Overview

Dataset statistics

Number of variables56
Number of observations451
Missing cells33
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory200.5 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 (73.4%)Imbalance
dcbymd is highly imbalanced (62.7%)Imbalance
dtlstatenm is highly imbalanced (63.8%)Imbalance
sitetel is highly imbalanced (53.2%)Imbalance
facilar is highly imbalanced (63.1%)Imbalance
regnsenm is highly imbalanced (51.9%)Imbalance
rdnpostno has 15 (3.3%) missing valuesMissing
rdnwhladdr has 6 (1.3%) missing valuesMissing
x has 6 (1.3%) missing valuesMissing
y has 6 (1.3%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:39:02.235707
Analysis finished2024-04-16 11:39:03.043105
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean839.37916
Minimum1
Maximum3058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:03.098093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.5
Q1113.5
median226
Q31524
95-th percentile3035.5
Maximum3058
Range3057
Interquartile range (IQR)1410.5

Descriptive statistics

Standard deviation1043.9101
Coefficient of variation (CV)1.2436693
Kurtosis-0.2094631
Mean839.37916
Median Absolute Deviation (MAD)175
Skewness1.1556513
Sum378560
Variance1089748.3
MonotonicityNot monotonic
2024-04-16T20:39:03.205055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
556 1
 
0.2%
838 1
 
0.2%
833 1
 
0.2%
830 1
 
0.2%
810 1
 
0.2%
809 1
 
0.2%
808 1
 
0.2%
806 1
 
0.2%
804 1
 
0.2%
Other values (441) 441
97.8%
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 (%)
3058 1
0.2%
3057 1
0.2%
3056 1
0.2%
3055 1
0.2%
3054 1
0.2%
3053 1
0.2%
3052 1
0.2%
3051 1
0.2%
3050 1
0.2%
3049 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3319401.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:03.302461image/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 deviation41191.649
Coefficient of variation (CV)0.012409361
Kurtosis-0.4791849
Mean3319401.3
Median Absolute Deviation (MAD)30000
Skewness0.10885367
Sum1.49705 × 109
Variance1.6967519 × 109
MonotonicityNot monotonic
2024-04-16T20:39:03.613477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 122
27.1%
3290000 78
17.3%
3250000 56
12.4%
3300000 29
 
6.4%
3350000 26
 
5.8%
3400000 26
 
5.8%
3320000 22
 
4.9%
3310000 20
 
4.4%
3380000 18
 
4.0%
3390000 15
 
3.3%
Other values (5) 39
 
8.6%
ValueCountFrequency (%)
3250000 56
12.4%
3260000 2
 
0.4%
3270000 7
 
1.6%
3290000 78
17.3%
3300000 29
 
6.4%
3310000 20
 
4.4%
3320000 22
 
4.9%
3330000 122
27.1%
3340000 13
 
2.9%
3350000 26
 
5.8%
ValueCountFrequency (%)
3400000 26
 
5.8%
3390000 15
 
3.3%
3380000 18
 
4.0%
3370000 9
 
2.0%
3360000 8
 
1.8%
3350000 26
 
5.8%
3340000 13
 
2.9%
3330000 122
27.1%
3320000 22
 
4.9%
3310000 20
 
4.4%

mgtno
Text

Distinct242
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-04-16T20:39:03.813213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters9020
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

Unique147 ?
Unique (%)32.6%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
4.0%
cdff5211012019000001 12
 
2.7%
cdff5211012021000001 11
 
2.4%
cdff5211012020000002 9
 
2.0%
cdff5211032020000001 8
 
1.8%
cdff5211042021000001 8
 
1.8%
cdff5211032019000001 8
 
1.8%
cdff5211042019000001 6
 
1.3%
cdff5211012021000002 5
 
1.1%
cdff5211032021000001 5
 
1.1%
Other values (232) 361
80.0%
2024-04-16T20:39:04.126246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3956
43.9%
2 1375
 
15.2%
F 902
 
10.0%
1 856
 
9.5%
C 451
 
5.0%
D 451
 
5.0%
4 380
 
4.2%
5 225
 
2.5%
9 132
 
1.5%
3 87
 
1.0%
Other values (3) 205
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7216
80.0%
Uppercase Letter 1804
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3956
54.8%
2 1375
 
19.1%
1 856
 
11.9%
4 380
 
5.3%
5 225
 
3.1%
9 132
 
1.8%
3 87
 
1.2%
7 84
 
1.2%
6 63
 
0.9%
8 58
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
F 902
50.0%
C 451
25.0%
D 451
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7216
80.0%
Latin 1804
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3956
54.8%
2 1375
 
19.1%
1 856
 
11.9%
4 380
 
5.3%
5 225
 
3.1%
9 132
 
1.8%
3 87
 
1.2%
7 84
 
1.2%
6 63
 
0.9%
8 58
 
0.8%
Latin
ValueCountFrequency (%)
F 902
50.0%
C 451
25.0%
D 451
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3956
43.9%
2 1375
 
15.2%
F 902
 
10.0%
1 856
 
9.5%
C 451
 
5.0%
D 451
 
5.0%
4 380
 
4.2%
5 225
 
2.5%
9 132
 
1.5%
3 87
 
1.0%
Other values (3) 205
 
2.3%

opnsvcid
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
03_13_02_P
290 
03_13_05_P
101 
03_13_01_P
30 
03_13_03_P
 
