Overview

Dataset statistics

Number of variables56
Number of observations424
Missing cells33
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory188.5 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 (75.5%)Imbalance
dcbymd is highly imbalanced (64.7%)Imbalance
dtlstatenm is highly imbalanced (66.4%)Imbalance
sitetel is highly imbalanced (59.8%)Imbalance
facilar is highly imbalanced (72.8%)Imbalance
nearenvnm is highly imbalanced (50.1%)Imbalance
regnsenm is highly imbalanced (53.3%)Imbalance
pasgbreth is highly imbalanced (52.0%)Imbalance
rdnpostno has 15 (3.5%) 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 11:40:34.902759
Analysis finished2024-04-16 11:40:35.706359
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct424
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean698.92689
Minimum1
Maximum3031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:35.768472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.15
Q1106.75
median212.5
Q31195.75
95-th percentile2957.55
Maximum3031
Range3030
Interquartile range (IQR)1089

Descriptive statistics

Standard deviation910.50128
Coefficient of variation (CV)1.3027132
Kurtosis0.65322109
Mean698.92689
Median Absolute Deviation (MAD)148
Skewness1.4103841
Sum296345
Variance829012.57
MonotonicityNot monotonic
2024-04-16T20:40:35.907964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
779 1
 
0.2%
705 1
 
0.2%
692 1
 
0.2%
690 1
 
0.2%
688 1
 
0.2%
582 1
 
0.2%
572 1
 
0.2%
564 1
 
0.2%
556 1
 
0.2%
Other values (414) 414
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
3031 1
0.2%
3030 1
0.2%
3029 1
0.2%
3028 1
0.2%
3027 1
0.2%
3026 1
0.2%
3025 1
0.2%
3024 1
0.2%
3023 1
0.2%
3022 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3318514.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:36.018176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation41002.909
Coefficient of variation (CV)0.012355804
Kurtosis-0.41485902
Mean3318514.2
Median Absolute Deviation (MAD)30000
Skewness0.11888942
Sum1.40705 × 109
Variance1.6812386 × 109
MonotonicityNot monotonic
2024-04-16T20:40:36.115682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 120
28.3%
3290000 75
17.7%
3250000 56
13.2%
3350000 26
 
6.1%
3300000 25
 
5.9%
3400000 24
 
5.7%
3320000 21
 
5.0%
3310000 19
 
4.5%
3390000 15
 
3.5%
3380000 14
 
3.3%
Other values (5) 29
 
6.8%
ValueCountFrequency (%)
3250000 56
13.2%
3260000 1
 
0.2%
3270000 5
 
1.2%
3290000 75
17.7%
3300000 25
 
5.9%
3310000 19
 
4.5%
3320000 21
 
5.0%
3330000 120
28.3%
3340000 13
 
3.1%
3350000 26
 
6.1%
ValueCountFrequency (%)
3400000 24
 
5.7%
3390000 15
 
3.5%
3380000 14
 
3.3%
3370000 9
 
2.1%
3360000 1
 
0.2%
3350000 26
 
6.1%
3340000 13
 
3.1%
3330000 120
28.3%
3320000 21
 
5.0%
3310000 19
 
4.5%

mgtno
Text

Distinct233
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-16T20:40:36.317470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8480
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

Unique141 ?
Unique (%)33.3%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
4.2%
cdff5211012019000001 12
 
2.8%
cdff5211012020000002 9
 
2.1%
cdff5211032019000001 8
 
1.9%
cdff5211032020000001 8
 
1.9%
cdff5211012021000001 6
 
1.4%
cdff5211042019000001 6
 
1.4%
cdff5211042021000001 5
 
1.2%
cdff5211042020000001 4
 
0.9%
cdff4220002007000001 4
 
0.9%
Other values (223) 344
81.1%
2024-04-16T20:40:36.626245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3753
44.3%
2 1280
 
15.1%
F 848
 
10.0%
1 766
 
9.0%
C 424
 
5.0%
D 424
 
5.0%
4 367
 
4.3%
5 204
 
2.4%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 200
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6784
80.0%
Uppercase Letter 1696
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3753
55.3%
2 1280
 
18.9%
1 766
 
11.3%
4 367
 
5.4%
5 204
 
3.0%
9 132
 
1.9%
7 82
 
1.2%
3 81
 
1.2%
6 62
 
0.9%
8 57
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
F 848
50.0%
C 424
25.0%
D 424
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6784
80.0%
Latin 1696
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3753
55.3%
2 1280
 
18.9%
1 766
 
11.3%
4 367
 
5.4%
5 204
 
3.0%
9 132
 
1.9%
7 82
 
1.2%
3 81
 
1.2%
6 62
 
0.9%
8 57
 
0.8%
Latin
ValueCountFrequency (%)
F 848
50.0%
C 424
25.0%
D 424
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3753
44.3%
2 1280
 
15.1%
F 848
 
10.0%
1 766
 
9.0%
C 424
 
5.0%
D 424
 
5.0%
4 367
 
4.3%
5 204
 
2.4%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 200
 
2.4%

opnsvcid
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
03_13_02_P
283 
03_13_05_P
90 
03_13_01_P
 
