Overview

Dataset statistics

Number of variables21
Number of observations10000
Missing cells21154
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 MiB
Average record size in memory186.0 B

Variable types

Numeric9
Categorical4
Text6
DateTime2

Dataset

Description시스템등록번호,시군구코드,법정동코드,자치구명,법정동명,지번구분,본번,부번,주소,중개업등록번호,중개업자명,사업자상호,전화번호,상태구분,행정처분 시작일,행정처분 종료일,조회 개수,도로명코드,건물,건물 본번,건물 부번
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15550/S/1/datasetView.do

Alerts

지번구분 is highly imbalanced (99.1%)Imbalance
상태구분 is highly imbalanced (97.9%)Imbalance
건물 is highly imbalanced (90.9%)Imbalance
전화번호 has 965 (9.7%) missing valuesMissing
행정처분 시작일 has 9989 (99.9%) missing valuesMissing
행정처분 종료일 has 9989 (99.9%) missing valuesMissing
건물 부번 has 203 (2.0%) missing valuesMissing
시스템등록번호 is highly skewed (γ1 = 55.54901036)Skewed
시군구코드 is highly skewed (γ1 = 74.2236707)Skewed
부번 has 2625 (26.2%) zerosZeros
건물 부번 has 8912 (89.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:11:54.215721
Analysis finished2024-05-10 23:11:59.351314
Duration5.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시스템등록번호
Real number (ℝ)

SKEWED 

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1479639 × 1014
Minimum1.1110198 × 1014
Maximum4.5113202 × 1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:11:59.660179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110198 × 1014
5-th percentile1.1170201 × 1014
Q11.1305201 × 1014
median1.1500202 × 1014
Q31.1650202 × 1014
95-th percentile1.1710202 × 1014
Maximum4.5113202 × 1014
Range3.4003004 × 1014
Interquartile range (IQR)3.450013 × 1012

Descriptive statistics

Standard deviation4.9023901 × 1012
Coefficient of variation (CV)0.04270509
Kurtosis3645.7391
Mean1.1479639 × 1014
Median Absolute Deviation (MAD)1.799992 × 1012
Skewness55.54901
Sum1.1479639 × 1018
Variance2.4033429 × 1025
MonotonicityNot monotonic
2024-05-10T23:12:00.108916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116802010000230 2
 
< 0.1%
116802022000682 1
 
< 0.1%
112002020000019 1
 
< 0.1%
115902002000254 1
 
< 0.1%
111702021000122 1
 
< 0.1%
113052019000025 1
 
< 0.1%
114102021000004 1
 
< 0.1%
116502014000147 1
 
< 0.1%
113052024000021 1
 
< 0.1%
113802009000313 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
111101984000002 1
< 0.1%
111101984000045 1
< 0.1%
111101984000154 1
< 0.1%
111101984000162 1
< 0.1%
111101986000137 1
< 0.1%
111101987000048 1
< 0.1%
111101988000020 1
< 0.1%
111101988000038 1
< 0.1%
111101988000152 1
< 0.1%
111101989000192 1
< 0.1%
ValueCountFrequency (%)
451132023000073 1
< 0.1%
416302003000278 1
< 0.1%
117402024000112 1
< 0.1%
117402024000110 1
< 0.1%
117402024000109 1
< 0.1%
117402024000108 1
< 0.1%
117402024000107 1
< 0.1%
117402024000105 1
< 0.1%
117402024000102 1
< 0.1%
117402024000100 1
< 0.1%

시군구코드
Real number (ℝ)

SKEWED 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11477.04
Minimum11110
Maximum52113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:00.617540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11170
Q111305
median11500
Q311650
95-th percentile11710
Maximum52113
Range41003
Interquartile range (IQR)345

Descriptive statistics

Standard deviation448.80203
Coefficient of variation (CV)0.039104336
Kurtosis6722.592
Mean11477.04
Median Absolute Deviation (MAD)180
Skewness74.223671
Sum1.147704 × 108
Variance201423.27
MonotonicityNot monotonic
2024-05-10T23:12:01.140528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
11680 1153
 
11.5%
11650 736
 
7.4%
11710 640
 
6.4%
11500 501
 
5.0%
11740 493
 
4.9%
11440 488
 
4.9%
11380 444
 
4.4%
11560 439
 
4.4%
11215 374
 
3.7%
11470 365
 
3.6%
Other values (16) 4367
43.7%
ValueCountFrequency (%)
11110 201
2.0%
11140 240
2.4%
11170 346
3.5%
11200 323
3.2%
11215 374
3.7%
11230 359
3.6%
11260 298
3.0%
11290 308
3.1%
11305 243
2.4%
11320 199
2.0%
ValueCountFrequency (%)
52113 1
 
< 0.1%
11740 493
4.9%
11710 640
6.4%
11680 1153
11.5%
11650 736
7.4%
11620 361
 
3.6%
11590 336
 
3.4%
11560 439
 
4.4%
11545 277
 
2.8%
11530 305
 
3.0%

법정동코드
Real number (ℝ)

Distinct390
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1472964 × 109
Minimum1.1110101 × 109
Maximum1.174011 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:01.626767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110101 × 109
5-th percentile1.1170109 × 109
Q11.1305101 × 109
median1.1500103 × 109
Q31.1650108 × 109
95-th percentile1.1710114 × 109
Maximum1.174011 × 109
Range63000900
Interquartile range (IQR)34500700

Descriptive statistics

Standard deviation19051063
Coefficient of variation (CV)0.01660518
Kurtosis-1.2473972
Mean1.1472964 × 109
Median Absolute Deviation (MAD)17999800
Skewness-0.28214162
Sum1.1472964 × 1013
Variance3.6294301 × 1014
MonotonicityNot monotonic
2024-05-10T23:12:02.160549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1168010100 332
 
3.3%
1165010800 275
 
2.8%
1162010200 183
 
1.8%
1162010100 172
 
1.7%
1150010300 164
 
1.6%
1147010100 163
 
1.6%
1135010500 155
 
1.6%
1168010600 154
 
1.5%
1165010100 148
 
1.5%
1153010200 140
 
1.4%
Other values (380) 8114
81.1%
ValueCountFrequency (%)
1111010100 2
< 0.1%
1111010200 1
 
