Overview

Dataset statistics

Number of variables28
Number of observations3548
Missing cells24617
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory838.6 KiB
Average record size in memory242.0 B

Variable types

Categorical3
Text6
DateTime2
Unsupported3
Numeric14

Alerts

영업상태구분코드 is highly imbalanced (50.9%)Imbalance
인허가취소일자 has 3548 (100.0%) missing valuesMissing
폐업일자 has 2357 (66.4%) missing valuesMissing
소재지시설전화번호 has 2992 (84.3%) missing valuesMissing
소재지면적정보 has 3548 (100.0%) missing valuesMissing
도로명우편번호 has 2428 (68.4%) missing valuesMissing
소재지도로명주소 has 38 (1.1%) missing valuesMissing
WGS84위도 has 86 (2.4%) missing valuesMissing
WGS84경도 has 86 (2.4%) missing valuesMissing
업태구분명정보 has 3548 (100.0%) missing valuesMissing
X좌표값 has 2469 (69.6%) missing valuesMissing
Y좌표값 has 2469 (69.6%) missing valuesMissing
사무실면적(㎡) has 481 (13.6%) missing valuesMissing
소독차량차고면적(㎡) has 528 (14.9%) missing valuesMissing
소독차량차고면적(㎡) is highly skewed (γ1 = 36.3520347)Skewed
휴대용소독기수(개) is highly skewed (γ1 = 31.14698491)Skewed
동력분무기수(개) is highly skewed (γ1 = 34.01320537)Skewed
방독면수(개) is highly skewed (γ1 = 48.33081515)Skewed
보호안경수(개) is highly skewed (γ1 = 25.71482521)Skewed
보호용의복수(개) is highly skewed (γ1 = 25.43819267)Skewed
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
사무실면적(㎡) has 267 (7.5%) zerosZeros
소독차량차고면적(㎡) has 275 (7.8%) zerosZeros
동력분무기수(개) has 1566 (44.1%) zerosZeros

Reproduction

Analysis started2023-12-10 22:32:47.876183
Analysis finished2023-12-10 22:32:49.277715
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct32
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
수원시
351 
안산시
301 
고양시
286 
성남시
253 
용인시
253 
Other values (27)
2104 

Length

Max length4
Median length3
Mean length3.1037204
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 351
 
9.9%
안산시 301
 
8.5%
고양시 286
 
8.1%
성남시 253
 
7.1%
용인시 253
 
7.1%
남양주시 191
 
5.4%
부천시 172
 
4.8%
화성시 165
 
4.7%
안양시 162
 
4.6%
시흥시 154
 
4.3%
Other values (22) 1260
35.5%

Length

2023-12-11T07:32:49.425382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 351
 
9.9%
안산시 301
 
8.5%
고양시 286
 
8.1%
성남시 253
 
7.1%
용인시 253
 
7.1%
남양주시 191
 
5.4%
부천시 172
 
4.8%
화성시 165
 
4.7%
안양시 162
 
4.6%
시흥시 154
 
4.3%
Other values (22) 1260
35.5%

사업장명
Text

Distinct3051
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
2023-12-11T07:32:49.795743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length22
Mean length7.2570462
Min length2

Characters and Unicode

Total characters25748
Distinct characters616
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2647 ?
Unique (%)74.6%

Sample

1st row(주) 국제씨앤씨
2nd row동진판매상사
3rd row(주)일진환경건설
4th row(주) 코리아 탑 시큐리티
5th row동진판매상사
ValueCountFrequency (%)
주식회사 385
 
8.9%
주)세스코 39
 
0.9%
주 32
 
0.7%
방역 18
 
0.4%
사회적협동조합 15
 
0.3%
그린f5 11
 
0.3%
유한회사 10
 
0.2%
이레피앤알 9
 
0.2%
코리아 9
 
0.2%
그린환경 8
 
0.2%
Other values (3169) 3813
87.7%
2023-12-11T07:32:50.305839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1705
 
6.6%
) 1252
 
4.9%
( 1236
 
4.8%
803
 
3.1%
사 758
 
2.9%
경 737
 
2.9%
스 722
 
2.8%
이 622
 
2.4%
환 582
 
2.3%
회 561
 
2.2%
Other values (606) 16770
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21710
84.3%
Close Punctuation 1252
 
4.9%
Open Punctuation 1236
 
4.8%
Space Separator 803
 
3.1%
Uppercase Letter 433
 
1.7%
Lowercase Letter 145
 
0.6%
Decimal Number 105
 
0.4%
Other Punctuation 44
 
0.2%
Dash Punctuation 14
 
0.1%
Other Symbol 4
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1705
 
7.9%
사 758
 
3.5%
경 737
 
3.4%
스 722
 
3.3%
이 622
 
2.9%
환 582
 
2.7%
회 561
 
2.6%
리 492
 
2.3%
식 480
 
2.2%
린 452
 
2.1%
Other values (539) 14599
67.2%
Uppercase Letter
ValueCountFrequency (%)
E 44
 
10.2%
S 41
 
9.5%
C 39
 
9.0%
I 28
 
6.5%
K 25
 
5.8%
M 24
 
5.5%
N 23
 
5.3%
F 22
 
5.1%
L 20
 
4.6%
O 20
 
4.6%
Other values (14) 147
33.9%
Lowercase Letter
ValueCountFrequency (%)
e 24
16.6%
a 14
 
9.7%
o 13
 
9.0%
r 12
 
8.3%
n 11
 
7.6%
s 8
 
5.5%
i 8
 
5.5%
c 7
 
4.8%
u 6
 
4.1%
t 6
 
4.1%
Other values (13) 36
24.8%
Decimal Number
ValueCountFrequency (%)
1 31
29.5%
5 29
27.6%
2 12
 
11.4%
9 10
 
9.5%
3 10
 
9.5%
6 8
 
7.6%
0 3
 
2.9%
4 2
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 20
45.5%
. 17
38.6%
, 5
 
11.4%
/ 1
 
2.3%
＆ 1
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 1252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1236
100.0%
Space Separator
ValueCountFrequency (%)
803
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21714
84.3%
Common 3456
 
13.4%
Latin 578
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1705
 
7.9%
사 758
 
3.5%
경 737
 
3.4%
스 722
 
3.3%
이 622
 
2.9%
환 582
 
2.7%
회 561
 
2.6%
리 492
 
2.3%
식 480
 
2.2%
린 452
 
2.1%
Other values (540) 14603
67.3%
Latin
ValueCountFrequency (%)
E 44
 
7.6%
S 41
 
7.1%
C 39
 
6.7%
I 28
 
4.8%
K 25
 
4.3%
e 24
 
4.2%
M 24
 
4.2%
N 23
 
4.0%
F 22
 
3.8%
L 20
 
3.5%
Other values (37) 288
49.8%
Common
ValueCountFrequency (%)
) 1252
36.2%
( 1236
35.8%
803
23.2%
1 31
 
