Overview

Dataset statistics

Number of variables47
Number of observations2187
Missing cells1812
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory811.7 KiB
Average record size in memory380.1 B

Variable types

Numeric4
Text10
Categorical30
DateTime1
Boolean2

Alerts

opnsvcid has constant value ""Constant
last_load_dttm has constant value ""Constant
clgstdt is highly imbalanced (51.3%)Imbalance
clgenddt is highly imbalanced (51.3%)Imbalance
ropnymd is highly imbalanced (51.3%)Imbalance
maneipcnt is highly imbalanced (72.2%)Imbalance
multusnupsoyn is highly imbalanced (64.8%)Imbalance
wmeipcnt is highly imbalanced (70.6%)Imbalance
cndpermstymd is highly imbalanced (75.2%)Imbalance
cndpermntwhy is highly imbalanced (68.9%)Imbalance
cndpermendymd is highly imbalanced (75.2%)Imbalance
rdnwhladdr has 620 (28.3%) missing valuesMissing
dcbymd has 994 (45.5%) missing valuesMissing
x has 84 (3.8%) missing valuesMissing
y has 84 (3.8%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 08:11:53.404730
Analysis finished2024-04-16 08:11:54.547432
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2187
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1096
Minimum3
Maximum2189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-04-16T17:11:54.608455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile112.3
Q1549.5
median1096
Q31642.5
95-th percentile2079.7
Maximum2189
Range2186
Interquartile range (IQR)1093

Descriptive statistics

Standard deviation631.47684
Coefficient of variation (CV)0.576165
Kurtosis-1.2
Mean1096
Median Absolute Deviation (MAD)547
Skewness0
Sum2396952
Variance398763
MonotonicityNot monotonic
2024-04-16T17:11:54.711227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
< 0.1%
1465 1
 
< 0.1%
1459 1
 
< 0.1%
1460 1
 
< 0.1%
1461 1
 
< 0.1%
1462 1
 
< 0.1%
1463 1
 
< 0.1%
1464 1
 
< 0.1%
1466 1
 
< 0.1%
1508 1
 
< 0.1%
Other values (2177) 2177
99.5%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
2189 1
< 0.1%
2188 1
< 0.1%
2187 1
< 0.1%
2186 1
< 0.1%
2185 1
< 0.1%
2184 1
< 0.1%
2183 1
< 0.1%
2182 1
< 0.1%
2181 1
< 0.1%
2180 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct149
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3516978.3
Minimum3010000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-04-16T17:11:54.809913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3260000
Q13290000
median3330000
Q33380000
95-th percentile4970000
Maximum6520000
Range3510000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation569074.02
Coefficient of variation (CV)0.16180766
Kurtosis8.9339109
Mean3516978.3
Median Absolute Deviation (MAD)40000
Skewness3.0392093
Sum7.6916315 × 109
Variance3.2384524 × 1011
MonotonicityNot monotonic
2024-04-16T17:11:54.929143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3290000 221
 
10.1%
3340000 171
 
7.8%
3300000 164
 
7.5%
3330000 159
 
7.3%
3310000 148
 
6.8%
3370000 131
 
6.0%
3320000 123
 
5.6%
3350000 116
 
5.3%
3380000 112
 
5.1%
3270000 93
 
4.3%
Other values (139) 749
34.2%
ValueCountFrequency (%)
3010000 8
0.4%
3020000 1
 
< 0.1%
3030000 1
 
< 0.1%
3040000 4
0.2%
3050000 1
 
< 0.1%
3070000 1
 
< 0.1%
3100000 4
0.2%
3110000 1
 
< 0.1%
3150000 6
0.3%
3160000 1
 
< 0.1%
ValueCountFrequency (%)
6520000 9
0.4%
6510000 7
 
0.3%
5710000 1
 
< 0.1%
5690000 1
 
< 0.1%
5680000 1
 
< 0.1%
5670000 6
 
0.3%
5600000 1
 
< 0.1%
5540000 1
 
< 0.1%
5530000 19
0.9%
5480000 8
0.4%

mgtno
Text

Distinct2073
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-04-16T17:11:55.093850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters48114
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

Unique2010 ?
Unique (%)91.9%

Sample

1st row3250000-202-2002-00001
2nd row3250000-202-1985-00156
3rd row3250000-202-2001-00013
4th row3250000-202-2007-00001
5th row3250000-202-1988-00159
ValueCountFrequency (%)
5530000-202-2020-00001 4
 
0.2%
5530000-202-2020-00004 4
 
0.2%
5190000-202-2019-00001 3
 
0.1%
4010000-202-2018-00001 3
 
0.1%
5210000-202-2020-00001 3
 
0.1%
5410000-202-2020-00001 3
 
0.1%
5480000-202-2020-00001 3
 
0.1%
3410000-202-2019-00001 3
 
0.1%
4960000-202-2020-00001 3
 
0.1%
3590000-202-2019-00001 3
 
0.1%
Other values (2063) 2155
98.5%
2024-04-16T17:11:55.346466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19315
40.1%
2 7063
 
14.7%
- 6561
 
13.6%
3 4169
 
8.7%
1 3323
 
6.9%
9 2773
 
5.8%
8 1269
 
2.6%
4 1152
 
2.4%
5 918
 
1.9%
7 887
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41553
86.4%
Dash Punctuation 6561
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19315
46.5%
2 7063
 
17.0%
3 4169
 
10.0%
1 3323
 
8.0%
9 2773
 
6.7%
8 1269
 
3.1%
4 1152
 
2.8%
5 918
 
2.2%
7 887
 
2.1%
6 684
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 6561
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19315
40.1%
2 7063
 
14.7%
- 6561
 
13.6%
3 4169
 
8.7%
1 3323
 
6.9%
9 2773
 
5.8%
8 1269
 
2.6%
4 1152
 
2.4%
5 918
 
1.9%
7 887
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19315
40.1%
2 7063
 
14.7%
- 6561
 
13.6%
3 4169
 
8.7%
1 3323
 
6.9%
9 2773
 
5.8%
8 1269
 
2.6%
4 1152
 
2.4%
5 918
 
1.9%
7 887
 
1.8%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
11_44_01_P
2187 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 2187
100.0%

Length

2024-04-16T17:11:55.457630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:55.527089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 2187
100.0%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
I
1744 
U
443 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1744
79.7%
U 443
 
20.3%

Length

2024-04-16T17:11:55.597750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:55.670642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1744
79.7%
u 443
 
20.3%

updatedt
Date

Distinct347
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 00:23:15
2024-04-16T17:11:55.752790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T17:11:55.863481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1548 
목욕장업
639 

Length

Max length4
Median length4
Mean length4
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> 1548
70.8%
목욕장업 639
29.2%

Length

2024-04-16T17:11:55.977394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:56.288744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1548
70.8%
목욕장업 639
29.2%

bplcnm
Text

Distinct1394
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-04-16T17:11:56.489041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length3
Mean length4.7453132
Min length2

Characters and Unicode

Total characters10378
Distinct characters460
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1087 ?
Unique (%)49.7%

Sample

1st row옥샘탕
2nd row금수탕
3rd row백록담
4th row유나목욕탕
5th row녹수탕
ValueCountFrequency (%)
사우나 38
 
1.5%
청수탕 21
 
0.8%
현대탕 21
 
0.8%
목욕탕 21
 
0.8%
찜질방 20
 
0.8%
옥천탕 19
 
0.8%
천수탕 15
 
0.6%
산수탕 15
 
0.6%
장수탕 14
 
0.6%
평화탕 13
 
0.5%
Other values (1491) 2290
92.1%
2024-04-16T17:11:56.818861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 1410
 
