Overview

Dataset statistics

Number of variables56
Number of observations6174
Missing cells22661
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
Categorical37
DateTime2

Alerts

opnsvcid has constant value ""Constant
culwrkrsenm has constant value ""Constant
culphyedcobnm has constant value ""Constant
updategbn is highly imbalanced (52.3%)Imbalance
clgstdt is highly imbalanced (83.7%)Imbalance
clgenddt is highly imbalanced (83.7%)Imbalance
ropnymd is highly imbalanced (59.3%)Imbalance
trdstatenm is highly imbalanced (50.0%)Imbalance
dtlstatenm is highly imbalanced (61.9%)Imbalance
uptaenm is highly imbalanced (59.3%)Imbalance
sitetel is highly imbalanced (94.1%)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 (55.9%)Imbalance
vdoretornm is highly imbalanced (59.3%)Imbalance
emerstairyn is highly imbalanced (60.6%)Imbalance
emexyn is highly imbalanced (62.1%)Imbalance
firefacilyn is highly imbalanced (59.3%)Imbalance
soundfacilyn is highly imbalanced (59.3%)Imbalance
autochaairyn is highly imbalanced (52.0%)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 (53.6%)Imbalance
totgasyscnt is highly imbalanced (59.3%)Imbalance
frstregts is highly imbalanced (59.3%)Imbalance
speclghtyn is highly imbalanced (56.6%)Imbalance
cnvefacilyn is highly imbalanced (59.3%)Imbalance
actlnm is highly imbalanced (59.3%)Imbalance
sitepostno has 4250 (68.8%) missing valuesMissing
rdnpostno has 2162 (35.0%) missing valuesMissing
rdnwhladdr has 363 (5.9%) missing valuesMissing
dcbymd has 3770 (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 (16.1%) missing valuesMissing
lghtfacilinillu has 4639 (75.1%) missing valuesMissing
pasgbreth has 4650 (75.3%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 21:14:08.035069
Analysis finished2024-04-16 21:14:10.110194
Duration2.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct6174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3087.9568
Minimum1
Maximum6176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:10.163143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile309.65
Q11544.25
median3087.5
Q34631.75
95-th percentile5867.35
Maximum6176
Range6175
Interquartile range (IQR)3087.5

Descriptive statistics

Standard deviation1783.0192
Coefficient of variation (CV)0.57741068
Kurtosis-1.1998359
Mean3087.9568
Median Absolute Deviation (MAD)1544
Skewness0.0005940553
Sum19065045
Variance3179157.5
MonotonicityNot monotonic
2024-04-17T06:14:10.278540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
4054 1
 
< 0.1%
4124 1
 
< 0.1%
4123 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%
Other values (6164) 6164
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 (%)
6176 1
< 0.1%
6175 1
< 0.1%
6174 1
< 0.1%
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%

opnsfteamcode
Real number (ℝ)

Distinct183
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3578457.2
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:10.416393image/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 deviation613332.32
Coefficient of variation (CV)0.17139574
Kurtosis6.6645827
Mean3578457.2
Median Absolute Deviation (MAD)50000
Skewness2.6426358
Sum2.2093394 × 1010
Variance3.7617654 × 1011
MonotonicityNot monotonic
2024-04-17T06:14:10.547409image/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 235
 
3.8%
Other values (173) 2273
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 size48.4 KiB
2024-04-17T06:14:10.738992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters123480
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 169
 
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) 5037
81.6%
2024-04-17T06:14:11.016799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41870
33.9%
2 19322
15.6%
F 12348
 
10.0%
3 7684
 
6.2%
4 7436
 
6.0%
5 7217
 
5.8%
1 6457
 
5.2%
C 6174
 
5.0%
D 6174
 
5.0%
9 5847
 
4.7%
Other values (3) 2951
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98784
80.0%
Uppercase Letter 24696
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41870
42.4%
2 19322
19.6%
3 7684
 
7.8%
4 7436
 
7.5%
5 7217
 
7.3%
1 6457
 
6.5%
9 5847
 
5.9%
8 1056
 
1.1%
6 950
 
1.0%
7 945
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
F 12348
50.0%
C 6174
25.0%
D 6174
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98784
80.0%
Latin 24696
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41870
42.4%
2 19322
19.6%
3 7684
 
7.8%
4 7436
 
7.5%
5 7217
 
7.3%
1 6457
 
6.5%
9 5847
 
5.9%
8 1056
 
1.1%
6 950
 
1.0%
7 945
 
1.0%
Latin
ValueCountFrequency (%)
F 12348
50.0%
C 6174
25.0%
D 6174
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41870
33.9%
2 19322
15.6%
F 12348
 
10.0%
3 7684
 
6.2%
4 7436
 
6.0%
5 7217
 
5.8%
1 6457
 
5.2%
C 6174
 
5.0%
D 6174
 
5.0%
9 5847
 
4.7%
Other values (3) 2951
 
2.4%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
03_09_01_P
6174 

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 6174
100.0%

Length

2024-04-17T06:14:11.317565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:11.386987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_09_01_p 6174
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
I
5541 
U
633 

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 5541
89.7%
U 633
 
10.3%

Length

2024-04-17T06:14:11.460819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:11.533132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5541
89.7%
u 633
 
10.3%
Distinct669
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T06:14:11.614501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:14:11.718588image/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 size48.4 KiB
<NA>
4306 
노래연습장업
1868 

Length

Max length6
Median length4
Mean length4.6051182
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
69.7%
노래연습장업 1868
30.3%

Length

2024-04-17T06:14:11.826771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:11.909004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4306
69.7%
노래연습장업 1868
30.3%

bplcnm
Text

Distinct3656
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
2024-04-17T06:14:12.104259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length7.6841594
Min length1

Characters and Unicode

Total characters47442
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 1464
 
17.4%
코인노래연습장 204
 
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 (3429) 6362
75.8%
2024-04-17T06:14:12.440165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5067
 
10.7%
5064
 
10.7%
4964
 
10.5%
4950
 
10.4%
4907
 
10.3%
2218
 
4.7%
1030
 
2.2%
1005
 
2.1%
788
 
1.7%
399
 
0.8%
Other values (767) 17050
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43560
91.8%
Space Separator 2218
 
