Overview

Dataset statistics

Number of variables28
Number of observations10000
Missing cells29035
Missing cells (%)10.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 MiB
Average record size in memory245.0 B

Variable types

Numeric11
Categorical8
Text7
DateTime2

Dataset

Description전라북도 군산시 관내 지번별 단독주택 현황(대지위치,건축물용도,층수,연면적,가구수,건물명,건축년도,사용승인일,도로명주소등)
Author전라북도 군산시
URLhttps://www.data.go.kr/data/15085947/fileData.do

Alerts

대장_종류_0 has constant value ""Constant
시군구_명_0 has constant value ""Constant
주_용도_0 has constant value ""Constant
대지_구분_0 is highly imbalanced (96.9%)Imbalance
세대_수_0 is highly imbalanced (66.8%)Imbalance
지하_층_수_0 is highly imbalanced (62.8%)Imbalance
건물명_0 has 9910 (99.1%) missing valuesMissing
동명칭_0 has 9514 (95.1%) missing valuesMissing
대지_면적_0 has 255 (2.5%) missing valuesMissing
가구_수_0 has 411 (4.1%) missing valuesMissing
허가_일_0 has 5199 (52.0%) missing valuesMissing
도로명주소_도로_명_0 has 1075 (10.8%) missing valuesMissing
도로명주소_본번_0 has 980 (9.8%) missing valuesMissing
도로명주소_부번_0 has 1650 (16.5%) missing valuesMissing
대지_면적_0 is highly skewed (γ1 = 59.26936944)Skewed
순번 has unique valuesUnique
부번_0 has 1622 (16.2%) zerosZeros
외필지수_0 has 9404 (94.0%) zerosZeros
대지_면적_0 has 5768 (57.7%) zerosZeros
건축_면적_0 has 206 (2.1%) zerosZeros
가구_수_0 has 513 (5.1%) zerosZeros
도로명주소_부번_0 has 3700 (37.0%) zerosZeros

Reproduction

Analysis started2023-12-12 03:33:35.258423
Analysis finished2023-12-12 03:33:36.700767
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12990.926
Minimum5
Maximum25897
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:36.768892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile1251.95
Q16363.5
median13036.5
Q319528.25
95-th percentile24616.05
Maximum25897
Range25892
Interquartile range (IQR)13164.75

Descriptive statistics

Standard deviation7514.2938
Coefficient of variation (CV)0.57842632
Kurtosis-1.2151849
Mean12990.926
Median Absolute Deviation (MAD)6577.5
Skewness-0.018035255
Sum1.2990926 × 108
Variance56464611
MonotonicityNot monotonic
2023-12-12T12:33:36.907291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4410 1
 
< 0.1%
7058 1
 
< 0.1%
9317 1
 
< 0.1%
25602 1
 
< 0.1%
5912 1
 
< 0.1%
14063 1
 
< 0.1%
7836 1
 
< 0.1%
10668 1
 
< 0.1%
2752 1
 
< 0.1%
18096 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
24 1
< 0.1%
25 1
< 0.1%
27 1
< 0.1%
ValueCountFrequency (%)
25897 1
< 0.1%
25893 1
< 0.1%
25892 1
< 0.1%
25889 1
< 0.1%
25888 1
< 0.1%
25887 1
< 0.1%
25886 1
< 0.1%
25885 1
< 0.1%
25882 1
< 0.1%
25881 1
< 0.1%

대장_종류_0
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반건축물
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반건축물 10000
100.0%

Length

2023-12-12T12:33:37.023455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:37.125825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 10000
100.0%

시군구_명_0
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전라북도 군산시
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라북도 군산시
2nd row전라북도 군산시
3rd row전라북도 군산시
4th row전라북도 군산시
5th row전라북도 군산시

Common Values

ValueCountFrequency (%)
전라북도 군산시 10000
100.0%

Length

2023-12-12T12:33:37.257958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:37.347466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 10000
50.0%
군산시 10000
50.0%

법정동_명_0
Text

Distinct128
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:33:37.664558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.6577
Min length2

Characters and Unicode

Total characters46577
Distinct characters115
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row조촌동
2nd row구암동
3rd row명산동
4th row개정면 운회리
5th row임피면 축산리
ValueCountFrequency (%)
대야면 542
 
3.9%
경암동 424
 
3.0%
개정면 410
 
2.9%
조촌동 399
 
2.9%
옥구읍 398
 
2.8%
수송동 397
 
2.8%
산북동 383
 
2.7%
옥산면 383
 
2.7%
임피면 364
 
2.6%
성산면 358
 
2.6%
Other values (129) 9907
70.9%
2023-12-12T12:33:38.156744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 6237
 
13.4%
리 3975
 
8.5%
3965
 
8.5%
면 3567
 
7.7%
산 1808
 
3.9%
옥 1737
 
3.7%
서 1065
 
2.3%
수 930
 
2.0%
경 726
 
1.6%
정 706
 
1.5%
Other values (105) 21861
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42529
91.3%
Space Separator 3965
 
8.5%
Decimal Number 83
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6237
 
14.7%
리 3975
 
9.3%
면 3567
 
8.4%
산 1808
 
4.3%
옥 1737
 
4.1%
서 1065
 
2.5%
수 930
 
2.2%
경 726
 
1.7%
정 706
 
1.7%
암 701
 
1.6%
Other values (101) 21077
49.6%
Decimal Number
ValueCountFrequency (%)
2 38
45.8%
1 27
32.5%
3 18
21.7%
Space Separator
ValueCountFrequency (%)
3965
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42529
91.3%
Common 4048
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6237
 
14.7%
리 3975
 
9.3%
면 3567
 
8.4%
산 1808
 
4.3%
옥 1737
 
4.1%
서 1065
 
2.5%
수 930
 
2.2%
경 726
 
1.7%
정 706
 
1.7%
암 701
 
1.6%
Other values (101) 21077
49.6%
Common
ValueCountFrequency (%)
3965
97.9%
2 38
 
0.9%
1 27
 
0.7%
3 18
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42529
91.3%
ASCII 4048
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 6237
 
14.7%
리 3975
 
9.3%
면 3567
 
8.4%
산 1808
 
4.3%
옥 1737
 
4.1%
서 1065
 
2.5%
수 930
 
2.2%
경 726
 
1.7%
정 706
 
1.7%
암 701
 
1.6%
Other values (101) 21077
49.6%
ASCII
ValueCountFrequency (%)
3965
97.9%
2 38
 
0.9%
1 27
 
0.7%
3 18
 
0.4%

대지_구분_0
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대지
9968 
산
 
32

Length

Max length2
Median length2
Mean length1.9968
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대지 9968
99.7%
산 32
 
