Overview

Dataset statistics

Number of variables56
Number of observations508
Missing cells41
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory225.9 KiB
Average record size in memory455.3 B

Variable types

Numeric7
Text5
Categorical42
DateTime2

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (72.7%)Imbalance
dcbymd is highly imbalanced (62.6%)Imbalance
trdstatenm is highly imbalanced (56.2%)Imbalance
dtlstatenm is highly imbalanced (63.6%)Imbalance
regnsenm is highly imbalanced (52.7%)Imbalance
rdnpostno has 21 (4.1%) missing valuesMissing
rdnwhladdr has 6 (1.2%) missing valuesMissing
x has 6 (1.2%) missing valuesMissing
y has 6 (1.2%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:35:36.682101
Analysis finished2024-04-16 11:35:37.823124
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct508
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1091.5728
Minimum1
Maximum3115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:37.880145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.35
Q1127.75
median254.5
Q32131.25
95-th percentile3089.65
Maximum3115
Range3114
Interquartile range (IQR)2003.5

Descriptive statistics

Standard deviation1213.0496
Coefficient of variation (CV)1.111286
Kurtosis-1.191848
Mean1091.5728
Median Absolute Deviation (MAD)228
Skewness0.73627446
Sum554519
Variance1471489.4
MonotonicityNot monotonic
2024-04-16T20:35:37.995569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
1427 1
 
0.2%
1648 1
 
0.2%
1647 1
 
0.2%
1645 1
 
0.2%
1643 1
 
0.2%
1576 1
 
0.2%
1571 1
 
0.2%
1542 1
 
0.2%
1525 1
 
0.2%
Other values (498) 498
98.0%
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 (%)
3115 1
0.2%
3114 1
0.2%
3113 1
0.2%
3112 1
0.2%
3111 1
0.2%
3110 1
0.2%
3109 1
0.2%
3108 1
0.2%
3107 1
0.2%
3106 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3321358.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:38.119628image/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 deviation40939.721
Coefficient of variation (CV)0.012326198
Kurtosis-0.53037488
Mean3321358.3
Median Absolute Deviation (MAD)30000
Skewness0.065482663
Sum1.68725 × 109
Variance1.6760607 × 109
MonotonicityNot monotonic
2024-04-16T20:35:38.218966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 134
26.4%
3290000 88
17.3%
3250000 56
11.0%
3300000 30
 
5.9%
3320000 29
 
5.7%
3380000 29
 
5.7%
3350000 28
 
5.5%
3400000 28
 
5.5%
3310000 21
 
4.1%
3390000 15
 
3.0%
Other values (5) 50
 
9.8%
ValueCountFrequency (%)
3250000 56
11.0%
3260000 2
 
0.4%
3270000 9
 
1.8%
3290000 88
17.3%
3300000 30
 
5.9%
3310000 21
 
4.1%
3320000 29
 
5.7%
3330000 134
26.4%
3340000 13
 
2.6%
3350000 28
 
5.5%
ValueCountFrequency (%)
3400000 28
 
5.5%
3390000 15
 
3.0%
3380000 29
 
5.7%
3370000 12
 
2.4%
3360000 14
 
2.8%
3350000 28
 
5.5%
3340000 13
 
2.6%
3330000 134
26.4%
3320000 29
 
5.7%
3310000 21
 
4.1%

mgtno
Text

Distinct259
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-04-16T20:35:38.414759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters10160
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

Unique148 ?
Unique (%)29.1%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
3.5%
cdff5211012021000001 13
 
2.6%
cdff5211012019000001 12
 
2.4%
cdff5211012022000001 12
 
2.4%
cdff5211012020000002 9
 
1.8%
cdff5211012021000002 9
 
1.8%
cdff5211042021000001 8
 
1.6%
cdff5211012022000002 8
 
1.6%
cdff5211032020000001 8
 
1.6%
cdff5211032019000001 8
 
1.6%
Other values (249) 403
79.3%
2024-04-16T20:35:38.714950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4376
43.1%
2 1607
 
15.8%
1 1035
 
10.2%
F 1016
 
10.0%
C 508
 
5.0%
D 508
 
5.0%
4 397
 
3.9%
5 273
 
2.7%
9 135
 
1.3%
3 95
 
0.9%
Other values (3) 210
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8128
80.0%
Uppercase Letter 2032
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4376
53.8%
2 1607
 
19.8%
1 1035
 
12.7%
4 397
 
4.9%
5 273
 
3.4%
9 135
 
1.7%
3 95
 
1.2%
7 84
 
1.0%
6 67
 
0.8%
8 59
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
F 1016
50.0%
C 508
25.0%
D 508
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8128
80.0%
Latin 2032
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4376
53.8%
2 1607
 
19.8%
1 1035
 
12.7%
4 397
 
4.9%
5 273
 
3.4%
9 135
 
1.7%
3 95
 
1.2%
7 84
 
1.0%
6 67
 
0.8%
8 59
 
0.7%
Latin
ValueCountFrequency (%)
F 1016
50.0%
C 508
25.0%
D 508
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4376
43.1%
2 1607
 
15.8%
1 1035
 
10.2%
F 1016
 
10.0%
C 508
 
5.0%
D 508
 
5.0%
4 397
 
3.9%
5 273
 
2.7%
9 135
 
1.3%
3 95
 
0.9%
Other values (3) 210
 
2.1%

opnsvcid
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
03_13_02_P
302 
03_13_05_P
141 
03_13_01_P
33 
03_13_03_P
 
24
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 302
59.4%
03_13_05_P 141
27.8%
03_13_01_P 33
 