4.7%
Uppercase Letter 904
 
1.9%
Decimal Number 291
 
0.6%
Lowercase Letter 178
 
0.4%
Close Punctuation 108
 
0.2%
Open 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 (%)
5067
 
11.6%
5064
 
11.6%
4964
 
11.4%
4950
 
11.4%
4907
 
11.3%
1030
 
2.4%
1005
 
2.3%
788
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (696) 14993
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%
t 15
 
8.4%
e 15
 
8.4%
i 13
 
7.3%
r 13
 
7.3%
n 11
 
6.2%
g 11
 
6.2%
a 10
 
5.6%
s 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%
4 5
 
1.7%
6 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 (%)
2218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Open 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 43555
91.8%
Common 2799
 
5.9%
Latin 1083
 
2.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5067
 
11.6%
5064
 
11.6%
4964
 
11.4%
4950
 
11.4%
4907
 
11.3%
1030
 
2.4%
1005
 
2.3%
788
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (692) 14988
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 (%)
2218
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 43555
91.8%
ASCII 3881
 
8.2%
CJK 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5067
 
11.6%
5064
 
11.6%
4964
 
11.4%
4950
 
11.4%
4907
 
11.3%
1030
 
2.4%
1005
 
2.3%
788
 
1.8%
399
 
0.9%
393
 
0.9%
Other values (692) 14988
34.4%
ASCII
ValueCountFrequency (%)
2218
57.2%
2 130
 
3.3%
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%
Missing4250
Missing (%)68.8%
Memory size48.4 KiB
2024-04-17T06:14:12.724411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters11544
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 503
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
60.2%
2024-04-17T06:14:13.081213image/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%
1006
8.7%
4 783
 
6.8%
9 641
 
5.6%
503
 
4.4%
503
 
4.4%
503
 
4.4%
Other values (5) 1971
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8526
73.9%
Other Letter 3018
 
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 (%)
1006
33.3%
503
16.7%
503
16.7%
503
16.7%
503
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 8526
73.9%
Hangul 3018
 
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 (%)
1006
33.3%
503
16.7%
503
16.7%
503
16.7%
503
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8526
73.9%
Hangul 3018
 
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 (%)
1006
33.3%
503
16.7%
503
16.7%
503
16.7%
503
16.7%
Distinct4982
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
2024-04-17T06:14:13.360656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length24.050696
Min length8

Characters and Unicode

Total characters148489
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

Unique4157 ?
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 4473
 
16.4%
금정구 688
 
2.5%
부산진구 574
 
2.1%
경기도 558
 
2.0%
동래구 459
 
1.7%
해운대구 434
 
1.6%
북구 368
 
1.3%
사상구 352
 
1.3%
사하구 316
 
1.2%
지하1층 301
 
1.1%
Other values (6354) 18762
68.8%
2024-04-17T06:14:13.743033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27105
 
18.3%
6744
 
4.5%
1 6273
 
4.2%
6225
 
4.2%
6142
 
4.1%
5722
 
3.9%
5715
 
3.8%
- 5607
 
3.8%
5525
 
3.7%
5516
 
3.7%
Other values (470) 67915
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85847
57.8%
Decimal Number 29188
 
19.7%
Space Separator 27105
 
18.3%
Dash Punctuation 5607
 
3.8%
Open Punctuation 286
 
0.2%
Close 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 (%)
6744
 
7.9%
6225
 
7.3%
6142
 
7.2%
5722
 
6.7%
5715
 
6.7%
5525
 
6.4%
5516
 
6.4%
4935
 
5.7%
4747
 
5.5%
1327
 
1.5%
Other values (424) 33249
38.7%
Uppercase Letter
ValueCountFrequency (%)
B 28
41.8%
C 7
 
10.4%
A 5
 
7.5%
G 5
 
7.5%
M 5
 
7.5%
T 4
 
6.0%
S 3
 
4.5%
I 2
 
3.0%
K 2
 
3.0%
D 2
 
3.0%
Other values (4) 4
 
6.0%
Decimal Number
ValueCountFrequency (%)
1 6273
21.5%
2 4161
14.3%
3 3155
10.8%
4 2882
9.9%
5 2484
 
8.5%
6 2244
 
7.7%
0 2229
 
7.6%
7 1969
 
6.7%
8 1939
 
6.6%
9 1852
 
6.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
20.0%
g 4
20.0%
s 3
15.0%
r 2
10.0%
c 2
10.0%
a 1
 
5.0%
m 1
 
5.0%
o 1
 
5.0%
l 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 (%)
27105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5607
100.0%
Open Punctuation
ValueCountFrequency (%)
( 286
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85847
57.8%
Common 62551
42.1%
Latin 91
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6744
 
7.9%
6225
 
7.3%
6142
 
7.2%
5722
 
6.7%
5715
 
6.7%
5525
 
6.4%
5516
 
6.4%
4935
 
5.7%
4747
 
5.5%
1327
 
1.5%
Other values (424) 33249
38.7%
Latin
ValueCountFrequency (%)
B 28
30.8%
C 7
 
7.7%
A 5
 
5.5%
G 5
 
5.5%
M 5
 
5.5%
e 4
 
4.4%
g 4
 
4.4%
T 4
 
4.4%
S 3
 
3.3%
s 3
 
3.3%
Other values (16) 23
25.3%
Common
ValueCountFrequency (%)
27105
43.3%
1 6273
 
10.0%
- 5607
 
9.0%
2 4161
 
6.7%
3 3155
 
5.0%
4 2882
 
4.6%
5 2484
 
4.0%
6 2244
 
3.6%
0 2229
 
3.6%
7 1969
 
3.1%
Other values (10) 4442
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85847
57.8%
ASCII 62638
42.2%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27105
43.3%
1 6273
 