22
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
64.3%
03_13_05_P 101
 
22.4%
03_13_01_P 30
 
6.7%
03_13_03_P 22
 
4.9%
03_13_04_P 8
 
1.8%

Length

2024-04-16T20:39:04.239575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:04.318717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 290
64.3%
03_13_05_p 101
 
22.4%
03_13_01_p 30
 
6.7%
03_13_03_p 22
 
4.9%
03_13_04_p 8
 
1.8%

updategbn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
I
295 
U
156 

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 295
65.4%
U 156
34.6%

Length

2024-04-16T20:39:04.407383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:04.482102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 295
65.4%
u 156
34.6%
Distinct109
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-11-18 00:22:44
2024-04-16T20:39:04.569639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:39:04.688430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
171 
영화상영관
119 
영화제작업
101 
영화배급업
30 
영화상영업
22 

Length

Max length5
Median length5
Mean length4.6208426
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 171
37.9%
영화상영관 119
26.4%
영화제작업 101
22.4%
영화배급업 30
 
6.7%
영화상영업 22
 
4.9%
영화수입업 8
 
1.8%

Length

2024-04-16T20:39:04.792972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:04.890450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 171
37.9%
영화상영관 119
26.4%
영화제작업 101
22.4%
영화배급업 30
 
6.7%
영화상영업 22
 
4.9%
영화수입업 8
 
1.8%

bplcnm
Text

Distinct377
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-04-16T20:39:05.089172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length10.904656
Min length2

Characters and Unicode

Total characters4918
Distinct characters255
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

Unique342 ?
Unique (%)75.8%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 92
 
9.3%
메가박스 48
 
4.8%
cgv 41
 
4.1%
주식회사 36
 
3.6%
해운대 26
 
2.6%
서면 20
 
2.0%
센텀시티 19
 
1.9%
정관 15
 
1.5%
6관 15
 
1.5%
제3관 15
 
1.5%
Other values (237) 666
67.1%
2024-04-16T20:39:05.393525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
544
 
11.1%
317
 
6.4%
164
 
3.3%
148
 
3.0%
144
 
2.9%
131
 
2.7%
116
 
2.4%
108
 
2.2%
107
 
2.2%
C 105
 
2.1%
Other values (245) 3034
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3452
70.2%
Space Separator 544
 
11.1%
Uppercase Letter 422
 
8.6%
Decimal Number 273
 
5.6%
Open Punctuation 97
 
2.0%
Close Punctuation 97
 
2.0%
Lowercase Letter 20
 
0.4%
Other Punctuation 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
317
 
9.2%
164
 
4.8%
148
 
4.3%
144
 
4.2%
131
 
3.8%
116
 
3.4%
108
 
3.1%
107
 
3.1%
99
 
2.9%
80
 
2.3%
Other values (198) 2038
59.0%
Uppercase Letter
ValueCountFrequency (%)
C 105
24.9%
G 83
19.7%
V 82
19.4%
N 24
 
5.7%
E 14
 
3.3%
O 12
 
2.8%
I 11
 
2.6%
A 10
 
2.4%
M 10
 
2.4%
U 10
 
2.4%
Other values (12) 61
14.5%
Decimal Number
ValueCountFrequency (%)
1 44
16.1%
2 38
13.9%
4 36
13.2%
3 32
11.7%
6 31
11.4%
5 30
11.0%
7 25
9.2%
8 16
 
5.9%
9 15
 
5.5%
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%
Open Punctuation
ValueCountFrequency (%)
( 96
99.0%
[ 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 96
99.0%
] 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
544
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3452
70.2%
Common 1024
 
20.8%
Latin 442
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
317
 
9.2%
164
 
4.8%
148
 
4.3%
144
 
4.2%
131
 
3.8%
116
 
3.4%
108
 
3.1%
107
 
3.1%
99
 
2.9%
80
 
2.3%
Other values (198) 2038
59.0%
Latin
ValueCountFrequency (%)
C 105
23.8%
G 83
18.8%
V 82
18.6%
N 24
 
5.4%
E 14
 
3.2%
O 12
 
2.7%
I 11
 
2.5%
A 10
 
2.3%
M 10
 
2.3%
U 10
 
2.3%
Other values (19) 81
18.3%
Common
ValueCountFrequency (%)
544
53.1%
( 96
 
9.4%
) 96
 
9.4%
1 44
 
4.3%
2 38
 
3.7%
4 36
 
3.5%
3 32
 
3.1%
6 31
 
3.0%
5 30
 
2.9%
7 25
 
2.4%
Other values (8) 52
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3452
70.2%
ASCII 1466
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
544
37.1%
C 105
 
7.2%
( 96
 
6.5%
) 96
 
6.5%
G 83
 
5.7%
V 82
 
5.6%
1 44
 
3.0%
2 38
 
2.6%
4 36
 
2.5%
3 32
 
2.2%
Other values (37) 310
21.1%
Hangul
ValueCountFrequency (%)
317
 
9.2%
164
 
4.8%
148
 
4.3%
144
 
4.2%
131
 
3.8%
116
 
3.4%
108
 
3.1%
107
 
3.1%
99
 
2.9%
80
 
2.3%
Other values (198) 2038
59.0%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
359 
지번우편번호
70 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.4079823
Min length4

Unique

Unique10 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 359
79.6%
지번우편번호 70
 
15.5%
614845 4
 
0.9%
600805 3
 
0.7%
601060 3
 
0.7%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.3%

Length

2024-04-16T20:39:05.517589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 359
79.6%
지번우편번호 70
 
