Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells104155
Missing cells (%)52.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory177.0 B

Variable types

Categorical2
Text5
DateTime3
Numeric6
Unsupported4

Dataset

Description의료기기 판매(임대)업체 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=05GJA39MCJY5F4O0U542201248&infSeq=1

Alerts

영업상태구분코드 is highly overall correlated with 영업상태명High correlation
도로명우편번호 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
X좌표값 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
Y좌표값 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
시군명 is highly overall correlated with 도로명우편번호 and 4 other fieldsHigh correlation
영업상태명 is highly overall correlated with 영업상태구분코드High correlation
인허가취소일자 has 9998 (> 99.9%) missing valuesMissing
영업상태구분코드 has 7888 (78.9%) missing valuesMissing
폐업일자 has 6086 (60.9%) missing valuesMissing
소재지시설전화번호 has 9669 (96.7%) missing valuesMissing
소재지면적정보 has 10000 (100.0%) missing valuesMissing
도로명우편번호 has 7893 (78.9%) missing valuesMissing
소재지지번주소 has 199 (2.0%) missing valuesMissing
소재지우편번호 has 1915 (19.1%) missing valuesMissing
WGS84위도 has 2255 (22.6%) missing valuesMissing
WGS84경도 has 2255 (22.6%) missing valuesMissing
업태구분명정보 has 10000 (100.0%) missing valuesMissing
X좌표값 has 7956 (79.6%) missing valuesMissing
Y좌표값 has 7956 (79.6%) missing valuesMissing
수리대상유형정보 has 10000 (100.0%) missing valuesMissing
다른 겸업 여부 has 10000 (100.0%) missing valuesMissing
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수리대상유형정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
다른 겸업 여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:18:50.968706
Analysis finished2023-12-10 22:19:05.697919
Duration14.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양시
1108 
성남시
1055 
수원시
997 
부천시
788 
안양시
669 
Other values (27)
5383 

Length

Max length4
Median length3
Mean length3.0831
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광명시
2nd row고양시
3rd row안양시
4th row용인시
5th row성남시

Common Values

ValueCountFrequency (%)
고양시 1108
 
11.1%
성남시 1055
 
10.5%
수원시 997
 
10.0%
부천시 788
 
7.9%
안양시 669
 
6.7%
용인시 581
 
5.8%
안산시 471
 
4.7%
남양주시 414
 
4.1%
화성시 395
 
4.0%
의정부시 359
 
3.6%
Other values (22) 3163
31.6%

Length

2023-12-11T07:19:05.750776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 1108
 
11.1%
성남시 1055
 
10.5%
수원시 997
 
10.0%
부천시 788
 
7.9%
안양시 669
 
6.7%
용인시 581
 
5.8%
안산시 471
 
4.7%
남양주시 414
 
4.1%
화성시 395
 
4.0%
의정부시 359
 
3.6%
Other values (22) 3163
31.6%
Distinct9237
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:19:05.975426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length7.905
Min length1

Characters and Unicode

Total characters79050
Distinct characters863
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8768 ?
Unique (%)87.7%

Sample

1st row광명의료기
2nd row연쇼핑
3rd row김정문알로에 신안양지사
4th row자연미인
5th row(주)다이아제닉스
ValueCountFrequency (%)
주식회사 408
 
3.1%
씨유 315
 
2.4%
세븐일레븐 225
 
1.7%
gs25 158
 
1.2%
주)코리아세븐 109
 
0.8%
cu 90
 
0.7%
주)아성다이소 75
 
0.6%
지에스25 59
 
0.4%
주)하이프라자 41
 
0.3%
신신의료기 36
 
0.3%
Other values (9586) 11638
88.5%
2023-12-11T07:19:06.349425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3156
 
4.0%
3056
 
3.9%
2547
 
3.2%
2457
 
3.1%
2167
 
2.7%
) 1996
 
2.5%
( 1976
 
2.5%
1451
 
1.8%
1415
 
1.8%
1241
 
1.6%
Other values (853) 57588
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66946
84.7%
Space Separator 3156
 
4.0%
Uppercase Letter 2481
 
3.1%
Close Punctuation 1996
 
2.5%
Open Punctuation 1976
 
2.5%
Decimal Number 1372
 
1.7%
Lowercase Letter 755
 
1.0%
Other Symbol 217
 
0.3%
Other Punctuation 117
 
0.1%
Dash Punctuation 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3056
 
4.6%
2547
 
3.8%
2457
 
3.7%
2167
 
3.2%
1451
 
2.2%
1415
 
2.1%
1241
 
1.9%
1118
 
1.7%
1039
 
1.6%
1007
 
1.5%
Other values (777) 49448
73.9%
Uppercase Letter
ValueCountFrequency (%)
S 473
19.1%
G 388
15.6%
C 346
13.9%
U 262
10.6%
M 113
 
4.6%
B 81
 
3.3%
H 78
 
3.1%
A 78
 
3.1%
K 72
 
2.9%
D 64
 
2.6%
Other values (16) 526
21.2%
Lowercase Letter
ValueCountFrequency (%)
e 102
13.5%
a 70
 
9.3%
i 67
 
8.9%
n 59
 
7.8%
o 57
 
7.5%
s 46
 
6.1%
r 45
 
6.0%
l 43
 
5.7%
d 37
 
4.9%
c 29
 
3.8%
Other values (15) 200
26.5%
Decimal Number
ValueCountFrequency (%)
2 566
41.3%
5 508
37.0%
1 96
 
