Overview

Dataset statistics

Number of variables56
Number of observations2757
Missing cells2416
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
Categorical41
DateTime1

Alerts

last_load_dttm has constant value ""Constant
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 (71.2%)Imbalance
dtlstatenm is highly imbalanced (81.1%)Imbalance
bdngsrvnm is highly imbalanced (58.9%)Imbalance
facilar is highly imbalanced (71.8%)Imbalance
nearenvnm is highly imbalanced (60.5%)Imbalance
regnsenm is highly imbalanced (63.0%)Imbalance
totnumlay is highly imbalanced (58.6%)Imbalance
pasgbreth is highly imbalanced (72.1%)Imbalance
dcbymd has 2062 (74.8%) missing valuesMissing
x has 98 (3.6%) missing valuesMissing
y has 98 (3.6%) missing valuesMissing
sitetel has 151 (5.5%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:42:13.631761
Analysis finished2024-04-16 11:42:15.041127
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2757
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1384.8128
Minimum1
Maximum2769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:15.097391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile138.8
Q1693
median1384
Q32079
95-th percentile2631.2
Maximum2769
Range2768
Interquartile range (IQR)1386

Descriptive statistics

Standard deviation800.06822
Coefficient of variation (CV)0.57774465
Kurtosis-1.200588
Mean1384.8128
Median Absolute Deviation (MAD)693
Skewness0.0016424814
Sum3817929
Variance640109.15
MonotonicityNot monotonic
2024-04-16T20:42:15.212860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1850 1
 
< 0.1%
1842 1
 
< 0.1%
1843 1
 
< 0.1%
1844 1
 
< 0.1%
1845 1
 
< 0.1%
1846 1
 
< 0.1%
1847 1
 
< 0.1%
1848 1
 
< 0.1%
1849 1
 
< 0.1%
Other values (2747) 2747
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 (%)
2769 1
< 0.1%
2768 1
< 0.1%
2767 1
< 0.1%
2766 1
< 0.1%
2765 1
< 0.1%
2764 1
< 0.1%
2763 1
< 0.1%
2762 1
< 0.1%
2761 1
< 0.1%
2760 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct156
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3629799.4
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:15.328736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3020000
Q13160000
median3290000
Q33860000
95-th percentile5530000
Maximum6520000
Range3520000
Interquartile range (IQR)700000

Descriptive statistics

Standard deviation753101.28
Coefficient of variation (CV)0.20747738
Kurtosis2.9425829
Mean3629799.4
Median Absolute Deviation (MAD)190000
Skewness1.8548447
Sum1.0007357 × 1010
Variance5.6716154 × 1011
MonotonicityNot monotonic
2024-04-16T20:42:15.444500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3220000 291
 
10.6%
3130000 182
 
6.6%
3210000 144
 
5.2%
3330000 107
 
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) 1653
60.0%
ValueCountFrequency (%)
3000000 60
2.2%
3010000 49
1.8%
3020000 63
2.3%
3030000 64
2.3%
3040000 33
1.2%
3050000 24
 
0.9%
3060000 16
 
0.6%
3070000 20
 
0.7%
3080000 4
 
0.1%
3090000 9
 
0.3%
ValueCountFrequency (%)
6520000 3
 
0.1%
6510000 33
1.2%
5710000 18
0.7%
5690000 11
 
0.4%
5680000 8
 
0.3%
5670000 18
0.7%
5600000 20
0.7%
5590000 13
 
0.5%
5540000 4
 
0.1%
5530000 12
 
0.4%

mgtno
Text

Distinct560
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2024-04-16T20:42:15.631219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters55140
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

Unique268 ?
Unique (%)9.7%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012019000001 110
 
4.0%
cdff5211012020000001 94
 
3.4%
cdff5211012019000002 77
 
2.8%
cdff5211032020000001 68
 
2.5%
cdff5211042020000001 65
 
2.4%
cdff5211012020000002 63
 
2.3%
cdff5211032019000001 58
 
2.1%
cdff4220002020000001 51
 
1.8%
cdff5211022020000001 50
 
1.8%
cdff5211012019000003 50
 
1.8%
Other values (550) 2071
75.1%
2024-04-16T20:42:15.917248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21660
39.3%
2 8218
 
14.9%
1 7667
 
13.9%
F 5514
 
10.0%
C 2757
 
5.0%
D 2757
 
5.0%
5 2253
 
4.1%
4 1322
 
2.4%
9 1300
 
2.4%
3 800
 
1.5%
Other values (3) 892
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44112
80.0%
Uppercase Letter 11028
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21660
49.1%
2 8218
 
18.6%
1 7667
 
17.4%
5 2253
 
5.1%
4 1322
 
3.0%
9 1300
 
2.9%
3 800
 
1.8%
8 417
 
0.9%
6 253
 
0.6%
7 222
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 5514
50.0%
C 2757
25.0%
D 2757
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44112
80.0%
Latin 11028
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21660
49.1%
2 8218
 
18.6%
1 7667
 
17.4%
5 2253
 
5.1%
4 1322
 
3.0%
9 1300
 
2.9%
3 800
 
1.8%
8 417
 
0.9%
6 253
 
0.6%
7 222
 
0.5%
Latin
ValueCountFrequency (%)
F 5514
50.0%
C 2757
25.0%
D 2757
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21660
39.3%
2 8218
 
14.9%
1 7667
 
13.9%
F 5514
 
10.0%
C 2757
 
5.0%
D 2757
 
5.0%
5 2253
 
4.1%
4 1322
 
2.4%
9 1300
 
2.4%
3 800
 
1.5%
Other values (3) 892
 
1.6%

opnsvcid
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
03_13_05_P
1130 
03_13_02_P
784 
03_13_01_P
402 
03_13_04_P
235 
03_13_03_P
206 

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 1130
41.0%
03_13_02_P 784
28.4%
03_13_01_P 402
 
14.6%
03_13_04_P 235
 
8.5%
03_13_03_P 206
 
7.5%

Length

2024-04-16T20:42:16.037591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:16.123398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_05_p 1130
41.0%
03_13_02_p 784
28.4%
03_13_01_p 402
 
