Overview

Dataset statistics

Number of variables56
Number of observations442
Missing cells33
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory196.5 KiB
Average record size in memory455.3 B

Variable types

Numeric7
Text5
Categorical43
DateTime1

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (74.7%)Imbalance
dcbymd is highly imbalanced (64.5%)Imbalance
dtlstatenm is highly imbalanced (67.0%)Imbalance
sitetel is highly imbalanced (56.1%)Imbalance
noroomcnt is highly imbalanced (60.8%)Imbalance
facilar is highly imbalanced (71.4%)Imbalance
lghtfacilinillu is highly imbalanced (60.8%)Imbalance
regnsenm is highly imbalanced (53.0%)Imbalance
bgroomcnt is highly imbalanced (60.8%)Imbalance
totgasyscnt is highly imbalanced (60.8%)Imbalance
pasgbreth is highly imbalanced (51.5%)Imbalance
rdnpostno has 15 (3.4%) missing valuesMissing
rdnwhladdr has 6 (1.4%) missing valuesMissing
x has 6 (1.4%) missing valuesMissing
y has 6 (1.4%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:40:03.957323
Analysis finished2024-04-16 11:40:04.713741
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct442
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean794.28507
Minimum1
Maximum3049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:04.779233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.05
Q1111.25
median221.5
Q31419.5
95-th percentile3026.95
Maximum3049
Range3048
Interquartile range (IQR)1308.25

Descriptive statistics

Standard deviation1004.9165
Coefficient of variation (CV)1.2651836
Kurtosis0.044128463
Mean794.28507
Median Absolute Deviation (MAD)166
Skewness1.2379243
Sum351074
Variance1009857.1
MonotonicityNot monotonic
2024-04-16T20:40:04.910185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
771 1
 
0.2%
804 1
 
0.2%
801 1
 
0.2%
799 1
 
0.2%
796 1
 
0.2%
794 1
 
0.2%
791 1
 
0.2%
789 1
 
0.2%
786 1
 
0.2%
Other values (432) 432
97.7%
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 (%)
3049 1
0.2%
3048 1
0.2%
3047 1
0.2%
3046 1
0.2%
3045 1
0.2%
3044 1
0.2%
3043 1
0.2%
3042 1
0.2%
3041 1
0.2%
3040 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3319819
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:05.006318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33340000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation41282.872
Coefficient of variation (CV)0.012435278
Kurtosis-0.47658971
Mean3319819
Median Absolute Deviation (MAD)30000
Skewness0.093569575
Sum1.46736 × 109
Variance1.7042756 × 109
MonotonicityNot monotonic
2024-04-16T20:40:05.097844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 121
27.4%
3290000 77
17.4%
3250000 56
12.7%
3300000 27
 
6.1%
3350000 26
 
5.9%
3400000 26
 
5.9%
3320000 22
 
5.0%
3310000 19
 
4.3%
3380000 18
 
4.1%
3390000 15
 
3.4%
Other values (5) 35
 
7.9%
ValueCountFrequency (%)
3250000 56
12.7%
3260000 1
 
0.2%
3270000 5
 
1.1%
3290000 77
17.4%
3300000 27
 
6.1%
3310000 19
 
4.3%
3320000 22
 
5.0%
3330000 121
27.4%
3340000 13
 
2.9%
3350000 26
 
5.9%
ValueCountFrequency (%)
3400000 26
 
5.9%
3390000 15
 
3.4%
3380000 18
 
4.1%
3370000 9
 
2.0%
3360000 7
 
1.6%
3350000 26
 
5.9%
3340000 13
 
2.9%
3330000 121
27.4%
3320000 22
 
5.0%
3310000 19
 
4.3%

mgtno
Text

Distinct240
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-16T20:40:05.301836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8840
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

Unique145 ?
Unique (%)32.8%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
4.1%
cdff5211012019000001 12
 
2.7%
cdff5211012020000002 9
 
2.0%
cdff5211042021000001 8
 
1.8%
cdff5211032020000001 8
 
1.8%
cdff5211012021000001 8
 
1.8%
cdff5211032019000001 8
 
1.8%
cdff5211042019000001 6
 
1.4%
cdff4220002007000002 4
 
0.9%
cdff5211032021000001 4
 
0.9%
Other values (230) 357
80.8%
2024-04-16T20:40:05.602182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3893
44.0%
2 1345
 
15.2%
F 884
 
10.0%
1 818
 
9.3%
C 442
 
5.0%
D 442
 
5.0%
4 379
 
4.3%
5 216
 
2.4%
9 132
 
1.5%
3 85
 
1.0%
Other values (3) 204
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7072
80.0%
Uppercase Letter 1768
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3893
55.0%
2 1345
 
19.0%
1 818
 
11.6%
4 379
 
5.4%
5 216
 
3.1%
9 132
 
1.9%
3 85
 
1.2%
7 84
 
1.2%
6 63
 
0.9%
8 57
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
F 884
50.0%
C 442
25.0%
D 442
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7072
80.0%
Latin 1768
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3893
55.0%
2 1345
 
19.0%
1 818
 
11.6%
4 379
 
5.4%
5 216
 
3.1%
9 132
 
1.9%
3 85
 
1.2%
7 84
 
1.2%
6 63
 
0.9%
8 57
 
0.8%
Latin
ValueCountFrequency (%)
F 884
50.0%
C 442
25.0%
D 442
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3893
44.0%
2 1345
 
15.2%
F 884
 
10.0%
1 818
 
9.3%
C 442
 
5.0%
D 442
 
5.0%
4 379
 
4.3%
5 216
 
2.4%
9 132
 
1.5%
3 85
 
1.0%
Other values (3) 204
 
2.3%

opnsvcid
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
03_13_02_P
290 
03_13_05_P
94 
03_13_01_P
 
