Overview

Dataset statistics

Number of variables36
Number of observations10000
Missing cells80878
Missing cells (%)22.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 MiB
Average record size in memory317.0 B

Variable types

Numeric19
Text7
Categorical8
DateTime2

Dataset

Description성동구 1988년~2002년까지 건축인허가 정보입니다. 건축인허가의 대지위치, 시군구코드, 법정동코드, 대지구분코드, 번, 지, 건물명, 지목코드 등의 정보를 제공합니다.
Author서울특별시 성동구
URLhttps://www.data.go.kr/data/15111095/fileData.do

Alerts

시군구코드 has constant value ""Constant
대지구분코드 has constant value ""Constant
생성일자 has constant value ""Constant
지목명 is highly imbalanced (96.5%)Imbalance
용도지역코드 is highly imbalanced (55.3%)Imbalance
용도지역명 is highly imbalanced (57.0%)Imbalance
용도지구코드 is highly imbalanced (98.4%)Imbalance
용도지구명 is highly imbalanced (82.3%)Imbalance
건축구분명 is highly imbalanced (80.0%)Imbalance
건물명 has 9931 (99.3%) missing valuesMissing
용적율산정연면적 has 9568 (95.7%) missing valuesMissing
주용도코드 has 7536 (75.4%) missing valuesMissing
세대수 has 9381 (93.8%) missing valuesMissing
호수 has 9971 (99.7%) missing valuesMissing
가구수 has 5940 (59.4%) missing valuesMissing
총주차수 has 6335 (63.3%) missing valuesMissing
착공예정일 has 7162 (71.6%) missing valuesMissing
착공연기일 has 9994 (99.9%) missing valuesMissing
실제착공일 has 3259 (32.6%) missing valuesMissing
사용승인일 has 1630 (16.3%) missing valuesMissing
대지면적 is highly skewed (γ1 = 29.37359546)Skewed
건축면적 is highly skewed (γ1 = 33.30284181)Skewed
건폐율 is highly skewed (γ1 = 23.25337221)Skewed
연면적 is highly skewed (γ1 = 46.05203959)Skewed
용적률 is highly skewed (γ1 = 64.68318359)Skewed
주건축물수 is highly skewed (γ1 = 20.86312776)Skewed
부속건축물동수 is highly skewed (γ1 = 20.43981731)Skewed
총주차수 is highly skewed (γ1 = 25.63998298)Skewed
연번 has unique valuesUnique
has 1735 (17.3%) zerosZeros
부속건축물동수 has 9753 (97.5%) zerosZeros

Reproduction

Analysis started2023-12-12 17:40:05.979144
Analysis finished2023-12-12 17:40:07.857741
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5242.4965
Minimum2
Maximum10492
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:07.993446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile518.95
Q12615.75
median5248.5
Q37865.25
95-th percentile9967.05
Maximum10492
Range10490
Interquartile range (IQR)5249.5

Descriptive statistics

Standard deviation3031.8667
Coefficient of variation (CV)0.57832498
Kurtosis-1.2009028
Mean5242.4965
Median Absolute Deviation (MAD)2625
Skewness-0.00049570375
Sum52424965
Variance9192215.4
MonotonicityNot monotonic
2023-12-13T02:40:08.182376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9031 1
 
< 0.1%
8306 1
 
< 0.1%
7638 1
 
< 0.1%
9166 1
 
< 0.1%
6619 1
 
< 0.1%
1071 1
 
< 0.1%
1527 1
 
< 0.1%
7114 1
 
< 0.1%
10295 1
 
< 0.1%
1649 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
10492 1
< 0.1%
10490 1
< 0.1%
10489 1
< 0.1%
10488 1
< 0.1%
10487 1
< 0.1%
10486 1
< 0.1%
10484 1
< 0.1%
10483 1
< 0.1%
10482 1
< 0.1%
10481 1
< 0.1%
Distinct9456
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:40:08.395393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.3412
Min length15

Characters and Unicode

Total characters203412
Distinct characters47
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

Unique9102 ?
Unique (%)91.0%

Sample

1st row서울특별시 성동구 사근동 309-80
2nd row서울특별시 성동구 성수동1가 447
3rd row서울특별시 성동구 성수동1가 559-2
4th row서울특별시 성동구 용답동 108-1
5th row서울특별시 성동구 성수동1가 169
ValueCountFrequency (%)
서울특별시 10000
25.0%
성동구 10000
25.0%
성수동2가 1563
 
3.9%
성수동1가 1405
 
3.5%
하왕십리동 1081
 
2.7%
행당동 1035
 
2.6%
용답동 795
 
2.0%
마장동 669
 
1.7%
금호동2가 535
 
1.3%
금호동3가 428
 
1.1%
Other values (8109) 12489
31.2%
2023-12-13T02:40:09.234471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30000
14.7%
20001
 
9.8%
12968
 
6.4%
10000
 
4.9%
10000
 
4.9%
10000
 
4.9%
10000
 
4.9%
10000
 
4.9%
10000
 
4.9%
1 9581
 
4.7%
Other values (37) 70862
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117129
57.6%
Decimal Number 48017
23.6%
Space Separator 30000
 
14.7%
Dash Punctuation 8266
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20001
17.1%
12968
11.1%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
4591
 
3.9%
3336
 
2.8%
Other values (25) 16233
13.9%
Decimal Number
ValueCountFrequency (%)
1 9581
20.0%
2 7938
16.5%
3 5593
11.6%
6 4506
9.4%
4 3819
 
8.0%
5 3775
 
7.9%
9 3478
 
7.2%
7 3351
 
7.0%
8 3192
 
6.6%
0 2784
 
5.8%
Space Separator
ValueCountFrequency (%)
30000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117129
57.6%
Common 86283
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20001
17.1%
12968
11.1%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
4591
 
3.9%
3336
 
2.8%
Other values (25) 16233
13.9%
Common
ValueCountFrequency (%)
30000
34.8%
1 9581
 
11.1%
- 8266
 
9.6%
2 7938
 
9.2%
3 5593
 
6.5%
6 4506
 
5.2%
4 3819
 
4.4%
5 3775
 
4.4%
9 3478
 
4.0%
7 3351
 
3.9%
Other values (2) 5976
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117129
57.6%
ASCII 86283
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30000
34.8%
1 9581
 
11.1%
- 8266
 
9.6%
2 7938
 
9.2%
3 5593
 
6.5%
6 4506
 
5.2%
4 3819
 
4.4%
5 3775
 
4.4%
9 3478
 
4.0%
7 3351
 
3.9%
Other values (2) 5976
 
6.9%
Hangul
ValueCountFrequency (%)
20001
17.1%
12968
11.1%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
10000
8.5%
4591
 
3.9%
3336
 
2.8%
Other values (25) 16233
13.9%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11200
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11200
2nd row11200
3rd row11200
4th row11200
5th row11200

Common Values

ValueCountFrequency (%)
11200 10000
100.0%

Length

2023-12-13T02:40:09.439597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:09.592598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11200 10000
100.0%

법정동코드
Real number (ℝ)

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1200111 × 109
Minimum1.1200101 × 109
Maximum1.1200122 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:09.701333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200101 × 109
5-th percentile1.1200102 × 109
Q11.1200106 × 109
median1.1200111 × 109
Q31.1200115 × 109
95-th percentile1.1200122 × 109
Maximum1.1200122 × 109
Range2100
Interquartile range (IQR)900