14.6%
03_13_04_p 235
 
8.5%
03_13_03_p 206
 
7.5%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
I
2178 
U
579 

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 2178
79.0%
U 579
 
21.0%

Length

2024-04-16T20:42:16.220357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:16.300816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2178
79.0%
u 579
 
21.0%
Distinct619
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-22 00:23:05
2024-04-16T20:42:16.391057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:42:16.541182image/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 size21.7 KiB
영화제작업
1130 
영화상영관
564 
영화배급업
402 
영화수입업
235 
<NA>
220 

Length

Max length5
Median length5
Mean length4.9202031
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화제작업 1130
41.0%
영화상영관 564
20.5%
영화배급업 402
 
14.6%
영화수입업 235
 
8.5%
<NA> 220
 
8.0%
영화상영업 206
 
7.5%

Length

2024-04-16T20:42:16.651378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:16.958155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1130
41.0%
영화상영관 564
20.5%
영화배급업 402
 
14.6%
영화수입업 235
 
8.5%
na 220
 
8.0%
영화상영업 206
 
7.5%

bplcnm
Text

Distinct1683
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2024-04-16T20:42:17.178311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length10.463547
Min length2

Characters and Unicode

Total characters28848
Distinct characters625
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

Unique1161 ?
Unique (%)42.1%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
주식회사 667
 
12.9%
롯데시네마 188
 
3.6%
cgv 130
 
2.5%
1관 91
 
1.8%
2관 89
 
1.7%
85
 
1.6%
메가박스 79
 
1.5%
3관 60
 
1.2%
4관 56
 
1.1%
메가박스중앙(주 54
 
1.0%
Other values (1424) 3654
70.9%
2024-04-16T20:42:17.542366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2398
 
8.3%
1461
 
5.1%
985
 
3.4%
888
 
3.1%
867
 
3.0%
) 862
 
3.0%
( 845
 
2.9%
728
 
2.5%
688
 
2.4%
679
 
2.4%
Other values (615) 18447
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22066
76.5%
Space Separator 2398
 
8.3%
Uppercase Letter 1360
 
4.7%
Close Punctuation 863
 
3.0%
Open Punctuation 846
 
2.9%
Decimal Number 839
 
2.9%
Lowercase Letter 422
 
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 (%)
1461
 
6.6%
985
 
4.5%
888
 
4.0%
867
 
3.9%
728
 
3.3%
688
 
3.1%
679
 
3.1%
398
 
1.8%
391
 
1.8%
389
 
1.8%
Other values (544) 14592
66.1%
Uppercase Letter
ValueCountFrequency (%)
C 300
22.1%
G 269
19.8%
V 254
18.7%
E 58
 
4.3%
A 49
 
3.6%
M 45
 
3.3%
S 38
 
2.8%
I 35
 
2.6%
N 32
 
2.4%
T 31
 
2.3%
Other values (16) 249
18.3%
Lowercase Letter
ValueCountFrequency (%)
e 45
 
10.7%
o 35
 
8.3%
i 34
 
8.1%
m 30
 
7.1%
a 28
 
6.6%
r 26
 
6.2%
n 24
 
5.7%
l 23
 
5.5%
d 22
 
5.2%
t 22
 
5.2%
Other values (12) 133
31.5%
Decimal Number
ValueCountFrequency (%)
1 170
20.3%
2 151
18.0%
3 112
13.3%
4 98
11.7%
5 88
10.5%
6 85
10.1%
7 56
 
6.7%
8 35
 
4.2%
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 (%)
) 862
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 845
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2398
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 22084
76.6%
Common 4982
 
17.3%
Latin 1782
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1461
 
6.6%
985
 
4.5%
888
 
4.0%
867
 
3.9%
728
 
3.3%
688
 
3.1%
679
 
3.1%
398
 
1.8%
391
 
1.8%
389
 
1.8%
Other values (545) 14610
66.2%
Latin
ValueCountFrequency (%)
C 300
16.8%
G 269
15.1%
V 254
 
14.3%
E 58
 
3.3%
A 49
 
2.7%
M 45
 
2.5%
e 45
 
2.5%
S 38
 
2.1%
o 35
 
2.0%
I 35
 
2.0%
Other values (38) 654
36.7%
Common
ValueCountFrequency (%)
2398
48.1%
) 862
 
17.3%
( 845
 
17.0%
1 170
 
3.4%
2 151
 
3.0%
3 112
 
2.2%
4 98
 
2.0%
5 88
 
1.8%
6 85
 
1.7%
7 56
 
1.1%
Other values (12) 117
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22066
76.5%
ASCII 6764
 
23.4%
None 18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2398
35.5%
) 862
 
12.7%
( 845
 
12.5%
C 300
 
4.4%
G 269
 
4.0%
V 254
 
3.8%
1 170
 
2.5%
2 151
 
2.2%
3 112
 
1.7%
4 98
 
1.4%
Other values (60) 1305
19.3%
Hangul
ValueCountFrequency (%)
1461
 
6.6%
985
 
4.5%
888
 
4.0%
867
 
3.9%
728
 
3.3%
688
 
3.1%
679
 
3.1%
398
 
1.8%
391
 
1.8%
389
 
1.8%
Other values (544) 14592
66.1%
None
ValueCountFrequency (%)
18
100.0%

sitepostno
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2216 
지번우편번호
508 
607787
 
7
614845
 
4
601060
 
3
Other values (14)
 
19

Length

Max length6
Median length4
Mean length4.3924556
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> 2216
80.4%
지번우편번호 508
 
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

2024-04-16T20:42:17.670651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2216
80.4%
지번우편번호 508
 
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%
Distinct1184
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2024-04-16T20:42:17.938744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length27.352557
Min length15

Characters and Unicode

Total characters75411
Distinct characters526
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

Unique649 ?
Unique (%)23.5%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1번지
3rd row부산광역시 중구 남포동5가 12-1번지
4th row부산광역시 중구 남포동5가 12-1번지
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
서울특별시 1308
 