26
03_13_03_P
 
18
03_13_04_P
 
7

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 283
66.7%
03_13_05_P 90
 
21.2%
03_13_01_P 26
 
6.1%
03_13_03_P 18
 
4.2%
03_13_04_P 7
 
1.7%

Length

2024-04-16T20:40:36.748473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:36.837935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 283
66.7%
03_13_05_p 90
 
21.2%
03_13_01_p 26
 
6.1%
03_13_03_p 18
 
4.2%
03_13_04_p 7
 
1.7%

updategbn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
I
285 
U
139 

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 285
67.2%
U 139
32.8%

Length

2024-04-16T20:40:36.932096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:37.027464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 285
67.2%
u 139
32.8%
Distinct93
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-30 02:40:00
2024-04-16T20:40:37.124125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:40:37.232296image/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 size3.4 KiB
<NA>
174 
영화상영관
109 
영화제작업
90 
영화배급업
26 
영화상영업
18 

Length

Max length5
Median length5
Mean length4.5896226
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
41.0%
영화상영관 109
25.7%
영화제작업 90
21.2%
영화배급업 26
 
6.1%
영화상영업 18
 
4.2%
영화수입업 7
 
1.7%

Length

2024-04-16T20:40:37.335336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:37.426512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 174
41.0%
영화상영관 109
25.7%
영화제작업 90
21.2%
영화배급업 26
 
6.1%
영화상영업 18
 
4.2%
영화수입업 7
 
1.7%

bplcnm
Text

Distinct357
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-16T20:40:37.602945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length10.863208
Min length2

Characters and Unicode

Total characters4606
Distinct characters250
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

Unique327 ?
Unique (%)77.1%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 86
 
9.2%
메가박스 48
 
5.1%
cgv 41
 
4.4%
주식회사 36
 
3.9%
해운대 26
 
2.8%
서면 20
 
2.1%
센텀시티 19
 
2.0%
제3관 15
 
1.6%
정관 15
 
1.6%
제2관 14
 
1.5%
Other values (217) 613
65.7%
2024-04-16T20:40:37.930571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
511
 
11.1%
311
 
6.8%
153
 
3.3%
143
 
3.1%
133
 
2.9%
122
 
2.6%
110
 
2.4%
101
 
2.2%
101
 
2.2%
C 101
 
2.2%
Other values (240) 2820
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3227
70.1%
Space Separator 511
 
11.1%
Uppercase Letter 392
 
8.5%
Decimal Number 261
 
5.7%
Close Punctuation 91
 
2.0%
Open Punctuation 91
 
2.0%
Lowercase Letter 20
 
0.4%
Other Punctuation 12
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
311
 
9.6%
153
 
4.7%
143
 
4.4%
133
 
4.1%
122
 
3.8%
110
 
3.4%
101
 
3.1%
101
 
3.1%
95
 
2.9%
79
 
2.4%
Other values (193) 1879
58.2%
Uppercase Letter
ValueCountFrequency (%)
C 101
25.8%
G 83
21.2%
V 82
20.9%
N 20
 
5.1%
E 11
 
2.8%
M 10
 
2.6%
A 9
 
2.3%
U 8
 
2.0%
O 8
 
2.0%
T 7
 
1.8%
Other values (12) 53
13.5%
Decimal Number
ValueCountFrequency (%)
1 44
16.9%
2 35
13.4%
4 33
12.6%
3 31
11.9%
6 30
11.5%
5 29
11.1%
7 24
9.2%
8 16
 
6.1%
9 13
 
5.0%
0 6
 
2.3%
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 (%)
) 90
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 90
98.9%
[ 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
511
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3227
70.1%
Common 967
 
21.0%
Latin 412
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
311
 
9.6%
153
 
4.7%
143
 
4.4%
133
 
4.1%
122
 
3.8%
110
 
3.4%
101
 
3.1%
101
 
3.1%
95
 
2.9%
79
 
2.4%
Other values (193) 1879
58.2%
Latin
ValueCountFrequency (%)
C 101
24.5%
G 83
20.1%
V 82
19.9%
N 20
 
4.9%
E 11
 
2.7%
M 10
 
2.4%
A 9
 
2.2%
U 8
 
1.9%
O 8
 
1.9%
T 7
 
1.7%
Other values (19) 73
17.7%
Common
ValueCountFrequency (%)
511
52.8%
) 90
 
9.3%
( 90
 
9.3%
1 44
 
4.6%
2 35
 
3.6%
4 33
 
3.4%
3 31
 
3.2%
6 30
 
3.1%
5 29
 
3.0%
7 24
 
2.5%
Other values (8) 50
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3227
70.1%
ASCII 1379
29.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
511
37.1%
C 101
 
7.3%
) 90
 
6.5%
( 90
 
6.5%
G 83
 
6.0%
V 82
 
5.9%
1 44
 
3.2%
2 35
 
2.5%
4 33
 
2.4%
3 31
 
2.2%
Other values (37) 279
20.2%
Hangul
ValueCountFrequency (%)
311
 
9.6%
153
 
4.7%
143
 
4.4%
133
 
4.1%
122
 
3.8%
110
 
3.4%
101
 
3.1%
101
 
3.1%
95
 
2.9%
79
 
2.4%
Other values (193) 1879
58.2%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
354 
지번우편번호
48 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.3301887
Min length4

