Overview

Dataset statistics

Number of variables56
Number of observations2785
Missing cells2455
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory454.0 B

Variable types

Numeric6
Text8
Categorical40
DateTime2

Alerts

sitepostno is highly imbalanced (80.6%)Imbalance
clgstdt is highly imbalanced (56.2%)Imbalance
clgenddt is highly imbalanced (56.2%)Imbalance
trdstatenm is highly imbalanced (71.3%)Imbalance
dtlstatenm is highly imbalanced (81.2%)Imbalance
bdngsrvnm is highly imbalanced (59.0%)Imbalance
facilar is highly imbalanced (71.8%)Imbalance
nearenvnm is highly imbalanced (60.6%)Imbalance
regnsenm is highly imbalanced (63.1%)Imbalance
totnumlay is highly imbalanced (58.4%)Imbalance
pasgbreth is highly imbalanced (72.2%)Imbalance
dcbymd has 2084 (74.8%) missing valuesMissing
x has 98 (3.5%) missing valuesMissing
y has 98 (3.5%) missing valuesMissing
sitetel has 168 (6.0%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:41:56.129966
Analysis finished2024-04-16 11:41:57.780656
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2785
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1398.875
Minimum1
Maximum2797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:41:57.841944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile140.2
Q1700
median1398
Q32100
95-th percentile2657.8
Maximum2797
Range2796
Interquartile range (IQR)1400

Descriptive statistics

Standard deviation808.17684
Coefficient of variation (CV)0.5777334
Kurtosis-1.2007559
Mean1398.875
Median Absolute Deviation (MAD)700
Skewness0.0015129061
Sum3895867
Variance653149.8
MonotonicityNot monotonic
2024-04-16T20:41:57.961246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1868 1
 
< 0.1%
1860 1
 
< 0.1%
1861 1
 
< 0.1%
1862 1
 
< 0.1%
1863 1
 
< 0.1%
1864 1
 
< 0.1%
1865 1
 
< 0.1%
1866 1
 
< 0.1%
1867 1
 
< 0.1%
Other values (2775) 2775
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2797 1
< 0.1%
2796 1
< 0.1%
2795 1
< 0.1%
2794 1
< 0.1%
2793 1
< 0.1%
2792 1
< 0.1%
2791 1
< 0.1%
2790 1
< 0.1%
2789 1
< 0.1%
2788 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct156
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3632559.1
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:41:58.076250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3020000
Q13160000
median3290000
Q33910000
95-th percentile5530000
Maximum6520000
Range3520000
Interquartile range (IQR)750000

Descriptive statistics

Standard deviation753601.14
Coefficient of variation (CV)0.20745737
Kurtosis2.927924
Mean3632559.1
Median Absolute Deviation (MAD)200000
Skewness1.8476815
Sum1.0116677 × 1010
Variance5.6791469 × 1011
MonotonicityNot monotonic
2024-04-16T20:41:58.196059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3220000 294
 
10.6%
3130000 182
 
6.5%
3210000 145
 
5.2%
3330000 108
 
3.9%
3290000 73
 
2.6%
3030000 64
 
2.3%
3020000 63
 
2.3%
4050000 61
 
2.2%
3000000 60
 
2.2%
3120000 59
 
2.1%
Other values (146) 1676
60.2%
ValueCountFrequency (%)
3000000 60
2.2%
3010000 49
1.8%
3020000 63
2.3%
3030000 64
2.3%
3040000 33
1.2%
3050000 25
 
0.9%
3060000 16
 
0.6%
3070000 20
 
0.7%
3080000 4
 
0.1%
3090000 9
 
0.3%
ValueCountFrequency (%)
6520000 4
 
0.1%
6510000 33
1.2%
5710000 18
0.6%
5690000 11
 
0.4%
5680000 8
 
0.3%
5670000 18
0.6%
5600000 20
0.7%
5590000 13
 
0.5%
5540000 4
 
0.1%
5530000 12
 
0.4%

mgtno
Text

Distinct563
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
2024-04-16T20:41:58.389595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters55700
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

Unique270 ?
Unique (%)9.7%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012019000001 110
 
3.9%
cdff5211012020000001 95
 
3.4%
cdff5211012019000002 77
 
2.8%
cdff5211032020000001 68
 
2.4%
cdff5211012020000002 66
 
2.4%
cdff5211042020000001 66
 
2.4%
cdff5211032019000001 58
 
2.1%
cdff4220002020000001 54
 
1.9%
cdff5211012019000003 50
 
1.8%
cdff5211022020000001 50
 
1.8%
Other values (553) 2091
75.1%
2024-04-16T20:41:58.679878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21895
39.3%
2 8325
 
14.9%
1 7726
 
13.9%
F 5570
 
10.0%
C 2785
 
5.0%
D 2785
 
5.0%
5 2274
 
4.1%
4 1333
 
2.4%
9 1300
 
2.3%
3 809
 
1.5%
Other values (3) 898
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44560
80.0%
Uppercase Letter 11140
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21895
49.1%
2 8325
 
18.7%
1 7726
 
17.3%
5 2274
 
5.1%
4 1333
 
3.0%
9 1300
 
2.9%
3 809
 
1.8%
8 419
 
0.9%
6 256
 
0.6%
7 223
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 5570
50.0%
C 2785
25.0%
D 2785
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44560
80.0%
Latin 11140
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21895
49.1%
2 8325
 
18.7%
1 7726
 
17.3%
5 2274
 
5.1%
4 1333
 
3.0%
9 1300
 
2.9%
3 809
 
1.8%
8 419
 
0.9%
6 256
 
0.6%
7 223
 
0.5%
Latin
ValueCountFrequency (%)
F 5570
50.0%
C 2785
25.0%
D 2785
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21895
39.3%
2 8325
 
14.9%
1 7726
 
13.9%
F 5570
 
10.0%
C 2785
 
5.0%
D 2785
 
5.0%
5 2274
 
4.1%
4 1333
 
2.4%
9 1300
 
2.3%
3 809
 
1.5%
Other values (3) 898
 
1.6%

opnsvcid
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
03_13_05_P
1144 
03_13_02_P
793 
03_13_01_P
405 
03_13_04_P
236 
03_13_03_P
207 

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_05_P 1144
41.1%
03_13_02_P 793
28.5%
03_13_01_P 405
 
14.5%
03_13_04_P 236
 
8.5%
03_13_03_P 207
 
7.4%

Length

2024-04-16T20:41:58.790659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:58.875007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_05_p 1144
41.1%
03_13_02_p 793
28.5%
03_13_01_p 405
 
14.5%
03_13_04_p 236
 
8.5%
03_13_03_p 207
 
7.4%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
I
2187 
U
598 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowU
4th rowU
5th rowI

Common Values

ValueCountFrequency (%)
I 2187
78.5%
U 598
 
21.5%

Length

2024-04-16T20:41:58.968418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:59.057090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2187
78.5%
u 598
 
21.5%
Distinct633
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 00:23:15
2024-04-16T20:41:59.152672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:59.290958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
영화제작업
1144 
영화상영관
573 
영화배급업
405 
영화수입업
236 
<NA>
220 

