Overview

Dataset statistics

Number of variables27
Number of observations629
Missing cells4878
Missing cells (%)28.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.2 KiB
Average record size in memory228.2 B

Variable types

Categorical6
Text7
Numeric11
DateTime3

Alerts

비고 has constant value ""Constant
기타산업시설면적(㎡) is highly imbalanced (95.5%)Imbalance
위도 has 110 (17.5%) missing valuesMissing
경도 has 110 (17.5%) missing valuesMissing
소재지도로명주소 has 99 (15.7%) missing valuesMissing
부지면적(㎡) has 59 (9.4%) missing valuesMissing
건축면적(㎡) has 71 (11.3%) missing valuesMissing
층수(지하/지상) has 212 (33.7%) missing valuesMissing
공장시설면적(㎡) has 74 (11.8%) missing valuesMissing
지원시설면적(㎡) has 91 (14.5%) missing valuesMissing
공동시설면적(㎡) has 531 (84.4%) missing valuesMissing
유치가능업체수 has 102 (16.2%) missing valuesMissing
입주업체수 has 417 (66.3%) missing valuesMissing
공장동수 has 330 (52.5%) missing valuesMissing
허가일자 has 238 (37.8%) missing valuesMissing
착공일자 has 280 (44.5%) missing valuesMissing
준공일자 has 366 (58.2%) missing valuesMissing
사용승인일 has 230 (36.6%) missing valuesMissing
사업자등록번호 has 546 (86.8%) missing valuesMissing
전화번호 has 384 (61.0%) missing valuesMissing
비고 has 627 (99.7%) missing valuesMissing
입주업체수 has 13 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-03 18:58:01.714175
Analysis finished2024-05-03 18:58:03.709207
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct27
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
시흥시
117 
화성시
54 
성남시
54 
안양시
50 
부천시
47 
Other values (22)
307 

Length

Max length4
Median length3
Mean length3.0413355
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
시흥시 117
18.6%
화성시 54
 
8.6%
성남시 54
 
8.6%
안양시 50
 
7.9%
부천시 47
 
7.5%
파주시 38
 
6.0%
군포시 32
 
5.1%
수원시 29
 
4.6%
평택시 29
 
4.6%
안산시 25
 
4.0%
Other values (17) 154
24.5%

Length

2024-05-03T18:58:03.952153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시흥시 117
18.6%
화성시 54
 
8.6%
성남시 54
 
8.6%
안양시 50
 
7.9%
부천시 47
 
7.5%
파주시 38
 
6.0%
군포시 32
 
5.1%
수원시 29
 
4.6%
평택시 29
 
4.6%
안산시 25
 
4.0%
Other values (17) 154
24.5%

지식산업센터명칭
Text

Distinct625
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-03T18:58:04.587196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.5373609
Min length2

Characters and Unicode

Total characters5370
Distinct characters408
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

Unique621 ?
Unique (%)98.7%

Sample

1st row광교더퍼스트
2nd row광교센트럴비즈타워
3rd row광교플렉스데시앙
4th row덴티움
5th row디지털엠파이어
ValueCountFrequency (%)
지식산업센터 40
 
4.5%
sk 8
 
0.9%
3차 7
 
0.8%
동탄 7
 
0.8%
의정부 6
 
0.7%
v1 6
 
0.7%
2차 6
 
0.7%
동일테크노타운 5
 
0.6%
한강듀클래스 4
 
0.4%
tower 4
 
0.4%
Other values (702) 801
89.6%
2024-05-03T18:58:06.129522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
4.9%
스 167
 
3.1%
타 162
 
3.0%
크 151
 
2.8%
테 139
 
2.6%
센 132
 
2.5%
터 120
 
2.2%
이 118
 
2.2%
지 117
 
2.2%
리 117
 
2.2%
Other values (398) 3882
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4463
83.1%
Uppercase Letter 313
 
5.8%
Space Separator 265
 
4.9%
Decimal Number 161
 
3.0%
Lowercase Letter 41
 
0.8%
Open Punctuation 37
 
0.7%
Close Punctuation 37
 
0.7%
Dash Punctuation 28
 
0.5%
Other Symbol 12
 
0.2%
Other Punctuation 6
 
0.1%
Other values (2) 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 167
 
3.7%
타 162
 
3.6%
크 151
 
3.4%
테 139
 
3.1%
센 132
 
3.0%
터 120
 
2.7%
이 118
 
2.6%
지 117
 
2.6%
리 117
 
2.6%
워 115
 
2.6%
Other values (336) 3125
70.0%
Uppercase Letter
ValueCountFrequency (%)
T 42
13.4%
I 34
 
10.9%
S 27
 
8.6%
A 24
 
7.7%
K 23
 
7.3%
C 17
 
5.4%
E 16
 
5.1%
M 15
 
4.8%
R 14
 
4.5%
B 12
 
3.8%
Other values (16) 89
28.4%
Lowercase Letter
ValueCountFrequency (%)
e 12
29.3%
r 6
14.6%
t 4
 
9.8%
n 4
 
9.8%
c 2
 
4.9%
a 2
 
4.9%
o 2
 
4.9%
i 2
 
4.9%
w 2
 
4.9%
h 1
 
2.4%
Other values (4) 4
 
9.8%
Decimal Number
ValueCountFrequency (%)
2 46
28.6%
1 42
26.1%
3 20
12.4%
5 10
 
6.2%
4 9
 
5.6%
6 8
 
5.0%
9 8
 
5.0%
7 8
 
5.0%
0 7
 
4.3%
8 3
 
1.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 1
 
16.7%
Ⅲ 1
 
16.7%
Ⅴ 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 2
33.3%
Space Separator
ValueCountFrequency (%)
265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4473
83.3%
Common 535
 
10.0%
Latin 360
 
6.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 167
 
3.7%
타 162
 
3.6%
크 151
 
3.4%
테 139
 
3.1%
센 132
 
3.0%
터 120
 
2.7%
이 118
 
2.6%
지 117
 
2.6%
리 117
 
2.6%
워 115
 
2.6%
Other values (335) 3135
70.1%
Latin
ValueCountFrequency (%)
T 42
 
11.7%
I 34
 
9.4%
S 27
 
7.5%
A 24
 
6.7%
K 23
 
6.4%
C 17
 
4.7%
E 16
 
4.4%
M 15
 
4.2%
R 14
 
3.9%
B 12
 
3.3%
Other values (34) 136
37.8%
Common
ValueCountFrequency (%)
265
49.5%
2 46
 
8.6%
1 42
 
7.9%
( 37
 
6.9%
) 37
 
6.9%
- 28
 
5.2%
3 20
 
3.7%
5 10
 
1.9%
4 9
 
1.7%
6 8
 
1.5%
Other values (7) 33
 
6.2%
Han
ValueCountFrequency (%)
堂 1
50.0%
美 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4461
83.1%
ASCII 889
 
16.6%
None 12
 
0.2%
Number Forms 6
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
29.8%
2 46
 