Descriptive statistics

Standard deviation582.97606
Coefficient of variation (CV)5.2050919 × 10-7
Kurtosis-0.82352359
Mean1.1200111 × 109
Median Absolute Deviation (MAD)400
Skewness0.10204837
Sum1.1200111 × 1013
Variance339861.09
MonotonicityNot monotonic
2023-12-13T02:40:09.904056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1120011500 1563
15.6%
1120011400 1405
14.1%
1120010200 1081
10.8%
1120010700 1035
10.3%
1120012200 795
8.0%
1120010500 669
 
6.7%
1120011000 535
 
5.3%
1120011100 428
 
4.3%
1120011800 424
 
4.2%
1120011200 381
 
3.8%
Other values (7) 1684
16.8%
ValueCountFrequency (%)
1120010100 186
 
1.9%
1120010200 1081
10.8%
1120010300 268
 
2.7%
1120010400 212
 
2.1%
1120010500 669
6.7%
1120010600 303
 
3.0%
1120010700 1035
10.3%
1120010800 68
 
0.7%
1120010900 279
 
2.8%
1120011000 535
5.3%
ValueCountFrequency (%)
1120012200 795
8.0%
1120011800 424
 
4.2%
1120011500 1563
15.6%
1120011400 1405
14.1%
1120011300 368
 
3.7%
1120011200 381
 
3.8%
1120011100 428
 
4.3%
1120011000 535
 
5.3%
1120010900 279
 
2.8%
1120010800 68
 
0.7%

대지구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-13T02:40:10.146672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:10.317644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%


Real number (ℝ)

Distinct1206
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean392.4663
Minimum1
Maximum1801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:10.521043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14
Q1128
median305.5
Q3578.5
95-th percentile1026
Maximum1801
Range1800
Interquartile range (IQR)450.5

Descriptive statistics

Standard deviation331.49226
Coefficient of variation (CV)0.84463878
Kurtosis1.1193193
Mean392.4663
Median Absolute Deviation (MAD)212.5
Skewness1.1516823
Sum3924663
Variance109887.12
MonotonicityNot monotonic
2023-12-13T02:40:10.723194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
656 405
 
4.0%
13 200
 
2.0%
128 197
 
2.0%
73 153
 
1.5%
299 104
 
1.0%
339 98
 
1.0%
301 90
 
0.9%
685 90
 
0.9%
72 87
 
0.9%
277 87
 
0.9%
Other values (1196) 8489
84.9%
ValueCountFrequency (%)
1 54
0.5%
2 16
 
0.2%
3 17
 
0.2%
4 26
0.3%
5 17
 
0.2%
6 25
0.2%
7 21
 
0.2%
8 33
0.3%
9 15
 
0.1%
10 29
0.3%
ValueCountFrequency (%)
1801 3
< 0.1%
1797 1
 
< 0.1%
1789 1
 
< 0.1%
1788 1
 
< 0.1%
1786 1
 
< 0.1%
1784 1
 
< 0.1%
1783 1
 
< 0.1%
1779 2
< 0.1%
1778 1
 
< 0.1%
1771 2
< 0.1%


Real number (ℝ)

ZEROS 

Distinct843
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.7454
Minimum0
Maximum1907
Zeros1735
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:10.904989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q351
95-th percentile508.15
Maximum1907
Range1907
Interquartile range (IQR)50

Descriptive statistics

Standard deviation215.89833
Coefficient of variation (CV)2.5476112
Kurtosis20.729185
Mean84.7454
Median Absolute Deviation (MAD)10
Skewness4.2036933
Sum847454
Variance46612.089
MonotonicityNot monotonic
2023-12-13T02:40:11.116235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1735
 
17.3%
1 845
 
8.5%
2 630
 
6.3%
3 370
 
3.7%
4 290
 
2.9%
5 260
 
2.6%
6 231
 
2.3%
7 218
 
2.2%
8 201
 
2.0%
9 186
 
1.9%
Other values (833) 5034
50.3%
ValueCountFrequency (%)
0 1735
17.3%
1 845
8.5%
2 630
 
6.3%
3 370
 
3.7%
4 290
 
2.9%
5 260
 
2.6%
6 231
 
2.3%
7 218
 
2.2%
8 201
 
2.0%
9 186
 
1.9%
ValueCountFrequency (%)
1907 1
< 0.1%
1886 2
< 0.1%
1872 2
< 0.1%
1839 1
< 0.1%
1835 1
< 0.1%
1834 1
< 0.1%
1832 1
< 0.1%
1829 1
< 0.1%
1828 1
< 0.1%
1825 1
< 0.1%

건물명
Text

MISSING 

Distinct52
Distinct (%)75.4%
Missing9931
Missing (%)99.3%
Memory size156.2 KiB
2023-12-13T02:40:11.382231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.1304348
Min length3

Characters and Unicode

Total characters423
Distinct characters121
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)60.9%

Sample

1st row옥수동 아파트
2nd row행복한 집
3rd row삼웅아파트
4th row대한빌딩
5th row송림빌라
ValueCountFrequency (%)
옥수동 5
 
5.4%
아파트 5
 
5.4%
토우마트 4
 
4.3%
2단지 4
 
4.3%
동성빌딩 4
 
4.3%
빌딩 3
 
3.2%
하왕십리동 2
 
2.2%
성수동공장 2
 
2.2%
다가구주택 2
 
2.2%
지성교회 2
 
2.2%
Other values (52) 60
64.5%
2023-12-13T02:40:11.828230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
5.7%
23
 
5.4%
21
 
5.0%
16
 
3.8%
16
 
3.8%
14
 
3.3%
13
 
3.1%
12
 
2.8%
10
 
2.4%
9
 
2.1%
Other values (111) 265
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
88.9%
Space Separator 24
 
5.7%
Decimal Number 10
 
2.4%
Uppercase Letter 7
 
1.7%
Other Symbol 4
 
0.9%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
 
6.1%
21
 
5.6%
16
 
4.3%
16
 
4.3%
14
 
3.7%
13
 
3.5%
12
 
3.2%
10
 
2.7%
9
 
2.4%
8
 
2.1%
Other values (98) 234
62.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
Y 1
14.3%
S 1
14.3%
V 1
14.3%
I 1
14.3%
P 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 6
60.0%
0 2
 
20.0%
3 1
 
10.0%
1 1
 
10.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 380
89.8%
Common 36
 
8.5%
Latin 7
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
 
6.1%
21
 
5.5%
16
 
4.2%
16
 
4.2%
14
 
3.7%
13
 
3.4%
12
 
3.2%
10
 
2.6%
9
 
2.4%
8
 
2.1%
Other values (99) 238
62.6%
Common
ValueCountFrequency (%)
24
66.7%
2 6
 
16.7%
. 2
 
5.6%
0 2
 
5.6%
3 1
 
2.8%
1 1
 
2.8%
Latin
ValueCountFrequency (%)
B 2
28.6%
Y 1
14.3%
S 1
14.3%
V 1
14.3%
I 1
14.3%
P 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
88.9%
ASCII 43
 
10.2%
None 4
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
55.8%
2 6
 
14.0%
B 2
 
4.7%
. 2
 
4.7%
0 2
 
4.7%
3 1
 
2.3%
Y 1
 
2.3%
S 1
 
2.3%
V 1
 
2.3%
I 1
 
2.3%
Other values (2) 2
 
4.7%
Hangul
ValueCountFrequency (%)
23
 
6.1%
21
 
5.6%
16
 
4.3%
16
 
4.3%
14
 
3.7%
13
 
3.5%
12
 
3.2%
10
 
2.7%
9
 
2.4%
8
 
2.1%
Other values (98) 234
62.2%
None
ValueCountFrequency (%)
4
100.0%

지목코드
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0104
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:11.969184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q18
median8
Q38
95-th percentile8
Maximum25
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.52279936
Coefficient of variation (CV)0.065265076
Kurtosis730.44975
Mean8.0104
Median Absolute Deviation (MAD)0
Skewness18.028031
Sum80104
Variance0.27331917
MonotonicityNot monotonic
2023-12-13T02:40:12.080831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
8 9893
98.9%
9 82
 