< 0.1%
1111010400 1
 
< 0.1%
1111010500 1
 
< 0.1%
1111010600 2
< 0.1%
1111010800 3
< 0.1%
1111011000 2
< 0.1%
1111011100 4
< 0.1%
1111011400 2
< 0.1%
1111011500 2
< 0.1%
ValueCountFrequency (%)
1174011000 11
 
0.1%
1174010900 93
0.9%
1174010800 123
1.2%
1174010700 38
 
0.4%
1174010600 39
 
0.4%
1174010500 70
0.7%
1174010300 28
 
0.3%
1174010200 56
0.6%
1174010100 37
 
0.4%
1171011400 29
 
0.3%

자치구명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
1152 
서초구
734 
송파구
 
639
강서구
 
501
강동구
 
493
Other values (21)
6481 

Length

Max length4
Median length3
Mean length3.0823
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강남구
2nd row중구
3rd row동작구
4th row서초구
5th row영등포구

Common Values

ValueCountFrequency (%)
강남구 1152
 
11.5%
서초구 734
 
7.3%
송파구 639
 
6.4%
강서구 501
 
5.0%
강동구 493
 
4.9%
마포구 488
 
4.9%
은평구 444
 
4.4%
영등포구 439
 
4.4%
광진구 374
 
3.7%
양천구 365
 
3.6%
Other values (16) 4371
43.7%

Length

2024-05-10T23:12:02.816811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 1152
 
11.5%
서초구 734
 
7.3%
송파구 639
 
6.4%
강서구 501
 
5.0%
강동구 493
 
4.9%
마포구 488
 
4.9%
은평구 444
 
4.4%
영등포구 439
 
4.4%
광진구 374
 
3.7%
양천구 365
 
3.6%
Other values (16) 4371
43.7%

법정동명
Text

Distinct393
Distinct (%)3.9%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2024-05-10T23:12:03.595480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1754404
Min length2

Characters and Unicode

Total characters31729
Distinct characters195
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.5%

Sample

1st row압구정동
2nd row황학동
3rd row본동
4th row서초동
5th row신길동
ValueCountFrequency (%)
역삼동 331
 
3.3%
서초동 275
 
2.8%
신림동 183
 
1.8%
봉천동 171
 
1.7%
화곡동 163
 
1.6%
신정동 162
 
1.6%
상계동 155
 
1.6%
대치동 154
 
1.5%
방배동 150
 
1.5%
구로동 138
 
1.4%
Other values (383) 8110
81.2%
2024-05-10T23:12:05.013029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9860
31.1%
가 1032
 
3.3%
신 931
 
2.9%
삼 513
 
1.6%
곡 477
 
1.5%
산 448
 
1.4%
성 426
 
1.3%
정 390
 
1.2%
방 382
 
1.2%
역 368
 
1.2%
Other values (185) 16902
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30987
97.7%
Decimal Number 742
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9860
31.8%
가 1032
 
3.3%
신 931
 
3.0%
삼 513
 
1.7%
곡 477
 
1.5%
산 448
 
1.4%
성 426
 
1.4%
정 390
 
1.3%
방 382
 
1.2%
역 368
 
1.2%
Other values (177) 16160
52.2%
Decimal Number
ValueCountFrequency (%)
1 208
28.0%
2 199
26.8%
3 122
16.4%
5 73
 
9.8%
4 72
 
9.7%
6 39
 
5.3%
7 19
 
2.6%
8 10
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30987
97.7%
Common 742
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9860
31.8%
가 1032
 
3.3%
신 931
 
3.0%
삼 513
 
1.7%
곡 477
 
1.5%
산 448
 
1.4%
성 426
 
1.4%
정 390
 
1.3%
방 382
 
1.2%
역 368
 
1.2%
Other values (177) 16160
52.2%
Common
ValueCountFrequency (%)
1 208
28.0%
2 199
26.8%
3 122
16.4%
5 73
 
9.8%
4 72
 
9.7%
6 39
 
5.3%
7 19
 
2.6%
8 10
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30987
97.7%
ASCII 742
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9860
31.8%
가 1032
 
3.3%
신 931
 
3.0%
삼 513
 
1.7%
곡 477
 
1.5%
산 448
 
1.4%
성 426
 
1.4%
정 390
 
1.3%
방 382
 
1.2%
역 368
 
1.2%
Other values (177) 16160
52.2%
ASCII
ValueCountFrequency (%)
1 208
28.0%
2 199
26.8%
3 122
16.4%
5 73
 
9.8%
4 72
 
9.7%
6 39
 
5.3%
7 19
 
2.6%
8 10
 
1.3%

지번구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9988 
<NA>
 
10
2
 
2

Length

Max length4
Median length1
Mean length1.003
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9988
99.9%
<NA> 10
 
0.1%
2 2
 
< 0.1%

Length

2024-05-10T23:12:05.679007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:12:06.111960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9988
99.9%
na 10
 
0.1%
2 2
 
< 0.1%

본번
Real number (ℝ)

Distinct1404
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean469.6713
Minimum0
Maximum4958
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:06.630133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q1125
median341
Q3693
95-th percentile1332.25
Maximum4958
Range4958
Interquartile range (IQR)568

Descriptive statistics

Standard deviation470.23622
Coefficient of variation (CV)1.0012028
Kurtosis18.060775
Mean469.6713
Median Absolute Deviation (MAD)260.5
Skewness2.8307866
Sum4696713
Variance221122.1
MonotonicityNot monotonic
2024-05-10T23:12:07.396093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 57
 
0.6%
20 44
 
0.4%
825 37
 
0.4%
19 36
 
0.4%
98 36
 
0.4%
18 36
 
0.4%
50 35
 
0.4%
2 35
 
0.4%
27 34
 
0.3%
10 34
 
0.3%
Other values (1394) 9616
96.2%
ValueCountFrequency (%)
0 25
0.2%
1 57
0.6%
2 35
0.4%
3 28
0.3%
4 25
0.2%
5 31
0.3%
6 11
 
