Overview

Dataset statistics

Number of variables56
Number of observations6171
Missing cells22655
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 MiB
Average record size in memory454.0 B

Variable types

Numeric6
Text11
Categorical38
DateTime1

Alerts

opnsvcid has constant value ""Constant
culwrkrsenm has constant value ""Constant
culphyedcobnm has constant value ""Constant
updategbn is highly imbalanced (52.7%)Imbalance
clgstdt is highly imbalanced (83.8%)Imbalance
clgenddt is highly imbalanced (83.8%)Imbalance
ropnymd is highly imbalanced (59.3%)Imbalance
trdstatenm is highly imbalanced (50.1%)Imbalance
dtlstatenm is highly imbalanced (61.9%)Imbalance
uptaenm is highly imbalanced (59.3%)Imbalance
sitetel is highly imbalanced (94.5%)Imbalance
bdngsrvnm is highly imbalanced (69.3%)Imbalance
perplaformsenm is highly imbalanced (59.3%)Imbalance
bfgameocptectcobnm is highly imbalanced (59.3%)Imbalance
souarfacilyn is highly imbalanced (56.4%)Imbalance
vdoretornm is highly imbalanced (59.3%)Imbalance
emerstairyn is highly imbalanced (61.2%)Imbalance
emexyn is highly imbalanced (62.7%)Imbalance
firefacilyn is highly imbalanced (59.3%)Imbalance
soundfacilyn is highly imbalanced (59.3%)Imbalance
autochaairyn is highly imbalanced (52.6%)Imbalance
prvdgathinnm is highly imbalanced (74.2%)Imbalance
mnfactreartclcn is highly imbalanced (59.3%)Imbalance
lghtfacilyn is highly imbalanced (59.3%)Imbalance
undernumlay is highly imbalanced (57.6%)Imbalance
bgroomyn is highly imbalanced (53.8%)Imbalance
totgasyscnt is highly imbalanced (59.3%)Imbalance
frstregts is highly imbalanced (59.3%)Imbalance
speclghtyn is highly imbalanced (57.4%)Imbalance
cnvefacilyn is highly imbalanced (59.3%)Imbalance
actlnm is highly imbalanced (59.3%)Imbalance
sitepostno has 4248 (68.8%) missing valuesMissing
rdnpostno has 2162 (35.0%) missing valuesMissing
rdnwhladdr has 363 (5.9%) missing valuesMissing
dcbymd has 3769 (61.1%) missing valuesMissing
x has 205 (3.3%) missing valuesMissing
y has 205 (3.3%) missing valuesMissing
noroomcnt has 1420 (23.0%) missing valuesMissing
facilar has 997 (16.2%) missing valuesMissing
lghtfacilinillu has 4637 (75.1%) missing valuesMissing
pasgbreth has 4649 (75.3%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 21:14:27.469016
Analysis finished2024-04-16 21:14:29.204255
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct6171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3086.456
Minimum1
Maximum6173
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:29.257766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile309.5
Q11543.5
median3086
Q34629.5
95-th percentile5864.5
Maximum6173
Range6172
Interquartile range (IQR)3086

Descriptive statistics

Standard deviation1782.1525
Coefficient of variation (CV)0.57741062
Kurtosis-1.1998346
Mean3086.456
Median Absolute Deviation (MAD)1543
Skewness0.00059436894
Sum19046520
Variance3176067.4
MonotonicityNot monotonic
2024-04-17T06:14:29.361511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
4052 1
 
< 0.1%
4122 1
 
< 0.1%
4121 1
 
< 0.1%
4120 1
 
< 0.1%
4119 1
 
< 0.1%
4118 1
 
< 0.1%
4117 1
 
< 0.1%
4116 1
 
< 0.1%
4115 1
 
< 0.1%
Other values (6161) 6161
99.8%
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 (%)
6173 1
< 0.1%
6172 1
< 0.1%
6171 1
< 0.1%
6170 1
< 0.1%
6169 1
< 0.1%
6168 1
< 0.1%
6167 1
< 0.1%
6166 1
< 0.1%
6165 1
< 0.1%
6164 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct183
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3578355.9
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:29.468334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3250000
Q13300000
median3350000
Q33390000
95-th percentile5220000
Maximum6520000
Range3520000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation613351.34
Coefficient of variation (CV)0.17140591
Kurtosis6.6688506
Mean3578355.9
Median Absolute Deviation (MAD)50000
Skewness2.6435536
Sum2.2082034 × 1010
Variance3.7619987 × 1011
MonotonicityNot monotonic
2024-04-17T06:14:29.579635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3350000 688
 
11.1%
3290000 574
 
9.3%
3300000 461
 
7.5%
3330000 434
 
7.0%
3390000 352
 
5.7%
3320000 338
 
5.5%
3340000 316
 
5.1%
3380000 256
 
4.1%
3310000 247
 
4.0%
3370000 234
 
3.8%
Other values (173) 2271
36.8%
ValueCountFrequency (%)
3000000 3
 
< 0.1%
3010000 2
 
< 0.1%
3020000 7
0.1%
3030000 3
 
< 0.1%
3040000 5
 
0.1%
3050000 8
0.1%
3060000 16
0.3%
3070000 6
 
0.1%
3080000 14
0.2%
3090000 9
0.1%
ValueCountFrequency (%)
6520000 18
 
0.3%
6510000 31
0.5%
5710000 49
0.8%
5700000 1
 
< 0.1%
5690000 29
0.5%
5680000 7
 
0.1%
5670000 7
 
0.1%
5600000 1
 
< 0.1%
5590000 11
 
0.2%
5540000 8
 
0.1%

mgtno
Text

Distinct1056
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-17T06:14:29.769700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters123420
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

Unique344 ?
Unique (%)5.6%

Sample

1st rowCDFF3242052001000002
2nd rowCDFF3242052003000006
3rd rowCDFF3242052003000007
4th rowCDFF3242052003000008
5th rowCDFF3242052004000001
ValueCountFrequency (%)
cdff3242052019000001 215
 
3.5%
cdff3242052019000002 180
 
2.9%
cdff3242052020000001 167
 
2.7%
cdff3242052019000003 128
 
2.1%
cdff3242052020000002 106
 
1.7%
cdff3242052019000004 102
 
1.7%
cdff3242052019000005 75
 
1.2%
cdff3242052019000006 57
 
0.9%
cdff3242052020000003 56
 
0.9%
cdff3242052019000007 49
 
0.8%
Other values (1046) 5036
81.6%
2024-04-17T06:14:30.057687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41846
33.9%
2 19310
15.6%
F 12342
 
10.0%
3 7681
 
6.2%
4 7432
 
6.0%
5 7214
 
5.8%
1 6455
 
5.2%
C 6171
 
5.0%
D 6171
 
5.0%
9 5847
 
4.7%
Other values (3) 2951
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98736
80.0%
Uppercase Letter 24684
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41846
42.4%
2 19310
19.6%
3 7681
 
7.8%
4 7432
 
7.5%
5 7214
 
7.3%
1 6455
 
6.5%
9 5847
 
5.9%
8 1056
 
1.1%
6 950
 
1.0%
7 945
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
F 12342
50.0%
C 6171
25.0%
D 6171
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98736
80.0%
Latin 24684
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41846
42.4%
2 19310
19.6%
3 7681
 
7.8%
4 7432
 
7.5%
5 7214
 
7.3%
1 6455
 
6.5%
9 5847
 
5.9%
8 1056
 
1.1%
6 950
 
1.0%
7 945
 
1.0%
Latin
ValueCountFrequency (%)
F 12342
50.0%
C 6171
25.0%
D 6171
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41846
33.9%
2 19310
15.6%
F 12342
 
10.0%
3 7681
 
6.2%
4 7432
 
6.0%
5 7214
 
5.8%
1 6455
 
5.2%
C 6171
 
5.0%
D 6171
 
5.0%
9 5847
 
4.7%
Other values (3) 2951
 
2.4%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
03_09_01_P
6171 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_09_01_P
2nd row03_09_01_P
3rd row03_09_01_P
4th row03_09_01_P
5th row03_09_01_P

Common Values

ValueCountFrequency (%)
03_09_01_P 6171
100.0%

Length

2024-04-17T06:14:30.166427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:30.251591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_09_01_p 6171
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
I
5547 
U
624 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5547
89.9%
U 624
 
10.1%

Length

2024-04-17T06:14:30.324953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:30.398409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5547
89.9%
u 624
 
10.1%
Distinct662
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-22 02:40:00
2024-04-17T06:14:30.481732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:14:30.588491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
4306 
노래연습장업
1865 

Length

Max length6
Median length4
Mean length4.6044401
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> 4306
69.8%
노래연습장업 1865
30.2%

Length

2024-04-17T06:14:30.697096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:30.781184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4306
69.8%
노래연습장업 1865
30.2%

bplcnm
Text

Distinct3655
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-17T06:14:31.184829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length7.6828715
Min length1

Characters and Unicode

Total characters47411
Distinct characters777
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2644 ?
Unique (%)42.8%

Sample

1st row도레미노래연습장
2nd row호심
3rd row진양
4th row도깨비노래연습장
5th row남포노래연습장
ValueCountFrequency (%)
노래연습장 1463
 
17.4%
코인노래연습장 203
 
2.4%
동전노래연습장 72
 
0.9%
코인 66
 
0.8%
세븐스타코인노래연습장 51
 
0.6%
세븐스타 39
 
0.5%
스타노래연습장 36
 
0.4%
궁전노래연습장 34
 
0.4%
궁전 32
 
0.4%
락휴 31
 
0.4%
Other values (3428) 6358
75.8%
2024-04-17T06:14:31.528776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5064
 