0.3%

Length

2023-12-12T12:33:38.343615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:38.466804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대지 9968
99.7%
산 32
 
0.3%

본번_0
Real number (ℝ)

Distinct1367
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean556.2238
Minimum1
Maximum3642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:38.597379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q1202
median485
Q3784
95-th percentile1358
Maximum3642
Range3641
Interquartile range (IQR)582

Descriptive statistics

Standard deviation529.93175
Coefficient of variation (CV)0.95273116
Kurtosis12.075855
Mean556.2238
Median Absolute Deviation (MAD)291
Skewness2.8192043
Sum5562238
Variance280827.65
MonotonicityNot monotonic
2023-12-12T12:33:38.765948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 81
 
0.8%
73 44
 
0.4%
77 44
 
0.4%
14 44
 
0.4%
15 42
 
0.4%
1249 41
 
0.4%
479 41
 
0.4%
13 40
 
0.4%
609 40
 
0.4%
273 39
 
0.4%
Other values (1357) 9544
95.4%
ValueCountFrequency (%)
1 36
0.4%
2 33
0.3%
3 33
0.3%
4 24
0.2%
5 33
0.3%
6 31
0.3%
7 27
0.3%
8 34
0.3%
9 33
0.3%
10 26
0.3%
ValueCountFrequency (%)
3642 1
 
< 0.1%
3638 4
< 0.1%
3636 3
< 0.1%
3627 1
 
< 0.1%
3622 2
< 0.1%
3621 2
< 0.1%
3620 2
< 0.1%
3618 2
< 0.1%
3617 2
< 0.1%
3616 3
< 0.1%

부번_0
Real number (ℝ)

ZEROS 

Distinct236
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.7551
Minimum0
Maximum891
Zeros1622
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:38.910891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q315
95-th percentile62.05
Maximum891
Range891
Interquartile range (IQR)14

Descriptive statistics

Standard deviation39.77705
Coefficient of variation (CV)2.5247095
Kurtosis125.58728
Mean15.7551
Median Absolute Deviation (MAD)5
Skewness9.1240125
Sum157551
Variance1582.2137
MonotonicityNot monotonic
2023-12-12T12:33:39.099288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1622
16.2%
1 1358
 
13.6%
2 714
 
7.1%
3 611
 
6.1%
4 471
 
4.7%
5 407
 
4.1%
6 355
 
3.5%
7 312
 
3.1%
8 302
 
3.0%
9 243
 
2.4%
Other values (226) 3605
36.0%
ValueCountFrequency (%)
0 1622
16.2%
1 1358
13.6%
2 714
7.1%
3 611
 
6.1%
4 471
 
4.7%
5 407
 
4.1%
6 355
 
3.5%
7 312
 
3.1%
8 302
 
3.0%
9 243
 
2.4%
ValueCountFrequency (%)
891 1
< 0.1%
694 1
< 0.1%
691 1
< 0.1%
689 2
< 0.1%
687 1
< 0.1%
684 1
< 0.1%
668 1
< 0.1%
667 1
< 0.1%
666 1
< 0.1%
657 1
< 0.1%

외필지수_0
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0722
Minimum0
Maximum6
Zeros9404
Zeros (%)94.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:39.245432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.31463798
Coefficient of variation (CV)4.3578668
Kurtosis44.059002
Mean0.0722
Median Absolute Deviation (MAD)0
Skewness5.6258591
Sum722
Variance0.09899706
MonotonicityNot monotonic
2023-12-12T12:33:39.365553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9404
94.0%
1 494
 
4.9%
2 85
 
0.9%
3 12
 
0.1%
4 4
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 9404
94.0%
1 494
 
4.9%
2 85
 
0.9%
3 12
 
0.1%
4 4
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 4
 
< 0.1%
3 12
 
0.1%
2 85
 
0.9%
1 494
 
4.9%
0 9404
94.0%

건물명_0
Text

MISSING 

Distinct53
Distinct (%)58.9%
Missing9910
Missing (%)99.1%
Memory size156.2 KiB
2023-12-12T12:33:39.676895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length4.0555556
Min length1

Characters and Unicode

Total characters365
Distinct characters131
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

Unique44 ?
Unique (%)48.9%

Sample

1st row나동
2nd row1동
3rd row대호주택
4th row3동
5th row전주보호관찰소군산지소직원합숙소
ValueCountFrequency (%)
1동 17
 
18.1%
2동 11
 
11.7%
대호주택 6
 
6.4%
단독주택 3
 
3.2%
a 2
 
2.1%
제1호 2
 
2.1%
2
 
2.1%
군산장애인복지회주택 2
 
2.1%
나동 2
 
2.1%
최산호 1
 
1.1%
Other values (46) 46
48.9%
2023-12-12T12:33:40.097024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 37
 
10.1%
1 24
 
6.6%
주 16
 
4.4%
2 14
 
3.8%
택 13
 
3.6%
호 11
 
3.0%
빌 10
 
2.7%
산 9
 
2.5%
회 9
 
2.5%
대 8
 
2.2%
Other values (121) 214
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
83.0%
Decimal Number 41
 
11.2%
Space Separator 6
 
1.6%
Uppercase Letter 4
 
1.1%
Close Punctuation 3
 
0.8%
Open Punctuation 3
 
0.8%
Other Punctuation 3
 
0.8%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
12.2%
주 16
 
5.3%
택 13
 
4.3%
호 11
 
3.6%
빌 10
 
3.3%
산 9
 
3.0%
회 9
 
3.0%
대 8
 
2.6%
교 7
 
2.3%
성 6
 
2.0%
Other values (108) 177
58.4%
Decimal Number
ValueCountFrequency (%)
1 24
58.5%
2 14
34.1%
7 1
 
2.4%
9 1
 
2.4%
3 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
83.0%
Common 58
 
15.9%
Latin 4
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
12.2%
주 16
 
5.3%
택 13
 
4.3%
호 11
 
3.6%
빌 10
 
3.3%
산 9
 
3.0%
회 9
 
3.0%
대 8
 
2.6%
교 7
 
2.3%
성 6
 
2.0%
Other values (108) 177
58.4%
Common
ValueCountFrequency (%)
1 24
41.4%
2 14
24.1%
6
 
10.3%
) 3
 
5.2%
( 3
 
5.2%
. 2
 
3.4%
- 2
 
3.4%
7 1
 
1.7%
9 1
 
1.7%
, 1
 
1.7%
Latin
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
83.0%
ASCII 62
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 37
 
