Overview

Dataset statistics

Number of variables56
Number of observations490
Missing cells39
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory217.9 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 (71.8%)Imbalance
dcbymd is highly imbalanced (61.7%)Imbalance
trdstatenm is highly imbalanced (55.9%)Imbalance
dtlstatenm is highly imbalanced (63.6%)Imbalance
facilar is highly imbalanced (51.4%)Imbalance
regnsenm is highly imbalanced (51.4%)Imbalance
rdnpostno has 21 (4.3%) 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 11:38:02.749444
Analysis finished2024-04-16 11:38:03.648404
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct490
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1017.5551
Minimum1
Maximum3097
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:03.704275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.45
Q1123.25
median245.5
Q31995.75
95-th percentile3072.55
Maximum3097
Range3096
Interquartile range (IQR)1872.5

Descriptive statistics

Standard deviation1170.7769
Coefficient of variation (CV)1.1505783
Kurtosis-0.9698687
Mean1017.5551
Median Absolute Deviation (MAD)213.5
Skewness0.85149475
Sum498602
Variance1370718.5
MonotonicityNot monotonic
2024-04-16T20:38:03.814082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
1523 1
 
0.2%
1459 1
 
0.2%
1453 1
 
0.2%
1443 1
 
0.2%
1427 1
 
0.2%
1421 1
 
0.2%
1415 1
 
0.2%
1301 1
 
0.2%
1299 1
 
0.2%
Other values (480) 480
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 (%)
3097 1
0.2%
3096 1
0.2%
3095 1
0.2%
3094 1
0.2%
3093 1
0.2%
3092 1
0.2%
3091 1
0.2%
3090 1
0.2%
3089 1
0.2%
3088 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3319959.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:03.906238image/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 deviation40704.411
Coefficient of variation (CV)0.012260515
Kurtosis-0.48741385
Mean3319959.2
Median Absolute Deviation (MAD)30000
Skewness0.10032885
Sum1.62678 × 109
Variance1.656849 × 109
MonotonicityNot monotonic
2024-04-16T20:38:03.998195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 130
26.5%
3290000 88
18.0%
3250000 56
11.4%
3300000 30
 
6.1%
3320000 27
 
5.5%
3350000 26
 
5.3%
3400000 26
 
5.3%
3380000 24
 
4.9%
3310000 21
 
4.3%
3390000 15
 
3.1%
Other values (5) 47
 
9.6%
ValueCountFrequency (%)
3250000 56
11.4%
3260000 2
 
0.4%
3270000 9
 
1.8%
3290000 88
18.0%
3300000 30
 
6.1%
3310000 21
 
4.3%
3320000 27
 
5.5%
3330000 130
26.5%
3340000 13
 
2.7%
3350000 26
 
5.3%
ValueCountFrequency (%)
3400000 26
 
5.3%
3390000 15
 
3.1%
3380000 24
 
4.9%
3370000 9
 
1.8%
3360000 14
 
2.9%
3350000 26
 
5.3%
3340000 13
 
2.7%
3330000 130
26.5%
3320000 27
 
5.5%
3310000 21
 
4.3%

mgtno
Text

Distinct254
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:38:04.183633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters9800
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 (%)30.2%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
3.7%
cdff5211012021000001 13
 
2.7%
cdff5211012019000001 12
 
2.4%
cdff5211012020000002 9
 
1.8%
cdff5211012021000002 9
 
1.8%
cdff5211032020000001 8
 
1.6%
cdff5211042021000001 8
 
1.6%
cdff5211032019000001 8
 
1.6%
cdff5211012022000001 7
 
1.4%
cdff5211042019000001 6
 
1.2%
Other values (244) 392
80.0%
2024-04-16T20:38:04.534726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4250
43.4%
2 1531
 
15.6%
F 980
 
10.0%
1 977
 
10.0%
C 490
 
5.0%
D 490
 
5.0%
4 393
 
4.0%
5 253
 
2.6%
9 135
 
1.4%
3 93
 
0.9%
Other values (3) 208
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7840
80.0%
Uppercase Letter 1960
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4250
54.2%
2 1531
 
19.5%
1 977
 
12.5%
4 393
 
5.0%
5 253
 
3.2%
9 135
 
1.7%
3 93
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
F 980
50.0%
C 490
25.0%
D 490
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7840
80.0%
Latin 1960
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4250
54.2%
2 1531
 
19.5%
1 977
 
12.5%
4 393
 
5.0%
5 253
 
3.2%
9 135
 
1.7%
3 93
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.8%
Latin
ValueCountFrequency (%)
F 980
50.0%
C 490
25.0%
D 490
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4250
43.4%
2 1531
 
15.6%
F 980
 
10.0%
1 977
 
10.0%
C 490
 
5.0%
D 490
 
5.0%
4 393
 
4.0%
5 253
 
2.6%
9 135
 
1.4%
3 93
 
0.9%
Other values (3) 208
 
2.1%

opnsvcid
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
03_13_02_P
302 
03_13_05_P
127 
03_13_01_P
31 
03_13_03_P
 