Unique

Unique10 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
83.5%
지번우편번호 48
 
11.3%
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

2024-04-16T20:40:38.052485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 354
83.5%
지번우편번호 48
 
11.3%
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%
Distinct139
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-16T20:40:38.301950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length27.183962
Min length18

Characters and Unicode

Total characters11526
Distinct characters227
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

Unique70 ?
Unique (%)16.5%

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 424
 
20.1%
해운대구 120
 
5.7%
우동 92
 
4.4%
부산진구 75
 
3.5%
중구 56
 
2.7%
부전동 47
 
2.2%
전포동 27
 
1.3%
금정구 26
 
1.2%
동래구 25
 
1.2%
기장군 24
 
1.1%
Other values (310) 1197
56.6%
2024-04-16T20:40:38.671814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2068
 
17.9%
589
 
5.1%
548
 
4.8%
1 477
 
4.1%
461
 
4.0%
454
 
3.9%
428
 
3.7%
424
 
3.7%
401
 
3.5%
- 355
 
3.1%
Other values (217) 5321
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6752
58.6%
Decimal Number 2147
 
18.6%
Space Separator 2068
 
17.9%
Dash Punctuation 355
 
3.1%
Uppercase Letter 132
 
1.1%
Other Punctuation 27
 
0.2%
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 (%)
589
 
8.7%
548
 
8.1%
461
 
6.8%
454
 
6.7%
428
 
6.3%
424
 
6.3%
401
 
5.9%
303
 
4.5%
288
 
4.3%
158
 
2.3%
Other values (182) 2698
40.0%
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 (%)
1 477
22.2%
2 307
14.3%
5 224
10.4%
6 214
10.0%
4 188
 
8.8%
0 183
 
8.5%
7 161
 
7.5%
8 158
 
7.4%
3 120
 
5.6%
9 115
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
o 3
20.0%
h 2
 
13.3%
r 2
 
13.3%
l 1
 
6.7%
i 1
 
6.7%
v 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 18
66.7%
& 9
33.3%
Space Separator
ValueCountFrequency (%)
2068
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 355
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 6752
58.6%
Common 4627
40.1%
Latin 147
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
589
 
8.7%
548
 
8.1%
461
 
6.8%
454
 
6.7%
428
 
6.3%
424
 
6.3%
401
 
5.9%
303
 
4.5%
288
 
4.3%
158
 
2.3%
Other values (182) 2698
40.0%
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%
Common
ValueCountFrequency (%)
2068
44.7%
1 477
 
10.3%
- 355
 
7.7%
2 307
 
6.6%
5 224
 
4.8%
6 214
 
4.6%
4 188
 
4.1%
0 183
 
4.0%
7 161
 
3.5%
8 158
 
3.4%
Other values (7) 292
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6752
58.6%
ASCII 4774
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2068
43.3%
1 477
 
10.0%
- 355
 
7.4%
2 307
 
6.4%
5 224
 
4.7%
6 214
 
4.5%
4 188
 
3.9%
0 183
 
3.8%
7 161
 
3.4%
8 158
 
3.3%
Other values (25) 439
 
9.2%
Hangul
ValueCountFrequency (%)
589
 
8.7%
548
 
8.1%
461
 
6.8%
454
 
6.7%
428
 
6.3%
424
 
6.3%
401
 
5.9%
303
 
4.5%
288
 
4.3%
158
 
2.3%
Other values (182) 2698
40.0%

rdnpostno
Text

MISSING 

Distinct78
Distinct (%)19.1%
Missing15
Missing (%)3.5%
Memory size3.4 KiB
2024-04-16T20:40:38.878062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.00489
Min length5

Characters and Unicode

Total characters2047
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 (%)9.3%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 60
 
14.7%
48058 42
 
10.3%
48953 20
 
4.9%
48059 17
 
4.2%
47296 16
 
3.9%
47299 12
 
2.9%
48944 11
 
2.7%
47285 11
 
2.7%
47710 10
 
2.4%
48948 10
 
2.4%
Other values (68) 200
48.9%
2024-04-16T20:40:39.202232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 551
26.9%
8 354
17.3%
9 244
11.9%
7 211
 
10.3%
5 156
 
7.6%
0 148
 
7.2%
2 124
 
6.1%
6 114
 
5.6%
1 74
 
3.6%
3 64
 
3.1%
Other values (7) 7
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2040
99.7%
Other Letter 7
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 551
27.0%
8 354
17.4%
9 244
12.0%
7 211
 
10.3%
5 156
 
7.6%
0 148
 
7.3%
2 124
 
6.1%
6 114
 
5.6%
1 74
 
3.6%
3 64
 
3.1%
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 2040
99.7%
Hangul 7
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 551
27.0%
8 354
17.4%
9 244
12.0%
7 211
 
10.3%
5 156
 
7.6%
0 148
 
7.3%
2 124
 
6.1%
6 114
 
5.6%
1 74
 
3.6%
3 64
 
3.1%
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 2040
99.7%
Hangul 7
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 551
27.0%
8 354
17.4%
9 244
12.0%
7 211
 
10.3%
5 156
 
7.6%
0 148
 
7.3%
2 124
 
6.1%
6 114
 
5.6%
1 74
 
3.6%
3 64
 
3.1%
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 

Distinct135
Distinct (%)32.3%
Missing6
Missing (%)1.4%
Memory size3.4 KiB
2024-04-16T20:40:39.454105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length32.425837
Min length22

