Overview

Dataset statistics

Number of variables11
Number of observations427
Missing cells176
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.2 KiB
Average record size in memory89.3 B

Variable types

Text6
Categorical2
Numeric1
DateTime2

Dataset

Description충청북도 제천시_개발행위허가현황입니다.파일내용은 허가번호, 소재지, 읍면동, 리, 지목, 용도지역, 허가면적, 용도, 허가일, 준공일, 데이터기준일 입니다.
Author충청북도 제천시
URLhttps://www.data.go.kr/data/15125581/fileData.do

Alerts

데이터기준일 has constant value ""Constant
리 has 159 (37.2%) missing valuesMissing
용도 has 17 (4.0%) missing valuesMissing
허가면적 is highly skewed (γ1 = 20.25345386)Skewed
허가번호 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:40:27.348028
Analysis finished2024-01-14 13:40:30.765455
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Text

UNIQUE 

Distinct427
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-01-14T22:40:31.117706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.7962529
Min length7

Characters and Unicode

Total characters3329
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

Unique427 ?
Unique (%)100.0%

Sample

1st row2023-001
2nd row2023-002
3rd row2023-003
4th row2023-004
5th row2023-005
ValueCountFrequency (%)
2023-001 1
 
0.2%
2023-293 1
 
0.2%
2023-291 1
 
0.2%
2023-290 1
 
0.2%
2023-289 1
 
0.2%
2023-288 1
 
0.2%
2023-287 1
 
0.2%
2023-286 1
 
0.2%
2023-285 1
 
0.2%
2023-284 1
 
0.2%
Other values (417) 417
97.7%
2024-01-14T22:40:31.750980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1045
31.4%
3 610
18.3%
0 530
15.9%
- 427
12.8%
1 193
 
5.8%
4 111
 
3.3%
6 83
 
2.5%
5 83
 
2.5%
7 83
 
2.5%
8 82
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2902
87.2%
Dash Punctuation 427
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1045
36.0%
3 610
21.0%
0 530
18.3%
1 193
 
6.7%
4 111
 
3.8%
6 83
 
2.9%
5 83
 
2.9%
7 83
 
2.9%
8 82
 
2.8%
9 82
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 427
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1045
31.4%
3 610
18.3%
0 530
15.9%
- 427
12.8%
1 193
 
5.8%
4 111
 
3.3%
6 83
 
2.5%
5 83
 
2.5%
7 83
 
2.5%
8 82
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1045
31.4%
3 610
18.3%
0 530
15.9%
- 427
12.8%
1 193
 
5.8%
4 111
 
3.3%
6 83
 
2.5%
5 83
 
2.5%
7 83
 
2.5%
8 82
 
2.5%

소재지
Text

Distinct414
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-01-14T22:40:32.221446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length56
Mean length24.156909
Min length16

Characters and Unicode

Total characters10315
Distinct characters122
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique402 ?
Unique (%)94.1%

Sample

1st row충청북도 제천시 강제동 177-10, 177-30
2nd row충청북도 제천시 봉양읍 원박리 234-1
3rd row충청북도 제천시 백운면 방학리 274
4th row충청북도 제천시 백운면 방학리 276-1, 272-29
5th row충청북도 제천시 백운면 방학리 274-2, 272-28
ValueCountFrequency (%)
제천시 428
19.5%
충청북도 427
19.5%
봉양읍 69
 
3.1%
송학면 47
 
2.1%
백운면 46
 
2.1%
청풍면 26
 
1.2%
수산면 25
 
1.1%
금성면 25
 
1.1%
고명동 21
 
1.0%
덕산면 20
 
0.9%
Other values (664) 1058
48.3%
2024-01-14T22:40:32.927695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1948
18.9%
1 503
 
4.9%
- 477
 
4.6%
도 470
 
4.6%
청 457
 
4.4%
제 443
 
4.3%
시 438
 
4.2%
천 436
 
4.2%
북 430
 
4.2%
충 427
 
4.1%
Other values (112) 4286
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5173
50.2%
Decimal Number 2484
24.1%
Space Separator 1948
 