7.0%
0 58
 
4.2%
4 51
 
3.7%
3 45
 
3.3%
6 22
 
1.6%
8 12
 
0.9%
7 11
 
0.8%
9 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
& 56
47.9%
. 39
33.3%
, 13
 
11.1%
· 3
 
2.6%
2
 
1.7%
* 1
 
0.9%
# 1
 
0.9%
: 1
 
0.9%
/ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
3156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1996
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1976
100.0%
Other Symbol
ValueCountFrequency (%)
217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67160
85.0%
Common 8651
 
10.9%
Latin 3236
 
4.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3056
 
4.6%
2547
 
3.8%
2457
 
3.7%
2167
 
3.2%
1451
 
2.2%
1415
 
2.1%
1241
 
1.8%
1118
 
1.7%
1039
 
1.5%
1007
 
1.5%
Other values (775) 49662
73.9%
Latin
ValueCountFrequency (%)
S 473
 
14.6%
G 388
 
12.0%
C 346
 
10.7%
U 262
 
8.1%
M 113
 
3.5%
e 102
 
3.2%
B 81
 
2.5%
H 78
 
2.4%
A 78
 
2.4%
K 72
 
2.2%
Other values (41) 1243
38.4%
Common
ValueCountFrequency (%)
3156
36.5%
) 1996
23.1%
( 1976
22.8%
2 566
 
6.5%
5 508
 
5.9%
1 96
 
1.1%
0 58
 
0.7%
& 56
 
0.6%
4 51
 
0.6%
3 45
 
0.5%
Other values (14) 143
 
1.7%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66942
84.7%
ASCII 11882
 
15.0%
None 222
 
0.3%
CJK 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3156
26.6%
) 1996
16.8%
( 1976
16.6%
2 566
 
4.8%
5 508
 
4.3%
S 473
 
4.0%
G 388
 
3.3%
C 346
 
2.9%
U 262
 
2.2%
M 113
 
1.0%
Other values (63) 2098
17.7%
Hangul
ValueCountFrequency (%)
3056
 
4.6%
2547
 
3.8%
2457
 
3.7%
2167
 
3.2%
1451
 
2.2%
1415
 
2.1%
1241
 
1.9%
1118
 
1.7%
1039
 
1.6%
1007
 
1.5%
Other values (773) 49444
73.9%
None
ValueCountFrequency (%)
217
97.7%
· 3
 
1.4%
2
 
0.9%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct3835
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1986-08-21 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T07:19:06.474319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:06.596949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
Minimum2023-07-27 00:00:00
Maximum2023-08-22 00:00:00
2023-12-11T07:19:06.688253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:06.770581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

영업상태구분코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)0.3%
Missing7888
Missing (%)78.9%
Infinite0
Infinite (%)0.0%
Mean11.013731
Minimum2
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:07.217277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q113
median13
Q313
95-th percentile13
Maximum99
Range97
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.0828569
Coefficient of variation (CV)0.46150182
Kurtosis83.908455
Mean11.013731
Median Absolute Deviation (MAD)0
Skewness4.1968764
Sum23261
Variance25.835434
MonotonicityNot monotonic
2023-12-11T07:19:07.300249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 1548
 
15.5%
3 464
 
4.6%
15 87
 
0.9%
24 10
 
0.1%
99 2
 
< 0.1%
2 1
 
< 0.1%
(Missing) 7888
78.9%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 464
 
4.6%
13 1548
15.5%
15 87
 
0.9%
24 10
 
0.1%
99 2
 
< 0.1%
ValueCountFrequency (%)
99 2
 
< 0.1%
24 10
 
0.1%
15 87
 
0.9%
13 1548
15.5%
3 464
 
4.6%
2 1
 
< 0.1%

영업상태명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
운영중
4439 
폐업 등
3440 
영업중
1548 
폐업
464 
전출
 
87
Other values (4)
 
22

Length

Max length4
Median length3
Mean length3.2905
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row운영중
2nd row운영중
3rd row폐업 등
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
운영중 4439
44.4%
폐업 등 3440
34.4%
영업중 1548
 
15.5%
폐업 464
 
4.6%
전출 87
 
0.9%
직권폐업 10
 
0.1%
휴업 등 9
 
0.1%
삭제 2
 
< 0.1%
휴업 1
 
< 0.1%

Length

2023-12-11T07:19:07.407827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:19:07.514389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 4439
33.0%
폐업 3904
29.0%
3449
25.6%
영업중 1548
 
11.5%
전출 87
 
0.6%
직권폐업 10
 
0.1%
휴업 10
 
0.1%
삭제 2
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1962
Distinct (%)50.1%
Missing6086
Missing (%)60.9%
Memory size156.2 KiB
Minimum1997-01-29 00:00:00
Maximum2023-12-06 00:00:00
2023-12-11T07:19:07.626357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:07.731440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct321
Distinct (%)97.0%
Missing9669
Missing (%)96.7%
Memory size156.2 KiB
2023-12-11T07:19:07.955975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length11.957704
Min length7

Characters and Unicode

Total characters3958
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique313 ?
Unique (%)94.6%