9.2%
경기도 472
 
3.3%
부산광역시 395
 
2.8%
강남구 291
 
2.0%
마포구 182
 
1.3%
서초구 145
 
1.0%
중구 139
 
1.0%
해운대구 107
 
0.8%
논현동 96
 
0.7%
경상남도 89
 
0.6%
Other values (2822) 11021
77.4%
2024-04-16T20:42:18.334473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13904
 
18.4%
2912
 
3.9%
1 2841
 
3.8%
2806
 
3.7%
2283
 
3.0%
2240
 
3.0%
2059
 
2.7%
- 2031
 
2.7%
1803
 
2.4%
2 1724
 
2.3%
Other values (516) 40808
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45309
60.1%
Space Separator 13904
 
18.4%
Decimal Number 13138
 
17.4%
Dash Punctuation 2031
 
2.7%
Uppercase Letter 712
 
0.9%
Lowercase Letter 111
 
0.1%
Other Punctuation 56
 
0.1%
Math Symbol 50
 
0.1%
Close Punctuation 46
 
0.1%
Open Punctuation 46
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2912
 
6.4%
2806
 
6.2%
2283
 
5.0%
2240
 
4.9%
2059
 
4.5%
1803
 
4.0%
1400
 
3.1%
1360
 
3.0%
1358
 
3.0%
989
 
2.2%
Other values (458) 26099
57.6%
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%
t 13
11.7%
c 13
11.7%
y 9
8.1%
r 6
 
5.4%
a 6
 
5.4%
o 3
 
2.7%
s 3
 
2.7%
Other values (4) 7
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 2841
21.6%
2 1724
13.1%
3 1321
10.1%
4 1182
9.0%
5 1176
9.0%
0 1175
8.9%
6 1114
 
8.5%
7 970
 
7.4%
9 849
 
6.5%
8 786
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 37
66.1%
& 19
33.9%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
13904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2031
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45309
60.1%
Common 29271
38.8%
Latin 831
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2912
 
6.4%
2806
 
6.2%
2283
 
5.0%
2240
 
4.9%
2059
 
4.5%
1803
 
4.0%
1400
 
3.1%
1360
 
3.0%
1358
 
3.0%
989
 
2.2%
Other values (458) 26099
57.6%
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 (%)
13904
47.5%
1 2841
 
9.7%
- 2031
 
6.9%
2 1724
 
5.9%
3 1321
 
4.5%
4 1182
 
4.0%
5 1176
 
4.0%
0 1175
 
4.0%
6 1114
 
3.8%
7 970
 
3.3%
Other values (7) 1833
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45309
60.1%
ASCII 30094
39.9%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13904
46.2%
1 2841
 
9.4%
- 2031
 
6.7%
2 1724
 
5.7%
3 1321
 
4.4%
4 1182
 
3.9%
5 1176
 
3.9%
0 1175
 
3.9%
6 1114
 
3.7%
7 970
 
3.2%
Other values (46) 2656
 
8.8%
Hangul
ValueCountFrequency (%)
2912
 
6.4%
2806
 
6.2%
2283
 
5.0%
2240
 
4.9%
2059
 
4.5%
1803
 
4.0%
1400
 
3.1%
1360
 
3.0%
1358
 
3.0%
989
 
2.2%
Other values (458) 26099
57.6%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

rdnpostno
Real number (ℝ)

Distinct931
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20633.625
Minimum1096
Maximum63627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:18.457907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1096
5-th percentile3182
Q16021
median10881
Q341484
95-th percentile54654
Maximum63627
Range62531
Interquartile range (IQR)35463

Descriptive statistics

Standard deviation19015.247
Coefficient of variation (CV)0.921566
Kurtosis-0.9527113
Mean20633.625
Median Absolute Deviation (MAD)6813
Skewness0.81132949
Sum56886903
Variance3.6157961 × 108
MonotonicityNot monotonic
2024-04-16T20:42:18.584783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 77
 
2.8%
48058 38
 
1.4%
34913 24
 
0.9%
7567 24
 
0.9%
44249 21
 
0.8%
3993 21
 
0.8%
6040 20
 
0.7%
6627 20
 
0.7%
48953 20
 
0.7%
16914 19
 
0.7%
Other values (921) 2473
89.7%
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%
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%
63168 1
 
< 0.1%
Distinct1220
Distinct (%)44.4%
Missing7
Missing (%)0.3%
Memory size21.7 KiB
2024-04-16T20:42:18.884167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length50
Mean length34.932364
Min length5

Characters and Unicode

Total characters96064
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

Unique670 ?
Unique (%)24.4%

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 1307
 
6.9%
경기도 470
 
2.5%
부산광역시 389
 
2.1%
강남구 291
 
1.5%
2층 213
 
1.1%
마포구 181
 
1.0%
3층 164
 
0.9%
서초구 145
 
0.8%
중구 136
 
0.7%
4층 128
 
0.7%
Other values (3321) 15522
81.9%
2024-04-16T20:42:19.315103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16225
 
16.9%
1 3522
 
3.7%
3379
 
3.5%
2839
 
3.0%
, 2807
 
2.9%
2733
 
2.8%
) 2518
 
2.6%
( 2518
 
2.6%
2 2328
 
2.4%
2323
 
2.4%
Other values (556) 54872
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54663
56.9%
Space Separator 16225
 
16.9%
Decimal Number 15768
 
16.4%
Other Punctuation 2826
 
2.9%
Close Punctuation 2518
 
2.6%
Open Punctuation 2518
 
2.6%
Uppercase Letter 810
 
0.8%
Dash Punctuation 496
 
0.5%
Lowercase Letter 120
 
0.1%
Math Symbol 112
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3379
 
6.2%
2839
 
5.2%
2733
 
5.0%
2323
 
4.2%
1899
 
3.5%
1414
 
2.6%
1360
 
2.5%
1357
 
2.5%
1298
 
2.4%
1291
 
2.4%
Other values (495) 34770
63.6%
Uppercase Letter
ValueCountFrequency (%)
C 82
 