12.2%
주 16
 
5.3%
택 13
 
4.3%
호 11
 
3.6%
빌 10
 
3.3%
산 9
 
3.0%
회 9
 
3.0%
대 8
 
2.6%
교 7
 
2.3%
성 6
 
2.0%
Other values (108) 177
58.4%
ASCII
ValueCountFrequency (%)
1 24
38.7%
2 14
22.6%
6
 
9.7%
) 3
 
4.8%
( 3
 
4.8%
A 3
 
4.8%
. 2
 
3.2%
- 2
 
3.2%
7 1
 
1.6%
9 1
 
1.6%
Other values (3) 3
 
4.8%

동명칭_0
Text

MISSING 

Distinct54
Distinct (%)11.1%
Missing9514
Missing (%)95.1%
Memory size156.2 KiB
2023-12-12T12:33:40.337614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.6707819
Min length1

Characters and Unicode

Total characters1298
Distinct characters42
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

Unique27 ?
Unique (%)5.6%

Sample

1st row2동
2nd row1동
3rd row1동
4th row제1동
5th row1동
ValueCountFrequency (%)
1동 150
30.9%
2동 73
15.1%
제1호 30
 
6.2%
주건축물제1동 28
 
5.8%
부속1동 28
 
5.8%
1 27
 
5.6%
제2호 24
 
4.9%
제1동 20
 
4.1%
1호 12
 
2.5%
부1동 9
 
1.9%
Other values (42) 84
17.3%
2023-12-12T12:33:40.776492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 360
27.7%
1 315
24.3%
2 118
 
9.1%
제 114
 
8.8%
호 82
 
6.3%
부 54
 
4.2%
속 40
 
3.1%
건 32
 
2.5%
축 31
 
2.4%
물 31
 
2.4%
Other values (32) 121
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 803
61.9%
Decimal Number 478
36.8%
Uppercase Letter 6
 
0.5%
Dash Punctuation 4
 
0.3%
Other Punctuation 3
 
0.2%
Space Separator 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 360
44.8%
제 114
 
14.2%
호 82
 
10.2%
부 54
 
6.7%
속 40
 
5.0%
건 32
 
4.0%
축 31
 
3.9%
물 31
 
3.9%
주 29
 
3.6%
가 9
 
1.1%
Other values (13) 21
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 315
65.9%
2 118
 
24.7%
3 17
 
3.6%
4 8
 
1.7%
0 5
 
1.0%
9 4
 
0.8%
5 3
 
0.6%
6 3
 
0.6%
8 3
 
0.6%
7 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
C 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 803
61.9%
Common 489
37.7%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 360
44.8%
제 114
 
14.2%
호 82
 
10.2%
부 54
 
6.7%
속 40
 
5.0%
건 32
 
4.0%
축 31
 
3.9%
물 31
 
3.9%
주 29
 
3.6%
가 9
 
1.1%
Other values (13) 21
 
2.6%
Common
ValueCountFrequency (%)
1 315
64.4%
2 118
 
24.1%
3 17
 
3.5%
4 8
 
1.6%
0 5
 
1.0%
9 4
 
0.8%
- 4
 
0.8%
5 3
 
0.6%
6 3
 
0.6%
8 3
 
0.6%
Other values (6) 9
 
1.8%
Latin
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
C 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 803
61.9%
ASCII 495
38.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 360
44.8%
제 114
 
14.2%
호 82
 
10.2%
부 54
 
6.7%
속 40
 
5.0%
건 32
 
4.0%
축 31
 
3.9%
물 31
 
3.9%
주 29
 
3.6%
가 9
 
1.1%
Other values (13) 21
 
2.6%
ASCII
ValueCountFrequency (%)
1 315
63.6%
2 118
 
23.8%
3 17
 
3.4%
4 8
 
1.6%
0 5
 
1.0%
9 4
 
0.8%
- 4
 
0.8%
A 3
 
0.6%
5 3
 
0.6%
6 3
 
0.6%
Other values (9) 15
 
3.0%

대지_면적_0
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1805
Distinct (%)18.5%
Missing255
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean168.54169
Minimum0
Maximum40130
Zeros5768
Zeros (%)57.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:40.941158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3260.9
95-th percentile661
Maximum40130
Range40130
Interquartile range (IQR)260.9

Descriptive statistics

Standard deviation480.79607
Coefficient of variation (CV)2.8526834
Kurtosis4898.4677
Mean168.54169
Median Absolute Deviation (MAD)0
Skewness59.269369
Sum1642438.7
Variance231164.86
MonotonicityNot monotonic
2023-12-12T12:33:41.150601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5768
57.7%
660.0 99
 
1.0%
331.0 23
 
0.2%
496.0 19
 
0.2%
661.0 15
 
0.1%
430.0 15
 
0.1%
229.6 14
 
0.1%
450.0 13
 
0.1%
248.0 13
 
0.1%
350.0 12
 
0.1%
Other values (1795) 3754
37.5%
(Missing) 255
 
2.5%
ValueCountFrequency (%)
0.0 5768
57.7%
19.8 1
 
< 0.1%
30.0 1
 
< 0.1%
31.0 1
 
< 0.1%
33.0 1
 
< 0.1%
36.0 4
 
< 0.1%
38.0 1
 
< 0.1%
40.0 1
 
< 0.1%
43.0 1
 
< 0.1%
48.6 1
 
< 0.1%
ValueCountFrequency (%)
40130.0 1
< 0.1%
2559.0 1
< 0.1%
2391.0 1
< 0.1%
2362.0 1
< 0.1%
2359.0 1
< 0.1%
2347.0 1
< 0.1%
2092.0 1
< 0.1%
2000.0 1
< 0.1%
1946.0 1
< 0.1%
1805.0 1
< 0.1%

건축_면적_0
Real number (ℝ)

ZEROS 

Distinct5779
Distinct (%)57.9%
Missing21
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean88.258113
Minimum0
Maximum890.88
Zeros206
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:41.342585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21.48
Q156.79
median83.84
Q3111.1
95-th percentile173.957
Maximum890.88
Range890.88
Interquartile range (IQR)54.31

Descriptive statistics

Standard deviation49.196644
Coefficient of variation (CV)0.55741781
Kurtosis12.979303
Mean88.258113
Median Absolute Deviation (MAD)27.16
Skewness1.8058245
Sum880727.71
Variance2420.3098
MonotonicityNot monotonic
2023-12-12T12:33:41.486620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 206
 