18.9%
Dash Punctuation 477
 
4.6%
Other Punctuation 231
 
2.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 470
 
9.1%
청 457
 
8.8%
제 443
 
8.6%
시 438
 
8.5%
천 436
 
8.4%
북 430
 
8.3%
충 427
 
8.3%
리 268
 
5.2%
면 198
 
3.8%
동 176
 
3.4%
Other values (97) 1430
27.6%
Decimal Number
ValueCountFrequency (%)
1 503
20.2%
2 347
14.0%
3 294
11.8%
5 235
9.5%
4 231
9.3%
6 195
 
7.9%
9 192
 
7.7%
7 171
 
6.9%
8 160
 
6.4%
0 156
 
6.3%
Space Separator
ValueCountFrequency (%)
1948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%
Other Punctuation
ValueCountFrequency (%)
, 231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5173
50.2%
Common 5142
49.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 470
 
9.1%
청 457
 
8.8%
제 443
 
8.6%
시 438
 
8.5%
천 436
 
8.4%
북 430
 
8.3%
충 427
 
8.3%
리 268
 
5.2%
면 198
 
3.8%
동 176
 
3.4%
Other values (97) 1430
27.6%
Common
ValueCountFrequency (%)
1948
37.9%
1 503
 
9.8%
- 477
 
9.3%
2 347
 
6.7%
3 294
 
5.7%
5 235
 
4.6%
, 231
 
4.5%
4 231
 
4.5%
6 195
 
3.8%
9 192
 
3.7%
Other values (5) 489
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5173
50.2%
ASCII 5142
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1948
37.9%
1 503
 
9.8%
- 477
 
9.3%
2 347
 
6.7%
3 294
 
5.7%
5 235
 
4.6%
, 231
 
4.5%
4 231
 
4.5%
6 195
 
3.8%
9 192
 
3.7%
Other values (5) 489
 
9.5%
Hangul
ValueCountFrequency (%)
도 470
 
9.1%
청 457
 
8.8%
제 443
 
8.6%
시 438
 
8.5%
천 436
 
8.4%
북 430
 
8.3%
충 427
 
8.3%
리 268
 
5.2%
면 198
 
3.8%
동 176
 
3.4%
Other values (97) 1430
27.6%

읍면동
Categorical

Distinct37
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
봉양읍
69 
백운면
46 
송학면
42 
청풍면
26 
수산면
25 
Other values (32)
219 

Length

Max length5
Median length3
Mean length3.0140515
Min length2

Unique

Unique9 ?
Unique (%)2.1%

Sample

1st row강제동
2nd row봉양읍
3rd row백운면
4th row백운면
5th row백운면

Common Values

ValueCountFrequency (%)
봉양읍 69
16.2%
백운면 46
 
10.8%
송학면 42
 
9.8%
청풍면 26
 
6.1%
수산면 25
 
5.9%
금성면 25
 
5.9%
덕산면 20
 
4.7%
고명동 20
 
4.7%
강제동 14
 
3.3%
두학동 14
 
3.3%
Other values (27) 126
29.5%

Length

2024-01-14T22:40:33.163701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
봉양읍 69
16.2%
송학면 47
 
11.0%
백운면 46
 
10.8%
청풍면 26
 
6.1%
수산면 25
 
5.9%
금성면 25
 
5.9%
고명동 21
 
4.9%
덕산면 20
 
4.7%
강제동 14
 
3.3%
두학동 14
 
3.3%
Other values (25) 120
28.1%

리
Text

MISSING 

Distinct75
Distinct (%)28.0%
Missing159
Missing (%)37.2%
Memory size3.5 KiB
2024-01-14T22:40:33.504562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0410448
Min length2

Characters and Unicode

Total characters815
Distinct characters78
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)9.7%