Characters and Unicode

Total characters13554
Distinct characters261
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

Unique67 ?
Unique (%)16.0%

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 418
 
15.9%
해운대구 120
 
4.6%
우동 82
 
3.1%
부산진구 75
 
2.9%
중구 53
 
2.0%
중앙대로 50
 
1.9%
부전동 47
 
1.8%
해운대로 44
 
1.7%
6층 35
 
1.3%
39 34
 
1.3%
Other values (379) 1671
63.6%
2024-04-16T20:40:39.829176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2236
 
16.5%
601
 
4.4%
555
 
4.1%
516
 
3.8%
468
 
3.5%
460
 
3.4%
418
 
3.1%
418
 
3.1%
( 410
 
3.0%
) 410
 
3.0%
Other values (251) 7062
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8082
59.6%
Space Separator 2236
 
16.5%
Decimal Number 1874
 
13.8%
Open Punctuation 411
 
3.0%
Close Punctuation 411
 
3.0%
Other Punctuation 364
 
2.7%
Uppercase Letter 135
 
1.0%
Dash Punctuation 19
 
0.1%
Lowercase Letter 16
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
601
 
7.4%
555
 
6.9%
516
 
6.4%
468
 
5.8%
460
 
5.7%
418
 
5.2%
418
 
5.2%
402
 
5.0%
344
 
4.3%
192
 
2.4%
Other values (210) 3708
45.9%
Uppercase Letter
ValueCountFrequency (%)
K 29
21.5%
S 19
14.1%
T 15
11.1%
B 11
 
8.1%
C 10
 
7.4%
H 10
 
7.4%
U 10
 
7.4%
G 9
 
6.7%
Y 9
 
6.7%
N 7
 
5.2%
Other values (3) 6
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 365
19.5%
2 251
13.4%
0 212
11.3%
3 197
10.5%
6 172
9.2%
5 158
8.4%
4 156
8.3%
7 148
7.9%
9 121
 
6.5%
8 94
 
5.0%
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 (%)
, 354
97.3%
& 9
 
2.5%
* 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 410
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 410
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8082
59.6%
Common 5321
39.3%
Latin 151
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
601
 
7.4%
555
 
6.9%
516
 
6.4%
468
 
5.8%
460
 
5.7%
418
 
5.2%
418
 
5.2%
402
 
5.0%
344
 
4.3%
192
 
2.4%
Other values (210) 3708
45.9%
Latin
ValueCountFrequency (%)
K 29
19.2%
S 19
12.6%
T 15
9.9%
B 11
 
7.3%
C 10
 
6.6%
H 10
 
6.6%
U 10
 
6.6%
G 9
 
6.0%
Y 9
 
6.0%
N 7
 
4.6%
Other values (11) 22
14.6%
Common
ValueCountFrequency (%)
2236
42.0%
( 410
 
7.7%
) 410
 
7.7%
1 365
 
6.9%
, 354
 
6.7%
2 251
 
4.7%
0 212
 
4.0%
3 197
 
3.7%
6 172
 
3.2%
5 158
 
3.0%
Other values (10) 556
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8082
59.6%
ASCII 5472
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2236
40.9%
( 410
 
7.5%
) 410
 
7.5%
1 365
 
6.7%
, 354
 
6.5%
2 251
 
4.6%
0 212
 
3.9%
3 197
 
3.6%
6 172
 
3.1%
5 158
 
2.9%
Other values (31) 707
 
12.9%
Hangul
ValueCountFrequency (%)
601
 
7.4%
555
 
6.9%
516
 
6.4%
468
 
5.8%
460
 
5.7%
418
 
5.2%
418
 
5.2%
402
 
5.0%
344
 
4.3%
192
 
2.4%
Other values (210) 3708
45.9%

apvpermymd
Real number (ℝ)

Distinct137
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20108536
Minimum19451015
Maximum20210527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:39.959847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000518
Q120050111
median20110513
Q320190322
95-th percentile20210119
Maximum20210527
Range759512
Interquartile range (IQR)140211

Descriptive statistics

Standard deviation89604.952
Coefficient of variation (CV)0.0044560655
Kurtosis8.8362316
Mean20108536
Median Absolute Deviation (MAD)79754
Skewness-1.7481765
Sum8.5260192 × 109
Variance8.0290474 × 109
MonotonicityNot monotonic
2024-04-16T20:40:40.082450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.8%
20190315 12
 
2.8%
20140822 11
 
2.6%
20010609 11
 
2.6%
20071204 10
 
2.4%
20090302 10
 
2.4%
20021112 10
 
2.4%
20050307 10
 
2.4%
20061023 9
 
2.1%
20200103 9
 
2.1%
Other values (127) 320
75.5%
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 (%)
20210527 1
0.2%
20210521 2
0.5%
20210513 2
0.5%
20210512 1
0.2%
20210405 1
0.2%
20210330 1
0.2%
20210329 1
0.2%
20210318 1
0.2%
20210317 1
0.2%
20210315 1
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct30
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
312 
폐업일자
47 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (25)
39 

