Overview

Dataset statistics

Number of variables39
Number of observations1935
Missing cells21640
Missing cells (%)28.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory636.9 KiB
Average record size in memory337.1 B

Variable types

Categorical17
Text7
Unsupported1
DateTime1
Numeric11
Boolean2

Dataset

Description목욕장업(공동탕업) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=K1WV04EI1HVTEA6993ZH14333731&infSeq=1

Alerts

영업상태구분코드 is highly imbalanced (63.3%)Imbalance
업태구분명정보 is highly imbalanced (72.4%)Imbalance
위생업태명 is highly imbalanced (63.3%)Imbalance
사용시작지하층수 is highly imbalanced (70.2%)Imbalance
사용끝지하층수 is highly imbalanced (74.3%)Imbalance
조건부허가시작일자 is highly imbalanced (99.4%)Imbalance
조건부허가종료일자 is highly imbalanced (99.4%)Imbalance
여성종사자수 is highly imbalanced (80.3%)Imbalance
남성종사자수 is highly imbalanced (78.5%)Imbalance
다중이용업소여부 is highly imbalanced (57.5%)Imbalance
인허가취소일자 has 1935 (100.0%) missing valuesMissing
폐업일자 has 654 (33.8%) missing valuesMissing
소재지시설전화번호 has 1751 (90.5%) missing valuesMissing
소재지면적정보 has 1719 (88.8%) missing valuesMissing
도로명우편번호 has 1727 (89.3%) missing valuesMissing
소재지도로명주소 has 258 (13.3%) missing valuesMissing
WGS84위도 has 102 (5.3%) missing valuesMissing
WGS84경도 has 102 (5.3%) missing valuesMissing
X좌표값 has 1727 (89.3%) missing valuesMissing
Y좌표값 has 1727 (89.3%) missing valuesMissing
건물지상층수 has 1721 (88.9%) missing valuesMissing
건물지하층수 has 1721 (88.9%) missing valuesMissing
사용시작지상층수 has 1723 (89.0%) missing valuesMissing
사용끝지상층수 has 1723 (89.0%) missing valuesMissing
욕실수(개) has 777 (40.2%) missing valuesMissing
발한실여부 has 177 (9.1%) missing valuesMissing
조건부허가신고사유 has 1933 (99.9%) missing valuesMissing
다중이용업소여부 has 155 (8.0%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 134 (6.9%) zerosZeros
건물지하층수 has 159 (8.2%) zerosZeros
사용시작지상층수 has 129 (6.7%) zerosZeros
사용끝지상층수 has 136 (7.0%) zerosZeros
욕실수(개) has 483 (25.0%) zerosZeros

Reproduction

Analysis started2023-12-10 22:24:54.836157
Analysis finished2023-12-10 22:24:55.799141
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct31
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
수원시
194 
부천시
187 
고양시
154 
성남시
135 
안양시
127 
Other values (26)
1138 

Length

Max length4
Median length3
Mean length3.0873385
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 194
 
10.0%
부천시 187
 
9.7%
고양시 154
 
8.0%
성남시 135
 
7.0%
안양시 127
 
6.6%
안산시 127
 
6.6%
의정부시 91
 
4.7%
시흥시 86
 
4.4%
평택시 78
 
4.0%
파주시 64
 
3.3%
Other values (21) 692
35.8%

Length

2023-12-11T07:24:55.853645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 194
 
10.0%
부천시 187
 
9.7%
고양시 154
 
8.0%
성남시 135
 
7.0%
안양시 127
 
6.6%
안산시 127
 
6.6%
의정부시 91
 
4.7%
시흥시 86
 
4.4%
평택시 78
 
4.0%
파주시 64
 
3.3%
Other values (21) 692
35.8%
Distinct1540
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-12-11T07:24:56.049664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length5.8981912
Min length2

Characters and Unicode

Total characters11413
Distinct characters452
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1287 ?
Unique (%)66.5%

Sample

1st row청평목욕탕
2nd row뉴새마을사우나
3rd row준수대중목욕탕
4th row보송목욕탕
5th row제일목욕탕
ValueCountFrequency (%)
사우나 43
 
2.1%
현대목욕탕 11
 
0.5%
목욕탕 10
 
0.5%
제일목욕탕 10
 
0.5%
중앙목욕탕 9
 
0.4%
수정목욕탕 9
 
0.4%
청수탕 9
 
0.4%
대성목욕탕 7
 
0.3%
금성목욕탕 6
 
0.3%
청수목욕탕 6
 
0.3%
Other values (1575) 1946
94.2%
2023-12-11T07:24:56.367469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1166
 
10.2%
878
 
7.7%
865
 
7.6%
562
 
4.9%
521
 
4.6%
515
 
4.5%
347
 
3.0%
254
 
2.2%
199
 
1.7%
186
 
1.6%
Other values (442) 5920
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11065
97.0%
Space Separator 131
 
1.1%
Decimal Number 85
 
0.7%
Close Punctuation 46
 
0.4%
Open Punctuation 44
 
0.4%
Uppercase Letter 27
 
0.2%
Other Punctuation 8
 
0.1%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1166
 
10.5%
878
 
7.9%
865
 
7.8%
562
 
5.1%
521
 
4.7%
515
 
4.7%
347
 
3.1%
254
 
2.3%
199
 
1.8%
186
 
1.7%
Other values (410) 5572
50.4%
Uppercase Letter
ValueCountFrequency (%)
G 6
22.2%
D 3
11.1%
M 3
11.1%
K 2
 
7.4%
C 2
 
7.4%
E 2
 
7.4%
T 2
 
7.4%
L 2
 
7.4%
W 1
 
3.7%
S 1
 
3.7%
Other values (3) 3
11.1%
Decimal Number
ValueCountFrequency (%)
2 40
47.1%
4 37
43.5%
1 3
 
3.5%
5 2
 
2.4%
8 2
 
2.4%
6 1
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
a 2
28.6%
n 1
14.3%
u 1
14.3%
s 1
14.3%
e 1
14.3%
h 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
& 2
25.0%
/ 1
 
12.5%
, 1
 
12.5%
Space Separator
ValueCountFrequency (%)
131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11065
97.0%
Common 314
 