Sample

1st row원박리
2nd row방학리
3rd row방학리
4th row방학리
5th row원월리
ValueCountFrequency (%)
도화리 16
 
6.0%
원박리 12
 
4.5%
원월리 12
 
4.5%
시곡리 10
 
3.7%
연박리 9
 
3.4%
무도리 9
 
3.4%
모정리 7
 
2.6%
동막리 7
 
2.6%
방학리 7
 
2.6%
운학리 7
 
2.6%
Other values (63) 172
64.2%
2024-01-14T22:40:34.019922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 268
32.9%
도 43
 
5.3%
곡 41
 
5.0%
원 25
 
3.1%
화 25
 
3.1%
학 22
 
2.7%
박 21
 
2.6%
월 19
 
2.3%
전 18
 
2.2%
동 16
 
2.0%
Other values (68) 317
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 800
98.2%
Space Separator 15
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 268
33.5%
도 43
 
5.4%
곡 41
 
5.1%
원 25
 
3.1%
화 25
 
3.1%
학 22
 
2.8%
박 21
 
2.6%
월 19
 
2.4%
전 18
 
2.2%
동 16
 
2.0%
Other values (67) 302
37.8%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 800
98.2%
Common 15
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 268
33.5%
도 43
 
5.4%
곡 41
 
5.1%
원 25
 
3.1%
화 25
 
3.1%
학 22
 
2.8%
박 21
 
2.6%
월 19
 
2.4%
전 18
 
2.2%
동 16
 
2.0%
Other values (67) 302
37.8%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 800
98.2%
ASCII 15
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 268
33.5%
도 43
 
5.4%
곡 41
 
5.1%
원 25
 
3.1%
화 25
 
3.1%
학 22
 
2.8%
박 21
 
2.6%
월 19
 
2.4%
전 18
 
2.2%
동 16
 
2.0%
Other values (67) 302
37.8%
ASCII
ValueCountFrequency (%)
15
100.0%

지목
Text

Distinct407
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-01-14T22:40:34.397234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length42
Mean length8.29274
Min length1

Characters and Unicode

Total characters3541
Distinct characters30
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

Unique388 ?
Unique (%)90.9%

Sample

1st row177-10, 177-30
2nd row234-1
3rd row274
4th row276-1, 272-29
5th row274-2, 272-28
ValueCountFrequency (%)
외 14
 
2.2%
1 10
 
1.5%
28 4
 
0.6%
산31 3
 
0.5%
128-1 3
 
0.5%
2 3
 
0.5%
253 3
 
0.5%
02월 3
 
0.5%
01월 3
 
0.5%
1097-10 3
 
0.5%
Other values (562) 602
92.5%
2024-01-14T22:40:34.894147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 507
14.3%
- 461
13.0%
2 344
9.7%
3 298
8.4%
5 232
 
6.6%
227
 
6.4%
, 226
 
6.4%
4 225
 
6.4%
6 195
 
5.5%
9 195
 
5.5%
Other values (20) 631
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
70.6%
Dash Punctuation 461
 
13.0%
Space Separator 227
 
6.4%
Other Punctuation 227
 
6.4%
Other Letter 122
 
3.4%
Math Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 83
68.0%
외 14
 
11.5%
월 8
 
6.6%
일 8
 
6.6%
동 2
 
1.6%
장 1
 
0.8%
관 1
 
0.8%
지 1
 
0.8%
제 1
 
0.8%
강 1
 
0.8%
Other values (2) 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 507
20.3%
2 344
13.8%
3 298
11.9%
5 232
9.3%
4 225
9.0%
6 195
 
7.8%
9 195
 
7.8%
7 175
 
7.0%
0 171
 
6.8%
8 158
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 226
99.6%
. 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 461
100.0%
Space Separator
ValueCountFrequency (%)
227
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3418
96.5%
Hangul 122
 
3.4%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 507
14.8%
- 461
13.5%
2 344
10.1%
3 298
8.7%
5 232
6.8%
227
6.6%
, 226
6.6%
4 225
6.6%
6 195
 
