Overview

Dataset statistics

Number of variables56
Number of observations410
Missing cells18
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory182.7 KiB
Average record size in memory456.3 B

Variable types

Numeric8
Text4
Categorical42
DateTime2

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (74.1%)Imbalance
dcbymd is highly imbalanced (65.9%)Imbalance
clgstdt is highly imbalanced (58.8%)Imbalance
clgenddt is highly imbalanced (58.8%)Imbalance
ropnymd is highly imbalanced (58.8%)Imbalance
dtlstatenm is highly imbalanced (66.6%)Imbalance
uptaenm is highly imbalanced (58.8%)Imbalance
sitetel is highly imbalanced (80.7%)Imbalance
bfgameocptectcobnm is highly imbalanced (58.8%)Imbalance
noroomcnt is highly imbalanced (58.8%)Imbalance
souarfacilyn is highly imbalanced (58.8%)Imbalance
vdoretornm is highly imbalanced (58.8%)Imbalance
emerstairyn is highly imbalanced (58.8%)Imbalance
emexyn is highly imbalanced (58.8%)Imbalance
firefacilyn is highly imbalanced (58.8%)Imbalance
facilar is highly imbalanced (76.8%)Imbalance
soundfacilyn is highly imbalanced (58.8%)Imbalance
autochaairyn is highly imbalanced (58.8%)Imbalance
prvdgathinnm is highly imbalanced (58.8%)Imbalance
mnfactreartclcn is highly imbalanced (58.8%)Imbalance
lghtfacilyn is highly imbalanced (58.8%)Imbalance
lghtfacilinillu is highly imbalanced (58.8%)Imbalance
nearenvnm is highly imbalanced (52.3%)Imbalance
regnsenm is highly imbalanced (54.7%)Imbalance
bgroomcnt is highly imbalanced (58.8%)Imbalance
bgroomyn is highly imbalanced (58.8%)Imbalance
totgasyscnt is highly imbalanced (58.8%)Imbalance
pasgbreth is highly imbalanced (52.6%)Imbalance
speclghtyn is highly imbalanced (58.8%)Imbalance
cnvefacilyn is highly imbalanced (58.8%)Imbalance
actlnm is highly imbalanced (58.8%)Imbalance
rdnwhladdr has 6 (1.5%) missing valuesMissing
x has 6 (1.5%) missing valuesMissing
y has 6 (1.5%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:41:06.959484
Analysis finished2024-04-16 11:41:08.091991
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean619.51707
Minimum1
Maximum3017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:08.151105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.45
Q1103.25
median205.5
Q3825
95-th percentile2468.6
Maximum3017
Range3016
Interquartile range (IQR)721.75

Descriptive statistics

Standard deviation816.05318
Coefficient of variation (CV)1.3172408
Kurtosis1.1206793
Mean619.51707
Median Absolute Deviation (MAD)135
Skewness1.5245234
Sum254002
Variance665942.79
MonotonicityStrictly increasing
2024-04-16T20:41:08.261696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
271 1
 
0.2%
495 1
 
0.2%
479 1
 
0.2%
477 1
 
0.2%
475 1
 
0.2%
459 1
 
0.2%
345 1
 
0.2%
335 1
 
0.2%
325 1
 
0.2%
Other values (400) 400
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
3017 1
0.2%
3016 1
0.2%
3015 1
0.2%
3014 1
0.2%
3013 1
0.2%
3012 1
0.2%
2962 1
0.2%
2958 1
0.2%
2955 1
0.2%
2953 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct14
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3318414.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:08.360556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33330000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation40740.983
Coefficient of variation (CV)0.012277243
Kurtosis-0.38270657
Mean3318414.6
Median Absolute Deviation (MAD)30000
Skewness0.13005185
Sum1.36055 × 109
Variance1.6598277 × 109
MonotonicityNot monotonic
2024-04-16T20:41:08.456789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3330000 115
28.0%
3290000 73
17.8%
3250000 53
12.9%
3350000 26
 
6.3%
3300000 25
 
6.1%
3400000 23
 
5.6%
3320000 21
 
5.1%
3310000 19
 
4.6%
3390000 15
 
3.7%
3340000 13
 
3.2%
Other values (4) 27
 
6.6%
ValueCountFrequency (%)
3250000 53
12.9%
3260000 1
 
0.2%
3270000 5
 
1.2%
3290000 73
17.8%
3300000 25
 
6.1%
3310000 19
 
4.6%
3320000 21
 
5.1%
3330000 115
28.0%
3340000 13
 
3.2%
3350000 26
 
6.3%
ValueCountFrequency (%)
3400000 23
 
5.6%
3390000 15
 
3.7%
3380000 12
 
2.9%
3370000 9
 
2.2%
3350000 26
 
6.3%
3340000 13
 
3.2%
3330000 115
28.0%
3320000 21
 
5.1%
3310000 19
 
4.6%
3300000 25
 
6.1%

mgtno
Text

Distinct227
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:08.654820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8200
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)33.7%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
4.4%
cdff5211012019000001 12
 
2.9%
cdff5211012020000002 9
 
2.2%
cdff5211032020000001 8
 
2.0%
cdff5211032019000001 8
 
2.0%
cdff5211042019000001 6
 
1.5%
cdff5211012021000001 6
 
1.5%
cdff5211042020000001 4
 
1.0%
cdff4220002007000002 4
 
1.0%
cdff5211012020000004 4
 
1.0%
Other values (217) 331
80.7%
2024-04-16T20:41:08.970974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3653
44.5%
2 1235
 
15.1%
F 820
 
10.0%
1 714
 
8.7%
C 410
 
5.0%
D 410
 
5.0%
4 362
 
4.4%
5 189
 
2.3%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 193
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6560
80.0%
Uppercase Letter 1640
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3653
55.7%
2 1235
 
18.8%
1 714
 
10.9%
4 362
 
5.5%
5 189
 
2.9%
9 132
 
2.0%
7 82
 
1.2%
3 75
 
1.1%
6 61
 
0.9%
8 57
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
F 820
50.0%
C 410
25.0%
D 410
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6560
80.0%
Latin 1640
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3653
55.7%
2 1235
 