13.6%
수 335
 
3.2%
우 305
 
2.9%
301
 
2.9%
사 290
 
2.8%
나 288
 
2.8%
천 262
 
2.5%
스 216
 
2.1%
대 194
 
1.9%
목 159
 
1.5%
Other values (450) 6618
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9806
94.5%
Space Separator 301
 
2.9%
Close Punctuation 74
 
0.7%
Uppercase Letter 72
 
0.7%
Open Punctuation 71
 
0.7%
Decimal Number 37
 
0.4%
Lowercase Letter 9
 
0.1%
Other Punctuation 6
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 1410
 
14.4%
수 335
 
3.4%
우 305
 
3.1%
사 290
 
3.0%
나 288
 
2.9%
천 262
 
2.7%
스 216
 
2.2%
대 194
 
2.0%
목 159
 
1.6%
성 144
 
1.5%
Other values (409) 6203
63.3%
Uppercase Letter
ValueCountFrequency (%)
G 10
13.9%
A 7
 
9.7%
S 6
 
8.3%
L 5
 
6.9%
E 5
 
6.9%
T 5
 
6.9%
M 4
 
5.6%
U 4
 
5.6%
H 3
 
4.2%
O 3
 
4.2%
Other values (12) 20
27.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
33.3%
n 2
22.2%
a 1
 
11.1%
d 1
 
11.1%
u 1
 
11.1%
r 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
2 18
48.6%
4 16
43.2%
6 1
 
2.7%
3 1
 
2.7%
5 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
& 2
33.3%
· 1
16.7%
, 1
16.7%
Space Separator
ValueCountFrequency (%)
301
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9803
94.5%
Common 491
 
4.7%
Latin 81
 
0.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 1410
 
14.4%
수 335
 
3.4%
우 305
 
3.1%
사 290
 
3.0%
나 288
 
2.9%
천 262
 
2.7%
스 216
 
2.2%
대 194
 
2.0%
목 159
 
1.6%
성 144
 
1.5%
Other values (407) 6200
63.2%
Latin
ValueCountFrequency (%)
G 10
 
12.3%
A 7
 
8.6%
S 6
 
7.4%
L 5
 
6.2%
E 5
 
6.2%
T 5
 
6.2%
M 4
 
4.9%
U 4
 
4.9%
H 3
 
3.7%
o 3
 
3.7%
Other values (18) 29
35.8%
Common
ValueCountFrequency (%)
301
61.3%
) 74
 
15.1%
( 71
 
14.5%
2 18
 
3.7%
4 16
 
3.3%
. 2
 
0.4%
- 2
 
0.4%
& 2
 
0.4%
6 1
 
0.2%
3 1
 
0.2%
Other values (3) 3
 
0.6%
Han
ValueCountFrequency (%)
溫 2
66.7%
愛 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9803
94.5%
ASCII 571
 
5.5%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 1410
 
14.4%
수 335
 
3.4%
우 305
 
3.1%
사 290
 
3.0%
나 288
 
2.9%
천 262
 
2.7%
스 216
 
2.2%
대 194
 
2.0%
목 159
 
1.6%
성 144
 
1.5%
Other values (407) 6200
63.2%
ASCII
ValueCountFrequency (%)
301
52.7%
) 74
 
13.0%
( 71
 
12.4%
2 18
 
3.2%
4 16
 
2.8%
G 10
 
1.8%
A 7
 
1.2%
S 6
 
1.1%
L 5
 
0.9%
E 5
 
0.9%
Other values (30) 58
 
10.2%
CJK
ValueCountFrequency (%)
溫 2
66.7%
愛 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

sitepostno
Text

Distinct875
Distinct (%)40.1%
Missing7
Missing (%)0.3%
Memory size17.2 KiB
2024-04-16T17:11:57.119860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters13080
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)17.2%

Sample

1st row600051
2nd row600816
3rd row600091
4th row600061
5th row600062
ValueCountFrequency (%)
604851 15
 
0.7%
612846 12
 
0.6%
612847 12
 
0.6%
607833 10
 
0.5%
608808 10
 
0.5%
608828 10
 
0.5%
614822 10
 
0.5%
607826 9
 
0.4%
607831 9
 
0.4%
613805 9
 
0.4%
Other values (865) 2074
95.1%
2024-04-16T17:11:57.491918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2394
18.3%
8 2248
17.2%
0 2072
15.8%
1 1961
15.0%
2 1041
8.0%
4 943
 
7.2%
3 789
 
6.0%
7 612
 
4.7%
5 515
 
3.9%
9 463
 
3.5%
Other values (5) 42
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13038
99.7%
Other Letter 42
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2394
18.4%
8 2248
17.2%
0 2072
15.9%
1 1961
15.0%
2 1041
8.0%
4 943
 
7.2%
3 789
 
6.1%
7 612
 
4.7%
5 515
 
3.9%
9 463
 
3.6%
Other Letter
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 13038
99.7%
Hangul 42
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2394
18.4%
8 2248
17.2%
0 2072
15.9%
1 1961
15.0%
2 1041
8.0%
4 943
 
7.2%
3 789
 
6.1%
7 612
 
4.7%
5 515
 
3.9%
9 463
 
3.6%
Hangul
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13038
99.7%
Hangul 42
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2394
18.4%
8 2248
17.2%
0 2072
15.9%
1 1961
15.0%
2 1041
8.0%
4 943
 
7.2%
3 789
 
6.1%
7 612
 
4.7%
5 515
 
3.9%
9 463
 
3.6%
Hangul
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

sitewhladdr
Text

Distinct1989
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-04-16T17:11:57.760006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length49
Mean length25.057156
Min length16

Characters and Unicode

Total characters54800
Distinct characters408
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

Unique1856 ?
Unique (%)84.9%

Sample

1st row부산광역시 중구 창선동1가 9-9번지
2nd row부산광역시 중구 중앙동4가 78-2번지
3rd row부산광역시 중구 대청동1가 34-1번지
4th row부산광역시 중구 신창동1가 5-1번지 (5~8층)
5th row부산광역시 중구 신창동2가 21-2번지
ValueCountFrequency (%)
부산광역시 1815
 
18.0%
t통b반 335
 
3.3%
부산진구 221
 
2.2%
사하구 171
 
1.7%
동래구 164
 
1.6%
해운대구 159
 
1.6%
남구 154
 
1.5%
연제구 131
 
1.3%
북구 130
 
1.3%
금정구 116
 
1.2%
Other values (3052) 6687
66.3%
2024-04-16T17:11:58.146598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10039
 
18.3%
동 2380
 
4.3%
1 2313
 
4.2%
산 2231
 
4.1%
부 2187
 
4.0%
시 2122
 
3.9%
지 2066
 
3.8%
구 1985
 
3.6%
광 1976
 
3.6%
- 1963
 
3.6%
Other values (398) 25538
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31162
56.9%
Decimal Number 10615
 
19.4%
Space Separator 10039
 
18.3%
Dash Punctuation 1963
 
3.6%
Uppercase Letter 714
 
1.3%
Other Punctuation 153
 
0.3%
Open Punctuation 66
 
0.1%
Close Punctuation 66
 
0.1%
Math Symbol 11
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2380
 
7.6%
산 2231
 
7.2%
부 2187
 
7.0%
시 2122
 
6.8%
지 2066
 
6.6%
구 1985
 
6.4%
광 1976
 
6.3%
번 1930
 
6.2%
역 1874
 
6.0%
남 398
 
1.3%
Other values (360) 12013
38.6%
Uppercase Letter
ValueCountFrequency (%)
B 349
48.9%
T 336
47.1%
I 7
 