15.5%
614845 4
 
0.9%
600805 3
 
0.7%
601060 3
 
0.7%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.3%
Distinct149
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-04-16T20:39:05.753133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length26.922395
Min length18

Characters and Unicode

Total characters12142
Distinct characters245
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

Unique73 ?
Unique (%)16.2%

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 451
 
20.2%
해운대구 122
 
5.5%
우동 92
 
4.1%
부산진구 78
 
3.5%
중구 56
 
2.5%
부전동 47
 
2.1%
동래구 29
 
1.3%
전포동 27
 
1.2%
금정구 26
 
1.2%
기장군 26
 
1.2%
Other values (325) 1284
57.4%
2024-04-16T20:39:06.098275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2194
 
18.1%
621
 
5.1%
581
 
4.8%
490
 
4.0%
487
 
4.0%
1 474
 
3.9%
455
 
3.7%
451
 
3.7%
426
 
3.5%
- 379
 
3.1%
Other values (235) 5584
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7095
58.4%
Space Separator 2194
 
18.1%
Decimal Number 2175
 
17.9%
Dash Punctuation 379
 
3.1%
Uppercase Letter 132
 
1.1%
Other Punctuation 122
 
1.0%
Lowercase Letter 15
 
0.1%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
621
 
8.8%
581
 
8.2%
490
 
6.9%
487
 
6.9%
455
 
6.4%
451
 
6.4%
426
 
6.0%
297
 
4.2%
275
 
3.9%
163
 
2.3%
Other values (199) 2849
40.2%
Uppercase Letter
ValueCountFrequency (%)
K 29
22.0%
S 19
14.4%
T 15
11.4%
B 11
 
8.3%
H 10
 
7.6%
C 10
 
7.6%
G 10
 
7.6%
U 10
 
7.6%
Y 9
 
6.8%
N 8
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 474
21.8%
2 314
14.4%
6 224
10.3%
5 219
10.1%
4 199
9.1%
0 180
 
8.3%
8 159
 
7.3%
7 155
 
7.1%
3 136
 
6.3%
9 115
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
o 3
20.0%
r 2
 
13.3%
h 2
 
13.3%
l 1
 
6.7%
v 1
 
6.7%
i 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 95
77.9%
, 18
 
14.8%
& 9
 
7.4%
Space Separator
ValueCountFrequency (%)
2194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 379
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7095
58.4%
Common 4900
40.4%
Latin 147
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
621
 
8.8%
581
 
8.2%
490
 
6.9%
487
 
6.9%
455
 
6.4%
451
 
6.4%
426
 
6.0%
297
 
4.2%
275
 
3.9%
163
 
2.3%
Other values (199) 2849
40.2%
Common
ValueCountFrequency (%)
2194
44.8%
1 474
 
9.7%
- 379
 
7.7%
2 314
 
6.4%
6 224
 
4.6%
5 219
 
4.5%
4 199
 
4.1%
0 180
 
3.7%
8 159
 
3.2%
7 155
 
3.2%
Other values (8) 403
 
8.2%
Latin
ValueCountFrequency (%)
K 29
19.7%
S 19
12.9%
T 15
10.2%
B 11
 
7.5%
H 10
 
6.8%
C 10
 
6.8%
G 10
 
6.8%
U 10
 
6.8%
Y 9
 
6.1%
N 8
 
5.4%
Other values (8) 16
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7095
58.4%
ASCII 5047
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2194
43.5%
1 474
 
9.4%
- 379
 
7.5%
2 314
 
6.2%
6 224
 
4.4%
5 219
 
4.3%
4 199
 
3.9%
0 180
 
3.6%
8 159
 
3.2%
7 155
 
3.1%
Other values (26) 550
 
10.9%
Hangul
ValueCountFrequency (%)
621
 
8.8%
581
 
8.2%
490
 
6.9%
487
 
6.9%
455
 
6.4%
451
 
6.4%
426
 
6.0%
297
 
4.2%
275
 
3.9%
163
 
2.3%
Other values (199) 2849
40.2%

rdnpostno
Text

MISSING 

Distinct86
Distinct (%)19.7%
Missing15
Missing (%)3.3%
Memory size3.7 KiB
2024-04-16T20:39:06.315317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0045872
Min length5

Characters and Unicode

Total characters2182
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

Unique38 ?
Unique (%)8.7%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 60
 
13.8%
48058 45
 
10.3%
48953 20
 
4.6%
47296 16
 
3.7%
48059 14
 
3.2%
47299 12
 
2.8%
47285 11
 
2.5%
48944 11
 
2.5%
46015 10
 
2.3%
48948 10
 
2.3%
Other values (76) 227
52.1%
2024-04-16T20:39:06.634680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 580
26.6%
8 371
17.0%
9 242
11.1%
7 233
10.7%
5 161
 
7.4%
0 151
 
6.9%
2 142
 
6.5%
6 131
 
6.0%
1 88
 
4.0%
3 76
 
3.5%
Other values (7) 7
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2175
99.7%
Other Letter 7
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 580
26.7%
8 371
17.1%
9 242
11.1%
7 233
10.7%
5 161
 
7.4%
0 151
 
6.9%
2 142
 
6.5%
6 131
 
6.0%
1 88
 
4.0%
3 76
 
3.5%
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 2175
99.7%
Hangul 7
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 580
26.7%
8 371
17.1%
9 242
11.1%
7 233
10.7%
5 161
 