10.0%
- 5607
 
9.0%
2 4161
 
6.6%
3 3155
 
5.0%
4 2882
 
4.6%
5 2484
 
4.0%
6 2244
 
3.6%
0 2229
 
3.6%
7 1969
 
3.1%
Other values (34) 4529
 
7.2%
Hangul
ValueCountFrequency (%)
6744
 
7.9%
6225
 
7.3%
6142
 
7.2%
5722
 
6.7%
5715
 
6.7%
5525
 
6.4%
5516
 
6.4%
4935
 
5.7%
4747
 
5.5%
1327
 
1.5%
Other values (424) 33249
38.7%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1771
Distinct (%)44.1%
Missing2162
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean76658.268
Minimum1039
Maximum619951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:13.854602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1039
5-th percentile6922.55
Q127352
median47018.5
Q348490.5
95-th percentile607837.45
Maximum619951
Range618912
Interquartile range (IQR)21138.5

Descriptive statistics

Standard deviation144712.57
Coefficient of variation (CV)1.8877621
Kurtosis9.6013045
Mean76658.268
Median Absolute Deviation (MAD)2425
Skewness3.3770498
Sum3.0755297 × 108
Variance2.0941728 × 1010
MonotonicityNot monotonic
2024-04-17T06:14:13.957449image/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%
47006 22
 
0.4%
48953 22
 
0.4%
46576 21
 
0.3%
48280 21
 
0.3%
48095 20
 
0.3%
47551 20
 
0.3%
Other values (1761) 3787
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 

Distinct4924
Distinct (%)84.7%
Missing363
Missing (%)5.9%
Memory size48.4 KiB
2024-04-17T06:14:14.243009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length53
Mean length28.361211
Min length18

Characters and Unicode

Total characters164807
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

Unique4339 ?
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 4112
 
12.5%
2층 664
 
2.0%
금정구 663
 
2.0%
경기도 558
 
1.7%
부산진구 527
 
1.6%
지하1층 525
 
1.6%
동래구 445
 
1.3%
해운대구 421
 
1.3%
3층 337
 
1.0%
사상구 333
 
1.0%
Other values (4865) 24396
74.0%
2024-04-17T06:14:14.641139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28686
 
17.4%
6791
 
4.1%
5943
 
3.6%
5546
 
3.4%
5439
 
3.3%
) 5438
 
3.3%
( 5438
 
3.3%
1 5398
 
3.3%
5259
 
3.2%
5231
 
3.2%
Other values (534) 85638
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96643
58.6%
Space Separator 28686
 
17.4%
Decimal Number 24707
 
15.0%
Close Punctuation 5438
 
3.3%
Open Punctuation 5438
 
3.3%
Other Punctuation 2737
 
1.7%
Dash Punctuation 990
 
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 (%)
6791
 
7.0%
5943
 
6.1%
5546
 
5.7%
5439
 
5.6%
5259
 
5.4%
5231
 
5.4%
4750
 
4.9%
4411
 
4.6%
2608
 
2.7%
2135
 
2.2%
Other values (488) 48530
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%
K 4
 
3.5%
T 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%
s 3
13.6%
g 3
13.6%
r 2
9.1%
a 1
 
4.5%
m 1
 
4.5%
o 1
 
4.5%
l 1
 
4.5%
t 1
 
4.5%
Other values (2) 2
9.1%
Decimal Number
ValueCountFrequency (%)
1 5398
21.8%
2 4090
16.6%
3 2950
11.9%
0 2111
 
8.5%
4 2080
 
8.4%
5 1901
 
7.7%
6 1739
 
7.0%
7 1603
 
6.5%
8 1419
 
5.7%
9 1416
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 2729
99.7%
. 7
 
0.3%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
28686
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5438
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5438
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 990
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96643
58.6%
Common 68023
41.3%
Latin 141
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6791
 
7.0%
5943
 
6.1%
5546
 
5.7%
5439
 
5.6%
5259
 
5.4%
5231
 
5.4%
4750
 
4.9%
4411
 
4.6%
2608
 
2.7%
2135
 
2.2%
Other values (488) 48530
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%
K 4
 
2.8%
e 4
 
2.8%
T 4
 
2.8%
N 4
 
2.8%
Other values (18) 30
21.3%
Common
ValueCountFrequency (%)
28686
42.2%
) 5438
 
8.0%
( 5438
 
8.0%
1 5398
 
7.9%
2 4090
 
6.0%
3 2950
 
4.3%
, 2729
 
4.0%
0 2111
 
3.1%
4 2080
 
3.1%
5 1901
 
2.8%
Other values (8) 7202
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96643
58.6%
ASCII 68160
41.4%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28686
42.1%
) 5438
 
8.0%
( 5438
 
8.0%
1 5398
 
7.9%
2 4090
 
6.0%
3 2950
 
4.3%
, 2729
 
4.0%
0 2111
 
3.1%
4 2080
 
3.1%
5 1901
 
2.8%
Other values (34) 7339
 
10.8%
Hangul
ValueCountFrequency (%)
6791
 
7.0%
5943
 
6.1%
5546
 
5.7%
5439
 
5.6%
5259
 
5.4%
5231
 
5.4%
4750
 
4.9%
4411
 
4.6%
2608
 
2.7%
2135
 
2.2%
Other values (488) 48530
50.2%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%

apvpermymd
Real number (ℝ)

Distinct3031
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20063372
Minimum19000101
Maximum20201230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:14.757152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19000101
5-th percentile19940176
Q119990430
median20021211
Q320181220
95-th percentile20200328
Maximum20201230
Range1201129
Interquartile range (IQR)190790

Descriptive statistics

Standard deviation95315.504
Coefficient of variation (CV)0.004750722
Kurtosis1.0040073
Mean20063372
Median Absolute Deviation (MAD)60101
Skewness0.10308724
Sum1.2387126 × 1011
Variance9.0850454 × 109
MonotonicityNot monotonic
2024-04-17T06:14:14.868036image/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 (3021) 5841
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 (%)
20201230 2
 
< 0.1%
20201222 1
 
< 0.1%
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%

dcbymd
Text

MISSING 

Distinct1440
Distinct (%)59.9%
Missing3770
Missing (%)61.1%
Memory size48.4 KiB
2024-04-17T06:14:15.085865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.1680532
Min length4