22
03_13_04_P
 
8

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
03_13_02_P 302
61.6%
03_13_05_P 127
25.9%
03_13_01_P 31
 
6.3%
03_13_03_P 22
 
4.5%
03_13_04_P 8
 
1.6%

Length

2024-04-16T20:38:04.651588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:04.738250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 302
61.6%
03_13_05_p 127
25.9%
03_13_01_p 31
 
6.3%
03_13_03_p 22
 
4.5%
03_13_04_p 8
 
1.6%

updategbn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
U
251 
I
239 

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 251
51.2%
I 239
48.8%

Length

2024-04-16T20:38:04.829311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:04.915785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 251
51.2%
i 239
48.8%
Distinct130
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2018-08-31 23:59:59
Maximum2022-03-27 00:22:35
2024-04-16T20:38:05.012526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:38:05.129387image/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 size4.0 KiB
영화상영관
205 
영화제작업
127 
<NA>
97 
영화배급업
31 
영화상영업
22 

Length

Max length5
Median length5
Mean length4.8020408
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
41.8%
영화제작업 127
25.9%
<NA> 97
19.8%
영화배급업 31
 
6.3%
영화상영업 22
 
4.5%
영화수입업 8
 
1.6%

Length

2024-04-16T20:38:05.228413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:05.337231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 205
41.8%
영화제작업 127
25.9%
na 97
19.8%
영화배급업 31
 
6.3%
영화상영업 22
 
4.5%
영화수입업 8
 
1.6%

bplcnm
Text

Distinct405
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:38:05.530143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length10.810204
Min length2

Characters and Unicode

Total characters5297
Distinct characters267
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

Unique360 ?
Unique (%)73.5%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 92
 
8.7%
메가박스 48
 
4.5%
cgv 41
 
3.9%
주식회사 40
 
3.8%
해운대 26
 
2.5%
서면 20
 
1.9%
센텀시티 19
 
1.8%
6관 16
 
1.5%
제3관 16
 
1.5%
4관 15
 
1.4%
Other values (258) 723
68.5%
2024-04-16T20:38:05.820217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
568
 
10.7%
329
 
6.2%
170
 
3.2%
154
 
2.9%
150
 
2.8%
144
 
2.7%
126
 
2.4%
C 111
 
2.1%
109
 
2.1%
108
 
2.0%
Other values (257) 3328
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3727
70.4%
Space Separator 568
 
10.7%
Uppercase Letter 457
 
8.6%
Decimal Number 299
 
5.6%
Close Punctuation 105
 
2.0%
Open Punctuation 105
 
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
 
8.8%
170
 
4.6%
154
 
4.1%
150
 
4.0%
144
 
3.9%
126
 
3.4%
109
 
2.9%
108
 
2.9%
107
 
2.9%
81
 
2.2%
Other values (208) 2249
60.3%
Uppercase Letter
ValueCountFrequency (%)
C 111
24.3%
G 90
19.7%
V 88
19.3%
N 26
 
5.7%
O 16
 
3.5%
E 15
 
3.3%
I 13
 
2.8%
M 12
 
2.6%
A 11
 
2.4%
T 10
 
2.2%
Other values (13) 65
14.2%
Decimal Number
ValueCountFrequency (%)
1 48
16.1%
2 44
14.7%
4 40
13.4%
3 34
11.4%
6 33
11.0%
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%
g 1
 
4.3%
i 1
 
4.3%
l 1
 
4.3%
s 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 104
99.0%
] 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 104
99.0%
[ 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
568
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3727
70.4%
Common 1090
 
20.6%
Latin 480
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
329
 
8.8%
170
 
4.6%
154
 
4.1%
150
 
4.0%
144
 
3.9%
126
 
3.4%
109
 
2.9%
108
 
2.9%
107
 
2.9%
81
 
2.2%
Other values (208) 2249
60.3%
Latin
ValueCountFrequency (%)
C 111
23.1%
G 90
18.8%
V 88
18.3%
N 26
 
5.4%
O 16
 
3.3%
E 15
 
3.1%
I 13
 
2.7%
M 12
 
2.5%
A 11
 
2.3%
T 10
 
2.1%
Other values (21) 88
18.3%
Common
ValueCountFrequency (%)
568
52.1%
) 104
 
9.5%
( 104
 
9.5%
1 48
 
4.4%
2 44
 
4.0%
4 40
 
3.7%
3 34
 
3.1%
6 33
 
3.0%
5 32
 
2.9%
7 25
 
2.3%
Other values (8) 58
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3727
70.4%
ASCII 1570
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
568
36.2%
C 111
 
7.1%
) 104
 
6.6%
( 104
 
6.6%
G 90
 
5.7%
V 88
 
5.6%
1 48
 
3.1%
2 44
 
2.8%
4 40
 
2.5%
3 34
 
2.2%
Other values (39) 339
21.6%
Hangul
ValueCountFrequency (%)
329
 
8.8%
170
 
4.6%
154
 
4.1%
150
 
4.0%
144
 
3.9%
126
 
3.4%
109
 
2.9%
108
 
2.9%
107
 
2.9%
81
 
2.2%
Other values (208) 2249
60.3%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
371 
지번우편번호
97 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.4857143
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> 371
75.7%
지번우편번호 97
 