10.7%
5061
 
10.7%
4961
 
10.5%
4947
 
10.4%
4904
 
10.3%
2215
 
4.7%
1028
 
2.2%
1003
 
2.1%
787
 
1.7%
399
 
0.8%
Other values (767) 17042
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43532
91.8%
Space Separator 2215
 
4.7%
Uppercase Letter 904
 
1.9%
Decimal Number 291
 
0.6%
Lowercase Letter 178
 
0.4%
Open Punctuation 108
 
0.2%
Close Punctuation 108
 
0.2%
Other Punctuation 52
 
0.1%
Dash Punctuation 20
 
< 0.1%
Letter Number 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5064
 
11.6%
5061
 
11.6%
4961
 
11.4%
4947
 
11.4%
4904
 
11.3%
1028
 
2.4%
1003
 
2.3%
787
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (696) 14985
34.4%
Uppercase Letter
ValueCountFrequency (%)
O 118
 
13.1%
K 113
 
12.5%
P 66
 
7.3%
S 62
 
6.9%
B 52
 
5.8%
M 48
 
5.3%
C 38
 
4.2%
A 37
 
4.1%
N 36
 
4.0%
G 36
 
4.0%
Other values (16) 298
33.0%
Lowercase Letter
ValueCountFrequency (%)
o 24
13.5%
e 15
 
8.4%
t 15
 
8.4%
r 13
 
7.3%
i 13
 
7.3%
g 11
 
6.2%
n 11
 
6.2%
s 10
 
5.6%
a 10
 
5.6%
k 9
 
5.1%
Other values (13) 47
26.4%
Decimal Number
ValueCountFrequency (%)
2 130
44.7%
1 48
 
16.5%
0 35
 
12.0%
3 26
 
8.9%
7 15
 
5.2%
8 14
 
4.8%
5 12
 
4.1%
6 5
 
1.7%
4 5
 
1.7%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 35
67.3%
& 10
 
19.2%
' 3
 
5.8%
# 3
 
5.8%
% 1
 
1.9%
Space Separator
ValueCountFrequency (%)
2215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43527
91.8%
Common 2796
 
5.9%
Latin 1083
 
2.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5064
 
11.6%
5061
 
11.6%
4961
 
11.4%
4947
 
11.4%
4904
 
11.3%
1028
 
2.4%
1003
 
2.3%
787
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (692) 14980
34.4%
Latin
ValueCountFrequency (%)
O 118
 
10.9%
K 113
 
10.4%
P 66
 
6.1%
S 62
 
5.7%
B 52
 
4.8%
M 48
 
4.4%
C 38
 
3.5%
A 37
 
3.4%
N 36
 
3.3%
G 36
 
3.3%
Other values (40) 477
44.0%
Common
ValueCountFrequency (%)
2215
79.2%
2 130
 
4.6%
( 108
 
3.9%
) 108
 
3.9%
1 48
 
1.7%
0 35
 
1.3%
. 35
 
1.3%
3 26
 
0.9%
- 20
 
0.7%
7 15
 
0.5%
Other values (11) 56
 
2.0%
Han
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43527
91.8%
ASCII 3878
 
8.2%
CJK 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5064
 
11.6%
5061
 
11.6%
4961
 
11.4%
4947
 
11.4%
4904
 
11.3%
1028
 
2.4%
1003
 
2.3%
787
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (692) 14980
34.4%
ASCII
ValueCountFrequency (%)
2215
57.1%
2 130
 
3.4%
O 118
 
3.0%
K 113
 
2.9%
( 108
 
2.8%
) 108
 
2.8%
P 66
 
1.7%
S 62
 
1.6%
B 52
 
1.3%
1 48
 
1.2%
Other values (60) 858
 
22.1%
CJK
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct365
Distinct (%)19.0%
Missing4248
Missing (%)68.8%
Memory size48.3 KiB
2024-04-17T06:14:31.799430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters11538
Distinct characters15
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

Unique139 ?
Unique (%)7.2%

Sample

1st row600023
2nd row600046
3rd row600045
4th row600092
5th row600060
ValueCountFrequency (%)
지번우편번호 502
26.1%
609839 81
 
4.2%
614847 35
 
1.8%
609848 31
 
1.6%
614846 21
 
1.1%
609843 20
 
1.0%
614853 19
 
1.0%
609837 19
 
1.0%
614845 18
 
0.9%
607833 18
 
0.9%
Other values (355) 1159
60.3%
2024-04-17T06:14:32.202323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1658
14.4%
0 1535
13.3%
8 1419
12.3%
1 1022
8.9%
1004
8.7%
4 783
 
6.8%
9 641
 
5.6%
502
 
4.4%
502
 
4.4%
502
 
4.4%
Other values (5) 1970
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8526
73.9%
Other Letter 3012
 
26.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1658
19.4%
0 1535
18.0%
8 1419
16.6%
1 1022
12.0%
4 783
9.2%
9 641
 
7.5%
2 454
 
5.3%
3 441
 
5.2%
7 366
 
4.3%
5 207
 
2.4%
Other Letter
ValueCountFrequency (%)
1004
33.3%
502
16.7%
502
16.7%
502
16.7%
502
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 8526
73.9%
Hangul 3012
 
26.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1658
19.4%
0 1535
18.0%
8 1419
16.6%
1 1022
12.0%
4 783
9.2%
9 641
 
7.5%
2 454
 
5.3%
3 441
 
5.2%
7 366
 
4.3%
5 207
 
2.4%
Hangul
ValueCountFrequency (%)
1004
33.3%
502
16.7%
502
16.7%
502
16.7%
502
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8526
73.9%
Hangul 3012
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1658
19.4%
0 1535
18.0%
8 1419
16.6%
1 1022
12.0%
4 783
9.2%
9 641
 
7.5%
2 454
 
5.3%
3 441
 
5.2%
7 366
 
4.3%
5 207
 
2.4%
Hangul
ValueCountFrequency (%)
1004
33.3%
502
16.7%
502
16.7%
502
16.7%
502
16.7%
Distinct4979
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-17T06:14:32.474668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length24.056879
Min length8

Characters and Unicode

Total characters148455
Distinct characters480
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

Unique4155 ?
Unique (%)67.3%

Sample

1st row부산광역시 중구 보수동2가 118-1번지
2nd row부산광역시 중구 동광동3가 21-1번지
3rd row부산광역시 중구 남포동6가 6번지
4th row부산광역시 중구 부평동2가 22-3번지
5th row부산광역시 중구 남포동2가 21-1번지
ValueCountFrequency (%)
부산광역시 4472
 
16.4%
금정구 688
 
2.5%
부산진구 574
 
2.1%
경기도 558
 
2.0%
동래구 459
 
1.7%
해운대구 434
 
1.6%
북구 367
 
1.3%
사상구 352
 
1.3%
사하구 316
 
1.2%
지하1층 301
 
1.1%
Other values (6348) 18752
68.8%
2024-04-17T06:14:32.861698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27093
 
18.2%
6740
 
4.5%
1 6269
 
4.2%
6237
 
4.2%
6139
 
4.1%
5734
 
3.9%
5712
 
3.8%
- 5605
 
3.8%
5524
 
3.7%
5513
 
3.7%
Other values (470) 67889
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85841
57.8%
Decimal Number 29174
 
19.7%
Space Separator 27093
 
18.2%
Dash Punctuation 5605
 
3.8%
Close Punctuation 286
 
0.2%
Open Punctuation 286
 
0.2%
Other Punctuation 68
 
< 0.1%
Uppercase Letter 67
 
< 0.1%
Lowercase Letter 20
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6740
 
7.9%
6237
 
7.3%
6139
 
7.2%
5734
 
6.7%
5712
 
6.7%
5524
 
6.4%
5513
 
6.4%
4933
 
5.7%
4745
 
5.5%
1326
 
1.5%
Other values (424) 33238
38.7%
Uppercase Letter
ValueCountFrequency (%)
B 28
41.8%
C 7
 
10.4%
G 5
 
7.5%
M 5
 
7.5%
A 5
 
7.5%
T 4
 
6.0%
S 3
 
4.5%
K 2
 
3.0%
I 2
 
3.0%
D 2
 
3.0%
Other values (4) 4
 
6.0%
Decimal Number
ValueCountFrequency (%)
1 6269
21.5%
2 4161
14.3%
3 3155
10.8%
4 2882
9.9%
5 2483
 
8.5%
6 2243
 
7.7%
0 2227
 
7.6%
7 1967
 
6.7%
8 1938
 
6.6%
9 1849
 
6.3%
Lowercase Letter
ValueCountFrequency (%)
g 4
20.0%
e 4
20.0%
s 3
15.0%
r 2
10.0%
c 2
10.0%
a 1
 
5.0%
l 1
 
5.0%
o 1
 
5.0%
m 1
 
5.0%
t 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 55
80.9%
. 8
 
11.8%
/ 3
 
4.4%
& 1
 
1.5%
@ 1
 
1.5%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
27093
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5605
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 286
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85841
57.8%
Common 62523
42.1%
Latin 91
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6740
 
7.9%
6237
 
7.3%
6139
 
7.2%
5734
 
6.7%
5712
 
6.7%
5524
 
6.4%
5513
 
6.4%
4933
 
5.7%
4745
 
5.5%
1326
 
1.5%
Other values (424) 33238
38.7%
Latin
ValueCountFrequency (%)
B 28
30.8%
C 7
 
7.7%
G 5
 
5.5%
M 5
 
5.5%
A 5
 
5.5%
T 4
 
4.4%
g 4
 
4.4%
e 4
 
4.4%
S 3
 
3.3%
s 3
 
3.3%
Other values (16) 23
25.3%
Common
ValueCountFrequency (%)
27093
43.3%
1 6269
 