Length

Max length8
Median length4
Mean length4.6132075
Min length4

Unique

Unique20 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 312
73.6%
폐업일자 47
 
11.1%
20170315 10
 
2.4%
20160617 8
 
1.9%
20110616 8
 
1.9%
20100806 7
 
1.7%
20001201 4
 
0.9%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (20) 20
 
4.7%

Length

2024-04-16T20:40:40.208571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 312
73.6%
폐업일자 47
 
11.1%
20170315 10
 
2.4%
20160617 8
 
1.9%
20110616 8
 
1.9%
20100806 7
 
1.7%
20001201 4
 
0.9%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (20) 20
 
4.7%

clgstdt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
휴업시작일자
48 

Length

Max length6
Median length4
Mean length4.2264151
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
휴업시작일자 48
 
11.3%

Length

2024-04-16T20:40:40.324097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:40.420908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
휴업시작일자 48
 
11.3%

clgenddt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
휴업종료일자
48 

Length

Max length6
Median length4
Mean length4.2264151
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
휴업종료일자 48
 
11.3%

Length

2024-04-16T20:40:40.541552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:40.650896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
휴업종료일자 48
 
11.3%

ropnymd
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
재개업일자
48 

Length

Max length5
Median length4
Mean length4.1132075
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
재개업일자 48
 
11.3%

Length

2024-04-16T20:40:40.740740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:40.828658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
재개업일자 48
 
11.3%

trdstatenm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
영업/정상
240 
13
117 
03
56 
폐업
 
7
제외/삭제/전출
 
2
Other values (2)
 
2

Length

Max length8
Median length5
Mean length3.7311321
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 240
56.6%
13 117
27.6%
03 56
 
13.2%
폐업 7
 
1.7%
제외/삭제/전출 2
 
0.5%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:40:40.925885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:41.026992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 240
56.6%
13 117
27.6%
03 56
 
13.2%
폐업 7
 
1.7%
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 size3.4 KiB
영업중
358 
폐업
63 
전출
 
2
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8490566
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 358
84.4%
폐업 63
 
14.9%
전출 2
 
0.5%
직권말소 1
 
0.2%

Length

2024-04-16T20:40:41.368889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:41.470519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 358
84.4%
폐업 63
 
14.9%
전출 2
 
0.5%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct111
Distinct (%)26.6%
Missing6
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean389986.03
Minimum374253.11
Maximum401646.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:41.567654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum374253.11
5-th percentile380757.33
Q1386284.62
median389751.94
Q3393828.35
95-th percentile398310.24
Maximum401646.7
Range27393.591
Interquartile range (IQR)7543.7301

Descriptive statistics

Standard deviation5325.822
Coefficient of variation (CV)0.013656443
Kurtosis-0.51705342
Mean389986.03
Median Absolute Deviation (MAD)4076.4153
Skewness-0.019849997
Sum1.6301416 × 108
Variance28364380
MonotonicityNot monotonic
2024-04-16T20:40:41.689114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 20
 
4.7%
387982.190387 14
 
3.3%
388011.197829908 12
 
2.8%
387608.014165034 11
 
2.6%
385622.780457355 11
 
2.6%
387443.214568 11
 
2.6%
396915.143441 10
 
2.4%
393952.264486105 10
 
2.4%
398310.243451 10
 
2.4%
394153.800755 10
 
2.4%
Other values (101) 299
70.5%
ValueCountFrequency (%)
374253.112340712 1
 
0.2%
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.2%
379240.573215267 3
0.7%
379280.632039 2
 
0.5%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380625.391364589 6
1.4%
380780.612775 7
1.7%
ValueCountFrequency (%)
401646.70301259 1
 
0.2%
401504.790177 6
1.4%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398628.503470003 2
 
0.5%
398341.802637 7
1.7%
398310.243451 10
2.4%
398275.475596001 1
 
0.2%
398242.150343638 2
 
0.5%
398035.0 5
1.2%

y
Real number (ℝ)

MISSING 

Distinct111
Distinct (%)26.6%
Missing6
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean187740.55
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:41.811018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178757.42
5-th percentile179823.23
Q1185679.05
median187480.44
Q3189911.43
95-th percentile195491.52
Maximum204621.66
Range25864.232
Interquartile range (IQR)4232.3797

Descriptive statistics

Standard deviation5410.2335
Coefficient of variation (CV)0.028817607
Kurtosis1.6734455
Mean187740.55
Median Absolute Deviation (MAD)2169.7385
Skewness0.90147485
Sum78475550
Variance29270626
MonotonicityNot monotonic
2024-04-16T20:40:41.940593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 20
 
4.7%
186465.864259 14
 
3.3%
185310.70532509 12
 
2.8%
185703.079007724 11
 
2.6%
179452.224754792 11
 
2.6%
186484.775084 11
 
2.6%
187480.443811 10
 
2.4%
187602.933160728 10
 
2.4%
188031.67198 10
 
2.4%
188019.100861 10
 
2.4%
Other values (101) 299
70.5%
ValueCountFrequency (%)
178757.423271048 1
 
0.2%
178872.461747926 1
 
0.2%
179411.189506548 1
 
0.2%
179452.224754792 11
2.6%
179597.592953541 6
1.4%
179823.23303496 4
 
0.9%
179885.813689 2
 
0.5%
179911.285409 5
1.2%
179919.437009 4
 
0.9%
179919.488084 8
1.9%
ValueCountFrequency (%)
204621.655738547 5
1.2%
204597.0 5
1.2%
204401.691446 6
1.4%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
1.9%
194992.355262 2
 