18.8%
1 714
 
10.9%
4 362
 
5.5%
5 189
 
2.9%
9 132
 
2.0%
7 82
 
1.2%
3 75
 
1.1%
6 61
 
0.9%
8 57
 
0.9%
Latin
ValueCountFrequency (%)
F 820
50.0%
C 410
25.0%
D 410
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3653
44.5%
2 1235
 
15.1%
F 820
 
10.0%
1 714
 
8.7%
C 410
 
5.0%
D 410
 
5.0%
4 362
 
4.4%
5 189
 
2.3%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 193
 
2.4%

opnsvcid
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
03_13_02_P
282 
03_13_05_P
84 
03_13_01_P
 
23
03_13_03_P
 
15
03_13_04_P
 
6

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_13_02_P
2nd row03_13_02_P
3rd row03_13_02_P
4th row03_13_02_P
5th row03_13_02_P

Common Values

ValueCountFrequency (%)
03_13_02_P 282
68.8%
03_13_05_P 84
 
20.5%
03_13_01_P 23
 
5.6%
03_13_03_P 15
 
3.7%
03_13_04_P 6
 
1.5%

Length

2024-04-16T20:41:09.112113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:09.206054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 282
68.8%
03_13_05_p 84
 
20.5%
03_13_01_p 23
 
5.6%
03_13_03_p 15
 
3.7%
03_13_04_p 6
 
1.5%

updategbn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
I
322 
U
88 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 322
78.5%
U 88
 
21.5%

Length

2024-04-16T20:41:09.307879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:09.386685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 322
78.5%
u 88
 
21.5%
Distinct87
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-01 00:22:58
2024-04-16T20:41:09.480330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:09.599715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
216 
영화제작업
84 
영화상영관
66 
영화배급업
23 
영화상영업
 
15

Length

Max length5
Median length4
Mean length4.4731707
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
52.7%
영화제작업 84
 
20.5%
영화상영관 66
 
16.1%
영화배급업 23
 
5.6%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

Length

2024-04-16T20:41:09.714607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:09.805032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
52.7%
영화제작업 84
 
20.5%
영화상영관 66
 
16.1%
영화배급업 23
 
5.6%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

bplcnm
Text

Distinct350
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:09.992624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length10.978049
Min length2

Characters and Unicode

Total characters4501
Distinct characters256
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique325 ?
Unique (%)79.3%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 85
 
9.3%
메가박스 48
 
5.3%
cgv 41
 
4.5%
주식회사 29
 
3.2%
해운대 26
 
2.9%
서면 20
 
2.2%
센텀시티 19
 
2.1%
정관 15
 
1.6%
제3관 15
 
1.6%
6관 14
 
1.5%
Other values (212) 599
65.8%
2024-04-16T20:41:10.306327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
503
 
11.2%
311
 
6.9%
151
 
3.4%
143
 
3.2%
132
 
2.9%
121
 
2.7%
107
 
2.4%
100
 
2.2%
100
 
2.2%
C 93
 
2.1%
Other values (246) 2740
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3127
69.5%
Space Separator 503
 
11.2%
Uppercase Letter 363
 
8.1%
Decimal Number 261
 
5.8%
Close Punctuation 89
 
2.0%
Open Punctuation 89
 
2.0%
Lowercase Letter 56
 
1.2%
Other Punctuation 12
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
311
 
9.9%
151
 
4.8%
143
 
4.6%
132
 
4.2%
121
 
3.9%
107
 
3.4%
100
 
3.2%
100
 
3.2%
87
 
2.8%
86
 
2.8%
Other values (192) 1789
57.2%
Uppercase Letter
ValueCountFrequency (%)
C 93
25.6%
G 75
20.7%
V 74
20.4%
N 19
 
5.2%
E 11
 
3.0%
M 10
 
2.8%
O 8
 
2.2%
A 8
 
2.2%
U 8
 
2.2%
I 7
 
1.9%
Other values (11) 50
13.8%
Lowercase Letter
ValueCountFrequency (%)
v 8
14.3%
g 8
14.3%
c 8
14.3%
o 7
12.5%
d 6
10.7%
t 5
8.9%
l 3
 
5.4%
m 2
 
3.6%
i 2
 
3.6%
e 2
 
3.6%
Other values (5) 5
8.9%
Decimal Number
ValueCountFrequency (%)
1 44
16.9%
2 35
13.4%
4 33
12.6%
3 31
11.9%
6 30
11.5%
5 29
11.1%
7 24
9.2%
8 16
 
6.1%
9 13
 
5.0%
0 6
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 88
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 88
98.9%
[ 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
503
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3127
69.5%
Common 955
 
21.2%
Latin 419
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
311
 
9.9%
151
 
4.8%
143
 
4.6%
132
 
4.2%
121
 
3.9%
107
 
3.4%
100
 
3.2%
100
 
3.2%
87
 
2.8%
86
 
2.8%
Other values (192) 1789
57.2%
Latin
ValueCountFrequency (%)
C 93
22.2%
G 75
17.9%
V 74
17.7%
N 19
 
4.5%
E 11
 
2.6%
M 10
 
2.4%
O 8
 
1.9%
A 8
 
1.9%
v 8
 
1.9%
g 8
 
1.9%
Other values (26) 105
25.1%
Common
ValueCountFrequency (%)
503
52.7%
) 88
 
9.2%
( 88
 
9.2%
1 44
 
4.6%
2 35
 
3.7%
4 33
 
3.5%
3 31
 
3.2%
6 30
 
3.1%
5 29
 
3.0%
7 24
 
2.5%
Other values (8) 50
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3127
69.5%
ASCII 1374
30.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
503
36.6%
C 93
 
6.8%
) 88
 
6.4%
( 88
 
6.4%
G 75
 
5.5%
V 74
 
5.4%
1 44
 
3.2%
2 35
 
2.5%
4 33
 
2.4%
3 31
 
2.3%
Other values (44) 310
22.6%
Hangul
ValueCountFrequency (%)
311
 
9.9%
151
 
4.8%
143
 
4.6%
132
 
4.2%
121
 
3.9%
107
 
3.4%
100
 
3.2%
100
 
3.2%
87
 
2.8%
86
 
2.8%
Other values (192) 1789
57.2%

sitepostno
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
344 
지번우편번호
 
34
607787
 
7
614845
 
4
601060
 
3
Other values (13)
 
18

Length

Max length6
Median length4
Mean length4.3219512
Min length4

Unique

Unique10 ?
Unique (%)2.4%

Sample

1st row600805
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 344
83.9%
지번우편번호 34
 