1.0%
S 4
 
0.6%
V 3
 
0.4%
A 3
 
0.4%
Y 3
 
0.4%
G 2
 
0.3%
C 2
 
0.3%
L 2
 
0.3%
Other values (3) 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 2313
21.8%
2 1400
13.2%
3 1168
11.0%
4 1066
10.0%
5 979
9.2%
6 817
 
7.7%
0 773
 
7.3%
7 754
 
7.1%
8 706
 
6.7%
9 639
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
30.0%
p 3
30.0%
o 1
 
10.0%
w 1
 
10.0%
r 1
 
10.0%
e 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 149
97.4%
. 3
 
2.0%
@ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
10039
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1963
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31162
56.9%
Common 22913
41.8%
Latin 725
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2380
 
7.6%
산 2231
 
7.2%
부 2187
 
7.0%
시 2122
 
6.8%
지 2066
 
6.6%
구 1985
 
6.4%
광 1976
 
6.3%
번 1930
 
6.2%
역 1874
 
6.0%
남 398
 
1.3%
Other values (360) 12013
38.6%
Latin
ValueCountFrequency (%)
B 349
48.1%
T 336
46.3%
I 7
 
1.0%
S 4
 
0.6%
V 3
 
0.4%
a 3
 
0.4%
p 3
 
0.4%
A 3
 
0.4%
Y 3
 
0.4%
G 2
 
0.3%
Other values (10) 12
 
1.7%
Common
ValueCountFrequency (%)
10039
43.8%
1 2313
 
10.1%
- 1963
 
8.6%
2 1400
 
6.1%
3 1168
 
5.1%
4 1066
 
4.7%
5 979
 
4.3%
6 817
 
3.6%
0 773
 
3.4%
7 754
 
3.3%
Other values (8) 1641
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31162
56.9%
ASCII 23637
43.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10039
42.5%
1 2313
 
9.8%
- 1963
 
8.3%
2 1400
 
5.9%
3 1168
 
4.9%
4 1066
 
4.5%
5 979
 
4.1%
6 817
 
3.5%
0 773
 
3.3%
7 754
 
3.2%
Other values (27) 2365
 
10.0%
Hangul
ValueCountFrequency (%)
동 2380
 
7.6%
산 2231
 
7.2%
부 2187
 
7.0%
시 2122
 
6.8%
지 2066
 
6.6%
구 1985
 
6.4%
광 1976
 
6.3%
번 1930
 
6.2%
역 1874
 
6.0%
남 398
 
1.3%
Other values (360) 12013
38.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

rdnpostno
Text

Distinct1124
Distinct (%)51.4%
Missing1
Missing (%)< 0.1%
Memory size17.2 KiB
2024-04-16T17:11:58.398243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0018298
Min length5

Characters and Unicode

Total characters10934
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique865 ?
Unique (%)39.6%

Sample

1st row48947
2nd row48947
3rd row48947
4th row48948
5th row48947
ValueCountFrequency (%)
48947 682
31.2%
47709 8
 
0.4%
48099 8
 
0.4%
18606 8
 
0.4%
46327 5
 
0.2%
47248 5
 
0.2%
58709 4
 
0.2%
48531 4
 
0.2%
48052 4
 
0.2%
48053 4
 
0.2%
Other values (1114) 1454
66.5%
2024-04-16T17:11:58.760070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2996
27.4%
7 1458
13.3%
8 1450
13.3%
9 1249
11.4%
6 669
 
6.1%
0 649
 
5.9%
5 648
 
5.9%
2 631
 
5.8%
1 611
 
5.6%
3 559
 
5.1%
Other values (7) 14
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10920
99.9%
Other Letter 14
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2996
27.4%
7 1458
13.4%
8 1450
13.3%
9 1249
11.4%
6 669
 
6.1%
0 649
 
5.9%
5 648
 
5.9%
2 631
 
5.8%
1 611
 
5.6%
3 559
 
5.1%
Other Letter
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 10920
99.9%
Hangul 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2996
27.4%
7 1458
13.4%
8 1450
13.3%
9 1249
11.4%
6 669
 
6.1%
0 649
 
5.9%
5 648
 
5.9%
2 631
 
5.8%
1 611
 
5.6%
3 559
 
5.1%
Hangul
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10920
99.9%
Hangul 14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2996
27.4%
7 1458
13.4%
8 1450
13.3%
9 1249
11.4%
6 669
 
6.1%
0 649
 
5.9%
5 648
 
5.9%
2 631
 
5.8%
1 611
 
5.6%
3 559
 
5.1%
Hangul
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

rdnwhladdr
Text

MISSING 

Distinct1435
Distinct (%)91.6%
Missing620
Missing (%)28.3%
Memory size17.2 KiB
2024-04-16T17:11:59.040858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length28.502234
Min length5

Characters and Unicode

Total characters44663
Distinct characters457
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1359 ?
Unique (%)86.7%

Sample

1st row부산광역시 중구 광복로55번길 14-2 (창선동1가)
2nd row부산광역시 중구 광복중앙로 25 (신창동1가)
3rd row부산광역시 중구 광복로43번길 12 (신창동2가)
4th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
5th row부산광역시 중구 비프광장로 20, 10층 (남포동6가)
ValueCountFrequency (%)
부산광역시 1197
 
13.8%
부산진구 153
 
1.8%
남구 110
 
1.3%
해운대구 103
 
1.2%
사하구 100
 
1.2%
동래구 99
 
1.1%
연제구 85
 
1.0%
북구 82
 
0.9%
금정구 77
 
0.9%
경기도 77
 
0.9%
Other values (2651) 6581
76.0%
2024-04-16T17:11:59.444329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7102
 
15.9%
동 1834
 
4.1%
1 1624
 
3.6%
시 1548
 
3.5%
산 1527
 
3.4%
부 1491
 
3.3%
로 1462
 
3.3%
) 1401
 
3.1%
( 1401
 
3.1%
구 1390
 
3.1%
Other values (447) 23883
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26702
59.8%
Space Separator 7102
 
15.9%
Decimal Number 6960
 
15.6%
Close Punctuation 1404
 
3.1%
Open Punctuation 1404
 
3.1%
Other Punctuation 713
 
1.6%
Dash Punctuation 296
 
0.7%
Uppercase Letter 45
 
0.1%
Math Symbol 32
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1834
 
6.9%
시 1548
 
5.8%
산 1527
 
5.7%
부 1491
 
5.6%
로 1462
 
5.5%
구 1390
 
5.2%
광 1364
 
5.1%
역 1260
 
4.7%
길 879
 
3.3%
번 733
 
2.7%
Other values (408) 13214
49.5%
Uppercase Letter
ValueCountFrequency (%)
B 26
57.8%
A 5
 
11.1%
I 4
 
8.9%
G 2
 
4.4%
C 2
 
4.4%
M 1
 
2.2%
L 1
 
2.2%
T 1
 
2.2%
S 1
 
2.2%
K 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 1624
23.3%
2 1054
15.1%
3 851
12.2%
0 579
 
8.3%
5 573
 
8.2%
4 536
 
7.7%
6 510
 
7.3%
7 468
 
6.7%
9 394
 
5.7%
8 371
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 702
98.5%
. 6
 
0.8%
* 3
 
0.4%
& 1
 
0.1%
@ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
w 1
25.0%
o 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 1401
99.8%
] 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1401
99.8%
[ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 31
96.9%
～ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
7102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26702
59.8%
Common 17911
40.1%
Latin 50
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1834
 