6.5%
03_13_03_P 24
 
4.7%
03_13_04_P 8
 
1.6%

Length

2024-04-16T20:35:38.835218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:38.935975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 302
59.4%
03_13_05_p 141
27.8%
03_13_01_p 33
 
6.5%
03_13_03_p 24
 
4.7%
03_13_04_p 8
 
1.6%

updategbn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
U
255 
I
253 

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 (%)
U 255
50.2%
I 253
49.8%

Length

2024-04-16T20:35:39.054073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:39.128770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 255
50.2%
i 253
49.8%
Distinct144
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum2018-08-31 23:59:59
Maximum2022-08-21 00:22:27
2024-04-16T20:35:39.216041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:35:39.354244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영화상영관
205 
영화제작업
141 
<NA>
97 
영화배급업
33 
영화상영업
24 

Length

Max length5
Median length5
Mean length4.8090551
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 205
40.4%
영화제작업 141
27.8%
<NA> 97
19.1%
영화배급업 33
 
6.5%
영화상영업 24
 
4.7%
영화수입업 8
 
1.6%

Length

2024-04-16T20:35:39.477475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:39.566003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 205
40.4%
영화제작업 141
27.8%
na 97
19.1%
영화배급업 33
 
6.5%
영화상영업 24
 
4.7%
영화수입업 8
 
1.6%

bplcnm
Text

Distinct418
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-04-16T20:35:39.725802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length10.779528
Min length2

Characters and Unicode

Total characters5476
Distinct characters281
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

Unique368 ?
Unique (%)72.4%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 85
 
7.8%
메가박스 48
 
4.4%
주식회사 47
 
4.3%
cgv 42
 
3.8%
해운대 26
 
2.4%
서면 21
 
1.9%
센텀시티 19
 
1.7%
2관 17
 
1.6%
6관 17
 
1.6%
4관 16
 
1.5%
Other values (267) 755
69.1%
2024-04-16T20:35:40.016775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
587
 
10.7%
329
 
6.0%
163
 
3.0%
150
 
2.7%
149
 
2.7%
143
 
2.6%
139
 
2.5%
124
 
2.3%
C 111
 
2.0%
) 106
 
1.9%
Other values (271) 3475
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3877
70.8%
Space Separator 587
 
10.7%
Uppercase Letter 464
 
8.5%
Decimal Number 298
 
5.4%
Close Punctuation 107
 
2.0%
Open Punctuation 107
 
2.0%
Lowercase Letter 23
 
0.4%
Other Punctuation 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
329
 
8.5%
163
 
4.2%
150
 
3.9%
149
 
3.8%
143
 
3.7%
139
 
3.6%
124
 
3.2%
101
 
2.6%
100
 
2.6%
81
 
2.1%
Other values (222) 2398
61.9%
Uppercase Letter
ValueCountFrequency (%)
C 111
23.9%
G 90
19.4%
V 88
19.0%
N 26
 
5.6%
E 16
 
3.4%
O 16
 
3.4%
I 13
 
2.8%
M 12
 
2.6%
A 12
 
2.6%
T 11
 
2.4%
Other values (13) 69
14.9%
Decimal Number
ValueCountFrequency (%)
1 47
15.8%
2 44
14.8%
4 40
13.4%
3 34
11.4%
6 33
11.1%
5 32
10.7%
7 25
8.4%
8 18
 
6.0%
9 17
 
5.7%
0 8
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
o 7
30.4%
d 5
21.7%
t 4
17.4%
m 3
13.0%
i 1
 
4.3%
s 1
 
4.3%
l 1
 
4.3%
g 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 106
99.1%
] 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 106
99.1%
[ 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
587
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3877
70.8%
Common 1112
 
20.3%
Latin 487
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
329
 
8.5%
163
 
4.2%
150
 
3.9%
149
 
3.8%
143
 
3.7%
139
 
3.6%
124
 
3.2%
101
 
2.6%
100
 
2.6%
81
 
2.1%
Other values (222) 2398
61.9%
Latin
ValueCountFrequency (%)
C 111
22.8%
G 90
18.5%
V 88
18.1%
N 26
 
5.3%
E 16
 
3.3%
O 16
 
3.3%
I 13
 
2.7%
M 12
 
2.5%
A 12
 
2.5%
T 11
 
2.3%
Other values (21) 92
18.9%
Common
ValueCountFrequency (%)
587
52.8%
) 106
 
9.5%
( 106
 
9.5%
1 47
 
4.2%
2 44
 
4.0%
4 40
 
3.6%
3 34
 
3.1%
6 33
 
3.0%
5 32
 
2.9%
7 25
 
2.2%
Other values (8) 58
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3877
70.8%
ASCII 1599
29.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
587
36.7%
C 111
 
6.9%
) 106
 
6.6%
( 106
 
6.6%
G 90
 
5.6%
V 88
 
5.5%
1 47
 
2.9%
2 44
 
2.8%
4 40
 
2.5%
3 34
 
2.1%
Other values (39) 346
21.6%
Hangul
ValueCountFrequency (%)
329
 
8.5%
163
 
4.2%
150
 
3.9%
149
 
3.8%
143
 
3.7%
139
 
3.6%
124
 
3.2%
101
 
2.6%
100
 
2.6%
81
 
2.1%
Other values (222) 2398
61.9%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
391 
지번우편번호
95 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.4606299
Min length4

Unique

Unique10 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 391
77.0%
지번우편번호 95
 
18.7%
614845 4
 
0.8%
600805 3
 
0.6%
601060 3
 
0.6%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.2%

Length

2024-04-16T20:35:40.130923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 391
77.0%
지번우편번호 95
 
