd row500,100,000
3rd row500,100,000
4th row500,100,000
5th row500,100,000

Common Values

ValueCountFrequency (%)
500,100,000 210
89.0%
50,080,000,000 4
 
1.7%
5,008,000,000 4
 
1.7%
500,800,000 4
 
1.7%
5,005,000 3
 
1.3%
50,010,000 2
 
0.8%
10,080,000,000 1
 
0.4%
100,250,000 1
 
0.4%
0,250000 1
 
0.4%
0,100000 1
 
0.4%
Other values (5) 5
 
2.1%

Length

2023-12-13T05:24:18.432153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
500,100,000 210
89.0%
50,080,000,000 4
 
1.7%
5,008,000,000 4
 
1.7%
500,800,000 4
 
1.7%
5,005,000 3
 
1.3%
50,010,000 2
 
0.8%
10,080,000,000 1
 
0.4%
100,250,000 1
 
0.4%
0,250000 1
 
0.4%
0,100000 1
 
0.4%
Other values (5) 5
 
2.1%

심볼유효축척
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
122 
0,0
113 
0
 
1

Length

Max length4
Median length4
Mean length3.5084746
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0,0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 122
51.7%
0,0 113
47.9%
0 1
 
0.4%

Length

2023-12-13T05:24:18.598162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:18.807605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 122
51.7%
0,0 113
47.9%
0 1
 
0.4%

심볼크기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
115 
0,0
113 
12,12
 
3
12,32
 
2
50,50
 
1
Other values (2)
 
2

Length

Max length7
Median length5
Mean length3.5635593
Min length3

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st row0,0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 115
48.7%
0,0 113
47.9%
12,12 3
 
1.3%
12,32 2
 
0.8%
50,50 1
 
0.4%
100,100 1
 
0.4%
30,30 1
 
0.4%

Length

2023-12-13T05:24:18.964204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:19.131245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
48.7%
0,0 113
47.9%
12,12 3
 
1.3%
12,32 2
 
0.8%
50,50 1
 
0.4%
100,100 1
 
0.4%
30,30 1
 
0.4%

라벨사용여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Y
224 
<NA>
 
9
N
 
2
 
1

Length

Max length4
Median length1
Mean length1.1144068
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
Y 224
94.9%
<NA> 9
 
3.8%
N 2
 
0.8%
1
 
0.4%

Length

2023-12-13T05:24:19.277352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:19.425564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 224
95.3%
na 9
 
3.8%
n 2
 
0.9%

라벨사용컬럼
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct13
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
uname
210 
<NA>
 
11
jibun
 
2
dogeun_poi
 
2
trag_point
 
2
Other values (8)
 
9

Length

Max length14
Median length5
Mean length5.2076271
Min length4

Unique

Unique7 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
uname 210
89.0%
<NA> 11
 
4.7%
jibun 2
 
0.8%
dogeun_poi 2
 
0.8%
trag_point 2
 
0.8%
trag_asstc 2
 
0.8%
sig_kor_nm 1
 
0.4%
emd_kor_nm 1
 
0.4%
li_kor_nm 1
 
0.4%
buld_nm,rd_lbl 1
 
0.4%
Other values (3) 3
 
1.3%

Length

2023-12-13T05:24:19.571515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uname 210
89.0%
na 11
 
4.7%
jibun 2
 
0.8%
dogeun_poi 2
 
0.8%
trag_point 2
 
0.8%
trag_asstc 2
 
0.8%
sig_kor_nm 1
 
0.4%
emd_kor_nm 1
 
0.4%
li_kor_nm 1
 
0.4%
buld_nm,rd_lbl 1
 
0.4%
Other values (3) 3
 
1.3%

라벨유효축척
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
500,100,000
211 
<NA>
 
10
0,0
 
5
500,800,000
 
3
5,001,500
 
1
Other values (6)
 
6

Length

Max length11
Median length11
Mean length10.504237
Min length3

Unique

Unique7 ?
Unique (%)3.0%

Sample

1st row500,100,000
2nd row500,100,000
3rd row500,100,000
4th row500,100,000
5th row500,100,000

Common Values

ValueCountFrequency (%)
500,100,000 211
89.4%
<NA> 10
 
4.2%
0,0 5
 
2.1%
500,800,000 3
 
1.3%
5,001,500 1
 
0.4%
250,010,000 1
 
0.4%
5,005,000 1
 
0.4%
50,040,000 1
 
0.4%
1,007,000 1
 
0.4%
200,100,000 1
 
0.4%

Length

2023-12-13T05:24:19.732029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
500,100,000 211
89.4%
na 10
 