0.8%
1 15
 
0.1%
25 6
 
0.1%
15 2
 
< 0.1%
17 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
1 15
 
0.1%
8 9893
98.9%
9 82
 
0.8%
10 1
 
< 0.1%
15 2
 
< 0.1%
17 1
 
< 0.1%
25 6
 
0.1%
ValueCountFrequency (%)
25 6
 
0.1%
17 1
 
< 0.1%
15 2
 
< 0.1%
10 1
 
< 0.1%
9 82
 
0.8%
8 9893
98.9%
1 15
 
0.1%

지목명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대지
9893 
공장용지
 
82
 
15
종교용지
 
6
철도용지
 
2
Other values (2)
 
2

Length

Max length4
Median length2
Mean length2.0167
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
대지 9893
98.9%
공장용지 82
 
0.8%
15
 
0.1%
종교용지 6
 
0.1%
철도용지 2
 
< 0.1%
하천 1
 
< 0.1%
학교용지 1
 
< 0.1%

Length

2023-12-13T02:40:12.227917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:12.345660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대지 9893
98.9%
공장용지 82
 
0.8%
15
 
0.1%
종교용지 6
 
0.1%
철도용지 2
 
< 0.1%
하천 1
 
< 0.1%
학교용지 1
 
< 0.1%

용도지역코드
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
UQA120
6493 
UQA100
1719 
UQA330
1447 
UQA130
 
143
UQA220
 
78
Other values (5)
 
120

Length

Max length6
Median length6
Mean length5.992
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowUQA120
2nd rowUQA120
3rd rowUQA120
4th rowUQA120
5th rowUQA120

Common Values

ValueCountFrequency (%)
UQA120 6493
64.9%
UQA100 1719
 
17.2%
UQA330 1447
 
14.5%
UQA130 143
 
1.4%
UQA220 78
 
0.8%
UQA001 53
 
0.5%
<NA> 40
 
0.4%
UQA200 20
 
0.2%
UQA400 6
 
0.1%
UQA430 1
 
< 0.1%

Length

2023-12-13T02:40:12.493438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:12.624746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqa120 6493
64.9%
uqa100 1719
 
17.2%
uqa330 1447
 
14.5%
uqa130 143
 
1.4%
uqa220 78
 
0.8%
uqa001 53
 
0.5%
na 40
 
0.4%
uqa200 20
 
0.2%
uqa400 6
 
0.1%
uqa430 1
 
< 0.1%

용도지역명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반주거지역
6493 
주거지역
1719 
준공업지역
1447 
준주거지역
 
143
일반상업지역
 
78
Other values (6)
 
120

Length

Max length6
Median length6
Mean length5.474
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반주거지역 6493
64.9%
주거지역 1719
 
17.2%
준공업지역 1447
 
14.5%
준주거지역 143
 
1.4%
일반상업지역 78
 
0.8%
도시지역 53
 
0.5%
<NA> 37
 
0.4%
상업지역 20
 
0.2%
녹지지역 6
 
0.1%
노선상업지역 3
 
< 0.1%

Length

2023-12-13T02:40:12.784507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반주거지역 6493
64.9%
주거지역 1719
 
17.2%
준공업지역 1447
 
14.5%
준주거지역 143
 
1.4%
일반상업지역 78
 
0.8%
도시지역 53
 
0.5%
na 37
 
0.4%
상업지역 20
 
0.2%
녹지지역 6
 
0.1%
노선상업지역 3
 
< 0.1%

용도지구코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9966 
UQG110
 
21
UQG120
 
7
UQI100
 
5
UQG100
 
1

Length

Max length6
Median length4
Mean length4.0068
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9966
99.7%
UQG110 21
 
0.2%
UQG120 7
 
0.1%
UQI100 5
 
0.1%
UQG100 1
 
< 0.1%

Length

2023-12-13T02:40:12.959372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:13.076654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9966
99.7%
uqg110 21
 
0.2%
uqg120 7
 
0.1%
uqi100 5
 
< 0.1%
uqg100 1
 
< 0.1%

용도지구명
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주차장정비지구
8837 
<NA>
 
700
주차정비지구
 
166
2종미관지구
 
154
4종미관지구
 
75
Other values (13)
 
68

Length

Max length8
Median length7
Mean length6.7442
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
주차장정비지구 8837
88.4%
<NA> 700
 
7.0%
주차정비지구 166
 
1.7%
2종미관지구 154
 
1.5%
4종미관지구 75
 
0.8%
중심지미관지구 21
 
0.2%
주차장지구 16
 
0.2%
역사문화미관지구 7
 
0.1%
방화지구 5
 
0.1%
주차지구 5
 
0.1%
Other values (8) 14
 
0.1%

Length

2023-12-13T02:40:13.208328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주차장정비지구 8837
88.4%
na 700
 
7.0%
주차정비지구 166
 
1.7%
2종미관지구 154
 
1.5%
4종미관지구 75
 
0.8%
중심지미관지구 21
 
0.2%
주차장지구 16
 
0.2%
역사문화미관지구 7
 
0.1%
주차지구 5
 
< 0.1%
방화지구 5
 
< 0.1%
Other values (8) 14
 
0.1%

건축구분코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.49
Minimum100
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:13.320558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1100
median100
Q3100
95-th percentile200
Maximum2000
Range1900
Interquartile range (IQR)0

Descriptive statistics

Standard deviation88.010877
Coefficient of variation (CV)0.73655433
Kurtosis145.80144
Mean119.49
Median Absolute Deviation (MAD)0
Skewness9.6681477
Sum1194900
Variance7745.9145
MonotonicityNot monotonic
2023-12-13T02:40:13.423017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
100 8900
89.0%
200 920
 
9.2%
700 98
 
1.0%
600 55
 
0.5%
300 12
 
0.1%
400 8
 
0.1%
2000 6
 
0.1%
500 1
 
< 0.1%
ValueCountFrequency (%)
100 8900
89.0%
200 920
 
9.2%
300 12
 
0.1%
400 8
 
0.1%
500 1
 
< 0.1%
600 55
 
0.5%
700 98
 
1.0%
2000 6
 
0.1%
ValueCountFrequency (%)
2000 6
 
0.1%
700 98
 
1.0%
600 55
 
0.5%
500 1
 
< 0.1%
400 8
 
0.1%
300 12
 
0.1%
200 920
 
9.2%
100 8900
89.0%

건축구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신축
8900 
증축
920 
용도변경
 
98
대수선
 
55
개축
 
12
Other values (3)
 
15

Length

Max length9
Median length2
Mean length2.0293
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
신축 8900
89.0%
증축 920
 
9.2%
용도변경 98
 
1.0%
대수선 55
 
0.5%
개축 12
 
0.1%
재축 8
 
0.1%
허가/신고사항변경 6
 
0.1%
이전 1
 
< 0.1%

Length

2023-12-13T02:40:13.561989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:13.671492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 8900
89.0%
증축 920
 
9.2%
용도변경 98
 
1.0%
대수선 55
 
0.5%
개축 12
 
0.1%
재축 8
 
0.1%
허가/신고사항변경 6
 
0.1%
이전 1
 
< 0.1%

대지면적
Real number (ℝ)