6.9%
시 1548
 
5.8%
산 1527
 
5.7%
부 1491
 
5.6%
로 1462
 
5.5%
구 1390
 
5.2%
광 1364
 
5.1%
역 1260
 
4.7%
길 879
 
3.3%
번 733
 
2.7%
Other values (408) 13214
49.5%
Common
ValueCountFrequency (%)
7102
39.7%
1 1624
 
9.1%
) 1401
 
7.8%
( 1401
 
7.8%
2 1054
 
5.9%
3 851
 
4.8%
, 702
 
3.9%
0 579
 
3.2%
5 573
 
3.2%
4 536
 
3.0%
Other values (13) 2088
 
11.7%
Latin
ValueCountFrequency (%)
B 26
52.0%
A 5
 
10.0%
I 4
 
8.0%
G 2
 
4.0%
C 2
 
4.0%
M 1
 
2.0%
L 1
 
2.0%
r 1
 
2.0%
e 1
 
2.0%
w 1
 
2.0%
Other values (6) 6
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26702
59.8%
ASCII 17959
40.2%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7102
39.5%
1 1624
 
9.0%
) 1401
 
7.8%
( 1401
 
7.8%
2 1054
 
5.9%
3 851
 
4.7%
, 702
 
3.9%
0 579
 
3.2%
5 573
 
3.2%
4 536
 
3.0%
Other values (27) 2136
 
11.9%
Hangul
ValueCountFrequency (%)
동 1834
 
6.9%
시 1548
 
5.8%
산 1527
 
5.7%
부 1491
 
5.6%
로 1462
 
5.5%
구 1390
 
5.2%
광 1364
 
5.1%
역 1260
 
4.7%
길 879
 
3.3%
번 733
 
2.7%
Other values (408) 13214
49.5%
None
ValueCountFrequency (%)
～ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

apvpermymd
Real number (ℝ)

Distinct1707
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19958195
Minimum19540131
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-04-16T17:11:59.558940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19701009
Q119840913
median19941219
Q320060756
95-th percentile20200403
Maximum20201231
Range661100
Interquartile range (IQR)219843

Descriptive statistics

Standard deviation154694.2
Coefficient of variation (CV)0.0077509113
Kurtosis-0.86200437
Mean19958195
Median Absolute Deviation (MAD)108998
Skewness0.059152785
Sum4.3648572 × 1010
Variance2.3930294 × 1010
MonotonicityNot monotonic
2024-04-16T17:11:59.671097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.7%
20190201 15
 
0.7%
20201231 10
 
0.5%
20191101 9
 
0.4%
20001130 9
 
0.4%
19921202 8
 
0.4%
20200207 7
 
0.3%
20191206 6
 
0.3%
20200221 6
 
0.3%
19971227 6
 
0.3%
Other values (1697) 2096
95.8%
ValueCountFrequency (%)
19540131 1
 
< 0.1%
19601210 3
 
0.1%
19630108 1
 
< 0.1%
19630109 3
 
0.1%
19630110 15
0.7%
19630610 4
 
0.2%
19631001 1
 
< 0.1%
19640211 1
 
< 0.1%
19640915 1
 
< 0.1%
19641015 1
 
< 0.1%
ValueCountFrequency (%)
20201231 10
0.5%
20201228 2
 
0.1%
20201223 2
 
0.1%
20201221 1
 
< 0.1%
20201217 2
 
0.1%
20201215 2
 
0.1%
20201211 2
 
0.1%
20201203 1
 
< 0.1%
20201202 1
 
< 0.1%
20201120 2
 
0.1%

dcbymd
Text

MISSING 

Distinct816
Distinct (%)68.4%
Missing994
Missing (%)45.5%
Memory size17.2 KiB
2024-04-16T17:11:59.890847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.2690696
Min length4

Characters and Unicode

Total characters8672
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique701 ?
Unique (%)58.8%

Sample

1st row20070612
2nd row20120221
3rd row20140401
4th row20131227
5th row20030703
ValueCountFrequency (%)
폐업일자 218
 
18.3%
20050121 12
 
1.0%
20051017 7
 
0.6%
20001130 7
 
0.6%
20030401 5
 
0.4%
20170310 5
 
0.4%
20120621 4
 
0.3%
20141030 4
 
0.3%
20030122 4
 
0.3%
20131002 3
 
0.3%
Other values (806) 924
77.5%
2024-04-16T17:12:00.235680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2640
30.4%
2 1610
18.6%
1 1413
16.3%
9 362
 
4.2%
3 349
 
4.0%
7 305
 
3.5%
5 293
 
3.4%
6 283
 
3.3%
8 277
 
3.2%
4 268
 
3.1%
Other values (4) 872
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7800
89.9%
Other Letter 872
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Other Letter
ValueCountFrequency (%)
폐 218
25.0%
업 218
25.0%
일 218
25.0%
자 218
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7800
89.9%
Hangul 872
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
폐 218
25.0%
업 218
25.0%
일 218
25.0%
자 218
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7800
89.9%
Hangul 872
 
10.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
폐 218
25.0%
업 218
25.0%
일 218
25.0%
자 218
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1956 
휴업시작일자
231 

Length

Max length6
Median length4
Mean length4.2112483
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> 1956
89.4%
휴업시작일자 231
 
10.6%

Length

2024-04-16T17:12:00.356005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:00.441331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1956
89.4%
휴업시작일자 231
 
10.6%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1956 
휴업종료일자
231 

Length

Max length6
Median length4
Mean length4.2112483
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> 1956
89.4%
휴업종료일자 231
 
10.6%

Length

2024-04-16T17:12:00.528984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:00.608765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1956
89.4%
휴업종료일자 231
 
10.6%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1956 
재개업일자
231 

Length

Max length5
Median length4
Mean length4.1056241
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> 1956
89.4%
재개업일자 231
 
10.6%

Length

2024-04-16T17:12:00.688492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:00.765662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1956
89.4%
재개업일자 231
 
10.6%

trdstatenm
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
02
925 
01
623 
영업/정상
583 
폐업
 
50
영업상태
 
4

Length

Max length5
Median length2
Mean length2.8052126
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01
2nd row02
3rd row02
4th row02
5th row01

Common Values

ValueCountFrequency (%)
02 925
42.3%
01 623
28.5%
영업/정상 583
26.7%
폐업 50
 
2.3%
영업상태 4
 
0.2%
<NA> 2
 
0.1%

Length

2024-04-16T17:12:00.849284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:00.936994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 925
42.3%
01 623
28.5%
영업/정상 583
26.7%
폐업 50
 
2.3%
영업상태 4
 
0.2%
na 2
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
영업
1212 
폐업
975 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row폐업
3rd row폐업
4th row폐업
5th row영업

Common Values

ValueCountFrequency (%)
영업 1212
55.4%
폐업 975
44.6%

Length

2024-04-16T17:12:01.040965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:01.115083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1212
55.4%
폐업 975
44.6%

x
Text

MISSING 

Distinct1919
Distinct (%)91.3%
Missing84
Missing (%)3.8%
Memory size17.2 KiB
2024-04-16T17:12:01.295900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.950547
Min length7

Characters and Unicode

Total characters41956
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1805 ?
Unique (%)85.8%

Sample

1st row385089.38491100000
2nd row385793.29931
3rd row385208.257554
4th row385157.86566400000
5th row385086.62014400000
ValueCountFrequency (%)
좌표정보(x 8
 