10.0%
- 5605
 
9.0%
2 4161
 
6.7%
3 3155
 
5.0%
4 2882
 
4.6%
5 2483
 
4.0%
6 2243
 
3.6%
0 2227
 
3.6%
7 1967
 
3.1%
Other values (10) 4438
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85841
57.8%
ASCII 62610
42.2%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27093
43.3%
1 6269
 
10.0%
- 5605
 
9.0%
2 4161
 
6.6%
3 3155
 
5.0%
4 2882
 
4.6%
5 2483
 
4.0%
6 2243
 
3.6%
0 2227
 
3.6%
7 1967
 
3.1%
Other values (34) 4525
 
7.2%
Hangul
ValueCountFrequency (%)
6740
 
7.9%
6237
 
7.3%
6139
 
7.2%
5734
 
6.7%
5712
 
6.7%
5524
 
6.4%
5513
 
6.4%
4933
 
5.7%
4745
 
5.5%
1326
 
1.5%
Other values (424) 33238
38.7%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1769
Distinct (%)44.1%
Missing2162
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean76685.21
Minimum1039
Maximum619951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:32.994849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1039
5-th percentile6922.4
Q127352
median47021
Q348492
95-th percentile607837.6
Maximum619951
Range618912
Interquartile range (IQR)21140

Descriptive statistics

Standard deviation144763.27
Coefficient of variation (CV)1.88776
Kurtosis9.5905704
Mean76685.21
Median Absolute Deviation (MAD)2421
Skewness3.3754828
Sum3.07431 × 108
Variance2.0956405 × 1010
MonotonicityNot monotonic
2024-04-17T06:14:33.113395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49431 28
 
0.5%
47865 24
 
0.4%
47736 24
 
0.4%
48106 23
 
0.4%
48953 22
 
0.4%
47006 22
 
0.4%
48280 21
 
0.3%
46576 21
 
0.3%
48095 20
 
0.3%
47551 19
 
0.3%
Other values (1759) 3785
61.3%
(Missing) 2162
35.0%
ValueCountFrequency (%)
1039 1
 
< 0.1%
1053 1
 
< 0.1%
1054 1
 
< 0.1%
1071 2
 
< 0.1%
1072 6
0.1%
1079 1
 
< 0.1%
1081 1
 
< 0.1%
1219 1
 
< 0.1%
1323 1
 
< 0.1%
1343 3
< 0.1%
ValueCountFrequency (%)
619951 1
 
< 0.1%
619912 1
 
< 0.1%
619905 2
< 0.1%
619904 2
< 0.1%
619903 3
< 0.1%
618808 1
 
< 0.1%
617846 1
 
< 0.1%
617840 1
 
< 0.1%
617838 2
< 0.1%
617837 1
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct4921
Distinct (%)84.7%
Missing363
Missing (%)5.9%
Memory size48.3 KiB
2024-04-17T06:14:33.393766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length53
Mean length28.358643
Min length18

Characters and Unicode

Total characters164707
Distinct characters544
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

Unique4336 ?
Unique (%)74.7%

Sample

1st row부산광역시 중구 흑교로45번길 5 (보수동2가)
2nd row부산광역시 중구 백산길 18 (동광동3가)
3rd row부산광역시 중구 중구로29번길 30-1 (부평동2가)
4th row부산광역시 중구 남포길 22-2 (남포동2가)
5th row부산광역시 중구 자갈치로37번길 4-1 (남포동5가)
ValueCountFrequency (%)
부산광역시 4111
 
12.5%
2층 663
 
2.0%
금정구 663
 
2.0%
경기도 558
 
1.7%
부산진구 527
 
1.6%
지하1층 525
 
1.6%
동래구 445
 
1.4%
해운대구 421
 
1.3%
3층 336
 
1.0%
사상구 333
 
1.0%
Other values (4861) 24379
74.0%
2024-04-17T06:14:33.791020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28669
 
17.4%
6786
 
4.1%
5939
 
3.6%
5543
 
3.4%
5436
 
3.3%
) 5435
 
3.3%
( 5435
 
3.3%
1 5395
 
3.3%
5256
 
3.2%
5230
 
3.2%
Other values (534) 85583
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96595
58.6%
Space Separator 28669
 
17.4%
Decimal Number 24683
 
15.0%
Close Punctuation 5435
 
3.3%
Open Punctuation 5435
 
3.3%
Other Punctuation 2734
 
1.7%
Dash Punctuation 988
 
0.6%
Uppercase Letter 115
 
0.1%
Math Symbol 27
 
< 0.1%
Lowercase Letter 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6786
 
7.0%
5939
 
6.1%
5543
 
5.7%
5436
 
5.6%
5256
 
5.4%
5230
 
5.4%
4748
 
4.9%
4409
 
4.6%
2606
 
2.7%
2133
 
2.2%
Other values (488) 48509
50.2%
Uppercase Letter
ValueCountFrequency (%)
B 49
42.6%
A 19
 
16.5%
C 9
 
7.8%
G 7
 
6.1%
M 6
 
5.2%
I 5
 
4.3%
T 4
 
3.5%
K 4
 
3.5%
N 4
 
3.5%
H 3
 
2.6%
Other values (4) 5
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
c 3
13.6%
g 3
13.6%
s 3
13.6%
r 2
9.1%
b 1
 
4.5%
d 1
 
4.5%
m 1
 
4.5%
o 1
 
4.5%
l 1
 
4.5%
Other values (2) 2
9.1%
Decimal Number
ValueCountFrequency (%)
1 5395
21.9%
2 4084
16.5%
3 2944
11.9%
0 2109
 
8.5%
4 2076
 
8.4%
5 1901
 
7.7%
6 1737
 
7.0%
7 1603
 
6.5%
8 1418
 
5.7%
9 1416
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 2726
99.7%
. 7
 
0.3%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
28669
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5435
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 988
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96595
58.6%
Common 67971
41.3%
Latin 141
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6786
 
7.0%
5939
 
6.1%
5543
 
5.7%
5436
 
5.6%
5256
 
5.4%
5230
 
5.4%
4748
 
4.9%
4409
 
4.6%
2606
 
2.7%
2133
 
2.2%
Other values (488) 48509
50.2%
Latin
ValueCountFrequency (%)
B 49
34.8%
A 19
 
13.5%
C 9
 
6.4%
G 7
 
5.0%
M 6
 
4.3%
I 5
 
3.5%
T 4
 
2.8%
K 4
 
2.8%
N 4
 
2.8%
e 4
 
2.8%
Other values (18) 30
21.3%
Common
ValueCountFrequency (%)
28669
42.2%
) 5435
 
8.0%
( 5435
 
8.0%
1 5395
 
7.9%
2 4084
 
6.0%
3 2944
 
4.3%
, 2726
 
4.0%
0 2109
 
3.1%
4 2076
 
3.1%
5 1901
 
2.8%
Other values (8) 7197
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96595
58.6%
ASCII 68108
41.4%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28669
42.1%
) 5435
 
8.0%
( 5435
 
8.0%
1 5395
 
7.9%
2 4084
 
6.0%
3 2944
 
4.3%
, 2726
 
4.0%
0 2109
 
3.1%
4 2076
 
3.0%
5 1901
 
2.8%
Other values (34) 7334
 
10.8%
Hangul
ValueCountFrequency (%)
6786
 
7.0%
5939
 
6.1%
5543
 
5.7%
5436
 
5.6%
5256
 
5.4%
5230
 
5.4%
4748
 
4.9%
4409
 
4.6%
2606
 
2.7%
2133
 
2.2%
Other values (488) 48509
50.2%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%

apvpermymd
Real number (ℝ)

Distinct3029
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20063305
Minimum19000101
Maximum20201218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:33.912940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19000101
5-th percentile19940166
Q119990430
median20021211
Q320181220
95-th percentile20200327
Maximum20201218
Range1201117
Interquartile range (IQR)190790

Descriptive statistics

Standard deviation95290.178
Coefficient of variation (CV)0.0047494755
Kurtosis1.0083756
Mean20063305
Median Absolute Deviation (MAD)60100
Skewness0.10385757
Sum1.2381066 × 1011
Variance9.080218 × 109
MonotonicityNot monotonic
2024-04-17T06:14:34.026904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021210 66
 
1.1%
20021211 60
 
1.0%
20021205 38
 
0.6%
20190329 26
 
0.4%
20021206 26
 
0.4%
19921013 25
 
0.4%
20191227 24
 
0.4%
20191129 24
 
0.4%
20021207 23
 
0.4%
20191206 21
 
0.3%
Other values (3019) 5838
94.6%
ValueCountFrequency (%)
19000101 1
 
< 0.1%
19920112 1
 
< 0.1%
19920710 1
 
< 0.1%
19920711 2
 
< 0.1%
19920713 7
0.1%
19920905 1
 
< 0.1%
19920907 2
 
< 0.1%
19920917 2
 
< 0.1%
19920919 1
 
< 0.1%
19920926 1
 
< 0.1%
ValueCountFrequency (%)
20201218 6
0.1%
20201216 1
 
< 0.1%
20201215 1
 
< 0.1%
20201211 2
 
< 0.1%
20201209 2
 
< 0.1%
20201203 2
 
< 0.1%
20201202 1
 
< 0.1%
20201201 2
 
< 0.1%
20201127 2
 
< 0.1%
20201126 1
 
< 0.1%

dcbymd
Text

MISSING 

Distinct1439
Distinct (%)59.9%
Missing3769
Missing (%)61.1%
Memory size48.3 KiB
2024-04-17T06:14:34.251516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.1690258
Min length4