18.7%
614845 4
 
0.8%
600805 3
 
0.6%
601060 3
 
0.6%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.2%
Distinct177
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-04-16T20:35:40.405578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length26.488189
Min length18

Characters and Unicode

Total characters13456
Distinct characters254
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

Unique85 ?
Unique (%)16.7%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1
3rd row부산광역시 중구 남포동5가 12-1
4th row부산광역시 중구 남포동5가 12-1
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
부산광역시 508
 
20.2%
해운대구 134
 
5.3%
우동 100
 
4.0%
부산진구 88
 
3.5%
72
 
2.9%
중구 56
 
2.2%
부전동 53
 
2.1%
동래구 30
 
1.2%
북구 29
 
1.2%
수영구 29
 
1.2%
Other values (342) 1419
56.4%
2024-04-16T20:35:40.817005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2468
18.3%
705
 
5.2%
663
 
4.9%
547
 
4.1%
547
 
4.1%
521
 
3.9%
510
 
3.8%
485
 
3.6%
1 469
 
3.5%
- 432
 
3.2%
Other values (244) 6109
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7771
57.8%
Space Separator 2468
 
18.3%
Decimal Number 2158
 
16.0%
Dash Punctuation 432
 
3.2%
Other Punctuation 432
 
3.2%
Uppercase Letter 150
 
1.1%
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 (%)
705
 
9.1%
663
 
8.5%
547
 
7.0%
547
 
7.0%
521
 
6.7%
510
 
6.6%
485
 
6.2%
207
 
2.7%
181
 
2.3%
178
 
2.3%
Other values (208) 3227
41.5%
Uppercase Letter
ValueCountFrequency (%)
K 35
23.3%
T 21
14.0%
S 19
12.7%
G 16
10.7%
B 11
 
7.3%
U 10
 
6.7%
H 10
 
6.7%
C 10
 
6.7%
Y 9
 
6.0%
N 8
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 469
21.7%
2 312
14.5%
5 227
10.5%
6 223
10.3%
4 199
9.2%
0 163
 
7.6%
8 158
 
7.3%
7 153
 
7.1%
3 142
 
6.6%
9 112
 
5.2%
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 (%)
* 399
92.4%
, 18
 
4.2%
& 15
 
3.5%
Space Separator
ValueCountFrequency (%)
2468
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 432
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 7771
57.8%
Common 5520
41.0%
Latin 165
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
705
 
9.1%
663
 
8.5%
547
 
7.0%
547
 
7.0%
521
 
6.7%
510
 
6.6%
485
 
6.2%
207
 
2.7%
181
 
2.3%
178
 
2.3%
Other values (208) 3227
41.5%
Common
ValueCountFrequency (%)
2468
44.7%
1 469
 
8.5%
- 432
 
7.8%
* 399
 
7.2%
2 312
 
5.7%
5 227
 
4.1%
6 223
 
4.0%
4 199
 
3.6%
0 163
 
3.0%
8 158
 
2.9%
Other values (8) 470
 
8.5%
Latin
ValueCountFrequency (%)
K 35
21.2%
T 21
12.7%
S 19
11.5%
G 16
9.7%
B 11
 
6.7%
U 10
 
6.1%
H 10
 
6.1%
C 10
 
6.1%
Y 9
 
5.5%
N 8
 
4.8%
Other values (8) 16
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7771
57.8%
ASCII 5685
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2468
43.4%
1 469
 
8.2%
- 432
 
7.6%
* 399
 
7.0%
2 312
 
5.5%
5 227
 
4.0%
6 223
 
3.9%
4 199
 
3.5%
0 163
 
2.9%
8 158
 
2.8%
Other values (26) 635
 
11.2%
Hangul
ValueCountFrequency (%)
705
 
9.1%
663
 
8.5%
547
 
7.0%
547
 
7.0%
521
 
6.7%
510
 
6.6%
485
 
6.2%
207
 
2.7%
181
 
2.3%
178
 
2.3%
Other values (208) 3227
41.5%

rdnpostno
Text

MISSING 

Distinct105
Distinct (%)21.6%
Missing21
Missing (%)4.1%
Memory size4.1 KiB
2024-04-16T20:35:41.251755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0082136
Min length5

Characters and Unicode

Total characters2439
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

Unique43 ?
Unique (%)8.8%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48058 53
 
10.9%
48947 49
 
10.1%
48953 20
 
4.1%
48059 16
 
3.3%
47296 16
 
3.3%
46726 14
 
2.9%
47299 12
 
2.5%
47288 12
 
2.5%
48944 11
 
2.3%
47285 11
 
2.3%
Other values (95) 273
56.1%
2024-04-16T20:35:41.562068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 631
25.9%
8 417
17.1%
7 248
 
10.2%
9 239
 
9.8%
5 182
 
7.5%
0 175
 
7.2%
2 174
 
7.1%
6 167
 
6.8%
1 101
 
4.1%
3 91
 
3.7%
Other values (7) 14
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2425
99.4%
Other Letter 14
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 631
26.0%
8 417
17.2%
7 248
 
10.2%
9 239
 
9.9%
5 182
 
7.5%
0 175
 
7.2%
2 174
 
7.2%
6 167
 
6.9%
1 101
 
4.2%
3 91
 
3.8%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2425
99.4%
Hangul 14
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
4 631
26.0%
8 417
17.2%
7 248
 
10.2%
9 239
 
9.9%
5 182
 
7.5%
0 175
 
7.2%
2 174
 
7.2%
6 167
 
6.9%
1 101
 
4.2%
3 91
 
3.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2425
99.4%
Hangul 14
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 631
26.0%
8 417
17.2%
7 248
 