5.2%
T 42
 
4.7%
1 42
 
4.7%
( 37
 
4.2%
) 37
 
4.2%
I 34
 
3.8%
- 28
 
3.1%
S 27
 
3.0%
A 24
 
2.7%
Other values (47) 307
34.5%
Hangul
ValueCountFrequency (%)
스 167
 
3.7%
타 162
 
3.6%
크 151
 
3.4%
테 139
 
3.1%
센 132
 
3.0%
터 120
 
2.7%
이 118
 
2.6%
지 117
 
2.6%
리 117
 
2.6%
워 115
 
2.6%
Other values (334) 3123
70.0%
None
ValueCountFrequency (%)
㈜ 12
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 1
 
16.7%
Ⅲ 1
 
16.7%
Ⅴ 1
 
16.7%
CJK
ValueCountFrequency (%)
堂 1
50.0%
美 1
50.0%

위도
Real number (ℝ)

MISSING 

Distinct508
Distinct (%)97.9%
Missing110
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean37.424873
Minimum37.000767
Maximum37.905497
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:06.710340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.000767
5-th percentile37.209661
Q137.349506
median37.422692
Q337.518387
95-th percentile37.716973
Maximum37.905497
Range0.9047293
Interquartile range (IQR)0.16888088

Descriptive statistics

Standard deviation0.16438719
Coefficient of variation (CV)0.0043924582
Kurtosis0.21785286
Mean37.424873
Median Absolute Deviation (MAD)0.088702353
Skewness0.082145843
Sum19423.509
Variance0.027023149
MonotonicityNot monotonic
2024-05-03T18:58:07.471453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.450092942 4
 
0.6%
37.8902057823 2
 
0.3%
37.3316162113 2
 
0.3%
37.6519200586 2
 
0.3%
37.3519725459 2
 
0.3%
37.4115781293 2
 
0.3%
37.3586667851 2
 
0.3%
37.37879772 2
 
0.3%
37.35732018 2
 
0.3%
37.5503668716 1
 
0.2%
Other values (498) 498
79.2%
(Missing) 110
 
17.5%
ValueCountFrequency (%)
37.0007674227 1
0.2%
37.0078342441 1
0.2%
37.0108058479 1
0.2%
37.0265412159 1
0.2%
37.0272893376 1
0.2%
37.0272923139 1
0.2%
37.0282281747 1
0.2%
37.0288110642 1
0.2%
37.0307371186 1
0.2%
37.0328519148 1
0.2%
ValueCountFrequency (%)
37.9054967198 1
0.2%
37.8902057823 2
0.3%
37.8830340689 1
0.2%
37.8306987229 1
0.2%
37.8168156964 1
0.2%
37.743389847 1
0.2%
37.7326978222 1
0.2%
37.7288844618 1
0.2%
37.7286290756 1
0.2%
37.7234941946 1
0.2%

경도
Real number (ℝ)

MISSING 

Distinct508
Distinct (%)97.9%
Missing110
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean126.93711
Minimum126.61766
Maximum127.49455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:08.051212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.61766
5-th percentile126.69013
Q1126.7885
median126.94944
Q3127.09224
95-th percentile127.17992
Maximum127.49455
Range0.87689974
Interquartile range (IQR)0.30373943

Descriptive statistics

Standard deviation0.17139541
Coefficient of variation (CV)0.0013502388
Kurtosis-0.89039852
Mean126.93711
Median Absolute Deviation (MAD)0.15045058
Skewness0.11360819
Sum65880.358
Variance0.029376387
MonotonicityNot monotonic
2024-05-03T18:58:08.608960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7962308446 4
 
0.6%
127.0539092204 2
 
0.3%
126.7378275507 2
 
0.3%
127.1280843097 2
 
0.3%
126.9495642609 2
 
0.3%
127.0939517004 2
 
0.3%
126.7104194921 2
 
0.3%
126.8668365804 2
 
0.3%
126.7085365853 2
 
0.3%
127.191138275 1
 
0.2%
Other values (498) 498
79.2%
(Missing) 110
 
17.5%
ValueCountFrequency (%)
126.6176552318 1
0.2%
126.6181342096 1
0.2%
126.6186484508 1
0.2%
126.621303491 1
0.2%
126.6213725483 1
0.2%
126.6215477941 1
0.2%
126.6221466711 1
0.2%
126.6222420686 1
0.2%
126.6226106542 1
0.2%
126.6256115183 1
0.2%
ValueCountFrequency (%)
127.4945549686 1
0.2%
127.473636621 1
0.2%
127.4033042612 1
0.2%
127.3237711713 1
0.2%
127.222402833 1
0.2%
127.2064191566 1
0.2%
127.2058720554 1
0.2%
127.2046107882 1
0.2%
127.2034877802 1
0.2%
127.203309312 1
0.2%

소재지지번주소
Text

Distinct623
Distinct (%)99.2%
Missing1
Missing (%)0.2%
Memory size5.0 KiB
2024-05-03T18:58:09.208312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length41
Mean length21.829618
Min length14

Characters and Unicode

Total characters13709
Distinct characters279
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique618 ?
Unique (%)98.4%

Sample

1st row경기도 수원시 영통구 원천동 476번지
2nd row경기도 수원시 영통구 이의동 1283번지
3rd row경기도 수원시 영통구 이의동 1285-1
4th row경기도 수원시 영통구 이의동 1287번지
5th row경기도 수원시 영통구 영통동 980-3번지
ValueCountFrequency (%)
경기도 628
 
20.8%
시흥시 117
 
3.9%
성남시 54
 
1.8%
화성시 54
 
1.8%
안양시 50
 
1.7%
부천시 47
 
1.6%
상대원동 42
 
1.4%
중원구 42
 
1.4%
동안구 39
 
1.3%
영천동 38
 
1.3%
Other values (993) 1902
63.1%
2024-05-03T18:58:10.587434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2387
 
17.4%
시 791
 
5.8%
동 655
 
4.8%
도 650
 
4.7%
기 649
 
4.7%
경 629
 
4.6%
- 499
 
3.6%
1 493
 
3.6%
2 397
 
2.9%
지 331
 
2.4%
Other values (269) 6228
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7893
57.6%
Decimal Number 2727
 
19.9%
Space Separator 2387
 
17.4%
Dash Punctuation 499
 
3.6%
Uppercase Letter 71
 
0.5%
Other Punctuation 59
 
0.4%
Lowercase Letter 25
 
0.2%
Open Punctuation 23
 
0.2%
Close Punctuation 23
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 791
 
10.0%
동 655
 
8.3%
도 650
 
8.2%
기 649
 
8.2%
경 629
 
8.0%
지 331
 
4.2%
구 230
 
2.9%
번 207
 
2.6%
원 182
 
2.3%
양 156
 
2.0%
Other values (231) 3413
43.2%
Uppercase Letter
ValueCountFrequency (%)
B 16
22.5%
L 14
19.7%
S 7
9.9%
K 7
9.9%
I 6
 