8.3%
607787 7
 
1.7%
614845 4
 
1.0%
601060 3
 
0.7%
608805 3
 
0.7%
600805 3
 
0.7%
600046 2
 
0.5%
612824 1
 
0.2%
613827 1
 
0.2%
Other values (8) 8
 
2.0%

Length

2024-04-16T20:41:10.447059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 344
83.9%
지번우편번호 34
 
8.3%
607787 7
 
1.7%
614845 4
 
1.0%
601060 3
 
0.7%
608805 3
 
0.7%
600805 3
 
0.7%
600046 2
 
0.5%
600807 1
 
0.2%
600045 1
 
0.2%
Other values (8) 8
 
2.0%
Distinct135
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:10.690587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length27.285366
Min length18

Characters and Unicode

Total characters11187
Distinct characters225
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

Unique69 ?
Unique (%)16.8%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1번지
3rd row부산광역시 중구 남포동5가 12-1번지
4th row부산광역시 중구 남포동5가 12-1번지
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
부산광역시 410
 
20.2%
해운대구 115
 
5.7%
우동 87
 
4.3%
부산진구 73
 
3.6%
중구 53
 
2.6%
부전동 45
 
2.2%
전포동 27
 
1.3%
금정구 26
 
1.3%
동래구 25
 
1.2%
기장군 23
 
1.1%
Other values (298) 1142
56.4%
2024-04-16T20:41:11.039633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1984
 
17.7%
567
 
5.1%
524
 
4.7%
1 463
 
4.1%
446
 
4.0%
441
 
3.9%
414
 
3.7%
410
 
3.7%
388
 
3.5%
362
 
3.2%
Other values (215) 5188
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6636
59.3%
Decimal Number 2081
 
18.6%
Space Separator 1984
 
17.7%
Dash Punctuation 342
 
3.1%
Uppercase Letter 86
 
0.8%
Other Punctuation 27
 
0.2%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Math Symbol 6
 
0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
567
 
8.5%
524
 
7.9%
446
 
6.7%
441
 
6.6%
414
 
6.2%
410
 
6.2%
388
 
5.8%
362
 
5.5%
348
 
5.2%
153
 
2.3%
Other values (182) 2583
38.9%
Uppercase Letter
ValueCountFrequency (%)
K 22
25.6%
T 13
15.1%
S 12
14.0%
G 10
11.6%
C 8
 
9.3%
N 8
 
9.3%
B 4
 
4.7%
U 3
 
3.5%
H 3
 
3.5%
Y 2
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 463
22.2%
2 293
14.1%
5 220
10.6%
6 205
9.9%
4 181
 
8.7%
0 180
 
8.6%
7 160
 
7.7%
8 152
 
7.3%
3 117
 
5.6%
9 110
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
v 1
20.0%
l 1
20.0%
i 1
20.0%
o 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 18
66.7%
& 9
33.3%
Space Separator
ValueCountFrequency (%)
1984
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6636
59.3%
Common 4460
39.9%
Latin 91
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
567
 
8.5%
524
 
7.9%
446
 
6.7%
441
 
6.6%
414
 
6.2%
410
 
6.2%
388
 
5.8%
362
 
5.5%
348
 
5.2%
153
 
2.3%
Other values (182) 2583
38.9%
Common
ValueCountFrequency (%)
1984
44.5%
1 463
 
10.4%
- 342
 
7.7%
2 293
 
6.6%
5 220
 
4.9%
6 205
 
4.6%
4 181
 
4.1%
0 180
 
4.0%
7 160
 
3.6%
8 152
 
3.4%
Other values (7) 280
 
6.3%
Latin
ValueCountFrequency (%)
K 22
24.2%
T 13
14.3%
S 12
13.2%
G 10
11.0%
C 8
 
8.8%
N 8
 
8.8%
B 4
 
4.4%
U 3
 
3.3%
H 3
 
3.3%
Y 2
 
2.2%
Other values (6) 6
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6636
59.3%
ASCII 4551
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1984
43.6%
1 463
 
10.2%
- 342
 
7.5%
2 293
 
6.4%
5 220
 
4.8%
6 205
 
4.5%
4 181
 
4.0%
0 180
 
4.0%
7 160
 
3.5%
8 152
 
3.3%
Other values (23) 371
 
8.2%
Hangul
ValueCountFrequency (%)
567
 
8.5%
524
 
7.9%
446
 
6.7%
441
 
6.6%
414
 
6.2%
410
 
6.2%
388
 
5.8%
362
 
5.5%
348
 
5.2%
153
 
2.3%
Other values (182) 2583
38.9%

rdnpostno
Real number (ℝ)

Distinct75
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47972.029
Minimum46015
Maximum49431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:11.173058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46015
5-th percentile46083
Q147293.75
median48059
Q348947
95-th percentile48953
Maximum49431
Range3416
Interquartile range (IQR)1653.25

Descriptive statistics

Standard deviation910.63611
Coefficient of variation (CV)0.018982647
Kurtosis-0.64143318
Mean47972.029
Median Absolute Deviation (MAD)774
Skewness-0.53065701
Sum19668532
Variance829258.12
MonotonicityNot monotonic
2024-04-16T20:41:11.291756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 70
 
17.1%
48058 43
 
10.5%
48953 20
 
4.9%
48059 17
 
4.1%
47296 14
 
3.4%
47299 12
 
2.9%
48944 11
 
2.7%
47285 11
 
2.7%
46015 10
 
2.4%
47710 10
 
2.4%
Other values (65) 192
46.8%
ValueCountFrequency (%)
46015 10
2.4%
46024 6
1.5%
46067 1
 