2.1%
66.0 30
 
0.3%
59.5 29
 
0.3%
40.74 29
 
0.3%
130.56 27
 
0.3%
59.4 25
 
0.2%
29.75 24
 
0.2%
49.58 23
 
0.2%
99.0 20
 
0.2%
41.005 19
 
0.2%
Other values (5769) 9547
95.5%
(Missing) 21
 
0.2%
ValueCountFrequency (%)
0.0 206
2.1%
1.0 2
 
< 0.1%
1.44 2
 
< 0.1%
1.62 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 2
 
< 0.1%
2.31 1
 
< 0.1%
2.4 1
 
< 0.1%
2.42 1
 
< 0.1%
2.55 1
 
< 0.1%
ValueCountFrequency (%)
890.88 1
< 0.1%
605.91 1
< 0.1%
586.2 1
< 0.1%
549.89 1
< 0.1%
465.58 1
< 0.1%
437.32 1
< 0.1%
431.8 1
< 0.1%
409.5 1
< 0.1%
396.39 1
< 0.1%
391.56 1
< 0.1%

연면적_0
Real number (ℝ)

Distinct6274
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.69448
Minimum0
Maximum1468.21
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:41.627829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile27.77
Q161.15
median87.335
Q3131.33
95-th percentile409.766
Maximum1468.21
Range1468.21
Interquartile range (IQR)70.18

Descriptive statistics

Standard deviation120.63584
Coefficient of variation (CV)0.96745128
Kurtosis9.3575097
Mean124.69448
Median Absolute Deviation (MAD)31.78
Skewness2.7137651
Sum1246944.8
Variance14553.005
MonotonicityNot monotonic
2023-12-12T12:33:41.812547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 36
 
0.4%
66.0 31
 
0.3%
40.74 29
 
0.3%
59.5 26
 
0.3%
29.75 25
 
0.2%
59.4 23
 
0.2%
49.58 22
 
0.2%
41.005 19
 
0.2%
49.5 16
 
0.2%
84.0 16
 
0.2%
Other values (6264) 9757
97.6%
ValueCountFrequency (%)
0.0 3
< 0.1%
1.0 1
 
< 0.1%
1.44 2
< 0.1%
1.62 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 2
< 0.1%
2.31 1
 
< 0.1%
2.4 1
 
< 0.1%
2.42 1
 
< 0.1%
2.55 1
 
< 0.1%
ValueCountFrequency (%)
1468.21 1
< 0.1%
1394.4 1
< 0.1%
993.39 1
< 0.1%
924.46 1
< 0.1%
917.82 1
< 0.1%
890.88 1
< 0.1%
881.235 1
< 0.1%
852.52 1
< 0.1%
825.84 1
< 0.1%
814.5 1
< 0.1%

주_구조_0
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
벽돌구조
4611 
일반목구조
1853 
철근콘크리트구조
1496 
블록구조
973 
경량철골구조
541 
Other values (13)
526 

Length

Max length8
Median length4
Mean length4.9855
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row경량철골구조
2nd row일반목구조
3rd row일반목구조
4th row벽돌구조
5th row일반목구조

Common Values

ValueCountFrequency (%)
벽돌구조 4611
46.1%
일반목구조 1853
18.5%
철근콘크리트구조 1496
 
15.0%
블록구조 973
 
9.7%
경량철골구조 541
 
5.4%
기타조적구조 346
 
3.5%
일반철골구조 110
 
1.1%
조적구조 38
 
0.4%
석구조 10
 
0.1%
기타콘크리트구조 4
 
< 0.1%
Other values (8) 18
 
0.2%

Length

2023-12-12T12:33:41.975354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벽돌구조 4611
46.1%
일반목구조 1853
18.5%
철근콘크리트구조 1496
 
15.0%
블록구조 973
 
9.7%
경량철골구조 541
 
5.4%
기타조적구조 346
 
3.5%
일반철골구조 110
 
1.1%
조적구조 38
 
0.4%
석구조 10
 
0.1%
기타구조 4
 
< 0.1%
Other values (8) 18
 
0.2%

기타_구조_0
Text

Distinct539
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:33:42.227298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length5.7154
Min length2

Characters and Unicode

Total characters57154
Distinct characters109
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique356 ?
Unique (%)3.6%

Sample

1st row경량철골조
2nd row목조
3rd row목조
4th row시멘트벽돌조
5th row목조
ValueCountFrequency (%)
적벽돌조 1946
18.2%
목조 1814
17.0%
철근콘크리트조 1185
11.1%
시멘트벽돌조 1046
9.8%
시멘트블록조 968
9.1%
조적조(적벽돌조 480
 
4.5%
경량철골조 450
 
4.2%
연와조 423
 
4.0%
조적조 272
 
2.5%
벽돌조 231
 
2.2%
Other values (331) 1877
17.6%
2023-12-12T12:33:42.650446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 13047
22.8%
벽 4690
 
8.2%
돌 4679
 
8.2%
트 4017
 
7.0%
적 3821
 
6.7%
멘 2480
 
4.3%
시 2475
 
4.3%
철 2399
 
4.2%
목 1945
 
3.4%
콘 1548
 
2.7%
Other values (99) 16053
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53507
93.6%
Other Punctuation 1061
 
1.9%
Open Punctuation 926
 
1.6%
Close Punctuation 919
 
1.6%
Space Separator 693
 
1.2%
Uppercase Letter 41
 
0.1%
Decimal Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 13047
24.4%
벽 4690
 
8.8%
돌 4679
 
8.7%
트 4017
 
7.5%
적 3821
 
7.1%
멘 2480
 
4.6%
시 2475
 
4.6%
철 2399
 
4.5%
목 1945
 
3.6%
콘 1548
 
2.9%
Other values (83) 12406
23.2%
Uppercase Letter
ValueCountFrequency (%)
C 14
34.1%
L 11
26.8%
A 11
26.8%
R 3
 
7.3%
B 1
 
2.4%
T 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
5 2
28.6%
2 1
14.3%
1 1
14.3%
7 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 1045
98.5%
. 16
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 926
100.0%
Close Punctuation
ValueCountFrequency (%)
) 919
100.0%
Space Separator
ValueCountFrequency (%)
693
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53507
93.6%
Common 3606
 
6.3%
Latin 41
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 13047
24.4%
벽 4690
 
8.8%
돌 4679
 
8.7%
트 4017
 
7.5%
적 3821
 
7.1%
멘 2480
 
4.6%
시 2475
 
4.6%
철 2399
 
4.5%
목 1945
 
3.6%
콘 1548
 
2.9%
Other values (83) 12406
23.2%
Common
ValueCountFrequency (%)
, 1045
29.0%
( 926
25.7%
) 919
25.5%
693
19.2%
. 16
 