Sample

1st row031-592-3288
2nd row031-702-9201
3rd row031-385-7272
4th row031-657-3838
5th row070-8098-1495
ValueCountFrequency (%)
031-669-8506 3
 
0.9%
02-526-6483 3
 
0.9%
02-2164-0891 2
 
0.6%
031-759-7476 2
 
0.6%
032-342-7949 2
 
0.6%
031-8003-8496 2
 
0.6%
031-593-7258 2
 
0.6%
031-555-3999 2
 
0.6%
032-323-7161 1
 
0.3%
070-7500-9928 1
 
0.3%
Other values (311) 311
94.0%
2023-12-11T07:19:08.283560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 631
15.9%
0 594
15.0%
3 458
11.6%
1 433
10.9%
7 318
8.0%
2 305
7.7%
8 269
6.8%
5 263
6.6%
6 255
6.4%
9 218
 
5.5%
Other values (3) 214
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3322
83.9%
Dash Punctuation 631
 
15.9%
Close Punctuation 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 594
17.9%
3 458
13.8%
1 433
13.0%
7 318
9.6%
2 305
9.2%
8 269
8.1%
5 263
7.9%
6 255
7.7%
9 218
 
6.6%
4 209
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 631
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3958
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 631
15.9%
0 594
15.0%
3 458
11.6%
1 433
10.9%
7 318
8.0%
2 305
7.7%
8 269
6.8%
5 263
6.6%
6 255
6.4%
9 218
 
5.5%
Other values (3) 214
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3958
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 631
15.9%
0 594
15.0%
3 458
11.6%
1 433
10.9%
7 318
8.0%
2 305
7.7%
8 269
6.8%
5 263
6.6%
6 255
6.4%
9 218
 
5.5%
Other values (3) 214
 
5.4%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

도로명우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1380
Distinct (%)65.5%
Missing7893
Missing (%)78.9%
Infinite0
Infinite (%)0.0%
Mean14153.218
Minimum2566
Maximum26103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:08.425897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2566
5-th percentile10209.5
Q111927
median14054
Q316622
95-th percentile18408.7
Maximum26103
Range23537
Interquartile range (IQR)4695

Descriptive statistics

Standard deviation2673.8695
Coefficient of variation (CV)0.18892307
Kurtosis-0.93146281
Mean14153.218
Median Absolute Deviation (MAD)2343
Skewness0.051483097
Sum29820831
Variance7149578.1
MonotonicityNot monotonic
2023-12-11T07:19:08.546803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10071 20
 
0.2%
11901 10
 
0.1%
12113 10
 
0.1%
12925 9
 
0.1%
12918 9
 
0.1%
12913 8
 
0.1%
10402 8
 
0.1%
12097 8
 
0.1%
15010 7
 
0.1%
16705 7
 
0.1%
Other values (1370) 2011
 
20.1%
(Missing) 7893
78.9%
ValueCountFrequency (%)
2566 1
< 0.1%
6524 1
< 0.1%
10008 1
< 0.1%
10010 1
< 0.1%
10011 2
< 0.1%
10012 1
< 0.1%
10013 2
< 0.1%
10019 1
< 0.1%
10023 1
< 0.1%
10031 1
< 0.1%
ValueCountFrequency (%)
26103 1
 
< 0.1%
18634 1
 
< 0.1%
18625 2
< 0.1%
18623 1
 
< 0.1%
18617 1
 
< 0.1%
18614 1
 
< 0.1%
18611 1
 
< 0.1%
18606 1
 
< 0.1%
18603 1
 
< 0.1%
18593 4
< 0.1%
Distinct8584
Distinct (%)86.6%
Missing85
Missing (%)0.9%
Memory size156.2 KiB
2023-12-11T07:19:08.776824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length58
Mean length33.041452
Min length13

Characters and Unicode

Total characters327606
Distinct characters669
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7663 ?
Unique (%)77.3%

Sample

1st row경기도 광명시 디지털로 **, *층 (철산동)
2nd row경기도 고양시 덕양구 화중로***번길 **, ***호 (화정동, 한마음프라자)
3rd row경기도 안양시 만안구 병목안로 *, *층 (안양동)
4th row경기도 용인시 기흥구 어정로 ** (상하동)
5th row경기도 성남시 분당구 황새울로 ***, ***호 (수내동, 분당트라팰리스)
ValueCountFrequency (%)
10080
 
14.8%
경기도 9912
 
14.6%
3874
 
5.7%
2965
 
4.4%
고양시 1098
 
1.6%
성남시 1048
 
1.5%
수원시 992
 
1.5%
부천시 786
 
1.2%
분당구 653
 
1.0%
안양시 647
 
1.0%
Other values (6814) 35927
52.8%
2023-12-11T07:19:09.175245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58128
17.7%
* 55301
16.9%
11329
 
3.5%
10604
 
3.2%
10432
 
3.2%
10406
 
3.2%
10235
 
3.1%
, 10031
 
3.1%
9609
 
2.9%
) 8877
 
2.7%
Other values (659) 132654
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183040
55.9%
Other Punctuation 65385
 