0.4%
192190.585454696 8
 
0.4%
210858.16481015 4
 
0.2%
387810.283167969 4
 
0.2%
389394.976154 4
 
0.2%
390974.056399381 4
 
0.2%
175185.261058397 4
 
0.2%
389727.58350700000 4
 
0.2%
144766.399755 4
 
0.2%
370674.351397752 3
 
0.1%
Other values (1909) 2056
97.8%
2024-04-16T17:12:01.602396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8623
20.6%
0 6869
16.4%
3 3961
9.4%
8 3330
 
7.9%
9 2955
 
7.0%
1 2433
 
5.8%
7 2409
 
5.7%
2 2394
 
5.7%
4 2310
 
5.5%
6 2267
 
5.4%
Other values (9) 4405
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31187
74.3%
Space Separator 8623
 
20.6%
Other Punctuation 2090
 
5.0%
Other Letter 32
 
0.1%
Close Punctuation 8
 
< 0.1%
Uppercase Letter 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6869
22.0%
3 3961
12.7%
8 3330
10.7%
9 2955
9.5%
1 2433
 
7.8%
7 2409
 
7.7%
2 2394
 
7.7%
4 2310
 
7.4%
6 2267
 
7.3%
5 2259
 
7.2%
Other Letter
ValueCountFrequency (%)
표 8
25.0%
보 8
25.0%
정 8
25.0%
좌 8
25.0%
Space Separator
ValueCountFrequency (%)
8623
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2090
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41916
99.9%
Hangul 32
 
0.1%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8623
20.6%
0 6869
16.4%
3 3961
9.4%
8 3330
 
7.9%
9 2955
 
7.0%
1 2433
 
5.8%
7 2409
 
5.7%
2 2394
 
5.7%
4 2310
 
5.5%
6 2267
 
5.4%
Other values (4) 4365
10.4%
Hangul
ValueCountFrequency (%)
표 8
25.0%
보 8
25.0%
정 8
25.0%
좌 8
25.0%
Latin
ValueCountFrequency (%)
X 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41924
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8623
20.6%
0 6869
16.4%
3 3961
9.4%
8 3330
 
7.9%
9 2955
 
7.0%
1 2433
 
5.8%
7 2409
 
5.7%
2 2394
 
5.7%
4 2310
 
5.5%
6 2267
 
5.4%
Other values (5) 4373
10.4%
Hangul
ValueCountFrequency (%)
표 8
25.0%
보 8
25.0%
정 8
25.0%
좌 8
25.0%

y
Text

MISSING 

Distinct1919
Distinct (%)91.3%
Missing84
Missing (%)3.8%
Memory size17.2 KiB
2024-04-16T17:12:01.802169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.950547
Min length7

Characters and Unicode

Total characters41956
Distinct characters21
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

Unique1805 ?
Unique (%)85.8%

Sample

1st row180062.56761800000
2nd row180910.386636
3rd row180108.034984
4th row180248.21457300000
5th row180119.33406400000
ValueCountFrequency (%)
좌표정보(y 8
 
0.4%
401648.714565483 8
 
0.4%
411413.605240051 4
 
0.2%
179178.742589729 4
 
0.2%
193519.152183 4
 
0.2%
182797.894969615 4
 
0.2%
427812.896240081 4
 
0.2%
191654.34294400000 4
 
0.2%
144689.635335 4
 
0.2%
184448.198703368 3
 
0.1%
Other values (1909) 2056
97.8%
2024-04-16T17:12:02.129791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8589
20.5%
0 6819
16.3%
1 4063
9.7%
8 3275
 
7.8%
9 2854
 
6.8%
7 2691
 
6.4%
4 2453
 
5.8%
6 2293
 
5.5%
3 2276
 
5.4%
2 2274
 
5.4%
Other values (11) 4369
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31203
74.4%
Space Separator 8589
 
20.5%
Other Punctuation 2090
 
5.0%
Other Letter 32
 
0.1%
Dash Punctuation 15
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Uppercase Letter 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6819
21.9%
1 4063
13.0%
8 3275
10.5%
9 2854
9.1%
7 2691
 
8.6%
4 2453
 
7.9%
6 2293
 
7.3%
3 2276
 
7.3%
2 2274
 
7.3%
5 2205
 
7.1%
Other Letter
ValueCountFrequency (%)
좌 8
25.0%
표 8
25.0%
보 8
25.0%
정 8
25.0%
Close Punctuation
ValueCountFrequency (%)
) 8
72.7%
] 3
 
27.3%
Space Separator
ValueCountFrequency (%)
8589
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2090
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41916
99.9%
Hangul 32
 
0.1%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8589
20.5%
0 6819
16.3%
1 4063
9.7%
8 3275
 
7.8%
9 2854
 
6.8%
7 2691
 
6.4%
4 2453
 
5.9%
6 2293
 
5.5%
3 2276
 
5.4%
2 2274
 
5.4%
Other values (6) 4329
10.3%
Hangul
ValueCountFrequency (%)
좌 8
25.0%
표 8
25.0%
보 8
25.0%
정 8
25.0%
Latin
ValueCountFrequency (%)
Y 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41924
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8589
20.5%
0 6819
16.3%
1 4063
9.7%
8 3275
 
7.8%
9 2854
 
6.8%
7 2691
 
6.4%
4 2453
 
5.9%
6 2293
 
5.5%
3 2276
 
5.4%
2 2274
 
5.4%
Other values (7) 4337
10.3%
Hangul
ValueCountFrequency (%)
좌 8
25.0%
표 8
25.0%
보 8
25.0%
정 8
25.0%

lastmodts
Real number (ℝ)

Distinct1749
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0126341 × 1013
Minimum1.999021 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-04-16T17:12:02.244957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020829 × 1013
Q12.0060208 × 1013
median2.0140326 × 1013
Q32.0190328 × 1013
95-th percentile2.0201016 × 1013
Maximum2.0201231 × 1013
Range2.1102117 × 1011
Interquartile range (IQR)1.3011963 × 1011

Descriptive statistics

Standard deviation6.5473516 × 1010
Coefficient of variation (CV)0.0032531257
Kurtosis-1.2212188
Mean2.0126341 × 1013
Median Absolute Deviation (MAD)5.078595 × 1010
Skewness-0.45995243
Sum4.4016307 × 1016
Variance4.2867812 × 1021
MonotonicityNot monotonic
2024-04-16T17:12:02.346823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030409000000 29
 
1.3%
20020418000000 27
 
1.2%
20040318000000 16
 
0.7%
20050415000000 14
 
0.6%
20030303000000 12
 
0.5%
20031217000000 12
 
0.5%
20040324000000 11
 
0.5%
20020422000000 10
 
0.5%
20041208000000 9
 
0.4%
20030722000000 8
 
0.4%
Other values (1739) 2039
93.2%
ValueCountFrequency (%)
19990210000000 2
 
0.1%
19990212000000 1
 
< 0.1%
19990302000000 7
0.3%
19990310000000 6
0.3%
19990315000000 1
 
< 0.1%
19990325000000 2
 
0.1%
19990420000000 2
 
0.1%
19990421000000 7
0.3%
19990422000000 1
 
< 0.1%
19990427000000 1
 
< 0.1%
ValueCountFrequency (%)
20201231165523 1
< 0.1%
20201231165441 1
< 0.1%
20201231165221 1
< 0.1%
20201231165147 1
< 0.1%
20201231165103 1
< 0.1%
20201231164842 1
< 0.1%
20201231164803 1
< 0.1%
20201231164639 1
< 0.1%
20201231164545 1
< 0.1%
20201231164349 1
< 0.1%

uptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
공동탕업
1693 
목욕장업 기타
214 
공동탕업+찜질시설서비스영업
 
