Overview

Dataset statistics

Number of variables17
Number of observations133
Missing cells487
Missing cells (%)21.5%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory18.4 KiB
Average record size in memory142.0 B

Variable types

Categorical5
Text3
DateTime5
Numeric4

Dataset

Description경상남도 거제시 미준공신축건축물 현황으로 개인요청에 의한 1회성 자료이며 2018년부터 2023년 8월까지 미준공된 신축 건축물의 허가일, 연면적 등의 자료를 포함하고 있습니다
URLhttps://www.data.go.kr/data/15121716/fileData.do

Alerts

건축구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (0.8%) duplicate rowsDuplicates
최대지상층수 is highly overall correlated with 총주차대수 and 2 other fieldsHigh correlation
최대지하층수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
총주차대수 is highly overall correlated with 최대지상층수 and 4 other fieldsHigh correlation
세대수 is highly overall correlated with 최대지상층수 and 4 other fieldsHigh correlation
신고허가구분 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
주용도 is highly overall correlated with 총주차대수 and 1 other fieldsHigh correlation
부속용도 is highly overall correlated with 최대지상층수 and 4 other fieldsHigh correlation
가구수 is highly overall correlated with 총주차대수 and 1 other fieldsHigh correlation
가구수 is highly imbalanced (73.5%)Imbalance
착공처리일 has 76 (57.1%) missing valuesMissing
착공예정일 has 76 (57.1%) missing valuesMissing
준공예정일(사용승인예정일) has 75 (56.4%) missing valuesMissing
총주차대수 has 26 (19.5%) missing valuesMissing
세대수 has 125 (94.0%) missing valuesMissing
시공자사무소명 has 109 (82.0%) missing valuesMissing
최대지하층수 has 100 (75.2%) zerosZeros
총주차대수 has 8 (6.0%) zerosZeros

Reproduction

Analysis started2023-12-12 02:27:41.694080
Analysis finished2023-12-12 02:27:44.891791
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신고허가구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
허가
81 
신고
52 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
허가 81
60.9%
신고 52
39.1%

Length

2023-12-12T11:27:44.966327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:27:45.338888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
허가 81
60.9%
신고 52
39.1%

건축구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
신축
133 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 133
100.0%

Length

2023-12-12T11:27:45.447834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:27:45.532344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 133
100.0%

대지위치
Text

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T11:27:45.859738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length23.052632
Min length16

Characters and Unicode

Total characters3066
Distinct characters91
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

Unique129 ?
Unique (%)97.0%

Sample

1st row경상남도 거제시 수월동 133-2
2nd row경상남도 거제시 장목면 관포리 178 외1필지
3rd row경상남도 거제시 장목면 대금리 424-4
4th row경상남도 거제시 장목면 대금리 317-10
5th row경상남도 거제시 남부면 다대리 112-2
ValueCountFrequency (%)
경상남도 133
18.8%
거제시 133
18.8%
장목면 29
 
4.1%
외1필지 26
 
3.7%
산 22
 
3.1%
외2필지 15
 
2.1%
일운면 15
 
2.1%
고현동 13
 
1.8%
사등면 11
 
1.6%
남부면 9
 
1.3%
Other values (194) 303
42.7%
2023-12-12T11:27:46.415272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
576
18.8%
남 142
 
4.6%
1 141
 
4.6%
거 141
 
4.6%
제 141
 
4.6%
시 136
 
4.4%
상 136
 
4.4%
경 133
 
4.3%
도 133
 
4.3%
- 91
 
3.0%
Other values (81) 1296
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1828
59.6%
Space Separator 576
 
18.8%
Decimal Number 571
 
18.6%
Dash Punctuation 91
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 142
 
7.8%
거 141
 
7.7%
제 141
 
7.7%
시 136
 
7.4%
상 136
 
7.4%
경 133
 
7.3%
도 133
 
7.3%
면 88
 
4.8%
리 88
 
4.8%
외 74
 
4.0%
Other values (69) 616
33.7%
Decimal Number
ValueCountFrequency (%)
1 141
24.7%
2 84
14.7%
3 69
12.1%
5 47
 
8.2%
4 42
 
7.4%
6 40
 
7.0%
7 39
 
6.8%
9 38
 
6.7%
0 36
 
6.3%
8 35
 
6.1%
Space Separator
ValueCountFrequency (%)
576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1828
59.6%
Common 1238
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 142
 