10.1%
B 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%
a 6
 
5.0%
b 6
 
5.0%
r 6
 
5.0%
o 3
 
2.5%
Other values (6) 11
9.2%
Decimal Number
ValueCountFrequency (%)
1 3522
22.3%
2 2328
14.8%
0 2019
12.8%
3 1745
11.1%
4 1371
 
8.7%
5 1299
 
8.2%
6 935
 
5.9%
7 921
 
5.8%
9 838
 
5.3%
8 790
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2807
99.3%
& 19
 
0.7%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
16225
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2518
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 496
100.0%
Math Symbol
ValueCountFrequency (%)
~ 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54663
56.9%
Common 40463
42.1%
Latin 938
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3379
 
6.2%
2839
 
5.2%
2733
 
5.0%
2323
 
4.2%
1899
 
3.5%
1414
 
2.6%
1360
 
2.5%
1357
 
2.5%
1298
 
2.4%
1291
 
2.4%
Other values (495) 34770
63.6%
Latin
ValueCountFrequency (%)
C 82
 
8.7%
B 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 (%)
16225
40.1%
1 3522
 
8.7%
, 2807
 
6.9%
) 2518
 
6.2%
( 2518
 
6.2%
2 2328
 
5.8%
0 2019
 
5.0%
3 1745
 
4.3%
4 1371
 
3.4%
5 1299
 
3.2%
Other values (7) 4111
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54663
56.9%
ASCII 41393
43.1%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16225
39.2%
1 3522
 
8.5%
, 2807
 
6.8%
) 2518
 
6.1%
( 2518
 
6.1%
2 2328
 
5.6%
0 2019
 
4.9%
3 1745
 
4.2%
4 1371
 
3.3%
5 1299
 
3.1%
Other values (49) 5041
 
12.2%
Hangul
ValueCountFrequency (%)
3379
 
6.2%
2839
 
5.2%
2733
 
5.0%
2323
 
4.2%
1899
 
3.5%
1414
 
2.6%
1360
 
2.5%
1357
 
2.5%
1298
 
2.4%
1291
 
2.4%
Other values (495) 34770
63.6%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

apvpermymd
Real number (ℝ)

Distinct631
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20177345
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:19.448910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20060926
Q120181207
median20190626
Q320200313
95-th percentile20201030
Maximum22030212
Range2579197
Interquartile range (IQR)19106

Descriptive statistics

Standard deviation60228.918
Coefficient of variation (CV)0.0029849773
Kurtosis338.64707
Mean20177345
Median Absolute Deviation (MAD)9600
Skewness8.2366907
Sum5.562894 × 1010
Variance3.6275226 × 109
MonotonicityNot monotonic
2024-04-16T20:42:19.570520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190412 30
 
1.1%
20190315 30
 
1.1%
20190503 27
 
1.0%
20200221 26
 
0.9%
20200214 26
 
0.9%
20181207 25
 
0.9%
20190322 24
 
0.9%
20190111 24
 
0.9%
20190125 24
 
0.9%
20181025 24
 
0.9%
Other values (621) 2497
90.6%
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%
20201218 6
0.2%
20201217 2
 
0.1%
20201216 9
0.3%
20201215 4
 
0.1%
20201214 1
 
< 0.1%
20201211 10
0.4%
20201208 10
0.4%
20201207 3
 
0.1%
20201204 2
 
0.1%

dcbymd
Text

MISSING 

Distinct85
Distinct (%)12.2%
Missing2062
Missing (%)74.8%
Memory size21.7 KiB
2024-04-16T20:42:19.776412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length5.0877698
Min length4

Characters and Unicode

Total characters3536
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

Unique48 ?
Unique (%)6.9%

Sample

1st row20080501
2nd row20070725
3rd row20160617
4th row20160617
5th row20160617
ValueCountFrequency (%)
폐업일자 506
72.8%
20200805 12
 
1.7%
20170315 10
 
1.4%
20160617 8
 
1.2%
20110616 8
 
1.2%
20200211 8
 
1.2%
20100806 7
 
1.0%
20200907 6
 
0.9%
20200713 5
 
0.7%
20201119 4
 
0.6%
Other values (75) 121
 
17.4%
2024-04-16T20:42:20.113754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 548
15.5%
506
14.3%
506
14.3%
506
14.3%
506
14.3%
2 384
10.9%
1 244
6.9%
6 69
 
2.0%
7 62
 
1.8%
9 59
 
1.7%
Other values (4) 146
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2024
57.2%
Decimal Number 1512
42.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 548
36.2%
2 384
25.4%
1 244
16.1%
6 69
 
4.6%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 29
 
1.9%
Other Letter
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2024
57.2%
Common 1512
42.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 548
36.2%
2 384
25.4%
1 244
16.1%
6 69
 
4.6%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 29
 
1.9%
Hangul
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2024
57.2%
ASCII 1512
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 548
36.2%
2 384
25.4%
1 244
16.1%
6 69
 
4.6%
7 62
 
4.1%
9 59
 
3.9%
3 45
 
3.0%
5 39
 
2.6%
8 33
 
2.2%
4 29
 
1.9%
Hangul
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2247 
휴업시작일자
509 
20200210
 
1

Length

Max length8
Median length4
Mean length4.3706928
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> 2247
81.5%
휴업시작일자 509
 
18.5%
20200210 1
 
< 0.1%

Length

2024-04-16T20:42:20.240479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:20.334991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2247
81.5%
휴업시작일자 509
 
18.5%
20200210 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2247 
휴업종료일자
509 
20210131
 
1

Length

Max length8
Median length4
Mean length4.3706928
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> 2247
81.5%
휴업종료일자 509
 
18.5%
20210131 1
 
< 0.1%

Length

2024-04-16T20:42:20.430171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:20.517141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2247
81.5%
휴업종료일자 509
 
18.5%
20210131 1
 
< 0.1%

ropnymd
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
재개업일자
509 

Length

Max length5
Median length4
Mean length4.184621
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> 2248
81.5%
재개업일자 509
 
18.5%

Length

2024-04-16T20:42:20.609248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:20.699514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
재개업일자 509
 
