Overview

Dataset statistics

Number of variables56
Number of observations4479
Missing cells13088
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory455.0 B

Variable types

Numeric7
Text9
Categorical39
DateTime1

Alerts

opnsvcid has constant value ""Constant
culwrkrsenm has constant value ""Constant
culphyedcobnm has constant value ""Constant
updategbn is highly imbalanced (75.4%)Imbalance
opnsvcnm is highly imbalanced (71.2%)Imbalance
clgstdt is highly imbalanced (95.6%)Imbalance
clgenddt is highly imbalanced (95.6%)Imbalance
ropnymd is highly imbalanced (91.9%)Imbalance
trdstatenm is highly imbalanced (53.8%)Imbalance
dtlstatenm is highly imbalanced (56.5%)Imbalance
uptaenm is highly imbalanced (91.9%)Imbalance
bdngsrvnm is highly imbalanced (73.6%)Imbalance
perplaformsenm is highly imbalanced (91.9%)Imbalance
bfgameocptectcobnm is highly imbalanced (91.9%)Imbalance
souarfacilyn is highly imbalanced (59.7%)Imbalance
vdoretornm is highly imbalanced (91.9%)Imbalance
emerstairyn is highly imbalanced (65.2%)Imbalance
emexyn is highly imbalanced (68.4%)Imbalance
firefacilyn is highly imbalanced (91.9%)Imbalance
soundfacilyn is highly imbalanced (91.9%)Imbalance
autochaairyn is highly imbalanced (55.5%)Imbalance
prvdgathinnm is highly imbalanced (94.7%)Imbalance
mnfactreartclcn is highly imbalanced (91.9%)Imbalance
lghtfacilyn is highly imbalanced (91.9%)Imbalance
nearenvnm is highly imbalanced (56.1%)Imbalance
jisgnumlay is highly imbalanced (51.4%)Imbalance
regnsenm is highly imbalanced (58.9%)Imbalance
undernumlay is highly imbalanced (63.5%)Imbalance
bgroomcnt is highly imbalanced (57.0%)Imbalance
bgroomyn is highly imbalanced (51.5%)Imbalance
totgasyscnt is highly imbalanced (91.9%)Imbalance
totnumlay is highly imbalanced (51.4%)Imbalance
frstregts is highly imbalanced (91.9%)Imbalance
pasgbreth is highly imbalanced (78.7%)Imbalance
speclghtyn is highly imbalanced (57.3%)Imbalance
cnvefacilyn is highly imbalanced (91.9%)Imbalance
actlnm is highly imbalanced (91.9%)Imbalance
last_load_dttm is highly imbalanced (89.9%)Imbalance
sitepostno has 3013 (67.3%) missing valuesMissing
rdnpostno has 2161 (48.2%) missing valuesMissing
rdnwhladdr has 363 (8.1%) missing valuesMissing
dcbymd has 2553 (57.0%) missing valuesMissing
x has 160 (3.6%) missing valuesMissing
y has 160 (3.6%) missing valuesMissing
facilar has 984 (22.0%) missing valuesMissing
lghtfacilinillu has 3656 (81.6%) missing valuesMissing
skey has unique valuesUnique
facilar has 47 (1.0%) zerosZeros

Reproduction

Analysis started2024-04-16 21:12:55.770202
Analysis finished2024-04-16 21:12:57.242519
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct4479
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2253.5028
Minimum1
Maximum6209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:12:57.296068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile224.9
Q11120.5
median2240
Q33359.5
95-th percentile4255.1
Maximum6209
Range6208
Interquartile range (IQR)2239

Descriptive statistics

Standard deviation1322.1768
Coefficient of variation (CV)0.58672071
Kurtosis-0.93306922
Mean2253.5028
Median Absolute Deviation (MAD)1120
Skewness0.11206145
Sum10093439
Variance1748151.4
MonotonicityNot monotonic
2024-04-17T06:12:57.402839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2992 1
 