0.1%
7 25
0.2%
8 27
0.3%
9 32
0.3%
ValueCountFrequency (%)
4958 1
 
< 0.1%
4955 1
 
< 0.1%
4950 8
0.1%
4945 1
 
< 0.1%
4937 1
 
< 0.1%
4934 1
 
< 0.1%
4921 1
 
< 0.1%
4780 2
 
< 0.1%
4765 1
 
< 0.1%
4759 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct350
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.4291
Minimum0
Maximum2181
Zeros2625
Zeros (%)26.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:07.915810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q320
95-th percentile95
Maximum2181
Range2181
Interquartile range (IQR)20

Descriptive statistics

Standard deviation80.122008
Coefficient of variation (CV)3.2797773
Kurtosis210.08632
Mean24.4291
Median Absolute Deviation (MAD)5
Skewness11.774607
Sum244291
Variance6419.5361
MonotonicityNot monotonic
2024-05-10T23:12:08.444842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2625
26.2%
1 898
 
9.0%
2 485
 
4.9%
3 419
 
4.2%
4 340
 
3.4%
5 317
 
3.2%
6 290
 
2.9%
8 237
 
2.4%
7 227
 
2.3%
9 191
 
1.9%
Other values (340) 3971
39.7%
ValueCountFrequency (%)
0 2625
26.2%
1 898
 
9.0%
2 485
 
4.9%
3 419
 
4.2%
4 340
 
3.4%
5 317
 
3.2%
6 290
 
2.9%
7 227
 
2.3%
8 237
 
2.4%
9 191
 
1.9%
ValueCountFrequency (%)
2181 1
< 0.1%
2150 1
< 0.1%
1738 1
< 0.1%
1539 1
< 0.1%
1503 1
< 0.1%
1483 1
< 0.1%
1406 1
< 0.1%
1312 1
< 0.1%
1268 1
< 0.1%
1130 1
< 0.1%

주소
Text

Distinct9825
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:12:09.517004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length55
Mean length32.4284
Min length16

Characters and Unicode

Total characters324284
Distinct characters613
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9684 ?
Unique (%)96.8%

Sample

1st row서울특별시 강남구 압구정로29길 71 1층 105호(압구정동, 점포4동)
2nd row서울특별시 중구 난계로11길 8 1층
3rd row서울특별시 동작구 노량진로 252 (본동)
4th row서울특별시 서초구 효령로 429 , 111호(서초동, 강남 삼부르네상스시티)
5th row서울특별시 영등포구 가마산로 466 104호
ValueCountFrequency (%)
서울특별시 10002
 
16.8%
1층 1697
 
2.8%
강남구 1152
 
1.9%
887
 
1.5%
서초구 731
 
1.2%
상가동 644
 
1.1%
송파구 639
 
1.1%
강서구 504
 
0.8%
강동구 496
 
0.8%
마포구 486
 
0.8%
Other values (11862) 42450
71.1%
2024-05-10T23:12:11.302779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50214
 
15.5%
1 18279
 
5.6%
동 12945
 
4.0%
서 12587
 
3.9%
구 10754
 
3.3%
로 10519
 
3.2%
시 10481
 
3.2%
울 10077
 
3.1%
특 10007
 
3.1%
별 10005
 
3.1%
Other values (603) 168416
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191348
59.0%
Decimal Number 56995
 
17.6%
Space Separator 50214
 
15.5%
Close Punctuation 9049
 
2.8%
Open Punctuation 9047
 
2.8%
Other Punctuation 4740
 
1.5%
Dash Punctuation 1442
 
0.4%
Uppercase Letter 1248
 
0.4%
Lowercase Letter 120
 
< 0.1%
Other Symbol 54
 
< 0.1%
Other values (5) 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12945
 
6.8%
서 12587
 
6.6%
구 10754
 
5.6%
로 10519
 
5.5%
시 10481
 
5.5%
울 10077
 
5.3%
특 10007
 
5.2%
별 10005
 
5.2%
호 5969
 
3.1%
길 5497
 
2.9%
Other values (526) 92507
48.3%
Uppercase Letter
ValueCountFrequency (%)
B 400
32.1%
A 194
15.5%
C 87
 
7.0%
S 77
 
6.2%
D 58
 
4.6%
K 55
 
4.4%
M 42
 
3.4%
L 36
 
2.9%
R 35
 
2.8%
O 34
 
2.7%
Other values (16) 230
18.4%
Lowercase Letter
ValueCountFrequency (%)
e 44
36.7%
r 8
 
6.7%
t 7
 
5.8%
o 7
 
5.8%
i 7
 
5.8%
n 6
 
5.0%
a 5
 
4.2%
w 4
 
3.3%
k 4
 
3.3%
b 4
 
3.3%
Other values (10) 24
20.0%
Decimal Number
ValueCountFrequency (%)
1 18279
32.1%
2 7251
 
12.7%
0 6548
 
11.5%
3 5540
 
9.7%
4 4212
 
7.4%
5 3786
 
6.6%
6 3214
 
5.6%
7 3009
 
5.3%
8 2658
 
4.7%
9 2498
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 4648
98.1%
@ 52
 
1.1%
. 16
 
0.3%
/ 7
 
0.1%
& 5
 
0.1%
; 5
 
0.1%
? 4
 
0.1%
？ 3
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 8752
96.7%
] 297
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 8748
96.7%
[ 299
 
3.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 8
66.7%
Ⅱ 4
33.3%
Space Separator
ValueCountFrequency (%)
50214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1442
100.0%
Other Symbol
ValueCountFrequency (%)
㈕ 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Number
ValueCountFrequency (%)
⑴ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191399
59.0%
Common 131502
40.6%
Latin 1380
 
0.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12945
 
6.8%
서 12587
 
6.6%
구 10754
 
5.6%
로 10519
 
5.5%
시 10481
 
5.5%
울 10077
 
5.3%
특 10007
 
5.2%
별 10005
 
5.2%
호 5969
 
3.1%
길 5497
 
2.9%
Other values (524) 92558
48.4%
Latin
ValueCountFrequency (%)
B 400
29.0%
A 194
14.1%
C 87
 
6.3%
S 77
 
5.6%
D 58
 
4.2%
K 55
 
4.0%
e 44
 
3.2%
M 42
 
3.0%
L 36
 
2.6%
R 35
 
2.5%
Other values (38) 352
25.5%
Common
ValueCountFrequency (%)
50214
38.2%
1 18279
 