0.5%
194681.150958776 7
1.7%
194622.201131 7
1.7%
194428.696617 7
1.7%

lastmodts
Real number (ℝ)

Distinct357
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0183414 × 1013
Minimum2.0030127 × 1013
Maximum2.0210528 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:42.067507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0180611 × 1013
median2.0190516 × 1013
Q32.0210202 × 1013
95-th percentile2.0210513 × 1013
Maximum2.0210528 × 1013
Range1.8040101 × 1011
Interquartile range (IQR)2.9590948 × 1010

Descriptive statistics

Standard deviation3.3240623 × 1010
Coefficient of variation (CV)0.0016469277
Kurtosis6.1422685
Mean2.0183414 × 1013
Median Absolute Deviation (MAD)1.0302017 × 1010
Skewness-2.3237424
Sum8.5577674 × 1015
Variance1.104939 × 1021
MonotonicityNot monotonic
2024-04-16T20:40:42.187648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210524175645 6
 
1.4%
20210421091411 5
 
1.2%
20190920121341 5
 
1.2%
20191017170859 4
 
0.9%
20030127161348 4
 
0.9%
20200103203958 3
 
0.7%
20210312113406 3
 
0.7%
20210312113428 3
 
0.7%
20200921144254 3
 
0.7%
20200320175117 3
 
0.7%
Other values (347) 385
90.8%
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 (%)
20210528174225 2
 
0.5%
20210528141448 1
 
0.2%
20210527180832 1
 
0.2%
20210527132430 1
 
0.2%
20210527132354 1
 
0.2%
20210526110648 1
 
0.2%
20210526110538 1
 
0.2%
20210524175645 6
1.4%
20210524175644 2
 
0.5%
20210521093521 2
 
0.5%

uptaenm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
업태구분명
48 

Length

Max length5
Median length4
Mean length4.1132075
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
업태구분명 48
 
11.3%

Length

2024-04-16T20:40:42.302731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:42.396079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
업태구분명 48
 
11.3%

sitetel
Categorical

IMBALANCE 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
051-123-1234
308 
<NA>
39 
전화번호
 
19
910-1411
 
12
051-366-2200
 
9
Other values (14)
37 

Length

Max length13
Median length12
Mean length10.733491
Min length4

Unique

Unique8 ?
Unique (%)1.9%

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 308
72.6%
<NA> 39
 
9.2%
전화번호 19
 
4.5%
910-1411 12
 
2.8%
051-366-2200 9
 
2.1%
051-745-2883 8
 
1.9%
364-0480 7
 
1.7%
051-626-0488 6
 
1.4%
051-507-5282 4
 
0.9%
051-520-3766 2
 
0.5%
Other values (9) 10
 
2.4%

Length

2024-04-16T20:40:42.491452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 308
72.6%
na 39
 
9.2%
전화번호 19
 
4.5%
910-1411 12
 
2.8%
051-366-2200 9
 
2.1%
051-745-2883 8
 
1.9%
364-0480 7
 
1.7%
051-626-0488 6
 
1.4%
051-507-5282 4
 
0.9%
051-805-0416 2
 
0.5%
Other values (9) 10
 
2.4%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
275 
문화시설
82 
건물용도명
44 
유통시설
 
9
근린생활시설
 
7
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.1061321
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> 275
64.9%
문화시설 82
 
19.3%
건물용도명 44
 
10.4%
유통시설 9
 
2.1%
근린생활시설 7
 
1.7%
호텔 6
 
1.4%
사무실 1
 
0.2%

Length

2024-04-16T20:40:42.601614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:42.705933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
64.9%
문화시설 82
 
19.3%
건물용도명 44
 
10.4%
유통시설 9
 
2.1%
근린생활시설 7
 
1.7%
호텔 6
 
1.4%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
영화관
275 
<NA>
105 
공연장형태구분명
40 
자동차극장
 
4

Length

Max length8
Median length3
Mean length3.7382075
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 275
64.9%
<NA> 105
 
24.8%
공연장형태구분명 40
 
9.4%
자동차극장 4
 
0.9%

Length

2024-04-16T20:40:42.820870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:42.911921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 275
64.9%
na 105
 
24.8%
공연장형태구분명 40
 
9.4%
자동차극장 4
 
0.9%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
기존게임업외업종명
48 

Length

Max length9
Median length4
Mean length4.5660377
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
기존게임업외업종명 48
 
11.3%

Length

2024-04-16T20:40:43.014528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:43.098448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
기존게임업외업종명 48
 
11.3%

noroomcnt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
노래방실수
48 

Length

Max length5
Median length4
Mean length4.1132075
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
노래방실수 48
 
11.3%

Length

2024-04-16T20:40:43.187938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:43.281080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
노래방실수 48
 
11.3%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
영화상영관
196 
<NA>
182 
문화사업자구분명
46 

Length

Max length8
Median length5
Mean length4.8962264
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
46.2%
<NA> 182
42.9%
문화사업자구분명 46
 