8.5%
T 6
 
8.5%
V 4
 
5.6%
A 3
 
4.2%
O 2
 
2.8%
E 2
 
2.8%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 493
18.1%
2 397
14.6%
3 286
10.5%
4 274
10.0%
5 241
8.8%
6 233
8.5%
8 227
8.3%
7 225
8.3%
9 180
 
6.6%
0 171
 
6.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
32.0%
n 4
16.0%
r 4
16.0%
t 4
16.0%
c 3
 
12.0%
o 1
 
4.0%
w 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 49
83.1%
/ 10
 
16.9%
Space Separator
ValueCountFrequency (%)
2387
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 499
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7893
57.6%
Common 5720
41.7%
Latin 96
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 791
 
10.0%
동 655
 
8.3%
도 650
 
8.2%
기 649
 
8.2%
경 629
 
8.0%
지 331
 
4.2%
구 230
 
2.9%
번 207
 
2.6%
원 182
 
2.3%
양 156
 
2.0%
Other values (231) 3413
43.2%
Latin
ValueCountFrequency (%)
B 16
16.7%
L 14
14.6%
e 8
 
8.3%
S 7
 
7.3%
K 7
 
7.3%
I 6
 
6.2%
T 6
 
6.2%
n 4
 
4.2%
r 4
 
4.2%
V 4
 
4.2%
Other values (11) 20
20.8%
Common
ValueCountFrequency (%)
2387
41.7%
- 499
 
8.7%
1 493
 
8.6%
2 397
 
6.9%
3 286
 
5.0%
4 274
 
4.8%
5 241
 
4.2%
6 233
 
4.1%
8 227
 
4.0%
7 225
 
3.9%
Other values (7) 458
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7893
57.6%
ASCII 5816
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2387
41.0%
- 499
 
8.6%
1 493
 
8.5%
2 397
 
6.8%
3 286
 
4.9%
4 274
 
4.7%
5 241
 
4.1%
6 233
 
4.0%
8 227
 
3.9%
7 225
 
3.9%
Other values (28) 554
 
9.5%
Hangul
ValueCountFrequency (%)
시 791
 
10.0%
동 655
 
8.3%
도 650
 
8.2%
기 649
 
8.2%
경 629
 
8.0%
지 331
 
4.2%
구 230
 
2.9%
번 207
 
2.6%
원 182
 
2.3%
양 156
 
2.0%
Other values (231) 3413
43.2%

소재지도로명주소
Text

MISSING 

Distinct526
Distinct (%)99.2%
Missing99
Missing (%)15.7%
Memory size5.0 KiB
2024-05-03T18:58:11.242100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length23.228302
Min length13

Characters and Unicode

Total characters12311
Distinct characters258
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique522 ?
Unique (%)98.5%

Sample

1st row경기도 수원시 영통구 매영로159번길 19
2nd row경기도 수원시 영통구 창룡대로 260
3rd row경기도 수원시 영통구 창룡대로256번길 50
4th row경기도 수원시 영통구 창룡대로256번길 76
5th row경기도 수원시 영통구 덕영대로1556번길 16
ValueCountFrequency (%)
경기도 530
 
19.9%
시흥시 107
 
4.0%
성남시 52
 
2.0%
부천시 47
 
1.8%
중원구 42
 
1.6%
상대원동 42
 
1.6%
화성시 42
 
1.6%
안양시 41
 
1.5%
파주시 37
 
1.4%
동안구 33
 
1.2%
Other values (793) 1687
63.4%
2024-05-03T18:58:12.998212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2130
 
17.3%
시 679
 
5.5%
기 570
 
4.6%
도 558
 
4.5%
경 541
 
4.4%
로 453
 
3.7%
1 404
 
3.3%
동 367
 
3.0%
2 274
 
2.2%
3 255
 
2.1%
Other values (248) 6080
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7383
60.0%
Space Separator 2130
 
17.3%
Decimal Number 2088
 
17.0%
Open Punctuation 247
 
2.0%
Close Punctuation 245
 
2.0%
Dash Punctuation 128
 
1.0%
Other Punctuation 79
 
0.6%
Uppercase Letter 8
 
0.1%
Letter Number 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 679
 
9.2%
기 570
 
7.7%
도 558
 
7.6%
경 541
 
7.3%
로 453
 
6.1%
동 367
 
5.0%
길 237
 
3.2%
구 175
 
2.4%
대 165
 
2.2%
번 158
 
2.1%
Other values (222) 3480
47.1%
Decimal Number
ValueCountFrequency (%)
1 404
19.3%
2 274
13.1%
3 255
12.2%
5 234
11.2%
6 187
9.0%
4 181
8.7%
0 172
8.2%
7 149
 
7.1%
8 118
 
5.7%
9 114
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
L 2
25.0%
I 2
25.0%
B 2
25.0%
G 1
12.5%
E 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 246
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 244
99.6%
] 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 77
97.5%
/ 2
 
2.5%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
2130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Lowercase Letter
ValueCountFrequency (%)
y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7383
60.0%
Common 4917
39.9%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 679
 
9.2%
기 570
 
7.7%
도 558
 
7.6%
경 541
 
7.3%
로 453
 
6.1%
동 367
 
5.0%
길 237
 
3.2%
구 175
 
2.4%
대 165
 
2.2%
번 158
 
2.1%
Other values (222) 3480
47.1%
Common
ValueCountFrequency (%)
2130
43.3%
1 404
 
8.2%
2 274
 
5.6%
3 255
 
5.2%
( 246
 
5.0%
) 244
 
5.0%
5 234
 
4.8%
6 187
 
3.8%
4 181
 
3.7%
0 172
 
3.5%
Other values (8) 590
 
12.0%
Latin
ValueCountFrequency (%)
L 2
18.2%
I 2
18.2%
B 2
18.2%
G 1
9.1%
Ⅰ 1
9.1%
E 1
9.1%
y 1
9.1%
Ⅱ 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7383
60.0%
ASCII 4926
40.0%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2130
43.2%
1 404
 
8.2%
2 274
 
5.6%
3 255
 
5.2%
( 246
 
5.0%
) 244
 
5.0%
5 234
 
4.8%
6 187
 
3.8%
4 181
 
3.7%
0 172
 
3.5%
Other values (14) 599
 
12.2%
Hangul
ValueCountFrequency (%)
시 679
 
9.2%
기 570
 
7.7%
도 558
 
7.6%
경 541
 
7.3%
로 453
 
6.1%
동 367
 
5.0%
길 237
 
3.2%
구 175
 
2.4%
대 165
 
2.2%
번 158
 
2.1%
Other values (222) 3480
47.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

용도지역
Categorical

Distinct22
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
준주거
195 
일반공업
178 
준공업
68 
준주거지역
64 
제1종일반주거지역
38 
Other values (17)
86 