0.2%
46083 6
1.5%
46251 1
 
0.2%
46259 1
 
0.2%
46291 6
1.5%
46321 1
 
0.2%
46527 9
2.2%
46548 9
2.2%
ValueCountFrequency (%)
49431 1
 
0.2%
49418 1
 
0.2%
49315 3
 
0.7%
49311 7
 
1.7%
49223 1
 
0.2%
48981 2
 
0.5%
48968 3
 
0.7%
48953 20
 
4.9%
48948 7
 
1.7%
48947 70
17.1%

rdnwhladdr
Text

MISSING 

Distinct132
Distinct (%)32.7%
Missing6
Missing (%)1.5%
Memory size3.3 KiB
2024-04-16T20:41:11.557164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length32.091584
Min length22

Characters and Unicode

Total characters12965
Distinct characters253
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

Unique68 ?
Unique (%)16.8%

Sample

1st row부산광역시 중구 중구로 13 (부평동1가)
2nd row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
3rd row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
4th row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
5th row부산광역시 중구 비프광장로 36 (남포동5가)
ValueCountFrequency (%)
부산광역시 404
 
16.0%
해운대구 115
 
4.6%
우동 83
 
3.3%
부산진구 73
 
2.9%
중구 50
 
2.0%
중앙대로 48
 
1.9%
부전동 45
 
1.8%
해운대로 44
 
1.7%
6층 32
 
1.3%
39 31
 
1.2%
Other values (359) 1599
63.4%
2024-04-16T20:41:11.942711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2145
 
16.5%
577
 
4.5%
530
 
4.1%
502
 
3.9%
448
 
3.5%
444
 
3.4%
404
 
3.1%
404
 
3.1%
) 395
 
3.0%
( 395
 
3.0%
Other values (243) 6721
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7751
59.8%
Space Separator 2145
 
16.5%
Decimal Number 1804
 
13.9%
Close Punctuation 395
 
3.0%
Open Punctuation 395
 
3.0%
Other Punctuation 355
 
2.7%
Uppercase Letter 89
 
0.7%
Dash Punctuation 19
 
0.1%
Math Symbol 6
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
577
 
7.4%
530
 
6.8%
502
 
6.5%
448
 
5.8%
444
 
5.7%
404
 
5.2%
404
 
5.2%
389
 
5.0%
334
 
4.3%
187
 
2.4%
Other values (207) 3532
45.6%
Uppercase Letter
ValueCountFrequency (%)
K 22
24.7%
T 13
14.6%
S 12
13.5%
G 9
10.1%
C 8
 
9.0%
N 7
 
7.9%
B 4
 
4.5%
H 3
 
3.4%
U 3
 
3.4%
E 2
 
2.2%
Other values (3) 6
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 351
19.5%
2 242
13.4%
0 205
11.4%
3 187
10.4%
6 161
8.9%
5 153
8.5%
7 152
8.4%
4 151
8.4%
9 113
 
6.3%
8 89
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 1
16.7%
o 1
16.7%
l 1
16.7%
i 1
16.7%
v 1
16.7%
p 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 346
97.5%
& 9
 
2.5%
Space Separator
ValueCountFrequency (%)
2145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 395
100.0%
Open Punctuation
ValueCountFrequency (%)
( 395
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7751
59.8%
Common 5119
39.5%
Latin 95
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
577
 
7.4%
530
 
6.8%
502
 
6.5%
448
 
5.8%
444
 
5.7%
404
 
5.2%
404
 
5.2%
389
 
5.0%
334
 
4.3%
187
 
2.4%
Other values (207) 3532
45.6%
Latin
ValueCountFrequency (%)
K 22
23.2%
T 13
13.7%
S 12
12.6%
G 9
9.5%
C 8
 
8.4%
N 7
 
7.4%
B 4
 
4.2%
H 3
 
3.2%
U 3
 
3.2%
E 2
 
2.1%
Other values (9) 12
12.6%
Common
ValueCountFrequency (%)
2145
41.9%
) 395
 
7.7%
( 395
 
7.7%
1 351
 
6.9%
, 346
 
6.8%
2 242
 
4.7%
0 205
 
4.0%
3 187
 
3.7%
6 161
 
3.1%
5 153
 
3.0%
Other values (7) 539
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7751
59.8%
ASCII 5214
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2145
41.1%
) 395
 
7.6%
( 395
 
7.6%
1 351
 
6.7%
, 346
 
6.6%
2 242
 
4.6%
0 205
 
3.9%
3 187
 
3.6%
6 161
 
3.1%
5 153
 
2.9%
Other values (26) 634
 
12.2%
Hangul
ValueCountFrequency (%)
577
 
7.4%
530
 
6.8%
502
 
6.5%
448
 
5.8%
444
 
5.7%
404
 
5.2%
404
 
5.2%
389
 
5.0%
334
 
4.3%
187
 
2.4%
Other values (207) 3532
45.6%

apvpermymd
Real number (ℝ)

Distinct131
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104978
Minimum19451015
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:12.067942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000516
Q120050111
median20090302
Q320190315
95-th percentile20200874
Maximum20210330
Range759315
Interquartile range (IQR)140204

Descriptive statistics

Standard deviation89464.971
Coefficient of variation (CV)0.0044498915
Kurtosis8.9917099
Mean20104978
Median Absolute Deviation (MAD)79693
Skewness-1.736836
Sum8.243041 × 109
Variance8.0039811 × 109
MonotonicityNot monotonic
2024-04-16T20:41:12.200270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.9%
20190315 12
 
2.9%
20140822 11
 
2.7%
20010609 11
 
2.7%
20050307 10
 
2.4%
20021112 10
 
2.4%
20090302 10
 
2.4%
20071204 10
 
2.4%
20080527 9
 
2.2%
20200103 9
 
2.2%
Other values (121) 306
74.6%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.5%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20210330 1
 
0.2%
20210329 1
 
0.2%
20210318 1
 
0.2%
20210317 1
 
0.2%
20210315 1
 
0.2%
20210304 1
 
0.2%
20210203 1
 
0.2%
20210202 4
1.0%
20210121 1
 
0.2%
20210120 1
 
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct29
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
312 
폐업일자
34 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (24)
38 