Characters and Unicode

Total characters17220
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

Unique1132 ?
Unique (%)47.1%

Sample

1st row20040901
2nd row20050216
3rd row20071116
4th row20070227
5th row20120207
ValueCountFrequency (%)
폐업일자 499
 
20.8%
20071126 24
 
1.0%
20040317 16
 
0.7%
20081217 9
 
0.4%
20140703 8
 
0.3%
20100219 8
 
0.3%
20000214 7
 
0.3%
20170530 7
 
0.3%
20151228 7
 
0.3%
20140325 7
 
0.3%
Other values (1429) 1810
75.4%
2024-04-17T06:14:34.593968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5291
30.7%
2 3138
18.2%
1 2767
16.1%
3 713
 
4.1%
7 688
 
4.0%
6 592
 
3.4%
5 528
 
3.1%
4 508
 
3.0%
8 502
 
2.9%
499
 
2.9%
Other values (4) 1994
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15224
88.4%
Other Letter 1996
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5291
34.8%
2 3138
20.6%
1 2767
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 502
 
3.3%
9 497
 
3.3%
Other Letter
ValueCountFrequency (%)
499
25.0%
499
25.0%
499
25.0%
499
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15224
88.4%
Hangul 1996
 
11.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5291
34.8%
2 3138
20.6%
1 2767
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 502
 
3.3%
9 497
 
3.3%
Hangul
ValueCountFrequency (%)
499
25.0%
499
25.0%
499
25.0%
499
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15224
88.4%
Hangul 1996
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5291
34.8%
2 3138
20.6%
1 2767
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 502
 
3.3%
9 497
 
3.3%
Hangul
ValueCountFrequency (%)
499
25.0%
499
25.0%
499
25.0%
499
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5663 
휴업시작일자
 
502
20201026
 
3
20120827
 
1
20091029
 
1

Length

Max length8
Median length4
Mean length4.1665856
Min length4

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> 5663
91.8%
휴업시작일자 502
 
8.1%
20201026 3
 
< 0.1%
20120827 1
 
< 0.1%
20091029 1
 
< 0.1%
20200818 1
 
< 0.1%

Length

2024-04-17T06:14:34.710852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:34.801098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5663
91.8%
휴업시작일자 502
 
8.1%
20201026 3
 
< 0.1%
20120827 1
 
< 0.1%
20091029 1
 
< 0.1%
20200818 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5663 
휴업종료일자
 
502
20201130
 
3
20150824
 
1
20091104
 
1

Length

Max length8
Median length4
Mean length4.1665856
Min length4

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> 5663
91.8%
휴업종료일자 502
 
8.1%
20201130 3
 
< 0.1%
20150824 1
 
< 0.1%
20091104 1
 
< 0.1%
20201201 1
 
< 0.1%

Length

2024-04-17T06:14:34.903751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:35.003050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5663
91.8%
휴업종료일자 502
 
8.1%
20201130 3
 
< 0.1%
20150824 1
 
< 0.1%
20091104 1
 
< 0.1%
20201201 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
재개업일자
 
502

Length

Max length5
Median length4
Mean length4.0813482
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> 5669
91.9%
재개업일자 502
 
8.1%

Length

2024-04-17T06:14:35.104215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:35.200448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
재개업일자 502
 
8.1%

trdstatenm
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
13
2293 
영업/정상
1784 
03
1728 
35
 
133
31
 
97
Other values (10)
 
136

Length

Max length14
Median length2
Mean length2.8783017
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row13
2nd row03
3rd row03
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 2293
37.2%
영업/정상 1784
28.9%
03 1728
28.0%
35 133
 
2.2%
31 97
 
1.6%
폐업 58
 
0.9%
30 30
 
0.5%
25 13
 
0.2%
<NA> 11
 
0.2%
33 10
 
0.2%
Other values (5) 14
 
0.2%

Length

2024-04-17T06:14:35.289537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13 2293
37.2%
영업/정상 1784
28.9%
03 1728
28.0%
35 133
 
2.2%
31 97
 
1.6%
폐업 58
 
0.9%
30 30
 
0.5%
25 13
 
0.2%
na 11
 
0.2%
33 10
 
0.2%
Other values (5) 14
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
영업중
4093 
폐업
1786 
직권말소
 
135
등록취소
 
98
허가취소
 
30
Other values (4)
 
29

Length

Max length5
Median length3
Mean length2.7564414
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 4093
66.3%
폐업 1786
28.9%
직권말소 135
 
2.2%
등록취소 98
 
1.6%
허가취소 30
 
0.5%
영업정지 13
 
0.2%
지정취소 10
 
0.2%
휴업 5
 
0.1%
영업장폐쇄 1
 
< 0.1%

Length

2024-04-17T06:14:35.383813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:35.475751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 4093
66.3%
폐업 1786
28.9%
직권말소 135
 
2.2%
등록취소 98
 
1.6%
허가취소 30
 
0.5%
영업정지 13
 
0.2%
지정취소 10
 
0.2%
휴업 5
 
0.1%
영업장폐쇄 1
 
< 0.1%

x
Text

MISSING 

Distinct4685
Distinct (%)78.5%
Missing205
Missing (%)3.3%
Memory size48.3 KiB
2024-04-17T06:14:35.650476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.945525
Min length7

Characters and Unicode

Total characters118995
Distinct characters20
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

Unique3803 ?
Unique (%)63.7%

Sample

1st row384596.82640100000
2nd row385501.48186900000
3rd row384754.70921800000
4th row385220.72387000000
5th row384971.19099500000
ValueCountFrequency (%)
좌표정보(x 25
 
0.4%
191690.8808747 9
 
0.2%
398274.39006400000 7
 
0.1%
208609.386752684 7
 
0.1%
170875.132162658 6
 
0.1%
389360.993759525 6
 
0.1%
400040.89421700000 6
 
0.1%
389728.19289000000 6
 
0.1%
223015.954114646 5
 
0.1%
384376.73788500000 4
 
0.1%
Other values (4675) 5885
98.6%
2024-04-17T06:14:35.925371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26310
22.1%
18583
15.6%
3 10701
9.0%
8 9031
 
7.6%
9 8123
 
6.8%
1 7334
 
6.2%
2 7005
 
5.9%
7 6697
 
5.6%
4 6511
 
5.5%
5 6442
 
5.4%
Other values (10) 12258
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94323
79.3%
Space Separator 18583
 
15.6%
Other Punctuation 5908
 
5.0%
Other Letter 100
 
0.1%
Close Punctuation 25
 
< 0.1%
Uppercase Letter 25
 
< 0.1%
Open Punctuation 25
 
< 0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26310
27.9%
3 10701
11.3%
8 9031
 
9.6%
9 8123
 
8.6%
1 7334
 
7.8%
2 7005
 
7.4%
7 6697
 
7.1%
4 6511
 
6.9%
5 6442
 
6.8%
6 6169
 
6.5%
Other Letter
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Space Separator
ValueCountFrequency (%)
18583
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5908
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118870
99.9%
Hangul 100
 
0.1%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26310
22.1%
18583
15.6%
3 10701
9.0%
8 9031
 
7.6%
9 8123
 
6.8%
1 7334
 
6.2%
2 7005
 
5.9%
7 6697
 
5.6%
4 6511
 
5.5%
5 6442
 
5.4%
Other values (5) 12133
10.2%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Latin
ValueCountFrequency (%)
X 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118895
99.9%
Hangul 100
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26310
22.1%
18583
15.6%
3 10701
9.0%
8 9031
 
7.6%
9 8123
 
6.8%
1 7334
 
6.2%
2 7005
 
5.9%
7 6697
 
5.6%
4 6511
 
5.5%
5 6442
 
5.4%
Other values (6) 12158
10.2%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

y
Text

MISSING 

Distinct4685
Distinct (%)78.5%
Missing205
Missing (%)3.3%
Memory size48.3 KiB
2024-04-17T06:14:36.147848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.945525
Min length7

Characters and Unicode

Total characters118995
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

Unique3803 ?
Unique (%)63.7%

Sample

1st row180453.48548000000
2nd row180233.23297100000
3rd row180131.91871200000
4th row179923.53241600000
5th row179770.98985200000
ValueCountFrequency (%)
좌표정보(y 25
 
0.4%
446122.774558898 9
 
0.2%
188234.66906700000 7
 
0.1%
410629.472499067 7
 
0.1%
447263.829719015 6
 
0.1%
191580.392783184 6
 
0.1%
188878.91983800000 6
 
0.1%
199652.82883000000 6
 
0.1%
332198.530078572 5
 
0.1%
177563.53610000000 4
 
0.1%
Other values (4675) 5885
98.6%
2024-04-17T06:14:36.431718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25758
21.6%
18506
15.6%
1 10969
9.2%
8 8590
 
7.2%
9 8327
 
7.0%
4 7509
 
6.3%
7 6985
 
5.9%
2 6627
 
5.6%
3 6606
 
5.6%
6 6605
 
5.6%
Other values (11) 12513
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94371
79.3%
Space Separator 18506
 
15.6%
Other Punctuation 5908
 
5.0%
Other Letter 100
 
0.1%
Dash Punctuation 32
 
< 0.1%
Close Punctuation 28
 
< 0.1%
Uppercase Letter 25
 
< 0.1%
Open Punctuation 25
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25758
27.3%
1 10969
11.6%
8 8590
 