0.9%
5 29
 
0.8%
& 20
 
0.6%
. 17
 
0.5%
- 14
 
0.4%
2 12
 
0.3%
9 10
 
0.3%
Other values (9) 32
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21710
84.3%
ASCII 4033
 
15.7%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1705
 
7.9%
사 758
 
3.5%
경 737
 
3.4%
스 722
 
3.3%
이 622
 
2.9%
환 582
 
2.7%
회 561
 
2.6%
리 492
 
2.3%
식 480
 
2.2%
린 452
 
2.1%
Other values (539) 14599
67.2%
ASCII
ValueCountFrequency (%)
) 1252
31.0%
( 1236
30.6%
803
19.9%
E 44
 
1.1%
S 41
 
1.0%
C 39
 
1.0%
1 31
 
0.8%
5 29
 
0.7%
I 28
 
0.7%
K 25
 
0.6%
Other values (55) 505
12.5%
None
ValueCountFrequency (%)
㈜ 4
80.0%
＆ 1
 
20.0%

인허가일자
Date

Distinct2383
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
Minimum1984-11-07 00:00:00
Maximum2023-12-06 00:00:00
2023-12-11T07:32:50.463117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.871835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3548
Missing (%)100.0%
Memory size31.3 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
<NA>
2420 
13
815 
3
244 
15
 
29
2
 
26

Length

Max length4
Median length4
Mean length3.2880496
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2420
68.2%
13 815
 
23.0%
3 244
 
6.9%
15 29
 
0.8%
2 26
 
0.7%
24 14
 
0.4%

Length

2023-12-11T07:32:51.036064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:51.220301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2420
68.2%
13 815
 
23.0%
3 244
 
6.9%
15 29
 
0.8%
2 26
 
0.7%
24 14
 
0.4%

영업상태명
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
운영중
1443 
폐업 등
933 
영업중
815 
폐업
244 
휴업 등
 
44
Other values (3)
 
69

Length

Max length4
Median length3
Mean length3.1950395
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 1443
40.7%
폐업 등 933
26.3%
영업중 815
23.0%
폐업 244
 
6.9%
휴업 등 44
 
1.2%
전출 29
 
0.8%
휴업 26
 
0.7%
직권폐업 14
 
0.4%

Length

2023-12-11T07:32:51.384662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:51.537310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 1443
31.9%
폐업 1177
26.0%
등 977
21.6%
영업중 815
18.0%
휴업 70
 
1.5%
전출 29
 
0.6%
직권폐업 14
 
0.3%

폐업일자
Date

MISSING 

Distinct859
Distinct (%)72.1%
Missing2357
Missing (%)66.4%
Memory size27.8 KiB
Minimum1993-05-19 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T07:32:51.690583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.869324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct531
Distinct (%)95.5%
Missing2992
Missing (%)84.3%
Memory size27.8 KiB
2023-12-11T07:32:52.168941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.532374
Min length8

Characters and Unicode

Total characters6412
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique512 ?
Unique (%)92.1%

Sample

1st row031-582-7544
2nd row03115442837
3rd row070-4148-0483
4th row907-1596
5th row031-918-7904
ValueCountFrequency (%)
031-511-1206 4
 
0.7%
031-729-0504 3
 
0.5%
031-711-8317 3
 
0.5%
1588-1106 3
 
0.5%
031-511-1208 3
 
0.5%
031-214-4839 2
 
0.4%
031-439-1607 2
 
0.4%
031-781-9955 2
 
0.4%
031-292-2926 2
 
0.4%
031-493-1172 2
 
0.4%
Other values (521) 530
95.3%
2023-12-11T07:32:52.614185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 984
15.3%
0 875
13.6%
1 854
13.3%
3 846
13.2%
2 447
7.0%
8 422
6.6%
4 422
6.6%
5 417
6.5%
7 406
6.3%
9 378
 
5.9%
Other values (4) 361
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5421
84.5%
Dash Punctuation 984
 
15.3%
Close Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 875
16.1%
1 854
15.8%
3 846
15.6%
2 447
8.2%
8 422
7.8%
4 422
7.8%
5 417
7.7%
7 406
7.5%
9 378
7.0%
6 354
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 984
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6412
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 984
15.3%
0 875
13.6%
1 854
13.3%
3 846
13.2%
2 447
7.0%
8 422
6.6%
4 422
6.6%
5 417
6.5%
7 406
6.3%
9 378
 
5.9%
Other values (4) 361
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 984
15.3%
0 875
13.6%
1 854
13.3%
3 846
13.2%
2 447
7.0%
8 422
6.6%
4 422
6.6%
5 417
6.5%
7 406
6.3%
9 378
 
5.9%
Other values (4) 361
 
5.6%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3548
Missing (%)100.0%
Memory size31.3 KiB

도로명우편번호
Text

MISSING 

Distinct819
Distinct (%)73.1%
Missing2428
Missing (%)68.4%
Memory size27.8 KiB
2023-12-11T07:32:52.999590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0017857
Min length5

Characters and Unicode

Total characters5602
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

Unique615 ?
Unique (%)54.9%

Sample

1st row12418
2nd row12419
3rd row10413
4th row10461
5th row10420
ValueCountFrequency (%)
12541 7
 
0.6%
18469 7
 
0.6%
14998 7
 
0.6%
14904 6
 
0.5%
10090 5
 
0.4%
14303 5
 
0.4%
15431 5
 
0.4%
17145 5
 
0.4%
16226 4
 
0.4%
16521 4
 
0.4%
Other values (809) 1065
95.1%
2023-12-11T07:32:53.510611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1582
28.2%
4 527
 
9.4%
0 509
 
9.1%
2 507
 
9.1%
5 472
 
8.4%
7 446
 
8.0%
3 426
 
7.6%
6 421
 
7.5%
9 359
 
6.4%
8 352
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5601
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1582
28.2%
4 527
 
9.4%
0 509
 
9.1%
2 507
 
9.1%
5 472
 
8.4%
7 446
 
8.0%
3 426
 
7.6%
6 421
 
7.5%
9 359
 
6.4%
8 352
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5602
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1582
28.2%
4 527
 