Length

Max length5
Median length5
Mean length4.9210054
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화제작업 1144
41.1%
영화상영관 573
20.6%
영화배급업 405
 
14.5%
영화수입업 236
 
8.5%
<NA> 220
 
7.9%
영화상영업 207
 
7.4%

Length

2024-04-16T20:41:59.402547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:59.493916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1144
41.1%
영화상영관 573
20.6%
영화배급업 405
 
14.5%
영화수입업 236
 
8.5%
na 220
 
7.9%
영화상영업 207
 
7.4%

bplcnm
Text

Distinct1708
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
2024-04-16T20:41:59.644918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length10.448474
Min length2

Characters and Unicode

Total characters29099
Distinct characters626
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1184 ?
Unique (%)42.5%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
주식회사 676
 
13.0%
롯데시네마 188
 
3.6%
cgv 130
 
2.5%
1관 93
 
1.8%
2관 91
 
1.7%
85
 
1.6%
메가박스 79
 
1.5%
3관 61
 
1.2%
4관 57
 
1.1%
메가박스중앙(주 54
 
1.0%
Other values (1445) 3688
70.9%
2024-04-16T20:41:59.929072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2419
 
8.3%
1475
 
5.1%
995
 
3.4%
898
 
3.1%
879
 
3.0%
) 868
 
3.0%
( 851
 
2.9%
737
 
2.5%
697
 
2.4%
685
 
2.4%
Other values (616) 18595
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22248
76.5%
Space Separator 2419
 
8.3%
Uppercase Letter 1380
 
4.7%
Close Punctuation 869
 
3.0%
Open Punctuation 852
 
2.9%
Decimal Number 847
 
2.9%
Lowercase Letter 430
 
1.5%
Other Punctuation 31
 
0.1%
Other Symbol 18
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1475
 
6.6%
995
 
4.5%
898
 
4.0%
879
 
4.0%
737
 
3.3%
697
 
3.1%
685
 
3.1%
398
 
1.8%
394
 
1.8%
389
 
1.7%
Other values (545) 14701
66.1%
Uppercase Letter
ValueCountFrequency (%)
C 306
22.2%
G 275
19.9%
V 260
18.8%
E 58
 
4.2%
A 50
 
3.6%
M 45
 
3.3%
S 38
 
2.8%
I 35
 
2.5%
N 32
 
2.3%
T 31
 
2.2%
Other values (16) 250
18.1%
Lowercase Letter
ValueCountFrequency (%)
e 45
 
10.5%
o 35
 
8.1%
i 35
 
8.1%
m 31
 
7.2%
a 29
 
6.7%
r 27
 
6.3%
n 25
 
5.8%
l 25
 
5.8%
t 22
 
5.1%
d 22
 
5.1%
Other values (12) 134
31.2%
Decimal Number
ValueCountFrequency (%)
1 172
20.3%
2 153
18.1%
3 113
13.3%
4 99
11.7%
5 89
10.5%
6 86
10.2%
7 56
 
6.6%
8 35
 
4.1%
9 27
 
3.2%
0 17
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 17
54.8%
& 6
 
19.4%
, 4
 
12.9%
" 2
 
6.5%
: 2
 
6.5%
Close Punctuation
ValueCountFrequency (%)
) 868
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 851
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2419
100.0%
Other Symbol
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22266
76.5%
Common 5023
 
17.3%
Latin 1810
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1475
 
6.6%
995
 
4.5%
898
 
4.0%
879
 
3.9%
737
 
3.3%
697
 
3.1%
685
 
3.1%
398
 
1.8%
394
 
1.8%
389
 
1.7%
Other values (546) 14719
66.1%
Latin
ValueCountFrequency (%)
C 306
16.9%
G 275
15.2%
V 260
 
14.4%
E 58
 
3.2%
A 50
 
2.8%
M 45
 
2.5%
e 45
 
2.5%
S 38
 
2.1%
I 35
 
1.9%
o 35
 
1.9%
Other values (38) 663
36.6%
Common
ValueCountFrequency (%)
2419
48.2%
) 868
 
17.3%
( 851
 
16.9%
1 172
 
3.4%
2 153
 
3.0%
3 113
 
2.2%
4 99
 
2.0%
5 89
 
1.8%
6 86
 
1.7%
7 56
 
1.1%
Other values (12) 117
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22248
76.5%
ASCII 6833
 
23.5%
None 18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2419
35.4%
) 868
 
12.7%
( 851
 
12.5%
C 306
 
4.5%
G 275
 
4.0%
V 260
 
3.8%
1 172
 
2.5%
2 153
 
2.2%
3 113
 
1.7%
4 99
 
1.4%
Other values (60) 1317
19.3%
Hangul
ValueCountFrequency (%)
1475
 
6.6%
995
 
4.5%
898
 
4.0%
879
 
4.0%
737
 
3.3%
697
 
3.1%
685
 
3.1%
398
 
1.8%
394
 
1.8%
389
 
1.7%
Other values (545) 14701
66.1%
None
ValueCountFrequency (%)
18
100.0%

sitepostno
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2239 
지번우편번호
513 
607787
 
7
614845
 
4
601060
 
3
Other values (14)
 
19

Length

Max length6
Median length4
Mean length4.3921005
Min length4

Unique

Unique11 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2239
80.4%
지번우편번호 513
 
18.4%
607787 7
 
0.3%
614845 4
 
0.1%
601060 3
 
0.1%
608805 3
 
0.1%
600805 3
 
0.1%
600046 2
 
0.1%
612821 1
 
< 0.1%
600807 1
 
< 0.1%
Other values (9) 9
 
0.3%

Length

2024-04-16T20:42:00.051438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2239
80.4%
지번우편번호 513
 
18.4%
607787 7
 
0.3%
614845 4
 
0.1%
601060 3
 
0.1%
608805 3
 
0.1%
600805 3
 
0.1%
600046 2
 
0.1%
614847 1
 
< 0.1%
600045 1
 
< 0.1%
Other values (9) 9
 
0.3%
Distinct1203
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
2024-04-16T20:42:00.312740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length27.305925
Min length15

Characters and Unicode

Total characters76047
Distinct characters528
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)23.8%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1번지
3rd row부산광역시 중구 남포동5가 12-1번지
4th row부산광역시 중구 남포동5가 12-1번지
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
서울특별시 1316
 
9.1%
경기도 481
 
3.3%
부산광역시 396
 
2.8%
강남구 294
 
2.0%
마포구 182
 
1.3%
서초구 146
 
1.0%
중구 139
 
1.0%
해운대구 108
 
0.8%
논현동 96
 
0.7%
경상남도 89
 
0.6%
Other values (2859) 11137
77.4%
2024-04-16T20:42:00.716884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14038
 
18.5%
2939
 
3.9%
1 2870
 
3.8%
2830
 
3.7%
2298
 
3.0%
2219
 
2.9%
- 2054
 
2.7%
2038
 
2.7%
1816
 
2.4%
2 1757
 
2.3%
Other values (518) 41188
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45650
60.0%
Space Separator 14038
 
18.5%
Decimal Number 13274
 
17.5%
Dash Punctuation 2054
 
2.7%
Uppercase Letter 712
 
0.9%
Lowercase Letter 111
 
0.1%
Other Punctuation 56
 
0.1%
Math Symbol 50
 
0.1%
Close Punctuation 47
 
0.1%
Open Punctuation 47
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2939
 