4.2%
0,0 5
 
2.1%
500,800,000 3
 
1.3%
5,001,500 1
 
0.4%
250,010,000 1
 
0.4%
5,005,000 1
 
0.4%
50,040,000 1
 
0.4%
1,007,000 1
 
0.4%
200,100,000 1
 
0.4%

라벨색상
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0,0,0,255
209 
<NA>
 
8
255,255,0,255
 
7
204,255,0,255
 
4
255,255,255,255
 
2
Other values (6)
 
6

Length

Max length15
Median length9
Mean length9.1355932
Min length4

Unique

Unique6 ?
Unique (%)2.5%

Sample

1st row0,0,0,255
2nd row0,0,0,255
3rd row0,0,0,255
4th row0,0,0,255
5th row0,0,0,255

Common Values

ValueCountFrequency (%)
0,0,0,255 209
88.6%
<NA> 8
 
3.4%
255,255,0,255 7
 
3.0%
204,255,0,255 4
 
1.7%
255,255,255,255 2
 
0.8%
0,0,255,255 1
 
0.4%
255,0,0,255 1
 
0.4%
51,153,204,255 1
 
0.4%
0,0,204,255 1
 
0.4%
51,0,153,255 1
 
0.4%

Length

2023-12-13T05:24:19.916842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0,0,0,255 209
88.6%
na 8
 
3.4%
255,255,0,255 7
 
3.0%
204,255,0,255 4
 
1.7%
255,255,255,255 2
 
0.8%
0,0,255,255 1
 
0.4%
255,0,0,255 1
 
0.4%
51,153,204,255 1
 
0.4%
0,0,204,255 1
 
0.4%
51,0,153,255 1
 
0.4%

선종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
100
215 
<NA>
 
13
 
4
103
 
1
104
 
1
Other values (2)
 
2

Length

Max length4
Median length3
Mean length3.0550847
Min length3

Unique

Unique4 ?
Unique (%)1.7%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 215
91.1%
<NA> 13
 
5.5%
4
 
1.7%
103 1
 
0.4%
104 1
 
0.4%
101 1
 
0.4%
500 1
 
0.4%

Length

2023-12-13T05:24:20.053300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:20.187778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 215
92.7%
na 13
 
5.6%
103 1
 
0.4%
104 1
 
0.4%
101 1
 
0.4%
500 1
 
0.4%

선색상
Text

MISSING 

Distinct128
Distinct (%)57.9%
Missing15
Missing (%)6.4%
Memory size2.0 KiB
2023-12-13T05:24:20.485733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.484163
Min length9

Characters and Unicode

Total characters2759
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

Unique117 ?
Unique (%)52.9%

Sample

1st row140,140,140,255
2nd row51,204,255,120
3rd row0,204,255,130
4th row102,102,102,130
5th row255,51,255,100
ValueCountFrequency (%)
0,0,0,255 48
21.7%
140,140,140,255 23
 
10.4%
255,0,0,255 13
 
5.9%
255,128,128,255 6
 
2.7%
204,0,255,150 2
 
0.9%
204,0,255,100 2
 
0.9%
51,102,0,255 2
 
0.9%
153,102,102,150 2
 
0.9%
255,51,255,100 2
 
0.9%
153,51,255,100 2
 
0.9%
Other values (118) 119
53.8%
2023-12-13T05:24:21.013980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 663
24.0%
5 545
19.8%
0 535
19.4%
1 395
14.3%
2 356
12.9%
4 112
 
4.1%
3 71
 
2.6%
8 32
 
1.2%
9 21
 
0.8%
7 15
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2096
76.0%
Other Punctuation 663
 
24.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 545
26.0%
0 535
25.5%
1 395
18.8%
2 356
17.0%
4 112
 
5.3%
3 71
 
3.4%
8 32
 
1.5%
9 21
 
1.0%
7 15
 
0.7%
6 14
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 663
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2759
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 663
24.0%
5 545
19.8%
0 535
19.4%
1 395
14.3%
2 356
12.9%
4 112
 
4.1%
3 71
 
2.6%
8 32
 
1.2%
9 21
 
0.8%
7 15
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2759
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 663
24.0%
5 545
19.8%
0 535
19.4%
1 395
14.3%
2 356
12.9%
4 112
 
4.1%
3 71
 
2.6%
8 32
 
1.2%
9 21
 
0.8%
7 15
 
0.5%

선굵기
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
115 
2
87 
1
18 
<NA>
15 
10
 
1

Length

Max length4
Median length1
Mean length1.1949153
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
0 115
48.7%
2 87
36.9%
1 18
 
7.6%
<NA> 15
 
6.4%
10 1
 
0.4%

Length

2023-12-13T05:24:21.216851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:21.328516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 115
48.7%
2 87
36.9%
1 18
 
7.6%
na 15
 
6.4%
10 1
 
0.4%

주제도사용여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size368.0 B
True
211 
False
25 
ValueCountFrequency (%)
True 211
89.4%
False 25
 
10.6%
2023-12-13T05:24:21.433263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