SKEWED 

Distinct4943
Distinct (%)49.5%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean670.80348
Minimum25.88
Maximum356566.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:13.800568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.88
5-th percentile66
Q195.39
median128.55
Q3208
95-th percentile975.5
Maximum356566.57
Range356540.69
Interquartile range (IQR)112.61

Descriptive statistics

Standard deviation9696.328
Coefficient of variation (CV)14.454797
Kurtosis918.81459
Mean670.80348
Median Absolute Deviation (MAD)42.85
Skewness29.373595
Sum6704680.8
Variance94018776
MonotonicityNot monotonic
2023-12-13T02:40:13.942204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119.0 58
 
0.6%
132.0 48
 
0.5%
93.0 46
 
0.5%
102.0 45
 
0.4%
106.0 40
 
0.4%
99.0 40
 
0.4%
109.0 40
 
0.4%
110.1 38
 
0.4%
122.0 38
 
0.4%
165.0 37
 
0.4%
Other values (4933) 9565
95.7%
ValueCountFrequency (%)
25.88 1
< 0.1%
26.0 1
< 0.1%
32.09 1
< 0.1%
38.2 1
< 0.1%
39.78 1
< 0.1%
41.24 1
< 0.1%
41.3 1
< 0.1%
43.0 2
< 0.1%
43.02 1
< 0.1%
43.32 1
< 0.1%
ValueCountFrequency (%)
356566.566 3
< 0.1%
268640.85 4
< 0.1%
262814.85 2
< 0.1%
184842.0 2
< 0.1%
143210.0 2
< 0.1%
69790.0 2
< 0.1%
44269.0 3
< 0.1%
39809.9 1
 
< 0.1%
20454.8 1
 
< 0.1%
18996.0 1
 
< 0.1%

건축면적
Real number (ℝ)

SKEWED 

Distinct5649
Distinct (%)56.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean179.556
Minimum7.33
Maximum53190.316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:14.093306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.33
5-th percentile37.73
Q153.22
median69.985
Q3110.655
95-th percentile444.43
Maximum53190.316
Range53182.986
Interquartile range (IQR)57.435

Descriptive statistics

Standard deviation1292.7557
Coefficient of variation (CV)7.1997351
Kurtosis1241.6607
Mean179.556
Median Absolute Deviation (MAD)21.865
Skewness33.302842
Sum1795200.9
Variance1671217.2
MonotonicityNot monotonic
2023-12-13T02:40:14.232087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
786.45 27
 
0.3%
343.5 20
 
0.2%
158.65 14
 
0.1%
49.14 12
 
0.1%
912.23 12
 
0.1%
66.24 10
 
0.1%
55.44 10
 
0.1%
45.0 10
 
0.1%
51.12 10
 
0.1%
66.0 9
 
0.1%
Other values (5639) 9864
98.6%
ValueCountFrequency (%)
7.33 1
< 0.1%
9.25 1
< 0.1%
17.22 1
< 0.1%
17.5 1
< 0.1%
18.39 1
< 0.1%
19.92 1
< 0.1%
20.1 1
< 0.1%
22.41 1
< 0.1%
22.64 1
< 0.1%
22.65 1
< 0.1%
ValueCountFrequency (%)
53190.316 1
 
< 0.1%
52897.686 2
< 0.1%
48053.68 1
 
< 0.1%
46609.39 1
 
< 0.1%
24260.48 4
< 0.1%
16393.0 1
 
< 0.1%
15263.0 1
 
< 0.1%
9745.75 1
 
< 0.1%
5633.6 4
< 0.1%
5562.59 1
 
< 0.1%

건폐율
Real number (ℝ)

SKEWED 

Distinct2199
Distinct (%)22.0%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean54.753041
Minimum0.9
Maximum654.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:14.375100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile43.2
Q149.72
median56.33
Q359.67
95-th percentile64.606
Maximum654.33
Range653.43
Interquartile range (IQR)9.95

Descriptive statistics

Standard deviation14.000761
Coefficient of variation (CV)0.25570745
Kurtosis885.94887
Mean54.753041
Median Absolute Deviation (MAD)3.65
Skewness23.253372
Sum547256.65
Variance196.0213
MonotonicityNot monotonic
2023-12-13T02:40:14.497936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.9 121
 
1.2%
49.8 105
 
1.1%
59.9 95
 
0.9%
59.98 94
 
0.9%
59.96 89
 
0.9%
59.97 86
 
0.9%
59.95 80
 
0.8%
59.93 79
 
0.8%
59.94 74
 
0.7%
59.86 72
 
0.7%
Other values (2189) 9100
91.0%
ValueCountFrequency (%)
0.9 1
< 0.1%
1.23 1
< 0.1%
2.89 1
< 0.1%
2.91 2
< 0.1%
3.08 1
< 0.1%
5.03 1
< 0.1%
5.34 1
< 0.1%
5.43 1
< 0.1%
5.98 1
< 0.1%
6.36 1
< 0.1%
ValueCountFrequency (%)
654.33 2
< 0.1%
498.0 1
< 0.1%
446.68 1
< 0.1%
419.49 1
< 0.1%
219.9 2
< 0.1%
193.26 1
< 0.1%
170.0 2
< 0.1%
166.12 1
< 0.1%
134.19 1
< 0.1%
119.68 1
< 0.1%

연면적
Real number (ℝ)

SKEWED 

Distinct7048
Distinct (%)70.5%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean655.47896
Minimum7.33
Maximum262324.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:14.627288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.33
5-th percentile105.921
Q1153.26
median221.74
Q3443.68
95-th percentile1690.242
Maximum262324.51
Range262317.18
Interquartile range (IQR)290.42

Descriptive statistics

Standard deviation4908.3948
Coefficient of variation (CV)7.4882568
Kurtosis2407.358
Mean655.47896
Median Absolute Deviation (MAD)86.06
Skewness46.05204
Sum6554134.2
Variance24092339
MonotonicityNot monotonic
2023-12-13T02:40:14.762747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4996.31 27
 
0.3%
1071.5 20
 
0.2%
199.8 17
 
0.2%
659.11 14
 
0.1%
2621.26 12
 
0.1%
149.85 11
 
0.1%
149.94 10
 
0.1%
149.96 10
 
0.1%
149.76 10
 
0.1%
198.72 10
 
0.1%
Other values (7038) 9858
98.6%
ValueCountFrequency (%)
7.33 1
< 0.1%
16.2 1
< 0.1%
17.5 1
< 0.1%
18.39 1
< 0.1%
23.76 1
< 0.1%
24.08 1
< 0.1%
24.71 1
< 0.1%
25.69 1
< 0.1%
26.08 1
< 0.1%
26.45 1
< 0.1%
ValueCountFrequency (%)
262324.51 1
 
< 0.1%
261424.62 2
< 0.1%
60127.59 1
 
< 0.1%
58296.3 1
 
< 0.1%
41911.17 1
 
< 0.1%
37697.03 4
< 0.1%
32119.47 1
 
< 0.1%
30285.99 3
< 0.1%
28864.94 4
< 0.1%
26861.95 2
< 0.1%

용적율산정연면적
Real number (ℝ)

MISSING 

Distinct320
Distinct (%)74.1%
Missing9568
Missing (%)95.7%
Infinite0
Infinite (%)0.0%
Mean1350.8079
Minimum17.5
Maximum26607.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:14.879348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.5
5-th percentile84.2425
Q1234.425
median487.265
Q31218.14
95-th percentile4133.95
Maximum26607.16
Range26589.66
Interquartile range (IQR)983.715