0.4%
0 2
 
0.1%
5 2
 
0.1%
2 1
 
< 0.1%
1 1
 
< 0.1%
7 1
 
< 0.1%
Latin
ValueCountFrequency (%)
C 14
34.1%
L 11
26.8%
A 11
26.8%
R 3
 
7.3%
B 1
 
2.4%
T 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53507
93.6%
ASCII 3647
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 13047
24.4%
벽 4690
 
8.8%
돌 4679
 
8.7%
트 4017
 
7.5%
적 3821
 
7.1%
멘 2480
 
4.6%
시 2475
 
4.6%
철 2399
 
4.5%
목 1945
 
3.6%
콘 1548
 
2.9%
Other values (83) 12406
23.2%
ASCII
ValueCountFrequency (%)
, 1045
28.7%
( 926
25.4%
) 919
25.2%
693
19.0%
. 16
 
0.4%
C 14
 
0.4%
L 11
 
0.3%
A 11
 
0.3%
R 3
 
0.1%
0 2
 
0.1%
Other values (6) 7
 
0.2%

주_용도_0
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 10000
100.0%

Length

2023-12-12T12:33:42.770773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:42.866162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 10000
100.0%

기타_용도_0
Text

Distinct187
Distinct (%)1.9%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T12:33:43.009277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length2
Mean length4.0639128
Min length2

Characters and Unicode

Total characters40631
Distinct characters100
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

Unique104 ?
Unique (%)1.0%

Sample

1st row주택
2nd row주택
3rd row주택,제1종 근린생활시설
4th row주택
5th row주택
ValueCountFrequency (%)
주택 7149
64.7%
단독주택 1985
 
18.0%
근린생활시설 693
 
6.3%
단독주택,제2종근린생활시설 305
 
2.8%
주택,제1종 141
 
1.3%
제2종근린생활시설 126
 
1.1%
단독주택,제1종근린생활시설 125
 
1.1%
제1종근린생활시설 99
 
0.9%
창고 44
 
0.4%
주택,제1종근린생활시설 25
 
0.2%
Other values (120) 358
 
3.2%
2023-12-12T12:33:43.317163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 9930
24.4%
택 9929
24.4%
단 2525
 
6.2%
독 2525
 
6.2%
, 1637
 
4.0%
시 1597
 
3.9%
설 1596
 
3.9%
근 1542
 
3.8%
생 1541
 
3.8%
린 1540
 
3.8%
Other values (90) 6269
15.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36826
90.6%
Other Punctuation 1659
 
4.1%
Space Separator 1054
 
2.6%
Decimal Number 1051
 
2.6%
Open Punctuation 20
 
< 0.1%
Close Punctuation 20
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 9930
27.0%
택 9929
27.0%
단 2525
 
6.9%
독 2525
 
6.9%
시 1597
 
4.3%
설 1596
 
4.3%
근 1542
 
4.2%
생 1541
 
4.2%
린 1540
 
4.2%
활 1538
 
4.2%
Other values (80) 2563
 
7.0%
Decimal Number
ValueCountFrequency (%)
2 568
54.0%
1 481
45.8%
6 1
 
0.1%
8 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 1637
98.7%
. 22
 
1.3%
Space Separator
ValueCountFrequency (%)
1054
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36826
90.6%
Common 3805
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 9930
27.0%
택 9929
27.0%
단 2525
 
6.9%
독 2525
 
6.9%
시 1597
 
4.3%
설 1596
 
4.3%
근 1542
 
4.2%
생 1541
 
4.2%
린 1540
 
4.2%
활 1538
 
4.2%
Other values (80) 2563
 
7.0%
Common
ValueCountFrequency (%)
, 1637
43.0%
1054
27.7%
2 568
 
14.9%
1 481
 
12.6%
. 22
 
0.6%
( 20
 
0.5%
) 20
 
0.5%
- 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36826
90.6%
ASCII 3805
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 9930
27.0%
택 9929
27.0%
단 2525
 
6.9%
독 2525
 
6.9%
시 1597
 
4.3%
설 1596
 
4.3%
근 1542
 
4.2%
생 1541
 
4.2%
린 1540
 
4.2%
활 1538
 
4.2%
Other values (80) 2563
 
7.0%
ASCII
ValueCountFrequency (%)
, 1637
43.0%
1054
27.7%
2 568
 
14.9%
1 481
 
12.6%
. 22
 
0.6%
( 20
 
0.5%
) 20
 
0.5%
- 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%

주_지붕_0
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(철근)콘크리트
5162 
슬레이트
1968 
기와
1582 
기타지붕
1279 
<NA>
 
9

Length

Max length8
Median length8
Mean length5.7484
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타지붕
2nd row슬레이트
3rd row슬레이트
4th row(철근)콘크리트
5th row슬레이트

Common Values

ValueCountFrequency (%)
(철근)콘크리트 5162
51.6%
슬레이트 1968
 
19.7%
기와 1582
 
15.8%
기타지붕 1279
 
12.8%
<NA> 9
 
0.1%

Length

2023-12-12T12:33:43.448252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:43.553425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근)콘크리트 5162
51.6%
슬레이트 1968
 
19.7%
기와 1582
 
15.8%
기타지붕 1279
 
12.8%
na 9
 
0.1%

기타_지붕_0
Text

Distinct558
Distinct (%)5.6%
Missing14
Missing (%)0.1%
Memory size156.2 KiB
2023-12-12T12:33:43.840669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length4.2066894
Min length2

Characters and Unicode

Total characters42008
Distinct characters170
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique387 ?
Unique (%)3.9%

Sample

1st row샌드위치판넬
2nd row스레이트
3rd row스레이트, 함석
4th row슬라브
5th row스레이트
ValueCountFrequency (%)
슬라브 3921
37.2%
스레이트 2015
19.1%
기와 1131
 
10.7%
평슬라브 560
 
5.3%
시멘트기와 476
 
4.5%
샌드위치판넬 389
 
3.7%
철근)콘크리트 281
 
2.7%
함석 134
 
1.3%
아연 118
 
1.1%
초가 70
 
0.7%
Other values (444) 1438
 
13.7%
2023-12-12T12:33:44.308478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
라 4941
 
11.8%
브 4910
 
11.7%
슬 4864
 
11.6%
트 3285
 
7.8%
스 2457
 
5.8%
레 2135
 
5.1%
이 2132
 
5.1%
기 1808
 
4.3%
와 1760
 
4.2%
판 879
 
2.1%
Other values (160) 12837
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39167
93.2%
Other Punctuation 659
 