9.4%
0 509
 
9.1%
2 507
 
9.1%
5 472
 
8.4%
7 446
 
8.0%
3 426
 
7.6%
6 421
 
7.5%
9 359
 
6.4%
8 352
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1582
28.2%
4 527
 
9.4%
0 509
 
9.1%
2 507
 
9.1%
5 472
 
8.4%
7 446
 
8.0%
3 426
 
7.6%
6 421
 
7.5%
9 359
 
6.4%
8 352
 
6.3%

소재지도로명주소
Text

MISSING 

Distinct3263
Distinct (%)93.0%
Missing38
Missing (%)1.1%
Memory size27.8 KiB
2023-12-11T07:32:53.900769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length31.426781
Min length11

Characters and Unicode

Total characters110308
Distinct characters577
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3024 ?
Unique (%)86.2%

Sample

1st row경기도 가평군 가평읍 가화로 103-1
2nd row경기도 가평군 가평읍 태평길 31
3rd row경기도 가평군 가평읍 보납로6번길 11
4th row경기도 가평군 가평읍 연인2길 14, 3층
5th row경기도 가평군 가평읍 태평길 31
ValueCountFrequency (%)
경기도 3509
 
15.1%
1층 354
 
1.5%
수원시 348
 
1.5%
안산시 298
 
1.3%
2층 294
 
1.3%
고양시 278
 
1.2%
용인시 253
 
1.1%
성남시 249
 
1.1%
남양주시 190
 
0.8%
부천시 171
 
0.7%
Other values (5307) 17315
74.4%
2023-12-11T07:32:54.500676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19851
 
18.0%
1 4325
 
3.9%
시 3692
 
3.3%
동 3690
 
3.3%
경 3670
 
3.3%
기 3669
 
3.3%
도 3620
 
3.3%
로 3266
 
3.0%
) 2990
 
2.7%
( 2990
 
2.7%
Other values (567) 58545
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61900
56.1%
Space Separator 19851
 
18.0%
Decimal Number 18616
 
16.9%
Close Punctuation 2990
 
2.7%
Open Punctuation 2990
 
2.7%
Other Punctuation 2787
 
2.5%
Dash Punctuation 895
 
0.8%
Uppercase Letter 233
 
0.2%
Lowercase Letter 36
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3692
 
6.0%
동 3690
 
6.0%
경 3670
 
5.9%
기 3669
 
5.9%
도 3620
 
5.8%
로 3266
 
5.3%
구 1740
 
2.8%
호 1634
 
2.6%
길 1622
 
2.6%
층 1280
 
2.1%
Other values (509) 34017
55.0%
Uppercase Letter
ValueCountFrequency (%)
B 79
33.9%
A 40
17.2%
I 16
 
6.9%
C 16
 
6.9%
S 13
 
5.6%
K 12
 
5.2%
T 10
 
4.3%
E 8
 
3.4%
W 4
 
1.7%
L 4
 
1.7%
Other values (14) 31
 
13.3%
Lowercase Letter
ValueCountFrequency (%)
n 6
16.7%
t 5
13.9%
e 4
11.1%
s 4
11.1%
k 4
11.1%
c 3
8.3%
i 3
8.3%
b 3
8.3%
w 1
 
2.8%
d 1
 
2.8%
Other values (2) 2
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 4325
23.2%
2 2805
15.1%
3 2152
11.6%
0 2051
11.0%
4 1595
 
8.6%
5 1406
 
7.6%
6 1279
 
6.9%
7 1093
 
5.9%
8 978
 
5.3%
9 932
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2776
99.6%
. 8
 
0.3%
@ 1
 
< 0.1%
: 1
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
19851
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2990
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 895
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61900
56.1%
Common 48136
43.6%
Latin 272
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3692
 
6.0%
동 3690
 
6.0%
경 3670
 
5.9%
기 3669
 
5.9%
도 3620
 
5.8%
로 3266
 
5.3%
구 1740
 
2.8%
호 1634
 
2.6%
길 1622
 
2.6%
층 1280
 
2.1%
Other values (509) 34017
55.0%
Latin
ValueCountFrequency (%)
B 79
29.0%
A 40
14.7%
I 16
 
5.9%
C 16
 
5.9%
S 13
 
4.8%
K 12
 
4.4%
T 10
 
3.7%
E 8
 
2.9%
n 6
 
2.2%
t 5
 
1.8%
Other values (28) 67
24.6%
Common
ValueCountFrequency (%)
19851
41.2%
1 4325
 
9.0%
) 2990
 
6.2%
( 2990
 
6.2%
2 2805
 
5.8%
, 2776
 
5.8%
3 2152
 
4.5%
0 2051
 
4.3%
4 1595
 
3.3%
5 1406
 
2.9%
Other values (10) 5195
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61900
56.1%
ASCII 48405
43.9%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19851
41.0%
1 4325
 
8.9%
) 2990
 
6.2%
( 2990
 
6.2%
2 2805
 
5.8%
, 2776
 
5.7%
3 2152
 
4.4%
0 2051
 
4.2%
4 1595
 
3.3%
5 1406
 
2.9%
Other values (46) 5464
 
11.3%
Hangul
ValueCountFrequency (%)
시 3692
 
6.0%
동 3690
 
6.0%
경 3670
 
5.9%
기 3669
 
5.9%
도 3620
 
5.8%
로 3266
 
5.3%
구 1740
 
2.8%
호 1634
 
2.6%
길 1622
 
2.6%
층 1280
 
2.1%
Other values (509) 34017
55.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%

소재지지번주소
Text

Distinct3264
Distinct (%)92.4%
Missing16
Missing (%)0.5%
Memory size27.8 KiB
2023-12-11T07:32:54.807583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48
Mean length26.398358
Min length10

Characters and Unicode

Total characters93239
Distinct characters510
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3006 ?
Unique (%)85.1%

Sample

1st row경기도 가평군 가평읍 읍내리 476-9번지
2nd row경기도 가평군 가평읍 376번지 1호
3rd row경기도 가평군 가평읍 읍내리 468번지 34호
4th row경기도 가평군 가평읍 읍내리 489-4번지 3층
5th row경기도 가평군 가평읍 376번지 1호
ValueCountFrequency (%)
경기도 3530
 
16.7%
수원시 325
 
1.5%
1호 296
 
1.4%
고양시 264
 
1.2%
용인시 253
 
1.2%
안산시 251
 
1.2%
성남시 211
 
1.0%
2호 204
 
1.0%
남양주시 189
 
0.9%
1층 177
 
0.8%
Other values (4576) 15422
73.0%
2023-12-11T07:32:55.264829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17723
 
19.0%
1 3896
 
4.2%
시 3663
 
3.9%
기 3636
 
3.9%
도 3622
 
3.9%
경 3548
 
3.8%
동 3485
 
3.7%
지 3194
 
3.4%
번 2814
 
3.0%
호 2805
 
3.0%
Other values (500) 44853
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55263
59.3%
Decimal Number 18657
 