7.8%
거 141
 
7.7%
제 141
 
7.7%
시 136
 
7.4%
상 136
 
7.4%
경 133
 
7.3%
도 133
 
7.3%
면 88
 
4.8%
리 88
 
4.8%
외 74
 
4.0%
Other values (69) 616
33.7%
Common
ValueCountFrequency (%)
576
46.5%
1 141
 
11.4%
- 91
 
7.4%
2 84
 
6.8%
3 69
 
5.6%
5 47
 
3.8%
4 42
 
3.4%
6 40
 
3.2%
7 39
 
3.2%
9 38
 
3.1%
Other values (2) 71
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1828
59.6%
ASCII 1238
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
576
46.5%
1 141
 
11.4%
- 91
 
7.4%
2 84
 
6.8%
3 69
 
5.6%
5 47
 
3.8%
4 42
 
3.4%
6 40
 
3.2%
7 39
 
3.2%
9 38
 
3.1%
Other values (2) 71
 
5.7%
Hangul
ValueCountFrequency (%)
남 142
 
7.8%
거 141
 
7.7%
제 141
 
7.7%
시 136
 
7.4%
상 136
 
7.4%
경 133
 
7.3%
도 133
 
7.3%
면 88
 
4.8%
리 88
 
4.8%
외 74
 
4.0%
Other values (69) 616
33.7%

연면적(제곱미터)
Text

Distinct132
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T11:27:46.727510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.7293233
Min length2

Characters and Unicode

Total characters762
Distinct characters12
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

Unique131 ?
Unique (%)98.5%

Sample

1st row74.4
2nd row120.46
3rd row100.04
4th row164.91
5th row56.2
ValueCountFrequency (%)
60 2
 
1.5%
2,111.13 1
 
0.8%
521.75 1
 
0.8%
103.46 1
 
0.8%
497.75 1
 
0.8%
297.66 1
 
0.8%
198.88 1
 
0.8%
3,750.62 1
 
0.8%
943.07 1
 
0.8%
451.4 1
 
0.8%
Other values (122) 122
91.7%
2023-12-12T11:27:47.202483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 116
15.2%
9 74
9.7%
1 71
9.3%
6 68
8.9%
3 68
8.9%
5 66
8.7%
2 62
8.1%
8 61
8.0%
4 59
7.7%
7 53
7.0%
Other values (2) 64
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 621
81.5%
Other Punctuation 141
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 74
11.9%
1 71
11.4%
6 68
11.0%
3 68
11.0%
5 66
10.6%
2 62
10.0%
8 61
9.8%
4 59
9.5%
7 53
8.5%
0 39
6.3%
Other Punctuation
ValueCountFrequency (%)
. 116
82.3%
, 25
 
17.7%

Most occurring scripts

ValueCountFrequency (%)
Common 762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 116
15.2%
9 74
9.7%
1 71
9.3%
6 68
8.9%
3 68
8.9%
5 66
8.7%
2 62
8.1%
8 61
8.0%
4 59
7.7%
7 53
7.0%
Other values (2) 64
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 116
15.2%
9 74
9.7%
1 71
9.3%
6 68
8.9%
3 68
8.9%
5 66
8.7%
2 62
8.1%
8 61
8.0%
4 59
7.7%
7 53
7.0%
Other values (2) 64
8.4%

허가일
Date

Distinct122
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-01-25 00:00:00
Maximum2023-08-23 00:00:00
2023-12-12T11:27:47.344996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:47.475889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct53
Distinct (%)93.0%
Missing76
Missing (%)57.1%
Memory size1.2 KiB
Minimum2018-05-01 00:00:00
Maximum2023-08-29 00:00:00
2023-12-12T11:27:47.601151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:47.730758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공예정일
Date

MISSING 

Distinct53
Distinct (%)93.0%
Missing76
Missing (%)57.1%
Memory size1.2 KiB
Minimum2018-04-30 00:00:00
Maximum2023-09-01 00:00:00
2023-12-12T11:27:47.881769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:48.036935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공예정일(사용승인예정일)
Date

MISSING 

Distinct52
Distinct (%)89.7%
Missing75
Missing (%)56.4%
Memory size1.2 KiB
Minimum2018-05-30 00:00:00
Maximum2024-06-30 00:00:00
2023-12-12T11:27:48.185070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:48.357353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3458647
Minimum0
Maximum42
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T11:27:48.523885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile12.6
Maximum42
Range42
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.4495553
Coefficient of variation (CV)1.6287435
Kurtosis23.435528
Mean3.3458647
Median Absolute Deviation (MAD)1
Skewness4.5056206
Sum445
Variance29.697653
MonotonicityNot monotonic
2023-12-12T11:27:48.664503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 51
38.3%
2 34
25.6%
3 18
 