7.4%
0 151
 
6.9%
2 142
 
6.5%
6 131
 
6.0%
1 88
 
4.0%
3 76
 
3.5%
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 2175
99.7%
Hangul 7
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 580
26.7%
8 371
17.1%
9 242
11.1%
7 233
10.7%
5 161
 
7.4%
0 151
 
6.9%
2 142
 
6.5%
6 131
 
6.0%
1 88
 
4.0%
3 76
 
3.5%
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 

Distinct151
Distinct (%)33.9%
Missing6
Missing (%)1.3%
Memory size3.7 KiB
2024-04-16T20:39:06.886699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length32.853933
Min length22

Characters and Unicode

Total characters14620
Distinct characters277
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

Unique77 ?
Unique (%)17.3%

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 445
 
15.7%
해운대구 122
 
4.3%
우동 82
 
2.9%
부산진구 78
 
2.8%
중구 53
 
1.9%
중앙대로 52
 
1.8%
부전동 47
 
1.7%
해운대로 44
 
1.6%
6층 35
 
1.2%
39 34
 
1.2%
Other values (413) 1836
64.9%
2024-04-16T20:39:07.299417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2408
 
16.5%
634
 
4.3%
588
 
4.0%
554
 
3.8%
496
 
3.4%
495
 
3.4%
445
 
3.0%
444
 
3.0%
) 435
 
3.0%
( 435
 
3.0%
Other values (267) 7686
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8705
59.5%
Space Separator 2408
 
16.5%
Decimal Number 1923
 
13.2%
Other Punctuation 528
 
3.6%
Close Punctuation 438
 
3.0%
Open Punctuation 438
 
3.0%
Uppercase Letter 137
 
0.9%
Dash Punctuation 21
 
0.1%
Lowercase Letter 16
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
634
 
7.3%
588
 
6.8%
554
 
6.4%
496
 
5.7%
495
 
5.7%
445
 
5.1%
444
 
5.1%
427
 
4.9%
366
 
4.2%
192
 
2.2%
Other values (226) 4064
46.7%
Uppercase Letter
ValueCountFrequency (%)
K 29
21.2%
S 19
13.9%
T 15
10.9%
B 12
8.8%
C 10
 
7.3%
H 10
 
7.3%
U 10
 
7.3%
Y 9
 
6.6%
G 9
 
6.6%
N 7
 
5.1%
Other values (3) 7
 
5.1%
Decimal Number
ValueCountFrequency (%)
1 367
19.1%
2 268
13.9%
0 217
11.3%
3 208
10.8%
6 172
8.9%
5 163
8.5%
7 158
8.2%
4 151
7.9%
9 122
 
6.3%
8 97
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
h 2
 
12.5%
r 2
 
12.5%
p 1
 
6.2%
v 1
 
6.2%
i 1
 
6.2%
l 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 384
72.7%
* 135
 
25.6%
& 9
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 435
99.3%
] 3
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 435
99.3%
[ 3
 
0.7%
Space Separator
ValueCountFrequency (%)
2408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8705
59.5%
Common 5762
39.4%
Latin 153
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
634
 
7.3%
588
 
6.8%
554
 
6.4%
496
 
5.7%
495
 
5.7%
445
 
5.1%
444
 
5.1%
427
 
4.9%
366
 
4.2%
192
 
2.2%
Other values (226) 4064
46.7%
Latin
ValueCountFrequency (%)
K 29
19.0%
S 19
12.4%
T 15
9.8%
B 12
7.8%
C 10
 
6.5%
H 10
 
6.5%
U 10
 
6.5%
Y 9
 
5.9%
G 9
 
5.9%
N 7
 
4.6%
Other values (11) 23
15.0%
Common
ValueCountFrequency (%)
2408
41.8%
) 435
 
7.5%
( 435
 
7.5%
, 384
 
6.7%
1 367
 
6.4%
2 268
 
4.7%
0 217
 
3.8%
3 208
 
3.6%
6 172
 
3.0%
5 163
 
2.8%
Other values (10) 705
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8705
59.5%
ASCII 5915
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2408
40.7%
) 435
 
7.4%
( 435
 
7.4%
, 384
 
6.5%
1 367
 
6.2%
2 268
 
4.5%
0 217
 
3.7%
3 208
 
3.5%
6 172
 
2.9%
5 163
 
2.8%
Other values (31) 858
 
14.5%
Hangul
ValueCountFrequency (%)
634
 
7.3%
588
 
6.8%
554
 
6.4%
496
 
5.7%
495
 
5.7%
445
 
5.1%
444
 
5.1%
427
 
4.9%
366
 
4.2%
192
 
2.2%
Other values (226) 4064
46.7%

apvpermymd
Real number (ℝ)

Distinct151
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20114056
Minimum19451015
Maximum20211116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:07.423864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120050307
median20130507
Q320190702
95-th percentile20210568
Maximum20211116
Range760101
Interquartile range (IQR)140395

Descriptive statistics

Standard deviation89910.864
Coefficient of variation (CV)0.0044700513
Kurtosis8.4618567
Mean20114056
Median Absolute Deviation (MAD)69596
Skewness-1.7327296
Sum9.0714394 × 109
Variance8.0839634 × 109
MonotonicityNot monotonic
2024-04-16T20:39:07.548799image/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
 