20.0%
Space Separator 17723
 
19.0%
Dash Punctuation 1091
 
1.2%
Uppercase Letter 205
 
0.2%
Open Punctuation 98
 
0.1%
Close Punctuation 97
 
0.1%
Other Punctuation 69
 
0.1%
Lowercase Letter 25
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3663
 
6.6%
기 3636
 
6.6%
도 3622
 
6.6%
경 3548
 
6.4%
동 3485
 
6.3%
지 3194
 
5.8%
번 2814
 
5.1%
호 2805
 
5.1%
구 1722
 
3.1%
양 1089
 
2.0%
Other values (440) 25685
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 62
30.2%
A 29
14.1%
S 14
 
6.8%
C 14
 
6.8%
K 12
 
5.9%
I 9
 
4.4%
T 9
 
4.4%
E 7
 
3.4%
D 6
 
2.9%
W 5
 
2.4%
Other values (15) 38
18.5%
Lowercase Letter
ValueCountFrequency (%)
n 5
20.0%
e 3
12.0%
i 3
12.0%
t 3
12.0%
r 2
 
8.0%
b 2
 
8.0%
h 1
 
4.0%
s 1
 
4.0%
k 1
 
4.0%
a 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
1 3896
20.9%
2 2582
13.8%
3 1991
10.7%
0 1865
10.0%
4 1761
9.4%
5 1647
8.8%
6 1393
 
7.5%
7 1349
 
7.2%
8 1161
 
6.2%
9 1012
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 58
84.1%
. 7
 
10.1%
@ 2
 
2.9%
/ 1
 
1.4%
: 1
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Space Separator
ValueCountFrequency (%)
17723
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1091
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55263
59.3%
Common 37742
40.5%
Latin 234
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3663
 
6.6%
기 3636
 
6.6%
도 3622
 
6.6%
경 3548
 
6.4%
동 3485
 
6.3%
지 3194
 
5.8%
번 2814
 
5.1%
호 2805
 
5.1%
구 1722
 
3.1%
양 1089
 
2.0%
Other values (440) 25685
46.5%
Latin
ValueCountFrequency (%)
B 62
26.5%
A 29
12.4%
S 14
 
6.0%
C 14
 
6.0%
K 12
 
5.1%
I 9
 
3.8%
T 9
 
3.8%
E 7
 
3.0%
D 6
 
2.6%
n 5
 
2.1%
Other values (30) 67
28.6%
Common
ValueCountFrequency (%)
17723
47.0%
1 3896
 
10.3%
2 2582
 
6.8%
3 1991
 
5.3%
0 1865
 
4.9%
4 1761
 
4.7%
5 1647
 
4.4%
6 1393
 
3.7%
7 1349
 
3.6%
8 1161
 
3.1%
Other values (10) 2374
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55263
59.3%
ASCII 37972
40.7%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17723
46.7%
1 3896
 
10.3%
2 2582
 
6.8%
3 1991
 
5.2%
0 1865
 
4.9%
4 1761
 
4.6%
5 1647
 
4.3%
6 1393
 
3.7%
7 1349
 
3.6%
8 1161
 
3.1%
Other values (48) 2604
 
6.9%
Hangul
ValueCountFrequency (%)
시 3663
 
6.6%
기 3636
 
6.6%
도 3622
 
6.6%
경 3548
 
6.4%
동 3485
 
6.3%
지 3194
 
5.8%
번 2814
 
5.1%
호 2805
 
5.1%
구 1722
 
3.1%
양 1089
 
2.0%
Other values (440) 25685
46.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%

소재지우편번호
Text

Distinct2168
Distinct (%)61.4%
Missing15
Missing (%)0.4%
Memory size27.8 KiB
2023-12-11T07:32:55.635297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4381545
Min length5

Characters and Unicode

Total characters19213
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

Unique1418 ?
Unique (%)40.1%

Sample

1st row12418
2nd row477-800
3rd row477805
4th row12418
5th row477800
ValueCountFrequency (%)
425807 15
 
0.4%
410837 13
 
0.4%
426863 11
 
0.3%
14303 11
 
0.3%
15431 11
 
0.3%
435040 10
 
0.3%
425906 9
 
0.3%
425780 9
 
0.3%
14998 9
 
0.3%
14544 8
 
0.2%
Other values (2158) 3427
97.0%
2023-12-11T07:32:56.099152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3827
19.9%
4 3009
15.7%
0 2183
11.4%
2 1942
10.1%
8 1755
9.1%
3 1531
8.0%
5 1388
 
7.2%
6 1320
 
6.9%
7 1240
 
6.5%
9 941
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19136
99.6%
Dash Punctuation 77
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3827
20.0%
4 3009
15.7%
0 2183
11.4%
2 1942
10.1%
8 1755
9.2%
3 1531
8.0%
5 1388
 
7.3%
6 1320
 
6.9%
7 1240
 
6.5%
9 941
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19213
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3827
19.9%
4 3009
15.7%
0 2183
11.4%
2 1942
10.1%
8 1755
9.1%
3 1531
8.0%
5 1388
 
7.2%
6 1320
 
6.9%
7 1240
 
6.5%
9 941
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3827
19.9%
4 3009
15.7%
0 2183
11.4%
2 1942
10.1%
8 1755
9.1%
3 1531
8.0%
5 1388
 
7.2%
6 1320
 
6.9%
7 1240
 
6.5%
9 941
 
4.9%

WGS84위도
Real number (ℝ)

MISSING 

Distinct2850
Distinct (%)82.3%
Missing86
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean37.432896
Minimum35.864964
Maximum38.083929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:56.260180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.864964
5-th percentile37.079946
Q137.289884
median37.398622
Q337.618369
95-th percentile37.778167
Maximum38.083929
Range2.2189655
Interquartile range (IQR)0.32848503

Descriptive statistics

Standard deviation0.21285851
Coefficient of variation (CV)0.0056864024
Kurtosis0.43587946
Mean37.432896
Median Absolute Deviation (MAD)0.12834525
Skewness0.14335791
Sum129592.68
Variance0.045308744
MonotonicityNot monotonic
2023-12-11T07:32:56.388160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3031097628 5
 
0.1%
37.6452868158 5
 
0.1%
37.3024919749 5
 
0.1%
37.2666654251 5
 
0.1%
37.2337036854 5
 
0.1%
37.4586249849 5
 
0.1%
37.3138544185 5
 
0.1%
37.2906893723 5
 
0.1%
37.2660060807 4
 
0.1%
37.6855870514 4
 
0.1%
Other values (2840) 3414
96.2%
(Missing) 86
 
2.4%
ValueCountFrequency (%)
35.8649637074 1
< 0.1%
36.949459485 1
< 0.1%
36.9548859578 1
< 0.1%
36.9591074648 1
< 0.1%
36.9610877079 1
< 0.1%
36.9693053239 1
< 0.1%
36.972222512 2
0.1%
36.9722991319 1
< 0.1%
36.9743901654 1
< 0.1%
36.9798193937 1
< 0.1%
ValueCountFrequency (%)
38.083929235 1
 