13.5%
4 14
 
10.5%
5 6
 
4.5%
20 2
 
1.5%
24 2
 
1.5%
0 1
 
0.8%
18 1
 
0.8%
42 1
 
0.8%
Other values (3) 3
 
2.3%
ValueCountFrequency (%)
0 1
 
0.8%
1 51
38.3%
2 34
25.6%
3 18
 
13.5%
4 14
 
10.5%
5 6
 
4.5%
6 1
 
0.8%
9 1
 
0.8%
18 1
 
0.8%
20 2
 
1.5%
ValueCountFrequency (%)
42 1
 
0.8%
24 2
 
1.5%
23 1
 
0.8%
20 2
 
1.5%
18 1
 
0.8%
9 1
 
0.8%
6 1
 
0.8%
5 6
 
4.5%
4 14
10.5%
3 18
13.5%

최대지하층수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.39849624
Minimum0
Maximum5
Zeros100
Zeros (%)75.2%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T11:27:48.778872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.91237162
Coefficient of variation (CV)2.2895363
Kurtosis11.929495
Mean0.39849624
Median Absolute Deviation (MAD)0
Skewness3.2531096
Sum53
Variance0.83242196
MonotonicityNot monotonic
2023-12-12T11:27:48.895000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 100
75.2%
1 24
 
18.0%
2 4
 
3.0%
4 2
 
1.5%
5 2
 
1.5%
3 1
 
0.8%
ValueCountFrequency (%)
0 100
75.2%
1 24
 
18.0%
2 4
 
3.0%
3 1
 
0.8%
4 2
 
1.5%
5 2
 
1.5%
ValueCountFrequency (%)
5 2
 
1.5%
4 2
 
1.5%
3 1
 
0.8%
2 4
 
3.0%
1 24
 
18.0%
0 100
75.2%

주용도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
제2종근린생활시설
105 
숙박시설
14 
운동시설
 
7
공동주택
 
7

Length

Max length9
Median length9
Mean length7.9473684
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제2종근린생활시설
2nd row제2종근린생활시설
3rd row제2종근린생활시설
4th row제2종근린생활시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 105
78.9%
숙박시설 14
 
10.5%
운동시설 7
 
5.3%
공동주택 7
 
5.3%

Length

2023-12-12T11:27:49.064152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:27:49.208452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종근린생활시설 105
78.9%
숙박시설 14
 
10.5%
운동시설 7
 
5.3%
공동주택 7
 
5.3%

부속용도
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
40 
사무소
20 
일반음식점
17 
제조업소
7 
휴게음식점
 
4
Other values (38)
45 

Length

Max length26
Median length22
Mean length5.5112782
Min length2

Unique

Unique33 ?
Unique (%)24.8%

Sample

1st row<NA>
2nd row사무소
3rd row일반음식점
4th row(일반음식점)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 40
30.1%
사무소 20
15.0%
일반음식점 17
12.8%
제조업소 7
 
5.3%
휴게음식점 4
 
3.0%
생활숙박시설 3
 
2.3%
외1 3
 
2.3%
관리실및화장실 2
 
1.5%
단독주택 2
 
1.5%
제2종근린생활시설(사무소) 2
 
1.5%
Other values (33) 33
24.8%

Length

2023-12-12T11:27:49.372472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 40
27.6%
사무소 23
15.9%
일반음식점 20
13.8%
제조업소 8
 
5.5%
단독주택 5
 
3.4%
휴게음식점 4
 
2.8%
생활숙박시설 3
 
2.1%
외1 3
 
2.1%
관리실및화장실 2
 
1.4%
제2종근린생활시설(사무소 2
 
1.4%
Other values (32) 35
24.1%

총주차대수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)35.5%
Missing26
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean33.28972
Minimum0
Maximum434
Zeros8
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T11:27:49.511576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q320
95-th percentile214.2
Maximum434
Range434
Interquartile range (IQR)18