19.8%
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

2024-04-16T20:38:05.945157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 371
75.7%
지번우편번호 97
 
19.8%
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%
Distinct167
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:38:06.220147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length26.406122
Min length18

Characters and Unicode

Total characters12939
Distinct characters252
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

Unique81 ?
Unique (%)16.5%

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 490
 
20.2%
해운대구 130
 
5.4%
우동 96
 
4.0%
부산진구 88
 
3.6%
중구 56
 
2.3%
55
 
2.3%
부전동 53
 
2.2%
동래구 30
 
1.2%
북구 27
 
1.1%
전포동 27
 
1.1%
Other values (331) 1371
56.6%
2024-04-16T20:38:06.600712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2376
18.4%
682
 
5.3%
637
 
4.9%
529
 
4.1%
529
 
4.1%
498
 
3.8%
490
 
3.8%
1 471
 
3.6%
467
 
3.6%
- 416
 
3.2%
Other values (242) 5844
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7457
57.6%
Space Separator 2376
 
18.4%
Decimal Number 2157
 
16.7%
Dash Punctuation 416
 
3.2%
Other Punctuation 338
 
2.6%
Uppercase Letter 150
 
1.2%
Lowercase Letter 15
 
0.1%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
682
 
9.1%
637
 
8.5%
529
 
7.1%
529
 
7.1%
498
 
6.7%
490
 
6.6%
467
 
6.3%
208
 
2.8%
179
 
2.4%
175
 
2.3%
Other values (206) 3063
41.1%
Uppercase Letter
ValueCountFrequency (%)
K 35
23.3%
T 21
14.0%
S 19
12.7%
G 16
10.7%
B 11
 
7.3%
C 10
 
6.7%
H 10
 
6.7%
U 10
 
6.7%
Y 9
 
6.0%
N 8
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 471
21.8%
2 313
14.5%
5 227
10.5%
6 221
10.2%
4 198
9.2%
0 164
 
7.6%
8 156
 
7.2%
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 (%)
* 305
90.2%
, 18
 
5.3%
& 15
 
4.4%
Space Separator
ValueCountFrequency (%)
2376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 416
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7457
57.6%
Common 5317
41.1%
Latin 165
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
682
 
9.1%
637
 
8.5%
529
 
7.1%
529
 
7.1%
498
 
6.7%
490
 
6.6%
467
 
6.3%
208
 
2.8%
179
 
2.4%
175
 
2.3%
Other values (206) 3063
41.1%
Common
ValueCountFrequency (%)
2376
44.7%
1 471
 
8.9%
- 416
 
7.8%
2 313
 
5.9%
* 305
 
5.7%
5 227
 
4.3%
6 221
 
4.2%
4 198
 
3.7%
0 164
 
3.1%
8 156
 
2.9%
Other values (8) 470
 
8.8%
Latin
ValueCountFrequency (%)
K 35
21.2%
T 21
12.7%
S 19
11.5%
G 16
9.7%
B 11
 
6.7%
C 10
 
6.1%
H 10
 
6.1%
U 10
 
6.1%
Y 9
 
5.5%
N 8
 
4.8%
Other values (8) 16
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7457
57.6%
ASCII 5482
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2376
43.3%
1 471
 
8.6%
- 416
 
7.6%
2 313
 
5.7%
* 305
 
5.6%
5 227
 
4.1%
6 221
 
4.0%
4 198
 
3.6%
0 164
 
3.0%
8 156
 
2.8%
Other values (26) 635
 
11.6%
Hangul
ValueCountFrequency (%)
682
 
9.1%
637
 
8.5%
529
 
7.1%
529
 
7.1%
498
 
6.7%
490
 
6.6%
467
 
6.3%
208
 
2.8%
179
 
2.4%
175
 
2.3%
Other values (206) 3063
41.1%

rdnpostno
Text

MISSING 

Distinct96
Distinct (%)20.5%
Missing21
Missing (%)4.3%
Memory size4.0 KiB
2024-04-16T20:38:06.816301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0085288
Min length5

Characters and Unicode

Total characters2349
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

Unique39 ?
Unique (%)8.3%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 49
 
10.4%
48058 49
 
10.4%
48953 20
 
4.3%
48059 16
 
3.4%
47296 16
 
3.4%
46726 14
 
3.0%
47288 12
 
2.6%
47299 12
 
2.6%
48944 11
 
2.3%
47285 11
 
2.3%
Other values (86) 259
55.2%
2024-04-16T20:38:07.150701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 612
26.1%
8 399
17.0%
7 242
 
10.3%
9 239
 
10.2%
5 172
 
7.3%
0 165
 
7.0%
2 162
 
6.9%
6 153
 
6.5%
1 101
 
4.3%
3 90
 
3.8%
Other values (7) 14
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2335
99.4%
Other Letter 14
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 612
26.2%
8 399
17.1%
7 242
 