10.8%

Length

2024-04-16T20:40:43.378266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:43.476516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 196
46.2%
na 182
42.9%
문화사업자구분명 46
 
10.8%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
영화상영관
283 
영화제작업
90 
영화배급업
 
26
영화상영업
 
18
영화수입업
 
7

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 283
66.7%
영화제작업 90
 
21.2%
영화배급업 26
 
6.1%
영화상영업 18
 
4.2%
영화수입업 7
 
1.7%

Length

2024-04-16T20:40:43.578003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:43.672368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 283
66.7%
영화제작업 90
 
21.2%
영화배급업 26
 
6.1%
영화상영업 18
 
4.2%
영화수입업 7
 
1.7%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:43.771517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:43.861189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

vdoretornm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
비디오재생기명
48 

Length

Max length7
Median length4
Mean length4.3396226
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
비디오재생기명 48
 
11.3%

Length

2024-04-16T20:40:43.955778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:44.062639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
비디오재생기명 48
 
11.3%

emerstairyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:44.160986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:44.250643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

emexyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:44.349989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:44.440340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

firefacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:44.541889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:44.636172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

facilar
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
370 
시설면적
48 
1578.8
 
4
147.46
 
1
181.3
 
1

Length

Max length6
Median length4
Mean length4.0259434
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
87.3%
시설면적 48
 
11.3%
1578.8 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:40:44.739923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:44.845406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
87.3%
시설면적 48
 
11.3%
1578.8 4
 
0.9%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:44.948259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:45.036041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

autochaairyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:45.124331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:45.210845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
제공게임물명
48 

Length

Max length6
Median length4
Mean length4.2264151
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
제공게임물명 48
 
11.3%

Length

2024-04-16T20:40:45.313424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:45.410291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
제공게임물명 48
 
11.3%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
제작취급품목내용
48 

Length

Max length8
Median length4
Mean length4.4528302
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
제작취급품목내용 48
 
11.3%

Length

2024-04-16T20:40:45.508404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:45.605175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
제작취급품목내용 48
 
11.3%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:45.697993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:45.784390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

lghtfacilinillu
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
조명시설조도
48 

Length

Max length6
Median length4
Mean length4.2264151
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
조명시설조도 48
 
11.3%

Length

2024-04-16T20:40:45.908371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:46.013192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
조명시설조도 48
 
11.3%

nearenvnm
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
317 
주변환경명
46 
기타
32 
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.1674528
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> 317
74.8%
주변환경명 46
 
10.8%
기타 32
 
7.5%
유흥업소밀집지역 18
 
4.2%
아파트지역 9
 
2.1%
학교정화(상대) 2
 
0.5%

Length

2024-04-16T20:40:46.129638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:46.230411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 317
74.8%
주변환경명 46
 
10.8%
기타 32
 
7.5%
유흥업소밀집지역 18
 
4.2%
아파트지역 9
 
2.1%
학교정화(상대 2
 
0.5%

jisgnumlay
Categorical

Distinct21
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
154 
지상층수
41 
10
37 
7
28 
9
27 
Other values (16)
137 

Length

Max length4
Median length2
Mean length2.6438679
Min length1

Unique

Unique4 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 154
36.3%
지상층수 41
 
9.7%
10 37
 
8.7%
7 28
 
6.6%
9 27
 
6.4%
5 20
 
4.7%
8 19
 
4.5%
42 17
 
4.0%
12 15
 
3.5%
6 12
 
2.8%
Other values (11) 54
 
12.7%

Length

2024-04-16T20:40:46.372755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 154
36.3%
지상층수 41
 
9.7%
10 37
 
8.7%
7 28
 
6.6%
9 27
 
6.4%
5 20
 
4.7%
8 19
 
4.5%
42 17
 
4.0%
12 15
 
3.5%
6 12
 
2.8%
Other values (11) 54
 
12.7%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
303 
지역구분명
46 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3443396
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 303
71.5%
지역구분명 46
 
10.8%
일반상업지역 30
 
7.1%
상업지역 16
 
3.8%
중심상업지역 12
 
2.8%
녹지지역 8
 
1.9%
일반주거지역 4
 
0.9%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:40:46.522299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:46.918550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 303
71.5%
지역구분명 46
 
10.8%
일반상업지역 30
 
7.1%
상업지역 16
 
3.8%
중심상업지역 12
 
2.8%
녹지지역 8
 
1.9%
일반주거지역 4
 
0.9%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct11
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
161 
5
53 
2
47 
지하층수
43 
1
35 
Other values (6)
85 

Length

Max length4
Median length1
Mean length2.4481132
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 161
38.0%
5 53
 
12.5%
2 47
 
11.1%
지하층수 43
 
10.1%
1 35
 
8.3%
3 24
 
5.7%
4 21
 
5.0%
6 20
 
4.7%
8 18
 
4.2%
58 1
 
0.2%

Length

2024-04-16T20:40:47.044524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 161
38.0%
5 53
 
12.5%
2 47
 
11.1%
지하층수 43
 
10.1%
1 35
 
8.3%
3 24
 
5.7%
4 21
 
5.0%
6 20
 
4.7%
8 18
 
4.2%
58 1
 
0.2%

bgroomcnt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
청소년실수
48 

Length

Max length5
Median length4
Mean length4.1132075
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
청소년실수 48
 