Descriptive statistics

Standard deviation82.825688
Coefficient of variation (CV)2.488026
Kurtosis13.554636
Mean33.28972
Median Absolute Deviation (MAD)4
Skewness3.6676359
Sum3562
Variance6860.0945
MonotonicityNot monotonic
2023-12-12T11:27:49.669298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
2 13
 
9.8%
1 10
 
7.5%
3 10
 
7.5%
0 8
 
6.0%
4 7
 
5.3%
5 6
 
4.5%
8 5
 
3.8%
7 5
 
3.8%
6 4
 
3.0%
22 3
 
2.3%
Other values (28) 36
27.1%
(Missing) 26
19.5%
ValueCountFrequency (%)
0 8
6.0%
1 10
7.5%
2 13
9.8%
3 10
7.5%
4 7
5.3%
5 6
4.5%
6 4
 
3.0%
7 5
 
3.8%
8 5
 
3.8%
9 2
 
1.5%
ValueCountFrequency (%)
434 1
0.8%
420 1
0.8%
418 1
0.8%
277 1
0.8%
256 1
0.8%
231 1
0.8%
175 1
0.8%
168 1
0.8%
124 1
0.8%
98 1
0.8%

세대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)100.0%
Missing125
Missing (%)94.0%
Infinite0
Infinite (%)0.0%
Mean104
Minimum1
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T11:27:49.780895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q112.75
median41.5
Q3210
95-th percentile268.7
Maximum289
Range288
Interquartile range (IQR)197.25

Descriptive statistics

Standard deviation116.91633
Coefficient of variation (CV)1.1241955
Kurtosis-1.5614961
Mean104
Median Absolute Deviation (MAD)35
Skewness0.73520512
Sum832
Variance13669.429
MonotonicityNot monotonic
2023-12-12T11:27:49.887554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
55 1
 
0.8%
289 1
 
0.8%
231 1
 
0.8%
203 1
 
0.8%
12 1
 
0.8%
13 1
 
0.8%
28 1
 
0.8%
1 1
 
0.8%
(Missing) 125
94.0%
ValueCountFrequency (%)
1 1
0.8%
12 1
0.8%
13 1
0.8%
28 1
0.8%
55 1
0.8%
203 1
0.8%
231 1
0.8%
289 1
0.8%
ValueCountFrequency (%)
289 1
0.8%
231 1
0.8%
203 1
0.8%
55 1
0.8%
28 1
0.8%
13 1
0.8%
12 1
0.8%
1 1
0.8%

가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
118 
1
 
10
8
 
2
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.6616541
Min length1

Unique

Unique3 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 118
88.7%
1 10
 
7.5%
8 2
 
1.5%
3 1
 
0.8%
2 1
 
0.8%
4 1
 
0.8%

Length

2023-12-12T11:27:50.026362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:27:50.165437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 118
88.7%
1 10
 
7.5%
8 2
 
1.5%
3 1
 
0.8%
2 1
 
0.8%
4 1
 
0.8%

시공자사무소명
Text

MISSING 

Distinct23
Distinct (%)95.8%
Missing109
Missing (%)82.0%
Memory size1.2 KiB
2023-12-12T11:27:50.390967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.8333333
Min length7

Characters and Unicode

Total characters212
Distinct characters53
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

Unique22 ?
Unique (%)91.7%

Sample

1st row거기건설주식회사
2nd row(주)삼양건설
3rd row삼원종합건설(주)
4th row주식회사 삼양건설
5th row주식회사준종합건설
ValueCountFrequency (%)
삼원종합건설(주 2
 
7.7%
주)거영종합건설 1
 
3.8%
주)비앤비건설 1
 
3.8%
주)성림건설 1
 
3.8%
기산종합건설(주 1
 
3.8%
주)삼강종합건설 1
 
3.8%
건우종합건설(주 1
 
3.8%
다원산업개발(주 1
 
3.8%
주)동산이엔씨 1
 
3.8%
성진종합건설(주 1
 
3.8%
Other values (15) 15
57.7%
2023-12-12T11:27:50.777623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 24
 
11.3%
건 21
 
9.9%
설 20
 
9.4%
( 20
 
9.4%
) 20
 
9.4%
종 13
 
6.1%
합 13
 
6.1%
삼 5
 
2.4%
산 5
 
2.4%
이 4
 
1.9%
Other values (43) 67
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
80.2%
Open Punctuation 20
 
9.4%
Close Punctuation 20
 
9.4%
Space Separator 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
14.1%
건 21
 