Length

Max length8
Median length4
Mean length4.6243902
Min length4

Unique

Unique19 ?
Unique (%)4.6%

Sample

1st row20080501
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 312
76.1%
폐업일자 34
 
8.3%
20170315 10
 
2.4%
20160617 8
 
2.0%
20110616 8
 
2.0%
20100806 7
 
1.7%
20001201 4
 
1.0%
20070725 3
 
0.7%
20200921 3
 
0.7%
20160913 2
 
0.5%
Other values (19) 19
 
4.6%

Length

2024-04-16T20:41:12.343854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 312
76.1%
폐업일자 34
 
8.3%
20170315 10
 
2.4%
20160617 8
 
2.0%
20110616 8
 
2.0%
20100806 7
 
1.7%
20001201 4
 
1.0%
20070725 3
 
0.7%
20200921 3
 
0.7%
20160913 2
 
0.5%
Other values (19) 19
 
4.6%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
휴업시작일자
 
34

Length

Max length6
Median length4
Mean length4.1658537
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> 376
91.7%
휴업시작일자 34
 
8.3%

Length

2024-04-16T20:41:12.491124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:12.598626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
휴업시작일자 34
 
8.3%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
휴업종료일자
 
34

Length

Max length6
Median length4
Mean length4.1658537
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> 376
91.7%
휴업종료일자 34
 
8.3%

Length

2024-04-16T20:41:12.703677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:12.805007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
휴업종료일자 34
 
8.3%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
재개업일자
 
34

Length

Max length5
Median length4
Mean length4.0829268
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> 376
91.7%
재개업일자 34
 
8.3%

Length

2024-04-16T20:41:12.919432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:13.034339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
재개업일자 34
 
8.3%

trdstatenm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영업/정상
184 
13
159 
03
56 
폐업
 
7
<NA>
 
2
Other values (2)
 
2

Length

Max length8
Median length2
Mean length3.3707317
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row03
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row13

Common Values

ValueCountFrequency (%)
영업/정상 184
44.9%
13 159
38.8%
03 56
 
13.7%
폐업 7
 
1.7%
<NA> 2
 
0.5%
35 1
 
0.2%
제외/삭제/전출 1
 
0.2%

Length

2024-04-16T20:41:13.123637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:13.218696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 184
44.9%
13 159
38.8%
03 56
 
13.7%
폐업 7
 
1.7%
na 2
 
0.5%
35 1
 
0.2%
제외/삭제/전출 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영업중
345 
폐업
63 
직권말소
 
1
전출
 
1

Length

Max length4
Median length3
Mean length2.8463415
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 345
84.1%
폐업 63
 
15.4%
직권말소 1
 
0.2%
전출 1
 
0.2%

Length

2024-04-16T20:41:13.331314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:13.429993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 345
84.1%
폐업 63
 
15.4%
직권말소 1
 
0.2%
전출 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)27.7%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean389989.9
Minimum377558
Maximum401504.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:13.528691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum377558
5-th percentile380780.61
Q1386497.95
median389751.94
Q3393952.26
95-th percentile398310.24
Maximum401504.79
Range23946.794
Interquartile range (IQR)7454.3149

Descriptive statistics

Standard deviation5285.7377
Coefficient of variation (CV)0.013553525
Kurtosis-0.62086641
Mean389989.9
Median Absolute Deviation (MAD)4102.7861
Skewness0.019530282
Sum1.5755592 × 108
Variance27939023
MonotonicityNot monotonic
2024-04-16T20:41:13.639825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 17
 
4.1%
387982.190387 14
 
3.4%
387443.214568 11
 
2.7%
385622.780457355 11
 
2.7%
388087.223988 11
 
2.7%
398310.243451 10
 
2.4%
396915.143441 10
 
2.4%
394153.800755 10
 
2.4%
387280.619672939 9
 
2.2%
387608.014165034 9
 
2.2%
Other values (102) 292
71.2%
ValueCountFrequency (%)
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.2%
379240.573215267 3
0.7%
379280.632039 2
 
0.5%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380625.391364589 6
1.5%
380780.612775 7
1.7%
382731.210151804 4
1.0%
ValueCountFrequency (%)
401504.790177 6
1.5%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398628.503470003 2
 
0.5%
398341.802637 7
1.7%
398310.243451 10
2.4%
398275.475596001 1
 
0.2%
398242.150343638 2
 
0.5%
398035.0 5
1.2%
398025.711375 6
1.5%

y
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)27.7%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean187859.27
Minimum178872.46
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:13.989490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178872.46
5-th percentile179885.81
Q1185679.05
median187480.44
Q3190048.6
95-th percentile195491.52
Maximum204621.66
Range25749.194
Interquartile range (IQR)4369.5539

Descriptive statistics

Standard deviation5445.462
Coefficient of variation (CV)0.028986922
Kurtosis1.5928012
Mean187859.27
Median Absolute Deviation (MAD)1855.9627
Skewness0.89523939
Sum75895146
Variance29653056
MonotonicityNot monotonic
2024-04-16T20:41:14.104944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 17
 
4.1%
186465.864259 14
 
3.4%
186484.775084 11
 
2.7%
179452.224754792 11
 
2.7%
185624.481146 11
 
2.7%
188031.67198 10
 
2.4%
187480.443811 10
 
2.4%
188019.100861 10
 
2.4%
185679.050795793 9
 
2.2%
185703.079007724 9
 
2.2%
Other values (102) 292
71.2%
ValueCountFrequency (%)
178872.461747926 1
 
0.2%
179411.189506548 1
 
0.2%
179452.224754792 11
2.7%
179597.592953541 6
1.5%
179823.23303496 1
 
0.2%
179885.813689 2
 
0.5%
179911.285409 5
1.2%
179919.437009 4
 
1.0%
179919.488084 8
2.0%
179957.089237 3
 
0.7%
ValueCountFrequency (%)
204621.655738547 5
1.2%
204597.0 5
1.2%
204401.691446 6
1.5%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
2.0%
194992.355262 9
2.2%
194622.201131 7
1.7%
194428.696617 7
1.7%
193896.1715796 1
 
0.2%

lastmodts
Real number (ℝ)