6.4%
2830
 
6.2%
2298
 
5.0%
2219
 
4.9%
2038
 
4.5%
1816
 
4.0%
1408
 
3.1%
1369
 
3.0%
1367
 
3.0%
996
 
2.2%
Other values (460) 26370
57.8%
Uppercase Letter
ValueCountFrequency (%)
C 64
 
9.0%
E 62
 
8.7%
A 54
 
7.6%
T 48
 
6.7%
B 42
 
5.9%
K 41
 
5.8%
G 41
 
5.8%
L 37
 
5.2%
V 36
 
5.1%
M 35
 
4.9%
Other values (15) 252
35.4%
Lowercase Letter
ValueCountFrequency (%)
i 19
17.1%
e 19
17.1%
n 13
11.7%
c 13
11.7%
t 13
11.7%
y 9
8.1%
r 6
 
5.4%
a 6
 
5.4%
h 3
 
2.7%
s 3
 
2.7%
Other values (4) 7
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 2870
21.6%
2 1757
13.2%
3 1332
10.0%
5 1191
9.0%
0 1190
9.0%
4 1190
9.0%
6 1121
 
8.4%
7 975
 
7.3%
9 854
 
6.4%
8 794
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 37
66.1%
& 19
33.9%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
14038
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2054
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45650
60.0%
Common 29566
38.9%
Latin 831
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2939
 
6.4%
2830
 
6.2%
2298
 
5.0%
2219
 
4.9%
2038
 
4.5%
1816
 
4.0%
1408
 
3.1%
1369
 
3.0%
1367
 
3.0%
996
 
2.2%
Other values (460) 26370
57.8%
Latin
ValueCountFrequency (%)
C 64
 
7.7%
E 62
 
7.5%
A 54
 
6.5%
T 48
 
5.8%
B 42
 
5.1%
K 41
 
4.9%
G 41
 
4.9%
L 37
 
4.5%
V 36
 
4.3%
M 35
 
4.2%
Other values (31) 371
44.6%
Common
ValueCountFrequency (%)
14038
47.5%
1 2870
 
9.7%
- 2054
 
6.9%
2 1757
 
5.9%
3 1332
 
4.5%
5 1191
 
4.0%
0 1190
 
4.0%
4 1190
 
4.0%
6 1121
 
3.8%
7 975
 
3.3%
Other values (7) 1848
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45650
60.0%
ASCII 30389
40.0%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14038
46.2%
1 2870
 
9.4%
- 2054
 
6.8%
2 1757
 
5.8%
3 1332
 
4.4%
5 1191
 
3.9%
0 1190
 
3.9%
4 1190
 
3.9%
6 1121
 
3.7%
7 975
 
3.2%
Other values (46) 2671
 
8.8%
Hangul
ValueCountFrequency (%)
2939
 
6.4%
2830
 
6.2%
2298
 
5.0%
2219
 
4.9%
2038
 
4.5%
1816
 
4.0%
1408
 
3.1%
1369
 
3.0%
1367
 
3.0%
996
 
2.2%
Other values (460) 26370
57.8%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

rdnpostno
Real number (ℝ)

Distinct944
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20646.605
Minimum1096
Maximum63627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:42:00.837547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1096
5-th percentile3182
Q16024
median10881
Q341484
95-th percentile54654
Maximum63627
Range62531
Interquartile range (IQR)35460

Descriptive statistics

Standard deviation19023.631
Coefficient of variation (CV)0.92139271
Kurtosis-0.94874617
Mean20646.605
Median Absolute Deviation (MAD)6813
Skewness0.81296125
Sum57500795
Variance3.6189855 × 108
MonotonicityNot monotonic
2024-04-16T20:42:00.946478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 77
 
2.8%
48058 39
 
1.4%
7567 24
 
0.9%
34913 24
 
0.9%
44249 21
 
0.8%
3993 21
 
0.8%
48953 20
 
0.7%
6627 20
 
0.7%
6040 20
 
0.7%
16914 19
 
0.7%
Other values (934) 2500
89.8%
ValueCountFrequency (%)
1096 1
 
< 0.1%
1170 3
0.1%
1318 1
 
< 0.1%
1320 1
 
< 0.1%
1337 1
 
< 0.1%
1361 1
 
< 0.1%
1379 1
 
< 0.1%
1400 1
 
< 0.1%
1410 1
 
< 0.1%
1422 1
 
< 0.1%
ValueCountFrequency (%)
63627 1
 
< 0.1%
63595 1
 
< 0.1%
63580 1
 
< 0.1%
63558 1
 
< 0.1%
63343 1
 
< 0.1%
63316 15
0.5%
63270 3
 
0.1%
63217 3
 
0.1%
63208 4
 
0.1%
63207 1
 
< 0.1%
Distinct1238
Distinct (%)44.6%
Missing7
Missing (%)0.3%
Memory size21.9 KiB
2024-04-16T20:42:01.241468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length50
Mean length34.899568
Min length5

Characters and Unicode

Total characters96951
Distinct characters566
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique683 ?
Unique (%)24.6%

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 (%)
서울특별시 1315
 
6.9%
경기도 479
 
2.5%
부산광역시 390
 
2.0%
강남구 294
 
1.5%
2층 215
 
1.1%
마포구 181
 
0.9%
3층 165
 
0.9%
서초구 146
 
0.8%
중구 136
 
0.7%
4층 128
 
0.7%
Other values (3354) 15677
82.0%
2024-04-16T20:42:01.924024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16378
 
16.9%
1 3567
 
3.7%
3411
 
3.5%
2863
 
3.0%
, 2832
 
2.9%
2758
 
2.8%
) 2539
 
2.6%
( 2539
 
2.6%
2 2348
 
2.4%
2338
 
2.4%
Other values (556) 55378
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55179
56.9%
Space Separator 16378
 
16.9%
Decimal Number 15915
 
16.4%
Other Punctuation 2851
 
2.9%
Close Punctuation 2539
 
2.6%
Open Punctuation 2539
 
2.6%
Uppercase Letter 810
 
0.8%
Dash Punctuation 500
 
0.5%
Lowercase Letter 120
 
0.1%
Math Symbol 112
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3411
 
6.2%
2863
 
5.2%
2758
 
5.0%
2338
 
4.2%
1910
 
3.5%
1422
 
2.6%
1369
 
2.5%
1366
 
2.5%
1310
 
2.4%
1305
 
2.4%
Other values (495) 35127
63.7%
Uppercase Letter
ValueCountFrequency (%)
B 82
 
10.1%
C 82
 
10.1%
E 69
 
8.5%
A 65
 
8.0%
T 49
 
6.0%
G 46
 
5.7%
K 45
 
5.6%
V 40
 
4.9%
L 37
 
4.6%
M 36
 
4.4%
Other values (16) 259
32.0%
Lowercase Letter
ValueCountFrequency (%)
e 19
15.8%
i 19
15.8%
c 15
12.5%
n 13
10.8%
t 13
10.8%
y 9
7.5%
b 6
 