12.4%
설 20
 
11.8%
종 13
 
7.6%
합 13
 
7.6%
삼 5
 
2.9%
산 5
 
2.9%
이 4
 
2.4%
식 4
 
2.4%
회 4
 
2.4%
Other values (40) 57
33.5%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
80.2%
Common 42
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
14.1%
건 21
 
12.4%
설 20
 
11.8%
종 13
 
7.6%
합 13
 
7.6%
삼 5
 
2.9%
산 5
 
2.9%
이 4
 
2.4%
식 4
 
2.4%
회 4
 
2.4%
Other values (40) 57
33.5%
Common
ValueCountFrequency (%)
( 20
47.6%
) 20
47.6%
2
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
80.2%
ASCII 42
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 24
14.1%
건 21
 
12.4%
설 20
 
11.8%
종 13
 
7.6%
합 13
 
7.6%
삼 5
 
2.9%
산 5
 
2.9%
이 4
 
2.4%
식 4
 
2.4%
회 4
 
2.4%
Other values (40) 57
33.5%
ASCII
ValueCountFrequency (%)
( 20
47.6%
) 20
47.6%
2
 
4.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2023-12-12T11:27:50.912431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:51.032775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T11:27:43.790646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:42.562903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:42.992810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.373766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.891778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:42.685991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.084059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.471576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.999702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:42.789526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.182975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.588025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:44.088573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:42.880630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.271708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:27:43.692074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:27:51.139174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고허가구분착공처리일착공예정일준공예정일(사용승인예정일)최대지상층수최대지하층수주용도부속용도총주차대수세대수가구수시공자사무소명
신고허가구분1.0001.0000.8730.6960.2970.3070.4200.4940.000NaN0.6490.000
착공처리일1.0001.0000.9720.8770.0000.0000.0000.9590.000NaN1.0000.971
착공예정일0.8730.9721.0000.9400.0000.0000.6691.0001.000NaN1.0000.986
준공예정일(사용승인예정일)0.6960.8770.9401.0001.0000.9461.0000.0001.000NaN0.0000.986
최대지상층수0.2970.0000.0001.0001.0000.9560.6220.9930.7540.9890.0000.000
최대지하층수0.3070.0000.0000.9460.9561.0000.5960.9560.7940.9720.0001.000
주용도0.4200.0000.6691.0000.6220.5961.0001.0000.9370.0000.0000.875
부속용도0.4940.9591.0000.0000.9930.9561.0001.0000.9751.0000.0001.000
총주차대수0.0000.0001.0001.0000.7540.7940.9370.9751.0000.676NaN1.000
세대수NaNNaNNaNNaN0.9890.9720.0001.0000.6761.000NaNNaN
가구수0.6491.0001.0000.0000.0000.0000.0000.000NaNNaN1.0001.000
시공자사무소명0.0000.9710.9860.9860.0001.0000.8751.0001.000NaN1.0001.000
2023-12-12T11:27:51.325108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도부속용도신고허가구분가구수
주용도1.0000.7570.2800.000
부속용도0.7571.0000.2890.000
신고허가구분0.2800.2891.0000.677
가구수0.0000.0000.6771.000
2023-12-12T11:27:51.460697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최대지상층수최대지하층수총주차대수세대수신고허가구분주용도부속용도가구수
최대지상층수1.0000.3890.6380.6750.2100.4480.6790.000
최대지하층수0.3891.0000.4890.8050.2170.4240.5700.000
총주차대수0.6380.4891.0000.9760.0000.6610.6371.000
세대수0.6750.8050.9761.0001.0000.0001.0000.000
신고허가구분0.2100.2170.0001.0001.0000.2800.2890.677
주용도0.4480.4240.6610.0000.2801.0000.7570.000
부속용도0.6790.5700.6371.0000.2890.7571.0000.000
가구수0.0000.0001.0000.0000.6770.0000.0001.000

Missing values

2023-12-12T11:27:44.298953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:27:44.578593image/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.
2023-12-12T11:27:44.779931image/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