Distinct358
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0177264 × 1013
Minimum2.0030127 × 1013
Maximum2.021033 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:14.225612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0170714 × 1013
median2.0180619 × 1013
Q32.0200103 × 1013
95-th percentile2.0210203 × 1013
Maximum2.021033 × 1013
Range1.8020294 × 1011
Interquartile range (IQR)2.9389071 × 1010

Descriptive statistics

Standard deviation3.1429397 × 1010
Coefficient of variation (CV)0.001557664
Kurtosis6.6232606
Mean2.0177264 × 1013
Median Absolute Deviation (MAD)1.0300989 × 1010
Skewness-2.3826093
Sum8.2726782 × 1015
Variance9.8780701 × 1020
MonotonicityNot monotonic
2024-04-16T20:41:14.349288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190920121341 5
 
1.2%
20191017170859 4
 
1.0%
20030127161348 4
 
1.0%
20190927173659 3
 
0.7%
20210312113428 3
 
0.7%
20200921144254 3
 
0.7%
20200320175117 3
 
0.7%
20200320103703 3
 
0.7%
20200331183509 3
 
0.7%
20200103163053 3
 
0.7%
Other values (348) 376
91.7%
ValueCountFrequency (%)
20030127161348 4
1.0%
20040731102817 1
 
0.2%
20050416094533 1
 
0.2%
20070725150334 1
 
0.2%
20070725150429 1
 
0.2%
20070725183312 1
 
0.2%
20071231132808 1
 
0.2%
20080506140353 1
 
0.2%
20080627132446 1
 
0.2%
20090622134847 1
 
0.2%
ValueCountFrequency (%)
20210330103227 1
 
0.2%
20210329113916 1
 
0.2%
20210324114447 1
 
0.2%
20210324114430 1
 
0.2%
20210324114416 1
 
0.2%
20210324114359 1
 
0.2%
20210318095008 1
 
0.2%
20210317095127 1
 
0.2%
20210315152340 1
 
0.2%
20210312113428 3
0.7%

uptaenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
업태구분명
 
34

Length

Max length5
Median length4
Mean length4.0829268
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> 376
91.7%
업태구분명 34
 
8.3%

Length

2024-04-16T20:41:14.468657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:14.558128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
업태구분명 34
 
8.3%

sitetel
Categorical

IMBALANCE 

Distinct8
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
051-123-1234
376 
<NA>
 
13
전화번호
 
13
051-366-2200
 
4
070-7728-6334
 
1
Other values (3)
 
3

Length

Max length13
Median length12
Mean length11.497561
Min length4

Unique

Unique4 ?
Unique (%)1.0%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 376
91.7%
<NA> 13
 
3.2%
전화번호 13
 
3.2%
051-366-2200 4
 
1.0%
070-7728-6334 1
 
0.2%
070-8899-7402 1
 
0.2%
051-704-7125 1
 
0.2%
02-3446-7823 1
 
0.2%

Length

2024-04-16T20:41:14.646254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:14.743525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 376
91.7%
na 13
 
3.2%
전화번호 13
 
3.2%
051-366-2200 4
 
1.0%
070-7728-6334 1
 
0.2%
070-8899-7402 1
 
0.2%
051-704-7125 1
 
0.2%
02-3446-7823 1
 
0.2%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
272 
문화시설
82 
건물용도명
33 
유통시설
 
9
근린생활시설
 
7
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.0829268
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 272
66.3%
문화시설 82
 
20.0%
건물용도명 33
 
8.0%
유통시설 9
 
2.2%
근린생활시설 7
 
1.7%
호텔 6
 
1.5%
사무실 1
 
0.2%

Length

2024-04-16T20:41:14.865531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:14.972642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 272
66.3%
문화시설 82
 
20.0%
건물용도명 33
 
8.0%
유통시설 9
 
2.2%
근린생활시설 7
 
1.7%
호텔 6
 
1.5%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화관
275 
<NA>
100 
공연장형태구분명
32 
자동차극장
 
3

Length

Max length8
Median length3
Mean length3.6487805
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 275
67.1%
<NA> 100
 
24.4%
공연장형태구분명 32
 
7.8%
자동차극장 3
 
0.7%

Length

2024-04-16T20:41:15.114121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:15.207934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 275
67.1%
na 100
 
24.4%
공연장형태구분명 32
 
7.8%
자동차극장 3
 
0.7%

bfgameocptectcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
기존게임업외업종명
 
34

Length

Max length9
Median length4
Mean length4.4146341
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> 376
91.7%
기존게임업외업종명 34
 
8.3%

Length

2024-04-16T20:41:15.308662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:15.415131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
기존게임업외업종명 34
 
8.3%

noroomcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
노래방실수
 
34

Length

Max length5
Median length4
Mean length4.0829268
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> 376
91.7%
노래방실수 34
 
8.3%

Length

2024-04-16T20:41:15.525619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:15.622118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
노래방실수 34
 
8.3%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화상영관
196 
<NA>
181 
문화사업자구분명
33 

Length

Max length8
Median length5
Mean length4.8
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 196
47.8%
<NA> 181
44.1%
문화사업자구분명 33
 
8.0%

Length

2024-04-16T20:41:15.720096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:15.820693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 196
47.8%
na 181
44.1%
문화사업자구분명 33
 
8.0%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화상영관
282 
영화제작업
84 
영화배급업
 
23
영화상영업
 
15
영화수입업
 
6

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 282
68.8%
영화제작업 84
 
20.5%
영화배급업 23
 
5.6%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

Length

2024-04-16T20:41:15.911351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:16.002739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 282
68.8%
영화제작업 84
 
20.5%
영화배급업 23
 
5.6%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

souarfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:16.128938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:16.230910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

vdoretornm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
비디오재생기명
 
34

Length

Max length7
Median length4
Mean length4.2487805
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> 376
91.7%
비디오재생기명 34
 
8.3%

Length

2024-04-16T20:41:16.335930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:16.423956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
비디오재생기명 34
 
8.3%

emerstairyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:16.528598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:16.619162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

emexyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:16.719456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:16.806987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

firefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:16.914117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:17.000202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

facilar
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
370 
시설면적
 
34
1578.8
 
4
147.46
 
1
181.3
 
1

Length

Max length6
Median length4
Mean length4.0268293
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
90.2%
시설면적 34
 