29
03_13_03_P
 
21
03_13_04_P
 
8

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 290
65.6%
03_13_05_P 94
 
21.3%
03_13_01_P 29
 
6.6%
03_13_03_P 21
 
4.8%
03_13_04_P 8
 
1.8%

Length

2024-04-16T20:40:05.722208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:05.808692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 290
65.6%
03_13_05_p 94
 
21.3%
03_13_01_p 29
 
6.6%
03_13_03_p 21
 
4.8%
03_13_04_p 8
 
1.8%

updategbn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
I
299 
U
143 

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 299
67.6%
U 143
32.4%

Length

2024-04-16T20:40:05.907322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:05.989385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 299
67.6%
u 143
32.4%
Distinct102
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-07-24 00:23:01
2024-04-16T20:40:06.305760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:40:06.416620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
174 
영화상영관
116 
영화제작업
94 
영화배급업
29 
영화상영업
21 

Length

Max length5
Median length5
Mean length4.6063348
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 174
39.4%
영화상영관 116
26.2%
영화제작업 94
21.3%
영화배급업 29
 
6.6%
영화상영업 21
 
4.8%
영화수입업 8
 
1.8%

Length

2024-04-16T20:40:06.534761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:06.630629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 174
39.4%
영화상영관 116
26.2%
영화제작업 94
21.3%
영화배급업 29
 
6.6%
영화상영업 21
 
4.8%
영화수입업 8
 
1.8%

bplcnm
Text

Distinct371
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-16T20:40:06.828331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length10.984163
Min length2

Characters and Unicode

Total characters4855
Distinct characters252
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

Unique339 ?
Unique (%)76.7%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 92
 
9.4%
메가박스 48
 
4.9%
cgv 41
 
4.2%
주식회사 36
 
3.7%
해운대 26
 
2.7%
서면 20
 
2.0%
센텀시티 19
 
1.9%
6관 15
 
1.5%
제3관 15
 
1.5%
정관 15
 
1.5%
Other values (230) 653
66.6%
2024-04-16T20:40:07.142635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
540
 
11.1%
317
 
6.5%
163
 
3.4%
147
 
3.0%
144
 
3.0%
130
 
2.7%
115
 
2.4%
108
 
2.2%
107
 
2.2%
C 105
 
2.2%
Other values (242) 2979
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3408
70.2%
Space Separator 540
 
11.1%
Uppercase Letter 419
 
8.6%
Decimal Number 267
 
5.5%
Close Punctuation 94
 
1.9%
Open Punctuation 94
 
1.9%
Lowercase Letter 20
 
0.4%
Other Punctuation 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
317
 
9.3%
163
 
4.8%
147
 
4.3%
144
 
4.2%
130
 
3.8%
115
 
3.4%
108
 
3.2%
107
 
3.1%
96
 
2.8%
80
 
2.3%
Other values (195) 2001
58.7%
Uppercase Letter
ValueCountFrequency (%)
C 105
25.1%
G 83
19.8%
V 82
19.6%
N 24
 
5.7%
E 13
 
3.1%
O 12
 
2.9%
I 11
 
2.6%
M 10
 
2.4%
U 10
 
2.4%
T 9
 
2.1%
Other values (12) 60
14.3%
Decimal Number
ValueCountFrequency (%)
1 44
16.5%
2 36
13.5%
4 34
12.7%
3 32
12.0%
6 31
11.6%
5 30
11.2%
7 25
9.4%
8 16
 
6.0%
9 13
 
4.9%
0 6
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
o 7
35.0%
d 5
25.0%
t 4
20.0%
i 1
 
5.0%
l 1
 
5.0%
m 1
 
5.0%
s 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 93
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 93
98.9%
[ 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
540
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3408
70.2%
Common 1008
 
20.8%
Latin 439
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
317
 
9.3%
163
 
4.8%
147
 
4.3%
144
 
4.2%
130
 
3.8%
115
 
3.4%
108
 
3.2%
107
 
3.1%
96
 
2.8%
80
 
2.3%
Other values (195) 2001
58.7%
Latin
ValueCountFrequency (%)
C 105
23.9%
G 83
18.9%
V 82
18.7%
N 24
 
5.5%
E 13
 
3.0%
O 12
 
2.7%
I 11
 
2.5%
M 10
 
2.3%
U 10
 
2.3%
T 9
 
2.1%
Other values (19) 80
18.2%
Common
ValueCountFrequency (%)
540
53.6%
) 93
 
9.2%
( 93
 
9.2%
1 44
 
4.4%
2 36
 
3.6%
4 34
 
3.4%
3 32
 
3.2%
6 31
 
3.1%
5 30
 
3.0%
7 25
 
2.5%
Other values (8) 50
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3408
70.2%
ASCII 1447
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
540
37.3%
C 105
 
7.3%
) 93
 
6.4%
( 93
 
6.4%
G 83
 
5.7%
V 82
 
5.7%
1 44
 
3.0%
2 36
 
2.5%
4 34
 
2.3%
3 32
 
2.2%
Other values (37) 305
21.1%
Hangul
ValueCountFrequency (%)
317
 
9.3%
163
 
4.8%
147
 
4.3%
144
 
4.2%
130
 
3.8%
115
 
3.4%
108
 
3.2%
107
 
3.1%
96
 
2.8%
80
 
2.3%
Other values (195) 2001
58.7%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
362 
지번우편번호
58 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.361991
Min length4

Unique

Unique10 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 362
81.9%
지번우편번호 58
 
13.1%
614845 4
 
0.9%
600805 3
 
0.7%
601060 3
 
0.7%
600046 2
 
0.5%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.4%

Length

2024-04-16T20:40:07.263361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 362
81.9%
지번우편번호 58
 