5.7%
9 195
 
5.7%
Other values (7) 508
14.9%
Hangul
ValueCountFrequency (%)
산 83
68.0%
외 14
 
11.5%
월 8
 
6.6%
일 8
 
6.6%
동 2
 
1.6%
장 1
 
0.8%
관 1
 
0.8%
지 1
 
0.8%
제 1
 
0.8%
강 1
 
0.8%
Other values (2) 2
 
1.6%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3419
96.6%
Hangul 122
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 507
14.8%
- 461
13.5%
2 344
10.1%
3 298
8.7%
5 232
6.8%
227
6.6%
, 226
6.6%
4 225
6.6%
6 195
 
5.7%
9 195
 
5.7%
Other values (8) 509
14.9%
Hangul
ValueCountFrequency (%)
산 83
68.0%
외 14
 
11.5%
월 8
 
6.6%
일 8
 
6.6%
동 2
 
1.6%
장 1
 
0.8%
관 1
 
0.8%
지 1
 
0.8%
제 1
 
0.8%
강 1
 
0.8%
Other values (2) 2
 
1.6%

용도지역
Categorical

Distinct29
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
계획관리지역
154 
생산관리지역
88 
자연녹지지역
80 
제2종일반주거지역
24 
보전관리지역
22 
Other values (24)
59 

Length

Max length29
Median length6
Mean length6.64637
Min length4

Unique

Unique12 ?
Unique (%)2.8%

Sample

1st row자연녹지지역
2nd row농림지역
3rd row계획관리지역
4th row계획관리지역
5th row계획관리지역

Common Values

ValueCountFrequency (%)
계획관리지역 154
36.1%
생산관리지역 88
20.6%
자연녹지지역 80
18.7%
제2종일반주거지역 24
 
5.6%
보전관리지역 22
 
5.2%
농림지역 13
 
3.0%
일반공업지역 8
 
1.9%
생산관리지역, 도축장 3
 
0.7%
자연녹지지역,자연취락지구 3
 
0.7%
자연환경보전지역 3
 
0.7%
Other values (19) 29
 
6.8%

Length

2024-01-14T22:40:35.056987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계획관리지역 163
36.0%
생산관리지역 95
21.0%
자연녹지지역 83
18.3%
보전관리지역 25
 
5.5%
제2종일반주거지역 24
 
5.3%
농림지역 24
 
5.3%
일반공업지역 9
 
2.0%
자연환경보전지역 3
 
0.7%
농업보호구역 3
 
0.7%
생산녹지지역 3
 
0.7%
Other values (13) 21
 
4.6%

허가면적
Real number (ℝ)

SKEWED 

Distinct362
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2276.932
Minimum0
Maximum387774
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-01-14T22:40:35.203601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile92.15
Q1405
median675
Q31194
95-th percentile6014.2
Maximum387774
Range387774
Interquartile range (IQR)789

Descriptive statistics

Standard deviation18825.989
Coefficient of variation (CV)8.2681383
Kurtosis415.5439
Mean2276.932
Median Absolute Deviation (MAD)327
Skewness20.253454
Sum972249.98
Variance3.5441787 × 108
MonotonicityNot monotonic
2024-01-14T22:40:35.375057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 9
 
2.1%
99.0 7
 
1.6%
367.0 5
 
1.2%
650.0 4
 
0.9%
661.0 4
 
0.9%
999.0 3
 
0.7%
330.0 3
 
0.7%
830.0 3
 
0.7%
92.0 3
 
0.7%
410.0 3
 
0.7%
Other values (352) 383
89.7%
ValueCountFrequency (%)
0.0 1
0.2%
7.0 1
0.2%
19.0 1
0.2%
23.0 1
0.2%
29.0 1
0.2%
40.0 2
0.5%
42.0 1
0.2%
49.0 1
0.2%
60.0 1
0.2%
66.0 1
0.2%
ValueCountFrequency (%)
387774.0 1
0.2%
17387.0 1
0.2%
16200.0 1
0.2%
10634.0 1
0.2%
9995.0 2
0.5%
9969.0 1
0.2%
9950.0 1
0.2%
9938.0 1
0.2%
9934.0 1
0.2%
9917.0 1
0.2%