10.2%
9 239
 
9.9%
5 182
 
7.5%
0 175
 
7.2%
2 174
 
7.2%
6 167
 
6.9%
1 101
 
4.2%
3 91
 
3.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

rdnwhladdr
Text

MISSING 

Distinct179
Distinct (%)35.7%
Missing6
Missing (%)1.2%
Memory size4.1 KiB
2024-04-16T20:35:41.823401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length33.541833
Min length22

Characters and Unicode

Total characters16838
Distinct characters284
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

Unique86 ?
Unique (%)17.1%

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 502
 
15.5%
해운대구 134
 
4.1%
우동 90
 
2.8%
부산진구 88
 
2.7%
72
 
2.2%
중앙대로 56
 
1.7%
중구 53
 
1.6%
부전동 53
 
1.6%
53
 
1.6%
해운대로 46
 
1.4%
Other values (452) 2097
64.6%
2024-04-16T20:35:42.199078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2767
 
16.4%
718
 
4.3%
670
 
4.0%
622
 
3.7%
564
 
3.3%
560
 
3.3%
504
 
3.0%
497
 
3.0%
* 495
 
2.9%
( 492
 
2.9%
Other values (274) 8949
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9952
59.1%
Space Separator 2767
 
16.4%
Decimal Number 1946
 
11.6%
Other Punctuation 966
 
5.7%
Open Punctuation 495
 
2.9%
Close Punctuation 495
 
2.9%
Uppercase Letter 159
 
0.9%
Dash Punctuation 30
 
0.2%
Lowercase Letter 16
 
0.1%
Math Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
718
 
7.2%
670
 
6.7%
622
 
6.2%
564
 
5.7%
560
 
5.6%
504
 
5.1%
497
 
5.0%
489
 
4.9%
395
 
4.0%
216
 
2.2%
Other values (233) 4717
47.4%
Uppercase Letter
ValueCountFrequency (%)
K 35
22.0%
T 21
13.2%
S 19
11.9%
G 15
9.4%
B 12
 
7.5%
C 11
 
6.9%
H 10
 
6.3%
U 10
 
6.3%
Y 9
 
5.7%
N 8
 
5.0%
Other values (3) 9
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 367
18.9%
2 268
13.8%
3 215
11.0%
0 215
11.0%
6 168
8.6%
5 164
8.4%
7 158
8.1%
4 149
7.7%
9 122
 
6.3%
8 120
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
r 2
 
12.5%
h 2
 
12.5%
p 1
 
6.2%
l 1
 
6.2%
i 1
 
6.2%
v 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
* 495
51.2%
, 456
47.2%
& 15
 
1.6%
Open Punctuation
ValueCountFrequency (%)
( 492
99.4%
[ 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 492
99.4%
] 3
 
0.6%
Space Separator
ValueCountFrequency (%)
2767
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9952
59.1%
Common 6711
39.9%
Latin 175
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
718
 
7.2%
670
 
6.7%
622
 
6.2%
564
 
5.7%
560
 
5.6%
504
 
5.1%
497
 
5.0%
489
 
4.9%
395
 
4.0%
216
 
2.2%
Other values (233) 4717
47.4%
Latin
ValueCountFrequency (%)
K 35
20.0%
T 21
12.0%
S 19
10.9%
G 15
8.6%
B 12
 
6.9%
C 11
 
6.3%
H 10
 
5.7%
U 10
 
5.7%
Y 9
 
5.1%
N 8
 
4.6%
Other values (11) 25
14.3%
Common
ValueCountFrequency (%)
2767
41.2%
* 495
 
7.4%
( 492
 
7.3%
) 492
 
7.3%
, 456
 
6.8%
1 367
 
5.5%
2 268
 
4.0%
3 215
 
3.2%
0 215
 
3.2%
6 168
 
2.5%
Other values (10) 776
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9952
59.1%
ASCII 6886
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2767
40.2%
* 495
 
7.2%
( 492
 
7.1%
) 492
 
7.1%
, 456
 
6.6%
1 367
 
5.3%
2 268
 
3.9%
3 215
 
3.1%
0 215
 
3.1%
6 168
 
2.4%
Other values (31) 951
 
13.8%
Hangul
ValueCountFrequency (%)
718
 
7.2%
670
 
6.7%
622
 
6.2%
564
 
5.7%
560
 
5.6%
504
 
5.1%
497
 
5.0%
489
 
4.9%
395
 
4.0%
216
 
2.2%
Other values (233) 4717
47.4%

apvpermymd
Real number (ℝ)

Distinct176
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20126098
Minimum19451015
Maximum20220819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:42.328502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060901
median20161013
Q320200330
95-th percentile20220125
Maximum20220819
Range769804
Interquartile range (IQR)139429.25

Descriptive statistics

Standard deviation89923.085
Coefficient of variation (CV)0.004467984
Kurtosis8.1645283
Mean20126098
Median Absolute Deviation (MAD)50202
Skewness-1.7689249
Sum1.0224058 × 1010
Variance8.0861613 × 109
MonotonicityNot monotonic
2024-04-16T20:35:42.449902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190315 12
 
2.4%
20211215 12
 
2.4%
20000529 12
 
2.4%
20010609 11
 
2.2%
20140822 11
 
2.2%
20050307 10
 
2.0%
20090302 10
 
2.0%
20210615 10
 
2.0%
20071204 10
 
2.0%
20021112 10
 
2.0%
Other values (166) 400
78.7%
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 (%)
20220819 2
0.4%
20220729 2
0.4%
20220728 1
0.2%
20220627 1
0.2%
20220624 2
0.4%
20220623 2
0.4%
20220621 2
0.4%
20220511 1
0.2%
20220427 2
0.4%
20220426 1
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct40
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
338 
폐업일자
90 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (35)
54 