10.4%
9 239
 
10.2%
5 172
 
7.4%
0 165
 
7.1%
2 162
 
6.9%
6 153
 
6.6%
1 101
 
4.3%
3 90
 
3.9%
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 2335
99.4%
Hangul 14
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
4 612
26.2%
8 399
17.1%
7 242
 
10.4%
9 239
 
10.2%
5 172
 
7.4%
0 165
 
7.1%
2 162
 
6.9%
6 153
 
6.6%
1 101
 
4.3%
3 90
 
3.9%
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 2335
99.4%
Hangul 14
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 612
26.2%
8 399
17.1%
7 242
 
10.4%
9 239
 
10.2%
5 172
 
7.4%
0 165
 
7.1%
2 162
 
6.9%
6 153
 
6.6%
1 101
 
4.3%
3 90
 
3.9%
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 

Distinct168
Distinct (%)34.7%
Missing6
Missing (%)1.2%
Memory size4.0 KiB
2024-04-16T20:38:07.427080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length33.349174
Min length22

Characters and Unicode

Total characters16141
Distinct characters282
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

Unique81 ?
Unique (%)16.7%

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 484
 
15.5%
해운대구 130
 
4.2%
부산진구 88
 
2.8%
우동 86
 
2.8%
55
 
1.8%
중앙대로 54
 
1.7%
부전동 53
 
1.7%
중구 53
 
1.7%
해운대로 46
 
1.5%
39
 
1.3%
Other values (434) 2026
65.1%
2024-04-16T20:38:07.820222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2655
 
16.4%
695
 
4.3%
644
 
4.0%
600
 
3.7%
540
 
3.3%
539
 
3.3%
484
 
3.0%
483
 
3.0%
( 474
 
2.9%
) 474
 
2.9%
Other values (272) 8553
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9546
59.1%
Space Separator 2655
 
16.4%
Decimal Number 1947
 
12.1%
Other Punctuation 826
 
5.1%
Open Punctuation 477
 
3.0%
Close Punctuation 477
 
3.0%
Uppercase Letter 159
 
1.0%
Dash Punctuation 26
 
0.2%
Lowercase Letter 16
 
0.1%
Math Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
695
 
7.3%
644
 
6.7%
600
 
6.3%
540
 
5.7%
539
 
5.6%
484
 
5.1%
483
 
5.1%
469
 
4.9%
386
 
4.0%
211
 
2.2%
Other values (231) 4495
47.1%
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%
U 10
 
6.3%
H 10
 
6.3%
Y 9
 
5.7%
N 8
 
5.0%
Other values (3) 9
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 371
19.1%
2 266
13.7%
0 216
11.1%
3 215
11.0%
6 170
8.7%
5 162
8.3%
7 157
8.1%
4 148
 
7.6%
9 122
 
6.3%
8 120
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
h 2
 
12.5%
r 2
 
12.5%
p 1
 
6.2%
l 1
 
6.2%
i 1
 
6.2%
v 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 433
52.4%
* 378
45.8%
& 15
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 474
99.4%
[ 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 474
99.4%
] 3
 
0.6%
Space Separator
ValueCountFrequency (%)
2655
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9546
59.1%
Common 6420
39.8%
Latin 175
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
695
 
7.3%
644
 
6.7%
600
 
6.3%
540
 
5.7%
539
 
5.6%
484
 
5.1%
483
 
5.1%
469
 
4.9%
386
 
4.0%
211
 
2.2%
Other values (231) 4495
47.1%
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%
U 10
 
5.7%
H 10
 
5.7%
Y 9
 
5.1%
N 8
 
4.6%
Other values (11) 25
14.3%
Common
ValueCountFrequency (%)
2655
41.4%
( 474
 
7.4%
) 474
 
7.4%
, 433
 
6.7%
* 378
 
5.9%
1 371
 
5.8%
2 266
 
4.1%
0 216
 
3.4%
3 215
 
3.3%
6 170
 
2.6%
Other values (10) 768
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9546
59.1%
ASCII 6595
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2655
40.3%
( 474
 
7.2%
) 474
 
7.2%
, 433
 
6.6%
* 378
 
5.7%
1 371
 
5.6%
2 266
 
4.0%
0 216
 
3.3%
3 215
 
3.3%
6 170
 
2.6%
Other values (31) 943
 
14.3%
Hangul
ValueCountFrequency (%)
695
 
7.3%
644
 
6.7%
600
 
6.3%
540
 
5.7%
539
 
5.6%
484
 
5.1%
483
 
5.1%
469
 
4.9%
386
 
4.0%
211
 
2.2%
Other values (231) 4495
47.1%

apvpermymd
Real number (ℝ)

Distinct165
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122627
Minimum19451015
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:07.935817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060825
median20151020
Q320200180
95-th percentile20211215
Maximum20220325
Range769310
Interquartile range (IQR)139354.75

Descriptive statistics

Standard deviation89682.81
Coefficient of variation (CV)0.0044568143
Kurtosis8.3731081
Mean20122627
Median Absolute Deviation (MAD)59786
Skewness-1.7756726
Sum9.8600871 × 109
Variance8.0430065 × 109
MonotonicityNot monotonic
2024-04-16T20:38:08.052191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211215 12
 