18.5%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
영업/정상
2359 
13
 
163
제외/삭제/전출
 
97
03
 
56
폐업
 
36
Other values (4)
 
46

Length

Max length8
Median length5
Mean length4.8099383
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 2359
85.6%
13 163
 
5.9%
제외/삭제/전출 97
 
3.5%
03 56
 
2.0%
폐업 36
 
1.3%
<NA> 36
 
1.3%
영업상태 8
 
0.3%
35 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:42:20.785330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:20.883345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2359
85.6%
13 163
 
5.9%
제외/삭제/전출 97
 
3.5%
03 56
 
2.0%
폐업 36
 
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 size21.7 KiB
영업중
2566 
전출
 
97
폐업
 
92
직권말소
 
1
휴업
 
1

Length

Max length4
Median length3
Mean length2.9314472
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2566
93.1%
전출 97
 
3.5%
폐업 92
 
3.3%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:42:21.020679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:21.126867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2566
93.1%
전출 97
 
3.5%
폐업 92
 
3.3%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

x
Text

MISSING 

Distinct1073
Distinct (%)40.4%
Missing98
Missing (%)3.6%
Memory size21.7 KiB
2024-04-16T20:42:21.310407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.936442
Min length7

Characters and Unicode

Total characters53011
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

Unique547 ?
Unique (%)20.6%

Sample

1st row384872.10053800000
2nd row384985.448097939
3rd row384985.448097939
4th row384985.448097939
5th row384992.28324900000
ValueCountFrequency (%)
238010.315065 24
 
0.9%
187210.917773717 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
 
0.5%
197257.765183997 12
 
0.5%
Other values (1063) 2487
93.5%
2024-04-16T20:42:21.607120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11710
22.1%
0 4727
8.9%
2 4526
 
8.5%
1 4413
 
8.3%
3 4137
 
7.8%
9 3976
 
7.5%
8 3564
 
6.7%
7 3525
 
6.6%
5 3433
 
6.5%
6 3161
 
6.0%
Other values (9) 5839
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38595
72.8%
Space Separator 11710
 
22.1%
Other Punctuation 2615
 
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 4727
12.2%
2 4526
11.7%
1 4413
11.4%
3 4137
10.7%
9 3976
10.3%
8 3564
9.2%
7 3525
9.1%
5 3433
8.9%
6 3161
8.2%
4 3133
8.1%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Space Separator
ValueCountFrequency (%)
11710
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2615
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 52946
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
11710
22.1%
0 4727
8.9%
2 4526
 
8.5%
1 4413
 
8.3%
3 4137
 
7.8%
9 3976
 
7.5%
8 3564
 
6.7%
7 3525
 
6.7%
5 3433
 
6.5%
6 3161
 
6.0%
Other values (4) 5774
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 52959
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11710
22.1%
0 4727
8.9%
2 4526
 
8.5%
1 4413
 
8.3%
3 4137
 
7.8%
9 3976
 
7.5%
8 3564
 
6.7%
7 3525
 
6.7%
5 3433
 
6.5%
6 3161
 
6.0%
Other values (5) 5787
10.9%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

y
Text

MISSING 

Distinct1073
Distinct (%)40.4%
Missing98
Missing (%)3.6%
Memory size21.7 KiB
2024-04-16T20:42:21.803545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.936442
Min length7

Characters and Unicode

Total characters53011
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

Unique547 ?
Unique (%)20.6%

Sample

1st row179957.08923700000
2nd row179597.592953541
3rd row179597.592953541
4th row179597.592953541
5th row179919.43700900000
ValueCountFrequency (%)
314178.057844 24
 
0.9%
450631.435497518 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
 
0.5%
447772.298383734 12
 
0.5%
Other values (1063) 2487
93.5%
2024-04-16T20:42:22.122253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11664
22.0%
4 6296
11.9%
0 4067
 
7.7%
1 3926
 
7.4%
5 3812
 
7.2%
8 3624
 
6.8%
3 3564
 
6.7%
2 3472
 
6.5%
6 3321
 
6.3%
7 3287
 
6.2%
Other values (11) 5978
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38632
72.9%
Space Separator 11664
 
22.0%
Other Punctuation 2615
 
4.9%
Other Letter 52
 
0.1%
Close Punctuation 15
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6296
16.3%
0 4067
10.5%
1 3926
10.2%
5 3812
9.9%
8 3624
9.4%
3 3564
9.2%
2 3472
9.0%
6 3321
8.6%
7 3287
8.5%
9 3263
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 (%)
11664
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52946
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
11664
22.0%
4 6296
11.9%
0 4067
 
7.7%
1 3926
 
7.4%
5 3812
 
7.2%
8 3624
 
6.8%
3 3564
 
6.7%
2 3472
 
6.6%
6 3321
 
6.3%
7 3287
 
6.2%
Other values (6) 5913
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 52959
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11664
22.0%
4 6296
11.9%
0 4067
 
7.7%
1 3926
 
7.4%
5 3812
 
7.2%
8 3624
 
6.8%
3 3564
 
6.7%
2 3472
 
6.6%
6 3321
 
6.3%
7 3287
 
6.2%
Other values (7) 5926
11.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

lastmodts
Real number (ℝ)

Distinct2104
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0192341 × 1013
Minimum2.0030127 × 1013
Maximum2.0201218 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:22.253109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0180593 × 1013
Q12.0190403 × 1013
median2.019121 × 1013
Q32.0200624 × 1013
95-th percentile2.0201119 × 1013
Maximum2.0201218 × 1013
Range1.7109099 × 1011
Interquartile range (IQR)1.0221 × 1010

Descriptive statistics

Standard deviation1.4771421 × 1010
Coefficient of variation (CV)0.00073153581
Kurtosis44.315208
Mean2.0192341 × 1013
Median Absolute Deviation (MAD)9.101001 × 109
Skewness-5.5931817
Sum5.5670285 × 1016
Variance2.1819487 × 1020
MonotonicityNot monotonic
2024-04-16T20:42:22.391801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190418131529 6
 