13.9%
) 8752
 
6.7%
( 8748
 
6.7%
2 7251
 
5.5%
0 6548
 
5.0%
3 5540
 
4.2%
, 4648
 
3.5%
4 4212
 
3.2%
5 3786
 
2.9%
Other values (18) 13524
 
10.3%
Han
ValueCountFrequency (%)
利 1
33.3%
景 1
33.3%
家 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191345
59.0%
ASCII 132866
41.0%
None 57
 
< 0.1%
Number Forms 12
 
< 0.1%
CJK 3
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50214
37.8%
1 18279
 
13.8%
) 8752
 
6.6%
( 8748
 
6.6%
2 7251
 
5.5%
0 6548
 
4.9%
3 5540
 
4.2%
, 4648
 
3.5%
4 4212
 
3.2%
5 3786
 
2.8%
Other values (62) 14888
 
11.2%
Hangul
ValueCountFrequency (%)
동 12945
 
6.8%
서 12587
 
6.6%
구 10754
 
5.6%
로 10519
 
5.5%
시 10481
 
5.5%
울 10077
 
5.3%
특 10007
 
5.2%
별 10005
 
5.2%
호 5969
 
3.1%
길 5497
 
2.9%
Other values (523) 92504
48.3%
None
ValueCountFrequency (%)
㈕ 54
94.7%
？ 3
 
5.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 8
66.7%
Ⅱ 4
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
⑴ 1
100.0%
CJK
ValueCountFrequency (%)
利 1
33.3%
景 1
33.3%
家 1
33.3%

중개업등록번호
Text

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:12:12.113760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length14.7064
Min length4

Characters and Unicode

Total characters147064
Distinct characters21
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

Unique9998 ?
Unique (%)> 99.9%

Sample

1st row11680-2022-00518
2nd row공92220000-1731
3rd row나-92460000-177
4th row11650-2023-00259
5th row11560-2021-00017
ValueCountFrequency (%)
9250-143 2
 
< 0.1%
9251-8798 1
 
< 0.1%
92380000-3994 1
 
< 0.1%
11350-2023-00049 1
 
< 0.1%
11590-2019-00088 1
 
< 0.1%
92460000-1369 1
 
< 0.1%
11170-2021-00122 1
 
< 0.1%
11305-2019-00027 1
 
< 0.1%
11410-2021-00004 1
 
< 0.1%
11305-2024-00021 1
 
< 0.1%
Other values (9989) 9989
99.9%
2024-05-10T23:12:13.580880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44025
29.9%
1 23630
16.1%
2 21231
14.4%
- 16646
 
11.3%
3 6907
 
4.7%
9 6802
 
4.6%
5 6546
 
4.5%
4 6532
 
4.4%
6 5216
 
3.5%
8 4367
 
3.0%
Other values (11) 5162
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 129623
88.1%
Dash Punctuation 16646
 
11.3%
Other Letter 794
 
0.5%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44025
34.0%
1 23630
18.2%
2 21231
16.4%
3 6907
 
5.3%
9 6802
 
5.2%
5 6546
 
5.1%
4 6532
 
5.0%
6 5216
 
4.0%
8 4367
 
3.4%
7 4367
 
3.4%
Other Letter
ValueCountFrequency (%)
가 290
36.5%
공 176
22.2%
다 150
18.9%
인 113
 
14.2%
나 58
 
7.3%
법 4
 
0.5%
예 1
 
0.1%
산 1
 
0.1%
주 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 16646
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 146270
99.5%
Hangul 794
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44025
30.1%
1 23630
16.2%
2 21231
14.5%
- 16646
 
11.4%
3 6907
 
4.7%
9 6802
 
4.7%
5 6546
 
4.5%
4 6532
 
4.5%
6 5216
 
3.6%
8 4367
 
3.0%
Other values (2) 4368
 
3.0%
Hangul
ValueCountFrequency (%)
가 290
36.5%
공 176
22.2%
다 150
18.9%
인 113
 
14.2%
나 58
 
7.3%
법 4
 
0.5%
예 1
 
0.1%
산 1
 
0.1%
주 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146270
99.5%
Hangul 794
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44025
30.1%
1 23630
16.2%
2 21231
14.5%
- 16646
 
11.4%
3 6907
 
4.7%
9 6802
 
4.7%
5 6546
 
4.5%
4 6532
 
4.5%
6 5216
 
3.6%
8 4367
 
3.0%
Other values (2) 4368
 
3.0%
Hangul
ValueCountFrequency (%)
가 290
36.5%
공 176
22.2%
다 150
18.9%
인 113
 
14.2%
나 58
 
7.3%
법 4
 
0.5%
예 1
 
0.1%
산 1
 
0.1%
주 1
 
0.1%

중개업자명
Text

Distinct8306
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:12:14.619023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length3
Mean length2.994
Min length2

Characters and Unicode

Total characters29940
Distinct characters324
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7300 ?
Unique (%)73.0%

Sample

1st row정지수
2nd row김은숙
3rd row송우용
4th row지정원
5th row양해숙
ValueCountFrequency (%)
김정희 14
 
0.1%
김정숙 12
 
0.1%
김영숙 11
 
0.1%
이정희 10
 
0.1%
김현숙 10
 
0.1%
김미희 9
 
0.1%
김민정 9
 
0.1%
김선희 9
 
0.1%
김미숙 9
 
0.1%
이경숙 8
 
0.1%
Other values (8300) 9903
99.0%
2024-05-10T23:12:16.342154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2092
 
7.0%
이 1514
 
5.1%
정 1222
 
4.1%
영 987
 
3.3%
박 812
 
2.7%
희 740
 
2.5%
경 633
 
2.1%
현 593
 
2.0%
숙 571
 
1.9%
성 502
 
1.7%
Other values (314) 20274
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29901
99.9%
Uppercase Letter 33
 
0.1%
Space Separator 4
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2092
 
7.0%
이 1514
 
5.1%
정 1222
 
4.1%
영 987
 
3.3%
박 812
 
2.7%
희 740
 
2.5%
경 633
 
2.1%
현 593
 
2.0%
숙 571
 
1.9%
성 502
 
1.7%
Other values (295) 20235
67.7%
Uppercase Letter
ValueCountFrequency (%)
N 6
18.2%
I 5
15.2%
H 4
12.1%
A 3
9.1%
G 2
 