20.0%
Space Separator 58128
 
17.7%
Close Punctuation 8877
 
2.7%
Open Punctuation 8877
 
2.7%
Dash Punctuation 2055
 
0.6%
Uppercase Letter 1023
 
0.3%
Lowercase Letter 138
 
< 0.1%
Math Symbol 79
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11329
 
6.2%
10604
 
5.8%
10432
 
5.7%
10406
 
5.7%
10235
 
5.6%
9609
 
5.2%
5421
 
3.0%
5260
 
2.9%
3815
 
2.1%
3643
 
2.0%
Other values (595) 102286
55.9%
Uppercase Letter
ValueCountFrequency (%)
B 243
23.8%
A 142
13.9%
C 79
 
7.7%
I 72
 
7.0%
T 57
 
5.6%
E 45
 
4.4%
K 42
 
4.1%
S 42
 
4.1%
R 38
 
3.7%
L 36
 
3.5%
Other values (15) 227
22.2%
Lowercase Letter
ValueCountFrequency (%)
e 25
18.1%
l 15
10.9%
i 10
 
7.2%
s 10
 
7.2%
t 9
 
6.5%
n 9
 
6.5%
o 8
 
5.8%
c 7
 
5.1%
a 7
 
5.1%
r 6
 
4.3%
Other values (11) 32
23.2%
Other Punctuation
ValueCountFrequency (%)
* 55301
84.6%
, 10031
 
15.3%
. 39
 
0.1%
& 6
 
< 0.1%
: 4
 
< 0.1%
@ 2
 
< 0.1%
/ 1
 
< 0.1%
· 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Math Symbol
ValueCountFrequency (%)
~ 78
98.7%
1
 
1.3%
Space Separator
ValueCountFrequency (%)
58128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8877
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8877
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2055
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183038
55.9%
Common 143402
43.8%
Latin 1164
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11329
 
6.2%
10604
 
5.8%
10432
 
5.7%
10406
 
5.7%
10235
 
5.6%
9609
 
5.2%
5421
 
3.0%
5260
 
2.9%
3815
 
2.1%
3643
 
2.0%
Other values (593) 102284
55.9%
Latin
ValueCountFrequency (%)
B 243
20.9%
A 142
 
12.2%
C 79
 
6.8%
I 72
 
6.2%
T 57
 
4.9%
E 45
 
3.9%
K 42
 
3.6%
S 42
 
3.6%
R 38
 
3.3%
L 36
 
3.1%
Other values (39) 368
31.6%
Common
ValueCountFrequency (%)
58128
40.5%
* 55301
38.6%
, 10031
 
7.0%
) 8877
 
6.2%
( 8877
 
6.2%
- 2055
 
1.4%
~ 78
 
0.1%
. 39
 
< 0.1%
& 6
 
< 0.1%
: 4
 
< 0.1%
Other values (5) 6
 
< 0.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183038
55.9%
ASCII 144561
44.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%
Math Operators 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58128
40.2%
* 55301
38.3%
, 10031
 
6.9%
) 8877
 
6.1%
( 8877
 
6.1%
- 2055
 
1.4%
B 243
 
0.2%
A 142
 
0.1%
C 79
 
0.1%
~ 78
 
0.1%
Other values (49) 750
 
0.5%
Hangul
ValueCountFrequency (%)
11329
 
6.2%
10604
 
5.8%
10432
 
5.7%
10406
 
5.7%
10235
 
5.6%
9609
 
5.2%
5421
 
3.0%
5260
 
2.9%
3815
 
2.1%
3643
 
2.0%
Other values (593) 102284
55.9%
Number Forms
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Math Operators
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

소재지지번주소
Text

MISSING 

Distinct7449
Distinct (%)76.0%
Missing199
Missing (%)2.0%
Memory size156.2 KiB
2023-12-11T07:19:09.448906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length49
Mean length26.807061
Min length5

Characters and Unicode

Total characters262736
Distinct characters613
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6259 ?
Unique (%)63.9%

Sample

1st row경기도 광명시 철산*동 ***번지 *호 , *층
2nd row경기도 고양시 덕양구 화정동 ***번지 *호 한마음프라자 ***호
3rd row경기도 안양시 만안구 안양*동 ***번지 ***호 *층
4th row경기도 용인시 기흥구 상하동 ***번지 *호
5th row경기도 성남시 분당구 수내동 **번지 *호 분당트라팰리스 ***호
ValueCountFrequency (%)
경기도 9654
 
16.4%
번지 7262
 
12.3%
6813
 
11.6%
2406
 
4.1%
1703
 
2.9%
고양시 1014
 
1.7%
수원시 969
 
1.6%
성남시 850
 
1.4%
부천시 714
 
1.2%
안양시 653
 
1.1%
Other values (4283) 26847
45.6%
2023-12-11T07:19:09.883133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 52158
19.9%
49347
18.8%
10537
 
4.0%
10103
 
3.8%
10023
 
3.8%
9890
 
3.8%
9745
 
3.7%
8340
 
3.2%
7638
 
2.9%
7289
 
2.8%
Other values (603) 87666
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156611
59.6%
Other Punctuation 52597
 
20.0%
Space Separator 49347
 
18.8%
Dash Punctuation 2845
 
1.1%
Uppercase Letter 674
 
0.3%
Open Punctuation 258
 
0.1%
Close Punctuation 253
 
0.1%
Lowercase Letter 114
 
< 0.1%
Math Symbol 34
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10537
 
6.7%
10103
 
6.5%
10023
 
6.4%
9890
 
6.3%
9745
 
6.2%
8340
 
5.3%
7638
 
4.9%
7289
 
4.7%
5265
 
3.4%
3458
 
2.2%
Other values (542) 74323
47.5%
Uppercase Letter
ValueCountFrequency (%)
B 145
21.5%
A 103
15.3%
I 58
 