2.8%
Latin 34
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1166
 
10.5%
878
 
7.9%
865
 
7.8%
562
 
5.1%
521
 
4.7%
515
 
4.7%
347
 
3.1%
254
 
2.3%
199
 
1.8%
186
 
1.7%
Other values (410) 5572
50.4%
Latin
ValueCountFrequency (%)
G 6
17.6%
D 3
 
8.8%
M 3
 
8.8%
K 2
 
5.9%
a 2
 
5.9%
C 2
 
5.9%
E 2
 
5.9%
T 2
 
5.9%
L 2
 
5.9%
W 1
 
2.9%
Other values (9) 9
26.5%
Common
ValueCountFrequency (%)
131
41.7%
) 46
 
14.6%
( 44
 
14.0%
2 40
 
12.7%
4 37
 
11.8%
. 4
 
1.3%
1 3
 
1.0%
& 2
 
0.6%
5 2
 
0.6%
8 2
 
0.6%
Other values (3) 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11065
97.0%
ASCII 348
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1166
 
10.5%
878
 
7.9%
865
 
7.8%
562
 
5.1%
521
 
4.7%
515
 
4.7%
347
 
3.1%
254
 
2.3%
199
 
1.8%
186
 
1.7%
Other values (410) 5572
50.4%
ASCII
ValueCountFrequency (%)
131
37.6%
) 46
 
13.2%
( 44
 
12.6%
2 40
 
11.5%
4 37
 
10.6%
G 6
 
1.7%
. 4
 
1.1%
D 3
 
0.9%
1 3
 
0.9%
M 3
 
0.9%
Other values (22) 31
 
8.9%
Distinct1616
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-12-11T07:24:56.626079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2232558
Min length8

Characters and Unicode

Total characters15912
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

Unique1416 ?
Unique (%)73.2%

Sample

1st row19900108
2nd row20140114
3rd row19970317
4th row19911118
5th row19851205
ValueCountFrequency (%)
20030424 27
 
1.4%
20030227 19
 
1.0%
20030327 16
 
0.8%
20030528 15
 
0.8%
2003-03-27 7
 
0.4%
19980421 7
 
0.4%
20030410 7
 
0.4%
20030422 5
 
0.3%
20031230 5
 
0.3%
19991115 4
 
0.2%
Other values (1606) 1823
94.2%
2023-12-11T07:24:57.007237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4059
25.5%
1 3179
20.0%
2 2434
15.3%
9 2109
13.3%
8 869
 
5.5%
3 792
 
5.0%
4 579
 
3.6%
7 512
 
3.2%
6 496
 
3.1%
5 451
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15480
97.3%
Dash Punctuation 432
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059
26.2%
1 3179
20.5%
2 2434
15.7%
9 2109
13.6%
8 869
 
5.6%
3 792
 
5.1%
4 579
 
3.7%
7 512
 
3.3%
6 496
 
3.2%
5 451
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4059
25.5%
1 3179
20.0%
2 2434
15.3%
9 2109
13.3%
8 869
 
5.5%
3 792
 
5.0%
4 579
 
3.6%
7 512
 
3.2%
6 496
 
3.1%
5 451
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4059
25.5%
1 3179
20.0%
2 2434
15.3%
9 2109
13.3%
8 869
 
5.5%
3 792
 
5.0%
4 579
 
3.6%
7 512
 
3.2%
6 496
 
3.1%
5 451
 
2.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1935
Missing (%)100.0%
Memory size17.1 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1719 
1
176 
2
 
40

Length

Max length4
Median length4
Mean length3.6651163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1719
88.8%
1 176
 
9.1%
2 40
 
2.1%

Length

2023-12-11T07:24:57.419745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:24:57.513139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1719
88.8%
1 176
 
9.1%
2 40
 
2.1%

영업상태명
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
폐업 등
1241 
운영중
478 
영업
176 
폐업
 
40

Length

Max length4
Median length4
Mean length3.5297158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 등 1241
64.1%
운영중 478
 
24.7%
영업 176
 
9.1%
폐업 40
 
2.1%

Length

2023-12-11T07:24:57.637881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:24:57.755257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1281
40.3%
1241
39.1%
운영중 478
 
15.1%
영업 176
 
5.5%

폐업일자
Date

MISSING 

Distinct980
Distinct (%)76.5%
Missing654
Missing (%)33.8%
Memory size15.2 KiB
Minimum1987-08-26 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T07:24:57.856120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.982543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct182
Distinct (%)98.9%
Missing1751
Missing (%)90.5%
Memory size15.2 KiB
2023-12-11T07:24:58.257823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.211957
Min length7

Characters and Unicode

Total characters2063
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

Unique180 ?
Unique (%)97.8%

Sample

1st row031 582 7763
2nd row031 51734500
3rd row031 9760045
4th row031 905 6008
5th row031 8130001
ValueCountFrequency (%)
031 148
34.7%
032 8
 
1.9%
02 6
 
1.4%
16615510 2
 
0.5%
376 2
 
0.5%
5188 2
 
0.5%
966 2
 
0.5%
842 2
 
0.5%
848 2
 
0.5%
941 2
 
0.5%
Other values (249) 250
58.7%
2023-12-11T07:24:58.668659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 328
15.9%
3 291
14.1%
1 264
12.8%
249
12.1%
6 172
8.3%
8 145
7.0%
5 140
6.8%
7 130
 
6.3%
2 130
 
6.3%
9 115
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1814
87.9%
Space Separator 249
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 328
18.1%
3 291
16.0%
1 264
14.6%
6 172
9.5%
8 145
8.0%
5 140
7.7%
7 130
 
7.2%
2 130
 
7.2%
9 115
 
6.3%
4 99
 
5.5%
Space Separator
ValueCountFrequency (%)
249
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2063
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 328
15.9%
3 291
14.1%
1 264
12.8%
249
12.1%
6 172
8.3%
8 145
7.0%
5 140
6.8%
7 130
 
6.3%
2 130
 
6.3%
9 115
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 328
15.9%
3 291
14.1%
1 264
12.8%
249
12.1%
6 172
8.3%
8 145
7.0%
5 140
6.8%
7 130
 
6.3%
2 130
 
6.3%
9 115
 
5.6%

소재지면적정보
Real number (ℝ)

MISSING 

Distinct210
Distinct (%)97.2%
Missing1719
Missing (%)88.8%
Infinite0
Infinite (%)0.0%
Mean1166.1741
Minimum0
Maximum7065.02
Zeros6
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:24:58.799724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile86.225
Q1382.655
median737.54
Q31537.6275
95-th percentile3310.26
Maximum7065.02
Range7065.02
Interquartile range (IQR)1154.9725