159
찜질시설서비스영업
 
76
한증막업
 
45

Length

Max length14
Median length4
Mean length5.1943301
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1693
77.4%
목욕장업 기타 214
 
9.8%
공동탕업+찜질시설서비스영업 159
 
7.3%
찜질시설서비스영업 76
 
3.5%
한증막업 45
 
2.1%

Length

2024-04-16T17:12:02.445911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:02.536231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1693
70.5%
목욕장업 214
 
8.9%
기타 214
 
8.9%
공동탕업+찜질시설서비스영업 159
 
6.6%
찜질시설서비스영업 76
 
3.2%
한증막업 45
 
1.9%

sitetel
Text

Distinct94
Distinct (%)4.3%
Missing20
Missing (%)0.9%
Memory size17.2 KiB
2024-04-16T17:12:02.686469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.928473
Min length4

Characters and Unicode

Total characters25849
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

Unique87 ?
Unique (%)4.0%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 2054
88.5%
051 44
 
1.9%
전화번호 14
 
0.6%
061 12
 
0.5%
339 10
 
0.4%
055 9
 
0.4%
031 8
 
0.3%
052 4
 
0.2%
064 4
 
0.2%
063 3
 
0.1%
Other values (140) 160
 
6.9%
2024-04-16T17:12:02.921736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6282
24.3%
3 4228
16.4%
2 4180
16.2%
- 4108
15.9%
0 2243
 
8.7%
5 2184
 
8.4%
4 2104
 
8.1%
160
 
0.6%
6 98
 
0.4%
7 80
 
0.3%
Other values (6) 182
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21525
83.3%
Dash Punctuation 4108
 
15.9%
Space Separator 160
 
0.6%
Other Letter 56
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6282
29.2%
3 4228
19.6%
2 4180
19.4%
0 2243
 
10.4%
5 2184
 
10.1%
4 2104
 
9.8%
6 98
 
0.5%
7 80
 
0.4%
9 64
 
0.3%
8 62
 
0.3%
Other Letter
ValueCountFrequency (%)
전 14
25.0%
화 14
25.0%
번 14
25.0%
호 14
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 4108
100.0%
Space Separator
ValueCountFrequency (%)
160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25793
99.8%
Hangul 56
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6282
24.4%
3 4228
16.4%
2 4180
16.2%
- 4108
15.9%
0 2243
 
8.7%
5 2184
 
8.5%
4 2104
 
8.2%
160
 
0.6%
6 98
 
0.4%
7 80
 
0.3%
Other values (2) 126
 
0.5%
Hangul
ValueCountFrequency (%)
전 14
25.0%
화 14
25.0%
번 14
25.0%
호 14
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25793
99.8%
Hangul 56
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6282
24.4%
3 4228
16.4%
2 4180
16.2%
- 4108
15.9%
0 2243
 
8.7%
5 2184
 
8.5%
4 2104
 
8.2%
160
 
0.6%
6 98
 
0.4%
7 80
 
0.3%
Other values (2) 126
 
0.5%
Hangul
ValueCountFrequency (%)
전 14
25.0%
화 14
25.0%
번 14
25.0%
호 14
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1509 
자가
340 
임대
174 
건물소유구분명
164 

Length

Max length7
Median length4
Mean length3.7549154
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1509
69.0%
자가 340
 
15.5%
임대 174
 
8.0%
건물소유구분명 164
 
7.5%

Length

2024-04-16T17:12:03.022044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:03.104172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1509
69.0%
자가 340
 
15.5%
임대 174
 
8.0%
건물소유구분명 164
 
7.5%

bdngjisgflrcnt
Categorical

Distinct37
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
521 
<NA>
466 
3
329 
4
223 
2
180 
Other values (32)
468 

Length

Max length6
Median length1
Mean length1.6959305
Min length1

Unique

Unique10 ?
Unique (%)0.5%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row9
5th row4

Common Values

ValueCountFrequency (%)
0 521
23.8%
<NA> 466
21.3%
3 329
15.0%
4 223
10.2%
2 180
 
8.2%
5 145
 
6.6%
6 58
 
2.7%
1 55
 
2.5%
7 51
 
2.3%
8 35
 
1.6%
Other values (27) 124
 
5.7%

Length

2024-04-16T17:12:03.196254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 521
23.8%
na 466
21.3%
3 329
15.0%
4 223
10.2%
2 180
 
8.2%
5 145
 
6.6%
6 58
 
2.7%
1 55
 
2.5%
7 51
 
2.3%
8 35
 
1.6%
Other values (27) 124
 
5.7%

bdngunderflrcnt
Categorical

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
798 
<NA>
707 
1
508 
2
94 
3
 
32
Other values (5)
 
48

Length

Max length6
Median length1
Mean length1.9858253
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row3
5th row1

Common Values

ValueCountFrequency (%)
0 798
36.5%
<NA> 707
32.3%
1 508
23.2%
2 94
 
4.3%
3 32
 
1.5%
4 21
 
1.0%
5 10
 
0.5%
6 9
 
0.4%
건물지하층수 7
 
0.3%
7 1
 
< 0.1%

Length

2024-04-16T17:12:03.289083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:03.387952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 798
36.5%
na 707
32.3%
1 508
23.2%
2 94
 
4.3%
3 32
 
1.5%
4 21
 
1.0%
5 10
 
0.5%
6 9
 
0.4%
건물지하층수 7
 
0.3%
7 1
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1771 
0
349 
1
 
32
남성종사자수
 
21
2
 
5
Other values (4)
 
9

Length

Max length6
Median length4
Mean length3.4773663
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> 1771
81.0%
0 349
 
16.0%
1 32
 
1.5%
남성종사자수 21
 
1.0%
2 5
 
0.2%
5 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
< 0.1%

Length

2024-04-16T17:12:03.518463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:03.612063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1771
81.0%
0 349
 
16.0%
1 32
 
1.5%
남성종사자수 21
 
1.0%
2 5
 
0.2%
5 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
< 0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
False
2042 
True
 
145
ValueCountFrequency (%)
False 2042
93.4%
True 145
 
6.6%
2024-04-16T17:12:03.699314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size4.4 KiB
False
1572 
True
613 
(Missing)
 
2
ValueCountFrequency (%)
False 1572
71.9%
True 613
 
28.0%
(Missing) 2
 
0.1%
2024-04-16T17:12:03.781529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
840 
2
437 
3
233 
0
222 
1
144 
Other values (9)
311 

Length

Max length6
Median length1
Mean length2.3589392
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row8
5th row4

Common Values

ValueCountFrequency (%)
<NA> 840
38.4%
2 437
20.0%
3 233
 
10.7%
0 222
 
10.2%
1 144
 
6.6%
4 93
 
4.3%
사용끝지상층 88
 
4.0%
5 60
 
2.7%
6 26
 
1.2%
7 14
 
0.6%
Other values (4) 30
 
1.4%

Length

2024-04-16T17:12:03.866433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 840
38.4%
2 437
20.0%
3 233
 
10.7%
0 222
 
10.2%
1 144
 
6.6%
4 93
 
4.3%
사용끝지상층 88
 
4.0%
5 60
 
2.7%
6 26
 
1.2%
7 14
 
0.6%
Other values (4) 30
 
1.4%

useunderendflr
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1311 
0
589 
사용끝지하층
148 
1
 
103
2
 
31
Other values (2)
 
5

Length

Max length6
Median length4
Mean length3.136717
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1311
59.9%
0 589
26.9%
사용끝지하층 148
 