9.1%
9 8327
 
8.8%
4 7509
 
8.0%
7 6985
 
7.4%
2 6627
 
7.0%
3 6606
 
7.0%
6 6605
 
7.0%
5 6395
 
6.8%
Other Letter
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Close Punctuation
ValueCountFrequency (%)
) 25
89.3%
] 3
 
10.7%
Space Separator
ValueCountFrequency (%)
18506
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5908
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118870
99.9%
Hangul 100
 
0.1%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25758
21.7%
18506
15.6%
1 10969
9.2%
8 8590
 
7.2%
9 8327
 
7.0%
4 7509
 
6.3%
7 6985
 
5.9%
2 6627
 
5.6%
3 6606
 
5.6%
6 6605
 
5.6%
Other values (6) 12388
10.4%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Latin
ValueCountFrequency (%)
Y 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118895
99.9%
Hangul 100
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25758
21.7%
18506
15.6%
1 10969
9.2%
8 8590
 
7.2%
9 8327
 
7.0%
4 7509
 
6.3%
7 6985
 
5.9%
2 6627
 
5.6%
3 6606
 
5.6%
6 6605
 
5.6%
Other values (7) 12413
10.4%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

lastmodts
Real number (ℝ)

Distinct5420
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0144552 × 1013
Minimum2.0021018 × 1013
Maximum2.020122 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:36.561761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0050308 × 1013
Q12.0100811 × 1013
median2.0160624 × 1013
Q32.0190405 × 1013
95-th percentile2.020081 × 1013
Maximum2.020122 × 1013
Range1.8020199 × 1011
Interquartile range (IQR)8.9593986 × 1010

Descriptive statistics

Standard deviation4.8984222 × 1010
Coefficient of variation (CV)0.0024316362
Kurtosis-0.61824072
Mean2.0144552 × 1013
Median Absolute Deviation (MAD)3.0582001 × 1010
Skewness-0.66817344
Sum1.2431203 × 1017
Variance2.399454 × 1021
MonotonicityNot monotonic
2024-04-17T06:14:36.682020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030127161348 90
 
1.5%
20180108090959 65
 
1.1%
20021018125445 39
 
0.6%
20200717165016 4
 
0.1%
20200915163144 4
 
0.1%
20200710134452 4
 
0.1%
20200221140721 3
 
< 0.1%
20200203095053 3
 
< 0.1%
20191114133200 3
 
< 0.1%
20190716155514 3
 
< 0.1%
Other values (5410) 5953
96.5%
ValueCountFrequency (%)
20021018125445 39
0.6%
20021108150513 1
 
< 0.1%
20021214125753 1
 
< 0.1%
20021227155914 1
 
< 0.1%
20030108162736 1
 
< 0.1%
20030108163209 1
 
< 0.1%
20030109125515 1
 
< 0.1%
20030114154112 1
 
< 0.1%
20030117135220 1
 
< 0.1%
20030122091653 1
 
< 0.1%
ValueCountFrequency (%)
20201220114028 3
< 0.1%
20201218174659 2
< 0.1%
20201218141533 2
< 0.1%
20201218094252 2
< 0.1%
20201217164726 1
 
< 0.1%
20201217150437 3
< 0.1%
20201217105332 1
 
< 0.1%
20201216150400 1
 
< 0.1%
20201216111826 1
 
< 0.1%
20201215173955 1
 
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
업태구분명
 
502

Length

Max length5
Median length4
Mean length4.0813482
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> 5669
91.9%
업태구분명 502
 
8.1%

Length

2024-04-17T06:14:36.796446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:36.874128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
업태구분명 502
 
8.1%

sitetel
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
051-123-1234
5976 
<NA>
 
104
전화번호
 
60
054-433-4625
 
3
041-567-7179
 
2
Other values (25)
 
26

Length

Max length12
Median length12
Mean length11.780911
Min length4

Unique

Unique24 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
051-123-1234 5976
96.8%
<NA> 104
 
1.7%
전화번호 60
 
1.0%
054-433-4625 3
 
< 0.1%
041-567-7179 2
 
< 0.1%
031-377-7955 2
 
< 0.1%
051-317-0711 1
 
< 0.1%
044-868-6366 1
 
< 0.1%
522-6761 1
 
< 0.1%
524-5759 1
 
< 0.1%
Other values (20) 20
 
0.3%

Length

2024-04-17T06:14:36.963255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 5976
96.8%
na 104
 
1.7%
전화번호 60
 
1.0%
054-433-4625 3
 
< 0.1%
041-567-7179 2
 
< 0.1%
031-377-7955 2
 
< 0.1%
032-422-5270 1
 
< 0.1%
031-677-9777 1
 
< 0.1%
558-2803 1
 
< 0.1%
02-2677-7693 1
 
< 0.1%
Other values (20) 20
 
0.3%

bdngsrvnm
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3655 
근린생활시설
2207 
건물용도명
 
257
사무실
 
13
기타
 
11
Other values (12)
 
28

Length

Max length7
Median length4
Mean length4.7523902
Min length2

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3655
59.2%
근린생활시설 2207
35.8%
건물용도명 257
 
4.2%
사무실 13
 
0.2%
기타 11
 
0.2%
문화시설 10
 
0.2%
유통시설 5
 
0.1%
숙박시설 3
 
< 0.1%
단독주택 2
 
< 0.1%
교육연구시설 1
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2024-04-17T06:14:37.066587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3655
59.2%
근린생활시설 2207
35.8%
건물용도명 257
 
4.2%
사무실 13
 
0.2%
기타 11
 
0.2%
문화시설 10
 
0.2%
유통시설 5
 
0.1%
숙박시설 3
 
< 0.1%
단독주택 2
 
< 0.1%
교육연구시설 1
 
< 0.1%
Other values (7) 7
 
0.1%

perplaformsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
공연장형태구분명
 
502

Length

Max length8
Median length4
Mean length4.325393
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> 5669
91.9%
공연장형태구분명 502
 
8.1%

Length

2024-04-17T06:14:37.166402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:37.254805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
공연장형태구분명 502
 
8.1%

bfgameocptectcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
기존게임업외업종명
 
502

Length

Max length9
Median length4
Mean length4.4067412
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> 5669
91.9%
기존게임업외업종명 502
 
8.1%

Length

2024-04-17T06:14:37.336996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:37.411046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
기존게임업외업종명 502
 
8.1%

noroomcnt
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)1.0%
Missing1420
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean9.280362
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:37.508291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15
median7
Q311
95-th percentile22
Maximum70
Range69
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.5354186
Coefficient of variation (CV)0.70422022
Kurtosis10.003015
Mean9.280362
Median Absolute Deviation (MAD)2
Skewness2.3239359
Sum44091
Variance42.711696
MonotonicityNot monotonic
2024-04-17T06:14:37.636001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
5 710
11.5%
6 611
9.9%
4 540
 
8.8%
7 535
 
8.7%
8 389
 
6.3%
9 242
 
3.9%
10 185
 
3.0%
3 154
 
2.5%
12 127
 
2.1%
11 122
 
2.0%
Other values (37) 1136
18.4%
(Missing) 1420
23.0%
ValueCountFrequency (%)
1 35
 
0.6%
2 56
 
0.9%
3 154
 
2.5%
4 540
8.8%
5 710
11.5%
6 611
9.9%
7 535
8.7%
8 389
6.3%
9 242
 
3.9%
10 185
 
3.0%
ValueCountFrequency (%)
70 3
< 0.1%
68 1
 
< 0.1%
59 1
 
< 0.1%
57 1
 
< 0.1%
53 2
< 0.1%
50 1
 
< 0.1%
44 1
 
< 0.1%
43 1
 
< 0.1%
42 1
 
< 0.1%
40 4
0.1%

culwrkrsenm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
유통관련업
6171 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통관련업 6171
100.0%

Length

2024-04-17T06:14:37.738213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:37.806866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 6171
100.0%

culphyedcobnm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
노래연습장업
6171 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노래연습장업 6171
100.0%

Length

2024-04-17T06:14:37.879235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:37.957136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장업 6171
100.0%

souarfacilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
4843 
Y
1197 
<NA>
 
86
 
45

Length

Max length4
Median length1
Mean length1.0418085
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowN
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 4843
78.5%
Y 1197
 
19.4%
<NA> 86
 
1.4%
45
 
0.7%

Length

2024-04-17T06:14:38.044478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:38.124960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4843
78.5%
y 1197
 
19.4%
na 86
 
1.4%
45
 
0.7%

vdoretornm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
비디오재생기명
 
502

Length

Max length7
Median length4
Mean length4.2440447
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> 5669
91.9%
비디오재생기명 502
 
8.1%

Length

2024-04-17T06:14:38.469266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:38.545467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
비디오재생기명 502
 
8.1%

emerstairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
5131 
Y
891 
<NA>
 
97
 
52

Length

Max length4
Median length1
Mean length1.0471561
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 5131
83.1%
Y 891
 
14.4%
<NA> 97
 
1.6%
52
 
0.8%

Length

2024-04-17T06:14:38.627939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:38.709476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5131
83.1%
y 891
 
14.4%
na 97
 
1.6%
52
 
0.8%

emexyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
5168 
Y
878 
<NA>
 
86
 
39

Length

Max length4
Median length1
Mean length1.0418085
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 5168
83.7%
Y 878
 
14.2%
<NA> 86
 
1.4%
39
 
0.6%

Length

2024-04-17T06:14:38.798066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:38.880783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5168
83.7%
y 878
 