5.0%
a 6
 
5.0%
r 6
 
5.0%
h 3
 
2.5%
Other values (6) 11
9.2%
Decimal Number
ValueCountFrequency (%)
1 3567
22.4%
2 2348
14.8%
0 2037
12.8%
3 1757
11.0%
4 1375
 
8.6%
5 1315
 
8.3%
6 941
 
5.9%
7 931
 
5.8%
9 843
 
5.3%
8 801
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2832
99.3%
& 19
 
0.7%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
16378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2539
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2539
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%
Math Symbol
ValueCountFrequency (%)
~ 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55179
56.9%
Common 40834
42.1%
Latin 938
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3411
 
6.2%
2863
 
5.2%
2758
 
5.0%
2338
 
4.2%
1910
 
3.5%
1422
 
2.6%
1369
 
2.5%
1366
 
2.5%
1310
 
2.4%
1305
 
2.4%
Other values (495) 35127
63.7%
Latin
ValueCountFrequency (%)
B 82
 
8.7%
C 82
 
8.7%
E 69
 
7.4%
A 65
 
6.9%
T 49
 
5.2%
G 46
 
4.9%
K 45
 
4.8%
V 40
 
4.3%
L 37
 
3.9%
M 36
 
3.8%
Other values (34) 387
41.3%
Common
ValueCountFrequency (%)
16378
40.1%
1 3567
 
8.7%
, 2832
 
6.9%
) 2539
 
6.2%
( 2539
 
6.2%
2 2348
 
5.8%
0 2037
 
5.0%
3 1757
 
4.3%
4 1375
 
3.4%
5 1315
 
3.2%
Other values (7) 4147
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55179
56.9%
ASCII 41764
43.1%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16378
39.2%
1 3567
 
8.5%
, 2832
 
6.8%
) 2539
 
6.1%
( 2539
 
6.1%
2 2348
 
5.6%
0 2037
 
4.9%
3 1757
 
4.2%
4 1375
 
3.3%
5 1315
 
3.1%
Other values (49) 5077
 
12.2%
Hangul
ValueCountFrequency (%)
3411
 
6.2%
2863
 
5.2%
2758
 
5.0%
2338
 
4.2%
1910
 
3.5%
1422
 
2.6%
1369
 
2.5%
1366
 
2.5%
1310
 
2.4%
1305
 
2.4%
Other values (495) 35127
63.7%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

apvpermymd
Real number (ℝ)

Distinct639
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20177488
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:42:02.048434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20060926
Q120181207
median20190702
Q320200319
95-th percentile20201106
Maximum22030212
Range2579197
Interquartile range (IQR)19112

Descriptive statistics

Standard deviation60007.348
Coefficient of variation (CV)0.0029739752
Kurtosis340.14968
Mean20177488
Median Absolute Deviation (MAD)9601
Skewness8.2364052
Sum5.6194304 × 1010
Variance3.6008818 × 109
MonotonicityNot monotonic
2024-04-16T20:42:02.170150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190315 30
 
1.1%
20190412 30
 
1.1%
20190503 27
 
1.0%
20200221 26
 
0.9%
20200214 26
 
0.9%
20181207 25
 
0.9%
20181025 24
 
0.9%
20190322 24
 
0.9%
20190125 24
 
0.9%
20190111 24
 
0.9%
Other values (629) 2525
90.7%
ValueCountFrequency (%)
19451015 1
< 0.1%
19591023 1
< 0.1%
19690925 1
< 0.1%
19820125 1
< 0.1%
19910826 1
< 0.1%
19930814 2
0.1%
19970308 1
< 0.1%
19980307 1
< 0.1%
19980319 1
< 0.1%
19980623 1
< 0.1%
ValueCountFrequency (%)
22030212 1
 
< 0.1%
20201231 2
 
0.1%
20201230 4
0.1%
20201229 2
 
0.1%
20201228 4
0.1%
20201224 3
0.1%
20201223 6
0.2%
20201222 4
0.1%
20201218 6
0.2%
20201217 2
 
0.1%

dcbymd
Text

MISSING 

Distinct86
Distinct (%)12.3%
Missing2084
Missing (%)74.8%
Memory size21.9 KiB
2024-04-16T20:42:02.379623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length5.0841655
Min length4

Characters and Unicode

Total characters3564
Distinct characters14
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

Unique49 ?
Unique (%)7.0%

Sample

1st row20080501
2nd row20070725
3rd row20160617
4th row20160617
5th row20160617
ValueCountFrequency (%)
폐업일자 511
72.9%
20200805 12
 
1.7%
20170315 10
 
1.4%
20110616 8
 
1.1%
20160617 8
 
1.1%
20200211 8
 
1.1%
20100806 7
 
1.0%
20200907 6
 
0.9%
20200713 5
 
0.7%
20201119 4
 
0.6%
Other values (76) 122
 
17.4%
2024-04-16T20:42:02.753308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 550
15.4%
511
14.3%
511
14.3%
511
14.3%
511
14.3%
2 388
10.9%
1 245
6.9%
6 69
 
1.9%
7 62
 
1.7%
9 59
 
1.7%
Other values (4) 147
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2044
57.4%
Decimal Number 1520
42.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 550
36.2%
2 388
25.5%
1 245
16.1%
6 69
 
4.5%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 30
 
2.0%
Other Letter
ValueCountFrequency (%)
511
25.0%
511
25.0%
511
25.0%
511
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2044
57.4%
Common 1520
42.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 550
36.2%
2 388
25.5%
1 245
16.1%
6 69
 
4.5%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 30
 
2.0%
Hangul
ValueCountFrequency (%)
511
25.0%
511
25.0%
511
25.0%
511
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2044
57.4%
ASCII 1520
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 550
36.2%
2 388
25.5%
1 245
16.1%
6 69
 
4.5%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 30
 
2.0%
Hangul
ValueCountFrequency (%)
511
25.0%
511
25.0%
511
25.0%
511
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2270 
휴업시작일자
514 
20200210
 
1

Length

Max length8
Median length4
Mean length4.3705566
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2270
81.5%
휴업시작일자 514
 
18.5%
20200210 1
 
< 0.1%

Length

2024-04-16T20:42:02.876951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:02.978355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2270
81.5%
휴업시작일자 514
 
18.5%
20200210 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2270 
휴업종료일자
514 
20210131
 
1

Length

Max length8
Median length4
Mean length4.3705566
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2270
81.5%
휴업종료일자 514
 
18.5%
20210131 1
 
< 0.1%

Length

2024-04-16T20:42:03.080379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:03.174167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2270
81.5%
휴업종료일자 514
 
18.5%
20210131 1
 
< 0.1%

ropnymd
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
재개업일자
514 

Length

Max length5
Median length4
Mean length4.1845601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
재개업일자 514
 
18.5%

Length

2024-04-16T20:42:03.257562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:03.343047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
재개업일자 514
 
18.5%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
영업/정상
2386 
13
 
163
제외/삭제/전출
 
97
03
 
56
폐업
 
37
Other values (4)
 
46

Length

Max length8
Median length5
Mean length4.810772
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2386
85.7%
13 163
 
5.9%
제외/삭제/전출 97
 
3.5%
03 56
 
2.0%
폐업 37
 
1.3%
<NA> 36
 
1.3%
영업상태 8
 
0.3%
35 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:42:03.433950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:03.531296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2386
85.7%
13 163
 