Characters and Unicode

Total characters17232
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

Unique1133 ?
Unique (%)47.1%

Sample

1st row20040901
2nd row20050216
3rd row20071116
4th row20070227
5th row20120207
ValueCountFrequency (%)
폐업일자 500
 
20.8%
20071126 24
 
1.0%
20040317 16
 
0.7%
20081217 9
 
0.4%
20140703 8
 
0.3%
20100219 8
 
0.3%
20170530 7
 
0.3%
20151228 7
 
0.3%
20140325 7
 
0.3%
20000214 7
 
0.3%
Other values (1430) 1811
75.3%
2024-04-17T06:14:15.423484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5293
30.7%
2 3142
18.2%
1 2768
16.1%
3 713
 
4.1%
7 688
 
4.0%
6 592
 
3.4%
5 528
 
3.1%
4 508
 
2.9%
8 503
 
2.9%
500
 
2.9%
Other values (4) 1997
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15232
88.4%
Other Letter 2000
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5293
34.7%
2 3142
20.6%
1 2768
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 503
 
3.3%
9 497
 
3.3%
Other Letter
ValueCountFrequency (%)
500
25.0%
500
25.0%
500
25.0%
500
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15232
88.4%
Hangul 2000
 
11.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5293
34.7%
2 3142
20.6%
1 2768
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 503
 
3.3%
9 497
 
3.3%
Hangul
ValueCountFrequency (%)
500
25.0%
500
25.0%
500
25.0%
500
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15232
88.4%
Hangul 2000
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5293
34.7%
2 3142
20.6%
1 2768
18.2%
3 713
 
4.7%
7 688
 
4.5%
6 592
 
3.9%
5 528
 
3.5%
4 508
 
3.3%
8 503
 
3.3%
9 497
 
3.3%
Hangul
ValueCountFrequency (%)
500
25.0%
500
25.0%
500
25.0%
500
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5665 
휴업시작일자
 
503
20201026
 
3
20120827
 
1
20091029
 
1

Length

Max length8
Median length4
Mean length4.1668286
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> 5665
91.8%
휴업시작일자 503
 
8.1%
20201026 3
 
< 0.1%
20120827 1
 
< 0.1%
20091029 1
 
< 0.1%
20200818 1
 
< 0.1%

Length

2024-04-17T06:14:15.549781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:15.652145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5665
91.8%
휴업시작일자 503
 
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 size48.4 KiB
<NA>
5665 
휴업종료일자
 
503
20201130
 
3
20150824
 
1
20091104
 
1

Length

Max length8
Median length4
Mean length4.1668286
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> 5665
91.8%
휴업종료일자 503
 
8.1%
20201130 3
 
< 0.1%
20150824 1
 
< 0.1%
20091104 1
 
< 0.1%
20201201 1
 
< 0.1%

Length

2024-04-17T06:14:15.745323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:15.836797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5665
91.8%
휴업종료일자 503
 
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 size48.4 KiB
<NA>
5671 
재개업일자
 
503

Length

Max length5
Median length4
Mean length4.0814707
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> 5671
91.9%
재개업일자 503
 
8.1%

Length

2024-04-17T06:14:15.924904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:15.998582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
재개업일자 503
 
8.1%

trdstatenm
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
13
2293 
영업/정상
1786 
03
1728 
35
 
133
31
 
97
Other values (10)
 
137

Length

Max length14
Median length2
Mean length2.8788468
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 2293
37.1%
영업/정상 1786
28.9%
03 1728
28.0%
35 133
 
2.2%
31 97
 
1.6%
폐업 59
 
1.0%
30 30
 
0.5%
25 13
 
0.2%
<NA> 11
 
0.2%
33 10
 
0.2%
Other values (5) 14
 
0.2%

Length

2024-04-17T06:14:16.076371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13 2293
37.1%
영업/정상 1786
28.9%
03 1728
28.0%
35 133
 
2.2%
31 97
 
1.6%
폐업 59
 
1.0%
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 size48.4 KiB
영업중
4095 
폐업
1787 
직권말소
 
135
등록취소
 
98
허가취소
 
30
Other values (4)
 
29

Length

Max length5
Median length3
Mean length2.7563978
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 4095
66.3%
폐업 1787
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

2024-04-17T06:14:16.165219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:16.259314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 4095
66.3%
폐업 1787
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 

Distinct4687
Distinct (%)78.5%
Missing205
Missing (%)3.3%
Memory size48.4 KiB
2024-04-17T06:14:16.442789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.945552
Min length7

Characters and Unicode

Total characters119055
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

Unique3804 ?
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%
208609.386752684 7
 
0.1%
398274.39006400000 7
 
0.1%
170875.132162658 6
 
0.1%
400040.89421700000 6
 
0.1%
389728.19289000000 6
 
0.1%
389360.993759525 6
 
0.1%
223015.954114646 5
 
0.1%
175411.593577176 4
 
0.1%
Other values (4677) 5888
98.6%
2024-04-17T06:14:16.723916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26313
22.1%
18601
15.6%
3 10710
9.0%
8 9033
 
7.6%
9 8129
 
6.8%
1 7339
 
6.2%
2 7007
 
5.9%
7 6699
 
5.6%
4 6513
 
5.5%
5 6446
 
5.4%
Other values (10) 12265
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94362
79.3%
Space Separator 18601
 
15.6%
Other Punctuation 5911
 
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 26313
27.9%
3 10710
11.3%
8 9033
 
9.6%
9 8129
 
8.6%
1 7339
 
7.8%
2 7007
 
7.4%
7 6699
 
7.1%
4 6513
 
6.9%
5 6446
 
6.8%
6 6173
 
6.5%
Other Letter
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Space Separator
ValueCountFrequency (%)
18601
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5911
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 118930
99.9%
Hangul 100
 
0.1%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26313
22.1%
18601
15.6%
3 10710
9.0%
8 9033
 
7.6%
9 8129
 
6.8%
1 7339
 
6.2%
2 7007
 
5.9%
7 6699
 
5.6%
4 6513
 
5.5%
5 6446
 
5.4%
Other values (5) 12140
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 118955
99.9%
Hangul 100
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26313
22.1%
18601
15.6%
3 10710
9.0%
8 9033
 