2.4%
20190315 12
 
2.4%
20000529 12
 
2.4%
20140822 11
 
2.2%
20010609 11
 
2.2%
20210615 10
 
2.0%
20021112 10
 
2.0%
20071204 10
 
2.0%
20090302 10
 
2.0%
20050307 10
 
2.0%
Other values (155) 382
78.0%
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 (%)
20220325 2
0.4%
20220322 1
0.2%
20220318 2
0.4%
20220302 1
0.2%
20220208 1
0.2%
20220125 2
0.4%
20220119 1
0.2%
20220114 2
0.4%
20211231 2
0.4%
20211230 1
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct38
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
320 
폐업일자
92 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (33)
52 

Length

Max length8
Median length4
Mean length4.6367347
Min length4

Unique

Unique25 ?
Unique (%)5.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 320
65.3%
폐업일자 92
 
18.8%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20070725 3
 
0.6%
20200921 3
 
0.6%
20210806 3
 
0.6%
Other values (28) 32
 
6.5%

Length

2024-04-16T20:38:08.171390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 320
65.3%
폐업일자 92
 
18.8%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20070725 3
 
0.6%
20200921 3
 
0.6%
20210806 3
 
0.6%
Other values (28) 32
 
6.5%

clgstdt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
휴업시작일자
97 

Length

Max length6
Median length4
Mean length4.3959184
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> 393
80.2%
휴업시작일자 97
 
19.8%

Length

2024-04-16T20:38:08.314115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:08.395132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
휴업시작일자 97
 
19.8%

clgenddt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
휴업종료일자
97 

Length

Max length6
Median length4
Mean length4.3959184
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> 393
80.2%
휴업종료일자 97
 
19.8%

Length

2024-04-16T20:38:08.484706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:08.565292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
휴업종료일자 97
 
19.8%

ropnymd
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
재개업일자
97 

Length

Max length5
Median length4
Mean length4.1979592
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> 393
80.2%
재개업일자 97
 
19.8%

Length

2024-04-16T20:38:08.642575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:08.717877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
재개업일자 97
 
19.8%

trdstatenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영업/정상
370 
03
56 
13
40 
폐업
 
14
제외/삭제/전출
 
8
Other values (2)
 
2

Length

Max length8
Median length5
Mean length4.3673469
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 370
75.5%
03 56
 
11.4%
13 40
 
8.2%
폐업 14
 
2.9%
제외/삭제/전출 8
 
1.6%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:38:08.802860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:08.890729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 370
75.5%
03 56
 
11.4%
13 40
 
8.2%
폐업 14
 
2.9%
제외/삭제/전출 8
 
1.6%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영업중
411 
폐업
70 
전출
 
8
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8428571
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 411
83.9%
폐업 70
 
14.3%
전출 8
 
1.6%
직권말소 1
 
0.2%

Length

2024-04-16T20:38:09.016260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:09.108296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 411
83.9%
폐업 70
 
14.3%
전출 8
 
1.6%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)27.9%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean389574.88
Minimum373470.6
Maximum401669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:09.195834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373470.6
5-th percentile379280.63
Q1385622.78
median389327.97
Q3393703.23
95-th percentile398310.24
Maximum401669
Range28198.396
Interquartile range (IQR)8080.446

Descriptive statistics

Standard deviation5855.1756
Coefficient of variation (CV)0.015029654
Kurtosis0.092555485
Mean389574.88
Median Absolute Deviation (MAD)4275.0011
Skewness-0.32545871
Sum1.8855424 × 108
Variance34283081
MonotonicityNot monotonic
2024-04-16T20:38:09.301911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 21
 
4.3%
388011.197829908 12
 
2.4%
387608.014165034 11
 
2.2%
385622.780457355 11
 
2.2%
387271.299492377 11
 
2.2%
396915.143441 10
 
2.0%
393952.264486105 10
 
2.0%
398310.243451 10
 
2.0%
394083.501537578 10
 
2.0%
387280.619672939 9
 
1.8%
Other values (125) 369
75.3%
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 

Distinct135
Distinct (%)27.9%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean187402.04
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:09.657692image/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
Maximum204621.66
Range25864.232
Interquartile range (IQR)4600.7252

Descriptive statistics

Standard deviation5300.7628
Coefficient of variation (CV)0.028285513
Kurtosis1.8048206
Mean187402.04
Median Absolute Deviation (MAD)2169.7385
Skewness0.87419472
Sum90702588
Variance28098086
MonotonicityNot monotonic
2024-04-16T20:38:09.767262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 21
 
4.3%
185310.70532509 12
 
2.4%
185703.079007724 11
 
2.2%
179452.224754792 11
 
2.2%
186099.137533193 11
 
2.2%
187480.443811 10
 
2.0%
187602.933160728 10
 
2.0%
188031.67198 10
 
2.0%
187707.586117775 10
 
2.0%
185679.050795793 9
 
1.8%
Other values (125) 369
75.3%
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 (%)
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%
194312.723690481 7
1.4%

lastmodts
Real number (ℝ)