13.1%
614845 4
 
0.9%
600805 3
 
0.7%
601060 3
 
0.7%
600046 2
 
0.5%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.4%
Distinct143
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-16T20:40:07.516885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length26.9819
Min length18

Characters and Unicode

Total characters11926
Distinct characters230
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 (%)15.6%

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 442
 
20.1%
해운대구 121
 
5.5%
우동 92
 
4.2%
부산진구 77
 
3.5%
중구 56
 
2.6%
부전동 47
 
2.1%
동래구 27
 
1.2%
전포동 27
 
1.2%
금정구 26
 
1.2%
기장군 26
 
1.2%
Other values (318) 1253
57.1%
2024-04-16T20:40:07.891506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2148
 
18.0%
609
 
5.1%
570
 
4.8%
1 483
 
4.0%
481
 
4.0%
473
 
4.0%
446
 
3.7%
442
 
3.7%
417
 
3.5%
- 370
 
3.1%
Other values (220) 5487
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6968
58.4%
Decimal Number 2206
 
18.5%
Space Separator 2148
 
18.0%
Dash Punctuation 370
 
3.1%
Uppercase Letter 132
 
1.1%
Other Punctuation 57
 
0.5%
Lowercase Letter 15
 
0.1%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
609
 
8.7%
570
 
8.2%
481
 
6.9%
473
 
6.8%
446
 
6.4%
442
 
6.3%
417
 
6.0%
307
 
4.4%
286
 
4.1%
160
 
2.3%
Other values (184) 2777
39.9%
Uppercase Letter
ValueCountFrequency (%)
K 29
22.0%
S 19
14.4%
T 15
11.4%
B 11
 
8.3%
H 10
 
7.6%
G 10
 
7.6%
U 10
 
7.6%
C 10
 
7.6%
Y 9
 
6.8%
N 8
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 483
21.9%
2 314
14.2%
6 229
10.4%
5 224
10.2%
4 201
9.1%
0 183
 
8.3%
7 161
 
7.3%
8 158
 
7.2%
3 138
 
6.3%
9 115
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
o 3
20.0%
h 2
 
13.3%
r 2
 
13.3%
v 1
 
6.7%
i 1
 
6.7%
l 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 30
52.6%
, 18
31.6%
& 9
 
15.8%
Space Separator
ValueCountFrequency (%)
2148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 370
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6968
58.4%
Common 4811
40.3%
Latin 147
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
609
 
8.7%
570
 
8.2%
481
 
6.9%
473
 
6.8%
446
 
6.4%
442
 
6.3%
417
 
6.0%
307
 
4.4%
286
 
4.1%
160
 
2.3%
Other values (184) 2777
39.9%
Common
ValueCountFrequency (%)
2148
44.6%
1 483
 
10.0%
- 370
 
7.7%
2 314
 
6.5%
6 229
 
4.8%
5 224
 
4.7%
4 201
 
4.2%
0 183
 
3.8%
7 161
 
3.3%
8 158
 
3.3%
Other values (8) 340
 
7.1%
Latin
ValueCountFrequency (%)
K 29
19.7%
S 19
12.9%
T 15
10.2%
B 11
 
7.5%
H 10
 
6.8%
G 10
 
6.8%
U 10
 
6.8%
C 10
 
6.8%
Y 9
 
6.1%
N 8
 
5.4%
Other values (8) 16
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6968
58.4%
ASCII 4958
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2148
43.3%
1 483
 
9.7%
- 370
 
7.5%
2 314
 
6.3%
6 229
 
4.6%
5 224
 
4.5%
4 201
 
4.1%
0 183
 
3.7%
7 161
 
3.2%
8 158
 
3.2%
Other values (26) 487
 
9.8%
Hangul
ValueCountFrequency (%)
609
 
8.7%
570
 
8.2%
481
 
6.9%
473
 
6.8%
446
 
6.4%
442
 
6.3%
417
 
6.0%
307
 
4.4%
286
 
4.1%
160
 
2.3%
Other values (184) 2777
39.9%

rdnpostno
Text

MISSING 

Distinct82
Distinct (%)19.2%
Missing15
Missing (%)3.4%
Memory size3.6 KiB
2024-04-16T20:40:08.095361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0046838
Min length5

Characters and Unicode

Total characters2137
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

Unique37 ?
Unique (%)8.7%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 60
 
14.1%
48058 42
 
9.8%
48953 20
 
4.7%
48059 17
 
4.0%
47296 16
 
3.7%
47299 12
 
2.8%
48944 11
 
2.6%
47285 11
 
2.6%
48948 10
 
2.3%
47710 10
 
2.3%
Other values (72) 218
51.1%
2024-04-16T20:40:08.413104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 570
26.7%
8 363
17.0%
9 244
11.4%
7 223
 
10.4%
5 159
 
7.4%
0 151
 
7.1%
2 138
 
6.5%
6 129
 
6.0%
1 80
 
3.7%
3 73
 
3.4%
Other values (7) 7
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2130
99.7%
Other Letter 7
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 570
26.8%
8 363
17.0%
9 244
11.5%
7 223
 
10.5%
5 159
 
7.5%
0 151
 
7.1%
2 138
 
6.5%
6 129
 
6.1%
1 80
 
3.8%
3 73
 
3.4%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2130
99.7%
Hangul 7
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 570
26.8%
8 363
17.0%
9 244
11.5%
7 223
 
10.5%
5 159
 
7.5%
0 151
 
7.1%
2 138
 
6.5%
6 129
 
6.1%
1 80
 
3.8%
3 73
 
3.4%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2130
99.7%
Hangul 7
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 570
26.8%
8 363
17.0%
9 244
11.5%
7 223
 