7.6%
9 8129
 
6.8%
1 7339
 
6.2%
2 7007
 
5.9%
7 6699
 
5.6%
4 6513
 
5.5%
5 6446
 
5.4%
Other values (6) 12165
10.2%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

y
Text

MISSING 

Distinct4687
Distinct (%)78.5%
Missing205
Missing (%)3.3%
Memory size48.4 KiB
2024-04-17T06:14:16.903514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.945552
Min length7

Characters and Unicode

Total characters119055
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

Unique3804 ?
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%
410629.472499067 7
 
0.1%
188234.66906700000 7
 
0.1%
447263.829719015 6
 
0.1%
188878.91983800000 6
 
0.1%
199652.82883000000 6
 
0.1%
191580.392783184 6
 
0.1%
332198.530078572 5
 
0.1%
433323.533492479 4
 
0.1%
Other values (4677) 5888
98.6%
2024-04-17T06:14:17.179041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25760
21.6%
18524
15.6%
1 10971
9.2%
8 8596
 
7.2%
9 8331
 
7.0%
4 7510
 
6.3%
7 6990
 
5.9%
2 6631
 
5.6%
3 6614
 
5.6%
6 6607
 
5.5%
Other values (11) 12521
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94410
79.3%
Space Separator 18524
 
15.6%
Other Punctuation 5911
 
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 25760
27.3%
1 10971
11.6%
8 8596
 
9.1%
9 8331
 
8.8%
4 7510
 
8.0%
7 6990
 
7.4%
2 6631
 
7.0%
3 6614
 
7.0%
6 6607
 
7.0%
5 6400
 
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 (%)
18524
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5911
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 118930
99.9%
Hangul 100
 
0.1%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25760
21.7%
18524
15.6%
1 10971
9.2%
8 8596
 
7.2%
9 8331
 
7.0%
4 7510
 
6.3%
7 6990
 
5.9%
2 6631
 
5.6%
3 6614
 
5.6%
6 6607
 
5.6%
Other values (6) 12396
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 118955
99.9%
Hangul 100
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25760
21.7%
18524
15.6%
1 10971
9.2%
8 8596
 
7.2%
9 8331
 
7.0%
4 7510
 
6.3%
7 6990
 
5.9%
2 6631
 
5.6%
3 6614
 
5.6%
6 6607
 
5.6%
Other values (7) 12421
10.4%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

lastmodts
Real number (ℝ)

Distinct5423
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.01446 × 1013
Minimum2.0021018 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:17.293548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0050308 × 1013
Q12.0100811 × 1013
median2.0160626 × 1013
Q32.019041 × 1013
95-th percentile2.020082 × 1013
Maximum2.0201231 × 1013
Range1.8021302 × 1011
Interquartile range (IQR)8.9598743 × 1010

Descriptive statistics

Standard deviation4.9009092 × 1010
Coefficient of variation (CV)0.002432865
Kurtosis-0.61895653
Mean2.01446 × 1013
Median Absolute Deviation (MAD)3.0580468 × 1010
Skewness-0.66774066
Sum1.2437276 × 1017
Variance2.4018911 × 1021
MonotonicityNot monotonic
2024-04-17T06:14:17.646525image/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%
20200915163144 4
 
0.1%
20200710134452 4
 
0.1%
20200717165016 4
 
0.1%
20190215173917 3
 
< 0.1%
20200709173213 3
 
< 0.1%
20200417173347 3
 
< 0.1%
20200630195552 3
 
< 0.1%
Other values (5413) 5956
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 (%)
20201231150115 1
 
< 0.1%
20201231101740 1
 
< 0.1%
20201230140006 1
 
< 0.1%
20201230105451 3
< 0.1%
20201230103102 1
 
< 0.1%
20201229154005 1
 
< 0.1%
20201228180123 3
< 0.1%
20201228174314 1
 
< 0.1%
20201228132738 1
 
< 0.1%
20201224135056 1
 
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
업태구분명
 
503

Length

Max length5
Median length4
Mean length4.0814707
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> 5671
91.9%
업태구분명 503
 
8.1%

Length

2024-04-17T06:14:17.748430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:17.822129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
업태구분명 503
 
8.1%

sitetel
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
051-123-1234
5962 
<NA>
 
116
전화번호
 
65
054-433-4625
 
3
041-567-7179
 
2
Other values (25)
 
26

Length

Max length12
Median length12
Mean length11.758989
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 5962
96.6%
<NA> 116
 
1.9%
전화번호 65
 
1.1%
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

2024-04-17T06:14:17.916031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 5962
96.6%
na 116
 
1.9%
전화번호 65
 
1.1%
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 size48.4 KiB
<NA>
3654 
근린생활시설
2210 
건물용도명
 
258
사무실
 
13
기타
 
11
Other values (12)
 
28

Length

Max length7
Median length4
Mean length4.7531584
Min length2

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3654
59.2%
근린생활시설 2210
35.8%
건물용도명 258
 
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

2024-04-17T06:14:18.027543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3654
59.2%
근린생활시설 2210
35.8%
건물용도명 258
 
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 size48.4 KiB
<NA>
5671 
공연장형태구분명
 
503

Length

Max length8
Median length4
Mean length4.3258827
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> 5671
91.9%
공연장형태구분명 503
 
8.1%

Length

2024-04-17T06:14:18.123240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:18.204640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
공연장형태구분명 503
 
8.1%

bfgameocptectcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
기존게임업외업종명
 
503

Length

Max length9
Median length4
Mean length4.4073534
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> 5671
91.9%
기존게임업외업종명 503
 
8.1%

Length

2024-04-17T06:14:18.282225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:18.355089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
기존게임업외업종명 503
 
8.1%

noroomcnt
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)1.0%
Missing1420
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean9.2835507
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-17T06:14:18.437287image/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 deviation6.5357579
Coefficient of variation (CV)0.70401489
Kurtosis9.9892112
Mean9.2835507
Median Absolute Deviation (MAD)2
Skewness2.3217107
Sum44134
Variance42.716132
MonotonicityNot monotonic
2024-04-17T06:14:18.549716image/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
 