Length

Max length9
Median length7
Mean length4.0349762
Min length2

Unique

Unique8 ?
Unique (%)1.3%

Sample

1st row일반공업
2nd row준주거
3rd row준주거
4th row준주거
5th row준주거

Common Values

ValueCountFrequency (%)
준주거 195
31.0%
일반공업 178
28.3%
준공업 68
 
10.8%
준주거지역 64
 
10.2%
제1종일반주거지역 38
 
6.0%
일반공업지역 23
 
3.7%
공업 22
 
3.5%
근린상업 9
 
1.4%
일반상업 9
 
1.4%
자연녹지 5
 
0.8%
Other values (12) 18
 
2.9%

Length

2024-05-03T18:58:13.692273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
준주거 195
31.0%
일반공업 178
28.3%
준공업 68
 
10.8%
준주거지역 64
 
10.2%
제1종일반주거지역 38
 
6.0%
일반공업지역 23
 
3.7%
공업 22
 
3.5%
근린상업 9
 
1.4%
일반상업 9
 
1.4%
자연녹지 5
 
0.8%
Other values (12) 18
 
2.9%

부지면적(㎡)
Real number (ℝ)

MISSING 

Distinct552
Distinct (%)96.8%
Missing59
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean8309.788
Minimum324
Maximum165344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:14.092463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum324
5-th percentile689.39
Q11979.5
median5298.1
Q39913.65
95-th percentile29074.4
Maximum165344
Range165020
Interquartile range (IQR)7934.15

Descriptive statistics

Standard deviation11265.976
Coefficient of variation (CV)1.3557476
Kurtosis68.898306
Mean8309.788
Median Absolute Deviation (MAD)3621.45
Skewness6.0735621
Sum4736579.2
Variance1.269222 × 108
MonotonicityNot monotonic
2024-05-03T18:58:14.726966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6086.0 3
 
0.5%
2784.0 3
 
0.5%
4154.0 2
 
0.3%
8111.0 2
 
0.3%
840.6 2
 
0.3%
724.0 2
 
0.3%
5742.1 2
 
0.3%
1855.0 2
 
0.3%
7459.0 2
 
0.3%
1001.0 2
 
0.3%
Other values (542) 548
87.1%
(Missing) 59
 
9.4%
ValueCountFrequency (%)
324.0 1
0.2%
372.0 1
0.2%
395.0 1
0.2%
406.0 1
0.2%
416.0 1
0.2%
425.0 1
0.2%
458.0 1
0.2%
484.0 1
0.2%
490.0 1
0.2%
506.0 1
0.2%
ValueCountFrequency (%)
165344.0 1
0.2%
73273.0 1
0.2%
51801.0 1
0.2%
51238.0 1
0.2%
47636.0 1
0.2%
46962.0 1
0.2%
42937.0 1
0.2%
41951.8 1
0.2%
40663.0 1
0.2%
39963.0 1
0.2%

건축면적(㎡)
Real number (ℝ)

MISSING 

Distinct554
Distinct (%)99.3%
Missing71
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean32912.88
Minimum299.55
Maximum360107.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:15.406757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum299.55
5-th percentile983.1
Q14282.795
median14801.97
Q343033.195
95-th percentile116396.17
Maximum360107.67
Range359808.12
Interquartile range (IQR)38750.4

Descriptive statistics

Standard deviation48077.351
Coefficient of variation (CV)1.4607458
Kurtosis13.550801
Mean32912.88
Median Absolute Deviation (MAD)12758.905
Skewness3.208054
Sum18365387
Variance2.3114317 × 109
MonotonicityNot monotonic
2024-05-03T18:58:16.029931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39145.96 2
 
0.3%
5658.36 2
 
0.3%
3622.15 2
 
0.3%
43950.0 2
 
0.3%
9688.83 1
 
0.2%
5953.28 1
 
0.2%
59467.32 1
 
0.2%
58881.98 1
 
0.2%
115789.14 1
 
0.2%
4426.73 1
 
0.2%
Other values (544) 544
86.5%
(Missing) 71
 
11.3%
ValueCountFrequency (%)
299.55 1
0.2%
404.0 1
0.2%
417.66 1
0.2%
431.06 1
0.2%
469.63 1
0.2%
491.5 1
0.2%
493.98 1
0.2%
494.75 1
0.2%
494.82 1
0.2%
498.86 1
0.2%
ValueCountFrequency (%)
360107.67 1
0.2%
331601.67 1
0.2%
330282.12 1
0.2%
286871.22 1
0.2%
269190.0 1
0.2%
256370.0 1
0.2%
249723.61 1
0.2%
238551.15 1
0.2%
216284.98 1
0.2%
199988.63 1
0.2%

층수(지하/지상)
Text

MISSING 

Distinct92
Distinct (%)22.1%
Missing212
Missing (%)33.7%
Memory size5.0 KiB
2024-05-03T18:58:16.825020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5923261
Min length4

Characters and Unicode

Total characters1915
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)8.6%

Sample

1st rowB1/15
2nd rowB3/11
3rd rowB5/15
4th rowB4/15
5th rowB2/14
ValueCountFrequency (%)
b2/10 29
 
7.0%
b3/10 23
 
5.5%
b1/6 20
 
4.8%
b4/10 18
 
4.3%
b2/15 18
 
4.3%
b1/10 14
 
3.4%
b1/5 13
 
3.1%
b1/7 13
 
3.1%
b0/4 12
 
2.9%
b2/8 11
 
2.6%
Other values (82) 246
59.0%
2024-05-03T18:58:17.790331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 417
21.8%
/ 417
21.8%
1 349
18.2%
2 176
9.2%
0 140
 
7.3%
3 115
 
6.0%
4 84
 
4.4%
5 81
 
4.2%
6 39
 
2.0%
7 38
 
2.0%
Other values (2) 59
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1081
56.4%
Uppercase Letter 417
 
21.8%
Other Punctuation 417
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 349
32.3%
2 176
16.3%
0 140
13.0%
3 115
 
10.6%
4 84
 
7.8%
5 81
 
7.5%
6 39
 
3.6%
7 38
 
3.5%
8 34
 
3.1%
9 25
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
B 417
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 417
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1498
78.2%
Latin 417
 
21.8%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 417
27.8%
1 349
23.3%
2 176
11.7%
0 140
 
9.3%
3 115
 
7.7%
4 84
 
5.6%
5 81
 
5.4%
6 39
 
2.6%
7 38
 
2.5%
8 34
 
2.3%
Latin
ValueCountFrequency (%)
B 417
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 417
21.8%
/ 417
21.8%
1 349
18.2%
2 176
9.2%
0 140
 
7.3%
3 115
 
6.0%
4 84
 
4.4%
5 81
 
4.2%
6 39
 
2.0%
7 38
 
2.0%
Other values (2) 59
 
3.1%

공장시설면적(㎡)
Real number (ℝ)