10.5%
5 159
 
7.5%
0 151
 
7.1%
2 138
 
6.5%
6 129
 
6.1%
1 80
 
3.8%
3 73
 
3.4%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

rdnwhladdr
Text

MISSING 

Distinct144
Distinct (%)33.0%
Missing6
Missing (%)1.4%
Memory size3.6 KiB
2024-04-16T20:40:08.654189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length32.662844
Min length22

Characters and Unicode

Total characters14241
Distinct characters263
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

Unique72 ?
Unique (%)16.5%

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 436
 
15.8%
해운대구 121
 
4.4%
우동 82
 
3.0%
부산진구 77
 
2.8%
중구 53
 
1.9%
중앙대로 50
 
1.8%
부전동 47
 
1.7%
해운대로 44
 
1.6%
6층 35
 
1.3%
39 34
 
1.2%
Other values (398) 1778
64.5%
2024-04-16T20:40:09.036451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2346
 
16.5%
622
 
4.4%
577
 
4.1%
538
 
3.8%
487
 
3.4%
486
 
3.4%
436
 
3.1%
436
 
3.1%
( 426
 
3.0%
) 426
 
3.0%
Other values (253) 7461
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8489
59.6%
Space Separator 2346
 
16.5%
Decimal Number 1947
 
13.7%
Open Punctuation 429
 
3.0%
Close Punctuation 429
 
3.0%
Other Punctuation 423
 
3.0%
Uppercase Letter 136
 
1.0%
Dash Punctuation 20
 
0.1%
Lowercase Letter 16
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
622
 
7.3%
577
 
6.8%
538
 
6.3%
487
 
5.7%
486
 
5.7%
436
 
5.1%
436
 
5.1%
418
 
4.9%
356
 
4.2%
194
 
2.3%
Other values (212) 3939
46.4%
Uppercase Letter
ValueCountFrequency (%)
K 29
21.3%
S 19
14.0%
T 15
11.0%
B 11
 
8.1%
C 10
 
7.4%
U 10
 
7.4%
H 10
 
7.4%
G 9
 
6.6%
Y 9
 
6.6%
N 7
 
5.1%
Other values (3) 7
 
5.1%
Decimal Number
ValueCountFrequency (%)
1 375
19.3%
2 271
13.9%
0 219
11.2%
3 207
10.6%
6 178
9.1%
5 163
8.4%
7 158
8.1%
4 157
8.1%
9 125
 
6.4%
8 94
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
r 2
 
12.5%
h 2
 
12.5%
v 1
 
6.2%
i 1
 
6.2%
l 1
 
6.2%
p 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 374
88.4%
* 40
 
9.5%
& 9
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 426
99.3%
[ 3
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 426
99.3%
] 3
 
0.7%
Space Separator
ValueCountFrequency (%)
2346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8489
59.6%
Common 5600
39.3%
Latin 152
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
622
 
7.3%
577
 
6.8%
538
 
6.3%
487
 
5.7%
486
 
5.7%
436
 
5.1%
436
 
5.1%
418
 
4.9%
356
 
4.2%
194
 
2.3%
Other values (212) 3939
46.4%
Latin
ValueCountFrequency (%)
K 29
19.1%
S 19
12.5%
T 15
9.9%
B 11
 
7.2%
C 10
 
6.6%
U 10
 
6.6%
H 10
 
6.6%
G 9
 
5.9%
Y 9
 
5.9%
N 7
 
4.6%
Other values (11) 23
15.1%
Common
ValueCountFrequency (%)
2346
41.9%
( 426
 
7.6%
) 426
 
7.6%
1 375
 
6.7%
, 374
 
6.7%
2 271
 
4.8%
0 219
 
3.9%
3 207
 
3.7%
6 178
 
3.2%
5 163
 
2.9%
Other values (10) 615
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8489
59.6%
ASCII 5752
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2346
40.8%
( 426
 
7.4%
) 426
 
7.4%
1 375
 
6.5%
, 374
 
6.5%
2 271
 
4.7%
0 219
 
3.8%
3 207
 
3.6%
6 178
 
3.1%
5 163
 
2.8%
Other values (31) 767
 
13.3%
Hangul
ValueCountFrequency (%)
622
 
7.3%
577
 
6.8%
538
 
6.3%
487
 
5.7%
486
 
5.7%
436
 
5.1%
436
 
5.1%
418
 
4.9%
356
 
4.2%
194
 
2.3%
Other values (212) 3939
46.4%

apvpermymd
Real number (ℝ)

Distinct145
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20112175
Minimum19451015
Maximum20210722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:09.158136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120050307
median20130412
Q320190702
95-th percentile20210401
Maximum20210722
Range759707
Interquartile range (IQR)140395

Descriptive statistics

Standard deviation89832.18
Coefficient of variation (CV)0.0044665571
Kurtosis8.566787
Mean20112175
Median Absolute Deviation (MAD)69587.5
Skewness-1.7326201
Sum8.8895815 × 109
Variance8.0698206 × 109
MonotonicityNot monotonic
2024-04-16T20:40:09.280554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.7%
20190315 12
 
2.7%
20140822 11
 
2.5%
20010609 11
 
2.5%
20210615 10
 
2.3%
20021112 10
 
2.3%
20090302 10
 
2.3%
20050307 10
 
2.3%
20071204 10
 
2.3%
20080527 9
 
2.0%
Other values (135) 337
76.2%
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 (%)
20210722 1
 
0.2%
20210709 2
 
0.5%
20210707 1
 
0.2%
20210630 1
 
0.2%
20210615 10
2.3%
20210608 1
 
0.2%
20210527 1
 
0.2%
20210521 2
 
0.5%
20210513 2
 
0.5%
20210512 1
 
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct31
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
319 
폐업일자
57 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (26)
40 