용도
Text

MISSING 

Distinct197
Distinct (%)48.0%
Missing17
Missing (%)4.0%
Memory size3.5 KiB
2024-01-14T22:40:35.589449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length10.821951
Min length2

Characters and Unicode

Total characters4437
Distinct characters178
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)35.1%

Sample

1st row단독주택 신축 부지조성
2nd row공작물-태양광 건물 위(축사)
3rd row단독주택 신축 부지조성
4th row단독주택 신축 부지조성
5th row단독주택 신축 부지조성
ValueCountFrequency (%)
단독주택 151
15.0%
부지조성 104
 
10.3%
신축 95
 
9.4%
및 82
 
8.1%
진출입로 69
 
6.8%
조성 32
 
3.2%
위 31
 
3.1%
사무소 26
 
2.6%
부지 24
 
2.4%
태양광(건물 22
 
2.2%
Other values (172) 372
36.9%
2024-01-14T22:40:35.964238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
601
 
13.5%
주 185
 
4.2%
지 171
 
3.9%
택 168
 
3.8%
단 162
 
3.7%
독 162
 
3.7%
부 160
 
3.6%
조 152
 
3.4%
성 144
 
3.2%
축 133
 
3.0%
Other values (168) 2399
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3539
79.8%
Space Separator 601
 
13.5%
Open Punctuation 101
 
2.3%
Close Punctuation 101
 
2.3%
Decimal Number 59
 
1.3%
Other Punctuation 17
 
0.4%
Dash Punctuation 12
 
0.3%
Math Symbol 4
 
0.1%
Uppercase Letter 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 185
 
5.2%
지 171
 
4.8%
택 168
 
4.7%
단 162
 
4.6%
독 162
 
4.6%
부 160
 
4.5%
조 152
 
4.3%
성 144
 
4.1%
축 133
 
3.8%
설 109
 
3.1%
Other values (147) 1993
56.3%
Decimal Number
ValueCountFrequency (%)
1 23
39.0%
2 21
35.6%
3 4
 
6.8%
5 3
 
5.1%
0 2
 
3.4%
9 2
 
3.4%
4 1
 
1.7%
8 1
 
1.7%
7 1
 
1.7%
6 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
. 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
= 2
50.0%
> 2
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3540
79.8%
Common 895
 
20.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 185
 
5.2%
지 171
 
4.8%
택 168
 
4.7%
단 162
 
4.6%
독 162
 
4.6%
부 160
 
4.5%
조 152
 
4.3%
성 144
 
4.1%
축 133
 
3.8%
설 109
 
3.1%
Other values (148) 1994
56.3%
Common
ValueCountFrequency (%)
601
67.2%
( 101
 
11.3%
) 101
 
11.3%
1 23
 
2.6%
2 21
 
2.3%
, 16
 
1.8%
- 12
 
1.3%
3 4
 
0.4%
5 3
 
0.3%
0 2
 
0.2%
Other values (8) 11
 
1.2%
Latin
ValueCountFrequency (%)
P 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3539
79.8%
ASCII 897
 
20.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
601
67.0%
( 101
 
11.3%
) 101
 
11.3%
1 23
 
2.6%
2 21
 
2.3%
, 16
 
1.8%
- 12
 
1.3%
3 4
 
0.4%
5 3
 
0.3%
0 2
 
0.2%
Other values (10) 13
 
1.4%
Hangul
ValueCountFrequency (%)
주 185
 
5.2%
지 171
 
4.8%
택 168
 
4.7%
단 162
 
4.6%
독 162
 
4.6%
부 160
 
4.5%
조 152
 
4.3%
성 144
 
4.1%
축 133
 
3.8%
설 109
 
3.1%
Other values (147) 1993
56.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