MISSING 

Distinct552
Distinct (%)99.5%
Missing74
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean30415.402
Minimum372.75
Maximum346480.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:18.367066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum372.75
5-th percentile1008.983
Q14236.995
median15198.93
Q339377.035
95-th percentile109914.35
Maximum346480.67
Range346107.92
Interquartile range (IQR)35140.04

Descriptive statistics

Standard deviation43596.866
Coefficient of variation (CV)1.4333812
Kurtosis14.750544
Mean30415.402
Median Absolute Deviation (MAD)12613.22
Skewness3.2470343
Sum16880548
Variance1.9006867 × 109
MonotonicityNot monotonic
2024-05-03T18:58:18.876424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13473.02 2
 
0.3%
48699.0 2
 
0.3%
3512.47 2
 
0.3%
20819.0 1
 
0.2%
33213.0 1
 
0.2%
3270.0 1
 
0.2%
2030.0 1
 
0.2%
109667.0 1
 
0.2%
51785.0 1
 
0.2%
19378.0 1
 
0.2%
Other values (542) 542
86.2%
(Missing) 74
 
11.8%
ValueCountFrequency (%)
372.75 1
0.2%
391.98 1
0.2%
406.96 1
0.2%
419.25 1
0.2%
423.62 1
0.2%
449.33 1
0.2%
466.04 1
0.2%
469.62 1
0.2%
484.09 1
0.2%
493.67 1
0.2%
ValueCountFrequency (%)
346480.67 1
0.2%
332562.92 1
0.2%
315161.09 1
0.2%
223038.0 1
0.2%
221539.0 1
0.2%
219787.0 1
0.2%
194365.0 1
0.2%
189444.94 1
0.2%
187433.96 1
0.2%
179538.084 1
0.2%

기타산업시설면적(㎡)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
623 
0.0
 
4
99.0
 
1
599.57
 
1

Length

Max length6
Median length4
Mean length3.9968203
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 623
99.0%
0.0 4
 
0.6%
99.0 1
 
0.2%
599.57 1
 
0.2%

Length

2024-05-03T18:58:19.385809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:58:19.719324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 623
99.0%
0.0 4
 
0.6%
99.0 1
 
0.2%
599.57 1
 
0.2%

지원시설면적(㎡)
Real number (ℝ)

MISSING 

Distinct524
Distinct (%)97.4%
Missing91
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean8476.993
Minimum0
Maximum98563.67
Zeros6
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:20.133042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile104.3885
Q1947.76
median3146.04
Q39933.2475
95-th percentile33739.6
Maximum98563.67
Range98563.67
Interquartile range (IQR)8985.4875

Descriptive statistics

Standard deviation13558.861
Coefficient of variation (CV)1.5994895
Kurtosis13.30647
Mean8476.993
Median Absolute Deviation (MAD)2669.32
Skewness3.178395
Sum4560622.3
Variance1.8384272 × 108
MonotonicityNot monotonic
2024-05-03T18:58:20.629513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 7
 
1.1%
0.0 6
 
1.0%
2145.89 2
 
0.3%
504.0 2
 
0.3%
25672.94 2
 
0.3%
3685.51 1
 
0.2%
1099.21 1
 
0.2%
11545.0 1
 
0.2%
10816.24 1
 
0.2%
16049.0 1
 
0.2%
Other values (514) 514
81.7%
(Missing) 91
 
14.5%
ValueCountFrequency (%)
0.0 6
1.0%
0.01 7
1.1%
0.02 1
 
0.2%
0.1 1
 
0.2%
24.1 1
 
0.2%
40.0 1
 
0.2%
42.17 1
 
0.2%
44.91 1
 
0.2%
52.36 1
 
0.2%
53.94 1
 
0.2%
ValueCountFrequency (%)
98563.67 1
0.2%
97186.0 1
0.2%
94393.0 1
0.2%
74890.03 1
0.2%
73746.0 1
0.2%
72394.03 1
0.2%
65870.0 1
0.2%
57151.53 1
0.2%
56952.0 1
0.2%
56905.66 1
0.2%

공동시설면적(㎡)
Real number (ℝ)

MISSING 

Distinct96
Distinct (%)98.0%
Missing531
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean20206.393
Minimum0
Maximum140337.22
Zeros3
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:21.065203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile417.426
Q17484.9175
median15022.27
Q323543.278
95-th percentile52276.433
Maximum140337.22
Range140337.22
Interquartile range (IQR)16058.36

Descriptive statistics

Standard deviation24210.394
Coefficient of variation (CV)1.1981552
Kurtosis12.822544
Mean20206.393
Median Absolute Deviation (MAD)7948.68
Skewness3.3181305
Sum1980226.5
Variance5.861432 × 108
MonotonicityNot monotonic
2024-05-03T18:58:21.571911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
0.5%
20456.87 1
 
0.2%
7184.24 1
 
0.2%
15548.61 1
 
0.2%
11927.33 1
 
0.2%
7626.68 1
 
0.2%
27133.03 1
 
0.2%
7029.18 1
 
0.2%
7500.15 1
 
0.2%
8588.35 1
 
0.2%
Other values (86) 86
 
13.7%
(Missing) 531
84.4%
ValueCountFrequency (%)
0.0 3
0.5%
90.0 1
 
0.2%
143.76 1
 
0.2%
465.72 1
 
0.2%
658.92 1
 
0.2%
1799.59 1
 
0.2%
1832.0 1
 
0.2%
1969.19 1
 
0.2%
2285.29 1
 
0.2%
2710.47 1
 
0.2%
ValueCountFrequency (%)
140337.22 1
0.2%
131875.0 1
0.2%
121863.13 1
0.2%
88741.0 1
0.2%
53180.0 1
0.2%
52116.98 1
0.2%
46285.35 1
0.2%
43970.23 1
0.2%
42681.67 1
0.2%
37368.52 1
0.2%

유치가능업체수
Real number (ℝ)

MISSING 

Distinct258
Distinct (%)49.0%
Missing102
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean204.83681
Minimum0
Maximum2063
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:22.029588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q110.5
median119
Q3302
95-th percentile683.9
Maximum2063
Range2063
Interquartile range (IQR)291.5

Descriptive statistics

Standard deviation280.37441
Coefficient of variation (CV)1.3687696
Kurtosis10.983089
Mean204.83681
Median Absolute Deviation (MAD)113
Skewness2.7803271
Sum107949
Variance78609.81
MonotonicityNot monotonic
2024-05-03T18:58:22.430208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 79
 
12.6%
10 16
 
2.5%
12 13
 
2.1%
8 12
 
1.9%
9 11
 
1.7%
7 10
 
1.6%
11 9
 
1.4%
150 9
 
1.4%
13 7
 
1.1%
16 6
 
1.0%
Other values (248) 355
56.4%
(Missing) 102
 
16.2%
ValueCountFrequency (%)
0 2
 
0.3%
5 2
 
0.3%
6 79
12.6%
7 10
 
1.6%
8 12
 
1.9%
9 11
 
1.7%
10 16
 
2.5%
11 9
 
1.4%
12 13
 
2.1%
13 7
 
1.1%
ValueCountFrequency (%)
2063 1
0.2%
1900 1
0.2%
1826 1
0.2%
1608 1
0.2%
1391 1
0.2%
1339 1
0.2%
1286 1
0.2%
1280 1
0.2%
1240 1
0.2%
1228 1
0.2%