Descriptive statistics

Standard deviation1189.7936
Coefficient of variation (CV)1.0202538
Kurtosis5.2863939
Mean1166.1741
Median Absolute Deviation (MAD)498.365
Skewness2.0430128
Sum251893.6
Variance1415608.8
MonotonicityNot monotonic
2023-12-11T07:24:58.921642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
0.3%
155.81 2
 
0.1%
983.99 1
 
0.1%
2370.56 1
 
0.1%
1153.77 1
 
0.1%
891.23 1
 
0.1%
497.86 1
 
0.1%
1557.0 1
 
0.1%
790.0 1
 
0.1%
3960.0 1
 
0.1%
Other values (200) 200
 
10.3%
(Missing) 1719
88.8%
ValueCountFrequency (%)
0.0 6
0.3%
23.2 1
 
0.1%
38.26 1
 
0.1%
59.16 1
 
0.1%
63.75 1
 
0.1%
74.0 1
 
0.1%
90.3 1
 
0.1%
98.94 1
 
0.1%
108.06 1
 
0.1%
109.51 1
 
0.1%
ValueCountFrequency (%)
7065.02 1
0.1%
6042.69 1
0.1%
6021.97 1
0.1%
5258.19 1
0.1%
5074.0 1
0.1%
4795.0 1
0.1%
4161.04 1
0.1%
3960.0 1
0.1%
3783.0 1
0.1%
3596.8 1
0.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct189
Distinct (%)90.9%
Missing1727
Missing (%)89.3%
Infinite0
Infinite (%)0.0%
Mean13779.361
Minimum10017
Maximum18511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:24:59.039292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10017
5-th percentile10282.75
Q111401.25
median13541
Q316263.5
95-th percentile18378.6
Maximum18511
Range8494
Interquartile range (IQR)4862.25

Descriptive statistics

Standard deviation2738.6715
Coefficient of variation (CV)0.19875171
Kurtosis-1.3041947
Mean13779.361
Median Absolute Deviation (MAD)2378
Skewness0.29125759
Sum2866107
Variance7500321.7
MonotonicityNot monotonic
2023-12-11T07:24:59.157937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11152 3
 
0.2%
18453 3
 
0.2%
17548 2
 
0.1%
11520 2
 
0.1%
11687 2
 
0.1%
17854 2
 
0.1%
10896 2
 
0.1%
10495 2
 
0.1%
10274 2
 
0.1%
17562 2
 
0.1%
Other values (179) 186
 
9.6%
(Missing) 1727
89.3%
ValueCountFrequency (%)
10017 1
0.1%
10057 1
0.1%
10083 1
0.1%
10125 1
0.1%
10130 1
0.1%
10228 1
0.1%
10252 1
0.1%
10274 2
0.1%
10275 1
0.1%
10281 1
0.1%
ValueCountFrequency (%)
18511 2
0.1%
18490 1
 
0.1%
18478 1
 
0.1%
18455 2
0.1%
18453 3
0.2%
18412 1
 
0.1%
18401 1
 
0.1%
18337 1
 
0.1%
18244 1
 
0.1%
18119 1
 
0.1%
Distinct1505
Distinct (%)89.7%
Missing258
Missing (%)13.3%
Memory size15.2 KiB
2023-12-11T07:24:59.456017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length53
Mean length24.379249
Min length13

Characters and Unicode

Total characters40884
Distinct characters424
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

Unique1348 ?
Unique (%)80.4%

Sample

1st row경기도 가평군 청평면 잠곡로 17
2nd row경기도 가평군 가평읍 문화로 154
3rd row경기도 가평군 가평읍 석봉로 209
4th row경기도 가평군 조종면 현창로56번길 27
5th row경기도 가평군 조종면 현창로 53 (.4)
ValueCountFrequency (%)
경기도 1677
 
18.6%
수원시 172
 
1.9%
부천시 160
 
1.8%
고양시 140
 
1.6%
성남시 123
 
1.4%
안산시 110
 
1.2%
안양시 107
 
1.2%
덕양구 81
 
0.9%
의정부시 78
 
0.9%
시흥시 78
 
0.9%
Other values (2435) 6281
69.7%
2023-12-11T07:24:59.901462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7340
 
18.0%
1760
 
4.3%
1755
 
4.3%
1721
 
4.2%
1704
 
4.2%
1 1584
 
3.9%
1557
 
3.8%
2 943
 
2.3%
923
 
2.3%
776
 
1.9%
Other values (414) 20821
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24214
59.2%
Space Separator 7340
 
18.0%
Decimal Number 6894
 
16.9%
Open Punctuation 738
 
1.8%
Close Punctuation 737
 
1.8%
Other Punctuation 565
 
1.4%
Dash Punctuation 300
 
0.7%
Uppercase Letter 74
 
0.2%
Math Symbol 16
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1760
 
7.3%
1755
 
7.2%
1721
 
7.1%
1704
 
7.0%
1557
 
6.4%
923
 
3.8%
776
 
3.2%
756
 
3.1%
621
 
2.6%
530
 
2.2%
Other values (372) 12111
50.0%
Uppercase Letter
ValueCountFrequency (%)
B 41
55.4%
A 9
 
12.2%
C 3
 
4.1%
M 3
 
4.1%
D 3
 
4.1%
I 3
 
4.1%
P 2
 
2.7%
K 2
 
2.7%
Y 2
 
2.7%
E 2
 
2.7%
Other values (3) 4
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 1584
23.0%
2 943
13.7%
3 732
10.6%
4 634
9.2%
5 583
 
8.5%
0 557
 
8.1%
7 519
 
7.5%
6 496
 
7.2%
8 433
 
6.3%
9 413
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
16.7%
s 1
16.7%
h 1
16.7%
e 1
16.7%
i 1
16.7%
r 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 551
97.5%
. 12
 
2.1%
& 1
 
0.2%
/ 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 735
99.6%
{ 2
 
0.3%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 734
99.6%
} 2
 
0.3%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
7340
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24214
59.2%
Common 16590
40.6%
Latin 80
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1760
 
7.3%
1755
 
7.2%
1721
 
7.1%
1704
 
7.0%
1557
 
6.4%
923
 
3.8%
776
 
3.2%
756
 
3.1%
621
 
2.6%
530
 
2.2%
Other values (372) 12111
50.0%
Common
ValueCountFrequency (%)
7340
44.2%
1 1584
 