< 0.1%
38.0426800055 3
0.1%
38.0315686733 1
 
< 0.1%
38.0300597047 1
 
< 0.1%
38.0233900697 3
0.1%
38.023097238 1
 
< 0.1%
38.0227688662 1
 
< 0.1%
38.0222084693 1
 
< 0.1%
38.0198316512 1
 
< 0.1%
38.01855979 1
 
< 0.1%

WGS84경도
Real number (ℝ)

MISSING 

Distinct2850
Distinct (%)82.3%
Missing86
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean127.00622
Minimum126.55205
Maximum128.79476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:56.533166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55205
5-th percentile126.74953
Q1126.83452
median127.01571
Q3127.13534
95-th percentile127.3183
Maximum128.79476
Range2.2427014
Interquartile range (IQR)0.30082612

Descriptive statistics

Standard deviation0.19646269
Coefficient of variation (CV)0.0015468746
Kurtosis2.1455861
Mean127.00622
Median Absolute Deviation (MAD)0.14945224
Skewness0.70933764
Sum439695.54
Variance0.038597589
MonotonicityNot monotonic
2023-12-11T07:32:56.699954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0050209688 5
 
0.1%
126.7066358146 5
 
0.1%
126.8112053986 5
 
0.1%
127.0156469974 5
 
0.1%
127.2802218461 5
 
0.1%
126.8774712115 5
 
0.1%
126.8293500999 5
 
0.1%
127.0009054604 5
 
0.1%
127.0242114358 4
 
0.1%
126.775615867 4
 
0.1%
Other values (2840) 3414
96.2%
(Missing) 86
 
2.4%
ValueCountFrequency (%)
126.5520541227 1
< 0.1%
126.5541850673 1
< 0.1%
126.5599348274 1
< 0.1%
126.5601196 1
< 0.1%
126.5748829205 1
< 0.1%
126.5773085098 2
0.1%
126.5800878105 1
< 0.1%
126.5837814903 2
0.1%
126.587057494 2
0.1%
126.5898937376 1
< 0.1%
ValueCountFrequency (%)
128.7947555566 1
< 0.1%
127.6898359511 1
< 0.1%
127.667384382 1
< 0.1%
127.6465244092 1
< 0.1%
127.6464389872 1
< 0.1%
127.6456468097 1
< 0.1%
127.6447874021 1
< 0.1%
127.6442946162 1
< 0.1%
127.6425698222 1
< 0.1%
127.6407297023 1
< 0.1%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3548
Missing (%)100.0%
Memory size31.3 KiB

X좌표값
Real number (ℝ)

MISSING 

Distinct981
Distinct (%)90.9%
Missing2469
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean202092.39
Minimum160414.55
Maximum361974.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:56.819922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160414.55
5-th percentile175876.53
Q1186113.2
median203695.31
Q3213951.46
95-th percentile232278.25
Maximum361974.7
Range201560.15
Interquartile range (IQR)27838.264

Descriptive statistics

Standard deviation19138.47
Coefficient of variation (CV)0.094701583
Kurtosis4.2363876
Mean202092.39
Median Absolute Deviation (MAD)14355.899
Skewness0.86209195
Sum2.1805769 × 108
Variance3.6628101 × 108
MonotonicityNot monotonic
2023-12-11T07:32:57.006616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
172060.790207415 4
 
0.1%
224593.956258907 3
 
0.1%
200010.511721975 3
 
0.1%
256277.303233602 3
 
0.1%
180749.468454166 3
 
0.1%
212455.949322708 3
 
0.1%
201322.167360331 3
 
0.1%
216116.774230063 3
 
0.1%
228487.592017134 3
 
0.1%
205377.468127778 3
 
0.1%
Other values (971) 1048
29.5%
(Missing) 2469
69.6%
ValueCountFrequency (%)
160414.546243465 1
< 0.1%
160609.047130038 1
< 0.1%
161123.450432282 1
< 0.1%
162432.962089186 1
< 0.1%
162882.067696362 1
< 0.1%
163711.409868201 1
< 0.1%
163847.174520614 1
< 0.1%
164498.358644195 1
< 0.1%
164770.315408568 1
< 0.1%
165047.421881027 1
< 0.1%
ValueCountFrequency (%)
361974.6962868 1
 
< 0.1%
256746.147888562 1
 
< 0.1%
256491.661612981 1
 
< 0.1%
256289.166667655 1
 
< 0.1%
256277.303233602 3
0.1%
256260.892747185 1
 
< 0.1%
256213.549065112 2
0.1%
255699.772760242 1
 
< 0.1%
255563.735406785 2
0.1%
254735.091450731 1
 
< 0.1%

Y좌표값
Real number (ℝ)

MISSING 

Distinct981
Distinct (%)90.9%
Missing2469
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean437989.81
Minimum264263.57
Maximum509045.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:57.162816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum264263.57
5-th percentile396989.38
Q1421389.16
median434936.27
Q3459059.75
95-th percentile476633.5
Maximum509045.01
Range244781.44
Interquartile range (IQR)37670.597

Descriptive statistics

Standard deviation24845.871
Coefficient of variation (CV)0.056727052
Kurtosis1.6601381
Mean437989.81
Median Absolute Deviation (MAD)16157.517
Skewness-0.10293636
Sum4.72591 × 108
Variance6.1731728 × 108
MonotonicityNot monotonic
2023-12-11T07:32:57.303864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459930.508280681 4
 
0.1%
473169.521635656 3
 
0.1%
420969.555008373 3
 
0.1%
441601.459006012 3
 
0.1%
427288.836589916 3
 
0.1%
438476.336876074 3
 
0.1%
418309.432794457 3
 
0.1%
467366.827893098 3
 
0.1%
467301.444870214 3
 
0.1%
418137.288094922 3
 
0.1%
Other values (971) 1048
29.5%
(Missing) 2469
69.6%
ValueCountFrequency (%)
264263.568394736 1
< 0.1%
383091.807222858 1
< 0.1%
385655.671844518 1
< 0.1%
385889.75012944 1
< 0.1%
386856.194651204 2
0.1%
387026.454168247 1
< 0.1%
387028.970095656 1
< 0.1%
387170.431421123 1
< 0.1%
387624.669687534 1
< 0.1%
387648.360303789 1
< 0.1%
ValueCountFrequency (%)
509045.007951927 1
 