6.8%
1 103
 
4.7%
2 31
 
1.4%
3 4
 
0.2%
4 1
 
< 0.1%

Length

2024-04-16T17:12:03.956839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:04.043482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1311
59.9%
0 589
26.9%
사용끝지하층 148
 
6.8%
1 103
 
4.7%
2 31
 
1.4%
3 4
 
0.2%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
688 
1
475 
0
383 
2
358 
3
91 
Other values (9)
192 

Length

Max length7
Median length1
Mean length2.1399177
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row5
5th row2

Common Values

ValueCountFrequency (%)
<NA> 688
31.5%
1 475
21.7%
0 383
17.5%
2 358
16.4%
3 91
 
4.2%
사용시작지상층 70
 
3.2%
4 53
 
2.4%
5 23
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 21
 
1.0%

Length

2024-04-16T17:12:04.149391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 688
31.5%
1 475
21.7%
0 383
17.5%
2 358
16.4%
3 91
 
4.2%
사용시작지상층 70
 
3.2%
4 53
 
2.4%
5 23
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 21
 
1.0%

useunderstflr
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1045 
0
850 
사용시작지하층
141 
1
130 
2
 
17

Length

Max length7
Median length4
Mean length2.8203018
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1045
47.8%
0 850
38.9%
사용시작지하층 141
 
6.4%
1 130
 
5.9%
2 17
 
0.8%
3 4
 
0.2%

Length

2024-04-16T17:12:04.253768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:04.348160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1045
47.8%
0 850
38.9%
사용시작지하층 141
 
6.4%
1 130
 
5.9%
2 17
 
0.8%
3 4
 
0.2%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1248 
0
933 
세탁기수
 
6

Length

Max length4
Median length4
Mean length2.7201646
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1248
57.1%
0 933
42.7%
세탁기수 6
 
0.3%

Length

2024-04-16T17:12:04.672659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:04.751856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1248
57.1%
0 933
42.7%
세탁기수 6
 
0.3%

yangsilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
1202 
<NA>
979 
양실수
 
6

Length

Max length4
Median length1
Mean length2.3484225
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1202
55.0%
<NA> 979
44.8%
양실수 6
 
0.3%

Length

2024-04-16T17:12:04.837503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:04.926588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1202
55.0%
na 979
44.8%
양실수 6
 
0.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1771 
0
351 
1
 
24
여성종사자수
 
21
2
 
10
Other values (3)
 
10

Length

Max length6
Median length4
Mean length3.4773663
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> 1771
81.0%
0 351
 
16.0%
1 24
 
1.1%
여성종사자수 21
 
1.0%
2 10
 
0.5%
5 6
 
0.3%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-04-16T17:12:05.016830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:05.107099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1771
81.0%
0 351
 
16.0%
1 24
 
1.1%
여성종사자수 21
 
1.0%
2 10
 
0.5%
5 6
 
0.3%
3 3
 
0.1%
4 1
 
< 0.1%

yoksilcnt
Categorical

Distinct21
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
687 
<NA>
643 
2
609 
1
70 
4
 
48
Other values (16)
130 

Length

Max length4
Median length1
Mean length1.8952904
Min length1

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 687
31.4%
<NA> 643
29.4%
2 609
27.8%
1 70
 
3.2%
4 48
 
2.2%
6 45
 
2.1%
8 30
 
1.4%
7 9
 
0.4%
3 8
 
0.4%
10 7
 
0.3%
Other values (11) 31
 
1.4%

Length

2024-04-16T17:12:05.221226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 687
31.4%
na 643
29.4%
2 609
27.8%
1 70
 
3.2%
4 48
 
2.2%
6 45
 
2.1%
8 30
 
1.4%
7 9
 
0.4%
3 8
 
0.4%
9 7
 
0.3%
Other values (11) 31
 
1.4%

sntuptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
공동탕업
1693 
목욕장업 기타
214 
공동탕업+찜질시설서비스영업
 
159
찜질시설서비스영업
 
76
한증막업
 
45

Length

Max length14
Median length4
Mean length5.1943301
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1693
77.4%
목욕장업 기타 214
 
9.8%
공동탕업+찜질시설서비스영업 159
 
7.3%
찜질시설서비스영업 76
 
3.5%
한증막업 45
 
2.1%

Length

2024-04-16T17:12:05.344960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:05.456989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1693
70.5%
목욕장업 214
 
8.9%
기타 214
 
8.9%
공동탕업+찜질시설서비스영업 159
 
6.6%
찜질시설서비스영업 76
 
3.2%
한증막업 45
 
1.9%

chaircnt
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
1201 
<NA>
979 
의자수
 
6
2
 
1

Length

Max length4
Median length1
Mean length2.3484225
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1201
54.9%
<NA> 979
44.8%
의자수 6
 
0.3%
2 1
 
< 0.1%

Length

2024-04-16T17:12:05.579207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:05.690059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1201
54.9%
na 979
44.8%
의자수 6
 
0.3%
2 1
 
< 0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1955 
조건부허가시작일자
230 
20190501
 
1
20190228
 
1

Length

Max length9
Median length4
Mean length4.5294925
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1955
89.4%
조건부허가시작일자 230
 
10.5%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

Length

2024-04-16T17:12:05.779298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:05.858566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1955
89.4%
조건부허가시작일자 230
 
10.5%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1955 
조건부허가신고사유
231 
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
 
1

Length

Max length36
Median length4
Mean length4.5427526
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> 1955
89.4%
조건부허가신고사유 231
 
10.6%
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고 1
 
< 0.1%

Length

2024-04-16T17:12:05.945551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.025825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1955
89.3%
조건부허가신고사유 231
 
10.6%
건축과-16824(2019.4.15),가설건축물 1
 
< 0.1%
존치기간연장 1
 
< 0.1%
신고 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1955 
조건부허가종료일자
230 
20210421
 
1
20220831
 
1

Length

Max length9
Median length4
Mean length4.5294925
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1955
89.4%
조건부허가종료일자 230
 
10.5%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

Length

2024-04-16T17:12:06.114033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.211591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1955
89.4%
조건부허가종료일자 230
 
10.5%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

abedcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1275 
0
905 
침대수
 
7

Length

Max length4
Median length4
Mean length2.7553727
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1275
58.3%
0 905
41.4%
침대수 7
 
0.3%

Length

2024-04-16T17:12:06.306108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.387832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1275
58.3%
0 905
41.4%
침대수 7
 
0.3%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
0
1202 
<NA>
979 
한실수
 
6

Length

Max length4
Median length1
Mean length2.3484225
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1202
55.0%
<NA> 979
44.8%
한실수 6
 
0.3%

Length

2024-04-16T17:12:06.473845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.569647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1202
55.0%
na 979
44.8%
한실수 6
 
0.3%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
1274 
0
906 
회수건조수
 
7

Length

Max length5
Median length4
Mean length2.7604024
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1274
58.3%
0 906
41.4%
회수건조수 7
 
0.3%

Length

2024-04-16T17:12:06.661417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.760997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1274
58.3%
0 906
41.4%
회수건조수 7
 
0.3%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2021-01-04 19:59:27
2187 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-04 19:59:27
2nd row2021-01-04 19:59:27
3rd row2021-01-04 19:59:27
4th row2021-01-04 19:59:27
5th row2021-01-04 19:59:27