8.3%
1578.8 4
 
1.0%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:41:17.099179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:17.210680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
90.2%
시설면적 34
 
8.3%
1578.8 4
 
1.0%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:17.317529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:17.420560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

autochaairyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:17.514458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:17.606733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

prvdgathinnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
제공게임물명
 
34

Length

Max length6
Median length4
Mean length4.1658537
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> 376
91.7%
제공게임물명 34
 
8.3%

Length

2024-04-16T20:41:17.705812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:17.805631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
제공게임물명 34
 
8.3%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
제작취급품목내용
 
34

Length

Max length8
Median length4
Mean length4.3317073
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> 376
91.7%
제작취급품목내용 34
 
8.3%

Length

2024-04-16T20:41:17.906722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:18.000423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
제작취급품목내용 34
 
8.3%

lghtfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:18.091084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:18.176177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

lghtfacilinillu
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
조명시설조도
 
34

Length

Max length6
Median length4
Mean length4.1658537
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> 376
91.7%
조명시설조도 34
 
8.3%

Length

2024-04-16T20:41:18.274323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:18.374132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
조명시설조도 34
 
8.3%

nearenvnm
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
315 
주변환경명
34 
기타
32 
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.1439024
Min length2

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> 315
76.8%
주변환경명 34
 
8.3%
기타 32
 
7.8%
유흥업소밀집지역 18
 
4.4%
아파트지역 9
 
2.2%
학교정화(상대) 2
 
0.5%

Length

2024-04-16T20:41:18.471616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:18.585002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
76.8%
주변환경명 34
 
8.3%
기타 32
 
7.8%
유흥업소밀집지역 18
 
4.4%
아파트지역 9
 
2.2%
학교정화(상대 2
 
0.5%

jisgnumlay
Categorical

Distinct21
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
151 
10
37 
지상층수
32 
7
28 
9
25 
Other values (16)
137 

Length

Max length4
Median length2
Mean length2.6121951
Min length1

Unique

Unique4 ?
Unique (%)1.0%

Sample

1st row4
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
<NA> 151
36.8%
10 37
 
9.0%
지상층수 32
 
7.8%
7 28
 
6.8%
9 25
 
6.1%
5 20
 
4.9%
8 19
 
4.6%
42 17
 
4.1%
12 15
 
3.7%
6 12
 
2.9%
Other values (11) 54
 
13.2%

Length

2024-04-16T20:41:18.699544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
36.8%
10 37
 
9.0%
지상층수 32
 
7.8%
7 28
 
6.8%
9 25
 
6.1%
5 20
 
4.9%
8 19
 
4.6%
42 17
 
4.1%
12 15
 
3.7%
6 12
 
2.9%
Other values (11) 54
 
13.2%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
301 
지역구분명
34 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3268293
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 301
73.4%
지역구분명 34
 
8.3%
일반상업지역 30
 
7.3%
상업지역 16
 
3.9%
중심상업지역 12
 
2.9%
녹지지역 8
 
2.0%
일반주거지역 4
 
1.0%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:41:18.810519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:18.922429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 301
73.4%
지역구분명 34
 
8.3%
일반상업지역 30
 
7.3%
상업지역 16
 
3.9%
중심상업지역 12
 
2.9%
녹지지역 8
 
2.0%
일반주거지역 4
 
1.0%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct11
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
159 
5
51 
2
47 
1
35 
지하층수
33 
Other values (6)
85 

Length

Max length4
Median length1
Mean length2.4097561
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row4
3rd row4
4th row4
5th row1

Common Values

ValueCountFrequency (%)
<NA> 159
38.8%
5 51
 
12.4%
2 47
 
11.5%
1 35
 
8.5%
지하층수 33
 
8.0%
3 24
 
5.9%
4 21
 
5.1%
6 20
 
4.9%
8 18
 
4.4%
58 1
 
0.2%

Length

2024-04-16T20:41:19.034936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 159
38.8%
5 51
 
12.4%
2 47
 
11.5%
1 35
 
8.5%
지하층수 33
 
8.0%
3 24
 
5.9%
4 21
 
5.1%
6 20
 
4.9%
8 18
 
4.4%
58 1
 
0.2%

bgroomcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
청소년실수
 
34

Length

Max length5
Median length4
Mean length4.0829268
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> 376
91.7%
청소년실수 34
 
8.3%

Length

2024-04-16T20:41:19.143012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:19.242723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
청소년실수 34
 
8.3%

bgroomyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:19.338188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:19.683249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

totgasyscnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
총게임기수
 
34

Length

Max length5
Median length4
Mean length4.0829268
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> 376
91.7%
총게임기수 34
 
8.3%

Length

2024-04-16T20:41:19.781277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:19.873001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
총게임기수 34
 
8.3%

totnumlay
Categorical

Distinct18
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
237 
총층수
33 
10
 
20
9
 
12
6
 
12
Other values (13)
96 

Length

Max length4
Median length4
Mean length3.1560976
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
57.8%
총층수 33
 
8.0%
10 20
 
4.9%
9 12
 
2.9%
6 12
 
2.9%
11 12
 
2.9%
18 11
 
2.7%
19 10
 
2.4%
15 9
 
2.2%
54 9
 
2.2%
Other values (8) 45
 
11.0%

Length

2024-04-16T20:41:19.961844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 237
57.8%
총층수 33
 
8.0%
10 20
 
4.9%
9 12
 
2.9%
6 12
 
2.9%
11 12
 
2.9%
18 11
 
2.7%
19 10
 
2.4%
54 9
 
2.2%
15 9
 
2.2%
Other values (8) 45
 
11.0%

frstregts
Real number (ℝ)

Distinct131
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104978
Minimum19451015
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:20.071049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000516
Q120050111
median20090302
Q320190315
95-th percentile20200874
Maximum20210330
Range759315
Interquartile range (IQR)140204