6.1%
J 2
 
6.1%
O 2
 
6.1%
D 1
 
3.0%
U 1
 
3.0%
C 1
 
3.0%
Other values (6) 6
18.2%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29901
99.9%
Latin 33
 
0.1%
Common 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2092
 
7.0%
이 1514
 
5.1%
정 1222
 
4.1%
영 987
 
3.3%
박 812
 
2.7%
희 740
 
2.5%
경 633
 
2.1%
현 593
 
2.0%
숙 571
 
1.9%
성 502
 
1.7%
Other values (295) 20235
67.7%
Latin
ValueCountFrequency (%)
N 6
18.2%
I 5
15.2%
H 4
12.1%
A 3
9.1%
G 2
 
6.1%
J 2
 
6.1%
O 2
 
6.1%
D 1
 
3.0%
U 1
 
3.0%
C 1
 
3.0%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
4
66.7%
( 1
 
16.7%
) 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29901
99.9%
ASCII 39
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2092
 
7.0%
이 1514
 
5.1%
정 1222
 
4.1%
영 987
 
3.3%
박 812
 
2.7%
희 740
 
2.5%
경 633
 
2.1%
현 593
 
2.0%
숙 571
 
1.9%
성 502
 
1.7%
Other values (295) 20235
67.7%
ASCII
ValueCountFrequency (%)
N 6
15.4%
I 5
12.8%
4
10.3%
H 4
10.3%
A 3
 
7.7%
G 2
 
5.1%
J 2
 
5.1%
O 2
 
5.1%
D 1
 
2.6%
U 1
 
2.6%
Other values (9) 9
23.1%

사업자상호
Text

Distinct6143
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:12:17.113658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length34
Mean length11.8848
Min length5

Characters and Unicode

Total characters118848
Distinct characters757
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5238 ?
Unique (%)52.4%

Sample

1st row압구정서울공인중개사사무소
2nd row필공인중개사사무소
3rd row중앙부동산중개인사무소
4th row강남삼부공인중개사사무소
5th row강산공인중개사사무소
ValueCountFrequency (%)
공인중개사사무소 119
 
1.2%
현대공인중개사사무소 100
 
1.0%
삼성공인중개사사무소 85
 
0.8%
미래공인중개사사무소 67
 
0.7%
우리공인중개사사무소 62
 
0.6%
주식회사 54
 
0.5%
하나공인중개사사무소 52
 
0.5%
행운공인중개사사무소 46
 
0.4%
중앙공인중개사사무소 43
 
0.4%
태양공인중개사사무소 42
 
0.4%
Other values (6160) 9577
93.5%
2024-05-10T23:12:18.595601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 18719
15.8%
중 10101
 
8.5%
개 10060
 
8.5%
인 9508
 
8.0%
소 9390
 
7.9%
무 9331
 
7.9%
공 8937
 
7.5%
동 2947
 
2.5%
산 2807
 
2.4%
부 2746
 
2.3%
Other values (747) 34302
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113332
95.4%
Decimal Number 2736
 
2.3%
Uppercase Letter 878
 
0.7%
Close Punctuation 489
 
0.4%
Open Punctuation 487
 
0.4%
Dash Punctuation 442
 
0.4%
Space Separator 252
 
0.2%
Lowercase Letter 177
 
0.1%
Other Punctuation 45
 
< 0.1%
Letter Number 5
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 18719
16.5%
중 10101
 
8.9%
개 10060
 
8.9%
인 9508
 
8.4%
소 9390
 
8.3%
무 9331
 
8.2%
공 8937
 
7.9%
동 2947
 
2.6%
산 2807
 
2.5%
부 2746
 
2.4%
Other values (670) 28786
25.4%
Uppercase Letter
ValueCountFrequency (%)
K 147
16.7%
S 94
 
10.7%
O 77
 
8.8%
A 52
 
5.9%
M 48
 
5.5%
L 43
 
4.9%
C 39
 
4.4%
B 36
 
4.1%
D 36
 
4.1%
E 33
 
3.8%
Other values (16) 273
31.1%
Lowercase Letter
ValueCountFrequency (%)
e 61
34.5%
h 15
 
8.5%
o 11
 
6.2%
i 10
 
5.6%
s 9
 
5.1%
a 9
 
5.1%
n 8
 
4.5%
p 7
 
4.0%
t 7
 
4.0%
l 6
 
3.4%
Other values (11) 34
19.2%
Decimal Number
ValueCountFrequency (%)
0 588
21.5%
2 336
12.3%
1 332
12.1%
4 266
9.7%
9 262
9.6%
3 240
8.8%
8 230
 
8.4%
7 196
 
7.2%
5 155
 
5.7%
6 131
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 25
55.6%
& 9
 
20.0%
? 2
 
4.4%
/ 2
 
4.4%
, 2
 
4.4%
？ 1
 
2.2%
' 1
 
2.2%
; 1
 
2.2%
% 1
 
2.2%
@ 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 488
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 486
99.8%
[ 1
 
0.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅰ 2
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 442
100.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113328
95.4%
Common 4454
 
3.7%
Latin 1060
 
0.9%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 18719
16.5%
중 10101
 
8.9%
개 10060
 
8.9%
인 9508
 
8.4%
소 9390
 
8.3%
무 9331
 
8.2%
공 8937
 
7.9%
동 2947
 
2.6%
산 2807
 
2.5%
부 2746
 
2.4%
Other values (667) 28782
25.4%
Latin
ValueCountFrequency (%)
K 147
 
13.9%
S 94
 
8.9%
O 77
 
7.3%
e 61
 
5.8%
A 52
 
4.9%
M 48
 
4.5%
L 43
 
4.1%
C 39
 
3.7%
B 36
 
3.4%
D 36
 
3.4%
Other values (39) 427
40.3%
Common
ValueCountFrequency (%)
0 588
13.2%
) 488
11.0%
( 486
10.9%
- 442
9.9%
2 336
7.5%
1 332
7.5%
4 266
 
6.0%
9 262
 
5.9%
252
 
5.7%
3 240
 
5.4%
Other values (17) 762
17.1%
Han
ValueCountFrequency (%)
秀 3
50.0%
美 1
 
16.7%
善 1
 
16.7%
正 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113326
95.4%
ASCII 5508
 