0.2%
20190920121341 5
 
0.2%
20200323160343 5
 
0.2%
20191218104848 4
 
0.1%
20190227142751 4
 
0.1%
20191002201445 4
 
0.1%
20030127161348 4
 
0.1%
20200918104840 4
 
0.1%
20201023135809 4
 
0.1%
20191017170859 4
 
0.1%
Other values (2094) 2713
98.4%
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 (%)
20201218155717 1
< 0.1%
20201218155018 1
< 0.1%
20201218154706 1
< 0.1%
20201218154416 1
< 0.1%
20201218154144 1
< 0.1%
20201218153723 1
< 0.1%
20201218094618 2
0.1%
20201218094549 2
0.1%
20201218094400 2
0.1%
20201217173911 2
0.1%

uptaenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
업태구분명
509 

Length

Max length5
Median length4
Mean length4.184621
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> 2248
81.5%
업태구분명 509
 
18.5%

Length

2024-04-16T20:42:22.530369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:22.615868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
업태구분명 509
 
18.5%

sitetel
Text

MISSING 

Distinct51
Distinct (%)2.0%
Missing151
Missing (%)5.5%
Memory size21.7 KiB
2024-04-16T20:42:22.738372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.858787
Min length4

Characters and Unicode

Total characters30904
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

Unique21 ?
Unique (%)0.8%

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 2427
93.1%
전화번호 37
 
1.4%
032-832-0510 15
 
0.6%
063-653-7057 9
 
0.3%
02-971-6602 8
 
0.3%
070-4268-7168 7
 
0.3%
031-795-6344 6
 
0.2%
02-3017-3666 6
 
0.2%
0230173666 6
 
0.2%
15440070 6
 
0.2%
Other values (41) 79
 
3.0%
2024-04-16T20:42:22.989135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7406
24.0%
- 5087
16.5%
3 5018
16.2%
2 4973
16.1%
0 2745
 
8.9%
5 2576
 
8.3%
4 2500
 
8.1%
7 150
 
0.5%
6 136
 
0.4%
8 103
 
0.3%
Other values (5) 210
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25669
83.1%
Dash Punctuation 5087
 
16.5%
Other Letter 148
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7406
28.9%
3 5018
19.5%
2 4973
19.4%
0 2745
 
10.7%
5 2576
 
10.0%
4 2500
 
9.7%
7 150
 
0.6%
6 136
 
0.5%
8 103
 
0.4%
9 62
 
0.2%
Other Letter
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 5087
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30756
99.5%
Hangul 148
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7406
24.1%
- 5087
16.5%
3 5018
16.3%
2 4973
16.2%
0 2745
 
8.9%
5 2576
 
8.4%
4 2500
 
8.1%
7 150
 
0.5%
6 136
 
0.4%
8 103
 
0.3%
Hangul
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30756
99.5%
Hangul 148
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7406
24.1%
- 5087
16.5%
3 5018
16.3%
2 4973
16.2%
0 2745
 
8.9%
5 2576
 
8.4%
4 2500
 
8.1%
7 150
 
0.5%
6 136
 
0.4%
8 103
 
0.3%
Hangul
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%

bdngsrvnm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
1915 
건물용도명
477 
문화시설
307 
근린생활시설
 
40
유통시설
 
9
Other values (4)
 
9

Length

Max length6
Median length4
Mean length4.1973159
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> 1915
69.5%
건물용도명 477
 
17.3%
문화시설 307
 
11.1%
근린생활시설 40
 
1.5%
유통시설 9
 
0.3%
호텔 6
 
0.2%
사무실 1
 
< 0.1%
기타 1
 
< 0.1%
식품위생시설 1
 
< 0.1%

Length

2024-04-16T20:42:23.111082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:23.228280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1915
69.5%
건물용도명 477
 
17.3%
문화시설 307
 
11.1%
근린생활시설 40
 
1.5%
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 size21.7 KiB
<NA>
1543 
영화관
764 
공연장형태구분명
434 
자동차극장
 
16

Length

Max length8
Median length4
Mean length4.3583605
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1543
56.0%
영화관 764
27.7%
공연장형태구분명 434
 
15.7%
자동차극장 16
 
0.6%

Length

2024-04-16T20:42:23.334012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:23.421702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1543
56.0%
영화관 764
27.7%
공연장형태구분명 434
 
15.7%
자동차극장 16
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
기존게임업외업종명
509 

Length

Max length9
Median length4
Mean length4.9231048
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> 2248
81.5%
기존게임업외업종명 509
 
18.5%

Length

2024-04-16T20:42:23.515370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:23.591241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
기존게임업외업종명 509
 
18.5%

noroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
노래방실수
509 

Length

Max length5
Median length4
Mean length4.184621
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> 2248
81.5%
노래방실수 509
 
18.5%

Length

2024-04-16T20:42:23.672778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:23.760334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
노래방실수 509
 
18.5%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2052 
문화사업자구분명
508 
영화상영관
 
197

Length

Max length8
Median length4
Mean length4.8084875
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> 2052
74.4%
문화사업자구분명 508
 
18.4%
영화상영관 197
 
7.1%

Length

2024-04-16T20:42:23.852576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:23.940176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2052
74.4%
문화사업자구분명 508
 
18.4%
영화상영관 197
 
7.1%

culphyedcobnm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
영화제작업
1130 
영화상영관
784 
영화배급업
402 
영화수입업
235 
영화상영업
206 

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 1130
41.0%
영화상영관 784
28.4%
영화배급업 402
 
14.6%
영화수입업 235
 
8.5%
영화상영업 206
 
7.5%

Length

2024-04-16T20:42:24.027325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:24.346353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1130
41.0%
영화상영관 784
28.4%
영화배급업 402
 
14.6%
영화수입업 235
 
8.5%
영화상영업 206
 
7.5%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:24.444889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:24.536937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

vdoretornm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
비디오재생기명
509 

Length

Max length7
Median length4
Mean length4.5538629
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> 2248
81.5%
비디오재생기명 509
 
18.5%

Length

2024-04-16T20:42:24.625463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:24.714593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
비디오재생기명 509
 
18.5%

emerstairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:24.800597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:24.882293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

emexyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:24.966585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.047586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

firefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:25.148844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.238786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2239 
시설면적
508 
1578.8
 