입주업체수
Real number (ℝ)

MISSING  ZEROS 

Distinct132
Distinct (%)62.3%
Missing417
Missing (%)66.3%
Infinite0
Infinite (%)0.0%
Mean116.0283
Minimum0
Maximum1196
Zeros13
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:22.807625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median56.5
Q3153.5
95-th percentile407.9
Maximum1196
Range1196
Interquartile range (IQR)141.5

Descriptive statistics

Standard deviation165.99075
Coefficient of variation (CV)1.4306057
Kurtosis11.663972
Mean116.0283
Median Absolute Deviation (MAD)52
Skewness2.9496011
Sum24598
Variance27552.928
MonotonicityNot monotonic
2024-05-03T18:58:23.281215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 13
 
2.1%
3 6
 
1.0%
9 5
 
0.8%
6 4
 
0.6%
10 4
 
0.6%
13 4
 
0.6%
12 4
 
0.6%
4 4
 
0.6%
1 4
 
0.6%
47 3
 
0.5%
Other values (122) 161
 
25.6%
(Missing) 417
66.3%
ValueCountFrequency (%)
0 13
2.1%
1 4
 
0.6%
2 3
 
0.5%
3 6
1.0%
4 4
 
0.6%
5 2
 
0.3%
6 4
 
0.6%
7 1
 
0.2%
8 3
 
0.5%
9 5
 
0.8%
ValueCountFrequency (%)
1196 1
0.2%
818 1
0.2%
777 1
0.2%
710 1
0.2%
656 1
0.2%
634 1
0.2%
633 1
0.2%
619 1
0.2%
432 1
0.2%
422 1
0.2%

공장동수
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)2.7%
Missing330
Missing (%)52.5%
Infinite0
Infinite (%)0.0%
Mean2.7458194
Minimum1
Maximum447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:23.583852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum447
Range446
Interquartile range (IQR)0

Descriptive statistics

Standard deviation25.799217
Coefficient of variation (CV)9.3958172
Kurtosis298.0123
Mean2.7458194
Median Absolute Deviation (MAD)0
Skewness17.249347
Sum821
Variance665.5996
MonotonicityNot monotonic
2024-05-03T18:58:23.785900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 269
42.8%
2 11
 
1.7%
4 8
 
1.3%
3 5
 
0.8%
5 3
 
0.5%
13 1
 
0.2%
8 1
 
0.2%
447 1
 
0.2%
(Missing) 330
52.5%
ValueCountFrequency (%)
1 269
42.8%
2 11
 
1.7%
3 5
 
0.8%
4 8
 
1.3%
5 3
 
0.5%
8 1
 
0.2%
13 1
 
0.2%
447 1
 
0.2%
ValueCountFrequency (%)
447 1
 
0.2%
13 1
 
0.2%
8 1
 
0.2%
5 3
 
0.5%
4 8
 
1.3%
3 5
 
0.8%
2 11
 
1.7%
1 269
42.8%

분양형태
Categorical

Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
분양
333 
<NA>
194 
분양+임대
60 
임대
 
33
자가+임대
 
6
Other values (2)
 
3

Length

Max length8
Median length2
Mean length2.9507154
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row분양
2nd row분양
3rd row분양
4th row자가
5th row분양

Common Values

ValueCountFrequency (%)
분양 333
52.9%
<NA> 194
30.8%
분양+임대 60
 
9.5%
임대 33
 
5.2%
자가+임대 6
 
1.0%
자가+분양+임대 2
 
0.3%
자가 1
 
0.2%

Length

2024-05-03T18:58:24.045627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:58:24.553644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 333
52.9%
na 194
30.8%
분양+임대 60
 
9.5%
임대 33
 
5.2%
자가+임대 6
 
1.0%
자가+분양+임대 2
 
0.3%
자가 1
 
0.2%

공사진행상황
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
준공
252 
사용승인
206 
<NA>
90 
건설중
46 
착공전
35 

Length

Max length4
Median length3
Mean length3.0699523
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
준공 252
40.1%
사용승인 206
32.8%
<NA> 90
 
14.3%
건설중 46
 
7.3%
착공전 35
 
5.6%

Length

2024-05-03T18:58:24.993814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:58:25.405462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준공 252
40.1%
사용승인 206
32.8%
na 90
 
14.3%
건설중 46
 
7.3%
착공전 35
 
5.6%

허가일자
Date

MISSING 

Distinct344
Distinct (%)88.0%
Missing238
Missing (%)37.8%
Memory size5.0 KiB
Minimum1990-08-20 00:00:00
Maximum2023-12-26 00:00:00
2024-05-03T18:58:25.705062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:58:25.998142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일자
Date

MISSING 

Distinct333
Distinct (%)95.4%
Missing280
Missing (%)44.5%
Memory size5.0 KiB
Minimum1990-11-09 00:00:00
Maximum2022-11-24 00:00:00
2024-05-03T18:58:26.355550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:58:26.802122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일자
Text

MISSING 

Distinct241
Distinct (%)91.6%
Missing366
Missing (%)58.2%
Memory size5.0 KiB
2024-05-03T18:58:27.511576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2630
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

Unique221 ?
Unique (%)84.0%

Sample

1st row2023-09-22
2nd row2018-05-23
3rd row2023-08-01
4th row2019-04-02
5th row2006-08-07
ValueCountFrequency (%)
2003-05-01 3
 
1.1%
2022-08-18 3
 
1.1%
2019-01-18 2
 
0.8%
2012-06-15 2
 
0.8%
2018-10-26 2
 
0.8%
2021-06-02 2
 
0.8%
2011-12-26 2
 
0.8%
2019-04-24 2
 
0.8%
2022-07-28 2
 
0.8%
2019-10-30 2
 
0.8%
Other values (231) 241
91.6%
2024-05-03T18:58:28.694249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 656
24.9%
2 526
20.0%
- 526
20.0%
1 408
15.5%
9 108
 
4.1%
3 87
 
3.3%
8 82
 
3.1%
7 71
 
2.7%
6 62
 
2.4%
4 54
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2104
80.0%
Dash Punctuation 526
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 656
31.2%
2 526
25.0%
1 408
19.4%
9 108
 
5.1%
3 87
 
4.1%
8 82
 
3.9%
7 71
 
3.4%
6 62
 
2.9%
4 54
 
2.6%
5 50
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 526
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2630
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 656
24.9%
2 526
20.0%
- 526
20.0%
1 408
15.5%
9 108
 
4.1%
3 87
 
3.3%
8 82
 
3.1%
7 71
 
2.7%
6 62
 
2.4%
4 54
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 656
24.9%
2 526
20.0%
- 526
20.0%
1 408
15.5%
9 108
 