Length

Max length8
Median length4
Mean length4.5972851
Min length4

Unique

Unique21 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
72.2%
폐업일자 57
 
12.9%
20170315 10
 
2.3%
20160617 8
 
1.8%
20110616 8
 
1.8%
20100806 7
 
1.6%
20001201 4
 
0.9%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (21) 21
 
4.8%

Length

2024-04-16T20:40:09.403496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 319
72.2%
폐업일자 57
 
12.9%
20170315 10
 
2.3%
20160617 8
 
1.8%
20110616 8
 
1.8%
20100806 7
 
1.6%
20001201 4
 
0.9%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (21) 21
 
4.8%

clgstdt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
휴업시작일자
58 

Length

Max length6
Median length4
Mean length4.2624434
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> 384
86.9%
휴업시작일자 58
 
13.1%

Length

2024-04-16T20:40:09.517972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:09.606751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
휴업시작일자 58
 
13.1%

clgenddt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
휴업종료일자
58 

Length

Max length6
Median length4
Mean length4.2624434
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> 384
86.9%
휴업종료일자 58
 
13.1%

Length

2024-04-16T20:40:09.707829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:09.796996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
휴업종료일자 58
 
13.1%

ropnymd
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
재개업일자
58 

Length

Max length5
Median length4
Mean length4.1312217
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> 384
86.9%
재개업일자 58
 
13.1%

Length

2024-04-16T20:40:09.891827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:09.996685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
재개업일자 58
 
13.1%

trdstatenm
Categorical

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
영업/정상
257 
13
117 
03
56 
폐업
 
8
제외/삭제/전출
 
2
Other values (2)
 
2

Length

Max length8
Median length5
Mean length3.7760181
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 257
58.1%
13 117
26.5%
03 56
 
12.7%
폐업 8
 
1.8%
제외/삭제/전출 2
 
0.5%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:40:10.092123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:10.199775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 257
58.1%
13 117
26.5%
03 56
 
12.7%
폐업 8
 
1.8%
제외/삭제/전출 2
 
0.5%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
영업중
375 
폐업
64 
전출
 
2
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8529412
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 375
84.8%
폐업 64
 
14.5%
전출 2
 
0.5%
직권말소 1
 
0.2%

Length

2024-04-16T20:40:10.311275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:10.411206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 375
84.8%
폐업 64
 
14.5%
전출 2
 
0.5%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)26.6%
Missing6
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean389816.98
Minimum374253.11
Maximum401646.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:10.508533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum374253.11
5-th percentile380625.39
Q1385622.78
median389751.94
Q3393797.99
95-th percentile398310.24
Maximum401646.7
Range27393.591
Interquartile range (IQR)8175.2047

Descriptive statistics

Standard deviation5624.5257
Coefficient of variation (CV)0.014428632
Kurtosis-0.15914422
Mean389816.98
Median Absolute Deviation (MAD)4129.1569
Skewness-0.18704549
Sum1.699602 × 108
Variance31635289
MonotonicityNot monotonic
2024-04-16T20:40:10.619423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 20
 
4.5%
387982.190387 14
 
3.2%
388011.197829908 12
 
2.7%
385622.780457355 11
 
2.5%
387608.014165034 11
 
2.5%
387443.214568 11
 
2.5%
394153.800755 10
 
2.3%
393952.264486105 10
 
2.3%
396915.143441 10
 
2.3%
398310.243451 10
 
2.3%
Other values (106) 317
71.7%
ValueCountFrequency (%)
374253.112340712 7
1.6%
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.1%
379240.573215267 3
0.7%
379280.632039 2
 
0.5%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380625.391364589 6
1.4%
380780.612775 7
1.6%
ValueCountFrequency (%)
401646.70301259 3
 
0.7%
401504.790177 6
1.4%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398628.503470003 2
 
0.5%
398341.802637 7
1.6%
398310.243451 10
2.3%
398275.475596001 1
 
0.2%
398242.150343638 2
 
0.5%
398233.483190899 1
 
0.2%

y
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)26.6%
Missing6
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean187653.72
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:10.738639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178757.42
5-th percentile179597.59
Q1185310.71
median187480.44
Q3189911.43
95-th percentile195491.52
Maximum204621.66
Range25864.232
Interquartile range (IQR)4600.7252

Descriptive statistics

Standard deviation5423.1079
Coefficient of variation (CV)0.028899549
Kurtosis1.6025892
Mean187653.72
Median Absolute Deviation (MAD)2169.7385
Skewness0.85053555
Sum81817021
Variance29410099
MonotonicityNot monotonic
2024-04-16T20:40:10.867192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 20
 
4.5%
186465.864259 14
 
3.2%
185310.70532509 12
 
2.7%
179452.224754792 11
 
2.5%
185703.079007724 11
 
2.5%
186484.775084 11
 
2.5%
188019.100861 10
 
2.3%
187602.933160728 10
 
2.3%
187480.443811 10
 
2.3%
188031.67198 10
 
2.3%
Other values (106) 317
71.7%
ValueCountFrequency (%)
178757.423271048 7
1.6%
178872.461747926 1
 
0.2%
179411.189506548 1
 
0.2%
179452.224754792 11
2.5%
179597.592953541 6
1.4%
179823.23303496 4
 
0.9%
179885.813689 2
 
0.5%
179911.285409 5
1.1%
179919.437009 4
 
0.9%
179919.488084 8
1.8%
ValueCountFrequency (%)
204621.655738547 5
1.1%
204597.0 5
1.1%
204401.691446 6
1.4%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
1.8%
195029.489621392 1
 
0.2%
194992.355262 2
 
0.5%
194681.150958776 7
1.6%
194622.201131 7
1.6%

lastmodts
Real number (ℝ)

Distinct373
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0184703 × 1013
Minimum2.0030127 × 1013
Maximum2.0210722 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:10.999416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0180614 × 1013
median2.019092 × 1013
Q32.0210331 × 1013
95-th percentile2.0210615 × 1013
Maximum2.0210722 × 1013
Range1.80595 × 1011
Interquartile range (IQR)2.9716722 × 1010