4
0
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.9996373
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> 2239
81.2%
시설면적 508
 
18.4%
1578.8 4
 
0.1%
0 4
 
0.1%
147.46 1
 
< 0.1%
181.3 1
 
< 0.1%

Length

2024-04-16T20:42:25.352685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.446247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2239
81.2%
시설면적 508
 
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 size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:25.542528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.629323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

autochaairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:25.733253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.821501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
제공게임물명
509 

Length

Max length6
Median length4
Mean length4.3692419
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> 2248
81.5%
제공게임물명 509
 
18.5%

Length

2024-04-16T20:42:25.912303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:25.997359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
제공게임물명 509
 
18.5%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
제작취급품목내용
509 

Length

Max length8
Median length4
Mean length4.7384839
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> 2248
81.5%
제작취급품목내용 509
 
18.5%

Length

2024-04-16T20:42:26.088757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:26.170370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
제작취급품목내용 509
 
18.5%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:26.258584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:26.336909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

lghtfacilinillu
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
조명시설조도
509 

Length

Max length6
Median length4
Mean length4.3692419
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> 2248
81.5%
조명시설조도 509
 
18.5%

Length

2024-04-16T20:42:26.449794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:26.539997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
조명시설조도 509
 
18.5%

nearenvnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2067 
주변환경명
493 
기타
 
152
유흥업소밀집지역
 
25
아파트지역
 
9
Other values (2)
 
11

Length

Max length8
Median length4
Mean length4.1164309
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> 2067
75.0%
주변환경명 493
 
17.9%
기타 152
 
5.5%
유흥업소밀집지역 25
 
0.9%
아파트지역 9
 
0.3%
주택가주변 7
 
0.3%
학교정화(상대) 4
 
0.1%

Length

2024-04-16T20:42:26.626679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:26.720413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2067
75.0%
주변환경명 493
 
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 size21.7 KiB
<NA>
1652 
지상층수
446 
10
 
120
7
 
72
9
 
65
Other values (18)
402 

Length

Max length4
Median length4
Mean length3.3775843
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1652
59.9%
지상층수 446
 
16.2%
10 120
 
4.4%
7 72
 
2.6%
9 65
 
2.4%
8 53
 
1.9%
2 52
 
1.9%
5 43
 
1.6%
3 33
 
1.2%
4 33
 
1.2%
Other values (13) 188
 
6.8%

Length

2024-04-16T20:42:26.824549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1652
59.9%
지상층수 446
 
16.2%
10 120
 
4.4%
7 72
 
2.6%
9 65
 
2.4%
8 53
 
1.9%
2 52
 
1.9%
5 43
 
1.6%
3 33
 
1.2%
4 33
 
1.2%
Other values (13) 188
 
6.8%

regnsenm
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
1984 
지역구분명
484 
일반상업지역
 
99
준주거지역
 
53
상업지역
 
50
Other values (9)
 
87

Length

Max length6
Median length4
Mean length4.3151977
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1984
72.0%
지역구분명 484
 
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

2024-04-16T20:42:26.944036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1984
72.0%
지역구분명 484
 
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 size21.7 KiB
<NA>
1705 
지하층수
470 
3
 
148
2
 
114
1
 
111
Other values (9)
209 

Length

Max length4
Median length4
Mean length3.3677911
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1705
61.8%
지하층수 470
 
17.0%
3 148
 
5.4%
2 114
 
4.1%
1 111
 
4.0%
5 75
 
2.7%
6 52
 
1.9%
4 33
 
1.2%
7 25
 
0.9%
8 18
 
0.7%
Other values (4) 6
 
0.2%

Length

2024-04-16T20:42:27.052760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1705
61.8%
지하층수 470
 
17.0%
3 148
 
5.4%
2 114
 
4.1%
1 111
 
4.0%
5 75
 
2.7%
6 52
 
1.9%
4 33
 
1.2%
7 25
 
0.9%
8 18
 
0.7%
Other values (4) 6
 
0.2%

bgroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
청소년실수
509 

Length

Max length5
Median length4
Mean length4.184621
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> 2248
81.5%
청소년실수 509
 
18.5%

Length

2024-04-16T20:42:27.160377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:27.241236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
청소년실수 509
 
18.5%

bgroomyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:27.338302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:27.435165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

totgasyscnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
총게임기수
509 

Length

Max length5
Median length4
Mean length4.184621
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> 2248
81.5%
총게임기수 509
 
18.5%

Length

2024-04-16T20:42:27.515396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:27.591773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
총게임기수 509
 
18.5%

totnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
1823 
총층수
458 
11
 
61
3
 
57
10
 
47
Other values (23)
311 

Length

Max length4
Median length4
Mean length3.4258252
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> 1823
66.1%
총층수 458
 
16.6%
11 61
 
2.2%
3 57
 
2.1%
10 47
 
1.7%
13 45
 
1.6%
14 32
 
1.2%
2 28
 
1.0%
15 21
 
0.8%
9 20
 
0.7%
Other values (18) 165
 
6.0%

Length

2024-04-16T20:42:27.696065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1823
66.1%
총층수 458
 
16.6%
11 61
 
2.2%
3 57
 
2.1%
10 47
 
1.7%
13 45
 
1.6%
14 32
 
1.2%
2 28
 
1.0%
15 21
 
0.8%
9 20
 
0.7%
Other values (18) 165
 
6.0%

frstregts
Real number (ℝ)

Distinct631
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20177345
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2024-04-16T20:42:27.814070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20060926
Q120181207
median20190626
Q320200313
95-th percentile20201030
Maximum22030212
Range2579197
Interquartile range (IQR)19106

Descriptive statistics

Standard deviation60228.918
Coefficient of variation (CV)0.0029849773
Kurtosis338.64707
Mean20177345
Median Absolute Deviation (MAD)9600
Skewness8.2366907
Sum5.562894 × 1010
Variance3.6275226 × 109
MonotonicityNot monotonic
2024-04-16T20:42:27.934415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190412 30
 