Descriptive statistics

Standard deviation2604.2955
Coefficient of variation (CV)1.9279539
Kurtosis41.434482
Mean1350.8079
Median Absolute Deviation (MAD)340.175
Skewness5.6104268
Sum583549.03
Variance6782354.8
MonotonicityNot monotonic
2023-12-13T02:40:15.003510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4133.95 13
 
0.1%
1078.18 6
 
0.1%
482.43 6
 
0.1%
659.77 5
 
0.1%
2212.36 5
 
0.1%
1218.14 5
 
0.1%
4066.18 5
 
0.1%
336.85 5
 
0.1%
3573.12 5
 
0.1%
2710.0 4
 
< 0.1%
Other values (310) 373
 
3.7%
(Missing) 9568
95.7%
ValueCountFrequency (%)
17.5 1
< 0.1%
18.39 1
< 0.1%
24.08 1
< 0.1%
24.71 1
< 0.1%
26.73 1
< 0.1%
39.51 1
< 0.1%
41.28 1
< 0.1%
46.16 1
< 0.1%
47.72 1
< 0.1%
52.59 1
< 0.1%
ValueCountFrequency (%)
26607.16 1
 
< 0.1%
22153.35 2
< 0.1%
14472.5 2
< 0.1%
10430.75 1
 
< 0.1%
10363.79 1
 
< 0.1%
9748.55 1
 
< 0.1%
7430.16 2
< 0.1%
6929.4 3
< 0.1%
6898.76 1
 
< 0.1%
5997.0 2
< 0.1%

용적률
Real number (ℝ)

SKEWED 

Distinct5676
Distinct (%)56.9%
Missing17
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean140.55087
Minimum0.9
Maximum10324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:15.129183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile78.848
Q199.865
median118.6
Q3170.16
95-th percentile240.58
Maximum10324
Range10323.1
Interquartile range (IQR)70.295

Descriptive statistics

Standard deviation118.14993
Coefficient of variation (CV)0.84062041
Kurtosis5534.4937
Mean140.55087
Median Absolute Deviation (MAD)24.65
Skewness64.683184
Sum1403119.4
Variance13959.406
MonotonicityNot monotonic
2023-12-13T02:40:15.273094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.8 32
 
0.3%
99.7 26
 
0.3%
99.9 25
 
0.2%
99.6 24
 
0.2%
99.0 22
 
0.2%
101.73 21
 
0.2%
99.92 20
 
0.2%
99.5 19
 
0.2%
99.1 19
 
0.2%
99.82 17
 
0.2%
Other values (5666) 9758
97.6%
(Missing) 17
 
0.2%
ValueCountFrequency (%)
0.9 1
< 0.1%
1.23 1
< 0.1%
2.89 1
< 0.1%
3.08 1
< 0.1%
5.03 1
< 0.1%
6.22 2
< 0.1%
6.36 1
< 0.1%
7.46 1
< 0.1%
9.0 1
< 0.1%
12.4 1
< 0.1%
ValueCountFrequency (%)
10324.0 1
< 0.1%
1879.26 1
< 0.1%
1001.22 1
< 0.1%
632.42 1
< 0.1%
595.27 2
< 0.1%
581.74 1
< 0.1%
529.31 1
< 0.1%
515.52 1
< 0.1%
488.59 1
< 0.1%
476.34 1
< 0.1%

주건축물수
Real number (ℝ)

SKEWED 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0752
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:15.400144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum33
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.81842039
Coefficient of variation (CV)0.76117968
Kurtosis577.77017
Mean1.0752
Median Absolute Deviation (MAD)0
Skewness20.863128
Sum10752
Variance0.66981194
MonotonicityNot monotonic
2023-12-13T02:40:15.497101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 9725
97.2%
2 172
 
1.7%
3 43
 
0.4%
4 23
 
0.2%
14 20
 
0.2%
6 4
 
< 0.1%
5 4
 
< 0.1%
9 3
 
< 0.1%
33 1
 
< 0.1%
16 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
ValueCountFrequency (%)
1 9725
97.2%
2 172
 
1.7%
3 43
 
0.4%
4 23
 
0.2%
5 4
 
< 0.1%
6 4
 
< 0.1%
7 1
 
< 0.1%
9 3
 
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
33 1
 
< 0.1%
32 1
 
< 0.1%
16 1
 
< 0.1%
14 20
0.2%
12 1
 
< 0.1%
11 1
 
< 0.1%
9 3
 
< 0.1%
7 1
 
< 0.1%
6 4
 
< 0.1%
5 4
 
< 0.1%

부속건축물동수
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)0.1%
Missing54
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean0.04082043
Minimum0
Maximum18
Zeros9753
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:15.912419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.42465813
Coefficient of variation (CV)10.403078
Kurtosis590.96526
Mean0.04082043
Median Absolute Deviation (MAD)0
Skewness20.439817
Sum406
Variance0.18033453
MonotonicityNot monotonic
2023-12-13T02:40:16.003154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9753
97.5%
1 111
 
1.1%
2 40
 
0.4%
3 21
 
0.2%
5 6
 
0.1%
7 4
 
< 0.1%
12 3
 
< 0.1%
4 3
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
(Missing) 54
 
0.5%
ValueCountFrequency (%)
0 9753
97.5%
1 111
 
1.1%
2 40
 
0.4%
3 21
 
0.2%
4 3
 
< 0.1%
5 6
 
0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
12 3
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
12 3
 
< 0.1%
8 2
 
< 0.1%
7 4
 
< 0.1%
6 2
 
< 0.1%
5 6
 
0.1%
4 3
 
< 0.1%
3 21
 
0.2%
2 40
 
0.4%
1 111
1.1%

주용도코드
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)1.4%
Missing7536
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean4338.099
Minimum1003
Maximum24000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:16.119034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1003
5-th percentile1003
Q11003
median1003
Q32003
95-th percentile17000
Maximum24000
Range22997
Interquartile range (IQR)1000

Descriptive statistics

Standard deviation6139.9812
Coefficient of variation (CV)1.4153622
Kurtosis0.81132354
Mean4338.099
Median Absolute Deviation (MAD)0
Skewness1.6027579
Sum10689076
Variance37699369
MonotonicityNot monotonic
2023-12-13T02:40:16.236793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1003 1503
 
15.0%
2003 264
 
2.6%
17000 211
 
2.1%
14000 83
 
0.8%
6000 60
 
0.6%
20000 50
 
0.5%
2002 47
 
0.5%
19000 44
 
0.4%
2000 42
 
0.4%
4000 31
 
0.3%
Other values (24) 129
 
1.3%
(Missing) 7536
75.4%
ValueCountFrequency (%)
1003 1503
15.0%
2000 42
 
0.4%
2002 47
 
0.5%
2003 264
 
2.6%
2007 1
 
< 0.1%
3000 26
 
0.3%
3001 3
 
< 0.1%
3005 2
 
< 0.1%
3011 1
 
< 0.1%
4000 31
 
0.3%
ValueCountFrequency (%)
24000 3
 
< 0.1%
20001 7
 
0.1%
20000 50
 
0.5%
19001 8
 
0.1%
19000 44
 
0.4%
18101 4
 
< 0.1%
17000 211
2.1%
16006 1
 
< 0.1%
15201 6
 
0.1%
15102 4
 
< 0.1%
Distinct89
Distinct (%)0.9%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T02:40:16.417334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.0778389
Min length2

Characters and Unicode

Total characters50753
Distinct characters128
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