9.5%
2 943
 
5.7%
( 735
 
4.4%
) 734
 
4.4%
3 732
 
4.4%
4 634
 
3.8%
5 583
 
3.5%
0 557
 
3.4%
, 551
 
3.3%
Other values (13) 2197
 
13.2%
Latin
ValueCountFrequency (%)
B 41
51.2%
A 9
 
11.2%
C 3
 
3.8%
M 3
 
3.8%
D 3
 
3.8%
I 3
 
3.8%
P 2
 
2.5%
K 2
 
2.5%
Y 2
 
2.5%
E 2
 
2.5%
Other values (9) 10
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24214
59.2%
ASCII 16670
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7340
44.0%
1 1584
 
9.5%
2 943
 
5.7%
( 735
 
4.4%
) 734
 
4.4%
3 732
 
4.4%
4 634
 
3.8%
5 583
 
3.5%
0 557
 
3.3%
, 551
 
3.3%
Other values (32) 2277
 
13.7%
Hangul
ValueCountFrequency (%)
1760
 
7.3%
1755
 
7.2%
1721
 
7.1%
1704
 
7.0%
1557
 
6.4%
923
 
3.8%
776
 
3.2%
756
 
3.1%
621
 
2.6%
530
 
2.2%
Other values (372) 12111
50.0%
Distinct1834
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-12-11T07:25:00.248428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length24.535401
Min length14

Characters and Unicode

Total characters47476
Distinct characters394
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

Unique1741 ?
Unique (%)90.0%

Sample

1st row경기도 가평군 청평면 청평리 397-6번지
2nd row경기도 가평군 가평읍 대곡리 318-4번지
3rd row경기도 가평군 가평읍 읍내리 637-6번지
4th row경기도 가평군 조종면 현리 261-8번지
5th row경기도 가평군 조종면 현리 268-3번지 .4
ValueCountFrequency (%)
경기도 1935
 
19.3%
수원시 194
 
1.9%
부천시 187
 
1.9%
고양시 154
 
1.5%
성남시 135
 
1.3%
안양시 128
 
1.3%
안산시 127
 
1.3%
덕양구 91
 
0.9%
의정부시 91
 
0.9%
시흥시 86
 
0.9%
Other values (2858) 6898
68.8%
2023-12-11T07:25:00.674049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8298
 
17.5%
2136
 
4.5%
1 2048
 
4.3%
1987
 
4.2%
1975
 
4.2%
1964
 
4.1%
1948
 
4.1%
1847
 
3.9%
1750
 
3.7%
- 1556
 
3.3%
Other values (384) 21967
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27638
58.2%
Decimal Number 9379
 
19.8%
Space Separator 8298
 
17.5%
Dash Punctuation 1556
 
3.3%
Other Punctuation 326
 
0.7%
Uppercase Letter 92
 
0.2%
Open Punctuation 82
 
0.2%
Close Punctuation 81
 
0.2%
Math Symbol 18
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2136
 
7.7%
1987
 
7.2%
1975
 
7.1%
1964
 
7.1%
1948
 
7.0%
1847
 
6.7%
1750
 
6.3%
845
 
3.1%
597
 
2.2%
562
 
2.0%
Other values (339) 12027
43.5%
Uppercase Letter
ValueCountFrequency (%)
B 55
59.8%
A 10
 
10.9%
C 4
 
4.3%
E 3
 
3.3%
M 3
 
3.3%
D 3
 
3.3%
T 2
 
2.2%
P 2
 
2.2%
Y 2
 
2.2%
S 2
 
2.2%
Other values (5) 6
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 2048
21.8%
2 1217
13.0%
3 973
10.4%
4 850
9.1%
5 816
 
8.7%
0 764
 
8.1%
7 751
 
8.0%
6 724
 
7.7%
8 630
 
6.7%
9 606
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
i 1
16.7%
s 1
16.7%
r 1
16.7%
e 1
16.7%
h 1
16.7%
t 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 286
87.7%
. 37
 
11.3%
& 1
 
0.3%
/ 1
 
0.3%
@ 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 79
96.3%
{ 2
 
2.4%
[ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 78
96.3%
} 2
 
2.5%
] 1
 
1.2%
Space Separator
ValueCountFrequency (%)
8298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1556
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27638
58.2%
Common 19740
41.6%
Latin 98
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2136
 
7.7%
1987
 
7.2%
1975
 
7.1%
1964
 
7.1%
1948
 
7.0%
1847
 
6.7%
1750
 
6.3%
845
 
3.1%
597
 
2.2%
562
 
2.0%
Other values (339) 12027
43.5%
Common
ValueCountFrequency (%)
8298
42.0%
1 2048
 
10.4%
- 1556
 
7.9%
2 1217
 
6.2%
3 973
 
4.9%
4 850
 
4.3%
5 816
 
4.1%
0 764
 
3.9%
7 751
 
3.8%
6 724
 
3.7%
Other values (14) 1743
 
8.8%
Latin
ValueCountFrequency (%)
B 55
56.1%
A 10
 
10.2%
C 4
 
4.1%
E 3
 
3.1%
M 3
 
3.1%
D 3
 
3.1%
T 2
 
2.0%
P 2
 
2.0%
Y 2
 
2.0%
S 2
 
2.0%
Other values (11) 12
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27638
58.2%
ASCII 19838
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8298
41.8%
1 2048
 
10.3%
- 1556
 
7.8%
2 1217
 
6.1%
3 973
 
4.9%
4 850
 
4.3%
5 816
 
4.1%
0 764
 
3.9%
7 751
 
3.8%
6 724
 
3.6%
Other values (35) 1841
 
9.3%
Hangul
ValueCountFrequency (%)
2136
 
7.7%
1987
 
7.2%
1975
 
7.1%
1964
 
7.1%
1948
 
7.0%
1847
 
6.7%
1750
 
6.3%
845
 
3.1%
597
 
2.2%
562
 
2.0%
Other values (339) 12027
43.5%
Distinct1145
Distinct (%)59.4%
Missing8
Missing (%)0.4%
Memory size15.2 KiB
2023-12-11T07:25:00.979044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9750908
Min length5

Characters and Unicode

Total characters11514
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

Unique704 ?
Unique (%)36.5%

Sample

1st row477813
2nd row477804
3rd row477801
4th row12437
5th row12437
ValueCountFrequency (%)
425868 15
 