공개여부
Boolean

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size368.0 B
False
123 
True
113 
ValueCountFrequency (%)
False 123
52.1%
True 113
47.9%
2023-12-13T05:24:21.536113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2022-09-27 00:00:00
Maximum2022-09-27 00:00:00
2023-12-13T05:24:21.634861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:21.746186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T05:24:21.851597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그룹코드레이어종류레이어유효축척레이어심볼유효축척심볼크기라벨사용여부라벨사용컬럼라벨유효축척라벨색상선종류선굵기주제도사용여부공개여부
그룹코드1.0000.8880.8760.8760.2890.8540.9490.8390.9100.8760.7680.8530.9570.585
레이어종류0.8881.0000.9440.9440.6951.0000.6731.0000.9610.7290.8130.1330.9260.402
레이어유효축척0.8760.9441.0001.0001.0000.9581.0000.9970.9810.9720.9970.7920.9680.310
레이어0.8760.9441.0001.0001.0000.9581.0000.9970.9810.9720.9970.7920.9680.310
심볼유효축척0.2890.6951.0001.0001.0000.6950.0001.0001.0000.0000.453NaN0.0000.000
심볼크기0.8541.0000.9580.9580.6951.0000.0000.9240.9440.7780.4351.0000.8850.065
라벨사용여부0.9490.6731.0001.0000.0000.0001.0001.0000.9190.8580.6240.1730.2530.051
라벨사용컬럼0.8391.0000.9970.9971.0000.9241.0001.0000.9670.9740.9960.9000.9910.255
라벨유효축척0.9100.9610.9810.9811.0000.9440.9190.9671.0000.9810.7870.4460.9840.283
라벨색상0.8760.7290.9720.9720.0000.7780.8580.9740.9811.0000.9150.8990.9220.344
선종류0.7680.8130.9970.9970.4530.4350.6240.9960.7870.9151.0000.7360.8160.215
선굵기0.8530.1330.7920.792NaN1.0000.1730.9000.4460.8990.7361.0000.5450.465
주제도사용여부0.9570.9260.9680.9680.0000.8850.2530.9910.9840.9220.8160.5451.0000.509
공개여부0.5850.4020.3100.3100.0000.0650.0510.2550.2830.3440.2150.4650.5091.000
2023-12-13T05:24:22.048192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨색상라벨사용여부주제도사용여부선굵기레이어종류레이어레이어유효축척심볼유효축척선종류라벨사용컬럼공개여부라벨유효축척그룹코드심볼크기
라벨색상1.0000.6780.7530.5930.5840.8810.8810.0000.8020.8880.2590.7590.4770.574
라벨사용여부0.6781.0000.4110.1140.7010.9750.9750.0000.3190.9770.0840.7480.7330.000
주제도사용여부0.7530.4111.0000.3700.7510.9490.9490.0000.6140.8960.3400.8750.8970.687
선굵기0.5930.1140.3701.0000.1250.6040.6041.0000.5680.5940.3120.3010.6370.996
레이어종류0.5840.7010.7510.1251.0000.8360.8360.4890.6630.9800.2680.9460.6850.983
레이어0.8810.9750.9490.6040.8361.0001.0000.9730.9040.8860.2750.9170.5000.865
레이어유효축척0.8810.9750.9490.6040.8361.0001.0000.9730.9040.8860.2750.9170.5000.865
심볼유효축척0.0000.0000.0001.0000.4890.9730.9731.0000.5430.9820.0000.9910.2110.489
선종류0.8020.3190.6140.5680.6630.9040.9040.5431.0000.9390.1530.6160.4740.362
라벨사용컬럼0.8880.9770.8960.5940.9800.8860.8860.9820.9391.0000.1930.8630.4660.745
공개여부0.2590.0840.3400.3120.2680.2750.2750.0000.1530.1931.0000.2120.4970.042
라벨유효축척0.7590.7480.8750.3010.9460.9170.9170.9910.6160.8630.2121.0000.5380.885
그룹코드0.4770.7330.8970.6370.6850.5000.5000.2110.4740.4660.4970.5381.0000.601
심볼크기0.5740.0000.6870.9960.9830.8650.8650.4890.3620.7450.0420.8850.6011.000
2023-12-13T05:24:22.232144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그룹코드레이어종류레이어유효축척레이어심볼유효축척심볼크기라벨사용여부라벨사용컬럼라벨유효축척라벨색상선종류선굵기주제도사용여부공개여부
그룹코드1.0000.6850.5000.5000.2110.6010.7330.4660.5380.4770.4740.6370.8970.497
레이어종류0.6851.0000.8360.8360.4890.9830.7010.9800.9460.5840.6630.1250.7510.268
레이어유효축척0.5000.8361.0001.0000.9730.8650.9750.8860.9170.8810.9040.6040.9490.275
레이어0.5000.8361.0001.0000.9730.8650.9750.8860.9170.8810.9040.6040.9490.275
심볼유효축척0.2110.4890.9730.9731.0000.4890.0000.9820.9910.0000.5431.0000.0000.000
심볼크기0.6010.9830.8650.8650.4891.0000.0000.7450.8850.5740.3620.9960.6870.042
라벨사용여부0.7330.7010.9750.9750.0000.0001.0000.9770.7480.6780.3190.1140.4110.084
라벨사용컬럼0.4660.9800.8860.8860.9820.7450.9771.0000.8630.8880.9390.5940.8960.193
라벨유효축척0.5380.9460.9170.9170.9910.8850.7480.8631.0000.7590.6160.3010.8750.212
라벨색상0.4770.5840.8810.8810.0000.5740.6780.8880.7591.0000.8020.5930.7530.259
선종류0.4740.6630.9040.9040.5430.3620.3190.9390.6160.8021.0000.5680.6140.153
선굵기0.6370.1250.6040.6041.0000.9960.1140.5940.3010.5930.5681.0000.3700.312
주제도사용여부0.8970.7510.9490.9490.0000.6870.4110.8960.8750.7530.6140.3701.0000.340
공개여부0.4970.2680.2750.2750.0000.0420.0840.1930.2120.2590.1530.3120.3401.000