1.6%
Space Separator 553
 
1.3%
Decimal Number 501
 
1.2%
Uppercase Letter 384
 
0.9%
Open Punctuation 347
 
0.8%
Close Punctuation 347
 
0.8%
Lowercase Letter 44
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
라 4941
12.6%
브 4910
12.5%
슬 4864
12.4%
트 3285
 
8.4%
스 2457
 
6.3%
레 2135
 
5.5%
이 2132
 
5.4%
기 1808
 
4.6%
와 1760
 
4.5%
판 879
 
2.2%
Other values (124) 9996
25.5%
Uppercase Letter
ValueCountFrequency (%)
T 148
38.5%
S 49
 
12.8%
P 47
 
12.2%
E 46
 
12.0%
K 41
 
10.7%
H 41
 
10.7%
O 5
 
1.3%
B 3
 
0.8%
A 1
 
0.3%
R 1
 
0.3%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 167
33.3%
1 134
26.7%
5 108
21.6%
7 58
 
11.6%
2 12
 
2.4%
6 12
 
2.4%
8 6
 
1.2%
4 2
 
0.4%
3 2
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
m 20
45.5%
t 18
40.9%
s 2
 
4.5%
e 2
 
4.5%
p 2
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 621
94.2%
. 26
 
3.9%
/ 12
 
1.8%
Other Symbol
ValueCountFrequency (%)
ⓣ 1
50.0%
㎜ 1
50.0%
Space Separator
ValueCountFrequency (%)
553
100.0%
Open Punctuation
ValueCountFrequency (%)
( 347
100.0%
Close Punctuation
ValueCountFrequency (%)
) 347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39167
93.2%
Common 2413
 
5.7%
Latin 428
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
라 4941
12.6%
브 4910
12.5%
슬 4864
12.4%
트 3285
 
8.4%
스 2457
 
6.3%
레 2135
 
5.5%
이 2132
 
5.4%
기 1808
 
4.6%
와 1760
 
4.5%
판 879
 
2.2%
Other values (124) 9996
25.5%
Common
ValueCountFrequency (%)
, 621
25.7%
553
22.9%
( 347
14.4%
) 347
14.4%
0 167
 
6.9%
1 134
 
5.6%
5 108
 
4.5%
7 58
 
2.4%
. 26
 
1.1%
2 12
 
0.5%
Other values (9) 40
 
1.7%
Latin
ValueCountFrequency (%)
T 148
34.6%
S 49
 
11.4%
P 47
 
11.0%
E 46
 
10.7%
K 41
 
9.6%
H 41
 
9.6%
m 20
 
4.7%
t 18
 
4.2%
O 5
 
1.2%
B 3
 
0.7%
Other values (7) 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39167
93.2%
ASCII 2839
 
6.8%
Enclosed Alphanum 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
라 4941
12.6%
브 4910
12.5%
슬 4864
12.4%
트 3285
 
8.4%
스 2457
 
6.3%
레 2135
 
5.5%
이 2132
 
5.4%
기 1808
 
4.6%
와 1760
 
4.5%
판 879
 
2.2%
Other values (124) 9996
25.5%
ASCII
ValueCountFrequency (%)
, 621
21.9%
553
19.5%
( 347
12.2%
) 347
12.2%
0 167
 
5.9%
T 148
 
5.2%
1 134
 
4.7%
5 108
 
3.8%
7 58
 
2.0%
S 49
 
1.7%
Other values (24) 307
10.8%
Enclosed Alphanum
ValueCountFrequency (%)
ⓣ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎜ 1
100.0%

세대_수_0
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
7975 
<NA>
1718 
1
 
298
2
 
5
19
 
2

Length

Max length4
Median length1
Mean length1.5156
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 7975
79.8%
<NA> 1718
 
17.2%
1 298
 
3.0%
2 5
 
0.1%
19 2
 
< 0.1%
9 2
 
< 0.1%

Length

2023-12-12T12:33:44.804842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:44.929114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 7975
79.8%
na 1718
 
17.2%
1 298
 
3.0%
2 5
 
< 0.1%
19 2
 
< 0.1%
9 2
 
< 0.1%

가구_수_0
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.2%
Missing411
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean1.6248827
Minimum0
Maximum42
Zeros513
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:45.081141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile8.6
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.663504
Coefficient of variation (CV)1.6391977
Kurtosis22.698221
Mean1.6248827
Median Absolute Deviation (MAD)0
Skewness4.4363943
Sum15581
Variance7.0942535
MonotonicityNot monotonic
2023-12-12T12:33:45.273374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 8209
82.1%
0 513
 
5.1%
11 177
 
1.8%
2 130
 
1.3%
3 118
 
1.2%
10 107
 
1.1%
4 36
 
0.4%
15 33
 
0.3%
9 31
 
0.3%
7 30
 
0.3%
Other values (11) 205
 
2.1%
(Missing) 411
 
4.1%
ValueCountFrequency (%)
0 513
 
5.1%
1 8209
82.1%
2 130
 
1.3%
3 118
 
1.2%
4 36
 
0.4%
5 24
 
0.2%
6 24
 
0.2%
7 30
 
0.3%
8 25
 
0.2%
9 31
 
0.3%
ValueCountFrequency (%)
42 1
 
< 0.1%
19 21
 
0.2%
18 29
 
0.3%
17 24
 
0.2%
16 8
 
0.1%
15 33
 
0.3%
14 26
 
0.3%
13 10
 
0.1%
12 13
 
0.1%
11 177
1.8%

지상_층_수_0
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.4090636
Minimum0
Maximum6
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:45.401823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.81250475
Coefficient of variation (CV)0.57662744
Kurtosis3.6794703
Mean1.4090636
Median Absolute Deviation (MAD)0
Skewness2.1143887
Sum14085
Variance0.66016397
MonotonicityNot monotonic
2023-12-12T12:33:45.569870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 7419
74.2%
2 1624
 
16.2%
4 552
 
5.5%
3 393
 
3.9%
5 5
 
0.1%
0 2
 
< 0.1%
6 1
 
< 0.1%
(Missing) 4
 
< 0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 7419
74.2%
2 1624
 
16.2%
3 393
 
3.9%
4 552
 
5.5%
5 5
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 5
 
0.1%
4 552
 
5.5%
3 393
 
3.9%
2 1624
 
16.2%
1 7419
74.2%
0 2
 
< 0.1%

지하_층_수_0
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8888 
<NA>
 
855
1
 
257

Length

Max length4
Median length1
Mean length1.2565
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8888
88.9%
<NA> 855
 
8.6%
1 257
 
2.6%

Length

2023-12-12T12:33:45.710448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:45.842457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8888
88.9%
na 855
 