Unique31 ?
Unique (%)0.3%

Sample

1st row다세대주택
2nd row근린생활시설
3rd row근린생활시설
4th row다가구주택
5th row다가구주택
ValueCountFrequency (%)
근린생활시설 3031
30.3%
주택 1895
19.0%
다가구용단독주택 1557
15.6%
다가구주택 1507
15.1%
단독주택 669
 
6.7%
다세대주택 264
 
2.6%
공장 211
 
2.1%
업무시설 83
 
0.8%
다가구용주택 82
 
0.8%
점포 75
 
0.8%
Other values (79) 621
 
6.2%
2023-12-13T02:40:16.753156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6125
12.1%
6109
12.0%
3451
 
6.8%
3436
 
6.8%
3431
 
6.8%
3193
 
6.3%
3184
 
6.3%
3103
 
6.1%
3103
 
6.1%
3096
 
6.1%
Other values (118) 12522
24.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50625
99.7%
Decimal Number 60
 
0.1%
Open Punctuation 34
 
0.1%
Close Punctuation 34
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6125
12.1%
6109
12.1%
3451
 
6.8%
3436
 
6.8%
3431
 
6.8%
3193
 
6.3%
3184
 
6.3%
3103
 
6.1%
3103
 
6.1%
3096
 
6.1%
Other values (113) 12394
24.5%
Decimal Number
ValueCountFrequency (%)
2 33
55.0%
1 26
43.3%
3 1
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50625
99.7%
Common 128
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6125
12.1%
6109
12.1%
3451
 
6.8%
3436
 
6.8%
3431
 
6.8%
3193
 
6.3%
3184
 
6.3%
3103
 
6.1%
3103
 
6.1%
3096
 
6.1%
Other values (113) 12394
24.5%
Common
ValueCountFrequency (%)
( 34
26.6%
) 34
26.6%
2 33
25.8%
1 26
20.3%
3 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50625
99.7%
ASCII 128
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6125
12.1%
6109
12.1%
3451
 
6.8%
3436
 
6.8%
3431
 
6.8%
3193
 
6.3%
3184
 
6.3%
3103
 
6.1%
3103
 
6.1%
3096
 
6.1%
Other values (113) 12394
24.5%
ASCII
ValueCountFrequency (%)
( 34
26.6%
) 34
26.6%
2 33
25.8%
1 26
20.3%
3 1
 
0.8%

세대수
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)3.4%
Missing9381
Missing (%)93.8%
Infinite0
Infinite (%)0.0%
Mean5.5282714
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:16.884092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q39
95-th percentile17
Maximum47
Range46
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.532817
Coefficient of variation (CV)1.0008222
Kurtosis5.8093064
Mean5.5282714
Median Absolute Deviation (MAD)2
Skewness1.7164631
Sum3422
Variance30.612064
MonotonicityNot monotonic
2023-12-13T02:40:17.000505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 227
 
2.3%
2 61
 
0.6%
9 50
 
0.5%
3 45
 
0.4%
8 43
 
0.4%
6 33
 
0.3%
7 21
 
0.2%
17 20
 
0.2%
10 18
 
0.2%
4 16
 
0.2%
Other values (11) 85
 
0.9%
(Missing) 9381
93.8%
ValueCountFrequency (%)
1 227
2.3%
2 61
 
0.6%
3 45
 
0.4%
4 16
 
0.2%
5 8
 
0.1%
6 33
 
0.3%
7 21
 
0.2%
8 43
 
0.4%
9 50
 
0.5%
10 18
 
0.2%
ValueCountFrequency (%)
47 1
 
< 0.1%
36 1
 
< 0.1%
19 10
0.1%
18 6
 
0.1%
17 20
0.2%
16 10
0.1%
15 10
0.1%
14 4
 
< 0.1%
13 14
0.1%
12 15
0.1%

호수
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)31.0%
Missing9971
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean4.4827586
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:17.114743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q38
95-th percentile9
Maximum13
Range12
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.4807705
Coefficient of variation (CV)0.77647958
Kurtosis-0.74193041
Mean4.4827586
Median Absolute Deviation (MAD)3
Skewness0.57797938
Sum130
Variance12.115764
MonotonicityNot monotonic
2023-12-13T02:40:17.218878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 10
 
0.1%
8 6
 
0.1%
4 3
 
< 0.1%
7 2
 
< 0.1%
2 2
 
< 0.1%
9 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
13 1
 
< 0.1%
(Missing) 9971
99.7%
ValueCountFrequency (%)
1 10
0.1%
2 2
 
< 0.1%
3 2
 
< 0.1%
4 3
 
< 0.1%
5 1
 
< 0.1%
7 2
 
< 0.1%
8 6
0.1%
9 2
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
9 2
 
< 0.1%
8 6
0.1%
7 2
 
< 0.1%
5 1
 
< 0.1%
4 3
 
< 0.1%
3 2
 
< 0.1%
2 2
 
< 0.1%
1 10
0.1%

가구수
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)0.5%
Missing5940
Missing (%)59.4%
Infinite0
Infinite (%)0.0%
Mean4.4541872
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:17.319845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile9
Maximum47
Range46
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.060146
Coefficient of variation (CV)0.6870268
Kurtosis65.488271
Mean4.4541872
Median Absolute Deviation (MAD)1
Skewness5.5657512
Sum18084
Variance9.3644934
MonotonicityNot monotonic
2023-12-13T02:40:17.458546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 1142
 
11.4%
5 794
 
7.9%
4 570
 
5.7%
1 377
 
3.8%
6 304
 
3.0%
7 290
 
2.9%
2 255
 
2.5%
8 110
 
1.1%
10 55
 
0.5%
9 42
 
0.4%
Other values (11) 121
 
1.2%
(Missing) 5940
59.4%
ValueCountFrequency (%)
1 377
 
3.8%
2 255
 
2.5%
3 1142
11.4%
4 570
5.7%
5 794
7.9%
6 304
 
3.0%
7 290
 
2.9%
8 110
 
1.1%
9 42
 
0.4%
10 55
 
0.5%
ValueCountFrequency (%)
47 7
 
0.1%
24 1
 
< 0.1%
19 4
 
< 0.1%
18 6
 
0.1%
17 4
 
< 0.1%
16 16
0.2%
15 5
 
0.1%
14 12
0.1%
13 5
 
0.1%
12 19
0.2%

총주차수
Real number (ℝ)

MISSING  SKEWED 

Distinct82
Distinct (%)2.2%
Missing6335
Missing (%)63.3%
Infinite0
Infinite (%)0.0%
Mean8.0769441
Minimum1
Maximum1142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:40:17.591495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile25.8
Maximum1142
Range1141
Interquartile range (IQR)3

Descriptive statistics

Standard deviation36.272923
Coefficient of variation (CV)4.4909217
Kurtosis778.18447
Mean8.0769441
Median Absolute Deviation (MAD)1
Skewness25.639983
Sum29602
Variance1315.725
MonotonicityNot monotonic
2023-12-13T02:40:17.736597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 792
 
7.9%
3 629
 
6.3%
1 519
 
5.2%
4 487
 
4.9%
5 324
 
3.2%
6 175
 
1.8%
8 86
 
0.9%
7 83
 
0.8%
10 59
 
0.6%
9 52
 
0.5%
Other values (72) 459
 
4.6%
(Missing) 6335
63.3%
ValueCountFrequency (%)
1 519
5.2%
2 792
7.9%
3 629
6.3%
4 487
4.9%
5 324
3.2%
6 175
 