< 0.1%
2998 1
 
< 0.1%
2997 1
 
< 0.1%
2996 1
 
< 0.1%
2995 1
 
< 0.1%
2994 1
 
< 0.1%
2993 1
 
< 0.1%
2991 1
 
< 0.1%
3000 1
 
< 0.1%
Other values (4469) 4469
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 (%)
6209 1
< 0.1%
6205 1
< 0.1%
6184 1
< 0.1%
6183 1
< 0.1%
6175 1
< 0.1%
6113 1
< 0.1%
6095 1
< 0.1%
6085 1
< 0.1%
6040 1
< 0.1%
5977 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3330080.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:12:57.508524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13300000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation38123.032
Coefficient of variation (CV)0.011448082
Kurtosis-0.800581
Mean3330080.4
Median Absolute Deviation (MAD)30000
Skewness0.00088190692
Sum1.491543 × 1010
Variance1.4533656 × 109
MonotonicityNot monotonic
2024-04-17T06:12:57.597898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 688
15.4%
3290000 574
12.8%
3300000 461
10.3%
3330000 435
9.7%
3390000 352
7.9%
3320000 338
7.5%
3340000 316
7.1%
3380000 259
 
5.8%
3310000 247
 
5.5%
3370000 235
 
5.2%
Other values (6) 574
12.8%
ValueCountFrequency (%)
3250000 125
 
2.8%
3260000 85
 
1.9%
3270000 77
 
1.7%
3280000 103
 
2.3%
3290000 574
12.8%
3300000 461
10.3%
3310000 247
5.5%
3320000 338
7.5%
3330000 435
9.7%
3340000 316
7.1%
ValueCountFrequency (%)
3400000 132
 
2.9%
3390000 352
7.9%
3380000 259
 
5.8%
3370000 235
 
5.2%
3360000 52
 
1.2%
3350000 688
15.4%
3340000 316
7.1%
3330000 435
9.7%
3320000 338
7.5%
3310000 247
 
5.5%

mgtno
Text

Distinct999
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2024-04-17T06:12:57.758717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters89580
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

Unique339 ?
Unique (%)7.6%

Sample

1st rowCDFF3242052001000002
2nd rowCDFF3242052003000006
3rd rowCDFF3242052003000007
4th rowCDFF3242052003000008
5th rowCDFF3242052004000001
ValueCountFrequency (%)
cdff3242052002000001 16
 
0.4%
cdff3242052017000001 16
 
0.4%
cdff3242052019000001 16
 
0.4%
cdff3242051999000002 15
 
0.3%
cdff3242052002000004 15
 
0.3%
cdff3242052002000005 15
 
0.3%
cdff3242052001000001 15
 
0.3%
cdff3242052014000001 15
 
0.3%
cdff3242052016000001 15
 
0.3%
cdff3242052002000003 15
 
0.3%
Other values (989) 4326
96.6%
2024-04-17T06:12:58.034467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29719
33.2%
2 13413
15.0%
F 8958
 
10.0%
3 5754
 
6.4%
4 5547
 
6.2%
5 5363
 
6.0%
9 4813
 
5.4%
1 4623
 
5.2%
C 4479
 
5.0%
D 4479
 
5.0%
Other values (3) 2432
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71664
80.0%
Uppercase Letter 17916
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29719
41.5%
2 13413
18.7%
3 5754
 
8.0%
4 5547
 
7.7%
5 5363
 
7.5%
9 4813
 
6.7%
1 4623
 
6.5%
7 846
 
1.2%
6 827
 
1.2%
8 759
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
F 8958
50.0%
C 4479
25.0%
D 4479
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71664
80.0%
Latin 17916
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29719
41.5%
2 13413
18.7%
3 5754
 
8.0%
4 5547
 
7.7%
5 5363
 
7.5%
9 4813
 
6.7%
1 4623
 
6.5%
7 846
 
1.2%
6 827
 
1.2%
8 759
 
1.1%
Latin
ValueCountFrequency (%)
F 8958
50.0%
C 4479
25.0%
D 4479
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29719
33.2%
2 13413
15.0%
F 8958
 
10.0%
3 5754
 
6.4%
4 5547
 
6.2%
5 5363
 
6.0%
9 4813
 
5.4%
1 4623
 
5.2%
C 4479
 
5.0%
D 4479
 
5.0%
Other values (3) 2432
 
2.7%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
03_09_01_P
4479 

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 4479
100.0%

Length

2024-04-17T06:12:58.144137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:12:58.218230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_09_01_p 4479
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
I
4296 
U
 