< 0.1%
504481.394506567 1
 
< 0.1%
503040.140693275 1
 
< 0.1%
502298.341576212 3
0.1%
501898.896027173 1
 
< 0.1%
501736.064911163 1
 
< 0.1%
501398.938702137 1
 
< 0.1%
499836.91449356 1
 
< 0.1%
499533.202605827 1
 
< 0.1%
497620.799019357 1
 
< 0.1%

사무실면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct1596
Distinct (%)52.0%
Missing481
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean43.714956
Minimum0
Maximum1030
Zeros267
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:57.455854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median27.9
Q353.06
95-th percentile134.568
Maximum1030
Range1030
Interquartile range (IQR)38.06

Descriptive statistics

Standard deviation55.293296
Coefficient of variation (CV)1.2648599
Kurtosis52.881634
Mean43.714956
Median Absolute Deviation (MAD)16.34
Skewness5.0943384
Sum134073.77
Variance3057.3485
MonotonicityNot monotonic
2023-12-11T07:32:57.606888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 267
 
7.5%
20.0 45
 
1.3%
30.0 35
 
1.0%
33.0 34
 
1.0%
18.0 26
 
0.7%
10.0 26
 
0.7%
40.0 25
 
0.7%
15.0 24
 
0.7%
21.0 19
 
0.5%
26.0 18
 
0.5%
Other values (1586) 2548
71.8%
(Missing) 481
 
13.6%
ValueCountFrequency (%)
0.0 267
7.5%
0.92 1
 
< 0.1%
1.6 1
 
< 0.1%
2.24 1
 
< 0.1%
2.8 1
 
< 0.1%
2.89 1
 
< 0.1%
3.0 7
 
0.2%
3.09 1
 
< 0.1%
3.2 2
 
0.1%
3.3 8
 
0.2%
ValueCountFrequency (%)
1030.0 1
< 0.1%
731.0 1
< 0.1%
574.76 1
< 0.1%
570.0 1
< 0.1%
467.0 1
< 0.1%
396.9 1
< 0.1%
396.69 2
0.1%
362.8 1
< 0.1%
360.0 1
< 0.1%
332.55 1
< 0.1%

소독차량차고면적(㎡)
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1158
Distinct (%)38.3%
Missing528
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean35.640964
Minimum0
Maximum19025
Zeros275
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:57.737082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.78
median11.88
Q321.225
95-th percentile68.5575
Maximum19025
Range19025
Interquartile range (IQR)15.445

Descriptive statistics

Standard deviation420.57628
Coefficient of variation (CV)11.800362
Kurtosis1492.6443
Mean35.640964
Median Absolute Deviation (MAD)7.25
Skewness36.352035
Sum107635.71
Variance176884.41
MonotonicityNot monotonic
2023-12-11T07:32:57.873631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 275
 
7.8%
10.0 66
 
1.9%
20.0 53
 
1.5%
15.0 46
 
1.3%
18.0 40
 
1.1%
6.0 37
 
1.0%
6.6 32
 
0.9%
5.0 32
 
0.9%
12.0 31
 
0.9%
9.0 31
 
0.9%
Other values (1148) 2377
67.0%
(Missing) 528
 
14.9%
ValueCountFrequency (%)
0.0 275
7.8%
0.52 1
 
< 0.1%
0.54 1
 
< 0.1%
0.72 1
 
< 0.1%
0.9 1
 
< 0.1%
0.91 1
 
< 0.1%
1.0 1
 
< 0.1%
1.2 1
 
< 0.1%
1.22 1
 
< 0.1%
1.3 1
 
< 0.1%
ValueCountFrequency (%)
19025.0 1
< 0.1%
9072.0 1
< 0.1%
8069.0 1
< 0.1%
2900.0 1
< 0.1%
2301.0 1
< 0.1%
2296.0 1
< 0.1%
1983.0 1
< 0.1%
731.0 1
< 0.1%
666.73 1
< 0.1%
570.0 1
< 0.1%

초미립자살포기수(개)
Real number (ℝ)

Distinct11
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.1513955
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:58.002357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum31
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.87609421
Coefficient of variation (CV)0.76089769
Kurtosis485.98854
Mean1.1513955
Median Absolute Deviation (MAD)0
Skewness17.713125
Sum4084
Variance0.76754106
MonotonicityNot monotonic
2023-12-11T07:32:58.114441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 3271
92.2%
2 177
 
5.0%
3 50
 
1.4%
4 18
 
0.5%
5 12
 
0.3%
7 9
 
0.3%
6 5
 
0.1%
8 2
 
0.1%
31 1
 
< 0.1%
21 1
 
< 0.1%
ValueCountFrequency (%)
1 3271
92.2%
2 177
 
5.0%
3 50
 
1.4%
4 18
 
0.5%
5 12
 
0.3%
6 5
 
0.1%
7 9
 
0.3%
8 2
 
0.1%
16 1
 
< 0.1%
21 1
 
< 0.1%
ValueCountFrequency (%)
31 1
 
< 0.1%
21 1
 
< 0.1%
16 1
 
< 0.1%
8 2
 
0.1%
7 9
 
0.3%
6 5
 
0.1%
5 12
 
0.3%
4 18
 
0.5%
3 50
 
1.4%
2 177
5.0%

휴대용소독기수(개)
Real number (ℝ)

SKEWED 

Distinct7
Distinct (%)0.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0405977
Minimum2
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:58.231466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median2
Q32
95-th percentile2
Maximum21
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.40587686
Coefficient of variation (CV)0.19890097
Kurtosis1361.3746
Mean2.0405977
Median Absolute Deviation (MAD)0
Skewness31.146985
Sum7238
Variance0.16473602
MonotonicityNot monotonic
2023-12-11T07:32:58.347034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 3453
97.3%
3 76
 
2.1%
5 8
 
0.2%
4 6
 
0.2%
6 2
 
0.1%
7 1
 
< 0.1%
21 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
2 3453
97.3%
3 76
 
2.1%
4 6
 
0.2%
5 8
 
0.2%
6 2
 
0.1%
7 1
 
< 0.1%
21 1
 
< 0.1%
ValueCountFrequency (%)
21 1
 
< 0.1%
7 1
 
< 0.1%
6 2
 
0.1%
5 8
 
0.2%
4 6
 
0.2%
3 76
 
2.1%
2 3453
97.3%

동력분무기수(개)
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.6196786
Minimum0
Maximum60
Zeros1566
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:58.455151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum60
Range60
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2181586
Coefficient of variation (CV)1.965791
Kurtosis1608.9918
Mean0.6196786
Median Absolute Deviation (MAD)0
Skewness34.013205
Sum2198
Variance1.4839104
MonotonicityNot monotonic
2023-12-11T07:32:58.604820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 1899
53.5%
0 1566
44.1%
2 47
 