8.6%
C 50
 
7.4%
K 37
 
5.5%
T 35
 
5.2%
S 29
 
4.3%
L 28
 
4.2%
E 26
 
3.9%
R 22
 
3.3%
Other values (15) 141
20.9%
Lowercase Letter
ValueCountFrequency (%)
e 23
20.2%
i 11
9.6%
t 9
 
7.9%
s 8
 
7.0%
n 8
 
7.0%
a 7
 
6.1%
c 6
 
5.3%
h 6
 
5.3%
b 5
 
4.4%
l 5
 
4.4%
Other values (10) 26
22.8%
Other Punctuation
ValueCountFrequency (%)
* 52158
99.2%
, 344
 
0.7%
. 74
 
0.1%
& 7
 
< 0.1%
/ 6
 
< 0.1%
: 4
 
< 0.1%
@ 4
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Math Symbol
ValueCountFrequency (%)
~ 33
97.1%
1
 
2.9%
Space Separator
ValueCountFrequency (%)
49347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2845
100.0%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 253
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156609
59.6%
Common 105334
40.1%
Latin 791
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10537
 
6.7%
10103
 
6.5%
10023
 
6.4%
9890
 
6.3%
9745
 
6.2%
8340
 
5.3%
7638
 
4.9%
7289
 
4.7%
5265
 
3.4%
3458
 
2.2%
Other values (540) 74321
47.5%
Latin
ValueCountFrequency (%)
B 145
18.3%
A 103
13.0%
I 58
 
7.3%
C 50
 
6.3%
K 37
 
4.7%
T 35
 
4.4%
S 29
 
3.7%
L 28
 
3.5%
E 26
 
3.3%
e 23
 
2.9%
Other values (38) 257
32.5%
Common
ValueCountFrequency (%)
* 52158
49.5%
49347
46.8%
- 2845
 
2.7%
, 344
 
0.3%
( 258
 
0.2%
) 253
 
0.2%
. 74
 
0.1%
~ 33
 
< 0.1%
& 7
 
< 0.1%
/ 6
 
< 0.1%
Other values (3) 9
 
< 0.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156609
59.6%
ASCII 106121
40.4%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 52158
49.1%
49347
46.5%
- 2845
 
2.7%
, 344
 
0.3%
( 258
 
0.2%
) 253
 
0.2%
B 145
 
0.1%
A 103
 
0.1%
. 74
 
0.1%
I 58
 
0.1%
Other values (47) 536
 
0.5%
Hangul
ValueCountFrequency (%)
10537
 
6.7%
10103
 
6.5%
10023
 
6.4%
9890
 
6.3%
9745
 
6.2%
8340
 
5.3%
7638
 
4.9%
7289
 
4.7%
5265
 
3.4%
3458
 
2.2%
Other values (540) 74321
47.5%
Math Operators
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

소재지우편번호
Text

MISSING 

Distinct3321
Distinct (%)41.1%
Missing1915
Missing (%)19.1%
Memory size156.2 KiB
2023-12-11T07:19:10.195884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5734075
Min length5

Characters and Unicode

Total characters45061
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

Unique1764 ?
Unique (%)21.8%

Sample

1st row423837
2nd row412271
3rd row430832
4th row16986
5th row463873
ValueCountFrequency (%)
410837 63
 
0.8%
435040 40
 
0.5%
463824 34
 
0.4%
14548 31
 
0.4%
14544 31
 
0.4%
431080 31
 
0.4%
463825 31
 
0.4%
431060 31
 
0.4%
420852 29
 
0.4%
412270 25
 
0.3%
Other values (3311) 7739
95.7%
2023-12-11T07:19:10.601690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 8314
18.5%
1 7863
17.4%
0 5311
11.8%
8 4695
10.4%
2 4341
9.6%
3 4041
9.0%
6 3143
 
7.0%
5 3128
 
6.9%
7 2435
 
5.4%
9 1733
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45004
99.9%
Dash Punctuation 57
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 8314
18.5%
1 7863
17.5%
0 5311
11.8%
8 4695
10.4%
2 4341
9.6%
3 4041
9.0%
6 3143
 
7.0%
5 3128
 
7.0%
7 2435
 
5.4%
9 1733
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45061
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 8314
18.5%
1 7863
17.4%
0 5311
11.8%
8 4695
10.4%
2 4341
9.6%
3 4041
9.0%
6 3143
 
7.0%
5 3128
 
6.9%
7 2435
 
5.4%
9 1733
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45061
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 8314
18.5%
1 7863
17.4%
0 5311
11.8%
8 4695
10.4%
2 4341
9.6%
3 4041
9.0%
6 3143
 
7.0%
5 3128
 
6.9%
7 2435
 
5.4%
9 1733
 
3.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6015
Distinct (%)77.7%
Missing2255
Missing (%)22.6%
Infinite0
Infinite (%)0.0%
Mean37.440025
Minimum36.94496
Maximum38.158161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:10.738960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.94496
5-th percentile37.131451
Q137.303899
median37.406696
Q337.613081
95-th percentile37.7462
Maximum38.158161
Range1.2132007
Interquartile range (IQR)0.30918277