0.8%
483030 10
 
0.5%
459120 9
 
0.5%
480867 8
 
0.4%
480840 8
 
0.4%
442819 7
 
0.4%
459110 7
 
0.4%
411827 6
 
0.3%
429862 6
 
0.3%
447802 6
 
0.3%
Other values (1135) 1845
95.7%
2023-12-11T07:25:01.417358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2670
23.2%
8 1696
14.7%
1 1337
11.6%
0 1141
9.9%
2 1114
9.7%
3 885
 
7.7%
6 778
 
6.8%
5 710
 
6.2%
7 565
 
4.9%
9 426
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11322
98.3%
Dash Punctuation 192
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2670
23.6%
8 1696
15.0%
1 1337
11.8%
0 1141
10.1%
2 1114
9.8%
3 885
 
7.8%
6 778
 
6.9%
5 710
 
6.3%
7 565
 
5.0%
9 426
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11514
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2670
23.2%
8 1696
14.7%
1 1337
11.6%
0 1141
9.9%
2 1114
9.7%
3 885
 
7.7%
6 778
 
6.8%
5 710
 
6.2%
7 565
 
4.9%
9 426
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2670
23.2%
8 1696
14.7%
1 1337
11.6%
0 1141
9.9%
2 1114
9.7%
3 885
 
7.7%
6 778
 
6.8%
5 710
 
6.2%
7 565
 
4.9%
9 426
 
3.7%

WGS84위도
Real number (ℝ)

MISSING 

Distinct1526
Distinct (%)83.3%
Missing102
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean37.449227
Minimum36.916271
Maximum38.195385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:01.550297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.916271
5-th percentile37.076994
Q137.295526
median37.415493
Q337.622458
95-th percentile37.84022
Maximum38.195385
Range1.2791139
Interquartile range (IQR)0.32693235

Descriptive statistics

Standard deviation0.22365462
Coefficient of variation (CV)0.0059722093
Kurtosis-0.019404243
Mean37.449227
Median Absolute Deviation (MAD)0.13466081
Skewness0.32094903
Sum68644.433
Variance0.05002139
MonotonicityNot monotonic
2023-12-11T07:25:01.679285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3852378798 5
 
0.3%
37.0737621131 4
 
0.2%
37.3173704199 4
 
0.2%
37.2884869029 4
 
0.2%
37.5204009633 4
 
0.2%
37.5229209923 4
 
0.2%
37.6227528209 4
 
0.2%
37.3484414041 3
 
0.2%
37.4823804994 3
 
0.2%
37.6559842555 3
 
0.2%
Other values (1516) 1795
92.8%
(Missing) 102
 
5.3%
ValueCountFrequency (%)
36.9162708577 1
0.1%
36.9541890474 1
0.1%
36.9598955481 1
0.1%
36.9610833576 1
0.1%
36.9615940422 1
0.1%
36.9628197157 1
0.1%
36.9630731148 1
0.1%
36.9635947812 1
0.1%
36.9806819927 1
0.1%
36.9836342686 1
0.1%
ValueCountFrequency (%)
38.1953848011 1
0.1%
38.1862048375 2
0.1%
38.1205826615 1
0.1%
38.099682319 1
0.1%
38.0925148864 1
0.1%
38.0920020502 1
0.1%
38.0911886465 2
0.1%
38.0910958227 1
0.1%
38.0841100318 1
0.1%
38.0428270203 1
0.1%

WGS84경도
Real number (ℝ)

MISSING 

Distinct1526
Distinct (%)83.3%
Missing102
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean126.99687
Minimum126.55724
Maximum127.75065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:01.800682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55724
5-th percentile126.75372
Q1126.83073
median126.99205
Q3127.11453
95-th percentile127.42116
Maximum127.75065
Range1.1934033
Interquartile range (IQR)0.28380339

Descriptive statistics

Standard deviation0.19982509
Coefficient of variation (CV)0.0015734647
Kurtosis0.90600094
Mean126.99687
Median Absolute Deviation (MAD)0.1453598
Skewness0.85980205
Sum232785.26
Variance0.039930067
MonotonicityNot monotonic
2023-12-11T07:25:01.943824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8592818605 5
 
0.3%
127.0495608065 4
 
0.2%
126.8423088804 4
 
0.2%
126.8631379166 4
 
0.2%
126.7876495515 4
 
0.2%
126.8051778322 4
 
0.2%
126.8348230329 4
 
0.2%
127.1677263134 3
 
0.2%
126.7844026011 3
 
0.2%
126.8363179091 3
 
0.2%
Other values (1516) 1795
92.8%
(Missing) 102
 
5.3%
ValueCountFrequency (%)
126.5572444891 1
0.1%
126.5655170392 1
0.1%
126.5829559918 2
0.1%
126.5855641997 1
0.1%
126.5976057487 1
0.1%
126.6000799574 1
0.1%
126.6006492591 1
0.1%
126.6055271509 1
0.1%
126.6108770808 2
0.1%
126.6234900982 1
0.1%
ValueCountFrequency (%)
127.7506477669 1
 
0.1%
127.7288275602 1
 
0.1%
127.7275117909 2
0.1%
127.699168526 1
 
0.1%
127.6745199482 1
 
0.1%
127.6616845117 1
 
0.1%
127.6610453985 2
0.1%
127.6507833872 1
 
0.1%
127.6444894892 3
0.2%
127.6394215896 1
 
0.1%

업태구분명정보
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1719 
공동탕업
 
100
공동탕업+찜질시설서비스영업
 
58
찜질시설서비스영업
 
31
목욕장업 기타
 
23

Length

Max length14
Median length4
Mean length4.4155039
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1719
88.8%
공동탕업 100
 
5.2%
공동탕업+찜질시설서비스영업 58
 
3.0%
찜질시설서비스영업 31
 
1.6%
목욕장업 기타 23
 
1.2%
한증막업 4
 
0.2%

Length

2023-12-11T07:25:02.058936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:02.154356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1719
87.8%
공동탕업 100
 
5.1%
공동탕업+찜질시설서비스영업 58
 
3.0%
찜질시설서비스영업 31
 
1.6%
목욕장업 23
 
1.2%
기타 23
 
1.2%
한증막업 4
 
0.2%

X좌표값
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)97.1%
Missing1727
Missing (%)89.3%
Infinite0
Infinite (%)0.0%
Mean201056.77
Minimum165639.15
Maximum266374.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:02.262698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165639.15
5-th percentile177413.01
Q1185303.51
median202124.12
Q3211730.94
95-th percentile238676.35
Maximum266374.55
Range100735.4
Interquartile range (IQR)26427.436