8.6%
1 257
 
2.6%

허가_일_0
Date

MISSING 

Distinct3428
Distinct (%)71.4%
Missing5199
Missing (%)52.0%
Memory size156.2 KiB
Minimum1931-09-25 00:00:00
Maximum2020-08-25 00:00:00
2023-12-12T12:33:45.986847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:33:46.140269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인_일_0
Date

Distinct4607
Distinct (%)46.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1832-01-01 00:00:00
Maximum2020-12-24 00:00:00
2023-12-12T12:33:46.312604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:33:46.508468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

도로명주소_도로_명_0
Text

MISSING 

Distinct1107
Distinct (%)12.4%
Missing1075
Missing (%)10.8%
Memory size156.2 KiB
2023-12-12T12:33:46.911976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length12.911036
Min length12

Characters and Unicode

Total characters115231
Distinct characters268
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

Unique133 ?
Unique (%)1.5%

Sample

1st row전라북도 군산시 백릉로
2nd row전라북도 군산시 외산2길
3rd row전라북도 군산시 오룡로
4th row전라북도 군산시 개정안길
5th row전라북도 군산시 월명로
ValueCountFrequency (%)
전라북도 8925
33.3%
군산시 8925
33.3%
번영로 101
 
0.4%
팔마로 85
 
0.3%
월명로 77
 
0.3%
대학로 72
 
0.3%
해망로 71
 
0.3%
경암3길 62
 
0.2%
경암2길 53
 
0.2%
중앙로 49
 
0.2%
Other values (1099) 8355
31.2%
2023-12-12T12:33:47.506917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17850
15.5%
산 9457
 
8.2%
도 9137
 
7.9%
전 9048
 
7.9%
군 9019
 
7.8%
북 9016
 
7.8%
시 8996
 
7.8%
라 8965
 
7.8%
길 7278
 
6.3%
로 1678
 
1.5%
Other values (258) 24787
21.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93143
80.8%
Space Separator 17850
 
15.5%
Decimal Number 4206
 
3.7%
Other Punctuation 32
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 9457
10.2%
도 9137
9.8%
전 9048
9.7%
군 9019
9.7%
북 9016
9.7%
시 8996
9.7%
라 8965
9.6%
길 7278
 
7.8%
로 1678
 
1.8%
안 1252
 
1.3%
Other values (246) 19297
20.7%
Decimal Number
ValueCountFrequency (%)
1 1395
33.2%
2 1287
30.6%
3 739
17.6%
4 316
 
7.5%
5 243
 
5.8%
7 75
 
1.8%
6 71
 
1.7%
8 40
 
1.0%
9 33
 
0.8%
0 7
 
0.2%
Space Separator
ValueCountFrequency (%)
17850
100.0%
Other Punctuation
ValueCountFrequency (%)
. 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93143
80.8%
Common 22088
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 9457
10.2%
도 9137
9.8%
전 9048
9.7%
군 9019
9.7%
북 9016
9.7%
시 8996
9.7%
라 8965
9.6%
길 7278
 
7.8%
로 1678
 
1.8%
안 1252
 
1.3%
Other values (246) 19297
20.7%
Common
ValueCountFrequency (%)
17850
80.8%
1 1395
 
6.3%
2 1287
 
5.8%
3 739
 
3.3%
4 316
 
1.4%
5 243
 
1.1%
7 75
 
0.3%
6 71
 
0.3%
8 40
 
0.2%
9 33
 
0.1%
Other values (2) 39
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93143
80.8%
ASCII 22088
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17850
80.8%
1 1395
 
6.3%
2 1287
 
5.8%
3 739
 
3.3%
4 316
 
1.4%
5 243
 
1.1%
7 75
 
0.3%
6 71
 
0.3%
8 40
 
0.2%
9 33
 
0.1%
Other values (2) 39
 
0.2%
Hangul
ValueCountFrequency (%)
산 9457
10.2%
도 9137
9.8%
전 9048
9.7%
군 9019
9.7%
북 9016
9.7%
시 8996
9.7%
라 8965
9.6%
길 7278
 
7.8%
로 1678
 
1.8%
안 1252
 
1.3%
Other values (246) 19297
20.7%

도로명주소_본번_0
Real number (ℝ)

MISSING 

Distinct534
Distinct (%)5.9%
Missing980
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean69.893237
Minimum0
Maximum2003
Zeros96
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:47.689753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.95
Q115
median32
Q365
95-th percentile261.1
Maximum2003
Range2003
Interquartile range (IQR)50

Descriptive statistics

Standard deviation137.41562
Coefficient of variation (CV)1.9660789
Kurtosis56.485861
Mean69.893237
Median Absolute Deviation (MAD)20
Skewness6.2459386
Sum630437
Variance18883.052
MonotonicityNot monotonic
2023-12-12T12:33:47.871766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 196
 
2.0%
15 188
 
1.9%
8 179
 
1.8%
7 178
 
1.8%
10 176
 
1.8%
6 174
 
1.7%
20 171
 
1.7%
13 170
 
1.7%
5 168
 
1.7%
19 164
 
1.6%
Other values (524) 7256
72.6%
(Missing) 980
 
9.8%
ValueCountFrequency (%)
0 96
1.0%
1 59
 
0.6%
2 60
 
0.6%
3 123
1.2%
4 113
1.1%
5 168
1.7%
6 174
1.7%
7 178
1.8%
8 179
1.8%
9 196
2.0%
ValueCountFrequency (%)
2003 1
 
< 0.1%
1933 1
 
< 0.1%
1929 5
0.1%
1919 1
 
< 0.1%
1915 1
 
< 0.1%
1587 1
 
< 0.1%
1532 1
 
< 0.1%
1526 1
 
< 0.1%
1517 1
 
< 0.1%
1484 2
 
< 0.1%

도로명주소_부번_0
Real number (ℝ)

MISSING  ZEROS 

Distinct75
Distinct (%)0.9%
Missing1650
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean4.3301796
Minimum0
Maximum218
Zeros3700
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:33:48.037754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile19
Maximum218
Range218
Interquartile range (IQR)5

Descriptive statistics

Standard deviation8.9563206
Coefficient of variation (CV)2.0683485
Kurtosis168.17607
Mean4.3301796
Median Absolute Deviation (MAD)1
Skewness9.1065214
Sum36157
Variance80.215678
MonotonicityNot monotonic
2023-12-12T12:33:48.195522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3700
37.0%
1 797
 