Descriptive statistics

Standard deviation0.19357197
Coefficient of variation (CV)0.005170188
Kurtosis-0.21892095
Mean37.440025
Median Absolute Deviation (MAD)0.12500292
Skewness0.082568229
Sum289972.99
Variance0.037470107
MonotonicityNot monotonic
2023-12-11T07:19:10.850096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3889401776 17
 
0.2%
37.370051815 14
 
0.1%
37.3923317778 13
 
0.1%
37.408678934 13
 
0.1%
37.3496997265 12
 
0.1%
37.6399272494 12
 
0.1%
37.3716127805 11
 
0.1%
37.3905041309 11
 
0.1%
37.4003344455 10
 
0.1%
37.5062759998 10
 
0.1%
Other values (6005) 7622
76.2%
(Missing) 2255
 
22.6%
ValueCountFrequency (%)
36.9449600423 1
< 0.1%
36.9494769474 1
< 0.1%
36.9577754385 1
< 0.1%
36.9590819913 1
< 0.1%
36.9605653293 1
< 0.1%
36.9606465634 1
< 0.1%
36.960911334 1
< 0.1%
36.9611783586 1
< 0.1%
36.9614678605 1
< 0.1%
36.9635885438 1
< 0.1%
ValueCountFrequency (%)
38.1581607278 1
< 0.1%
38.091004052 1
< 0.1%
38.0907657107 1
< 0.1%
38.0288206418 1
< 0.1%
38.0285691646 1
< 0.1%
38.0273348041 1
< 0.1%
38.0270406935 1
< 0.1%
38.0268567174 1
< 0.1%
38.0254969868 1
< 0.1%
38.0248523014 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6015
Distinct (%)77.7%
Missing2255
Missing (%)22.6%
Infinite0
Infinite (%)0.0%
Mean126.98884
Minimum126.53465
Maximum127.66211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:10.961244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53465
5-th percentile126.75129
Q1126.82938
median126.99915
Q3127.11416
95-th percentile127.25844
Maximum127.66211
Range1.1274639
Interquartile range (IQR)0.28478356

Descriptive statistics

Standard deviation0.17833197
Coefficient of variation (CV)0.0014043121
Kurtosis0.31900922
Mean126.98884
Median Absolute Deviation (MAD)0.13588176
Skewness0.46563893
Sum983528.6
Variance0.031802293
MonotonicityNot monotonic
2023-12-11T07:19:11.071713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.122552825 17
 
0.2%
126.9530364977 14
 
0.1%
126.9565123356 13
 
0.1%
127.122114828 13
 
0.1%
127.110408487 12
 
0.1%
126.7861697718 12
 
0.1%
126.9514327046 11
 
0.1%
126.9491825612 11
 
0.1%
126.976147584 10
 
0.1%
126.7553573099 10
 
0.1%
Other values (6005) 7622
76.2%
(Missing) 2255
 
22.6%
ValueCountFrequency (%)
126.5346479848 1
< 0.1%
126.5368619573 1
< 0.1%
126.5637120533 1
< 0.1%
126.5695814694 1
< 0.1%
126.5728322765 1
< 0.1%
126.5741117196 1
< 0.1%
126.5807391884 1
< 0.1%
126.5828604939 1
< 0.1%
126.5955590242 1
< 0.1%
126.5976057487 1
< 0.1%
ValueCountFrequency (%)
127.6621119016 1
< 0.1%
127.6594616227 1
< 0.1%
127.6538862143 1
< 0.1%
127.647300169 1
< 0.1%
127.6459893506 1
< 0.1%
127.6417238832 1
< 0.1%
127.641372682 1
< 0.1%
127.6400258302 1
< 0.1%
127.6399066986 1
< 0.1%
127.6398930001 1
< 0.1%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

X좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1825
Distinct (%)89.3%
Missing7956
Missing (%)79.6%
Infinite0
Infinite (%)0.0%
Mean200409.69
Minimum161739.77
Maximum350641.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:11.190684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum161739.77
5-th percentile175605.38
Q1185080.74
median203927.11
Q3211159.9
95-th percentile226816.94
Maximum350641.44
Range188901.67
Interquartile range (IQR)26079.156

Descriptive statistics

Standard deviation17345.51
Coefficient of variation (CV)0.086550254
Kurtosis2.6405334
Mean200409.69
Median Absolute Deviation (MAD)11740.945
Skewness0.56086625
Sum4.0963741 × 108
Variance3.0086672 × 108
MonotonicityNot monotonic
2023-12-11T07:19:11.298946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211022.980991253 7
 
0.1%
216038.566179914 6
 
0.1%
166542.983302429 6
 
0.1%
199920.194662903 5
 
0.1%
213491.170141499 5
 
0.1%
190220.795104756 5
 
0.1%
217964.353815516 5
 
0.1%
181429.886692476 4
 
< 0.1%
166714.986493674 4
 
< 0.1%
190124.458858418 4
 
< 0.1%
Other values (1815) 1993
 
19.9%
(Missing) 7956
79.6%
ValueCountFrequency (%)
161739.767923413 1
 
< 0.1%
161893.250712491 1
 
< 0.1%
164362.684414923 1
 
< 0.1%
164492.318964908 1
 
< 0.1%
164839.668045509 1
 
< 0.1%
165265.749714462 1
 
< 0.1%
165511.751095968 1
 
< 0.1%
166451.21936166 1
 
< 0.1%
166484.61536235 1
 
< 0.1%
166542.983302429 6
0.1%
ValueCountFrequency (%)
350641.436259224 1
< 0.1%
262005.123129258 1
< 0.1%
258365.088066118 1
< 0.1%
258145.37927289 1
< 0.1%
257406.362654 2
< 0.1%
256876.746677465 1
< 0.1%
256507.103682509 1
< 0.1%
256351.288108837 1
< 0.1%
256340.546474461 1
< 0.1%
256300.20833588 1
< 0.1%