Descriptive statistics

Standard deviation18544.655
Coefficient of variation (CV)0.092235917
Kurtosis0.71821426
Mean201056.77
Median Absolute Deviation (MAD)13350.369
Skewness0.73265961
Sum41819808
Variance3.4390425 × 108
MonotonicityNot monotonic
2023-12-11T07:25:02.376814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206471.194103481 3
 
0.2%
210652.858662964 2
 
0.1%
178951.22540722 2
 
0.1%
206962.889471431 2
 
0.1%
239710.683350335 2
 
0.1%
205706.990927239 1
 
0.1%
205683.725259652 1
 
0.1%
196392.985187818 1
 
0.1%
197864.213593629 1
 
0.1%
195688.461806568 1
 
0.1%
Other values (192) 192
 
9.9%
(Missing) 1727
89.3%
ValueCountFrequency (%)
165639.149530017 1
0.1%
166959.614317371 1
0.1%
170608.880032241 1
0.1%
174999.893224902 1
0.1%
175664.38434522 1
0.1%
175941.924905526 1
0.1%
176050.349785259 1
0.1%
176313.285156484 1
0.1%
176445.884436837 1
0.1%
176955.625319079 1
0.1%
ValueCountFrequency (%)
266374.549446121 1
0.1%
264532.546815963 1
0.1%
258476.005943628 1
0.1%
244698.347651322 1
0.1%
243486.988795276 1
0.1%
242173.405064909 1
0.1%
239936.874017955 1
0.1%
239710.683350335 2
0.1%
239553.261443143 1
0.1%
238752.709300856 1
0.1%

Y좌표값
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)97.1%
Missing1727
Missing (%)89.3%
Infinite0
Infinite (%)0.0%
Mean441917.9
Minimum387559.39
Maximum520364.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:02.482591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum387559.39
5-th percentile389661.87
Q1422839.03
median441564.74
Q3465021.75
95-th percentile481770.16
Maximum520364.12
Range132804.73
Interquartile range (IQR)42182.724

Descriptive statistics

Standard deviation27606.652
Coefficient of variation (CV)0.062470092
Kurtosis-0.63289594
Mean441917.9
Median Absolute Deviation (MAD)21119.68
Skewness-0.20900039
Sum91918922
Variance7.6212722 × 108
MonotonicityNot monotonic
2023-12-11T07:25:02.607703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411723.937975842 3
 
0.2%
459434.426215342 2
 
0.1%
469510.566913954 2
 
0.1%
408114.363030603 2
 
0.1%
420445.055803857 2
 
0.1%
481346.665149204 1
 
0.1%
481998.194839239 1
 
0.1%
471366.511969349 1
 
0.1%
470387.112430508 1
 
0.1%
469518.815342144 1
 
0.1%
Other values (192) 192
 
9.9%
(Missing) 1727
89.3%
ValueCountFrequency (%)
387559.389577978 1
0.1%
387661.780102072 1
0.1%
388093.036705258 1
0.1%
388198.517072238 1
0.1%
388446.455743245 1
0.1%
388526.797535673 1
0.1%
388645.341311963 1
0.1%
388925.793714913 1
0.1%
389323.024936923 1
0.1%
389412.560526882 1
0.1%
ValueCountFrequency (%)
520364.124479398 1
0.1%
489570.351594913 1
0.1%
489433.058429201 1
0.1%
488322.116635734 1
0.1%
488008.343928707 1
0.1%
487373.659052862 1
0.1%
487353.217662945 1
0.1%
487308.589341288 1
0.1%
483236.824840494 1
0.1%
483034.854971294 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
공동탕업
1616 
<NA>
 
155
목욕장업 기타
 
71
공동탕업+찜질시설서비스영업
 
58
찜질시설서비스영업
 
31

Length

Max length14
Median length4
Mean length4.4899225
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1616
83.5%
<NA> 155
 
8.0%
목욕장업 기타 71
 
3.7%
공동탕업+찜질시설서비스영업 58
 
3.0%
찜질시설서비스영업 31
 
1.6%
한증막업 4
 
0.2%

Length

2023-12-11T07:25:02.715023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:02.801577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1616
80.6%
na 155
 
7.7%
목욕장업 71
 
3.5%
기타 71
 
3.5%
공동탕업+찜질시설서비스영업 58
 
2.9%
찜질시설서비스영업 31
 
1.5%
한증막업 4
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)7.9%
Missing1721
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean1.9579439
Minimum0
Maximum23
Zeros134
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:02.884181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile9
Maximum23
Range23
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6273747
Coefficient of variation (CV)1.8526448
Kurtosis9.9298947
Mean1.9579439
Median Absolute Deviation (MAD)0
Skewness2.783061
Sum419
Variance13.157847
MonotonicityNot monotonic
2023-12-11T07:25:02.968840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 134
 
6.9%
4 13
 
0.7%
2 11
 
0.6%
3 11
 
0.6%
1 10
 
0.5%
5 7
 
0.4%
7 6
 
0.3%
6 6
 
0.3%
9 5
 
0.3%
8 3
 
0.2%
Other values (7) 8
 
0.4%
(Missing) 1721
88.9%
ValueCountFrequency (%)
0 134
6.9%
1 10
 
0.5%
2 11
 
0.6%
3 11
 
0.6%
4 13
 
0.7%
5 7
 
0.4%
6 6
 
0.3%
7 6
 
0.3%
8 3
 
0.2%
9 5
 
0.3%
ValueCountFrequency (%)
23 1
 
0.1%
20 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%
12 1
 
0.1%
11 1
 
0.1%
10 2
 
0.1%
9 5
0.3%
8 3
0.2%
7 6
0.3%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.8%
Missing1721
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean0.43457944
Minimum0
Maximum5
Zeros159
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:03.047241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.87903092
Coefficient of variation (CV)2.0227163
Kurtosis6.0347099
Mean0.43457944
Median Absolute Deviation (MAD)0
Skewness2.3782843
Sum93
Variance0.77269536
MonotonicityNot monotonic
2023-12-11T07:25:03.336997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 159
 