2.4%
20010609 11
 
2.4%
20090302 10
 
2.2%
20021112 10
 
2.2%
20210615 10
 
2.2%
20050307 10
 
2.2%
20071204 10
 
2.2%
20200103 9
 
2.0%
Other values (141) 346
76.7%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.4%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20211116 1
0.2%
20211115 1
0.2%
20211101 1
0.2%
20210826 1
0.2%
20210806 2
0.4%
20210802 1
0.2%
20210722 1
0.2%
20210709 2
0.4%
20210707 1
0.2%
20210630 1
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct33
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
313 
폐업일자
67 
20170315
 
10
20110616
 
8
20160617
 
8
Other values (28)
45 

Length

Max length8
Median length4
Mean length4.6297118
Min length4

Unique

Unique21 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 313
69.4%
폐업일자 67
 
14.9%
20170315 10
 
2.2%
20110616 8
 
1.8%
20160617 8
 
1.8%
20100806 7
 
1.6%
20001201 4
 
0.9%
20210806 3
 
0.7%
20200921 3
 
0.7%
20070725 3
 
0.7%
Other values (23) 25
 
5.5%

Length

2024-04-16T20:39:07.696820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 313
69.4%
폐업일자 67
 
14.9%
20170315 10
 
2.2%
20110616 8
 
1.8%
20160617 8
 
1.8%
20100806 7
 
1.6%
20001201 4
 
0.9%
20210806 3
 
0.7%
20200921 3
 
0.7%
20070725 3
 
0.7%
Other values (23) 25
 
5.5%

clgstdt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
휴업시작일자
70 

Length

Max length6
Median length4
Mean length4.3104213
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> 381
84.5%
휴업시작일자 70
 
15.5%

Length

2024-04-16T20:39:07.805411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:07.887047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
휴업시작일자 70
 
15.5%

clgenddt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
휴업종료일자
70 

Length

Max length6
Median length4
Mean length4.3104213
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> 381
84.5%
휴업종료일자 70
 
15.5%

Length

2024-04-16T20:39:07.974514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:08.054653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
휴업종료일자 70
 
15.5%

ropnymd
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
재개업일자
70 

Length

Max length5
Median length4
Mean length4.1552106
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> 381
84.5%
재개업일자 70
 
15.5%

Length

2024-04-16T20:39:08.145780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:08.221869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
재개업일자 70
 
15.5%

trdstatenm
Categorical

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
영업/정상
264 
13
114 
03
56 
폐업
 
8
제외/삭제/전출
 
7
Other values (2)
 
2

Length

Max length8
Median length5
Mean length3.8536585
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 264
58.5%
13 114
25.3%
03 56
 
12.4%
폐업 8
 
1.8%
제외/삭제/전출 7
 
1.6%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:39:08.307042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:08.430637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 264
58.5%
13 114
25.3%
03 56
 
12.4%
폐업 8
 
1.8%
제외/삭제/전출 7
 
1.6%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
영업중
379 
폐업
64 
전출
 
7
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8447894
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 379
84.0%
폐업 64
 
14.2%
전출 7
 
1.6%
직권말소 1
 
0.2%

Length

2024-04-16T20:39:08.549235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:08.640498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 379
84.0%
폐업 64
 
14.2%
전출 7
 
1.6%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)27.2%
Missing6
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean389772.25
Minimum373470.6
Maximum401646.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:08.729016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373470.6
5-th percentile380625.39
Q1385622.78
median389751.94
Q3393724.66
95-th percentile398310.24
Maximum401646.7
Range28176.099
Interquartile range (IQR)8101.8747

Descriptive statistics

Standard deviation5652.6747
Coefficient of variation (CV)0.014502507
Kurtosis-0.10331548
Mean389772.25
Median Absolute Deviation (MAD)4076.4153
Skewness-0.20745945
Sum1.7344865 × 108
Variance31952731
MonotonicityNot monotonic
2024-04-16T20:39:08.836740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 20
 
4.4%
387982.190387 14
 
3.1%
388011.197829908 12
 
2.7%
387443.214568 11
 
2.4%
387608.014165034 11
 
2.4%
385622.780457355 11
 
2.4%
393952.264486105 10
 
2.2%
398310.243451 10
 
2.2%
394153.800755 10
 
2.2%
396915.143441 10
 
2.2%
Other values (111) 326
72.3%
ValueCountFrequency (%)
373470.60373869 1
 
0.2%
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
 
0.4%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380625.391364589 6
1.3%
ValueCountFrequency (%)
401646.70301259 3
 
0.7%
401504.790177 6
1.3%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398757.078098629 1
 
0.2%
398628.503470003 2
 
0.4%
398341.802637 7
1.6%
398310.243451 10
2.2%
398275.475596001 1
 
0.2%
398242.150343638 2
 
0.4%

y
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)27.2%
Missing6
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean187596.18
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:08.953550image/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 deviation5413.2385
Coefficient of variation (CV)0.028855804
Kurtosis1.6057279
Mean187596.18
Median Absolute Deviation (MAD)2169.7385
Skewness0.85061913
Sum83480299
Variance29303151
MonotonicityNot monotonic
2024-04-16T20:39:09.077293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 20
 
4.4%
186465.864259 14
 
3.1%
185310.70532509 12
 
2.7%
186484.775084 11
 
2.4%
185703.079007724 11
 
2.4%
179452.224754792 11
 
2.4%
187602.933160728 10
 
2.2%
188031.67198 10
 
2.2%
188019.100861 10
 
2.2%
187480.443811 10
 
2.2%
Other values (111) 326
72.3%
ValueCountFrequency (%)
178757.423271048 7
1.6%
178872.461747926 1
 