4.6%
CJK 6
 
< 0.1%
Number Forms 5
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 18719
16.5%
중 10101
 
8.9%
개 10060
 
8.9%
인 9508
 
8.4%
소 9390
 
8.3%
무 9331
 
8.2%
공 8937
 
7.9%
동 2947
 
2.6%
산 2807
 
2.5%
부 2746
 
2.4%
Other values (666) 28780
25.4%
ASCII
ValueCountFrequency (%)
0 588
 
10.7%
) 488
 
8.9%
( 486
 
8.8%
- 442
 
8.0%
2 336
 
6.1%
1 332
 
6.0%
4 266
 
4.8%
9 262
 
4.8%
252
 
4.6%
3 240
 
4.4%
Other values (63) 1816
33.0%
CJK
ValueCountFrequency (%)
秀 3
50.0%
美 1
 
16.7%
善 1
 
16.7%
正 1
 
16.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅰ 2
40.0%
None
ValueCountFrequency (%)
㈜ 2
66.7%
？ 1
33.3%

전화번호
Text

MISSING 

Distinct8461
Distinct (%)93.6%
Missing965
Missing (%)9.7%
Memory size156.2 KiB
2024-05-10T23:12:19.100035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length480
Median length466
Mean length11.862313
Min length1

Characters and Unicode

Total characters107176
Distinct characters52
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8424 ?
Unique (%)93.2%

Sample

1st row02-546-6262
2nd row02-2238-3113
3rd row02-813-9254
4th row 02-575-2070
5th row408-6700
ValueCountFrequency (%)
685
 
6.6%
02 5
 
< 0.1%
추가 4
 
< 0.1%
1588-4802 3
 
< 0.1%
02-766-4700 2
 
< 0.1%
02-909-9300 2
 
< 0.1%
02-445-0002 2
 
< 0.1%
02-943-4800 2
 
< 0.1%
02-3437-4000 2
 
< 0.1%
354-6699 2
 
< 0.1%
Other values (9644) 9688
93.2%
2024-05-10T23:12:20.248503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 16889
15.8%
0 16565
15.5%
2 14083
13.1%
4 8363
7.8%
5 7530
7.0%
8 7507
7.0%
9 7359
6.9%
3 6927
6.5%
6 6100
 
5.7%
7 5965
 
5.6%
Other values (42) 9888
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86057
80.3%
Dash Punctuation 16889
 
15.8%
Other Punctuation 1908
 
1.8%
Space Separator 1784
 
1.7%
Other Letter 237
 
0.2%
Close Punctuation 126
 
0.1%
Open Punctuation 103
 
0.1%
Math Symbol 49
 
< 0.1%
Lowercase Letter 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 64
27.0%
가 64
27.0%
경 12
 
5.1%
변 12
 
5.1%
서 10
 
4.2%
의 10
 
4.2%
동 10
 
4.2%
외 5
 
2.1%
전 4
 
1.7%
록 4
 
1.7%
Other values (19) 42
17.7%
Decimal Number
ValueCountFrequency (%)
0 16565
19.2%
2 14083
16.4%
4 8363
9.7%
5 7530
8.8%
8 7507
8.7%
9 7359
8.6%
3 6927
8.0%
6 6100
 
7.1%
7 5965
 
6.9%
1 5658
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
r 10
43.5%
q 10
43.5%
f 1
 
4.3%
a 1
 
4.3%
x 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1675
87.8%
. 208
 
10.9%
/ 25
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 16889
100.0%
Space Separator
ValueCountFrequency (%)
1784
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Math Symbol
ValueCountFrequency (%)
~ 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106916
99.8%
Hangul 237
 
0.2%
Latin 23
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 64
27.0%
가 64
27.0%
경 12
 
5.1%
변 12
 
5.1%
서 10
 
4.2%
의 10
 
4.2%
동 10
 
4.2%
외 5
 
2.1%
전 4
 
1.7%
록 4
 
1.7%
Other values (19) 42
17.7%
Common
ValueCountFrequency (%)
- 16889
15.8%
0 16565
15.5%
2 14083
13.2%
4 8363
7.8%
5 7530
7.0%
8 7507
7.0%
9 7359
6.9%
3 6927
6.5%
6 6100
 
5.7%
7 5965
 
5.6%
Other values (8) 9628
9.0%
Latin
ValueCountFrequency (%)
r 10
43.5%
q 10
43.5%
f 1
 
4.3%
a 1
 
4.3%
x 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106939
99.8%
Hangul 237
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 16889
15.8%
0 16565
15.5%
2 14083
13.2%
4 8363
7.8%
5 7530
7.0%
8 7507
7.0%
9 7359
6.9%
3 6927
6.5%
6 6100
 
5.7%
7 5965
 
5.6%
Other values (13) 9651
9.0%
Hangul
ValueCountFrequency (%)
추 64
27.0%
가 64
27.0%
경 12
 
5.1%
변 12
 
5.1%
서 10
 
4.2%
의 10
 
4.2%
동 10
 
4.2%
외 5
 
2.1%
전 4
 
1.7%
록 4
 
1.7%
Other values (19) 42
17.7%

상태구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
9960 
휴업
 
28
업무정지
 
11
휴업연장
 
1

Length

Max length4
Median length3
Mean length2.9984
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 9960
99.6%
휴업 28
 
0.3%
업무정지 11
 
0.1%
휴업연장 1
 
< 0.1%

Length

2024-05-10T23:12:20.996842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:12:21.843155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 9960
99.6%
휴업 28
 
0.3%
업무정지 11
 
0.1%
휴업연장 1
 
< 0.1%

행정처분 시작일
Date

MISSING 

Distinct10
Distinct (%)90.9%
Missing9989
Missing (%)99.9%
Memory size156.2 KiB
Minimum2024-02-28 00:00:00
Maximum2024-05-10 00:00:00
2024-05-10T23:12:22.486792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:12:23.038447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

행정처분 종료일
Date

MISSING 

Distinct9
Distinct (%)81.8%
Missing9989
Missing (%)99.9%
Memory size156.2 KiB
Minimum2024-05-17 00:00:00
Maximum2024-10-21 00:00:00
2024-05-10T23:12:23.773379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:12:24.469547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