Y좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1825
Distinct (%)89.3%
Missing7956
Missing (%)79.6%
Infinite0
Infinite (%)0.0%
Mean437313.55
Minimum383622.31
Maximum502642.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:19:11.429533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum383622.31
5-th percentile394966.43
Q1420027.14
median434580.39
Q3459356.36
95-th percentile472369.66
Maximum502642.7
Range119020.38
Interquartile range (IQR)39329.223

Descriptive statistics

Standard deviation23747.578
Coefficient of variation (CV)0.054303322
Kurtosis-0.67495952
Mean437313.55
Median Absolute Deviation (MAD)17927.528
Skewness-0.04678294
Sum8.9386889 × 108
Variance5.6394747 × 108
MonotonicityNot monotonic
2023-12-11T07:19:11.579303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
460402.799208436 7
 
0.1%
450059.249204826 6
 
0.1%
460146.42097319 6
 
0.1%
418246.927112644 5
 
0.1%
418778.755712447 5
 
0.1%
455402.818543143 5
 
0.1%
450753.941494285 5
 
0.1%
469045.573730663 4
 
< 0.1%
460134.632987089 4
 
< 0.1%
435332.556961729 4
 
< 0.1%
Other values (1815) 1993
 
19.9%
(Missing) 7956
79.6%
ValueCountFrequency (%)
383622.310327551 1
< 0.1%
383730.582827031 1
< 0.1%
384345.984975926 1
< 0.1%
384642.952234495 1
< 0.1%
384931.572033676 1
< 0.1%
386141.645 1
< 0.1%
386161.280079734 1
< 0.1%
386549.665248928 1
< 0.1%
386562.543079876 1
< 0.1%
386737.45545712 1
< 0.1%
ValueCountFrequency (%)
502642.695069169 1
< 0.1%
502586.156331591 1
< 0.1%
498081.899153035 1
< 0.1%
493857.896761673 1
< 0.1%
492689.484042078 1
< 0.1%
491904.711441061 1
< 0.1%
490539.35741103 1
< 0.1%
488902.173769161 1
< 0.1%
488531.076228049 1
< 0.1%
488283.358223315 1
< 0.1%

수리대상유형정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

다른 겸업 여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Interactions

2023-12-11T07:19:03.236933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:52.892806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:54.822357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:00.513747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.160140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.552471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:03.326417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:52.970983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:55.975310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:00.799714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.225833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.642578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:04.712169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:54.483555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:58.319210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:00.849522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.271792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:02.885227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:04.788265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:54.579226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:58.373327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:00.945615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.349486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:02.969675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:04.863875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:54.648123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:58.449212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.029583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.419235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:03.062138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:04.955394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:54.731448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:18:59.212297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.100135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:01.488760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:19:03.154330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:19:11.682262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가취소일자영업상태구분코드영업상태명도로명우편번호WGS84위도WGS84경도X좌표값Y좌표값
시군명1.0000.0000.2660.2310.9960.9620.9480.9470.959
인허가취소일자0.0001.000NaNNaN0.000NaNNaNNaN0.000
영업상태구분코드0.266NaN1.0001.0000.000NaNNaN0.0000.021
영업상태명0.231NaN1.0001.0000.1590.0930.0750.0530.000
도로명우편번호0.9960.0000.0000.1591.0000.0000.0000.7310.767
WGS84위도0.962NaNNaN0.0930.0001.0000.707NaN0.000
WGS84경도0.948NaNNaN0.0750.0000.7071.000NaN0.000
X좌표값0.947NaN0.0000.0530.731NaNNaN1.0000.430
Y좌표값0.9590.0000.0210.0000.7670.0000.0000.4301.000
2023-12-11T07:19:11.785304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명
시군명1.0000.088
영업상태명0.0881.000
2023-12-11T07:19:11.853929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구분코드도로명우편번호WGS84위도WGS84경도X좌표값Y좌표값시군명영업상태명
영업상태구분코드1.000-0.016NaNNaN0.0300.0170.1391.000
도로명우편번호-0.0161.000-0.5000.5000.215-0.9210.5920.129
WGS84위도NaN-0.5001.000-0.2710.5001.0000.7770.056
WGS84경도NaN0.500-0.2711.0001.0000.5000.7260.045
X좌표값0.0300.2150.5001.0001.000-0.1880.7760.031
Y좌표값0.017-0.9211.0000.500-0.1881.0000.7650.000
시군명0.1390.5920.7770.7260.7760.7651.0000.088
영업상태명1.0000.1290.0560.0450.0310.0000.0881.000