Common Values

ValueCountFrequency (%)
2021-01-04 19:59:27 2187
100.0%

Length

2024-04-16T17:12:06.864000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:06.961537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-04 2187
50.0%
19:59:27 2187
50.0%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0332500003250000-202-2002-0000111_44_01_PI2018-08-31 23:59:59.0<NA>옥샘탕600051부산광역시 중구 창선동1가 9-9번지48947부산광역시 중구 광복로55번길 14-2 (창선동1가)20020513<NA><NA><NA><NA>01영업385089.38491100000180062.5676180000020180724131551공동탕업+찜질시설서비스영업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-01-04 19:59:27
1432500003250000-202-1985-0015611_44_01_PI2018-08-31 23:59:59.0<NA>금수탕600816부산광역시 중구 중앙동4가 78-2번지48947<NA>1985040920070612<NA><NA><NA>02폐업385793.29931180910.38663620041116000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:59:27
2532500003250000-202-2001-0001311_44_01_PI2018-08-31 23:59:59.0<NA>백록담600091부산광역시 중구 대청동1가 34-1번지48947<NA>2001111620120221<NA><NA><NA>02폐업385208.257554180108.03498420120227093749공동탕업+찜질시설서비스영업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업+찜질시설서비스영업<NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:59:27
3632500003250000-202-2007-0000111_44_01_PI2018-08-31 23:59:59.0<NA>유나목욕탕600061부산광역시 중구 신창동1가 5-1번지 (5~8층)48948부산광역시 중구 광복중앙로 25 (신창동1가)2007040620140401<NA><NA><NA>02폐업385157.86566400000180248.2145730000020130208113918공동탕업+찜질시설서비스영업051-123-1234자가93<NA>NY805000<NA>2공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-01-04 19:59:27
4732500003250000-202-1988-0015911_44_01_PI2018-08-31 23:59:59.0<NA>녹수탕600062부산광역시 중구 신창동2가 21-2번지48947부산광역시 중구 광복로43번길 12 (신창동2가)19880913<NA><NA><NA><NA>01영업385086.62014400000180119.3340640000020130208111503공동탕업051-123-1234임대41<NA>NN402000<NA>0공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
5832500003250000-202-1960-0014411_44_01_PU2018-11-30 02:40:00.0목욕장업금강스파600808부산광역시 중구 부평동3가 22-1번지 외 2필지48976부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)19601210<NA><NA><NA><NA>영업/정상영업384542.121201746179994.20210389820181128093116공동탕업+찜질시설서비스영업051-123-1234<NA>51<NA>NN515100<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-01-04 19:59:27
6932500003250000-202-2009-0000111_44_01_PI2018-08-31 23:59:59.0<NA>오투(O2)600046부산광역시 중구 남포동6가 85번지 (10층)48981부산광역시 중구 비프광장로 20, 10층 (남포동6가)2009022320131227<NA><NA><NA>02폐업384892.63184400000179895.5128170000020130208114221공동탕업+찜질시설서비스영업051-123-1234임대104<NA>NY10010000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-01-04 19:59:27
71032500003250000-202-1984-0015411_44_01_PI2018-08-31 23:59:59.0<NA>영진사우나600045부산광역시 중구 남포동5가 88번지48947<NA>1984020120030703<NA><NA><NA>02폐업384910.466574179447.22650620030703000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:59:27
81132500003250000-202-1984-0015211_44_01_PI2018-08-31 23:59:59.0<NA>거북목욕탕600110부산광역시 중구 영주동 292-10번지48916부산광역시 중구 영주로 20 (영주동)19840217<NA><NA><NA><NA>01영업385241.59002600000181147.1401790000020130208111357공동탕업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
91232500003250000-202-1973-0015011_44_01_PI2018-08-31 23:59:59.0<NA>부원탕600101부산광역시 중구 대창동1가 54-2번지48947<NA>1973011220051013<NA><NA><NA>02폐업<NA><NA>20040531000000공동탕업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:59:27
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
2177218048300004830000-202-2020-0001111_44_01_PI2021-01-02 00:23:15.0목욕장업봉황면 공중목욕장520852전라남도 나주시 봉황면 죽석리 537-1458307전라남도 나주시 봉황면 죽석길 920201231폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업180366.936555162125.16452320201231165523공동탕업061 339 3826자가100NN1사용끝지하층1사용시작지하층0001공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-01-04 19:59:27
2178218148300004830000-202-2020-0000111_44_01_PI2021-01-02 00:23:15.0목욕장업세지면 공중목욕장520873전라남도 나주시 세지면 오봉리 186-258318전라남도 나주시 세지면 동창로 130-1120201231<NA><NA><NA><NA>영업/정상영업177006.410157157974.10006120201231164349공동탕업061 339 3613자가200NN1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2179218248300004830000-202-2020-0000811_44_01_PI2021-01-02 00:23:15.0목욕장업금천면 공중목욕장520824전라남도 나주시 금천면 오강리 250-158215전라남도 나주시 금천면 금영로 93420201231<NA><NA><NA><NA>영업/정상영업177424.882502170223.62373720201231165147공동탕업061 339 3562자가210NY1<NA>1<NA>0002공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2180218348300004830000-202-2020-0000911_44_01_PI2021-01-02 00:23:15.0목욕장업산포면 공중목욕장520831전라남도 나주시 산포면 매성리 1266-158214전라남도 나주시 산포면 산포로 468-1520201231<NA><NA><NA><NA>영업/정상영업182209.347329171254.12362520201231165221공동탕업061 339 3601자가100NN1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2181218448300004830000-202-2020-0000611_44_01_PI2021-01-02 00:23:15.0목욕장업문평면 공중목욕장520943전라남도 나주시 문평면 옥당리 1262-1358286전라남도 나주시 문평면 체암로 15-220201231<NA><NA><NA><NA>영업/정상영업164221.175192170307.10500620201231164842공동탕업061 339 3749자가100NN1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2182218548300004830000-202-2020-0000511_44_01_PI2021-01-02 00:23:15.0목욕장업다시면 공중목욕장520934전라남도 나주시 다시면 월태리 590-3858203전라남도 나주시 다시면 다시로 175-2420201231<NA><NA><NA><NA>영업/정상영업166815.641325168981.53969620201231164803공동탕업061 339 3718자가100NN1<NA>1<NA>0002공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2183218648300004830000-202-2020-0000311_44_01_PI2021-01-02 00:23:15.0목욕장업반남면 공중목욕장520923전라남도 나주시 반남면 흥덕리 22-1258302전라남도 나주시 반남면 고분로 594-720201231<NA><NA><NA><NA>영업/정상영업168148.412376155975.58533420201231164639공동탕업061 339 3664자가200NY1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2184218748300004830000-202-2020-0000211_44_01_PI2021-01-02 00:23:15.0목욕장업왕곡면 공중목욕장520881전라남도 나주시 왕곡면 덕산리 590-152<NA><NA>20201231<NA><NA><NA><NA>영업/정상영업170041.303214163338.36077720201231164545공동탕업061 339 3654자가100NY1<NA>1<NA>0003공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2185218848300004830000-202-2020-0000711_44_01_PI2021-01-02 00:23:15.0목욕장업노안면 공중목욕장520813전라남도 나주시 노안면 금동리 221-658209전라남도 나주시 노안면 금산로 1420201231<NA><NA><NA><NA>영업/정상영업175480.078867175234.0258920201231165103공동탕업061 339 3777자가200NN1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27
2186218948300004830000-202-2020-0001011_44_01_PI2021-01-02 00:23:15.0목욕장업다도면 공중목욕장520861전라남도 나주시 다도면 신동리 309-358319전라남도 나주시 다도면 다도로 75920201231<NA><NA><NA><NA>영업/정상영업184169.935828160937.47211720201231165441공동탕업061 339 3789자가100NN1<NA>1<NA>0001공동탕업0<NA><NA><NA>0002021-01-04 19:59:27