조회 개수
Real number (ℝ)

Distinct2146
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean649.4873
Minimum1
Maximum3055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:25.060589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile54
Q1261.75
median520
Q3838
95-th percentile1753
Maximum3055
Range3054
Interquartile range (IQR)576.25

Descriptive statistics

Standard deviation561.10296
Coefficient of variation (CV)0.86391675
Kurtosis3.6741131
Mean649.4873
Median Absolute Deviation (MAD)283
Skewness1.7597474
Sum6494873
Variance314836.53
MonotonicityNot monotonic
2024-05-10T23:12:25.586267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
504 17
 
0.2%
368 16
 
0.2%
591 16
 
0.2%
177 15
 
0.1%
283 15
 
0.1%
549 15
 
0.1%
56 15
 
0.1%
229 15
 
0.1%
574 15
 
0.1%
154 15
 
0.1%
Other values (2136) 9846
98.5%
ValueCountFrequency (%)
1 11
0.1%
2 12
0.1%
3 9
0.1%
4 8
0.1%
5 9
0.1%
6 11
0.1%
7 8
0.1%
8 10
0.1%
9 7
0.1%
10 12
0.1%
ValueCountFrequency (%)
3055 1
< 0.1%
3051 1
< 0.1%
3049 1
< 0.1%
3045 1
< 0.1%
3044 1
< 0.1%
3043 1
< 0.1%
3040 1
< 0.1%
3039 1
< 0.1%
3035 1
< 0.1%
3034 1
< 0.1%

도로명코드
Real number (ℝ)

Distinct3389
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1473213 × 1011
Minimum1.111021 × 1011
Maximum1.1740486 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:26.013555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111021 × 1011
5-th percentile1.1170301 × 1011
Q11.1305301 × 1011
median1.1500316 × 1011
Q31.1650416 × 1011
95-th percentile1.1710485 × 1011
Maximum1.1740486 × 1011
Range6.302758 × 109
Interquartile range (IQR)3.4511583 × 109

Descriptive statistics

Standard deviation1.9051638 × 109
Coefficient of variation (CV)0.016605321
Kurtosis-1.2472515
Mean1.1473213 × 1011
Median Absolute Deviation (MAD)1.799028 × 109
Skewness-0.28220608
Sum1.1473213 × 1015
Variance3.6296492 × 1018
MonotonicityNot monotonic
2024-05-10T23:12:26.520798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116803122006 70
 
0.7%
117103123023 51
 
0.5%
116503121017 51
 
0.5%
114703114003 50
 
0.5%
116803122005 49
 
0.5%
113503000001 48
 
0.5%
115003115001 47
 
0.5%
115453117001 45
 
0.4%
115002005007 45
 
0.4%
116803122010 44
 
0.4%
Other values (3379) 9500
95.0%
ValueCountFrequency (%)
111102100001 2
 
< 0.1%
111102100002 2
 
< 0.1%
111103000008 4
< 0.1%
111103005003 1
 
< 0.1%
111103005004 2
 
< 0.1%
111103005006 4
< 0.1%
111103005007 5
0.1%
111103005008 1
 
< 0.1%
111103100002 7
0.1%
111103100003 2
 
< 0.1%
ValueCountFrequency (%)
117404858048 1
 
< 0.1%
117404858046 1
 
< 0.1%
117404172446 1
 
< 0.1%
117404172435 3
< 0.1%
117404172431 2
< 0.1%
117404172430 1
 
< 0.1%
117404172429 1
 
< 0.1%
117404172428 2
< 0.1%
117404172426 1
 
< 0.1%
117404172425 1
 
< 0.1%

건물
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9745 
<NA>
 
236
 
18
1
 
1

Length

Max length4
Median length1
Mean length1.0708
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 9745
97.5%
<NA> 236
 
2.4%
18
 
0.2%
1 1
 
< 0.1%

Length

2024-05-10T23:12:27.000484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:12:27.433628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9745
97.6%
na 236
 
2.4%
1 1
 
< 0.1%

건물 본번
Real number (ℝ)

Distinct792
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.5884
Minimum1
Maximum2936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:27.889303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q119
median48
Q3158.25
95-th percentile537
Maximum2936
Range2935
Interquartile range (IQR)139.25

Descriptive statistics

Standard deviation278.13098
Coefficient of variation (CV)1.9103924
Kurtosis35.239548
Mean145.5884
Median Absolute Deviation (MAD)38
Skewness5.0693189
Sum1455884
Variance77356.842
MonotonicityNot monotonic
2024-05-10T23:12:28.365088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 201
 
2.0%
7 183
 
1.8%
8 180
 
1.8%
10 173
 
1.7%
11 162
 
1.6%
16 160
 
1.6%
17 149
 
1.5%
15 147
 
1.5%
9 147
 
1.5%
14 144
 
1.4%
Other values (782) 8354
83.5%
ValueCountFrequency (%)
1 56
 
0.6%
2 79
 
0.8%
3 104
1.0%
4 90
0.9%
5 140
1.4%
6 201
2.0%
7 183
1.8%
8 180
1.8%
9 147
1.5%
10 173
1.7%
ValueCountFrequency (%)
2936 1
 
< 0.1%
2921 5
0.1%
2917 8
0.1%
2912 6
0.1%
2806 1
 
< 0.1%
2803 3
 
< 0.1%
2737 1
 
< 0.1%
2728 1
 
< 0.1%
2615 1
 
< 0.1%
2340 2
 
< 0.1%

건물 부번
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)0.5%
Missing203
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean0.60763499
Minimum0
Maximum91
Zeros8912
Zeros (%)89.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:12:28.873867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum91
Range91
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.279229
Coefficient of variation (CV)5.3967087
Kurtosis135.36582
Mean0.60763499
Median Absolute Deviation (MAD)0
Skewness9.5217613
Sum5953
Variance10.753343
MonotonicityNot monotonic
2024-05-10T23:12:29.404723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 8912
89.1%
1 342
 