Descriptive statistics

Standard deviation3.310651 × 1010
Coefficient of variation (CV)0.0016401782
Kurtosis6.2917206
Mean2.0184703 × 1013
Median Absolute Deviation (MAD)1.080297 × 1010
Skewness-2.3433552
Sum8.9216388 × 1015
Variance1.096041 × 1021
MonotonicityNot monotonic
2024-04-16T20:40:11.130966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210524175645 6
 
1.4%
20210421091411 5
 
1.1%
20190920121341 5
 
1.1%
20191017170859 4
 
0.9%
20030127161348 4
 
0.9%
20190322121903 3
 
0.7%
20200103203958 3
 
0.7%
20200320103703 3
 
0.7%
20200115103223 3
 
0.7%
20181026112015 3
 
0.7%
Other values (363) 403
91.2%
ValueCountFrequency (%)
20030127161348 4
0.9%
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 (%)
20210722164112 1
 
0.2%
20210719181444 1
 
0.2%
20210715175449 1
 
0.2%
20210709130952 2
0.5%
20210707112122 1
 
0.2%
20210630103741 1
 
0.2%
20210629143805 1
 
0.2%
20210621093401 1
 
0.2%
20210621093400 3
0.7%
20210621093217 1
 
0.2%

uptaenm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
업태구분명
58 

Length

Max length5
Median length4
Mean length4.1312217
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> 384
86.9%
업태구분명 58
 
13.1%

Length

2024-04-16T20:40:11.253256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:11.340444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
업태구분명 58
 
13.1%

sitetel
Categorical

IMBALANCE 

Distinct22
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
051-123-1234
301 
<NA>
45 
전화번호
 
26
910-1411
 
12
051-366-2200
 
9
Other values (17)
49 

Length

Max length13
Median length12
Mean length10.529412
Min length4

Unique

Unique9 ?
Unique (%)2.0%

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 301
68.1%
<NA> 45
 
10.2%
전화번호 26
 
5.9%
910-1411 12
 
2.7%
051-366-2200 9
 
2.0%
051-745-2883 8
 
1.8%
364-0480 7
 
1.6%
070-4159-8881 7
 
1.6%
051-626-0488 6
 
1.4%
051-507-5282 4
 
0.9%
Other values (12) 17
 
3.8%

Length

2024-04-16T20:40:11.433980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 301
68.1%
na 45
 
10.2%
전화번호 26
 
5.9%
910-1411 12
 
2.7%
051-366-2200 9
 
2.0%
051-745-2883 8
 
1.8%
364-0480 7
 
1.6%
070-4159-8881 7
 
1.6%
051-626-0488 6
 
1.4%
051-507-5282 4
 
0.9%
Other values (12) 17
 
3.8%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
279 
문화시설
82 
건물용도명
52 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.1470588
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> 279
63.1%
문화시설 82
 
18.6%
건물용도명 52
 
11.8%
근린생활시설 13
 
2.9%
유통시설 9
 
2.0%
호텔 6
 
1.4%
사무실 1
 
0.2%

Length

2024-04-16T20:40:11.556265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:11.660255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 279
63.1%
문화시설 82
 
18.6%
건물용도명 52
 
11.8%
근린생활시설 13
 
2.9%
유통시설 9
 
2.0%
호텔 6
 
1.4%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
영화관
282 
<NA>
109 
공연장형태구분명
47 
자동차극장
 
4

Length

Max length8
Median length3
Mean length3.7963801
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 282
63.8%
<NA> 109
 
24.7%
공연장형태구분명 47
 
10.6%
자동차극장 4
 
0.9%

Length

2024-04-16T20:40:11.768357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:11.854021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 282
63.8%
na 109
 
24.7%
공연장형태구분명 47
 
10.6%
자동차극장 4
 
0.9%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
기존게임업외업종명
58 

Length

Max length9
Median length4
Mean length4.6561086
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> 384
86.9%
기존게임업외업종명 58
 
13.1%

Length

2024-04-16T20:40:11.948415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:12.029965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
기존게임업외업종명 58
 
13.1%

noroomcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
382 
노래방실수
56 
0
 
4

Length

Max length5
Median length4
Mean length4.0995475
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> 382
86.4%
노래방실수 56
 
12.7%
0 4
 
0.9%

Length

2024-04-16T20:40:12.123165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:12.216694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 382
86.4%
노래방실수 56
 
12.7%
0 4
 
0.9%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
영화상영관
196 
<NA>
190 
문화사업자구분명
56 

Length

Max length8
Median length5
Mean length4.9502262
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
44.3%
<NA> 190
43.0%
문화사업자구분명 56
 
12.7%

Length

2024-04-16T20:40:12.345696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:12.691140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 196
44.3%
na 190
43.0%
문화사업자구분명 56
 
12.7%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
영화상영관
290 
영화제작업
94 
영화배급업
 
29
영화상영업
 
21
영화수입업
 
8

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 290
65.6%
영화제작업 94
 
21.3%
영화배급업 29
 
6.6%
영화상영업 21
 
4.8%
영화수입업 8
 
1.8%

Length

2024-04-16T20:40:12.773814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:12.858781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 290
65.6%
영화제작업 94
 
21.3%
영화배급업 29
 
6.6%
영화상영업 21
 
4.8%
영화수입업 8
 
1.8%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:12.955354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:13.052498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

vdoretornm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
비디오재생기명
58 

Length

Max length7
Median length4
Mean length4.3936652
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> 384
86.9%
비디오재생기명 58
 
13.1%

Length

2024-04-16T20:40:13.161549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:13.256916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
비디오재생기명 58
 