0.2%
178919.583231221 1
 
0.2%
179411.189506548 1
 
0.2%
179452.224754792 11
2.4%
179597.592953541 6
1.3%
179823.23303496 4
 
0.9%
179885.813689 2
 
0.4%
179911.285409 5
1.1%
179919.437009 4
 
0.9%
ValueCountFrequency (%)
204621.655738547 5
1.1%
204597.0 5
1.1%
204401.691446 6
1.3%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
1.8%
195029.489621392 1
 
0.2%
194992.355262 2
 
0.4%
194681.150958776 7
1.6%
194622.201131 7
1.6%

lastmodts
Real number (ℝ)

Distinct386
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0185717 × 1013
Minimum2.0030127 × 1013
Maximum2.0211116 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:09.192370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0180614 × 1013
median2.0191015 × 1013
Q32.0210422 × 1013
95-th percentile2.0210823 × 1013
Maximum2.0211116 × 1013
Range1.8098894 × 1011
Interquartile range (IQR)2.9808017 × 1010

Descriptive statistics

Standard deviation3.315981 × 1010
Coefficient of variation (CV)0.0016427363
Kurtosis6.3476473
Mean2.0185717 × 1013
Median Absolute Deviation (MAD)1.9207006 × 1010
Skewness-2.3551527
Sum9.1037582 × 1015
Variance1.099573 × 1021
MonotonicityNot monotonic
2024-04-16T20:39:09.336647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190920121341 5
 
1.1%
20210421091411 5
 
1.1%
20030127161348 4
 
0.9%
20191017170859 4
 
0.9%
20190315161624 3
 
0.7%
20200320175117 3
 
0.7%
20190111110139 3
 
0.7%
20211024133544 3
 
0.7%
20190215180346 3
 
0.7%
20210806103802 3
 
0.7%
Other values (376) 415
92.0%
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 (%)
20211116103920 1
 
0.2%
20211115140841 1
 
0.2%
20211114121213 2
0.4%
20211101150525 1
 
0.2%
20211024133544 3
0.7%
20210917145721 2
0.4%
20210917131955 1
 
0.2%
20210917131929 1
 
0.2%
20210917131908 1
 
0.2%
20210917131846 1
 
0.2%

uptaenm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
업태구분명
70 

Length

Max length5
Median length4
Mean length4.1552106
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> 381
84.5%
업태구분명 70
 
15.5%

Length

2024-04-16T20:39:09.446371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:09.523159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
업태구분명 70
 
15.5%

sitetel
Categorical

IMBALANCE 

Distinct24
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
051-123-1234
289 
<NA>
49 
전화번호
36 
910-1411
 
12
051-366-2200
 
9
Other values (19)
56 

Length

Max length13
Median length12
Mean length10.297118
Min length4

Unique

Unique10 ?
Unique (%)2.2%

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 289
64.1%
<NA> 49
 
10.9%
전화번호 36
 
8.0%
910-1411 12
 
2.7%
051-366-2200 9
 
2.0%
051-745-2883 8
 
1.8%
070-4159-8881 7
 
1.6%
364-0480 7
 
1.6%
02-371-6670 6
 
1.3%
051-626-0488 6
 
1.3%
Other values (14) 22
 
4.9%

Length

2024-04-16T20:39:09.612025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 289
64.1%
na 49
 
10.9%
전화번호 36
 
8.0%
910-1411 12
 
2.7%
051-366-2200 9
 
2.0%
051-745-2883 8
 
1.8%
070-4159-8881 7
 
1.6%
364-0480 7
 
1.6%
02-371-6670 6
 
1.3%
051-626-0488 6
 
1.3%
Other values (14) 22
 
4.9%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
277 
문화시설
82 
건물용도명
63 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.1685144
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> 277
61.4%
문화시설 82
 
18.2%
건물용도명 63
 
14.0%
근린생활시설 13
 
2.9%
유통시설 9
 
2.0%
호텔 6
 
1.3%
사무실 1
 
0.2%

Length

2024-04-16T20:39:09.726311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:09.822126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 277
61.4%
문화시설 82
 
18.2%
건물용도명 63
 
14.0%
근린생활시설 13
 
2.9%
유통시설 9
 
2.0%
호텔 6
 
1.3%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
영화관
282 
<NA>
106 
공연장형태구분명
59 
자동차극장
 
4

Length

Max length8
Median length3
Mean length3.9068736
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 282
62.5%
<NA> 106
 
23.5%
공연장형태구분명 59
 
13.1%
자동차극장 4
 
0.9%

Length

2024-04-16T20:39:10.164060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:10.244721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 282
62.5%
na 106
 
23.5%
공연장형태구분명 59
 
13.1%
자동차극장 4
 
0.9%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
기존게임업외업종명
70 

Length

Max length9
Median length4
Mean length4.7760532
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> 381
84.5%
기존게임업외업종명 70
 
15.5%

Length

2024-04-16T20:39:10.334261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:10.414779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
기존게임업외업종명 70
 
15.5%

noroomcnt
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
369 
노래방실수
59 
0
 
23

Length

Max length5
Median length4
Mean length3.9778271
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> 369
81.8%
노래방실수 59
 
13.1%
0 23
 
5.1%

Length

2024-04-16T20:39:10.510390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:10.603014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
81.8%
노래방실수 59
 