Length

Max length8
Median length4
Mean length4.6299213
Min length4

Unique

Unique27 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 338
66.5%
폐업일자 90
 
17.7%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20200921 3
 
0.6%
20070725 3
 
0.6%
20210806 3
 
0.6%
Other values (30) 34
 
6.7%

Length

2024-04-16T20:35:42.579263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 338
66.5%
폐업일자 90
 
17.7%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20200921 3
 
0.6%
20070725 3
 
0.6%
20211217 3
 
0.6%
Other values (30) 34
 
6.7%

clgstdt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
휴업시작일자
95 

Length

Max length6
Median length4
Mean length4.3740157
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
휴업시작일자 95
 
18.7%

Length

2024-04-16T20:35:42.686594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:42.769941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
휴업시작일자 95
 
18.7%

clgenddt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
휴업종료일자
95 

Length

Max length6
Median length4
Mean length4.3740157
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
휴업종료일자 95
 
18.7%

Length

2024-04-16T20:35:42.872865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:42.974044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
휴업종료일자 95
 
18.7%

ropnymd
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
재개업일자
95 

Length

Max length5
Median length4
Mean length4.1870079
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
재개업일자 95
 
18.7%

Length

2024-04-16T20:35:43.078654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:43.182704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
재개업일자 95
 
18.7%

trdstatenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영업/정상
386 
03
56 
13
40 
폐업
 
15
제외/삭제/전출
 
9
Other values (2)
 
2

Length

Max length8
Median length5
Mean length4.3897638
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 386
76.0%
03 56
 
11.0%
13 40
 
7.9%
폐업 15
 
3.0%
제외/삭제/전출 9
 
1.8%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:35:43.292173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:43.394742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 386
76.0%
03 56
 
11.0%
13 40
 
7.9%
폐업 15
 
3.0%
제외/삭제/전출 9
 
1.8%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영업중
427 
폐업
71 
전출
 
9
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8444882
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 427
84.1%
폐업 71
 
14.0%
전출 9
 
1.8%
직권말소 1
 
0.2%

Length

2024-04-16T20:35:43.505186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:43.605172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 427
84.1%
폐업 71
 
14.0%
전출 9
 
1.8%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct144
Distinct (%)28.7%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean389645.61
Minimum373470.6
Maximum401669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:43.716422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373470.6
5-th percentile379293.93
Q1385622.78
median389751.94
Q3393674.03
95-th percentile398308.51
Maximum401669
Range28198.396
Interquartile range (IQR)8051.2525

Descriptive statistics

Standard deviation5805.1191
Coefficient of variation (CV)0.014898459
Kurtosis0.12365739
Mean389645.61
Median Absolute Deviation (MAD)3972.7178
Skewness-0.35412266
Sum1.9560209 × 108
Variance33699408
MonotonicityNot monotonic
2024-04-16T20:35:43.830642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 24
 
4.7%
388011.197829908 12
 
2.4%
387608.014165034 11
 
2.2%
387271.299492377 11
 
2.2%
385622.780457355 11
 
2.2%
396915.143441 10
 
2.0%
393952.264486105 10
 
2.0%
398310.243451 10
 
2.0%
394083.501537578 10
 
2.0%
389816.233000769 9
 
1.8%
Other values (134) 384
75.6%
ValueCountFrequency (%)
373470.60373869 7
1.4%
374253.112340712 7
1.4%
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.0%
379240.573215267 3
0.6%
379280.632039 2
 
0.4%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380509.783073762 7
1.4%
ValueCountFrequency (%)
401669.0 6
1.2%
401646.70301259 3
 
0.6%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398757.078098629 1
 
0.2%
398628.503470003 2
 
0.4%
398330.516530402 2
 
0.4%
398310.243451 10
2.0%
398275.475596001 1
 
0.2%
398269.05154158 7
1.4%

y
Real number (ℝ)

MISSING 

Distinct144
Distinct (%)28.7%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean187529.17
Minimum178757.42
Maximum206353.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:43.943645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178757.42
5-th percentile179452.22
Q1185310.71
median187480.44
Q3189911.43
95-th percentile195491.52
Maximum206353.86
Range27596.432
Interquartile range (IQR)4600.7252

Descriptive statistics

Standard deviation5368.7662
Coefficient of variation (CV)0.028628966
Kurtosis1.9465273
Mean187529.17
Median Absolute Deviation (MAD)2169.7385
Skewness0.92628113
Sum94139645
Variance28823651
MonotonicityNot monotonic
2024-04-16T20:35:44.050010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 24
 
4.7%
185310.70532509 12
 
2.4%
185703.079007724 11
 
2.2%
186099.137533193 11
 
2.2%
179452.224754792 11
 
2.2%
187480.443811 10
 
2.0%
187602.933160728 10
 
2.0%
188031.67198 10
 
2.0%
187707.586117775 10
 
2.0%
193329.605871168 9
 
1.8%
Other values (134) 384
75.6%
ValueCountFrequency (%)
178757.423271048 7
1.4%
178872.461747926 1
 
0.2%
178919.583231221 7
1.4%
179411.189506548 1
 
0.2%
179452.224754792 11
2.2%
179597.592953541 6
1.2%
179823.23303496 4
 
0.8%
179885.813689 2
 
0.4%
179911.285409 5
1.0%
179919.437009 4
 
0.8%
ValueCountFrequency (%)
206353.855586145 2
 
0.4%
204621.655738547 5
1.0%
204597.0 5
1.0%
204401.691446 6
1.2%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
1.6%
195029.489621392 1
 