4.1%
3 87
 
3.3%
8 82
 
3.1%
7 71
 
2.7%
6 62
 
2.4%
4 54
 
2.1%

사용승인일
Date

MISSING 

Distinct368
Distinct (%)92.2%
Missing230
Missing (%)36.6%
Memory size5.0 KiB
Minimum1980-06-16 00:00:00
Maximum2024-02-07 00:00:00
2024-05-03T18:58:29.093012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:58:29.545443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업자등록번호
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)49.4%
Missing546
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean2.0266775 × 109
Minimum1.0781855 × 109
Maximum7.9081011 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-03T18:58:30.013419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0781855 × 109
5-th percentile1.081858 × 109
Q11.1111111 × 109
median1.2087071 × 109
Q32.1486341 × 109
95-th percentile6.851152 × 109
Maximum7.9081011 × 109
Range6.8299156 × 109
Interquartile range (IQR)1.037523 × 109

Descriptive statistics

Standard deviation1.6845174 × 109
Coefficient of variation (CV)0.8311719
Kurtosis4.1660384
Mean2.0266775 × 109
Median Absolute Deviation (MAD)97595993
Skewness2.2337848
Sum1.6821423 × 1011
Variance2.8375989 × 1018
MonotonicityNot monotonic
2024-05-03T18:58:30.537639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1111111111 20
 
3.2%
1208707104 7
 
1.1%
2148634082 6
 
1.0%
1208658362 3
 
0.5%
1208184768 3
 
0.5%
1208167944 3
 
0.5%
2118181882 2
 
0.3%
6928100244 2
 
0.3%
1078607628 2
 
0.3%
2158652007 2
 
0.3%
Other values (31) 33
 
5.2%
(Missing) 546
86.8%
ValueCountFrequency (%)
1078185459 2
 
0.3%
1078197673 1
 
0.2%
1078607628 2
 
0.3%
1111111111 20
3.2%
1168165952 2
 
0.3%
1198669627 1
 
0.2%
1208167944 3
 
0.5%
1208184768 3
 
0.5%
1208658362 3
 
0.5%
1208707104 7
 
1.1%
ValueCountFrequency (%)
7908101080 1
0.2%
7638601481 1
0.2%
6928101087 1
0.2%
6928100244 2
0.3%
6158618290 1
0.2%
5148288821 1
0.2%
4808800349 1
0.2%
4378101495 1
0.2%
4118285049 1
0.2%
3970501024 1
0.2%

데이터기준일자
Categorical

Distinct22
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2022-10-05
117 
2023-07-31
57 
2024-02-26
54 
2023-08-02
50 
2023-02-02
49 
Other values (17)
302 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row2024-02-01
2nd row2024-02-01
3rd row2024-02-01
4th row2024-02-01
5th row2024-02-01

Common Values

ValueCountFrequency (%)
2022-10-05 117
18.6%
2023-07-31 57
9.1%
2024-02-26 54
8.6%
2023-08-02 50
 
7.9%
2023-02-02 49
 
7.8%
2023-07-24 46
 
7.3%
2023-07-20 40
 
6.4%
2024-03-04 32
 
5.1%
2024-02-01 29
 
4.6%
2023-08-25 29
 
4.6%
Other values (12) 126
20.0%

Length

2024-05-03T18:58:30.986209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-10-05 117
18.6%
2023-07-31 57
9.1%
2024-02-26 54
8.6%
2023-08-02 50
 
7.9%
2023-02-02 49
 
7.8%
2023-07-24 46
 
7.3%
2023-07-20 40
 
6.4%
2024-03-04 32
 
5.1%
2024-02-01 29
 
4.6%
2023-08-25 29
 
4.6%
Other values (12) 126
20.0%

전화번호
Text

MISSING 

Distinct235
Distinct (%)95.9%
Missing384
Missing (%)61.0%
Memory size5.0 KiB
2024-05-03T18:58:31.656444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.012245
Min length9

Characters and Unicode

Total characters2943
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

Unique227 ?
Unique (%)92.7%

Sample

1st row031-747-0969
2nd row055-922-5114
3rd row031-8035-3000
4th row031-776-0300
5th row031-736-0888
ValueCountFrequency (%)
031-928-5295 3
 
1.2%
02-3431-9000 3
 
1.2%
031-8086-7699 2
 
0.8%
033-490-5868 2
 
0.8%
02-2190-9800 2
 
0.8%
031-607-6300 2
 
0.8%
02-2055-0000 2
 
0.8%
02-3468-7766 2
 
0.8%
031-459-6450 1
 
0.4%
031-479-7500 1
 
0.4%
Other values (225) 225
91.8%
2024-05-03T18:58:32.915182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 532
18.1%
- 481
16.3%
1 407
13.8%
3 333
11.3%
4 190
 
6.5%
7 184
 
6.3%
5 177
 
6.0%
9 176
 
6.0%
6 164
 
5.6%
2 154
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2462
83.7%
Dash Punctuation 481
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 532
21.6%
1 407
16.5%
3 333
13.5%
4 190
 
7.7%
7 184
 
7.5%
5 177
 
7.2%
9 176
 
7.1%
6 164
 
6.7%
2 154
 
6.3%
8 145
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 481
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2943
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 532
18.1%
- 481
16.3%
1 407
13.8%
3 333
11.3%
4 190
 
6.5%
7 184
 
6.3%
5 177
 
6.0%
9 176
 
6.0%
6 164
 
5.6%
2 154
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 532
18.1%
- 481
16.3%
1 407
13.8%
3 333
11.3%
4 190
 
6.5%
7 184
 
6.3%
5 177
 
6.0%
9 176
 
6.0%
6 164
 
5.6%
2 154
 
5.2%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing627
Missing (%)99.7%
Memory size5.0 KiB
2024-05-03T18:58:33.361606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters18
Distinct characters7
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1877-9610
2nd row1877-9610
ValueCountFrequency (%)
1877-9610 2
100.0%
2024-05-03T18:58:34.061524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
22.2%
7 4
22.2%
8 2
11.1%
- 2
11.1%
9 2
11.1%
6 2
11.1%
0 2
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
88.9%
Dash Punctuation 2
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
25.0%
7 4
25.0%
8 2
12.5%
9 2
12.5%
6 2
12.5%
0 2
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
22.2%
7 4
22.2%
8 2
11.1%
- 2
11.1%
9 2
11.1%
6 2
11.1%
0 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
22.2%
7 4
22.2%
8 2
11.1%
- 2
11.1%
9 2
11.1%
6 2
11.1%
0 2
11.1%