허가일
Date

Distinct187
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2022-06-12 00:00:00
Maximum2023-12-11 00:00:00
2024-01-14T22:40:36.103282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:40:36.252784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일
Text

Distinct66
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-01-14T22:40:36.482211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.3114754
Min length2

Characters and Unicode

Total characters1841
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)11.7%

Sample

1st row진행중
2nd row진행중
3rd row진행중
4th row진행중
5th row진행중
ValueCountFrequency (%)
진행중 345
80.8%
2023-08-08 3
 
0.7%
2023-12-11 3
 
0.7%
2023-09-01 2
 
0.5%
2023-07-20 2
 
0.5%
2023-12-07 2
 
0.5%
2023-09-25 2
 
0.5%
2023-05-16 2
 
0.5%
2023-07-11 2
 
0.5%
2023-12-06 2
 
0.5%
Other values (56) 62
 
14.5%
2024-01-14T22:40:36.973232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 345
18.7%
행 345
18.7%
중 345
18.7%
2 196
10.6%
0 175
9.5%
- 156
8.5%
3 92
 
5.0%
1 82
 
4.5%
7 19
 
1.0%
8 18
 
1.0%
Other values (9) 68
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1039
56.4%
Decimal Number 640
34.8%
Dash Punctuation 156
 
8.5%
Other Punctuation 6
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 196
30.6%
0 175
27.3%
3 92
14.4%
1 82
12.8%
7 19
 
3.0%
8 18
 
2.8%
9 18
 
2.8%
6 17
 
2.7%
5 12
 
1.9%
4 11
 
1.7%
Other Letter
ValueCountFrequency (%)
진 345
33.2%
행 345
33.2%
중 345
33.2%
취 1
 
0.1%
하 1
 
0.1%
불 1
 
0.1%
허 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1039
56.4%
Common 802
43.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 196
24.4%
0 175
21.8%
- 156
19.5%
3 92
11.5%
1 82
10.2%
7 19
 
2.4%
8 18
 
2.2%
9 18
 
2.2%
6 17
 
2.1%
5 12
 
1.5%
Other values (2) 17
 
2.1%
Hangul
ValueCountFrequency (%)
진 345
33.2%
행 345
33.2%
중 345
33.2%
취 1
 
0.1%
하 1
 
0.1%
불 1
 
0.1%
허 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1039
56.4%
ASCII 802
43.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 345
33.2%
행 345
33.2%
중 345
33.2%
취 1
 
0.1%
하 1
 
0.1%
불 1
 
0.1%
허 1
 
0.1%
ASCII
ValueCountFrequency (%)
2 196
24.4%
0 175
21.8%
- 156
19.5%
3 92
11.5%
1 82
10.2%
7 19
 
2.4%
8 18
 
2.2%
9 18
 
2.2%
6 17
 
2.1%
5 12
 
1.5%
Other values (2) 17
 
2.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2023-12-29 00:00:00
Maximum2023-12-29 00:00:00
2024-01-14T22:40:37.126616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:40:37.220623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-14T22:40:30.173899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:40:37.311042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동리용도지역허가면적준공일
읍면동1.0000.9940.8860.0000.879
리0.9941.0000.9260.0000.000
용도지역0.8860.9261.0000.0000.285
허가면적0.0000.0000.0001.0000.000
준공일0.8790.0000.2850.0001.000
2024-01-14T22:40:37.409663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도지역읍면동
용도지역1.0000.387
읍면동0.3871.000
2024-01-14T22:40:37.509996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가면적읍면동용도지역
허가면적1.0000.0000.000
읍면동0.0001.0000.387
용도지역0.0000.3871.000

Missing values

2024-01-14T22:40:30.394277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:40:30.564995image/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.
2024-01-14T22:40:30.698745image/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