8.0%
3 507
 
5.1%
4 477
 
4.8%
2 459
 
4.6%
5 336
 
3.4%
6 320
 
3.2%
7 236
 
2.4%
8 213
 
2.1%
9 153
 
1.5%
Other values (65) 1152
 
11.5%
(Missing) 1650
16.5%
ValueCountFrequency (%)
0 3700
37.0%
1 797
 
8.0%
2 459
 
4.6%
3 507
 
5.1%
4 477
 
4.8%
5 336
 
3.4%
6 320
 
3.2%
7 236
 
2.4%
8 213
 
2.1%
9 153
 
1.5%
ValueCountFrequency (%)
218 1
< 0.1%
212 1
< 0.1%
210 1
< 0.1%
206 1
< 0.1%
188 1
< 0.1%
102 1
< 0.1%
95 1
< 0.1%
93 1
< 0.1%
84 1
< 0.1%
81 1
< 0.1%

Sample

순번대장_종류_0시군구_명_0법정동_명_0대지_구분_0본번_0부번_0외필지수_0건물명_0동명칭_0대지_면적_0건축_면적_0연면적_0주_구조_0기타_구조_0주_용도_0기타_용도_0주_지붕_0기타_지붕_0세대_수_0가구_수_0지상_층_수_0지하_층_수_0허가_일_0사용승인_일_0도로명주소_도로_명_0도로명주소_본번_0도로명주소_부번_0
44094410일반건축물전라북도 군산시조촌동대지94430<NA><NA>167.967.567.5경량철골구조경량철골조단독주택주택기타지붕샌드위치판넬01101999-10-162000-01-10전라북도 군산시 백릉로12425
70677068일반건축물전라북도 군산시구암동대지48310<NA><NA>0.036.336.3일반목구조목조단독주택주택슬레이트스레이트0110<NA>1935-01-01전라북도 군산시 외산2길2424
27122713일반건축물전라북도 군산시명산동대지22180<NA><NA>0.0137.85137.85일반목구조목조단독주택주택,제1종 근린생활시설슬레이트스레이트, 함석0110<NA>1930-01-01전라북도 군산시 오룡로520
1319913200일반건축물전라북도 군산시개정면 운회리대지90380<NA><NA>0.084.8884.88벽돌구조시멘트벽돌조단독주택주택(철근)콘크리트슬라브0110<NA>1992-04-01전라북도 군산시 개정안길610
1289212893일반건축물전라북도 군산시임피면 축산리대지18900<NA><NA>0.066.4466.44일반목구조목조단독주택주택슬레이트스레이트0110<NA>1936-01-01<NA><NA><NA>
86078608일반건축물전라북도 군산시수송동대지40800<NA><NA>0.063.8163.81일반목구조목조단독주택주택기타지붕함석0110<NA>1940-01-01<NA><NA><NA>
24902491일반건축물전라북도 군산시선양동대지21302<NA><NA>0.0103.8103.8일반목구조목조단독주택주택, 근린생활시설기와기와0110<NA>1931-01-01전라북도 군산시 월명로4340
1207212073일반건축물전라북도 군산시회현면 월연리대지48990<NA><NA>0.00.083.1벽돌구조적벽돌조단독주택주택(철근)콘크리트슬라브0010<NA>1991-01-01전라북도 군산시 오봉길670
94279428일반건축물전라북도 군산시소룡동대지138880<NA><NA>0.0104.37132.9벽돌구조적벽돌조단독주택주택, 근린생활시설(철근)콘크리트슬라브01201983-07-191983-12-27전라북도 군산시 솔꼬지3길40
49484949일반건축물전라북도 군산시조촌동대지742100<NA><NA>0.081.4781.47벽돌구조적벽돌조단독주택주택(철근)콘크리트슬라브01101980-04-231980-10-30전라북도 군산시 양안2길84
순번대장_종류_0시군구_명_0법정동_명_0대지_구분_0본번_0부번_0외필지수_0건물명_0동명칭_0대지_면적_0건축_면적_0연면적_0주_구조_0기타_구조_0주_용도_0기타_용도_0주_지붕_0기타_지붕_0세대_수_0가구_수_0지상_층_수_0지하_층_수_0허가_일_0사용승인_일_0도로명주소_도로_명_0도로명주소_본번_0도로명주소_부번_0
87348735일반건축물전라북도 군산시지곡동대지49250<NA><NA>223.3127.74241.92벽돌구조조적조(적벽돌조)단독주택주택(철근)콘크리트평슬라브, 칼라아스팔트슁글01201997-07-151997-11-18전라북도 군산시 상지곡안4길800
1351713518일반건축물전라북도 군산시성산면 도암리대지3510<NA><NA>730.098.5688.97벽돌구조적벽돌단독주택주택(철근)콘크리트슬라브0110<NA>1987-01-01전라북도 군산시 창암길633
2364223643일반건축물전라북도 군산시중동대지25110<NA><NA>0.046.1946.19블록구조시멘트블록조단독주택주택기와시멘트기와01101974-05-311983-08-10<NA><NA><NA>
38303831일반건축물전라북도 군산시장재동대지45320<NA><NA>0.072.5872.58벽돌구조적벽돌조단독주택주택(철근)콘크리트슬라브0110<NA>1978-12-13전라북도 군산시 풍마길274
98719872일반건축물전라북도 군산시옥구읍 상평리대지48100<NA><NA>0.062.462.4일반목구조목조단독주택주택슬레이트스레이트0110<NA>1940-01-01전라북도 군산시 상평향교길220
1536315364일반건축물전라북도 군산시옥서면 옥봉리대지74320<NA><NA>0.083.6883.68벽돌구조적벽돌조단독주택주택(철근)콘크리트슬라브01101983-07-051983-12-31전라북도 군산시 옥봉초교길99
55195520일반건축물전라북도 군산시동흥남동대지93141<NA><NA>0.074.0574.05기타조적구조흙담단독주택주택슬레이트스레이트0110<NA>1955-01-01전라북도 군산시 흥남2길470
164165일반건축물전라북도 군산시해망동대지1000510<NA>가동0.064.4699.5벽돌구조시멘트벽돌조단독주택주택(철근)콘크리트슬라브0120<NA>1960-01-01전라북도 군산시 중앙로2600
2101121012일반건축물전라북도 군산시개정동대지20940<NA><NA>629.091.5698.29철근콘크리트구조철근콘크리트조단독주택단독주택(철근)콘크리트슬래브<NA>1202012-10-182013-04-05전라북도 군산시 달여길62<NA>
1571615717일반건축물전라북도 군산시옥도면 선유도리대지2100<NA><NA>0.073.773.7블록구조시멘트블록조단독주택주택슬레이트스레이트0110<NA>1993-01-01전라북도 군산시 선유도2길670