Missing values

2023-12-11T07:19:05.114778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:19:05.367204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T07:19:05.566140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값수리대상유형정보다른 겸업 여부
3697광명시광명의료기20070307<NA><NA>운영중<NA><NA><NA><NA>경기도 광명시 디지털로 **, *층 (철산동)경기도 광명시 철산*동 ***번지 *호 , *층42383737.474128126.870534<NA><NA><NA><NA><NA>
608고양시연쇼핑20141113<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 화중로***번길 **, ***호 (화정동, 한마음프라자)경기도 고양시 덕양구 화정동 ***번지 *호 한마음프라자 ***호41227137.638408126.833006<NA><NA><NA><NA><NA>
19904안양시김정문알로에 신안양지사20120629<NA><NA>폐업 등20130925<NA><NA><NA>경기도 안양시 만안구 병목안로 *, *층 (안양동)경기도 안양시 만안구 안양*동 ***번지 ***호 *층43083237.399567126.919899<NA><NA><NA><NA><NA>
21726용인시자연미인20090410<NA><NA>운영중<NA><NA><NA><NA>경기도 용인시 기흥구 어정로 ** (상하동)경기도 용인시 기흥구 상하동 ***번지 *호1698637.274455127.139853<NA><NA><NA><NA><NA>
11538성남시(주)다이아제닉스20091008<NA><NA>운영중<NA><NA><NA><NA>경기도 성남시 분당구 황새울로 ***, ***호 (수내동, 분당트라팰리스)경기도 성남시 분당구 수내동 **번지 *호 분당트라팰리스 ***호46387337.37953127.114241<NA><NA><NA><NA><NA>
17358안산시김정문알로에단원지사20141022<NA><NA>운영중<NA><NA><NA><NA>경기도 안산시 단원구 예술대학로 **, 중앙시장 ***호 (고잔동)경기도 안산시 단원구 고잔동 ***번지 *호 중앙시장 ***호1533937.324294126.837666<NA><NA><NA><NA><NA>
27083하남시지컴퍼니20160215<NA><NA>폐업 등20170621<NA><NA><NA>경기도 하남시 고골로***번길 **, *층 (하사창동)경기도 하남시 하사창동 ***번지1301937.513036127.199428<NA><NA><NA><NA><NA>
13394수원시삼성전자판매 주식회사 수원삼성디지털시티2호점2022-11-22<NA>13영업중<NA><NA><NA>16677경기도 수원시 영통구 삼성로 ***, 삼성전자 G-G*동 B*층 (매탄동)경기도 수원시 영통구 매탄동 *** 삼성전자<NA><NA><NA><NA>204466.046132417102.662117<NA><NA>
776고양시웰라이프20140829<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 현중로 **, ***호 (탄현동, 탄현마을상가동)경기도 고양시 일산서구 탄현동 ****번지 탄현마을상가동 ***호41132037.693262126.767692<NA><NA><NA><NA><NA>
21346용인시윤메디케어2023-05-25<NA>13영업중<NA><NA><NA>16842경기도 용인시 수지구 포은대로 ***, 힐스테이트 수지구청역 ***동 ****호 (풍덕천동)경기도 용인시 수지구 풍덕천동 **** 힐스테이트 수지구청역<NA><NA><NA><NA>208305.51199424055.504844<NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값수리대상유형정보다른 겸업 여부
9649부천시페이스터치20091113<NA><NA>폐업 등20150317<NA><NA><NA>경기도 부천시 부일로 ***-* (상동,,*층일부)경기도 부천시 상동 ***번지 *호 ,*층일부42081637.487967126.754996<NA><NA><NA><NA><NA>
2270고양시엠테크20041223<NA><NA>폐업 등20060628<NA><NA><NA>경기도 고양시 덕양구 용현로 * (행신동)경기도 고양시덕양구 행신동 ***번지 *호41222037.613077126.835623<NA><NA><NA><NA><NA>
2907고양시메디코리아20031020<NA><NA>폐업 등20040826<NA><NA><NA>경기도 고양시 덕양구 충장로 ** (행신동)경기도 고양시덕양구 행신동 ***번지 *호41222037.614395126.834444<NA><NA><NA><NA><NA>
2849고양시일산종로의료기20040503<NA><NA>폐업 등20121128<NA><NA><NA>경기도 고양시 일산서구 강선로 **, ***호 (주엽동, 일산비스타오피스텔)경기도 고양시 일산서구 주엽동 *** 일산비스타오피스텔***호1038637.668756126.763363<NA><NA><NA><NA><NA>
19421안양시(주)왓슨스코리아 만안점20101230<NA><NA>폐업 등20170602<NA><NA><NA>경기도 안양시 만안구 안양로 ***-* (안양동, *층)경기도 안양시 만안구 안양*동 ***번지 *호 *층43083237.399255126.920568<NA><NA><NA><NA><NA>
14011수원시동양인터내셔널20010706<NA><NA>운영중<NA><NA><NA><NA>경기도 수원시 영통구 봉영로****번길 **경기도 수원시 영통구 영통동 ****-*44347037.265755127.084507<NA><NA><NA><NA><NA>
23679의정부시비케이상사20170209<NA><NA>운영중<NA><NA><NA><NA>경기도 의정부시 경의로 **, *층 ***호 (의정부동, 범골빌딩)경기도 의정부시 의정부동 ***번지 *호1162637.732609127.039173<NA><NA><NA><NA><NA>
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