8.2%
1 30
 
1.6%
2 16
 
0.8%
3 6
 
0.3%
4 2
 
0.1%
5 1
 
0.1%
(Missing) 1721
88.9%
ValueCountFrequency (%)
0 159
8.2%
1 30
 
1.6%
2 16
 
0.8%
3 6
 
0.3%
4 2
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.1%
3 6
 
0.3%
2 16
 
0.8%
1 30
 
1.6%
0 159
8.2%

사용시작지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)5.2%
Missing1723
Missing (%)89.0%
Infinite0
Infinite (%)0.0%
Mean1.2924528
Minimum0
Maximum11
Zeros129
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:03.417899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6.45
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2768856
Coefficient of variation (CV)1.7616779
Kurtosis3.3883009
Mean1.2924528
Median Absolute Deviation (MAD)0
Skewness2.0027365
Sum274
Variance5.1842082
MonotonicityNot monotonic
2023-12-11T07:25:03.503623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 129
 
6.7%
1 33
 
1.7%
2 10
 
0.5%
5 9
 
0.5%
4 8
 
0.4%
3 6
 
0.3%
8 6
 
0.3%
6 6
 
0.3%
7 3
 
0.2%
10 1
 
0.1%
(Missing) 1723
89.0%
ValueCountFrequency (%)
0 129
6.7%
1 33
 
1.7%
2 10
 
0.5%
3 6
 
0.3%
4 8
 
0.4%
5 9
 
0.5%
6 6
 
0.3%
7 3
 
0.2%
8 6
 
0.3%
10 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
10 1
 
0.1%
8 6
 
0.3%
7 3
 
0.2%
6 6
 
0.3%
5 9
 
0.5%
4 8
 
0.4%
3 6
 
0.3%
2 10
 
0.5%
1 33
1.7%

사용끝지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.7%
Missing1723
Missing (%)89.0%
Infinite0
Infinite (%)0.0%
Mean1.4481132
Minimum0
Maximum12
Zeros136
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:03.586661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5485143
Coefficient of variation (CV)1.7598861
Kurtosis3.0234036
Mean1.4481132
Median Absolute Deviation (MAD)0
Skewness1.9347849
Sum307
Variance6.4949253
MonotonicityNot monotonic
2023-12-11T07:25:03.677506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 136
 
7.0%
2 17
 
0.9%
3 13
 
0.7%
1 13
 
0.7%
6 8
 
0.4%
4 6
 
0.3%
9 6
 
0.3%
5 4
 
0.2%
8 4
 
0.2%
7 3
 
0.2%
Other values (2) 2
 
0.1%
(Missing) 1723
89.0%
ValueCountFrequency (%)
0 136
7.0%
1 13
 
0.7%
2 17
 
0.9%
3 13
 
0.7%
4 6
 
0.3%
5 4
 
0.2%
6 8
 
0.4%
7 3
 
0.2%
8 4
 
0.2%
9 6
 
0.3%
ValueCountFrequency (%)
12 1
 
0.1%
10 1
 
0.1%
9 6
 
0.3%
8 4
 
0.2%
7 3
 
0.2%
6 8
0.4%
5 4
 
0.2%
4 6
 
0.3%
3 13
0.7%
2 17
0.9%

사용시작지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1723 
0
 
166
1
 
39
2
 
7

Length

Max length4
Median length4
Mean length3.6713178
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1723
89.0%
0 166
 
8.6%
1 39
 
2.0%
2 7
 
0.4%

Length

2023-12-11T07:25:03.780675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:03.894462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1723
89.0%
0 166
 
8.6%
1 39
 
2.0%
2 7
 
0.4%

사용끝지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1724 
0
 
168
1
 
32
2
 
10
3
 
1

Length

Max length4
Median length4
Mean length3.6728682
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1724
89.1%
0 168
 
8.7%
1 32
 
1.7%
2 10
 
0.5%
3 1
 
0.1%

Length

2023-12-11T07:25:04.001945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:04.088423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1724
89.1%
0 168
 
8.7%
1 32
 
1.7%
2 10
 
0.5%
3 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:04.179178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:04.259395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:04.343675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:04.424868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%

욕실수(개)
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)2.4%
Missing777
Missing (%)40.2%
Infinite0
Infinite (%)0.0%
Mean2.1493955
Minimum0
Maximum74
Zeros483
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T07:25:04.498981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile6
Maximum74
Range74
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.1529044
Coefficient of variation (CV)2.3973738
Kurtosis76.918037
Mean2.1493955
Median Absolute Deviation (MAD)2
Skewness7.8150235
Sum2489
Variance26.552424
MonotonicityNot monotonic
2023-12-11T07:25:04.592192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 483
25.0%
2 459
23.7%
1 47
 
2.4%
6 47
 
2.4%
4 46
 
2.4%
3 18
 
0.9%
8 12
 
0.6%
7 7
 
0.4%
10 6
 
0.3%
9 6
 
0.3%
Other values (18) 27
 
1.4%
(Missing) 777
40.2%
ValueCountFrequency (%)
0 483
25.0%
1 47
 
2.4%
2 459
23.7%
3 18
 
0.9%
4 46
 
2.4%
5 4
 
0.2%
6 47
 
2.4%
7 7
 
0.4%
8 12
 
0.6%
9 6
 
0.3%
ValueCountFrequency (%)
74 1
0.1%
58 1
0.1%
55 1
0.1%
54 1
0.1%
43 1
0.1%
41 1
0.1%
39 1
0.1%
37 1
0.1%
36 1
0.1%
33 2
0.1%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.1%
Missing177
Missing (%)9.1%
Memory size3.9 KiB
False
1144 
True
614 
(Missing)
177 
ValueCountFrequency (%)
False 1144
59.1%
True 614
31.7%
(Missing) 177
 
9.1%
2023-12-11T07:25:04.677556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:04.763450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:04.844386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%
Distinct2
Distinct (%)100.0%
Missing1933
Missing (%)99.9%
Memory size15.2 KiB
2023-12-11T07:25:04.940768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8.5
Mean length8.5
Min length8

Characters and Unicode

Total characters17
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row위탁계약기간 영업
2nd row황준성(운영자)
ValueCountFrequency (%)
위탁계약기간 1
33.3%
영업 1
33.3%
황준성(운영자 1
33.3%
2023-12-11T07:25:05.147158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (6) 6
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
82.4%
Space Separator 1
 