Missing values

2023-12-13T05:24:16.717640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:24:16.930182image/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

그룹코드레이어명레이어종류레이어유효축척레이어심볼유효축척심볼크기라벨사용여부라벨사용컬럼라벨유효축척라벨색상선종류선색상선굵기주제도사용여부공개여부데이터기준일자
0연속주제(환경)영산강수계/수변구역MA500,100,000500,100,0000,00,0Yuname500,100,0000,0,0,255100140,140,140,2550YN2022-09-27
1연속주제(환경)하수도/배수구역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,25510051,204,255,1202YY2022-09-27
2연속주제(환경)한강수계/수변구역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,2551000,204,255,1302YY2022-09-27
3연속주제(환경)폐기물처리시설설치지역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,255100102,102,102,1302YY2022-09-27
4연속주제(환경)야생동식물보호/용도구역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,255100255,51,255,1002YY2022-09-27
5연속주제(환경)자연환경/용도구역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,2551000,153,153,1202YY2022-09-27
6연속주제(환경)자연환경/용도지역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,25510051,153,102,1502YY2022-09-27
7연속주제(환경)자연공원/용도지구MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,255100153,51,255,1002YY2022-09-27
8연속주제(환경)자연공원/용도구역MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,255100153,153,0,1502YY2022-09-27
9연속주제(군사)군사기지/군사시설보호MA500,100,000500,100,000<NA><NA>Yuname500,100,0000,0,0,2551000,51,0,1502YY2022-09-27
그룹코드레이어명레이어종류레이어유효축척레이어심볼유효축척심볼크기라벨사용여부라벨사용컬럼라벨유효축척라벨색상선종류선색상선굵기주제도사용여부공개여부데이터기준일자
226항공(위성)영상정선군2015년ST5,008,000,0005,008,000,000<NA><NA><NA><NA><NA><NA><NA><NA><NA>NY2022-09-27
227항공(위성)영상정선군2017년ST50,080,000,00050,080,000,000<NA><NA><NA><NA><NA><NA><NA>NY2022-09-27
228KLIS(지적기반)연속지적MA1,007,0001,007,0000,00,0Yjibun1,007,000255,255,255,255100255,153,0,2550NY2022-09-27
229지적기준점지적도근점SP500,800,000500,800,000<NA>12,12Ydogeun_poi500,800,000204,255,0,255<NA><NA><NA>NY2022-09-27
230지적기준점지적삼각점SP500,800,000500,800,000<NA>12,12Ytrag_point500,800,000204,255,0,255<NA><NA><NA>NY2022-09-27
231지적기준점지적삼각보조점SP500,800,000500,800,000<NA>12,12Ytrag_asstc500,800,000204,255,0,255<NA><NA><NA>NY2022-09-27
232연속주제(공업)지역개발사업구역/지역개발사업구역MA500,100,000500,100,0000,00,0Yuname500,100,0000,0,0,255100140,140,140,2550YY2022-09-27
233연속주제(지역)지적도근점1SP500,800,000500,800,000<NA>50,50Ytrag_point500,100,0000,0,0,255<NA><NA><NA>NY2022-09-27
234연속주제(지역)지적삼각보조점1SP3,001,000,0003,001,000,000<NA>100,100Ytrag_asstc200,100,000255,255,255<NA><NA><NA>NY2022-09-27
235연속주제(지역)지적삼각점1SP2,001,000,0002,001,000,000030,30Ydogeun_poi100,100,0000,0,0,255<NA><NA>YY2022-09-27