8.7%
7 535
 
8.7%
8 390
 
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) 1138
18.4%
(Missing) 1420
23.0%
ValueCountFrequency (%)
1 35
 
0.6%
2 56
 
0.9%
3 154
 
2.5%
4 540
8.7%
5 710
11.5%
6 611
9.9%
7 535
8.7%
8 390
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 size48.4 KiB
유통관련업
6174 

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 6174
100.0%

Length

2024-04-17T06:14:18.673554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:18.750637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 6174
100.0%

culphyedcobnm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
노래연습장업
6174 

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 6174
100.0%

Length

2024-04-17T06:14:18.824058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:18.894768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장업 6174
100.0%

souarfacilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
N
4832 
Y
1201 
<NA>
 
94
 
47

Length

Max length4
Median length1
Mean length1.0456754
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 4832
78.3%
Y 1201
 
19.5%
<NA> 94
 
1.5%
47
 
0.8%

Length

2024-04-17T06:14:18.975728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:19.056185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4832
78.3%
y 1201
 
19.5%
na 94
 
1.5%
47
 
0.8%

vdoretornm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
비디오재생기명
 
503

Length

Max length7
Median length4
Mean length4.2444121
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> 5671
91.9%
비디오재생기명 503
 
8.1%

Length

2024-04-17T06:14:19.142033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:19.219192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
비디오재생기명 503
 
8.1%

emerstairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
N
5119 
Y
895 
<NA>
 
106
 
54

Length

Max length4
Median length1
Mean length1.0515063
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 5119
82.9%
Y 895
 
14.5%
<NA> 106
 
1.7%
54
 
0.9%

Length

2024-04-17T06:14:19.312563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:19.396765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5119
82.9%
y 895
 
14.5%
na 106
 
1.7%
54
 
0.9%

emexyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
N
5157 
Y
882 
<NA>
 
94
 
41

Length

Max length4
Median length1
Mean length1.0456754
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 5157
83.5%
Y 882
 
14.3%
<NA> 94
 
1.5%
41
 
0.7%

Length

2024-04-17T06:14:19.484208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:19.565340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5157
83.5%
y 882
 
14.3%
na 94
 
1.5%
41
 
0.7%

firefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
 
503

Length

Max length4
Median length4
Mean length3.7555879
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> 5671
91.9%
503
 
8.1%

Length

2024-04-17T06:14:19.651016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:19.728715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
503
 
8.1%

facilar
Text

MISSING 

Distinct3438
Distinct (%)66.4%
Missing997
Missing (%)16.1%
Memory size48.4 KiB
2024-04-17T06:14:19.985250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1684373
Min length1

Characters and Unicode

Total characters26757
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

Unique2606 ?
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 (3428) 4914
94.9%
2024-04-17T06:14:20.381376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4674
17.5%
. 4551
17.0%
2 2886
10.8%
4 1979
7.4%
8 1973
7.4%
9 1961
7.3%
5 1918
7.2%
3 1911
7.1%
6 1855
 
6.9%
7 1703
 
6.4%
Other values (5) 1346
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22194
82.9%
Other Punctuation 4551
 
17.0%
Other Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4674
21.1%
2 2886
13.0%
4 1979
8.9%
8 1973
8.9%
9 1961
8.8%
5 1918
8.6%
3 1911
8.6%
6 1855
 
8.4%
7 1703
 
7.7%
0 1334
 
6.0%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Other Punctuation
ValueCountFrequency (%)
. 4551
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26745
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4674
17.5%
. 4551
17.0%
2 2886
10.8%
4 1979
7.4%
8 1973
7.4%
9 1961
7.3%
5 1918
7.2%
3 1911
7.1%
6 1855
 
6.9%
7 1703
 
6.4%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26745
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4674
17.5%
. 4551
17.0%
2 2886
10.8%
4 1979
7.4%
8 1973
7.4%
9 1961
7.3%
5 1918
7.2%
3 1911
7.1%
6 1855
 
6.9%
7 1703
 
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 size48.4 KiB
<NA>
5671 
 
503

Length

Max length4
Median length4
Mean length3.7555879
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> 5671
91.9%
503
 
8.1%

Length

2024-04-17T06:14:20.499365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:20.577366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
503
 
8.1%

autochaairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
N
4624 
Y
1387 
<NA>
 
104
 
59

Length

Max length4
Median length1
Mean length1.0505345
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 4624
74.9%
Y 1387
 
22.5%
<NA> 104
 
1.7%
59
 
1.0%

Length

2024-04-17T06:14:20.663476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:20.748891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4624
74.9%
y 1387
 
22.5%
na 104
 
1.7%
59
 
1.0%

prvdgathinnm
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5670 
제공게임물명
 
503
전체이용가
 
1

Length

Max length6
Median length4
Mean length4.1631033
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> 5670
91.8%
제공게임물명 503
 
8.1%
전체이용가 1
 
< 0.1%

Length

2024-04-17T06:14:20.842618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:20.926187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5670
91.8%
제공게임물명 503
 
8.1%
전체이용가 1
 
< 0.1%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
제작취급품목내용
 
503

Length

Max length8
Median length4
Mean length4.3258827
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> 5671
91.9%
제작취급품목내용 503
 
8.1%

Length

2024-04-17T06:14:21.015308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:21.095511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
제작취급품목내용 503
 
8.1%

lghtfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
 
503

Length

Max length4
Median length4
Mean length3.7555879
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> 5671
91.9%
503
 
8.1%

Length

2024-04-17T06:14:21.174718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:21.250847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
503
 
8.1%

lghtfacilinillu
Text

MISSING 

Distinct183
Distinct (%)11.9%
Missing4639
Missing (%)75.1%
Memory size48.4 KiB
2024-04-17T06:14:21.423041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length3.1465798
Min length1

Characters and Unicode

Total characters4830
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
24.0%
조명시설조도 363
23.6%
35 142
 
9.3%
40 127
 
8.3%
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%
2024-04-17T06:14:21.708387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 731
15.1%
726
15.0%
6 450
9.3%
363
7.5%
363
7.5%
363
7.5%
363
7.5%
5 332
6.9%
3 298
6.2%
4 271
 