5.9%
Open Punctuation 1
 
5.9%
Close Punctuation 1
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (3) 3
21.4%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
82.4%
Common 3
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (3) 3
21.4%
Common
ValueCountFrequency (%)
1
33.3%
( 1
33.3%
) 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
82.4%
ASCII 3
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (3) 3
21.4%
ASCII
ValueCountFrequency (%)
1
33.3%
( 1
33.3%
) 1
33.3%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1934 
20141127
 
1

Length

Max length8
Median length4
Mean length4.0020672
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1934
99.9%
20141127 1
 
0.1%

Length

2023-12-11T07:25:05.253006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:05.334887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1934
99.9%
20141127 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1934 
20151130
 
1

Length

Max length8
Median length4
Mean length4.0020672
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1934
99.9%
20151130 1
 
0.1%

Length

2023-12-11T07:25:05.418396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:05.499792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1934
99.9%
20151130 1
 
0.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:05.581391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:05.664428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1731 
0
199 
1
 
2
3
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.6842377
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1731
89.5%
0 199
 
10.3%
1 2
 
0.1%
3 1
 
0.1%
7 1
 
0.1%
50 1
 
0.1%

Length

2023-12-11T07:25:05.750309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:05.839126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1731
89.5%
0 199
 
10.3%
1 2
 
0.1%
3 1
 
0.1%
7 1
 
0.1%
50 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1731 
0
201 
4
 
1
2
 
1
17
 
1

Length

Max length4
Median length4
Mean length3.6842377
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1731
89.5%
0 201
 
10.4%
4 1
 
0.1%
2 1
 
0.1%
17 1
 
0.1%

Length

2023-12-11T07:25:05.935732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:06.022824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1731
89.5%
0 201
 
10.4%
4 1
 
0.1%
2 1
 
0.1%
17 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:06.117393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:06.197000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1722 
0
213 

Length

Max length4
Median length4
Mean length3.6697674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
89.0%
0 213
 
11.0%

Length

2023-12-11T07:25:06.283507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:06.362542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1722
89.0%
0 213
 
11.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing155
Missing (%)8.0%
Memory size3.9 KiB
False
1626 
True
 
154
(Missing)
 
155
ValueCountFrequency (%)
False 1626
84.0%
True 154
 
8.0%
(Missing) 155
 
8.0%
2023-12-11T07:25:06.431471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수(개)발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
0가평군청평목욕탕19900108<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 청평면 잠곡로 17경기도 가평군 청평면 청평리 397-6번지47781337.737169127.420713<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1가평군뉴새마을사우나20140114<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 문화로 154경기도 가평군 가평읍 대곡리 318-4번지47780437.826814127.508511<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>2Y<NA><NA><NA><NA><NA><NA><NA><NA><NA>Y
2가평군준수대중목욕탕19970317<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 석봉로 209경기도 가평군 가평읍 읍내리 637-6번지47780137.833817127.509273<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
3가평군보송목욕탕19911118<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 조종면 현창로56번길 27경기도 가평군 조종면 현리 261-8번지1243737.819734127.350179<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
4가평군제일목욕탕19851205<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 조종면 현창로 53 (.4)경기도 가평군 조종면 현리 268-3번지 .41243737.819424127.347623<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
5가평군(주)DFD인터내셔날 더스테이힐링파크20170524<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 설악면 한서로268번길 157, 1층경기도 가평군 설악면 위곡리 303-3번지47785537.661806127.524331<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>2Y<NA><NA><NA><NA><NA><NA><NA><NA><NA>Y
6가평군설악면종합복지회관20150623<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 설악면 한서로 18-16, 1층경기도 가평군 설악면 신천리 156-5번지47785337.675373127.494965<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>2N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
7가평군숲속의노천탕20160304<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 설악면 유명로 1007-90경기도 가평군 설악면 방일리 715번지 외 19필지47785137.62413127.480101<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>4N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
8가평군동영사우나19881220<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 가화로 54경기도 가평군 가평읍 대곡리 167-2번지47780437.824731127.515817<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
9가평군청평백암천19991204<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 청평면 경춘로 699경기도 가평군 청평면 청평리 650-5번지47781337.731311127.408587<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>0N<NA><NA><NA><NA><NA><NA><NA><NA><NA>Y
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수(개)발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
1925화성시불로장생19991122<NA><NA>폐업 등20060220<NA><NA><NA><NA>경기도 화성시 송산동 158-17번지445370<NA><NA><NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1926화성시신라목욕탕19891111<NA><NA>폐업 등20180813<NA><NA><NA>경기도 화성시 향남읍 3.1만세로 1103경기도 화성시 향남읍 평리 109-3번지44593937.132463126.908063<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>0N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1927화성시태양목욕탕19900115<NA><NA>폐업 등20110318<NA><NA><NA>경기도 화성시 송산면 사강시장길 67경기도 화성시 송산면 사강리 647-1번지44587437.213784126.7372<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1928화성시보성목욕탕19910108<NA><NA>폐업 등20120116<NA><NA><NA><NA>경기도 화성시 봉담읍 수영리 648-3번지44589637.221161126.949285<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>0N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1929화성시장수목욕탕19961126<NA><NA>폐업 등20070313<NA><NA><NA>경기도 화성시 봉담읍 와우로15번길 59경기도 화성시 봉담읍 와우리 79-5번지 6통44589737.21634126.975326<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA>0N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1930화성시워터월드20010604<NA><NA>폐업 등20031030<NA><NA><NA>경기도 화성시 팔탄면 온천로165번길 31-62경기도 화성시 팔탄면 덕우리 15-5번지44591837.137774126.856545<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1931화성시수촌식염목욕탕20011123<NA><NA>폐업 등20180330<NA><NA><NA>경기도 화성시 장안면 황골길 60경기도 화성시 장안면 수촌리 22번지44594437.093877126.866886<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1932화성시남양대중사우나19991203<NA><NA>폐업 등20040413<NA><NA><NA>경기도 화성시 효행로 1366경기도 화성시 반월동 347-42번지44533037.229306127.065419<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1933화성시김해목욕탕19840314<NA><NA>폐업 등20120724<NA><NA><NA>경기도 화성시 향남읍 3.1만세로 1108경기도 화성시 향남읍 평리 110-5번지44593937.132411126.908491<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
1934화성시화성스파빌호텔20011020<NA><NA>폐업 등20170124<NA><NA><NA>경기도 화성시 팔탄면 온천로 29경기도 화성시 팔탄면 덕우리 233-1번지44591837.128289126.859417<NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA>N