5.9%
제외/삭제/전출 97
 
3.5%
03 56
 
2.0%
폐업 37
 
1.3%
na 36
 
1.3%
영업상태 8
 
0.3%
35 1
 
< 0.1%
휴업 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
영업중
2593 
전출
 
97
폐업
 
93
직권말소
 
1
휴업
 
1

Length

Max length4
Median length3
Mean length2.9317774
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2593
93.1%
전출 97
 
3.5%
폐업 93
 
3.3%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:42:03.661778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:03.777129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2593
93.1%
전출 97
 
3.5%
폐업 93
 
3.3%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

x
Text

MISSING 

Distinct1087
Distinct (%)40.5%
Missing98
Missing (%)3.5%
Memory size21.9 KiB
2024-04-16T20:42:03.939306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.937105
Min length7

Characters and Unicode

Total characters53571
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique555 ?
Unique (%)20.7%

Sample

1st row384872.10053800000
2nd row384985.448097939
3rd row384985.448097939
4th row384985.448097939
5th row384992.28324900000
ValueCountFrequency (%)
187210.917773717 24
 
0.9%
238010.315065 24
 
0.9%
413436.345603296 21
 
0.8%
213057.927567229 19
 
0.7%
195858.214517145 18
 
0.7%
168216.577756851 15
 
0.6%
387982.19038700000 14
 
0.5%
좌표정보(x 13
 
0.5%
205013.09097466 12
 
0.4%
393674.032955782 12
 
0.4%
Other values (1077) 2515
93.6%
2024-04-16T20:42:04.220946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11851
22.1%
0 4763
8.9%
2 4565
 
8.5%
1 4457
 
8.3%
3 4173
 
7.8%
9 4009
 
7.5%
8 3587
 
6.7%
7 3562
 
6.6%
5 3500
 
6.5%
6 3200
 
6.0%
Other values (9) 5904
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38986
72.8%
Space Separator 11851
 
22.1%
Other Punctuation 2643
 
4.9%
Other Letter 52
 
0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4763
12.2%
2 4565
11.7%
1 4457
11.4%
3 4173
10.7%
9 4009
10.3%
8 3587
9.2%
7 3562
9.1%
5 3500
9.0%
6 3200
8.2%
4 3170
8.1%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Space Separator
ValueCountFrequency (%)
11851
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53506
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
11851
22.1%
0 4763
8.9%
2 4565
 
8.5%
1 4457
 
8.3%
3 4173
 
7.8%
9 4009
 
7.5%
8 3587
 
6.7%
7 3562
 
6.7%
5 3500
 
6.5%
6 3200
 
6.0%
Other values (4) 5839
10.9%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
X 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53519
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11851
22.1%
0 4763
8.9%
2 4565
 
8.5%
1 4457
 
8.3%
3 4173
 
7.8%
9 4009
 
7.5%
8 3587
 
6.7%
7 3562
 
6.7%
5 3500
 
6.5%
6 3200
 
6.0%
Other values (5) 5852
10.9%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

y
Text

MISSING 

Distinct1087
Distinct (%)40.5%
Missing98
Missing (%)3.5%
Memory size21.9 KiB
2024-04-16T20:42:04.410661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.937105
Min length7

Characters and Unicode

Total characters53571
Distinct characters21
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique555 ?
Unique (%)20.7%

Sample

1st row179957.08923700000
2nd row179597.592953541
3rd row179597.592953541
4th row179597.592953541
5th row179919.43700900000
ValueCountFrequency (%)
450631.435497518 24
 
0.9%
314178.057844 24
 
0.9%
233285.560332478 21
 
0.8%
421057.235457141 19
 
0.7%
419228.504806355 18
 
0.7%
431393.9120421 15
 
0.6%
186465.86425900000 14
 
0.5%
좌표정보(y 13
 
0.5%
420324.083289569 12
 
0.4%
187973.297243244 12
 
0.4%
Other values (1077) 2515
93.6%
2024-04-16T20:42:04.730030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11797
22.0%
4 6357
11.9%
0 4100
 
7.7%
1 3979
 
7.4%
5 3841
 
7.2%
8 3649
 
6.8%
3 3616
 
6.7%
2 3501
 
6.5%
6 3367
 
6.3%
7 3324
 
6.2%
Other values (11) 6040
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39030
72.9%
Space Separator 11797
 
22.0%
Other Punctuation 2643
 
4.9%
Other Letter 52
 
0.1%
Close Punctuation 15
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6357
16.3%
0 4100
10.5%
1 3979
10.2%
5 3841
9.8%
8 3649
9.3%
3 3616
9.3%
2 3501
9.0%
6 3367
8.6%
7 3324
8.5%
9 3296
8.4%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Close Punctuation
ValueCountFrequency (%)
) 13
86.7%
] 2
 
13.3%
Space Separator
ValueCountFrequency (%)
11797
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53506
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
11797
22.0%
4 6357
11.9%
0 4100
 
7.7%
1 3979
 
7.4%
5 3841
 
7.2%
8 3649
 
6.8%
3 3616
 
6.8%
2 3501
 
6.5%
6 3367
 
6.3%
7 3324
 
6.2%
Other values (6) 5975
11.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
Y 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53519
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11797
22.0%
4 6357
11.9%
0 4100
 
7.7%
1 3979
 
7.4%
5 3841
 
7.2%
8 3649
 
6.8%
3 3616
 
6.8%
2 3501
 
6.5%
6 3367
 
6.3%
7 3324
 
6.2%
Other values (7) 5988
11.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

lastmodts
Real number (ℝ)

Distinct2131
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0192489 × 1013
Minimum2.0030127 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:42:04.864229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0180608 × 1013
Q12.0190405 × 1013
median2.0191216 × 1013
Q32.0200706 × 1013
95-th percentile2.0201204 × 1013
Maximum2.0201231 × 1013
Range1.7110402 × 1011
Interquartile range (IQR)1.0301075 × 1010

Descriptive statistics

Standard deviation1.4738382 × 1010
Coefficient of variation (CV)0.00072989428
Kurtosis44.486214
Mean2.0192489 × 1013
Median Absolute Deviation (MAD)9.1010047 × 109
Skewness-5.6007661
Sum5.6236082 × 1016
Variance2.1721991 × 1020
MonotonicityNot monotonic
2024-04-16T20:42:04.990907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190418131529 6
 
0.2%
20200323160343 5
 
0.2%
20190920121341 5
 
0.2%
20030127161348 4
 
0.1%
20191218104848 4
 
0.1%
20191017170859 4
 
0.1%
20190227142751 4
 
0.1%
20201023135809 4
 
0.1%
20200918104840 4
 
0.1%
20190614141950 3
 
0.1%
Other values (2121) 2742
98.5%
ValueCountFrequency (%)
20030127161348 4
0.1%
20040731102817 1
 