5.6%
Other values (6) 570
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2594
53.7%
Other Letter 2178
45.1%
Other Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 731
28.2%
6 450
17.3%
5 332
12.8%
3 298
11.5%
4 271
 
10.4%
1 192
 
7.4%
2 107
 
4.1%
7 81
 
3.1%
8 79
 
3.0%
9 53
 
2.0%
Other Letter
ValueCountFrequency (%)
726
33.3%
363
16.7%
363
16.7%
363
16.7%
363
16.7%
Other Punctuation
ValueCountFrequency (%)
. 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2652
54.9%
Hangul 2178
45.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 731
27.6%
6 450
17.0%
5 332
12.5%
3 298
11.2%
4 271
 
10.2%
1 192
 
7.2%
2 107
 
4.0%
7 81
 
3.1%
8 79
 
3.0%
. 58
 
2.2%
Hangul
ValueCountFrequency (%)
726
33.3%
363
16.7%
363
16.7%
363
16.7%
363
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2652
54.9%
Hangul 2178
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 731
27.6%
6 450
17.0%
5 332
12.5%
3 298
11.2%
4 271
 
10.2%
1 192
 
7.2%
2 107
 
4.0%
7 81
 
3.1%
8 79
 
3.0%
. 58
 
2.2%
Hangul
ValueCountFrequency (%)
726
33.3%
363
16.7%
363
16.7%
363
16.7%
363
16.7%

nearenvnm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
4283 
기타
546 
주택가주변
531 
주변환경명
 
369
유흥업소밀집지역
 
262
Other values (4)
 
183

Length

Max length8
Median length4
Mean length4.2309686
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 369
 
6.0%
유흥업소밀집지역 262
 
4.2%
학교정화(상대) 121
 
2.0%
아파트지역 53
 
0.9%
학교정화(절대) 6
 
0.1%
결혼예식장주변 3
 
< 0.1%

Length

2024-04-17T06:14:21.811546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:21.902521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4283
69.4%
기타 546
 
8.8%
주택가주변 531
 
8.6%
주변환경명 369
 
6.0%
유흥업소밀집지역 262
 
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 size48.4 KiB
<NA>
3404 
2
717 
3
514 
5
394 
4
 
314
Other values (17)
831 

Length

Max length4
Median length4
Mean length2.8056365
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3404
55.1%
2 717
 
11.6%
3 514
 
8.3%
5 394
 
6.4%
4 314
 
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

2024-04-17T06:14:22.008352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3404
55.1%
2 717
 
11.6%
3 514
 
8.3%
5 394
 
6.4%
4 314
 
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 size48.4 KiB
<NA>
3997 
일반주거지역
414 
일반상업지역
 
392
준주거지역
 
379
주거지역
 
373
Other values (10)
619 

Length

Max length6
Median length4
Mean length4.4191772
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> 3997
64.7%
일반주거지역 414
 
6.7%
일반상업지역 392
 
6.3%
준주거지역 379
 
6.1%
주거지역 373
 
6.0%
지역구분명 287
 
4.6%
상업지역 138
 
2.2%
근린상업지역 75
 
1.2%
중심상업지역 48
 
0.8%
관리지역 33
 
0.5%
Other values (5) 38
 
0.6%

Length

2024-04-17T06:14:22.107684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3997
64.7%
일반주거지역 414
 
6.7%
일반상업지역 392
 
6.3%
준주거지역 379
 
6.1%
주거지역 373
 
6.0%
지역구분명 287
 
4.6%
상업지역 138
 
2.2%
근린상업지역 75
 
1.2%
중심상업지역 48
 
0.8%
관리지역 33
 
0.5%
Other values (5) 38
 
0.6%

undernumlay
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
3553 
1
1958 
지하층수
373 
2
 
135
0
 
102
Other values (7)
 
53

Length

Max length4
Median length4
Mean length2.9078393
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> 3553
57.5%
1 1958
31.7%
지하층수 373
 
6.0%
2 135
 
2.2%
0 102
 
1.7%
3 34
 
0.6%
6 7
 
0.1%
4 6
 
0.1%
5 3
 
< 0.1%
10 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T06:14:22.208695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3553
57.5%
1 1958
31.7%
지하층수 373
 
6.0%
2 135
 
2.2%
0 102
 
1.7%
3 34
 
0.6%
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 size48.4 KiB
<NA>
3220 
1
601 
2
497 
3
 
239
청소년실수
 
186
Other values (42)
1431 

Length

Max length5
Median length4
Mean length2.8147068
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> 3220
52.2%
1 601
 
9.7%
2 497
 
8.0%
3 239
 
3.9%
청소년실수 186
 
3.0%
0 185
 
3.0%
4 123
 
2.0%
5 95
 
1.5%
20 74
 
1.2%
15 74
 
1.2%
Other values (37) 880
 
14.3%

Length

2024-04-17T06:14:22.309474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3220
52.2%
1 601
 
9.7%
2 497
 
8.0%
3 239
 
3.9%
청소년실수 186
 
3.0%
0 185
 
3.0%
4 123
 
2.0%
5 95
 
1.5%
20 74
 
1.2%
15 74
 
1.2%
Other values (37) 880
 
14.3%

bgroomyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
N
4455 
Y
1653 
<NA>
 
43
 
23

Length

Max length4
Median length1
Mean length1.0208941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 4455
72.2%
Y 1653
 
26.8%
<NA> 43
 
0.7%
23
 
0.4%

Length

2024-04-17T06:14:22.434560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:22.518025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4455
72.2%
y 1653
 
26.8%
na 43
 
0.7%
23
 
0.4%

totgasyscnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
총게임기수
 
503

Length

Max length5
Median length4
Mean length4.0814707
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> 5671
91.9%
총게임기수 503
 
8.1%

Length

2024-04-17T06:14:22.602850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:22.678179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
총게임기수 503
 
8.1%

totnumlay
Categorical

Distinct27
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
3516 
5
561 
3
374 
4
371 
총층수
 