1.3%
3 21
 
0.6%
4 7
 
0.2%
5 3
 
0.1%
10 2
 
0.1%
60 1
 
< 0.1%
19 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 1566
44.1%
1 1899
53.5%
2 47
 
1.3%
3 21
 
0.6%
4 7
 
0.2%
5 3
 
0.1%
10 2
 
0.1%
19 1
 
< 0.1%
60 1
 
< 0.1%
ValueCountFrequency (%)
60 1
 
< 0.1%
19 1
 
< 0.1%
10 2
 
0.1%
5 3
 
0.1%
4 7
 
0.2%
3 21
 
0.6%
2 47
 
1.3%
1 1899
53.5%
0 1566
44.1%

수동식분무기수(개)
Real number (ℝ)

Distinct16
Distinct (%)0.5%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4.3146321
Minimum3
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:58.731125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q13
median5
Q35
95-th percentile5
Maximum55
Range52
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6770296
Coefficient of variation (CV)0.38868426
Kurtosis247.66759
Mean4.3146321
Median Absolute Deviation (MAD)0
Skewness9.7960249
Sum15304
Variance2.8124283
MonotonicityNot monotonic
2023-12-11T07:32:59.106321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
5 1843
51.9%
3 1472
41.5%
6 73
 
2.1%
4 63
 
1.8%
10 28
 
0.8%
7 28
 
0.8%
8 16
 
0.5%
15 6
 
0.2%
12 5
 
0.1%
20 4
 
0.1%
Other values (6) 9
 
0.3%
ValueCountFrequency (%)
3 1472
41.5%
4 63
 
1.8%
5 1843
51.9%
6 73
 
2.1%
7 28
 
0.8%
8 16
 
0.5%
9 3
 
0.1%
10 28
 
0.8%
11 1
 
< 0.1%
12 5
 
0.1%
ValueCountFrequency (%)
55 1
 
< 0.1%
20 4
 
0.1%
16 1
 
< 0.1%
15 6
 
0.2%
14 1
 
< 0.1%
13 2
 
0.1%
12 5
 
0.1%
11 1
 
< 0.1%
10 28
0.8%
9 3
 
0.1%

방독면수(개)
Real number (ℝ)

SKEWED 

Distinct11
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.1567522
Minimum5
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:59.196063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile5
Maximum155
Range150
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7128429
Coefficient of variation (CV)0.52607587
Kurtosis2631.9798
Mean5.1567522
Median Absolute Deviation (MAD)0
Skewness48.330815
Sum18291
Variance7.3595166
MonotonicityNot monotonic
2023-12-11T07:32:59.288678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5 3444
97.1%
6 32
 
0.9%
10 26
 
0.7%
7 20
 
0.6%
8 12
 
0.3%
20 6
 
0.2%
30 2
 
0.1%
12 2
 
0.1%
15 1
 
< 0.1%
155 1
 
< 0.1%
ValueCountFrequency (%)
5 3444
97.1%
6 32
 
0.9%
7 20
 
0.6%
8 12
 
0.3%
9 1
 
< 0.1%
10 26
 
0.7%
12 2
 
0.1%
15 1
 
< 0.1%
20 6
 
0.2%
30 2
 
0.1%
ValueCountFrequency (%)
155 1
 
< 0.1%
30 2
 
0.1%
20 6
 
0.2%
15 1
 
< 0.1%
12 2
 
0.1%
10 26
0.7%
9 1
 
< 0.1%
8 12
 
0.3%
7 20
0.6%
6 32
0.9%

보호안경수(개)
Real number (ℝ)

SKEWED 

Distinct10
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.1404003
Minimum5
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:59.378597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile5
Maximum65
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4340238
Coefficient of variation (CV)0.27897123
Kurtosis925.00221
Mean5.1404003
Median Absolute Deviation (MAD)0
Skewness25.714825
Sum18233
Variance2.0564243
MonotonicityNot monotonic
2023-12-11T07:32:59.462301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
5 3436
96.8%
6 34
 
1.0%
10 30
 
0.8%
7 18
 
0.5%
8 15
 
0.4%
20 5
 
0.1%
12 4
 
0.1%
30 2
 
0.1%
15 2
 
0.1%
65 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
5 3436
96.8%
6 34
 
1.0%
7 18
 
0.5%
8 15
 
0.4%
10 30
 
0.8%
12 4
 
0.1%
15 2
 
0.1%
20 5
 
0.1%
30 2
 
0.1%
65 1
 
< 0.1%
ValueCountFrequency (%)
65 1
 
< 0.1%
30 2
 
0.1%
20 5
 
0.1%
15 2
 
0.1%
12 4
 
0.1%
10 30
 
0.8%
8 15
 
0.4%
7 18
 
0.5%
6 34
 
1.0%
5 3436
96.8%

보호용의복수(개)
Real number (ℝ)

SKEWED 

Distinct19
Distinct (%)0.5%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.3312659
Minimum5
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:59.560719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile5
Maximum134
Range129
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.3166997
Coefficient of variation (CV)0.62212237
Kurtosis846.08374
Mean5.3312659
Median Absolute Deviation (MAD)0
Skewness25.438193
Sum18910
Variance11.000497
MonotonicityNot monotonic
2023-12-11T07:32:59.674864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
5 3376
95.2%
6 49
 
1.4%
10 40
 
1.1%
7 31
 
0.9%
20 14
 
0.4%
8 9
 
0.3%
30 5
 
0.1%
9 5
 
0.1%
18 3
 
0.1%
12 3
 
0.1%
Other values (9) 12
 
0.3%
ValueCountFrequency (%)
5 3376
95.2%
6 49
 
1.4%
7 31
 
0.9%
8 9
 
0.3%
9 5
 
0.1%
10 40
 
1.1%
12 3
 
0.1%
13 2
 
0.1%
15 2
 
0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
134 1
 
< 0.1%
100 1
 
< 0.1%
50 1
 
< 0.1%
40 1
 
< 0.1%
37 1
 
< 0.1%
30 5
 
0.1%
24 2
 
0.1%
20 14
0.4%
18 3
 
0.1%
17 1
 
< 0.1%

진공청소기수(개)
Real number (ℝ)

Distinct12
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.1984776
Minimum0
Maximum14
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2023-12-11T07:32:59.762424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78232588
Coefficient of variation (CV)0.65276638
Kurtosis74.335307
Mean1.1984776
Median Absolute Deviation (MAD)0
Skewness7.3062635
Sum4251
Variance0.61203378
MonotonicityNot monotonic
2023-12-11T07:32:59.851017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 3140
88.5%
2 276
 