1.8%
7 83
 
0.8%
8 86
 
0.9%
9 52
 
0.5%
10 59
 
0.6%
ValueCountFrequency (%)
1142 1
 
< 0.1%
1138 2
< 0.1%
401 1
 
< 0.1%
169 1
 
< 0.1%
165 3
< 0.1%
164 3
< 0.1%
153 2
< 0.1%
150 1
 
< 0.1%
139 1
 
< 0.1%
137 4
< 0.1%

착공예정일
Text

MISSING 

Distinct1484
Distinct (%)52.3%
Missing7162
Missing (%)71.6%
Memory size156.2 KiB
2023-12-13T02:40:18.056149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9992953
Min length9

Characters and Unicode

Total characters28378
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

Unique810 ?
Unique (%)28.5%

Sample

1st row1992-03-07
2nd row1997-02-19
3rd row1995-05-06
4th row1991-05-07
5th row1993-03-26
ValueCountFrequency (%)
1997-04-07 14
 
0.5%
1993-04-20 14
 
0.5%
1994-06-20 11
 
0.4%
1995-09-25 11
 
0.4%
1995-05-06 10
 
0.4%
1993-02-16 10
 
0.4%
1994-08-26 10
 
0.4%
1995-05-03 9
 
0.3%
1995-06-29 9
 
0.3%
1996-09-10 9
 
0.3%
Other values (1474) 2731
96.2%
2023-12-13T02:40:18.557119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 5798
20.4%
- 5674
20.0%
1 4760
16.8%
0 4066
14.3%
2 1925
 
6.8%
3 1280
 
4.5%
5 1145
 
4.0%
4 998
 
3.5%
6 971
 
3.4%
8 935
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22704
80.0%
Dash Punctuation 5674
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 5798
25.5%
1 4760
21.0%
0 4066
17.9%
2 1925
 
8.5%
3 1280
 
5.6%
5 1145
 
5.0%
4 998
 
4.4%
6 971
 
4.3%
8 935
 
4.1%
7 826
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 5674
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 5798
20.4%
- 5674
20.0%
1 4760
16.8%
0 4066
14.3%
2 1925
 
6.8%
3 1280
 
4.5%
5 1145
 
4.0%
4 998
 
3.5%
6 971
 
3.4%
8 935
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 5798
20.4%
- 5674
20.0%
1 4760
16.8%
0 4066
14.3%
2 1925
 
6.8%
3 1280
 
4.5%
5 1145
 
4.0%
4 998
 
3.5%
6 971
 
3.4%
8 935
 
3.3%

착공연기일
Date

MISSING 

Distinct6
Distinct (%)100.0%
Missing9994
Missing (%)99.9%
Memory size156.2 KiB
Minimum1989-04-24 00:00:00
Maximum1998-12-02 00:00:00
2023-12-13T02:40:18.682426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:40:18.809705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

실제착공일
Text

MISSING 

Distinct2548
Distinct (%)37.8%
Missing3259
Missing (%)32.6%
Memory size156.2 KiB
2023-12-13T02:40:19.227064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters67410
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

Unique1105 ?
Unique (%)16.4%

Sample

1st row1992-10-03
2nd row1991-11-01
3rd row1992-03-07
4th row1997-07-13
5th row1990-07-09
ValueCountFrequency (%)
1987-07-10 21
 
0.3%
1993-03-16 20
 
0.3%
1993-04-08 20
 
0.3%
1993-03-15 20
 
0.3%
1993-04-20 18
 
0.3%
1993-03-11 17
 
0.3%
1993-03-22 16
 
0.2%
1993-03-17 16
 
0.2%
1991-07-16 16
 
0.2%
1995-05-03 16
 
0.2%
Other values (2538) 6561
97.3%
2023-12-13T02:40:19.827127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 13589
20.2%
- 13482
20.0%
1 11951
17.7%
0 9940
14.7%
2 4779
 
7.1%
3 3183
 
4.7%
8 2498
 
3.7%
4 2256
 
3.3%
5 2068
 
3.1%
6 1872
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53928
80.0%
Dash Punctuation 13482
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 13589
25.2%
1 11951
22.2%
0 9940
18.4%
2 4779
 
8.9%
3 3183
 
5.9%
8 2498
 
4.6%
4 2256
 
4.2%
5 2068
 
3.8%
6 1872
 
3.5%
7 1792
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 13482
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67410
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 13589
20.2%
- 13482
20.0%
1 11951
17.7%
0 9940
14.7%
2 4779
 
7.1%
3 3183
 
4.7%
8 2498
 
3.7%
4 2256
 
3.3%
5 2068
 
3.1%
6 1872
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67410
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 13589
20.2%
- 13482
20.0%
1 11951
17.7%
0 9940
14.7%
2 4779
 
7.1%
3 3183
 
4.7%
8 2498
 
3.7%
4 2256
 
3.3%
5 2068
 
3.1%
6 1872
 
2.8%
Distinct3246
Distinct (%)32.7%
Missing82
Missing (%)0.8%
Memory size156.2 KiB
2023-12-13T02:40:20.179654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9995967
Min length8

Characters and Unicode

Total characters99176
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

Unique1224 ?
Unique (%)12.3%

Sample

1st row1992-10-02
2nd row1987-09-10
3rd row1991-10-26
4th row1991-03-16
5th row1991-07-01
ValueCountFrequency (%)
1991-07-04 53
 
0.5%
1991-07-01 40
 
0.4%
1992-12-28 27
 
0.3%
1992-12-30 26
 
0.3%
1993-07-02 24
 
0.2%
1993-07-05 24
 
0.2%
1992-12-23 24
 
0.2%
1992-10-02 23
 
0.2%
1993-01-04 22
 
0.2%
1987-06-10 21
 
0.2%
Other values (3236) 9634
97.1%
2023-12-13T02:40:20.742343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 19836
20.0%
9 19107
19.3%
1 17785
17.9%
0 14994
15.1%
2 7249
 
7.3%
8 5288
 
5.3%
3 3877
 
3.9%
4 2904
 
2.9%
6 2746
 
2.8%
7 2705
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79340
80.0%
Dash Punctuation 19836
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 19107
24.1%
1 17785
22.4%
0 14994
18.9%
2 7249
 
9.1%
8 5288
 
6.7%
3 3877
 
4.9%
4 2904
 
3.7%
6 2746
 
3.5%
7 2705
 
3.4%
5 2685
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 19836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 19836
20.0%
9 19107
19.3%
1 17785
17.9%
0 14994
15.1%
2 7249
 
7.3%
8 5288
 
5.3%
3 3877
 
3.9%
4 2904
 
2.9%
6 2746
 
2.8%
7 2705
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 19836
20.0%
9 19107
19.3%
1 17785
17.9%
0 14994
15.1%
2 7249
 
7.3%
8 5288
 
5.3%
3 3877
 
3.9%
4 2904
 
2.9%
6 2746
 
2.8%
7 2705
 
2.7%

사용승인일
Text

MISSING 

Distinct2899
Distinct (%)34.6%
Missing1630
Missing (%)16.3%
Memory size156.2 KiB
2023-12-13T02:40:21.166706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters83700
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

Unique1114 ?
Unique (%)13.3%

Sample

1st row1993-04-06
2nd row1987-12-00
3rd row1992-01-30
4th row1991-07-18
5th row1992-07-07
ValueCountFrequency (%)
1993-09-28 31
 