신고허가구분건축구분대지위치연면적(제곱미터)허가일착공처리일착공예정일준공예정일(사용승인예정일)최대지상층수최대지하층수주용도부속용도총주차대수세대수가구수시공자사무소명데이터기준일자
0신고신축경상남도 거제시 수월동 133-274.42023-08-22<NA><NA><NA>10제2종근린생활시설<NA>0<NA><NA><NA>2023-08-31
1신고신축경상남도 거제시 장목면 관포리 178 외1필지120.462023-08-01<NA><NA><NA>11제2종근린생활시설사무소2<NA><NA><NA>2023-08-31
2신고신축경상남도 거제시 장목면 대금리 424-4100.042023-07-20<NA><NA><NA>10제2종근린생활시설일반음식점0<NA><NA><NA>2023-08-31
3신고신축경상남도 거제시 장목면 대금리 317-10164.912023-06-272023-07-092023-07-122023-09-3010제2종근린생활시설(일반음식점)1<NA><NA><NA>2023-08-31
4신고신축경상남도 거제시 남부면 다대리 112-256.22023-06-22<NA><NA><NA>10제2종근린생활시설<NA>0<NA><NA><NA>2023-08-31
5신고신축경상남도 거제시 고현동 521-131.912023-06-20<NA><NA><NA>10제2종근린생활시설사무소0<NA><NA><NA>2023-08-31
6신고신축경상남도 거제시 장목면 율천리 1-1 외3필지386.52023-05-162023-05-222023-05-302023-08-1110제2종근린생활시설일반음식점3<NA><NA><NA>2023-08-31
7신고신축경상남도 거제시 장목면 외포리 457-1 외1필지148.08262023-04-28<NA><NA><NA>12제2종근린생활시설사진관1<NA><NA><NA>2023-08-31
8신고신축경상남도 거제시 장목면 관포리 128-268.822023-01-27<NA><NA><NA>01제2종근린생활시설사무소0<NA><NA><NA>2023-08-31
9신고신축경상남도 거제시 장평동 371-635.642023-01-202023-03-222023-03-212023-06-2020제2종근린생활시설일반음식점0<NA><NA><NA>2023-08-31
신고허가구분건축구분대지위치연면적(제곱미터)허가일착공처리일착공예정일준공예정일(사용승인예정일)최대지상층수최대지하층수주용도부속용도총주차대수세대수가구수시공자사무소명데이터기준일자
123허가신축경상남도 거제시 고현동 21 외2필지225.152018-09-192019-01-252019-01-262019-12-3120제2종근린생활시설일반음식점2<NA><NA><NA>2023-08-31
124허가신축경상남도 거제시 상동동 861-1444.182018-09-19<NA><NA><NA>30제2종근린생활시설사무소4<NA><NA><NA>2023-08-31
125허가신축경상남도 거제시 고현동 160-1316.952018-08-03<NA><NA><NA>40제2종근린생활시설사무소21<NA><NA>2023-08-31
126허가신축경상남도 거제시 장목면 농소리 산 71,085.182018-08-012023-03-152023-03-062024-02-2941제2종근린생활시설외 117<NA><NA>(주)성림건설2023-08-31
127허가신축경상남도 거제시 장승포동 562-1 외2필지499.622018-07-16<NA><NA><NA>40제2종근린생활시설<NA>4<NA><NA><NA>2023-08-31
128허가신축경상남도 거제시 하청면 하청리 675-5 외1필지299.812018-06-12<NA><NA><NA>40제2종근린생활시설외15<NA>4<NA>2023-08-31
129허가신축경상남도 거제시 장목면 관포리 122-8 외2필지2,482.252018-05-31<NA><NA><NA>42숙박시설생활숙박시설22<NA><NA><NA>2023-08-31
130허가신축경상남도 거제시 고현동 820-1 외4필지19,533.722018-04-272022-04-052021-11-012024-05-30205숙박시설생활숙박시설,제1,2종근린생활시설175<NA><NA>나경종합건설(주)2023-08-31
131허가신축경상남도 거제시 연초면 연사리 97 외1필지494.062018-04-26<NA><NA><NA>30제2종근린생활시설단독주택10<NA>1<NA>2023-08-31
132허가신축경상남도 거제시 장평동 169643.52018-03-30<NA><NA><NA>50제2종근린생활시설<NA>8<NA>1<NA>2023-08-31

Duplicate rows

Most frequently occurring

신고허가구분건축구분대지위치연면적(제곱미터)허가일착공처리일착공예정일준공예정일(사용승인예정일)최대지상층수최대지하층수주용도부속용도총주차대수세대수가구수시공자사무소명데이터기준일자# duplicates
0신고신축경상남도 거제시 사등면 창호리 790602022-06-09<NA><NA><NA>10제2종근린생활시설사무소1<NA><NA><NA>2023-08-312