11.3%

Length

2024-04-16T20:40:47.180737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:47.279391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
청소년실수 48
 
11.3%

bgroomyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:47.395703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:47.483148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

totgasyscnt
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
총게임기수
48 

Length

Max length5
Median length4
Mean length4.1132075
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
총게임기수 48
 
11.3%

Length

2024-04-16T20:40:47.573621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:47.691655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
총게임기수 48
 
11.3%

totnumlay
Categorical

Distinct18
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
240 
총층수
44 
10
 
20
9
 
12
6
 
12
Other values (13)
96 

Length

Max length4
Median length4
Mean length3.1580189
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> 240
56.6%
총층수 44
 
10.4%
10 20
 
4.7%
9 12
 
2.8%
6 12
 
2.8%
11 12
 
2.8%
18 11
 
2.6%
19 10
 
2.4%
15 9
 
2.1%
54 9
 
2.1%
Other values (8) 45
 
10.6%

Length

2024-04-16T20:40:47.822240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 240
56.6%
총층수 44
 
10.4%
10 20
 
4.7%
9 12
 
2.8%
6 12
 
2.8%
11 12
 
2.8%
18 11
 
2.6%
19 10
 
2.4%
54 9
 
2.1%
15 9
 
2.1%
Other values (8) 45
 
10.6%

frstregts
Real number (ℝ)

Distinct137
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20108536
Minimum19451015
Maximum20210527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-16T20:40:47.945726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000518
Q120050111
median20110513
Q320190322
95-th percentile20210119
Maximum20210527
Range759512
Interquartile range (IQR)140211

Descriptive statistics

Standard deviation89604.952
Coefficient of variation (CV)0.0044560655
Kurtosis8.8362316
Mean20108536
Median Absolute Deviation (MAD)79754
Skewness-1.7481765
Sum8.5260192 × 109
Variance8.0290474 × 109
MonotonicityNot monotonic
2024-04-16T20:40:48.098256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.8%
20190315 12
 
2.8%
20140822 11
 
2.6%
20010609 11
 
2.6%
20071204 10
 
2.4%
20090302 10
 
2.4%
20021112 10
 
2.4%
20050307 10
 
2.4%
20061023 9
 
2.1%
20200103 9
 
2.1%
Other values (127) 320
75.5%
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 (%)
20210527 1
0.2%
20210521 2
0.5%
20210513 2
0.5%
20210512 1
0.2%
20210405 1
0.2%
20210330 1
0.2%
20210329 1
0.2%
20210318 1
0.2%
20210317 1
0.2%
20210315 1
0.2%

pasgbreth
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
234 
1
102 
통로너비
43 
1.5
 
12
1.2
 
7
Other values (13)
26 

Length

Max length4
Median length4
Mean length3.2122642
Min length1

Unique

Unique8 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 234
55.2%
1 102
24.1%
통로너비 43
 
10.1%
1.5 12
 
2.8%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
0.9%
1.3 4
 
0.9%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
1.9%

Length

2024-04-16T20:40:48.288713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 234
55.2%
1 102
24.1%
통로너비 43
 
10.1%
1.5 12
 
2.8%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
0.9%
1.3 4
 
0.9%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
1.9%

speclghtyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:48.424498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:48.548599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
48 

Length

Max length4
Median length4
Mean length3.6603774
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
48
 
11.3%

Length

2024-04-16T20:40:48.682008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:48.817291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
48
 
11.3%

actlnm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
376 
품목명
48 

Length

Max length4
Median length4
Mean length3.8867925
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
88.7%
품목명 48
 
11.3%

Length

2024-04-16T20:40:48.939060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:49.059896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
88.7%
품목명 48
 
11.3%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2021-06-01 05:20:03
424 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-06-01 05:20:03
2nd row2021-06-01 05:20:03
3rd row2021-06-01 05:20:03
4th row2021-06-01 05:20:03
5th row2021-06-01 05:20:03

Common Values

ValueCountFrequency (%)
2021-06-01 05:20:03 424
100.0%

Length

2024-04-16T20:40:49.164140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:40:49.279465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 424
50.0%
05:20:03 424
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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
41430163400000CDFF521101202100000103_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/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2021-06-01 05:20:03
41530173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2021-06-01 05:20:03
41630183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2021-06-01 05:20:03
41730193360000CDFF521104202100000103_13_03_PI2021-05-14 00:22:56.0영화상영업롯데시네마 부산 명지점지번우편번호부산광역시 강서구 명지동 3432-346726부산광역시 강서구 명지국제6로 107, 부산명지 대방디엠시티 센텀오션 2차 2층 (명지동)20210512폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중374253.112341178757.42327120210512174838업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2021-06-01 05:20:03
41830203330000CDFF521103202100000303_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/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2021-06-01 05:20:03
41930213330000CDFF521101202100000503_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>2021-06-01 05:20:03
42030223250000CDFF521102202100000103_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>2021-06-01 05:20:03
42130233250000CDFF521103202100000103_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>2021-06-01 05:20:03
42230243250000CDFF521101202100000203_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>2021-06-01 05:20:03
42330253290000CDFF521104202100000103_13_03_PI2021-05-23 00:22:56.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210521093521업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2021-06-01 05:20:03