14.2%
na 86
 
1.4%
39
 
0.6%

firefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
 
502

Length

Max length4
Median length4
Mean length3.7559553
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> 5669
91.9%
502
 
8.1%

Length

2024-04-17T06:14:38.969858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:39.048043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
502
 
8.1%

facilar
Text

MISSING 

Distinct3436
Distinct (%)66.4%
Missing997
Missing (%)16.2%
Memory size48.3 KiB
2024-04-17T06:14:39.339119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1681484
Min length1

Characters and Unicode

Total characters26740
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

Unique2605 ?
Unique (%)50.3%

Sample

1st row80
2nd row114.05
3rd row121.68
4th row130.81
5th row159.77
ValueCountFrequency (%)
99 52
 
1.0%
0 47
 
0.9%
132 30
 
0.6%
82.5 25
 
0.5%
165 21
 
0.4%
115.5 20
 
0.4%
92.4 19
 
0.4%
125.4 17
 
0.3%
66 17
 
0.3%
198 15
 
0.3%
Other values (3426) 4911
94.9%
2024-04-17T06:14:39.745125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4671
17.5%
. 4548
17.0%
2 2883
10.8%
4 1977
7.4%
8 1973
7.4%
9 1960
7.3%
5 1917
7.2%
3 1909
7.1%
6 1854
 
6.9%
7 1702
 
6.4%
Other values (5) 1346
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22180
82.9%
Other Punctuation 4548
 
17.0%
Other Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4671
21.1%
2 2883
13.0%
4 1977
8.9%
8 1973
8.9%
9 1960
8.8%
5 1917
8.6%
3 1909
8.6%
6 1854
 
8.4%
7 1702
 
7.7%
0 1334
 
6.0%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Other Punctuation
ValueCountFrequency (%)
. 4548
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26728
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4671
17.5%
. 4548
17.0%
2 2883
10.8%
4 1977
7.4%
8 1973
7.4%
9 1960
7.3%
5 1917
7.2%
3 1909
7.1%
6 1854
 
6.9%
7 1702
 
6.4%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26728
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4671
17.5%
. 4548
17.0%
2 2883
10.8%
4 1977
7.4%
8 1973
7.4%
9 1960
7.3%
5 1917
7.2%
3 1909
7.1%
6 1854
 
6.9%
7 1702
 
6.4%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

soundfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
 
502

Length

Max length4
Median length4
Mean length3.7559553
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> 5669
91.9%
502
 
8.1%

Length

2024-04-17T06:14:39.857889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:39.935263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
502
 
8.1%

autochaairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
4635 
Y
1385 
<NA>
 
96
 
55

Length

Max length4
Median length1
Mean length1.0466699
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 4635
75.1%
Y 1385
 
22.4%
<NA> 96
 
1.6%
55
 
0.9%

Length

2024-04-17T06:14:40.014909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:40.098039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4635
75.1%
y 1385
 
22.4%
na 96
 
1.6%
55
 
0.9%

prvdgathinnm
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5668 
제공게임물명
 
502
전체이용가
 
1

Length

Max length6
Median length4
Mean length4.1628585
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> 5668
91.8%
제공게임물명 502
 
8.1%
전체이용가 1
 
< 0.1%

Length

2024-04-17T06:14:40.191490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:40.273395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5668
91.8%
제공게임물명 502
 
8.1%
전체이용가 1
 
< 0.1%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
제작취급품목내용
 
502

Length

Max length8
Median length4
Mean length4.325393
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> 5669
91.9%
제작취급품목내용 502
 
8.1%

Length

2024-04-17T06:14:40.366120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:40.453242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
제작취급품목내용 502
 
8.1%

lghtfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
 
502

Length

Max length4
Median length4
Mean length3.7559553
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> 5669
91.9%
502
 
8.1%

Length

2024-04-17T06:14:40.545783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:40.633108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
502
 
8.1%

lghtfacilinillu
Text

MISSING 

Distinct183
Distinct (%)11.9%
Missing4637
Missing (%)75.1%
Memory size48.3 KiB
2024-04-17T06:14:40.805832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length3.1499348
Min length1

Characters and Unicode

Total characters4832
Distinct characters16
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

Unique98 ?
Unique (%)6.4%

Sample

1st row40
2nd row44
3rd row38
4th row80
5th row45
ValueCountFrequency (%)
60 369
24.1%
조명시설조도 364
23.7%
35 142
 
9.3%
40 125
 
8.1%
30 54
 
3.5%
50 37
 
2.4%
100 22
 
1.4%
45 20
 
1.3%
80 14
 
0.9%
48 12
 
0.8%
Other values (173) 375
24.4%
2024-04-17T06:14:41.095627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 729
15.1%
728
15.1%
6 450
9.3%
364
7.5%
364
7.5%
364
7.5%
364
7.5%
5 332
6.9%
3 298
6.2%
4 269
 
5.6%
Other values (6) 570
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2590
53.6%
Other Letter 2184
45.2%
Other Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 729
28.1%
6 450
17.4%
5 332
12.8%
3 298
11.5%
4 269
 
10.4%
1 192
 
7.4%
2 107
 
4.1%
7 81
 
3.1%
8 79
 
3.1%
9 53
 
2.0%
Other Letter
ValueCountFrequency (%)
728
33.3%
364
16.7%
364
16.7%
364
16.7%
364
16.7%
Other Punctuation
ValueCountFrequency (%)
. 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2648
54.8%
Hangul 2184
45.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 729
27.5%
6 450
17.0%
5 332
12.5%
3 298
11.3%
4 269
 
10.2%
1 192
 
7.3%
2 107
 
4.0%
7 81
 
3.1%
8 79
 
3.0%
. 58
 
2.2%
Hangul
ValueCountFrequency (%)
728
33.3%
364
16.7%
364
16.7%
364
16.7%
364
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2648
54.8%
Hangul 2184
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 729
27.5%
6 450
17.0%
5 332
12.5%
3 298
11.3%
4 269
 
10.2%
1 192
 
7.3%
2 107
 
4.0%
7 81
 
3.1%
8 79
 
3.0%
. 58
 
2.2%
Hangul
ValueCountFrequency (%)
728
33.3%
364
16.7%
364
16.7%
364
16.7%
364
16.7%

nearenvnm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
4283 
기타
546 
주택가주변
531 
주변환경명
 
367
유흥업소밀집지역
 
261
Other values (4)
 
183

Length

Max length8
Median length4
Mean length4.2301086
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4283
69.4%
기타 546
 
8.8%
주택가주변 531
 
8.6%
주변환경명 367
 
5.9%
유흥업소밀집지역 261
 
4.2%
학교정화(상대) 121
 
2.0%
아파트지역 53
 
0.9%
학교정화(절대) 6
 
0.1%
결혼예식장주변 3
 
< 0.1%

Length

2024-04-17T06:14:41.201640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:41.292327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4283
69.4%
기타 546
 
8.8%
주택가주변 531
 
8.6%
주변환경명 367
 
5.9%
유흥업소밀집지역 261
 
4.2%
학교정화(상대 121
 
2.0%
아파트지역 53
 
0.9%
학교정화(절대 6
 
0.1%
결혼예식장주변 3
 
< 0.1%

jisgnumlay
Categorical

Distinct22
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3403 
2
717 
3
513 
5
394 
4
 
313
Other values (17)
831 

Length

Max length4
Median length4
Mean length2.8060282
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row1
3rd row<NA>
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3403
55.1%
2 717
 
11.6%
3 513
 
8.3%
5 394
 
6.4%
4 313
 
5.1%
지상층수 291
 
4.7%
1 153
 
2.5%
6 109
 
1.8%
7 69
 
1.1%
8 62
 
1.0%
Other values (12) 147
 
2.4%

Length

2024-04-17T06:14:41.409448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3403
55.1%
2 717
 
11.6%
3 513
 
8.3%
5 394
 
6.4%
4 313
 
5.1%
지상층수 291
 
4.7%
1 153
 
2.5%
6 109
 
1.8%
7 69
 
1.1%
8 62
 
1.0%
Other values (12) 147
 
2.4%

regnsenm
Categorical

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3998 
일반주거지역
413 
일반상업지역
 
392
준주거지역
 
379
주거지역
 
373
Other values (10)
616 

Length

Max length6
Median length4
Mean length4.4184087
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3998
64.8%
일반주거지역 413
 
6.7%
일반상업지역 392
 
6.4%
준주거지역 379
 
6.1%
주거지역 373
 
6.0%
지역구분명 285
 
4.6%
상업지역 138
 
2.2%
근린상업지역 75
 
1.2%
중심상업지역 47
 
0.8%
관리지역 33
 
0.5%
Other values (5) 38
 
0.6%

Length

2024-04-17T06:14:41.508932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3998
64.8%
일반주거지역 413
 
6.7%
일반상업지역 392
 
6.4%
준주거지역 379
 
6.1%
주거지역 373
 
6.0%
지역구분명 285
 
4.6%
상업지역 138
 
2.2%
근린상업지역 75
 
1.2%
중심상업지역 47
 
0.8%
관리지역 33
 
0.5%
Other values (5) 38
 
0.6%

undernumlay
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3552 
1
1958 
지하층수
372 
2
 
135
0
 
102
Other values (7)
 
52

Length

Max length4
Median length4
Mean length2.9077945
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3552
57.6%
1 1958
31.7%
지하층수 372
 
6.0%
2 135
 
2.2%
0 102
 
1.7%
3 33
 
0.5%
6 7
 
0.1%
4 6
 
0.1%
5 3
 
< 0.1%
10 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T06:14:41.604741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3552
57.6%
1 1958
31.7%
지하층수 372
 