< 0.1%
20050416094533 1
 
< 0.1%
20070725150334 1
 
< 0.1%
20070725150429 1
 
< 0.1%
20070725183312 1
 
< 0.1%
20071231132808 1
 
< 0.1%
20080506140353 1
 
< 0.1%
20080627132446 1
 
< 0.1%
20090622134847 1
 
< 0.1%
ValueCountFrequency (%)
20201231182744 1
< 0.1%
20201231114327 1
< 0.1%
20201230181742 1
< 0.1%
20201230181643 1
< 0.1%
20201230175549 1
< 0.1%
20201230164010 1
< 0.1%
20201230090940 1
< 0.1%
20201230090834 1
< 0.1%
20201230090810 1
< 0.1%
20201230090734 1
< 0.1%

uptaenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
업태구분명
514 

Length

Max length5
Median length4
Mean length4.1845601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
업태구분명 514
 
18.5%

Length

2024-04-16T20:42:05.103640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:05.177973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
업태구분명 514
 
18.5%

sitetel
Text

MISSING 

Distinct61
Distinct (%)2.3%
Missing168
Missing (%)6.0%
Memory size21.9 KiB
2024-04-16T20:42:05.304753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.834543
Min length4

Characters and Unicode

Total characters30971
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)1.0%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 2406
91.9%
전화번호 42
 
1.6%
032-832-0510 15
 
0.6%
063-653-7057 9
 
0.3%
02-971-6602 8
 
0.3%
070-4268-7168 7
 
0.3%
1544-0070 6
 
0.2%
02-3017-3693 6
 
0.2%
15440070 6
 
0.2%
031-629-1937 6
 
0.2%
Other values (51) 106
 
4.1%
2024-04-16T20:42:05.553691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7377
23.8%
- 5085
16.4%
3 5022
16.2%
2 4951
16.0%
0 2776
 
9.0%
5 2566
 
8.3%
4 2495
 
8.1%
7 182
 
0.6%
6 153
 
0.5%
8 110
 
0.4%
Other values (5) 254
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25718
83.0%
Dash Punctuation 5085
 
16.4%
Other Letter 168
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7377
28.7%
3 5022
19.5%
2 4951
19.3%
0 2776
 
10.8%
5 2566
 
10.0%
4 2495
 
9.7%
7 182
 
0.7%
6 153
 
0.6%
8 110
 
0.4%
9 86
 
0.3%
Other Letter
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 5085
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30803
99.5%
Hangul 168
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7377
23.9%
- 5085
16.5%
3 5022
16.3%
2 4951
16.1%
0 2776
 
9.0%
5 2566
 
8.3%
4 2495
 
8.1%
7 182
 
0.6%
6 153
 
0.5%
8 110
 
0.4%
Hangul
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30803
99.5%
Hangul 168
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7377
23.9%
- 5085
16.5%
3 5022
16.3%
2 4951
16.1%
0 2776
 
9.0%
5 2566
 
8.3%
4 2495
 
8.1%
7 182
 
0.6%
6 153
 
0.5%
8 110
 
0.4%
Hangul
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%

bdngsrvnm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
1936 
건물용도명
481 
문화시설
310 
근린생활시설
 
40
유통시설
 
9
Other values (4)
 
9

Length

Max length6
Median length4
Mean length4.1967684
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1936
69.5%
건물용도명 481
 
17.3%
문화시설 310
 
11.1%
근린생활시설 40
 
1.4%
유통시설 9
 
0.3%
호텔 6
 
0.2%
사무실 1
 
< 0.1%
기타 1
 
< 0.1%
식품위생시설 1
 
< 0.1%

Length

2024-04-16T20:42:05.670333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:05.773211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1936
69.5%
건물용도명 481
 
17.3%
문화시설 310
 
11.1%
근린생활시설 40
 
1.4%
유통시설 9
 
0.3%
호텔 6
 
0.2%
사무실 1
 
< 0.1%
기타 1
 
< 0.1%
식품위생시설 1
 
< 0.1%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
1557 
영화관
772 
공연장형태구분명
439 
자동차극장
 
17

Length

Max length8
Median length4
Mean length4.3594255
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1557
55.9%
영화관 772
27.7%
공연장형태구분명 439
 
15.8%
자동차극장 17
 
0.6%

Length

2024-04-16T20:42:05.889558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:05.982559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1557
55.9%
영화관 772
27.7%
공연장형태구분명 439
 
15.8%
자동차극장 17
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
기존게임업외업종명
514 

Length

Max length9
Median length4
Mean length4.9228007
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
기존게임업외업종명 514
 
18.5%

Length

2024-04-16T20:42:06.083557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:06.160689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
기존게임업외업종명 514
 
18.5%

noroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
노래방실수
514 

Length

Max length5
Median length4
Mean length4.1845601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
노래방실수 514
 
18.5%

Length

2024-04-16T20:42:06.242642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:06.319914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
노래방실수 514
 
18.5%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2075 
문화사업자구분명
513 
영화상영관
 
197

Length

Max length8
Median length4
Mean length4.8075404
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2075
74.5%
문화사업자구분명 513
 
18.4%
영화상영관 197
 
7.1%

Length

2024-04-16T20:42:06.418875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:06.507322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
74.5%
문화사업자구분명 513
 
18.4%
영화상영관 197
 
7.1%

culphyedcobnm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
영화제작업
1144 
영화상영관
793 
영화배급업
405 
영화수입업
236 
영화상영업
207 

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 (%)
영화제작업 1144
41.1%
영화상영관 793
28.5%
영화배급업 405
 
14.5%
영화수입업 236
 
8.5%
영화상영업 207
 
7.4%

Length

2024-04-16T20:42:06.601548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:06.710150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1144
41.1%
영화상영관 793
28.5%
영화배급업 405
 
14.5%
영화수입업 236
 
8.5%
영화상영업 207
 
7.4%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:06.824902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:06.906375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

vdoretornm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
비디오재생기명
514 

Length

Max length7
Median length4
Mean length4.5536804
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
비디오재생기명 514
 
18.5%

Length

2024-04-16T20:42:06.991508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:07.074901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
비디오재생기명 514
 
18.5%

emerstairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:07.167832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:07.248405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

emexyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:07.332848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:07.421216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

firefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:07.506610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:07.592648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2262 
시설면적
513 
1578.8
 
4
0
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.9996409
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2262
81.2%
시설면적 513
 
18.4%
1578.8 4
 
0.1%
0 4
 
0.1%
147.46 1
 
< 0.1%
181.3 1
 
< 0.1%

Length

2024-04-16T20:42:07.693598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:07.800138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2262
81.2%
시설면적 513
 
18.4%
1578.8 4
 
0.1%
0 4
 
0.1%
147.46 1
 
< 0.1%
181.3 1
 
< 0.1%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:07.917636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.000138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

autochaairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:08.083084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.160873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
제공게임물명
514 

Length

Max length6
Median length4
Mean length4.3691203
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
제공게임물명 514
 
18.5%

Length

2024-04-16T20:42:08.254684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.343473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
제공게임물명 514
 
18.5%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
제작취급품목내용
514 

Length

Max length8
Median length4
Mean length4.7382406
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
제작취급품목내용 514
 
18.5%

Length

2024-04-16T20:42:08.431671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.516906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
제작취급품목내용 514
 
18.5%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:08.606440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.696020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

lghtfacilinillu
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
조명시설조도
514 

Length

Max length6
Median length4
Mean length4.3691203
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
조명시설조도 514
 