13.1%

emerstairyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:13.356835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:13.468921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

emexyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:13.576789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:13.660898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

firefacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:13.768330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:13.872118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
376 
시설면적
56 
1578.8
 
4
0
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.9977376
Min length1

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> 376
85.1%
시설면적 56
 
12.7%
1578.8 4
 
0.9%
0 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:40:13.981772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:14.081090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
85.1%
시설면적 56
 
12.7%
1578.8 4
 
0.9%
0 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:14.186599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:14.274046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

autochaairyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:14.368249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:14.456187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
제공게임물명
58 

Length

Max length6
Median length4
Mean length4.2624434
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> 384
86.9%
제공게임물명 58
 
13.1%

Length

2024-04-16T20:40:14.557968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:14.667214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
제공게임물명 58
 
13.1%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
제작취급품목내용
58 

Length

Max length8
Median length4
Mean length4.5248869
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> 384
86.9%
제작취급품목내용 58
 
13.1%

Length

2024-04-16T20:40:14.765979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:14.855642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
제작취급품목내용 58
 
13.1%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:14.949394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:15.031802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

lghtfacilinillu
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
382 
조명시설조도
56 
0
 
4

Length

Max length6
Median length4
Mean length4.2262443
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> 382
86.4%
조명시설조도 56
 
12.7%
0 4
 
0.9%

Length

2024-04-16T20:40:15.131936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:15.216082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 382
86.4%
조명시설조도 56
 
12.7%
0 4
 
0.9%

nearenvnm
Categorical

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
326 
주변환경명
55 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.1809955
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> 326
73.8%
주변환경명 55
 
12.4%
기타 32
 
7.2%
유흥업소밀집지역 18
 
4.1%
아파트지역 9
 
2.0%
학교정화(상대) 2
 
0.5%

Length

2024-04-16T20:40:15.315412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:15.427591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 326
73.8%
주변환경명 55
 
12.4%
기타 32
 
7.2%
유흥업소밀집지역 18
 
4.1%
아파트지역 9
 
2.0%
학교정화(상대 2
 
0.5%

jisgnumlay
Categorical

Distinct23
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
156 
지상층수
47 
10
37 
7
28 
9
27 
Other values (18)
147 

Length

Max length4
Median length2
Mean length2.6447964
Min length1

Unique

Unique4 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 156
35.3%
지상층수 47
 
10.6%
10 37
 
8.4%
7 28
 
6.3%
9 27
 
6.1%
5 20
 
4.5%
8 19
 
4.3%
42 17
 
3.8%
12 15
 
3.4%
6 12
 
2.7%
Other values (13) 64
14.5%

Length

2024-04-16T20:40:15.532495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 156
35.3%
지상층수 47
 
10.6%
10 37
 
8.4%
7 28
 
6.3%
9 27
 
6.1%
5 20
 
4.5%
8 19
 
4.3%
42 17
 
3.8%
12 15
 
3.4%
6 12
 
2.7%
Other values (13) 64
14.5%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
312 
지역구분명
55 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3506787
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 312
70.6%
지역구분명 55
 
12.4%
일반상업지역 30
 
6.8%
상업지역 16
 
3.6%
중심상업지역 12
 
2.7%
녹지지역 8
 
1.8%
일반주거지역 4
 
0.9%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:40:15.651148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:15.772194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 312
70.6%
지역구분명 55
 
12.4%
일반상업지역 30
 
6.8%
상업지역 16
 
3.6%
중심상업지역 12
 
2.7%
녹지지역 8
 
1.8%
일반주거지역 4
 
0.9%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct12
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
163 
5
59 
지하층수
49 
2
47 
1
35 
Other values (7)
89 

Length

Max length4
Median length1
Mean length2.4434389
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 163
36.9%
5 59
 
13.3%
지하층수 49
 
11.1%
2 47
 
10.6%
1 35
 
7.9%
3 24
 
5.4%
4 21
 
4.8%
6 20
 
4.5%
8 18
 
4.1%
0 4
 
0.9%
Other values (2) 2
 
0.5%

Length

2024-04-16T20:40:15.899204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 163
36.9%
5 59
 
13.3%
지하층수 49
 
11.1%
2 47
 
10.6%
1 35
 
7.9%
3 24
 
5.4%
4 21
 
4.8%
6 20
 
4.5%
8 18
 
4.1%
0 4
 
0.9%
Other values (2) 2
 
0.5%

bgroomcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
382 
청소년실수
56 
0
 
4

Length

Max length5
Median length4
Mean length4.0995475
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> 382
86.4%
청소년실수 56
 
12.7%
0 4
 
0.9%

Length

2024-04-16T20:40:16.008384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:16.102046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 382
86.4%
청소년실수 56
 
12.7%
0 4
 
0.9%

bgroomyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:16.192240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:16.278978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

totgasyscnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
382 
총게임기수
56 
0
 
4

Length

Max length5
Median length4
Mean length4.0995475
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> 382
86.4%
총게임기수 56
 
12.7%
0 4
 
0.9%

Length

2024-04-16T20:40:16.380151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:16.479419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 382
86.4%
총게임기수 56
 
12.7%
0 4
 
0.9%

totnumlay
Categorical

Distinct20
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
242 
총층수
50 
10
 
20
9
 
12
11
 
12
Other values (15)
106 

Length

Max length4
Median length4
Mean length3.1244344
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> 242
54.8%
총층수 50
 
11.3%
10 20
 
4.5%
9 12
 
2.7%
11 12
 
2.7%
6 12
 
2.7%
18 11
 
2.5%
19 10
 
2.3%
54 9
 
2.0%
15 9
 
2.0%
Other values (10) 55
 
12.4%

Length

2024-04-16T20:40:16.583312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 242
54.8%
총층수 50
 