6.0%
2 135
 
2.2%
0 102
 
1.7%
3 33
 
0.5%
6 7
 
0.1%
4 6
 
0.1%
5 3
 
< 0.1%
10 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

bgroomcnt
Categorical

Distinct47
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3218 
1
601 
2
497 
3
 
239
청소년실수
 
187
Other values (42)
1429 

Length

Max length5
Median length4
Mean length2.8149409
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row7

Common Values

ValueCountFrequency (%)
<NA> 3218
52.1%
1 601
 
9.7%
2 497
 
8.1%
3 239
 
3.9%
청소년실수 187
 
3.0%
0 185
 
3.0%
4 123
 
2.0%
5 95
 
1.5%
15 74
 
1.2%
20 73
 
1.2%
Other values (37) 879
 
14.2%

Length

2024-04-17T06:14:41.713502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3218
52.1%
1 601
 
9.7%
2 497
 
8.1%
3 239
 
3.9%
청소년실수 187
 
3.0%
0 185
 
3.0%
4 123
 
2.0%
5 95
 
1.5%
15 74
 
1.2%
20 73
 
1.2%
Other values (37) 879
 
14.2%

bgroomyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
4466 
Y
1641 
<NA>
 
42
 
22

Length

Max length4
Median length1
Mean length1.0204181
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowY

Common Values

ValueCountFrequency (%)
N 4466
72.4%
Y 1641
 
26.6%
<NA> 42
 
0.7%
22
 
0.4%

Length

2024-04-17T06:14:41.826092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:41.910835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4466
72.4%
y 1641
 
26.6%
na 42
 
0.7%
22
 
0.4%

totgasyscnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
총게임기수
 
502

Length

Max length5
Median length4
Mean length4.0813482
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> 5669
91.9%
총게임기수 502
 
8.1%

Length

2024-04-17T06:14:41.992837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:42.069402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
총게임기수 502
 
8.1%

totnumlay
Categorical

Distinct27
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
3515 
5
560 
3
373 
4
371 
총층수
 
324
Other values (22)
1028 

Length

Max length4
Median length4
Mean length2.8361692
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row4
2nd row3
3rd row6
4th row5
5th row4

Common Values

ValueCountFrequency (%)
<NA> 3515
57.0%
5 560
 
9.1%
3 373
 
6.0%
4 371
 
6.0%
총층수 324
 
5.3%
6 223
 
3.6%
1 190
 
3.1%
2 179
 
2.9%
7 98
 
1.6%
8 72
 
1.2%
Other values (17) 266
 
4.3%

Length

2024-04-17T06:14:42.153786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3515
57.0%
5 560
 
9.1%
3 373
 
6.0%
4 371
 
6.0%
총층수 324
 
5.3%
6 223
 
3.6%
1 190
 
3.1%
2 179
 
2.9%
7 98
 
1.6%
8 72
 
1.2%
Other values (17) 266
 
4.3%

frstregts
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
최초등록시점
 
502

Length

Max length6
Median length4
Mean length4.1626965
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> 5669
91.9%
최초등록시점 502
 
8.1%

Length

2024-04-17T06:14:42.301947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:42.404689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
최초등록시점 502
 
8.1%

pasgbreth
Text

MISSING 

Distinct69
Distinct (%)4.5%
Missing4649
Missing (%)75.3%
Memory size48.3 KiB
2024-04-17T06:14:42.555761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.9540079
Min length1

Characters and Unicode

Total characters4496
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

Unique35 ?
Unique (%)2.3%

Sample

1st row1.3
2nd row1.2
3rd row1
4th row1
5th row1.45
ValueCountFrequency (%)
1.2 480
31.5%
통로너비 395
26.0%
1 240
15.8%
1.5 120
 
7.9%
1.3 45
 
3.0%
1.6 29
 
1.9%
1.4 27
 
1.8%
120 21
 
1.4%
2 15
 
1.0%
1.1 13
 
0.9%
Other values (59) 137
 
9.0%
2024-04-17T06:14:42.827614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1121
24.9%
. 795
17.7%
2 575
12.8%
395
 
8.8%
395
 
8.8%
395
 
8.8%
395
 
8.8%
5 171
 
3.8%
3 74
 
1.6%
0 50
 
1.1%
Other values (5) 130
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2121
47.2%
Other Letter 1580
35.1%
Other Punctuation 795
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1121
52.9%
2 575
27.1%
5 171
 
8.1%
3 74
 
3.5%
0 50
 
2.4%
6 49
 
2.3%
4 40
 
1.9%
7 20
 
0.9%
8 12
 
0.6%
9 9
 
0.4%
Other Letter
ValueCountFrequency (%)
395
25.0%
395
25.0%
395
25.0%
395
25.0%
Other Punctuation
ValueCountFrequency (%)
. 795
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2916
64.9%
Hangul 1580
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1121
38.4%
. 795
27.3%
2 575
19.7%
5 171
 
5.9%
3 74
 
2.5%
0 50
 
1.7%
6 49
 
1.7%
4 40
 
1.4%
7 20
 
0.7%
8 12
 
0.4%
Hangul
ValueCountFrequency (%)
395
25.0%
395
25.0%
395
25.0%
395
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2916
64.9%
Hangul 1580
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1121
38.4%
. 795
27.3%
2 575
19.7%
5 171
 
5.9%
3 74
 
2.5%
0 50
 
1.7%
6 49
 
1.7%
4 40
 
1.4%
7 20
 
0.7%
8 12
 
0.4%
Hangul
ValueCountFrequency (%)
395
25.0%
395
25.0%
395
25.0%
395
25.0%

speclghtyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
N
4980 
Y
1012 
<NA>
 
117
 
62

Length

Max length4
Median length1
Mean length1.0568789
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 4980
80.7%
Y 1012
 
16.4%
<NA> 117
 
1.9%
62
 
1.0%

Length

2024-04-17T06:14:42.932744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:43.015386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4980
80.7%
y 1012
 
16.4%
na 117
 
1.9%
62
 
1.0%

cnvefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
 
502

Length

Max length4
Median length4
Mean length3.7559553
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> 5669
91.9%
502
 
8.1%

Length

2024-04-17T06:14:43.099758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:43.178154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
502
 
8.1%

actlnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
<NA>
5669 
품목명
 
502

Length

Max length4
Median length4
Mean length3.9186518
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> 5669
91.9%
품목명 502
 
8.1%

Length

2024-04-17T06:14:43.271770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:43.375548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5669
91.9%
품목명 502
 
8.1%

last_load_dttm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2020-12-22 13:53:32
5049 
2020-12-22 13:53:31
1122 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22 13:53:31
2nd row2020-12-22 13:53:31
3rd row2020-12-22 13:53:31
4th row2020-12-22 13:53:31
5th row2020-12-22 13:53:31

Common Values

ValueCountFrequency (%)
2020-12-22 13:53:32 5049
81.8%
2020-12-22 13:53:31 1122
 
18.2%

Length

2024-04-17T06:14:43.465785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:43.544309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-22 6171
50.0%
13:53:32 5049
40.9%
13:53:31 1122
 