0.4%
1993-12-24 25
 
0.3%
1992-12-31 25
 
0.3%
1991-12-12 25
 
0.3%
1991-07-22 24
 
0.3%
1994-05-20 21
 
0.3%
1991-07-18 18
 
0.2%
1993-10-15 18
 
0.2%
1989-12-29 17
 
0.2%
1993-01-05 17
 
0.2%
Other values (2889) 8149
97.4%
2023-12-13T02:40:21.757058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16750
20.0%
- 16740
20.0%
9 16706
20.0%
0 11114
13.3%
2 7167
8.6%
8 3920
 
4.7%
3 2800
 
3.3%
7 2310
 
2.8%
4 2302
 
2.8%
6 2090
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66960
80.0%
Dash Punctuation 16740
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16750
25.0%
9 16706
24.9%
0 11114
16.6%
2 7167
10.7%
8 3920
 
5.9%
3 2800
 
4.2%
7 2310
 
3.4%
4 2302
 
3.4%
6 2090
 
3.1%
5 1801
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 16740
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16750
20.0%
- 16740
20.0%
9 16706
20.0%
0 11114
13.3%
2 7167
8.6%
8 3920
 
4.7%
3 2800
 
3.3%
7 2310
 
2.8%
4 2302
 
2.8%
6 2090
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16750
20.0%
- 16740
20.0%
9 16706
20.0%
0 11114
13.3%
2 7167
8.6%
8 3920
 
4.7%
3 2800
 
3.3%
7 2310
 
2.8%
4 2302
 
2.8%
6 2090
 
2.5%

생성일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-15 00:00:00
Maximum2022-12-15 00:00:00
2023-12-13T02:40:21.903105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:40:22.026515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

연번대지위치시군구코드법정동코드대지구분코드건물명지목코드지목명용도지역코드용도지역명용도지구코드용도지구명건축구분코드건축구분명대지면적건축면적건폐율연면적용적율산정연면적용적률주건축물수부속건축물동수주용도코드주용도명세대수호수가구수총주차수착공예정일착공연기일실제착공일건축허가일사용승인일생성일자
90309031서울특별시 성동구 사근동 309-80112001120010600030980<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축308.27158.6551.46659.11<NA>175.12102003다세대주택17<NA><NA>5<NA><NA>1992-10-031992-10-021993-04-062022-12-15
24822483서울특별시 성동구 성수동1가 44711200112001140004470<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축202.095.5547.3388.23<NA>131.7910<NA>근린생활시설<NA><NA><NA>3<NA><NA><NA>1987-09-101987-12-002022-12-15
24942495서울특별시 성동구 성수동1가 559-211200112001140005592<NA>8대지UQA120일반주거지역<NA>주차장정비지구200증축47.4528.4659.97113.84<NA>179.9310<NA>근린생활시설<NA><NA><NA><NA><NA><NA>1991-11-011991-10-261992-01-302022-12-15
37873788서울특별시 성동구 용답동 108-111200112001220001081<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축82.3149.2159.78143.56229.24114.62101003다가구주택<NA><NA>5<NA><NA><NA><NA>1991-03-161991-07-182022-12-15
24082409서울특별시 성동구 성수동1가 16911200112001140001690<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축183.9283.6354.92249.85<NA>90.65101003다가구주택<NA><NA>611992-03-07<NA>1992-03-071991-07-011992-07-072022-12-15
971972서울특별시 성동구 금호동1가 280-611200112001090002806<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축183.7384.5546.01249.45<NA>89.7210<NA>주택<NA><NA><NA><NA><NA><NA><NA>1990-04-12<NA>2022-12-15
61476148서울특별시 성동구 성수동2가 339-1191120011200115000339119<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축142.082.4658.07296.34<NA>151.2610<NA>다가구용단독주택<NA><NA>92<NA><NA>1997-07-131996-06-271997-04-242022-12-15
99439944서울특별시 성동구 성수동2가 5-651120011200115000565<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축106.157.5254.21179.76<NA>108.4210<NA>주택<NA><NA><NA><NA><NA><NA><NA>1990-06-041990-02-072022-12-15
33143315서울특별시 성동구 성수동2가 315-48112001120011500031548<NA>8대지UQA330준공업지역<NA>주차장정비지구200증축139.569.5749.87268.63<NA>135.3410<NA>다가구용단독주택<NA><NA>42<NA><NA><NA><NA>1992-10-302022-12-15
448449서울특별시 성동구 성수동2가 277-35112001120011500027735<NA>8대지UQA330준공업지역<NA>주차장정비지구100신축1213.9727.4859.937165.39<NA>393.6810<NA>일반공장(도시형공장)<NA><NA><NA>32<NA><NA>1990-07-091989-04-111995-09-042022-12-15
연번대지위치시군구코드법정동코드대지구분코드건물명지목코드지목명용도지역코드용도지역명용도지구코드용도지구명건축구분코드건축구분명대지면적건축면적건폐율연면적용적율산정연면적용적률주건축물수부속건축물동수주용도코드주용도명세대수호수가구수총주차수착공예정일착공연기일실제착공일건축허가일사용승인일생성일자
1006310064서울특별시 성동구 하왕십리동 1000-53011200112001020001000530<NA>8대지UQA100주거지역<NA>주차장정비지구100신축167.6582.8549.4214.29<NA>98.21<NA><NA>주택<NA><NA><NA><NA><NA><NA>1987-07-151987-06-24<NA>2022-12-15
41424143서울특별시 성동구 용답동 43-41120011200122000434<NA>8대지UQA100주거지역<NA>주차장정비지구100신축125.662.6449.87208.14<NA>99.7410<NA>주택<NA><NA><NA><NA><NA><NA><NA>1988-04-20<NA>2022-12-15
65396540서울특별시 성동구 성수동1가 656-6231120011200114000656623<NA>8대지UQA330준공업지역<NA>주차장정비지구100신축56.2633.7159.91101.13<NA>119.8310<NA>다가구용단독주택<NA><NA>3<NA>1993-04-20<NA>1993-04-201993-04-081994-05-202022-12-15
34283429서울특별시 성동구 송정동 66-122112001120011800066122<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축109.062.457.25187.2<NA>114.510<NA>다가구용단독주택<NA><NA><NA><NA><NA><NA><NA>1991-02-261991-06-282022-12-15
38273828서울특별시 성동구 용답동 134-111200112001220001341<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축65.042.0164.63100.13<NA>98.2710<NA>근린생활시설<NA><NA>3<NA><NA><NA>1992-07-071992-06-181992-12-042022-12-15
81508151서울특별시 성동구 옥수동 523-811200112001130005238<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축1108.4553.0949.893954.842212.36199.59105000문화및집회시설<NA><NA><NA>22<NA><NA>1991-08-251991-07-161999-12-092022-12-15
52765277서울특별시 성동구 홍익동 56711200112001030005670<NA>8대지UQA100주거지역<NA>주차장정비지구100신축79.344.255.73189.4<NA>165.1910<NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA>1988-04-111988-08-162022-12-15
47084709서울특별시 성동구 행당동 128-105211200112001070001281052<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축72.5136.053.04109.81<NA>100.6710<NA>주택<NA><NA><NA><NA><NA><NA><NA>1990-05-041991-04-092022-12-15
70037004서울특별시 성동구 성수동2가 331-24112001120011500033124<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축144.585.9659.48296.66<NA>153.0210<NA>다가구용단독주택<NA><NA>721995-03-17<NA>1995-03-161995-03-171995-06-192022-12-15
89398940서울특별시 성동구 하왕십리동 712-411200112001020007124<NA>8대지UQA120일반주거지역<NA>주차장정비지구100신축93.054.5258.62149.02<NA>105.19101003다가구주택<NA><NA>3<NA><NA><NA>1993-06-241993-04-201993-11-172022-12-15