Distinct385
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.019366 × 1013
Minimum2.0030127 × 1013
Maximum2.0220325 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:09.873178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0190316 × 1013
median2.0210422 × 1013
Q32.0211216 × 1013
95-th percentile2.0220105 × 1013
Maximum2.0220325 × 1013
Range1.9019794 × 1011
Interquartile range (IQR)2.090025 × 1010

Descriptive statistics

Standard deviation3.3920335 × 1010
Coefficient of variation (CV)0.0016797517
Kurtosis7.0867351
Mean2.019366 × 1013
Median Absolute Deviation (MAD)7.9993716 × 108
Skewness-2.5905701
Sum9.8948932 × 1015
Variance1.1505891 × 1021
MonotonicityNot monotonic
2024-04-16T20:38:09.990591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211220133307 6
 
1.2%
20190920121341 5
 
1.0%
20211216174849 5
 
1.0%
20211220133338 5
 
1.0%
20210421091411 5
 
1.0%
20211221180318 4
 
0.8%
20211217153628 4
 
0.8%
20211220133308 4
 
0.8%
20211220161532 4
 
0.8%
20191017170859 4
 
0.8%
Other values (375) 444
90.6%
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 (%)
20220325104350 2
0.4%
20220322140026 1
0.2%
20220318084652 2
0.4%
20220314135813 1
0.2%
20220311093350 2
0.4%
20220302174827 1
0.2%
20220214093110 2
0.4%
20220210155131 1
0.2%
20220210155101 1
0.2%
20220210154958 1
0.2%

uptaenm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
업태구분명
97 

Length

Max length5
Median length4
Mean length4.1979592
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> 393
80.2%
업태구분명 97
 
19.8%

Length

2024-04-16T20:38:10.135364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:10.216911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
업태구분명 97
 
19.8%

sitetel
Categorical

Distinct41
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
051-123-1234
192 
<NA>
75 
전화번호
57 
910-1411
 
12
810-3941
 
11
Other values (36)
143 

Length

Max length13
Median length12
Mean length9.6306122
Min length4

Unique

Unique12 ?
Unique (%)2.4%

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 192
39.2%
<NA> 75
 
15.3%
전화번호 57
 
11.6%
910-1411 12
 
2.4%
810-3941 11
 
2.2%
070-7495-8542 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
070-7465-3972 7
 
1.4%
051-507-0202 7
 
1.4%
Other values (31) 101
20.6%

Length

2024-04-16T20:38:10.301301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 192
39.2%
na 75
 
15.3%
전화번호 57
 
11.6%
910-1411 12
 
2.4%
810-3941 11
 
2.2%
070-7495-8542 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
364-0480 7
 
1.4%
051-581-5950 7
 
1.4%
Other values (31) 101
20.6%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
286 
문화시설
88 
건물용도명
87 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.2040816
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> 286
58.4%
문화시설 88
 
18.0%
건물용도명 87
 
17.8%
근린생활시설 13
 
2.7%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

Length

2024-04-16T20:38:10.407976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:10.500476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 286
58.4%
문화시설 88
 
18.0%
건물용도명 87
 
17.8%
근린생활시설 13
 
2.7%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영화관
294 
<NA>
112 
공연장형태구분명
80 
자동차극장
 
4

Length

Max length8
Median length3
Mean length4.0612245
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 294
60.0%
<NA> 112
 
22.9%
공연장형태구분명 80
 
16.3%
자동차극장 4
 
0.8%

Length

2024-04-16T20:38:10.609490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:10.691668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 294
60.0%
na 112
 
22.9%
공연장형태구분명 80
 
16.3%
자동차극장 4
 
0.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
기존게임업외업종명
97 

Length

Max length9
Median length4
Mean length4.9897959
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> 393
80.2%
기존게임업외업종명 97
 
19.8%

Length

2024-04-16T20:38:10.785438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:10.863549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
기존게임업외업종명 97
 
19.8%

noroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
349 
0
75 
노래방실수
66 

Length

Max length5
Median length4
Mean length3.6755102
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> 349
71.2%
0 75
 
15.3%
노래방실수 66
 
13.5%

Length

2024-04-16T20:38:10.951361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.039568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
71.2%
0 75
 
15.3%
노래방실수 66
 
13.5%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
202 
영화상영관
196 
문화사업자구분명
92 

Length

Max length8
Median length5
Mean length5.1510204
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 202
41.2%
영화상영관 196
40.0%
문화사업자구분명 92
18.8%

Length

2024-04-16T20:38:11.132156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.229442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
41.2%
영화상영관 196
40.0%
문화사업자구분명 92
18.8%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영화상영관
302 
영화제작업
127 
영화배급업
31 
영화상영업
 
22
영화수입업
 
8

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 302
61.6%
영화제작업 127
25.9%
영화배급업 31
 
6.3%
영화상영업 22
 
4.5%
영화수입업 8
 
1.6%

Length

2024-04-16T20:38:11.315398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.410813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 302
61.6%
영화제작업 127
25.9%
영화배급업 31
 
6.3%
영화상영업 22
 
4.5%
영화수입업 8
 
1.6%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:11.526654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.603277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

vdoretornm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
비디오재생기명
97 

Length

Max length7
Median length4
Mean length4.5938776
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> 393
80.2%
비디오재생기명 97
 