11.3%
10 20
 
4.5%
9 12
 
2.7%
11 12
 
2.7%
6 12
 
2.7%
18 11
 
2.5%
19 10
 
2.3%
54 9
 
2.0%
15 9
 
2.0%
Other values (10) 55
 
12.4%

frstregts
Real number (ℝ)

Distinct145
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20112175
Minimum19451015
Maximum20210722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-16T20:40:16.688733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120050307
median20130412
Q320190702
95-th percentile20210401
Maximum20210722
Range759707
Interquartile range (IQR)140395

Descriptive statistics

Standard deviation89832.18
Coefficient of variation (CV)0.0044665571
Kurtosis8.566787
Mean20112175
Median Absolute Deviation (MAD)69587.5
Skewness-1.7326201
Sum8.8895815 × 109
Variance8.0698206 × 109
MonotonicityNot monotonic
2024-04-16T20:40:16.807246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.7%
20190315 12
 
2.7%
20140822 11
 
2.5%
20010609 11
 
2.5%
20210615 10
 
2.3%
20021112 10
 
2.3%
20090302 10
 
2.3%
20050307 10
 
2.3%
20071204 10
 
2.3%
20080527 9
 
2.0%
Other values (135) 337
76.2%
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 (%)
20210722 1
 
0.2%
20210709 2
 
0.5%
20210707 1
 
0.2%
20210630 1
 
0.2%
20210615 10
2.3%
20210608 1
 
0.2%
20210527 1
 
0.2%
20210521 2
 
0.5%
20210513 2
 
0.5%
20210512 1
 
0.2%

pasgbreth
Categorical

IMBALANCE 

Distinct19
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
240 
1
103 
통로너비
50 
1.5
 
12
1.2
 
7
Other values (14)
30 

Length

Max length4
Median length4
Mean length3.2104072
Min length1

Unique

Unique8 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
54.3%
1 103
23.3%
통로너비 50
 
11.3%
1.5 12
 
2.7%
1.2 7
 
1.6%
1.45 5
 
1.1%
1.15 4
 
0.9%
0 4
 
0.9%
1.3 4
 
0.9%
1.7 3
 
0.7%
Other values (9) 10
 
2.3%

Length

2024-04-16T20:40:16.952866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 240
54.3%
1 103
23.3%
통로너비 50
 
11.3%
1.5 12
 
2.7%
1.2 7
 
1.6%
1.45 5
 
1.1%
1.15 4
 
0.9%
0 4
 
0.9%
1.3 4
 
0.9%
1.7 3
 
0.7%
Other values (9) 10
 
2.3%

speclghtyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:17.066238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:17.162528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
58 

Length

Max length4
Median length4
Mean length3.6063348
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> 384
86.9%
58
 
13.1%

Length

2024-04-16T20:40:17.257749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:17.341959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
58
 
13.1%

actlnm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
384 
품목명
58 

Length

Max length4
Median length4
Mean length3.8687783
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> 384
86.9%
품목명 58
 
13.1%

Length

2024-04-16T20:40:17.427529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:17.519271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 384
86.9%
품목명 58
 
13.1%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2021-08-01 05:20:03
442 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-01 05:20:03
2nd row2021-08-01 05:20:03
3rd row2021-08-01 05:20:03
4th row2021-08-01 05:20:03
5th row2021-08-01 05:20:03

Common Values

ValueCountFrequency (%)
2021-08-01 05:20:03 442
100.0%

Length

2024-04-16T20:40:17.606681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:17.686319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-01 442
50.0%
05:20:03 442
50.0%

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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 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>2021-08-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
43230163400000CDFF521101202100000103_13_05_PI2021-03-31 00:22:59.0영화제작업필름상가509호지번우편번호부산광역시 기장군 기장읍 대라리 1000 월가 아델리스 아파트 304호46067부산광역시 기장군 기장읍 차성남로 23, 304호 (월가 아델리스 아파트)20210329폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2021-08-01 05:20:03
43330173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2021-08-01 05:20:03
43430183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2021-08-01 05:20:03
43530193360000CDFF521104202100000103_13_03_PU2021-06-13 02:40:00.0영화상영업롯데시네마 부산 명지점지번우편번호부산광역시 강서구 명지동 3432-346726부산광역시 강서구 명지국제6로 107, 부산명지 대방디엠시티 센텀오션 2차 2층 (명지동)20210512폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2021-08-01 05:20:03
43630203330000CDFF521103202100000303_13_01_PI2021-05-15 00:22:56.0영화배급업주식회사 엠앤미디어지번우편번호부산광역시 해운대구 우동 1466-1 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩48058부산광역시 해운대구 수영강변대로 140, 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩 (우동)20210513폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2021-08-01 05:20:03
43730213330000CDFF521101202100000503_13_05_PI2021-05-15 00:22:56.0영화제작업주식회사 엠앤미디어<NA>부산광역시 해운대구 우동 1466-1 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩48058부산광역시 해운대구 수영강변대로 140, 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩 (우동)20210513<NA><NA><NA><NA>영업/정상영업중393573.517297188018.68713820210513125158<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>20210513<NA><NA><NA><NA>2021-08-01 05:20:03
43830223250000CDFF521102202100000103_13_04_PI2021-05-15 00:22:56.0영화수입업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513163139<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>20161013<NA><NA><NA><NA>2021-08-01 05:20:03
43930233250000CDFF521103202100000103_13_01_PI2021-05-15 00:22:56.0영화배급업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513163400<NA><NA><NA><NA><NA><NA><NA>영화배급업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20161013<NA><NA><NA><NA>2021-08-01 05:20:03
44030243250000CDFF521101202100000203_13_05_PI2021-05-15 00:22:56.0영화제작업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513162803<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>20161013<NA><NA><NA><NA>2021-08-01 05:20:03
44130253290000CDFF521104202100000103_13_03_PI2021-05-23 00:22:56.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210521093521업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2021-08-01 05:20:03