13.1%
0 23
 
5.1%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
영화상영관
196 
<NA>
187 
문화사업자구분명
68 

Length

Max length8
Median length5
Mean length5.037694
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
43.5%
<NA> 187
41.5%
문화사업자구분명 68
 
15.1%

Length

2024-04-16T20:39:10.699942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:10.794579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 196
43.5%
na 187
41.5%
문화사업자구분명 68
 
15.1%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
영화상영관
290 
영화제작업
101 
영화배급업
30 
영화상영업
 
22
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
64.3%
영화제작업 101
 
22.4%
영화배급업 30
 
6.7%
영화상영업 22
 
4.9%
영화수입업 8
 
1.8%

Length

2024-04-16T20:39:10.883565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:10.964856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 290
64.3%
영화제작업 101
 
22.4%
영화배급업 30
 
6.7%
영화상영업 22
 
4.9%
영화수입업 8
 
1.8%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:11.068521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.156158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

vdoretornm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
비디오재생기명
70 

Length

Max length7
Median length4
Mean length4.4656319
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> 381
84.5%
비디오재생기명 70
 
15.5%

Length

2024-04-16T20:39:11.243491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.320748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
비디오재생기명 70
 
15.5%

emerstairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:11.404126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.481144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

emexyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:11.563205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.642570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

firefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:11.726246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.804194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
363 
시설면적
59 
0
 
23
1578.8
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.8713969
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 363
80.5%
시설면적 59
 
13.1%
0 23
 
5.1%
1578.8 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:39:11.888932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:11.994859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
80.5%
시설면적 59
 
13.1%
0 23
 
5.1%
1578.8 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:12.120873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:12.215212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

autochaairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:12.325613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:12.413197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
제공게임물명
70 

Length

Max length6
Median length4
Mean length4.3104213
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> 381
84.5%
제공게임물명 70
 
15.5%

Length

2024-04-16T20:39:12.503850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:12.595987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
제공게임물명 70
 
15.5%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
제작취급품목내용
70 

Length

Max length8
Median length4
Mean length4.6208426
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> 381
84.5%
제작취급품목내용 70
 
15.5%

Length

2024-04-16T20:39:12.688985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:12.770226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
제작취급품목내용 70
 
15.5%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:12.851854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:12.925671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

lghtfacilinillu
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
369 
조명시설조도
59 
0
 
23

Length

Max length6
Median length4
Mean length4.1086475
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> 369
81.8%
조명시설조도 59
 
13.1%
0 23
 
5.1%

Length

2024-04-16T20:39:13.009725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:13.100676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
81.8%
조명시설조도 59
 
13.1%
0 23
 
5.1%

nearenvnm
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
324 
주변환경명
66 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.2017738
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> 324
71.8%
주변환경명 66
 
14.6%
기타 32
 
7.1%
유흥업소밀집지역 18
 
4.0%
아파트지역 9
 
2.0%
학교정화(상대) 2
 
0.4%

Length

2024-04-16T20:39:13.201231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:13.297823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 324
71.8%
주변환경명 66
 
14.6%
기타 32
 
7.1%
유흥업소밀집지역 18
 
4.0%
아파트지역 9
 
2.0%
학교정화(상대 2
 
0.4%

jisgnumlay
Categorical

Distinct23
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
153 
지상층수
52 
10
37 
7
28 
9
27 
Other values (18)
154 

Length

Max length4
Median length2
Mean length2.6252772
Min length1

Unique

Unique4 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
33.9%
지상층수 52
 
11.5%
10 37
 
8.2%
7 28
 
6.2%
9 27
 
6.0%
5 20
 
4.4%
8 19
 
4.2%
42 17
 
3.8%
12 15
 
3.3%
6 12
 
2.7%
Other values (13) 71
15.7%

Length

2024-04-16T20:39:13.395202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 153
33.9%
지상층수 52
 
11.5%
10 37
 
8.2%
7 28
 
6.2%
9 27
 
6.0%
5 20
 
4.4%
8 19
 
4.2%
42 17
 
3.8%
12 15
 
3.3%
6 12
 
2.7%
Other values (13) 71
15.7%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
310 
지역구분명
66 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.368071
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 310
68.7%
지역구분명 66
 
14.6%
일반상업지역 30
 
6.7%
상업지역 16
 
3.5%
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

2024-04-16T20:39:13.502384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:13.598985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 310
68.7%
지역구분명 66
 
14.6%
일반상업지역 30
 
6.7%
상업지역 16
 
3.5%
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 size3.7 KiB
<NA>
160 
5
59 
지하층수
54 
2
47 
1
35 
Other values (7)
96 

Length

Max length4
Median length1
Mean length2.4279379
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
35.5%
5 59
 
13.1%
지하층수 54
 
12.0%
2 47
 
10.4%
1 35
 
7.8%
3 24
 
5.3%
4 21
 
4.7%
6 20
 
4.4%
8 18
 
4.0%
0 11
 
2.4%
Other values (2) 2
 
0.4%

Length

2024-04-16T20:39:13.713074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 160
35.5%
5 59
 
13.1%
지하층수 54
 
12.0%
2 47
 
10.4%
1 35
 
7.8%
3 24
 
5.3%
4 21
 
4.7%
6 20
 
4.4%
8 18
 
4.0%
0 11
 
2.4%
Other values (2) 2
 
0.4%

bgroomcnt
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
369 
청소년실수
59 
0
 
23

Length

Max length5
Median length4
Mean length3.9778271
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> 369
81.8%
청소년실수 59
 