9.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
013250000CDFF324205200100000203_09_01_PI2018-08-31 23:59:59.0<NA>도레미노래연습장<NA>부산광역시 중구 보수동2가 118-1번지48964부산광역시 중구 흑교로45번길 5 (보수동2가)20010924<NA><NA><NA><NA>13영업중384596.82640100000180453.4854800000020141107112320<NA>051-123-1234근린생활시설<NA><NA>3유통관련업노래연습장업N<NA>NN<NA>80<NA>N<NA><NA><NA><NA><NA>2<NA><NA><NA>N<NA>4<NA><NA>N<NA><NA>2020-12-22 13:53:31
123250000CDFF324205200300000603_09_01_PI2018-08-31 23:59:59.0<NA>호심600023부산광역시 중구 동광동3가 21-1번지<NA>부산광역시 중구 백산길 18 (동광동3가)2003041720040901<NA><NA><NA>03폐업385501.48186900000180233.2329710000020040901144719<NA>051-123-1234근린생활시설<NA><NA>3유통관련업노래연습장업Y<NA>NY<NA>114.05<NA>Y<NA><NA><NA>40기타1일반상업지역<NA><NA>N<NA>3<NA>1.3Y<NA><NA>2020-12-22 13:53:31
233250000CDFF324205200300000703_09_01_PI2018-08-31 23:59:59.0<NA>진양600046부산광역시 중구 남포동6가 6번지<NA><NA>2003070220050216<NA><NA><NA>03폐업<NA><NA>20050216174232<NA>051-123-1234근린생활시설<NA><NA>5유통관련업노래연습장업N<NA>YY<NA>121.68<NA>Y<NA><NA><NA>44<NA><NA><NA>1<NA>N<NA>6<NA>1.2Y<NA><NA>2020-12-22 13:53:31
343250000CDFF324205200300000803_09_01_PI2018-08-31 23:59:59.0<NA>도깨비노래연습장<NA>부산광역시 중구 부평동2가 22-3번지48977부산광역시 중구 중구로29번길 30-1 (부평동2가)20031215<NA><NA><NA><NA>13영업중384754.70921800000180131.9187120000020170314174221<NA>051-123-1234근린생활시설<NA><NA>5유통관련업노래연습장업Y<NA>YY<NA>130.81<NA>Y<NA><NA><NA>38<NA>2<NA><NA><NA>N<NA>5<NA>1Y<NA><NA>2020-12-22 13:53:31
453250000CDFF324205200400000103_09_01_PI2018-08-31 23:59:59.0<NA>남포노래연습장<NA>부산광역시 중구 남포동2가 21-1번지48953부산광역시 중구 남포길 22-2 (남포동2가)20040527<NA><NA><NA><NA>13영업중385220.72387000000179923.5324160000020120720110231<NA>051-123-1234근린생활시설<NA><NA>9유통관련업노래연습장업Y<NA>YY<NA>159.77<NA>Y<NA><NA><NA>80유흥업소밀집지역<NA>상업지역17Y<NA>4<NA>1Y<NA><NA>2020-12-22 13:53:31
563250000CDFF324205200500000103_09_01_PI2018-08-31 23:59:59.0<NA>열창노래연습장600045부산광역시 중구 남포동5가 90번지<NA>부산광역시 중구 자갈치로37번길 4-1 (남포동5가)20050223<NA><NA><NA><NA>30허가취소384971.19099500000179770.9898520000020051118121659<NA>051-123-1234근린생활시설<NA><NA><NA>유통관련업노래연습장업N<NA>NN<NA>138.28<NA>N<NA><NA><NA><NA><NA>4<NA>1<NA>N<NA>5<NA><NA>N<NA><NA>2020-12-22 13:53:31
673250000CDFF324205200600000103_09_01_PI2018-08-31 23:59:59.0<NA>GIV 노래연습장600092부산광역시 중구 대청동2가 34-1번지<NA>부산광역시 중구 광복중앙로 28-1 (대청동2가)2006040520071116<NA><NA><NA>03폐업385198.60018500000180287.4883950000020071116142528<NA>051-123-1234근린생활시설<NA><NA><NA>유통관련업노래연습장업N<NA>NN<NA>206.85<NA>N<NA><NA><NA><NA>학교정화(상대)5상업지역1<NA>N<NA>6<NA><NA>N<NA><NA>2020-12-22 13:53:31
783250000CDFF324205200200000903_09_01_PI2018-08-31 23:59:59.0<NA>600060부산광역시 중구 신창동1가 36-6번지<NA>부산광역시 중구 광복중앙로33번길 7-2 (신창동1가)2002080220070227<NA><NA><NA>03폐업385094.07382900000180302.1635580000020070227174949<NA>051-123-1234<NA><NA><NA>4유통관련업노래연습장업N<NA>NN<NA>41.5<NA>N<NA><NA><NA><NA><NA>1<NA><NA><NA>N<NA>2<NA><NA>N<NA><NA>2020-12-22 13:53:31
893250000CDFF324205200200001003_09_01_PI2018-08-31 23:59:59.0<NA>금호노래연습장<NA>부산광역시 중구 영주동 161번지48917부산광역시 중구 영주로 51-1 (영주동)20020131<NA><NA><NA><NA>13영업중385130.56549300000181318.9137460000020170206111033<NA>051-123-1234근린생활시설<NA><NA>14유통관련업노래연습장업N<NA>NN<NA>258.7<NA>N<NA><NA><NA><NA><NA><NA>일반주거지역1<NA>N<NA>3<NA><NA>N<NA><NA>2020-12-22 13:53:31
9103250000CDFF324205200200001103_09_01_PI2018-08-31 23:59:59.0<NA>라이브<NA>부산광역시 중구 창선동1가 6-1번지600051부산광역시 중구 광복로55번길 8 (창선동1가)2002060420120207<NA><NA><NA>35직권말소385175.33520100000180057.5588260000020120504141048<NA>051-123-1234근린생활시설<NA><NA>14유통관련업노래연습장업N<NA>NN<NA>177.7<NA>N<NA><NA><NA><NA><NA>4<NA><NA>14Y<NA>5<NA><NA>N<NA><NA>2020-12-22 13:53:31
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
616161645380000CDFF324205202000000203_09_01_PI2020-12-13 00:23:06.0노래연습장업OX 코인노래연습장지번우편번호경상남도 양산시 동면 석산리 1452-3 동진그린타워50650경상남도 양산시 동면 금오13길 18, 동진그린타워20201211폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중384149.516540851203872.66926682320201211150959업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명10유통관련업노래연습장업비디오재생기명67.76제공게임물명제작취급품목내용133주변환경명지상층수지역구분명지하층수10Y총게임기수총층수최초등록시점120품목명2020-12-22 13:53:32
616261654800000CDFF324205200900001403_09_01_PI2020-12-16 00:23:06.0노래연습장업빅뱅노래연습장<NA>전라남도 목포시 상동 993 (2층)58691전라남도 목포시 비파로51번길 17 (상동,(2층))20091126<NA><NA><NA><NA>영업/정상영업중147302.308797145006.31787220201214094135<NA>061-278-4194근린생활시설<NA><NA>8유통관련업노래연습장업Y<NA>YY<NA>161<NA>Y<NA><NA><NA><NA>유흥업소밀집지역2일반상업지역<NA>2Y<NA>3<NA><NA>Y<NA><NA>2020-12-22 13:53:32
616361663780000CDFF324205202000000703_09_01_PI2020-12-17 00:23:06.0노래연습장업연 노래연습장지번우편번호경기도 성남시 중원구 상대원동 204513242경기도 성남시 중원구 희망로326번길 6, 지하1층 (상대원동)20201215폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중213974.002179808436995.79004534220201215093529업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명5유통관련업노래연습장업비디오재생기명103.93제공게임물명제작취급품목내용조명시설조도주변환경명4준주거지역1청소년실수총게임기수5최초등록시점통로너비품목명2020-12-22 13:53:32
616461675020000CDFF324205202000000503_09_01_PI2020-12-18 00:23:06.0노래연습장업정나눔노래연습장지번우편번호경상북도 포항시 남구 해도동 63-1937806경상북도 포항시 남구 해동로 23-1, 2층 (해도동)20201216폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중413901.166317108282734.34240963620201216111826업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명4유통관련업노래연습장업비디오재생기명YY115.5Y제공게임물명제작취급품목내용조명시설조도기타지상층수일반상업지역지하층수청소년실수총게임기수총층수최초등록시점통로너비품목명2020-12-22 13:53:32
616561685390000CDFF324205202000000103_09_01_PI2020-12-20 00:23:06.0노래연습장업대남PC&코인노래연습장지번우편번호경상남도 의령군 의령읍 서동리 490-2052150경상남도 의령군 의령읍 의병로 20820201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중314464.587439325202943.36789292220201218141533업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명12유통관련업노래연습장업Y비디오재생기명Y123.4제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수12Y총게임기수총층수최초등록시점통로너비품목명2020-12-22 13:53:32
616661694000000CDFF324205202000000803_09_01_PI2020-12-20 00:23:06.0노래연습장업철구PC 노래<NA>경기도 오산시 원동 811-8 중앙씨티월118139경기도 오산시 성호대로 130, 중앙씨티월1 502-1호 (원동)20201218<NA><NA><NA><NA>영업/정상영업중206663.103451455405187.03358203620201218094252<NA>031-377-7955근린생활시설<NA><NA>4유통관련업노래연습장업<NA><NA><NA><NA><NA>123.12<NA><NA><NA><NA><NA><NA>유흥업소밀집지역11일반상업지역14Y<NA>12<NA><NA><NA><NA><NA>2020-12-22 13:53:32
616761703940000CDFF324205202000001303_09_01_PI2020-12-20 00:23:06.0노래연습장업엔젤스코인 노래연습장 화정점<NA>경기도 고양시 덕양구 화정동 984-4 301호10500경기도 고양시 덕양구 화신로272번길 21, 301호 (화정동)20201218<NA><NA><NA><NA>영업/정상영업중185026.202272059458859.38287308820201218174659<NA><NA><NA><NA><NA>20유통관련업노래연습장업Y<NA>YY<NA>149.25<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA>Y<NA><NA><NA><NA><NA><NA><NA>2020-12-22 13:53:32
616861715390000CDFF324205202000000103_09_01_PI2020-12-20 00:23:06.0노래연습장업대남PC&코인노래연습장지번우편번호경상남도 의령군 의령읍 서동리 490-2052150경상남도 의령군 의령읍 의병로 20820201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중314464.587439325202943.36789292220201218141533업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명12유통관련업노래연습장업Y비디오재생기명Y123.4제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수12Y총게임기수총층수최초등록시점통로너비품목명2020-12-22 13:53:32
616961724000000CDFF324205202000000803_09_01_PI2020-12-20 00:23:06.0노래연습장업철구PC 노래<NA>경기도 오산시 원동 811-8 중앙씨티월118139경기도 오산시 성호대로 130, 중앙씨티월1 502-1호 (원동)20201218<NA><NA><NA><NA>영업/정상영업중206663.103451455405187.03358203620201218094252<NA>031-377-7955근린생활시설<NA><NA>4유통관련업노래연습장업<NA><NA><NA><NA><NA>123.12<NA><NA><NA><NA><NA><NA>유흥업소밀집지역11일반상업지역14Y<NA>12<NA><NA><NA><NA><NA>2020-12-22 13:53:32
617061733940000CDFF324205202000001303_09_01_PI2020-12-20 00:23:06.0노래연습장업엔젤스코인 노래연습장 화정점<NA>경기도 고양시 덕양구 화정동 984-4 301호10500경기도 고양시 덕양구 화신로272번길 21, 301호 (화정동)20201218<NA><NA><NA><NA>영업/정상영업중185026.202272059458859.38287308820201218174659<NA><NA><NA><NA><NA>20유통관련업노래연습장업Y<NA>YY<NA>149.25<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA>Y<NA><NA><NA><NA><NA><NA><NA>2020-12-22 13:53:32