0.2%
194992.355262 2
 
0.4%
194681.150958776 7
1.4%

lastmodts
Real number (ℝ)

Distinct404
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0194845 × 1013
Minimum2.0030127 × 1013
Maximum2.0220819 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:44.164731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0190322 × 1013
median2.0210423 × 1013
Q32.0211218 × 1013
95-th percentile2.0220427 × 1013
Maximum2.0220819 × 1013
Range1.9069194 × 1011
Interquartile range (IQR)2.089579 × 1010

Descriptive statistics

Standard deviation3.3811364 × 1010
Coefficient of variation (CV)0.0016742572
Kurtosis7.2324036
Mean2.0194845 × 1013
Median Absolute Deviation (MAD)8.0555137 × 108
Skewness-2.6022953
Sum1.0258981 × 1016
Variance1.1432083 × 1021
MonotonicityNot monotonic
2024-04-16T20:35:44.289609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211220133307 6
 
1.2%
20190920121341 5
 
1.0%
20211220133338 5
 
1.0%
20210421091411 5
 
1.0%
20191017170859 4
 
0.8%
20211220161532 4
 
0.8%
20211221180318 4
 
0.8%
20211220133308 4
 
0.8%
20030127161348 4
 
0.8%
20211217153628 4
 
0.8%
Other values (394) 463
91.1%
ValueCountFrequency (%)
20030127161348 4
0.8%
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 (%)
20220819102726 2
0.4%
20220811170555 1
0.2%
20220810130445 1
0.2%
20220809131921 1
0.2%
20220729110036 2
0.4%
20220728163632 1
0.2%
20220708111314 1
0.2%
20220708111017 1
0.2%
20220708110636 1
0.2%
20220708110453 1
0.2%

uptaenm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
업태구분명
95 

Length

Max length5
Median length4
Mean length4.1870079
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
업태구분명 95
 
18.7%

Length

2024-04-16T20:35:44.420056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:44.511711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
업태구분명 95
 
18.7%

sitetel
Categorical

Distinct44
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
051-123-1234
191 
<NA>
92 
전화번호
55 
910-1411
 
12
070-7495-8542
 
11
Other values (39)
147 

Length

Max length13
Median length12
Mean length9.4783465
Min length4

Unique

Unique14 ?
Unique (%)2.8%

Sample

1st row051-123-1234
2nd row070-7438-5100
3rd row070-7438-5100
4th row070-7438-5100
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 191
37.6%
<NA> 92
18.1%
전화번호 55
 
10.8%
910-1411 12
 
2.4%
070-7495-8542 11
 
2.2%
810-3941 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
051-507-0202 7
 
1.4%
364-0480 7
 
1.4%
Other values (34) 105
20.7%

Length

2024-04-16T20:35:44.614537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 191
37.6%
na 92
18.1%
전화번호 55
 
10.8%
910-1411 12
 
2.4%
070-7495-8542 11
 
2.2%
810-3941 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
070-4159-8881 7
 
1.4%
070-7465-3972 7
 
1.4%
Other values (34) 105
20.7%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
306 
문화시설
88 
건물용도명
85 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.1929134
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 306
60.2%
문화시설 88
 
17.3%
건물용도명 85
 
16.7%
근린생활시설 13
 
2.6%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

Length

2024-04-16T20:35:44.723783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:44.839024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 306
60.2%
문화시설 88
 
17.3%
건물용도명 85
 
16.7%
근린생활시설 13
 
2.6%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영화관
294 
<NA>
132 
공연장형태구분명
78 
자동차극장
 
4

Length

Max length8
Median length3
Mean length4.0433071
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 294
57.9%
<NA> 132
26.0%
공연장형태구분명 78
 
15.4%
자동차극장 4
 
0.8%

Length

2024-04-16T20:35:44.946504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:45.055590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 294
57.9%
na 132
26.0%
공연장형태구분명 78
 
15.4%
자동차극장 4
 
0.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
기존게임업외업종명
95 

Length

Max length9
Median length4
Mean length4.9350394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
기존게임업외업종명 95
 
18.7%

Length

2024-04-16T20:35:45.176182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:45.261708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
기존게임업외업종명 95
 
18.7%

noroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
343 
0
99 
노래방실수
66 

Length

Max length5
Median length4
Mean length3.5452756
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 343
67.5%
0 99
 
19.5%
노래방실수 66
 
13.0%

Length

2024-04-16T20:35:45.372213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:45.475312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
67.5%
0 99
 
19.5%
노래방실수 66
 
13.0%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
222 
영화상영관
196 
문화사업자구분명
90 

Length

Max length8
Median length5
Mean length5.0944882
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 222
43.7%
영화상영관 196
38.6%
문화사업자구분명 90
17.7%

Length

2024-04-16T20:35:45.582085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:45.690648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
43.7%
영화상영관 196
38.6%
문화사업자구분명 90
17.7%

culphyedcobnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영화상영관
302 
영화제작업
139 
영화배급업
33 
영화상영업
 
24
영화수입업
 
8

Length

Max length5
Median length5
Mean length4.996063
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 302
59.4%
영화제작업 139
27.4%
영화배급업 33
 
6.5%
영화상영업 24
 
4.7%
영화수입업 8
 
1.6%
<NA> 2
 
0.4%

Length

2024-04-16T20:35:45.805123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:45.895400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 302
59.4%
영화제작업 139
27.4%
영화배급업 33
 