19.8%

Length

2024-04-16T20:38:11.688361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.772333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
비디오재생기명 97
 
19.8%

emerstairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:11.855998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:11.936784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

emexyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:12.018681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.101221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

firefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:12.186574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.265358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
343 
0
75 
시설면적
66 
1578.8
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.5632653
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> 343
70.0%
0 75
 
15.3%
시설면적 66
 
13.5%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:38:12.353884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.439788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
70.0%
0 75
 
15.3%
시설면적 66
 
13.5%
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 size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:12.534976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.627972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

autochaairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:12.729117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.802319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
제공게임물명
97 

Length

Max length6
Median length4
Mean length4.3959184
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> 393
80.2%
제공게임물명 97
 
19.8%

Length

2024-04-16T20:38:12.911251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:12.999308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
제공게임물명 97
 
19.8%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
제작취급품목내용
97 

Length

Max length8
Median length4
Mean length4.7918367
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> 393
80.2%
제작취급품목내용 97
 
19.8%

Length

2024-04-16T20:38:13.085986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:13.164049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
제작취급품목내용 97
 
19.8%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:13.255925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:13.331213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

lghtfacilinillu
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
349 
0
75 
조명시설조도
66 

Length

Max length6
Median length4
Mean length3.8102041
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> 349
71.2%
0 75
 
15.3%
조명시설조도 66
 
13.5%

Length

2024-04-16T20:38:13.427295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:13.529700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
71.2%
0 75
 
15.3%
조명시설조도 66
 
13.5%

nearenvnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
338 
주변환경명
91 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.2367347
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> 338
69.0%
주변환경명 91
 
18.6%
기타 32
 
6.5%
유흥업소밀집지역 18
 
3.7%
아파트지역 9
 
1.8%
학교정화(상대) 2
 
0.4%

Length

2024-04-16T20:38:13.622810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:13.712932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 338
69.0%
주변환경명 91
 
18.6%
기타 32
 
6.5%
유흥업소밀집지역 18
 
3.7%
아파트지역 9
 
1.8%
학교정화(상대 2
 
0.4%

jisgnumlay
Categorical

Distinct23
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
149 
지상층수
56 
10
43 
0
38 
7
28 
Other values (18)
176 

Length

Max length4
Median length2
Mean length2.5204082
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
30.4%
지상층수 56
 
11.4%
10 43
 
8.8%
0 38
 
7.8%
7 28
 
5.7%
9 27
 
5.5%
5 20
 
4.1%
8 19
 
3.9%
42 17
 
3.5%
13 15
 
3.1%
Other values (13) 78
15.9%

Length

2024-04-16T20:38:13.810439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 149
30.4%
지상층수 56
 
11.4%
10 43
 
8.8%
0 38
 
7.8%
7 28
 
5.7%
9 27
 
5.5%
5 20
 
4.1%
8 19
 
3.9%
42 17
 
3.5%
13 15
 
3.1%
Other values (13) 78
15.9%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
325 
지역구분명
90 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3877551
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 325
66.3%
지역구분명 90
 
18.4%
일반상업지역 30
 
6.1%
상업지역 16
 
3.3%
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

2024-04-16T20:38:13.918752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:14.022085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 325
66.3%
지역구분명 90
 
18.4%
일반상업지역 30
 
6.1%
상업지역 16
 
3.3%
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 size4.0 KiB
<NA>
157 
5
65 
지하층수
57 
2
53 
0
38 
Other values (7)
120 

Length

Max length4
Median length1
Mean length2.3142857
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
32.0%
5 65
13.3%
지하층수 57
 
11.6%
2 53
 
10.8%
0 38
 
7.8%
1 35
 
7.1%
3 24
 
4.9%
4 21
 
4.3%
6 20
 
4.1%
8 18
 
3.7%
Other values (2) 2
 
0.4%

Length

2024-04-16T20:38:14.146626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 157
32.0%
5 65
13.3%
지하층수 57
 
11.6%
2 53
 
10.8%
0 38
 
7.8%
1 35
 
7.1%
3 24
 
4.9%
4 21
 
4.3%
6 20
 
4.1%
8 18
 
3.7%
Other values (2) 2
 
0.4%

bgroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
349 
0
75 
청소년실수
66 

Length

Max length5
Median length4
Mean length3.6755102
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> 349
71.2%
0 75
 
15.3%
청소년실수 66
 
13.5%

Length

2024-04-16T20:38:14.259254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:14.340883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
71.2%
0 75
 
15.3%
청소년실수 66
 
13.5%

bgroomyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:14.438875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:14.518648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

totgasyscnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
349 
0
75 
총게임기수
66 

Length

Max length5
Median length4
Mean length3.6755102
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> 349
71.2%
0 75
 
15.3%
총게임기수 66
 
13.5%

Length

2024-04-16T20:38:14.609521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:14.693512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
71.2%
0 75
 
15.3%
총게임기수 66
 
13.5%

totnumlay
Categorical

Distinct20
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
235 
총층수
59 
0
44 
10
 