3.4%
2 83
 
0.8%
3 45
 
0.4%
5 37
 
0.4%
6 36
 
0.4%
4 35
 
0.4%
7 34
 
0.3%
8 32
 
0.3%
10 26
 
0.3%
Other values (35) 215
 
2.1%
(Missing) 203
 
2.0%
ValueCountFrequency (%)
0 8912
89.1%
1 342
 
3.4%
2 83
 
0.8%
3 45
 
0.4%
4 35
 
0.4%
5 37
 
0.4%
6 36
 
0.4%
7 34
 
0.3%
8 32
 
0.3%
9 21
 
0.2%
ValueCountFrequency (%)
91 1
 
< 0.1%
55 3
< 0.1%
53 1
 
< 0.1%
48 1
 
< 0.1%
47 1
 
< 0.1%
43 2
< 0.1%
42 1
 
< 0.1%
40 1
 
< 0.1%
38 1
 
< 0.1%
37 2
< 0.1%

Sample

시스템등록번호시군구코드법정동코드자치구명법정동명지번구분본번부번주소중개업등록번호중개업자명사업자상호전화번호상태구분행정처분 시작일행정처분 종료일조회 개수도로명코드건물건물 본번건물 부번
21756116802022000682116801168011000강남구압구정동13691서울특별시 강남구 압구정로29길 71 1층 105호(압구정동, 점포4동)11680-2022-00518정지수압구정서울공인중개사사무소02-546-6262영업중<NA><NA>16111168041665140710
2665111402008000052111401114016500중구황학동18110서울특별시 중구 난계로11길 8 1층공92220000-1731김은숙필공인중개사사무소02-2238-3113영업중<NA><NA>478111404103003080
11178115901984000021115901159010400동작구본동1480서울특별시 동작구 노량진로 252 (본동)나-92460000-177송우용중앙부동산중개인사무소02-813-9254영업중<NA><NA>84311590311901102520
17117116502023000263116501165010800서초구서초동113394서울특별시 서초구 효령로 429 , 111호(서초동, 강남 삼부르네상스시티)11650-2023-00259지정원강남삼부공인중개사사무소<NA>영업중<NA><NA>103111650312102104290
9981115602021000019115601156013200영등포구신길동126112서울특별시 영등포구 가마산로 466 104호11560-2021-00017양해숙강산공인중개사사무소<NA>영업중<NA><NA>36911560300002304660
1711116802019000407116801168010300강남구개포동11580서울특별시 강남구 선릉로 28 1층[101호](개포동, 일영빌딩)11680-2019-00344심언우황금공인중개사사무소02-575-2070영업중<NA><NA>8271168031220060280
1220117102004000211117101171010700송파구가락동1980서울특별시 송파구 송파대로30길 16 109호(가락동)9253-4490송기출재성공인중개사사무소408-6700영업중<NA><NA>12671171041693340160
9608117402019000214117401174010300강동구상일동14900서울특별시 강동구 상일로 74 상가2동 102호 (상일동, 고덕리엔파크3단지)11740-2019-00214권혁추리엔한강(441-6789)공인중개사사무소02-441-6789영업중<NA><NA>2711174031240040740
17804117402019000241117401174010900강동구천호동13281서울특별시 강동구 천중로 6 제1층 제108호(천호동)11740-2019-00241유한승갤럭시공인중개사사무소02-471-7107영업중<NA><NA>280117403124009060
11198115602019000244115601156011000영등포구여의도동1412서울특별시 영등포구 여의대방로 417 108호(여의도동)11560-2019-00243정우영고바우공인중개사사무소02-782-2459영업중<NA><NA>27211560311802804170
시스템등록번호시군구코드법정동코드자치구명법정동명지번구분본번부번주소중개업등록번호중개업자명사업자상호전화번호상태구분행정처분 시작일행정처분 종료일조회 개수도로명코드건물건물 본번건물 부번
8638116802019000156116801168010400강남구청담동113420서울특별시 강남구 학동로101길 26 1층 128호(청담동, 청담삼익상가)11680-2019-00138김학돈부자촌공인중개사사무소02-517-4252영업중<NA><NA>7681168041667700260
20643116802023000504116801168010800강남구논현동119115서울특별시 강남구 논현로 615 1층, 2층(논현동)11680-2023-00376김주환빌딩온부동산중개주식회사02-2088-5477, 02-2088-1042, 6141, 8206, 8605, 8317, 1779, 0735, 8631, 8134, 8471, 3951, 1043, 1486, 1966, 0680, 5424, 2059, 8603, 5477영업중<NA><NA>186411680312102206150
516111702023000031111701117012900용산구이촌동130010서울특별시 용산구 이촌로 290 제10호 (이촌동, 점보상가)11170-2023-00028홍경헌라인부동산공인중개사사무소02-790-4911영업중<NA><NA>54811170310200802900
13574115302011000251115301153011000구로구온수동199서울특별시 구로구 부일로 875 (온수동)92420000-3839이안순광개토공인중개사사무소2060-1114영업중<NA><NA>63911530300001908750
9046111102014000045111101111012000종로구신문로1가11630서울특별시 종로구 새문안로 92 광화문오피시아빌딩 제404-2호(신문로1가)92200000-2715정현애LB공인중개사사무소02-720-4020영업중<NA><NA>4961111030050040920
566111402020000068111401114016200중구신당동130020서울특별시 중구 다산로33길 2 1층 (신당동)11140-2020-00057김만호온나라공인중개사사무소02-2252-8945영업중<NA><NA>155111404103050020
21492116802002000156116801168010100강남구역삼동17400서울특별시 강남구 테헤란로20길 25 1층(역삼동)9250-4299정재영동명공인중개사사무소556-5365영업중<NA><NA>26401168041667230250
22571113802024000016113801138010600은평구대조동12222서울특별시 은평구 연서로20길 4 ,1층11380-2024-00016유정우동신공인중개사사무소<NA>영업중<NA><NA>720113804133151040
14199115302007000248115301153010800구로구오류동131280서울특별시 구로구 경인로 233 지하1층 B104호(오류동, 구로예미지어반코어)92420000-2793이다경예미지공인중개사사무소02-2614-9999영업중<NA><NA>54011530300002802330
20766116802023000470116801168010100강남구역삼동17550서울특별시 강남구 역삼로 310 1층 95호(역삼동, 한솔필리아)11680-2023-00354송광동KD부동산중개<NA>영업중<NA><NA>184911680312200803100