6.5%
영화상영업 24
 
4.7%
영화수입업 8
 
1.6%
na 2
 
0.4%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:45.989762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:46.070532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

vdoretornm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
비디오재생기명
95 

Length

Max length7
Median length4
Mean length4.5610236
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
비디오재생기명 95
 
18.7%

Length

2024-04-16T20:35:46.154915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:46.270929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
비디오재생기명 95
 
18.7%

emerstairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:46.355816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:46.434414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

emexyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:46.541858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:46.640119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

firefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:46.742895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:46.836358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

facilar
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
337 
0
99 
시설면적
66 
1578.8
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.4370079
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
66.3%
0 99
 
19.5%
시설면적 66
 
13.0%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:35:46.936420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:47.031544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
66.3%
0 99
 
19.5%
시설면적 66
 
13.0%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:47.138293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:47.248336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

autochaairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:47.642640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:47.736856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
제공게임물명
95 

Length

Max length6
Median length4
Mean length4.3740157
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
제공게임물명 95
 
18.7%

Length

2024-04-16T20:35:47.860501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:47.980862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
제공게임물명 95
 
18.7%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
제작취급품목내용
95 

Length

Max length8
Median length4
Mean length4.7480315
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
제작취급품목내용 95
 
18.7%

Length

2024-04-16T20:35:48.128039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:48.233090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
제작취급품목내용 95
 
18.7%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:48.329441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:48.417552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

lghtfacilinillu
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
343 
0
99 
조명시설조도
66 

Length

Max length6
Median length4
Mean length3.6751969
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 343
67.5%
0 99
 
19.5%
조명시설조도 66
 
13.0%

Length

2024-04-16T20:35:48.512949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:48.610413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
67.5%
0 99
 
19.5%
조명시설조도 66
 
13.0%

nearenvnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
358 
주변환경명
89 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.2244094
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 358
70.5%
주변환경명 89
 
17.5%
기타 32
 
6.3%
유흥업소밀집지역 18
 
3.5%
아파트지역 9
 
1.8%
학교정화(상대) 2
 
0.4%

Length

2024-04-16T20:35:48.714693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:48.822145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 358
70.5%
주변환경명 89
 
17.5%
기타 32
 
6.3%
유흥업소밀집지역 18
 
3.5%
아파트지역 9
 
1.8%
학교정화(상대 2
 
0.4%

jisgnumlay
Categorical

Distinct23
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
151 
지상층수
56 
0
54 
10
43 
7
28 
Other values (18)
176 

Length

Max length4
Median length2
Mean length2.4783465
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
29.7%
지상층수 56
 
11.0%
0 54
 
10.6%
10 43
 
8.5%
7 28
 
5.5%
9 27
 
5.3%
5 20
 
3.9%
8 19
 
3.7%
42 17
 
3.3%
13 15
 
3.0%
Other values (13) 78
15.4%

Length

2024-04-16T20:35:48.924916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
29.7%
지상층수 56
 
11.0%
0 54
 
10.6%
10 43
 
8.5%
7 28
 
5.5%
9 27
 
5.3%
5 20
 
3.9%
8 19
 
3.7%
42 17
 
3.3%
13 15
 
3.0%
Other values (13) 78
15.4%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
345 
지역구분명
88 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3700787
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 345
67.9%
지역구분명 88
 
17.3%
일반상업지역 30
 
5.9%
상업지역 16
 
3.1%
중심상업지역 12
 
2.4%
녹지지역 8
 
1.6%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:35:49.035653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:49.146477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 345
67.9%
지역구분명 88
 
17.3%
일반상업지역 30
 
5.9%
상업지역 16
 
3.1%
중심상업지역 12
 
2.4%
녹지지역 8
 
1.6%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
159 
5
65 
지하층수
57 
0
54 
2
53 
Other values (7)
120 

Length

Max length4
Median length1
Mean length2.2795276
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
31.3%
5 65
12.8%
지하층수 57
 
11.2%
0 54
 
10.6%
2 53
 
10.4%
1 35
 
6.9%
3 24
 
4.7%
4 21
 
4.1%
6 20
 
3.9%
8 18
 
3.5%
Other values (2) 2
 
0.4%

Length

2024-04-16T20:35:49.277238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 159
31.3%
5 65
12.8%
지하층수 57
 
11.2%
0 54
 
10.6%
2 53
 
10.4%
1 35
 
6.9%
3 24
 
4.7%
4 21
 
4.1%
6 20
 
3.9%
8 18
 
3.5%
Other values (2) 2
 
0.4%

bgroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
343 
0
99 
청소년실수
66 

Length

Max length5
Median length4
Mean length3.5452756
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 343
67.5%
0 99
 
19.5%
청소년실수 66
 
13.0%

Length

2024-04-16T20:35:49.405605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:49.494286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
67.5%
0 99
 
19.5%
청소년실수 66
 
13.0%

bgroomyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:49.602065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:49.685588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

totgasyscnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
343 
0
99 
총게임기수
66 

Length

Max length5
Median length4
Mean length3.5452756
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 343
67.5%
0 99
 
19.5%
총게임기수 66
 
13.0%

Length

2024-04-16T20:35:49.772588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:49.875959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
67.5%
0 99
 
19.5%
총게임기수 66
 
13.0%

totnumlay
Categorical

Distinct20
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
236 
0
61 
총층수
59 
10
 
20
12
 
13
Other values (15)
119 

Length

Max length4
Median length3
Mean length2.8602362
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 236
46.5%
0 61
 
12.0%
총층수 59
 
11.6%
10 20
 
3.9%
12 13
 
2.6%
9 12
 
2.4%
6 12
 
2.4%
11 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.2%

Length

2024-04-16T20:35:49.968713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 236
46.5%
0 61
 