20
12
 
13
Other values (15)
119 

Length

Max length4
Median length3
Mean length2.922449
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> 235
48.0%
총층수 59
 
12.0%
0 44
 
9.0%
10 20
 
4.1%
12 13
 
2.7%
6 12
 
2.4%
11 12
 
2.4%
9 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.7%

Length

2024-04-16T20:38:14.783500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 235
48.0%
총층수 59
 
12.0%
0 44
 
9.0%
10 20
 
4.1%
12 13
 
2.7%
6 12
 
2.4%
11 12
 
2.4%
9 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.7%

frstregts
Real number (ℝ)

Distinct165
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122627
Minimum19451015
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:14.909575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060825
median20151020
Q320200180
95-th percentile20211215
Maximum20220325
Range769310
Interquartile range (IQR)139354.75

Descriptive statistics

Standard deviation89682.81
Coefficient of variation (CV)0.0044568143
Kurtosis8.3731081
Mean20122627
Median Absolute Deviation (MAD)59786
Skewness-1.7756726
Sum9.8600871 × 109
Variance8.0430065 × 109
MonotonicityNot monotonic
2024-04-16T20:38:15.044025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211215 12
 
2.4%
20190315 12
 
2.4%
20000529 12
 
2.4%
20140822 11
 
2.2%
20010609 11
 
2.2%
20210615 10
 
2.0%
20021112 10
 
2.0%
20071204 10
 
2.0%
20090302 10
 
2.0%
20050307 10
 
2.0%
Other values (155) 382
78.0%
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 (%)
20220325 2
0.4%
20220322 1
0.2%
20220318 2
0.4%
20220302 1
0.2%
20220208 1
0.2%
20220125 2
0.4%
20220119 1
0.2%
20220114 2
0.4%
20211231 2
0.4%
20211230 1
0.2%

pasgbreth
Categorical

Distinct19
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
216 
1
103 
0
66 
통로너비
60 
1.5
 
12
Other values (14)
33 

Length

Max length4
Median length4
Mean length2.9081633
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> 216
44.1%
1 103
21.0%
0 66
 
13.5%
통로너비 60
 
12.2%
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

2024-04-16T20:38:15.163683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 216
44.1%
1 103
21.0%
0 66
 
13.5%
통로너비 60
 
12.2%
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 size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:15.292225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:15.369379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
97 

Length

Max length4
Median length4
Mean length3.4061224
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> 393
80.2%
97
 
19.8%

Length

2024-04-16T20:38:15.447048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:15.772151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
97
 
19.8%

actlnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
품목명
97 

Length

Max length4
Median length4
Mean length3.8020408
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> 393
80.2%
품목명 97
 
19.8%

Length

2024-04-16T20:38:15.845658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:15.920429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
80.2%
품목명 97
 
19.8%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2022-04-01 05:20:03
Maximum2022-04-01 05:20:03
2024-04-16T20:38:15.985055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:38:16.067238image/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>2022-04-01 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>2022-04-01 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>2022-04-01 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/정상영업중384985.448098179597.59295420211220135431업태구분명070-7438-5100건물용도명영화관기존게임업외업종명노래방실수문화사업자구분명영화상영관비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명6상업지역4청소년실수총게임기수총층수20170309통로너비품목명2022-04-01 05:20:03
453250000CDFF422000198200000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 1관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19820125<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102116<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19820125<NA><NA><NA><NA>2022-04-01 05:20:03
563250000CDFF422000199300000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 2관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102237<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19930814<NA><NA><NA><NA>2022-04-01 05:20:03
673250000CDFF422000199300000203_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 3관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621103110<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19930814<NA><NA><NA><NA>2022-04-01 05:20:03
783250000CDFF422000199800000103_13_02_PI2018-08-31 23:59:59.0<NA>삼보극장600807부산광역시 중구 부평동2가 56번지48947<NA>1998030720070725<NA><NA><NA>03폐업<NA><NA>20070725183312<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19980307<NA><NA><NA><NA>2022-04-01 05:20:03
893250000CDFF422000199900000103_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 1관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104121<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1019990716<NA><NA><NA><NA>2022-04-01 05:20:03
9103250000CDFF422000199900000203_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 2관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104156<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>4<NA><NA><NA><NA>19990716<NA><NA><NA><NA>2022-04-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
48030163400000CDFF521101202100000103_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/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2022-04-01 05:20:03
48130173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2022-04-01 05:20:03
48230183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2022-04-01 05:20:03
48330193360000CDFF521104202100000103_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/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2022-04-01 05:20:03
48430203330000CDFF521103202100000303_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/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2022-04-01 05:20:03
48530213330000CDFF521101202100000503_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>2022-04-01 05:20:03
48630223250000CDFF521102202100000103_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>2022-04-01 05:20:03
48730233250000CDFF521103202100000103_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>2022-04-01 05:20:03
48830243250000CDFF521101202100000203_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>2022-04-01 05:20:03
48930253290000CDFF521104202100000103_13_03_PU2021-09-19 02:40:00.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210917145721업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2022-04-01 05:20:03