7.8%
3 63
 
1.8%
4 26
 
0.7%
5 18
 
0.5%
6 8
 
0.2%
10 7
 
0.2%
0 3
 
0.1%
9 2
 
0.1%
7 2
 
0.1%
Other values (2) 2
 
0.1%
ValueCountFrequency (%)
0 3
 
0.1%
1 3140
88.5%
2 276
 
7.8%
3 63
 
1.8%
4 26
 
0.7%
5 18
 
0.5%
6 8
 
0.2%
7 2
 
0.1%
9 2
 
0.1%
10 7
 
0.2%
ValueCountFrequency (%)
14 1
 
< 0.1%
12 1
 
< 0.1%
10 7
 
0.2%
9 2
 
0.1%
7 2
 
0.1%
6 8
 
0.2%
5 18
 
0.5%
4 26
 
0.7%
3 63
 
1.8%
2 276
7.8%

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값사무실면적(㎡)소독차량차고면적(㎡)초미립자살포기수(개)휴대용소독기수(개)동력분무기수(개)수동식분무기수(개)방독면수(개)보호안경수(개)보호용의복수(개)진공청소기수(개)
0가평군(주) 국제씨앤씨2015-11-09<NA>13영업중<NA><NA><NA>12418경기도 가평군 가평읍 가화로 103-1경기도 가평군 가평읍 읍내리 476-9번지1241837.82895127.513784<NA>245161.409383480835.97697911.66.012035551
1가평군동진판매상사2007-07-20<NA>13영업중<NA>031-582-7544<NA>12419경기도 가평군 가평읍 태평길 31경기도 가평군 가평읍 376번지 1호477-80037.826822127.516658<NA>245417.761584480599.488898105.170.012155551
2가평군(주)일진환경건설20000708<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 보납로6번길 11경기도 가평군 가평읍 읍내리 468번지 34호47780537.830266127.511534<NA><NA><NA>198.025.012165551
3가평군(주) 코리아 탑 시큐리티20101221<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 연인2길 14, 3층경기도 가평군 가평읍 읍내리 489-4번지 3층1241837.830032127.511886<NA><NA><NA>106.2615.512155551
4가평군동진판매상사20070720<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 태평길 31경기도 가평군 가평읍 376번지 1호47780037.826822127.516658<NA><NA><NA>105.17<NA>12155551
5가평군크린데이20061214<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 하면 현창로 49-1경기도 가평군 하면 현리 268번지 6호 2층47783437.819217127.34784<NA><NA><NA>17.923.012155551
6가평군(주) 국제씨앤씨20151109<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 가화로 103-1경기도 가평군 가평읍 읍내리 476-9번지1241837.82895127.513784<NA><NA><NA>11.66.012035551
7가평군제일소독20120516<NA><NA>폐업 등20120611<NA><NA><NA>경기도 가평군 청평면 행자골길 18-29경기도 가평군 청평면 상천리 1171번지 9호47781437.763412127.446389<NA><NA><NA><NA><NA>12155551
8가평군(주)한신환경기업20120221<NA><NA>폐업 등20140515<NA><NA><NA>경기도 가평군 청평면 상천역로 5경기도 가평군 청평면 상천리 1722번지 10호47781437.771905127.452333<NA><NA><NA>45.07.412155551
9가평군피폴인력개발20161212<NA><NA>폐업 등20171207<NA><NA><NA>경기도 가평군 청평면 경춘로 557 (24시돌솥설렁탕)경기도 가평군 청평면 대성리 47-1번지 (24시돌솥설렁탕)1245737.720536127.403415<NA><NA><NA><NA><NA>12035551
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값사무실면적(㎡)소독차량차고면적(㎡)초미립자살포기수(개)휴대용소독기수(개)동력분무기수(개)수동식분무기수(개)방독면수(개)보호안경수(개)보호용의복수(개)진공청소기수(개)
3538화성시올케어20111122<NA><NA>폐업 등20120105<NA><NA><NA>경기도 화성시 장안면 포승장안로 1428, 나동경기도 화성시 장안면 사랑리 129-3번지 나동1858437.076365126.832786<NA><NA><NA>66.0318.012155551
3539화성시대성크린텍20120402<NA><NA>폐업 등20121127<NA><NA><NA>경기도 화성시 남양로930번길 36, 202호 (북양동)경기도 화성시 북양동 204번지 2호 202호44504037.220788126.834492<NA><NA><NA>150.530.012155551
3540화성시(주)에코나인20121115<NA><NA>폐업 등20160215<NA><NA><NA>경기도 화성시 봉담읍 동화새터길 66경기도 화성시 봉담읍 동화리 484번지 8호 2층44589337.219521126.957191<NA><NA><NA>30.06.012155551
3541화성시(주)배니솔20121228<NA><NA>폐업 등20140714<NA><NA><NA>경기도 화성시 병점동로 110-14, 5층 (진안동)경기도 화성시 진안동 874번지 3호 5층44539037.213988127.040666<NA><NA><NA>32.08.012155551
3542화성시신영청소재활용센터20130118<NA><NA>폐업 등20170208<NA><NA><NA>경기도 화성시 경기대로 1025-5, 114호 (병점동)경기도 화성시 병점동 381번지 17호44536037.20691127.035356<NA><NA><NA>28.012.012155551
3543화성시중앙방역20130717<NA><NA>폐업 등20161230<NA><NA><NA>경기도 화성시 향남읍 동오2길 31-60경기도 화성시 향남읍 동오리 110번지 3호44592937.136014126.960794<NA><NA><NA>28.0162.012155551
3544화성시주식회사 앰앰아이2014-08-05<NA>2휴업<NA>031-8003-9818<NA>18511경기도 화성시 금곡로249번길 34-1 (금곡동)경기도 화성시 금곡동 130번지1851137.183127127.07526<NA>206622.430001409015.6650060.00.012155551
3545화성시동방Industry20130128<NA><NA>휴업 등<NA><NA><NA><NA>경기도 화성시 남양로930번길 8 (북양동)경기도 화성시 북양동 254번지 8호44504037.2192126.832567<NA><NA><NA>20.020.012155551
3546화성시한동이엔지 주식회사20170329<NA><NA>휴업 등<NA><NA><NA><NA>경기도 화성시 효행로 1073, 404호 (진안동, 거성프라자)경기도 화성시 진안동 914번지 7호1839837.215416127.043938<NA><NA><NA>68.06.012035551
3547<NA>주)케이피에스2015-03-18<NA>15전출<NA>031-658-2290<NA>38492경상북도 경산시 진량읍 선화로20길 23-1, 윤성1차아파트상가 107동 2층 204호경상북도 경산시 진량읍 선화리 10893849235.864964128.794756<NA>361974.696287264263.56839537.1221.5612155551