18.5%

Length

2024-04-16T20:42:08.792754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:08.879734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
조명시설조도 514
 
18.5%

nearenvnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2090 
주변환경명
498 
기타
 
152
유흥업소밀집지역
 
25
아파트지역
 
9
Other values (2)
 
11

Length

Max length8
Median length4
Mean length4.1170557
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2090
75.0%
주변환경명 498
 
17.9%
기타 152
 
5.5%
유흥업소밀집지역 25
 
0.9%
아파트지역 9
 
0.3%
주택가주변 7
 
0.3%
학교정화(상대) 4
 
0.1%

Length

2024-04-16T20:42:09.211579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:09.297035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2090
75.0%
주변환경명 498
 
17.9%
기타 152
 
5.5%
유흥업소밀집지역 25
 
0.9%
아파트지역 9
 
0.3%
주택가주변 7
 
0.3%
학교정화(상대 4
 
0.1%

jisgnumlay
Categorical

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
1669 
지상층수
451 
10
 
120
7
 
72
9
 
65
Other values (18)
408 

Length

Max length4
Median length4
Mean length3.3795332
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1669
59.9%
지상층수 451
 
16.2%
10 120
 
4.3%
7 72
 
2.6%
9 65
 
2.3%
8 53
 
1.9%
2 52
 
1.9%
5 43
 
1.5%
3 33
 
1.2%
4 33
 
1.2%
Other values (13) 194
 
7.0%

Length

2024-04-16T20:42:09.408194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1669
59.9%
지상층수 451
 
16.2%
10 120
 
4.3%
7 72
 
2.6%
9 65
 
2.3%
8 53
 
1.9%
2 52
 
1.9%
5 43
 
1.5%
3 33
 
1.2%
4 33
 
1.2%
Other values (13) 194
 
7.0%

regnsenm
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2007 
지역구분명
489 
일반상업지역
 
99
준주거지역
 
53
상업지역
 
50
Other values (9)
 
87

Length

Max length6
Median length4
Mean length4.3138241
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2007
72.1%
지역구분명 489
 
17.6%
일반상업지역 99
 
3.6%
준주거지역 53
 
1.9%
상업지역 50
 
1.8%
중심상업지역 24
 
0.9%
일반주거지역 20
 
0.7%
자연녹지지역 15
 
0.5%
주거지역 10
 
0.4%
녹지지역 8
 
0.3%
Other values (4) 10
 
0.4%

Length

2024-04-16T20:42:09.520565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2007
72.1%
지역구분명 489
 
17.6%
일반상업지역 99
 
3.6%
준주거지역 53
 
1.9%
상업지역 50
 
1.8%
중심상업지역 24
 
0.9%
일반주거지역 20
 
0.7%
자연녹지지역 15
 
0.5%
주거지역 10
 
0.4%
녹지지역 8
 
0.3%
Other values (4) 10
 
0.4%

undernumlay
Categorical

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
1722 
지하층수
475 
3
 
148
2
 
114
1
 
111
Other values (9)
215 

Length

Max length4
Median length4
Mean length3.367684
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1722
61.8%
지하층수 475
 
17.1%
3 148
 
5.3%
2 114
 
4.1%
1 111
 
4.0%
5 81
 
2.9%
6 52
 
1.9%
4 33
 
1.2%
7 25
 
0.9%
8 18
 
0.6%
Other values (4) 6
 
0.2%

Length

2024-04-16T20:42:09.657045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1722
61.8%
지하층수 475
 
17.1%
3 148
 
5.3%
2 114
 
4.1%
1 111
 
4.0%
5 81
 
2.9%
6 52
 
1.9%
4 33
 
1.2%
7 25
 
0.9%
8 18
 
0.6%
Other values (4) 6
 
0.2%

bgroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
청소년실수
514 

Length

Max length5
Median length4
Mean length4.1845601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
청소년실수 514
 
18.5%

Length

2024-04-16T20:42:09.768069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:09.864716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
청소년실수 514
 
18.5%

bgroomyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:09.970492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:10.053229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

totgasyscnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
총게임기수
514 

Length

Max length5
Median length4
Mean length4.1845601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
총게임기수 514
 
18.5%

Length

2024-04-16T20:42:10.133521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:10.209212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
총게임기수 514
 
18.5%

totnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
1839 
총층수
462 
11
 
61
3
 
57
10
 
47
Other values (23)
319 

Length

Max length4
Median length4
Mean length3.4236984
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1839
66.0%
총층수 462
 
16.6%
11 61
 
2.2%
3 57
 
2.0%
10 47
 
1.7%
13 45
 
1.6%
14 32
 
1.1%
2 28
 
1.0%
15 21
 
0.8%
9 20
 
0.7%
Other values (18) 173
 
6.2%

Length

2024-04-16T20:42:10.306489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1839
66.0%
총층수 462
 
16.6%
11 61
 
2.2%
3 57
 
2.0%
10 47
 
1.7%
13 45
 
1.6%
14 32
 
1.1%
2 28
 
1.0%
15 21
 
0.8%
9 20
 
0.7%
Other values (18) 173
 
6.2%

frstregts
Real number (ℝ)

Distinct639
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20177488
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-16T20:42:10.433324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20060926
Q120181207
median20190702
Q320200319
95-th percentile20201106
Maximum22030212
Range2579197
Interquartile range (IQR)19112

Descriptive statistics

Standard deviation60007.348
Coefficient of variation (CV)0.0029739752
Kurtosis340.14968
Mean20177488
Median Absolute Deviation (MAD)9601
Skewness8.2364052
Sum5.6194304 × 1010
Variance3.6008818 × 109
MonotonicityNot monotonic
2024-04-16T20:42:10.557943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190315 30
 
1.1%
20190412 30
 
1.1%
20190503 27
 
1.0%
20200221 26
 
0.9%
20200214 26
 
0.9%
20181207 25
 
0.9%
20181025 24
 
0.9%
20190322 24
 
0.9%
20190125 24
 
0.9%
20190111 24
 
0.9%
Other values (629) 2525
90.7%
ValueCountFrequency (%)
19451015 1
< 0.1%
19591023 1
< 0.1%
19690925 1
< 0.1%
19820125 1
< 0.1%
19910826 1
< 0.1%
19930814 2
0.1%
19970308 1
< 0.1%
19980307 1
< 0.1%
19980319 1
< 0.1%
19980623 1
< 0.1%
ValueCountFrequency (%)
22030212 1
 
< 0.1%
20201231 2
 
0.1%
20201230 4
0.1%
20201229 2
 
0.1%
20201228 4
0.1%
20201224 3
0.1%
20201223 6
0.2%
20201222 4
0.1%
20201218 6
0.2%
20201217 2
 
0.1%

pasgbreth
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2030 
통로너비
501 
1
 
145
1.2
 
19
1050
 
12
Other values (23)
 
78

Length

Max length5
Median length4
Mean length3.8229803
Min length1

Unique

Unique10 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2030
72.9%
통로너비 501
 
18.0%
1 145
 
5.2%
1.2 19
 
0.7%
1050 12
 
0.4%
1.5 12
 
0.4%
1.3 10
 
0.4%
1.1 9
 
0.3%
1.08 9
 
0.3%
1.45 5
 
0.2%
Other values (18) 33
 
1.2%

Length

2024-04-16T20:42:10.692991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2030
72.9%
통로너비 501
 