허가번호소재지읍면동리지목용도지역허가면적용도허가일준공일데이터기준일
02023-001충청북도 제천시 강제동 177-10, 177-30강제동<NA>177-10, 177-30자연녹지지역2277.0단독주택 신축 부지조성2023-01-05진행중2023-12-29
12023-002충청북도 제천시 봉양읍 원박리 234-1봉양읍원박리234-1농림지역720.0공작물-태양광 건물 위(축사)2023-01-05진행중2023-12-29
22023-003충청북도 제천시 백운면 방학리 274백운면방학리274계획관리지역535.0단독주택 신축 부지조성2023-01-02진행중2023-12-29
32023-004충청북도 제천시 백운면 방학리 276-1, 272-29백운면방학리276-1, 272-29계획관리지역90.0단독주택 신축 부지조성2023-01-02진행중2023-12-29
42023-005충청북도 제천시 백운면 방학리 274-2, 272-28백운면방학리274-2, 272-28계획관리지역131.0단독주택 신축 부지조성2023-01-02진행중2023-12-29
52023-006충청북도 제천시 백운면 원월리 160-19백운면원월리160-19생산관리지역419.0단독주택2023-01-04진행중2023-12-29
62023-007충청북도 제천시 청풍면 북진리 27, 27-4, 28청풍면북진리27, 27-4, 28계획관리지역750.0창고 증축2023-01-02진행중2023-12-29
72023-008충청북도 제천시 수산면 율지리 110-1수산면율지리110-1계획관리지역79.0다목적회관 진출입로2023-01-042023-01-102023-12-29
82023-009충청북도 제천시 봉양읍 삼거리 1230-6봉양읍삼거리1230-6보전관리지역40.0농업용창고 진출입로 부지조성2023-01-022023-03-022023-12-29
92023-010충청북도 제천시 봉양읍 공전리 849-1봉양읍공전리849-1계획관리지역330.0단독주택 신축 부지조성2023-01-06진행중2023-12-29
허가번호소재지읍면동리지목용도지역허가면적용도허가일준공일데이터기준일
4172023-418충청북도 제천시 송학면 도화리 925-57, 924-11, 925-56, 925-59송학면도화리925-57, 924-11, 925-56, 925-59자연녹지지역9934.0사무소 및 부속창고 부지조성2023-11-24진행중2023-12-29
4182023-419충청북도 제천시 고명동 503-55고명동<NA>503-55계획관리지역1712.0창고 부지 및 진출입로 조성2023-11-30진행중2023-12-29
4192023-420충청북도 제천시 송학면 도화리 721-5송학면도화리721-5계획관리지역500.0단독주택, 부속창고 부지조성2023-11-30진행중2023-12-29
4202023-421충청북도 제천시 수산면 수리 222수산면수리222계획관리지역929.0단독주택 신축 부지조성2023-12-01진행중2023-12-29
4212023-422충청북도 제천시 봉양읍 공전리 869봉양읍공전리869계획관리지역843.0단독주택 신축 및 진출입로 부지조성2023-12-04진행중2023-12-29
4222023-423충청북도 제천시 봉양읍 원박리 141, 141-4봉양읍원박리141, 141-4생산관리지역1562.0공작물-태양광2023-12-06진행중2023-12-29
4232023-424충청북도 제천시 동현동 107-18동현동<NA>107-18제2종일반주거지역171.0성토 및 보강토옹벽 설치2023-12-08진행중2023-12-29
4242023-425충청북도 제천시 두학동 1063, 1069두학동<NA>1063, 1069자연녹지지역588.68공작물-태양광2023-12-11진행중2023-12-29
4252023-426충청북도 제천시 명지동 136-18명지동<NA>136-18자연녹지지역82.91공작물-태양광2023-12-11진행중2023-12-29
4262023-427충청북도 제천시 강제동 산43-2, 산44-2, 589-4, 621-4강제동<NA>산43-2, 산44-2, 589-4, 621-4자연녹지지역9938.0사무소 및 진출입로2023-12-11진행중2023-12-29