Sample

시군명지식산업센터명칭위도경도소재지지번주소소재지도로명주소용도지역부지면적(㎡)건축면적(㎡)층수(지하/지상)공장시설면적(㎡)기타산업시설면적(㎡)지원시설면적(㎡)공동시설면적(㎡)유치가능업체수입주업체수공장동수분양형태공사진행상황허가일자착공일자준공일자사용승인일사업자등록번호데이터기준일자전화번호비고
0수원시광교더퍼스트37.266254127.060289경기도 수원시 영통구 원천동 476번지경기도 수원시 영통구 매영로159번길 19일반공업5483.03250.55B1/1537491.479<NA>1323.257<NA>29491분양준공2021-04-212021-07-082023-09-222023-07-21<NA>2024-02-01<NA><NA>
1수원시광교센트럴비즈타워37.295544127.037644경기도 수원시 영통구 이의동 1283번지경기도 수원시 영통구 창룡대로 260준주거4154.03703.76B3/1122474.0<NA>22735.0<NA>252901분양준공2016-04-042016-05-122018-05-232018-03-20<NA>2024-02-01<NA><NA>
2수원시광교플렉스데시앙37.295441127.038919경기도 수원시 영통구 이의동 1285-1경기도 수원시 영통구 창룡대로256번길 50준주거6292.43190.07B5/1542836.32<NA>1819.21<NA>298451분양준공2021-01-142021-04-202023-08-012023-06-28<NA>2024-02-01<NA><NA>
3수원시덴티움37.295285127.040658경기도 수원시 영통구 이의동 1287번지경기도 수원시 영통구 창룡대로256번길 76준주거9800.05780.77B4/1560509.65<NA>2643.46<NA>9141자가준공2016-08-312016-12-122019-04-022019-02-20<NA>2024-02-01<NA><NA>
4수원시디지털엠파이어37.244953127.059996경기도 수원시 영통구 영통동 980-3번지경기도 수원시 영통구 덕영대로1556번길 16준주거19664.011244.12B2/14126379.0<NA>32268.0<NA>3691861분양준공2003-05-172004-04-012006-08-072006-08-07<NA>2024-02-01<NA><NA>
5수원시디지털엠파이어237.2473127.051435경기도 수원시 영통구 신동 486번지경기도 수원시 영통구 신원로 88일반공업29339.012352.13B2/15132943.0<NA>9493.0<NA>5843194분양준공2006-03-142006-04-102008-06-302008-06-30<NA>2024-02-01<NA><NA>
6수원시삼성테크노파크37.266539127.059408경기도 수원시 영통구 원천동 471번지경기도 수원시 영통구 중부대로448번길 97일반공업4197.02339.17B2/714660.0<NA>5467.0<NA>66261분양준공2001-04-272002-07-102003-09-292003-09-29<NA>2024-02-01<NA><NA>
7수원시성신테크노37.25499127.061167경기도 수원시 영통구 매탄동 509-7번지경기도 수원시 영통구 영통로323번길 38준공업3100.01671.47B1/69344.0<NA><NA><NA>30241분양준공2002-11-122003-01-212004-01-202004-01-20<NA>2024-02-01<NA><NA>
8수원시수원델타원37.242367126.986364경기도 수원시 권선구 고색동 1098-2경기도 수원시 권선구 산업로 198일반공업9985.17786.72B2/859653.38<NA>4929.78<NA>2602371분양준공2020-04-222020-08-042022-07-062022-07-01<NA>2024-02-01<NA><NA>
9수원시수원벤처밸리237.23841126.986481경기도 수원시 권선구 고색동 1152번지경기도 수원시 권선구 산업로156번길 142-10일반공업13278.09870.31B2/879081.0<NA>5700.0<NA>3553551분양준공2015-08-242015-09-152017-06-142017-06-08<NA>2024-02-01<NA><NA>
시군명지식산업센터명칭위도경도소재지지번주소소재지도로명주소용도지역부지면적(㎡)건축면적(㎡)층수(지하/지상)공장시설면적(㎡)기타산업시설면적(㎡)지원시설면적(㎡)공동시설면적(㎡)유치가능업체수입주업체수공장동수분양형태공사진행상황허가일자착공일자준공일자사용승인일사업자등록번호데이터기준일자전화번호비고
619양주시메가시티<NA><NA>경기도 양주시 옥정동1007-4<NA>준주거지역8747.636960.69B1/536960.69<NA>14852.841799.59232<NA>1<NA>건설중2022-07-152022-10-17<NA><NA><NA>2023-07-01<NA><NA>
620양주시슈프림 더 브릭스 타워<NA><NA>경기도 양주시 옥정동1004-3<NA>준주거지역9341.739067.62B1/539067.62<NA>18420.64465.72255<NA>1<NA>건설중2022-05-032022-07-18<NA><NA><NA>2023-07-01<NA><NA>
621양주시양주 에코밸리 비즈타워<NA><NA>경기도 양주시 덕정동 68-2,-4,-5,-6,-7,-10,-11, 69-6,-18,-22,70,산23-17,산24-2,-4<NA>일반공업지역14689.098885.0B1/1198885.0<NA>44178.72710.47600<NA>1<NA>착공전2023-03-03<NA><NA><NA><NA>2023-07-01<NA><NA>
622양주시양주옥정 아이테크엠<NA><NA>경기도 양주시 옥정동1024-6<NA>준주거지역6254.930741.07B2/530741.07<NA>15359.55658.92150<NA>1<NA>건설중2022-05-302022-11-14<NA><NA><NA>2023-07-01<NA><NA>
623양주시양주테크노시티37.816816126.988204경기도 양주시 광적면 가납리 428경기도 양주시 부흥로 847준공업지역11314.046390.0B1/646390.0<NA><NA><NA>2772501<NA>사용승인2009-03-122009-11-242011-10-192011-10-19<NA>2023-07-01<NA><NA>
624양주시양주패션복합단지지식산업센터37.830699127.050768경기도 양주시 회정동 457-1경기도 양주시 평화로1597번길 41제2종일반주거지역12072.018642.55B0/318642.55<NA><NA><NA>1081<NA>사용승인2012-06-142012-07-182013-02-222013-02-22<NA>2023-07-01<NA><NA>
625양주시한강양주옥정듀클래스<NA><NA>경기도 양주시 옥정동 987-1<NA>준주거지역15735.175816.9B2/575816.9<NA>33436.093979.52515<NA>1<NA>사용승인2020-03-092020-10-212022-07-272022-07-27<NA>2023-07-01<NA><NA>
626양주시한강양주옥정듀클래스 2차<NA><NA>경기도 양주시 옥정동1006-1,-2<NA>준주거지역13644.457144.15B1/557144.15<NA>26897.071969.19351<NA>1<NA>건설중2021-12-082022-01-27<NA><NA><NA>2023-07-01<NA><NA>
627포천시포천 웰플렉스 용정산단37.883034127.203309경기도 포천시 군내면 용정리 479-1경기도 포천시 용정경제로1길 13-20준공업13330.566823.39B2/1151827.63<NA>14995.76<NA><NA>11447분양준공2016-11-232022-01-282023-09-272023-09-27<NA>2024-03-06<NA><NA>
628연천군부존재<NA><NA><NA><NA>공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-05-23<NA><NA>