Descriptive statistics

Standard deviation89464.971
Coefficient of variation (CV)0.0044498915
Kurtosis8.9917099
Mean20104978
Median Absolute Deviation (MAD)79693
Skewness-1.736836
Sum8.243041 × 109
Variance8.0039811 × 109
MonotonicityNot monotonic
2024-04-16T20:41:20.193781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.9%
20190315 12
 
2.9%
20140822 11
 
2.7%
20010609 11
 
2.7%
20050307 10
 
2.4%
20021112 10
 
2.4%
20090302 10
 
2.4%
20071204 10
 
2.4%
20080527 9
 
2.2%
20200103 9
 
2.2%
Other values (121) 306
74.6%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.5%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20210330 1
 
0.2%
20210329 1
 
0.2%
20210318 1
 
0.2%
20210317 1
 
0.2%
20210315 1
 
0.2%
20210304 1
 
0.2%
20210203 1
 
0.2%
20210202 4
1.0%
20210121 1
 
0.2%
20210120 1
 
0.2%

pasgbreth
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
230 
1
102 
통로너비
33 
1.5
 
12
1.2
 
7
Other values (13)
26 

Length

Max length4
Median length4
Mean length3.1853659
Min length1

Unique

Unique8 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
56.1%
1 102
24.9%
통로너비 33
 
8.0%
1.5 12
 
2.9%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
1.0%
1.3 4
 
1.0%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
2.0%

Length

2024-04-16T20:41:20.311821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 230
56.1%
1 102
24.9%
통로너비 33
 
8.0%
1.5 12
 
2.9%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
1.0%
1.3 4
 
1.0%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
2.0%

speclghtyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:20.434756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:20.519418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

cnvefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
 
34

Length

Max length4
Median length4
Mean length3.7512195
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> 376
91.7%
34
 
8.3%

Length

2024-04-16T20:41:20.614168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:20.701302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
34
 
8.3%

actlnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
376 
품목명
 
34

Length

Max length4
Median length4
Mean length3.9170732
Min length3

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> 376
91.7%
품목명 34
 
8.3%

Length

2024-04-16T20:41:20.797739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:20.891585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
91.7%
품목명 34
 
8.3%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2021-04-01 05:20:03
Maximum2021-04-01 05:20:03
2024-04-16T20:41:20.961777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:21.036127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
013250000CDFF422000200500000103_13_02_PI2018-08-31 23:59:59.0<NA>국도극장 예술관600805부산광역시 중구 부평동1가 45-9번지48947부산광역시 중구 중구로 13 (부평동1가)2005041520080501<NA><NA><NA>03폐업384872.100538179957.08923720080506140353<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>20050415<NA><NA><NA><NA>2021-04-01 05:20:03
123250000CDFF422000201700000303_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162055<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-04-01 05:20:03
233250000CDFF422000201700000603_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162131<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-04-01 05:20:03
343250000CDFF422000201700000503_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제5관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162119<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-04-01 05:20:03
453250000CDFF422000198200000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 1관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19820125<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102116<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19820125<NA><NA><NA><NA>2021-04-01 05:20:03
563250000CDFF422000199300000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 2관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102237<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-04-01 05:20:03
673250000CDFF422000199300000203_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 3관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621103110<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-04-01 05:20:03
783250000CDFF422000199800000103_13_02_PI2018-08-31 23:59:59.0<NA>삼보극장600807부산광역시 중구 부평동2가 56번지48947<NA>1998030720070725<NA><NA><NA>03폐업<NA><NA>20070725183312<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19980307<NA><NA><NA><NA>2021-04-01 05:20:03
893250000CDFF422000199900000103_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 1관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104121<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1019990716<NA><NA><NA><NA>2021-04-01 05:20:03
9103250000CDFF422000199900000203_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 2관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104156<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>4<NA><NA><NA><NA>19990716<NA><NA><NA><NA>2021-04-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
40029533330000CDFF521101202100000103_13_05_PI2021-02-04 00:23:03.0영화제작업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122737<NA><NA><NA><NA><NA><NA><NA>영화제작업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-04-01 05:20:03
40129553330000CDFF521102202100000103_13_04_PI2021-02-04 00:23:03.0영화수입업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122805<NA><NA><NA><NA><NA><NA><NA>영화수입업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-04-01 05:20:03
40229583330000CDFF521104202100000103_13_03_PI2021-02-04 00:23:03.0영화상영업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122837<NA><NA><NA><NA><NA><NA><NA>영화상영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-04-01 05:20:03
40329623270000CDFF521104202100000103_13_03_PI2021-02-05 00:23:13.0영화상영업부산일보(주)지번우편번호부산광역시 동구 수정동 1-1048789부산광역시 동구 중앙대로 365 (수정동)20210203폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중386604.613131182960.14536720210203130757업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210203통로너비품목명2021-04-01 05:20:03
40430123310000CDFF521101202100000103_13_05_PI2021-03-06 00:23:00.0영화제작업방과후 필름지번우편번호부산광역시 남구 대연동 1730-7 목화베스트빌라48504부산광역시 남구 유엔평화로9번길 25, 2동 501호 (대연동, 목화베스트빌라)20210304폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중390736.864795183695.96040120210304173110업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210304통로너비품목명2021-04-01 05:20:03
40530133330000CDFF521101202100000203_13_05_PI2021-03-17 00:22:59.0영화제작업디테일스튜디오지번우편번호부산광역시 해운대구 우동 1462 센텀그린타워 605호48059부산광역시 해운대구 센텀중앙로 78, 센텀그린타워 605호 (우동)20210315폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393696.083566188229.68954720210315152340업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210315통로너비품목명2021-04-01 05:20:03
40630143380000CDFF521101202100000103_13_05_PI2021-03-19 00:22:59.0영화제작업더블에이 필름지번우편번호부산광역시 수영구 남천동 28-28 금양시티48314부산광역시 수영구 수영로 452-13 (남천동, 금양시티)20210317폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392289.032724185044.48104120210317095127업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210317통로너비품목명2021-04-01 05:20:03
40730153330000CDFF521101202100000303_13_05_PI2021-03-20 00:22:59.0영화제작업세발자전거 아트센터지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 1002호, 1014호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1002호, 1014호 (우동)20210318폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210318095008업태구분명02-3446-7823건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210318통로너비품목명2021-04-01 05:20:03
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