12.0%
총층수 59
 
11.6%
10 20
 
3.9%
12 13
 
2.6%
9 12
 
2.4%
6 12
 
2.4%
11 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.2%

frstregts
Real number (ℝ)

Distinct175
Distinct (%)34.6%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean20125725
Minimum19451015
Maximum20220819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-04-16T20:35:50.074074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060850
median20161013
Q320200324
95-th percentile20220118
Maximum20220819
Range769804
Interquartile range (IQR)139473.5

Descriptive statistics

Standard deviation89904.433
Coefficient of variation (CV)0.00446714
Kurtosis8.1840479
Mean20125725
Median Absolute Deviation (MAD)50202
Skewness-1.7691657
Sum1.0183617 × 1010
Variance8.0828071 × 109
MonotonicityNot monotonic
2024-04-16T20:35:50.194664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.4%
20190315 12
 
2.4%
20211215 12
 
2.4%
20010609 11
 
2.2%
20140822 11
 
2.2%
20050307 10
 
2.0%
20210615 10
 
2.0%
20021112 10
 
2.0%
20090302 10
 
2.0%
20071204 10
 
2.0%
Other values (165) 398
78.3%
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 (%)
20220819 2
0.4%
20220729 2
0.4%
20220728 1
0.2%
20220627 1
0.2%
20220624 2
0.4%
20220623 2
0.4%
20220621 2
0.4%
20220511 1
0.2%
20220426 1
0.2%
20220405 2
0.4%

pasgbreth
Categorical

Distinct19
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
212 
1
103 
0
88 
통로너비
60 
1.5
 
12
Other values (14)
33 

Length

Max length4
Median length4
Mean length2.8169291
Min length1

Unique

Unique8 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 212
41.7%
1 103
20.3%
0 88
17.3%
통로너비 60
 
11.8%
1.5 12
 
2.4%
1.2 7
 
1.4%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.0%

Length

2024-04-16T20:35:50.317070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 212
41.7%
1 103
20.3%
0 88
17.3%
통로너비 60
 
11.8%
1.5 12
 
2.4%
1.2 7
 
1.4%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.0%

speclghtyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:50.431469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:50.508909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
95 

Length

Max length4
Median length4
Mean length3.4389764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
95
 
18.7%

Length

2024-04-16T20:35:50.599662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:50.691998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
95
 
18.7%

actlnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
413 
품목명
95 

Length

Max length4
Median length4
Mean length3.8129921
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
81.3%
품목명 95
 
18.7%

Length

2024-04-16T20:35:50.796696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:35:50.881697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
81.3%
품목명 95
 
18.7%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum2022-09-01 05:20:03
Maximum2022-09-01 05:20:03
2024-04-16T20:35:50.948684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:35:51.022685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
013250000CDFF422000200500000103_13_02_PI2018-08-31 23:59:59.0<NA>국도극장 예술관600805부산광역시 중구 부평동1가 45-9번지48947부산광역시 중구 중구로 13 (부평동1가)2005041520080501<NA><NA><NA>03폐업384872.100538179957.08923720080506140353<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>20050415<NA><NA><NA><NA>2022-09-01 05:20:03
123250000CDFF422000201700000303_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420211220135303<NA>070-7438-5100<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>2022-09-01 05:20:03
233250000CDFF422000201700000603_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420211220135540<NA>070-7438-5100<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>2022-09-01 05:20:03
343250000CDFF422000201700000503_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제5관지번우편번호부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중384985.448098179597.59295420211220135431업태구분명070-7438-5100건물용도명영화관기존게임업외업종명노래방실수문화사업자구분명영화상영관비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명6상업지역4청소년실수총게임기수총층수20170309통로너비품목명2022-09-01 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>2022-09-01 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>2022-09-01 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>2022-09-01 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>2022-09-01 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>2022-09-01 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>2022-09-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
49830183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2022-09-01 05:20:03
49930193360000CDFF521104202100000103_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/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2022-09-01 05:20:03
50030203330000CDFF521103202100000303_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/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2022-09-01 05:20:03
50130213330000CDFF521101202100000503_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>2022-09-01 05:20:03
50230223250000CDFF521102202100000103_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>2022-09-01 05:20:03
50330233250000CDFF521103202100000103_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>2022-09-01 05:20:03
50430243250000CDFF521101202100000203_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>2022-09-01 05:20:03
50530253290000CDFF521104202100000103_13_03_PU2021-09-19 02:40:00.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210917145721업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2022-09-01 05:20:03
50631143370000CDFF521101202200000103_13_05_PI2022-08-21 00:22:27.0영화제작업경 필름<NA>부산광역시 연제구 연산동 ***-* 한양아파트47566부산광역시 연제구 온천천남로 ***, **동 ***호 (연산동, 한양아파트)20220819<NA><NA><NA><NA>영업/정상영업중391504.565166189919.18534320220819102726<NA>051-759-1434<NA><NA><NA>0<NA>영화제작업<NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>00<NA>00202208190<NA><NA><NA>2022-09-01 05:20:03
50731153370000CDFF521101202200000103_13_05_PI2022-08-21 00:22:27.0영화제작업경 필름<NA>부산광역시 연제구 연산동 ***-* 한양아파트47566부산광역시 연제구 온천천남로 ***, **동 ***호 (연산동, 한양아파트)20220819<NA><NA><NA><NA>영업/정상영업중391504.565166189919.18534320220819102726<NA>051-759-1434<NA><NA><NA>0<NA>영화제작업<NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>00<NA>00202208190<NA><NA><NA>2022-09-01 05:20:03