18.0%
1 145
 
5.2%
1.2 19
 
0.7%
1050 12
 
0.4%
1.5 12
 
0.4%
1.3 10
 
0.4%
1.1 9
 
0.3%
1.08 9
 
0.3%
1.45 5
 
0.2%
Other values (18) 33
 
1.2%

speclghtyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:10.803312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:10.889744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
514 

Length

Max length4
Median length4
Mean length3.4463196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
514
 
18.5%

Length

2024-04-16T20:42:10.975932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:11.062277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
514
 
18.5%

actlnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
<NA>
2271 
품목명
514 

Length

Max length4
Median length4
Mean length3.8154399
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2271
81.5%
품목명 514
 
18.5%

Length

2024-04-16T20:42:11.164203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:11.242068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
81.5%
품목명 514
 
18.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.9 KiB
Minimum2021-01-04 21:10:25
Maximum2021-01-04 21:10:26
2024-04-16T20:42:11.311711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:42:11.389777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

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>03폐업384872.10053800000179957.0892370000020080506140353<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>20050415<NA><NA><NA><NA>2021-01-04 21:10:25
123250000CDFF422000201700000303_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162055<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-01-04 21:10:25
233250000CDFF422000201700000603_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162131<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-01-04 21:10:25
343250000CDFF422000201700000503_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제5관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162119<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-01-04 21:10:25
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>13영업중384992.28324900000179919.4370090000020180621102116<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19820125<NA><NA><NA><NA>2021-01-04 21:10:25
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>13영업중384992.28324900000179919.4370090000020180621102237<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-01-04 21:10:25
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>13영업중384992.28324900000179919.4370090000020180621103110<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-01-04 21:10:25
783250000CDFF422000199800000103_13_02_PI2018-08-31 23:59:59.0<NA>삼보극장600807부산광역시 중구 부평동2가 56번지48947<NA>1998030720070725<NA><NA><NA>03폐업<NA><NA>20070725183312<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19980307<NA><NA><NA><NA>2021-01-04 21:10:25
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>03폐업385057.25808100000179919.4880840000020160617104121<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1019990716<NA><NA><NA><NA>2021-01-04 21:10:25
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>03폐업385057.25808100000179919.4880840000020160617104156<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>4<NA><NA><NA><NA>19990716<NA><NA><NA><NA>2021-01-04 21:10:25
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
277527883110000CDFF521101202000001203_13_05_PI2020-12-31 00:23:05.0영화제작업주식회사 영화사플레이리스트<NA>서울특별시 은평구 증산동 산 10-22 한신빌라 상가동 101호3494서울특별시 은평구 증산로9길 36-5, 상가동 101호 (증산동, 한신빌라)20201229<NA><NA><NA><NA>영업/정상영업중191687.439669628453867.31029504420201229100032<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>20201229<NA><NA><NA><NA>2021-01-04 21:10:26
277627893220000CDFF521103202000003203_13_01_PI2020-12-31 00:23:05.0영화배급업(주)뉴스와이<NA>서울특별시 강남구 삼성동 121-56155서울특별시 강남구 삼성로107길 13, 지하층 (삼성동)20111007<NA><NA><NA><NA>영업/정상영업중204597.940769361445449.22413669320201229102556<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>20111007<NA><NA><NA><NA>2021-01-04 21:10:26
277727903220000CDFF521101202000007203_13_05_PI2020-12-31 00:23:05.0영화제작업(주)뉴스와이<NA>서울특별시 강남구 삼성동 121-56155서울특별시 강남구 삼성로107길 13, 지하층 (삼성동)20111007<NA><NA><NA><NA>영업/정상영업중204597.940769361445449.22413669320201229102546<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>20111007<NA><NA><NA><NA>2021-01-04 21:10:26
277827913220000CDFF521102202000002203_13_04_PI2020-12-31 00:23:05.0영화수입업(주)뉴스와이<NA>서울특별시 강남구 삼성동 121-56155서울특별시 강남구 삼성로107길 13, 지하층 (삼성동)20111007<NA><NA><NA><NA>영업/정상영업중204597.940769361445449.22413669320201229102608<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>20111007<NA><NA><NA><NA>2021-01-04 21:10:26
277927923050000CDFF521101202000000503_13_05_PI2021-01-01 00:23:05.0영화제작업(주)스페이스포지번우편번호서울특별시 동대문구 용두동 237-24 승원빌라2585서울특별시 동대문구 천호대로25길 45, 201호 (용두동, 승원빌라)20201230폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중202931.650778943452651.64913022320201230164010업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20201230통로너비품목명2021-01-04 21:10:26
278027933230000CDFF521101202000000603_13_05_PI2021-01-01 00:23:05.0영화제작업즐거운상상<NA>서울특별시 송파구 잠실동 295-175574서울특별시 송파구 백제고분로12길 8-10, 201호 (잠실동)20201230<NA><NA><NA><NA>영업/정상영업중207043.444918134444832.8050592420201230175549<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>20201230<NA><NA><NA><NA>2021-01-04 21:10:26
278127943570000CDFF521103202000000203_13_01_PI2021-01-01 00:23:05.0영화배급업강화군작은영화관 주식회사<NA>인천광역시 강화군 강화읍 국화리 239 강화문예회관23028인천광역시 강화군 강화읍 고비고개로19번길 12, 강화문예회관 2층20201230<NA><NA><NA><NA>영업/정상영업중153562.217984173471636.37720440320201230181742<NA>0329347053<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>20201230<NA><NA><NA><NA>2021-01-04 21:10:26
278227953570000CDFF521104202000000103_13_03_PI2021-01-01 00:23:05.0영화상영업강화군작은영화관 주식회사<NA>인천광역시 강화군 강화읍 국화리 239 강화문예회관23028인천광역시 강화군 강화읍 고비고개로19번길 12, 강화문예회관 2층20201230<NA><NA><NA><NA>영업/정상영업중153562.217984173471636.37720440320201230181643<NA>0329347053<NA><NA><NA><NA><NA>영화상영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20201230<NA><NA><NA><NA>2021-01-04 21:10:26
278327964090000CDFF521103202000000303_13_01_PI2021-01-02 00:23:15.0영화배급업용성 인터내셔날지번우편번호경기도 김포시 걸포동 1-24 김포현대공구타운10092경기도 김포시 금포로 1117-18, 김포현대공구타운 가동 1층 4호 (걸포동)20201231폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중174038.638517377460367.10774115920201231182744업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20201231통로너비품목명2021-01-04 21:10:26
278427973740000CDFF521101202000000603_13_05_PI2021-01-02 00:23:15.0영화제작업모티브미디어 주식회사<NA>경기도 수원시 팔달구 인계동 1046-1 남경빌딩16490경기도 수원시 팔달구 권광로 173, 남경빌딩 지하1층 101호 (인계동)20201231<NA><NA><NA><NA>영업/정상영업중202763.475383886417905.98062984720201231114327<NA>031-775-1879<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>20201231<NA><NA><NA><NA>2021-01-04 21:10:26