1.1%
20190315 30
 
1.1%
20190503 27
 
1.0%
20200221 26
 
0.9%
20200214 26
 
0.9%
20181207 25
 
0.9%
20190322 24
 
0.9%
20190111 24
 
0.9%
20190125 24
 
0.9%
20181025 24
 
0.9%
Other values (621) 2497
90.6%
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%
20201218 6
0.2%
20201217 2
 
0.1%
20201216 9
0.3%
20201215 4
 
0.1%
20201214 1
 
< 0.1%
20201211 10
0.4%
20201208 10
0.4%
20201207 3
 
0.1%
20201204 2
 
0.1%

pasgbreth
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2008 
통로너비
495 
1
 
145
1.2
 
19
1050
 
12
Other values (23)
 
78

Length

Max length5
Median length4
Mean length3.8211824
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> 2008
72.8%
통로너비 495
 
18.0%
1 145
 
5.3%
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

2024-04-16T20:42:28.058691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2008
72.8%
통로너비 495
 
18.0%
1 145
 
5.3%
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 size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:28.166323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:28.250676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
509 

Length

Max length4
Median length4
Mean length3.4461371
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> 2248
81.5%
509
 
18.5%

Length

2024-04-16T20:42:28.355850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:28.434505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
509
 
18.5%

actlnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
<NA>
2248 
품목명
509 

Length

Max length4
Median length4
Mean length3.815379
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> 2248
81.5%
품목명 509
 
18.5%

Length

2024-04-16T20:42:28.523920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:28.602138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.5%
품목명 509
 
18.5%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2020-12-22 13:59:06
2757 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22 13:59:06
2nd row2020-12-22 13:59:06
3rd row2020-12-22 13:59:06
4th row2020-12-22 13:59:06
5th row2020-12-22 13:59:06

Common Values

ValueCountFrequency (%)
2020-12-22 13:59:06 2757
100.0%

Length

2024-04-16T20:42:28.682379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:42:28.754903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-22 2757
50.0%
13:59:06 2757
50.0%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
013250000CDFF422000200500000103_13_02_PI2018-08-31 23:59:59.0<NA>국도극장 예술관600805부산광역시 중구 부평동1가 45-9번지48947부산광역시 중구 중구로 13 (부평동1가)2005041520080501<NA><NA><NA>03폐업384872.10053800000179957.0892370000020080506140353<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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
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>2020-12-22 13:59:06
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
274727603220000CDFF521101202000007103_13_05_PI2020-12-20 00:23:06.0영화제작업주식회사 바이어스이엔티지번우편번호서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중202233.376703439446247.90249674520201218094618업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20201218통로너비품목명2020-12-22 13:59:06
274827613220000CDFF521102202000002103_13_04_PI2020-12-20 00:23:06.0영화수입업주식회사 바이어스이엔티<NA>서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218<NA><NA><NA><NA>영업/정상영업중202233.376703439446247.90249674520201218094549<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>20201218<NA><NA><NA><NA>2020-12-22 13:59:06
274927623220000CDFF521103202000003103_13_01_PI2020-12-20 00:23:06.0영화배급업주식회사 바이어스이엔티<NA>서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218<NA><NA><NA><NA>영업/정상영업중202233.376703439446247.90249674520201218094400<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>20201218<NA><NA><NA><NA>2020-12-22 13:59:06
275027633220000CDFF521101202000007103_13_05_PI2020-12-20 00:23:06.0영화제작업주식회사 바이어스이엔티지번우편번호서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중202233.376703439446247.90249674520201218094618업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20201218통로너비품목명2020-12-22 13:59:06
275127643220000CDFF521102202000002103_13_04_PI2020-12-20 00:23:06.0영화수입업주식회사 바이어스이엔티<NA>서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218<NA><NA><NA><NA>영업/정상영업중202233.376703439446247.90249674520201218094549<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>20201218<NA><NA><NA><NA>2020-12-22 13:59:06
275227653220000CDFF521103202000003103_13_01_PI2020-12-20 00:23:06.0영화배급업주식회사 바이어스이엔티<NA>서울특별시 강남구 논현동 6-21 세양 APEX TOWER6040서울특별시 강남구 도산대로 158, 세양 APEX TOWER 907호 (논현동)20201218<NA><NA><NA><NA>영업/정상영업중202233.376703439446247.90249674520201218094400<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>20201218<NA><NA><NA><NA>2020-12-22 13:59:06
275327663210000CDFF521101202000003603_13_05_PI2020-12-22 00:23:05.0영화제작업(주)라이크콘텐츠지번우편번호서울특별시 서초구 잠원동 38-66531서울특별시 서초구 신반포로47길 22, 202호 (잠원동)20130814폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중201652.33335549445507.84581186620201217171714업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20130814통로너비품목명2020-12-22 13:59:06
275427673210000CDFF521103202000001703_13_01_PI2020-12-22 00:23:05.0영화배급업(주)라이크콘텐츠<NA>서울특별시 서초구 잠원동 38-66531서울특별시 서초구 신반포로47길 22, 202호 (잠원동)20130814<NA><NA><NA><NA>영업/정상영업중201652.33335549445507.84581186620201217171829<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>20130814<NA><NA><NA><NA>2020-12-22 13:59:06
275527683210000CDFF521102202000001003_13_04_PI2020-12-22 00:23:05.0영화수입업(주)라이크콘텐츠<NA>서울특별시 서초구 잠원동 38-66531서울특별시 서초구 신반포로47길 22, 202호 (잠원동)20130814<NA><NA><NA><NA>영업/정상영업중201652.33335549445507.84581186620201217171757<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>20130814<NA><NA><NA><NA>2020-12-22 13:59:06
275627693210000CDFF521101202000003703_13_05_PI2020-12-22 00:23:05.0영화제작업㈜씨네이천<NA>서울특별시 서초구 잠원동 10-48 명성빌딩6525서울특별시 서초구 강남대로101안길 12, 명성빌딩 3층 301호 (잠원동)20061208<NA><NA><NA><NA>영업/정상영업중201508.138150123446036.07466058920201217172051<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>20061208<NA><NA><NA><NA>2020-12-22 13:59:06