324
Other values (22)
1028 

Length

Max length4
Median length4
Mean length2.8357629
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3516
56.9%
5 561
 
9.1%
3 374
 
6.1%
4 371
 
6.0%
총층수 324
 
5.2%
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

2024-04-17T06:14:22.766161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3516
56.9%
5 561
 
9.1%
3 374
 
6.1%
4 371
 
6.0%
총층수 324
 
5.2%
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 size48.4 KiB
<NA>
5671 
최초등록시점
 
503

Length

Max length6
Median length4
Mean length4.1629414
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> 5671
91.9%
최초등록시점 503
 
8.1%

Length

2024-04-17T06:14:22.876910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:22.964006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
최초등록시점 503
 
8.1%

pasgbreth
Text

MISSING 

Distinct69
Distinct (%)4.5%
Missing4650
Missing (%)75.3%
Memory size48.4 KiB
2024-04-17T06:14:23.112986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.9540682
Min length1

Characters and Unicode

Total characters4502
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 (%)
1.2 482
31.6%
통로너비 395
25.9%
1 240
15.7%
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%
2024-04-17T06:14:23.367316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1123
24.9%
. 797
17.7%
2 577
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 2125
47.2%
Other Letter 1580
35.1%
Other Punctuation 797
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1123
52.8%
2 577
27.2%
5 171
 
8.0%
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 (%)
. 797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2922
64.9%
Hangul 1580
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1123
38.4%
. 797
27.3%
2 577
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 2922
64.9%
Hangul 1580
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1123
38.4%
. 797
27.3%
2 577
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 size48.4 KiB
N
4966 
Y
1013 
<NA>
 
128
 
67

Length

Max length4
Median length1
Mean length1.0621963
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 4966
80.4%
Y 1013
 
16.4%
<NA> 128
 
2.1%
67
 
1.1%

Length

2024-04-17T06:14:23.471539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:23.550681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 4966
80.4%
y 1013
 
16.4%
na 128
 
2.1%
67
 
1.1%

cnvefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
 
503

Length

Max length4
Median length4
Mean length3.7555879
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> 5671
91.9%
503
 
8.1%

Length

2024-04-17T06:14:23.637748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:23.723493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
503
 
8.1%

actlnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
<NA>
5671 
품목명
 
503

Length

Max length4
Median length4
Mean length3.9185293
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> 5671
91.9%
품목명 503
 
8.1%

Length

2024-04-17T06:14:23.826458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:14:23.898614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5671
91.9%
품목명 503
 
8.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.4 KiB
Minimum2021-01-04 20:28:19
Maximum2021-01-04 20:28:20
2024-04-17T06:14:23.960882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:14:24.278947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
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>2021-01-04 20:28:19
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
616461675020000CDFF324205202000000503_09_01_PI2020-12-18 00:23:06.0노래연습장업정나눔노래연습장지번우편번호경상북도 포항시 남구 해도동 63-1937806경상북도 포항시 남구 해동로 23-1, 2층 (해도동)20201216폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중413901.166317108282734.34240963620201216111826업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명4유통관련업노래연습장업비디오재생기명YY115.5Y제공게임물명제작취급품목내용조명시설조도기타지상층수일반상업지역지하층수청소년실수총게임기수총층수최초등록시점통로너비품목명2021-01-04 20:28:20
616561685390000CDFF324205202000000103_09_01_PI2020-12-20 00:23:06.0노래연습장업대남PC&코인노래연습장지번우편번호경상남도 의령군 의령읍 서동리 490-2052150경상남도 의령군 의령읍 의병로 20820201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중314464.587439325202943.36789292220201218141533업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명12유통관련업노래연습장업Y비디오재생기명Y123.4제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수12Y총게임기수총층수최초등록시점통로너비품목명2021-01-04 20:28:20
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>2021-01-04 20:28:20
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>2021-01-04 20:28:20
616861715390000CDFF324205202000000103_09_01_PI2020-12-20 00:23:06.0노래연습장업대남PC&코인노래연습장지번우편번호경상남도 의령군 의령읍 서동리 490-2052150경상남도 의령군 의령읍 의병로 20820201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중314464.587439325202943.36789292220201218141533업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명12유통관련업노래연습장업Y비디오재생기명Y123.4제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수12Y총게임기수총층수최초등록시점통로너비품목명2021-01-04 20:28:20
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>2021-01-04 20:28:20
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>2021-01-04 20:28:20
617161743450000CDFF324205202000000403_09_01_PI2020-12-24 00:23:06.0노래연습장업큐코인노래연습장지번우편번호대구광역시 북구 동천동 897-741423대구광역시 북구 동천로 138-24, 4층 402호 (동천동)20201222폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중340930.639461272554.17507620201222173638업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명15유통관련업노래연습장업Y비디오재생기명YY176.24Y제공게임물명제작취급품목내용40유흥업소밀집지역4중심상업지역지하층수12Y총게임기수5최초등록시점통로너비품목명2021-01-04 20:28:20
617261753370000CDFF324205202000000103_09_01_PI2021-01-01 00:23:05.0노래연습장업하늘 노래연습장지번우편번호부산광역시 연제구 연산동 590-10647551부산광역시 연제구 고분로13번길 43, 3층 (연산동)20201230폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중389861.325719933189580.52333383820201230103102업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명8유통관련업노래연습장업Y비디오재생기명YY225.9제공게임물명제작취급품목내용40주변환경명3지역구분명지하층수청소년실수총게임기수총층수최초등록시점1.2품목명2021-01-04 20:28:20
617361764540000CDFF324205202000000103_09_01_PI2021-01-01 00:23:05.0노래연습장업엔젤스 코인노래연습장 논산점<NA>충청남도 논산시 내동 111932991충청남도 논산시 시민로132번길 36-6, 2층 202호 (내동)20201230<NA><NA><NA><NA>영업/정상영업중209355.161753297739.38963820201230140006<NA><NA>근린생활시설<NA><NA>20유통관련업노래연습장업Y<NA>YY<NA>133.14<NA>Y<NA><NA><NA><NA><NA><NA>일반주거지역320Y<NA>3<NA>1.2Y<NA><NA>2021-01-04 20:28:20