13.1%
0 23
 
5.1%

Length

2024-04-16T20:39:13.818503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:13.904405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
81.8%
청소년실수 59
 
13.1%
0 23
 
5.1%

bgroomyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:13.988780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:14.065655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

totgasyscnt
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
369 
총게임기수
59 
0
 
23

Length

Max length5
Median length4
Mean length3.9778271
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> 369
81.8%
총게임기수 59
 
13.1%
0 23
 
5.1%

Length

2024-04-16T20:39:14.154938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:14.243947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
81.8%
총게임기수 59
 
13.1%
0 23
 
5.1%

totnumlay
Categorical

Distinct20
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
239 
총층수
55 
10
 
20
9
 
12
11
 
12
Other values (15)
113 

Length

Max length4
Median length4
Mean length3.0842572
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> 239
53.0%
총층수 55
 
12.2%
10 20
 
4.4%
9 12
 
2.7%
11 12
 
2.7%
6 12
 
2.7%
18 11
 
2.4%
0 11
 
2.4%
19 10
 
2.2%
15 9
 
2.0%
Other values (10) 60
 
13.3%

Length

2024-04-16T20:39:14.354205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 239
53.0%
총층수 55
 
12.2%
10 20
 
4.4%
9 12
 
2.7%
11 12
 
2.7%
6 12
 
2.7%
18 11
 
2.4%
0 11
 
2.4%
19 10
 
2.2%
54 9
 
2.0%
Other values (10) 60
 
13.3%

frstregts
Real number (ℝ)

Distinct151
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20114056
Minimum19451015
Maximum20211116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-04-16T20:39:14.472625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120050307
median20130507
Q320190702
95-th percentile20210568
Maximum20211116
Range760101
Interquartile range (IQR)140395

Descriptive statistics

Standard deviation89910.864
Coefficient of variation (CV)0.0044700513
Kurtosis8.4618567
Mean20114056
Median Absolute Deviation (MAD)69596
Skewness-1.7327296
Sum9.0714394 × 109
Variance8.0839634 × 109
MonotonicityNot monotonic
2024-04-16T20:39:14.595605image/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
 
2.4%
20010609 11
 
2.4%
20090302 10
 
2.2%
20021112 10
 
2.2%
20210615 10
 
2.2%
20050307 10
 
2.2%
20071204 10
 
2.2%
20200103 9
 
2.0%
Other values (141) 346
76.7%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.4%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20211116 1
0.2%
20211115 1
0.2%
20211101 1
0.2%
20210826 1
0.2%
20210806 2
0.4%
20210802 1
0.2%
20210722 1
0.2%
20210709 2
0.4%
20210707 1
0.2%
20210630 1
0.2%

pasgbreth
Categorical

Distinct19
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
233 
1
103 
통로너비
54 
0
 
16
1.5
 
12
Other values (14)
33 

Length

Max length4
Median length4
Mean length3.1463415
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> 233
51.7%
1 103
22.8%
통로너비 54
 
12.0%
0 16
 
3.5%
1.5 12
 
2.7%
1.2 7
 
1.6%
1.45 5
 
1.1%
1.3 4
 
0.9%
1.15 4
 
0.9%
1.7 3
 
0.7%
Other values (9) 10
 
2.2%

Length

2024-04-16T20:39:14.710102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 233
51.7%
1 103
22.8%
통로너비 54
 
12.0%
0 16
 
3.5%
1.5 12
 
2.7%
1.2 7
 
1.6%
1.45 5
 
1.1%
1.3 4
 
0.9%
1.15 4
 
0.9%
1.7 3
 
0.7%
Other values (9) 10
 
2.2%

speclghtyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:14.810571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:14.886402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
70 

Length

Max length4
Median length4
Mean length3.5343681
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> 381
84.5%
70
 
15.5%

Length

2024-04-16T20:39:14.969207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:15.047599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
70
 
15.5%

actlnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
품목명
70 

Length

Max length4
Median length4
Mean length3.8447894
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> 381
84.5%
품목명 70
 
15.5%

Length

2024-04-16T20:39:15.143354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:15.233628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
84.5%
품목명 70
 
15.5%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2021-12-01 05:20:03
451 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-01 05:20:03
2nd row2021-12-01 05:20:03
3rd row2021-12-01 05:20:03
4th row2021-12-01 05:20:03
5th row2021-12-01 05:20:03

Common Values

ValueCountFrequency (%)
2021-12-01 05:20:03 451
100.0%

Length

2024-04-16T20:39:15.321033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:39:15.401309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-01 451
50.0%
05:20:03 451
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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 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>2021-12-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
44130163400000CDFF521101202100000103_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/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2021-12-01 05:20:03
44230173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2021-12-01 05:20:03
44330183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2021-12-01 05:20:03
44430193360000CDFF521104202100000103_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/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2021-12-01 05:20:03
44530203330000CDFF521103202100000303_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/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2021-12-01 05:20:03
44630213330000CDFF521101202100000503_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>2021-12-01 05:20:03
44730223250000CDFF521102202100000103_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>2021-12-01 05:20:03
44830233250000CDFF521103202100000103_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>2021-12-01 05:20:03
44930243250000CDFF521101202100000203_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>2021-12-01 05:20:03
45030253290000CDFF521104202100000103_13_03_PU2021-09-19 02:40:00.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210917145721업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2021-12-01 05:20:03