183

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 4296
95.9%
U 183
 
4.1%

Length

2024-04-17T06:12:58.290126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:12:58.366666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4296
95.9%
u 183
 
4.1%
Distinct150
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-17T06:12:58.456078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:12:58.554139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4253 
노래연습장업
 
226

Length

Max length6
Median length4
Mean length4.1009154
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> 4253
95.0%
노래연습장업 226
 
5.0%

Length

2024-04-17T06:12:58.653839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:12:58.749013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4253
95.0%
노래연습장업 226
 
5.0%

bplcnm
Text

Distinct2843
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2024-04-17T06:12:59.135795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length6.7202501
Min length1

Characters and Unicode

Total characters30100
Distinct characters704
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

Unique2147 ?
Unique (%)47.9%

Sample

1st row도레미노래연습장
2nd row호심
3rd row진양
4th row도깨비노래연습장
5th row남포노래연습장
ValueCountFrequency (%)
노래연습장 1050
 
18.3%
궁전노래연습장 34
 
0.6%
동전노래연습장 33
 
0.6%
궁전 31
 
0.5%
코인노래연습장 28
 
0.5%
스타노래연습장 24
 
0.4%
스타 24
 
0.4%
락휴 22
 
0.4%
앵콜 22
 
0.4%
팡팡노래연습장 22
 
0.4%
Other values (2619) 4438
77.5%
2024-04-17T06:12:59.446211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3318
 
11.0%
3294
 
10.9%
3286
 
10.9%
3271
 
10.9%
3240
 
10.8%
1250
 
4.2%
413
 
1.4%
319
 
1.1%
281
 
0.9%
213
 
0.7%
Other values (694) 11215
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28003
93.0%
Space Separator 1250
 
4.2%
Uppercase Letter 473
 
1.6%
Decimal Number 219
 
0.7%
Lowercase Letter 40
 
0.1%
Other Punctuation 35
 
0.1%
Open Punctuation 34
 
0.1%
Close Punctuation 34
 
0.1%
Dash Punctuation 9
 
< 0.1%
Math Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3318
 
11.8%
3294
 
11.8%
3286
 
11.7%
3271
 
11.7%
3240
 
11.6%
413
 
1.5%
319
 
1.1%
281
 
1.0%
213
 
0.8%
205
 
0.7%
Other values (628) 10163
36.3%
Uppercase Letter
ValueCountFrequency (%)
O 56
 
11.8%
K 49
 
10.4%
S 40
 
8.5%
P 36
 
7.6%
B 35
 
7.4%
M 33
 
7.0%
V 22
 
4.7%
I 21
 
4.4%
C 19
 
4.0%
R 19
 
4.0%
Other values (16) 143
30.2%
Lowercase Letter
ValueCountFrequency (%)
o 8
20.0%
e 4
10.0%
i 3
 
7.5%
n 3
 
7.5%
t 3
 
7.5%
h 2
 
5.0%
g 2
 
5.0%
s 2
 
5.0%
d 2
 
5.0%
k 2
 
5.0%
Other values (9) 9
22.5%
Decimal Number
ValueCountFrequency (%)
2 99
45.2%
1 39
 
17.8%
0 32
 
14.6%
3 16
 
7.3%
8 9
 
4.1%
5 8
 
3.7%
7 7
 
3.2%
4 4
 
1.8%
6 4
 
1.8%
9 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 27
77.1%
& 5
 
14.3%
' 2
 
5.7%
% 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1250
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28002
93.0%
Common 1583
 
5.3%
Latin 514
 
1.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3318
 
11.8%
3294
 
11.8%
3286
 
11.7%
3271
 
11.7%
3240
 
11.6%
413
 
1.5%
319
 
1.1%
281
 
1.0%
213
 
0.8%
205
 
0.7%
Other values (627) 10162
36.3%
Latin
ValueCountFrequency (%)
O 56
 
10.9%
K 49
 
9.5%
S 40
 
7.8%
P 36
 
7.0%
B 35
 
6.8%
M 33
 
6.4%
V 22
 
4.3%
I 21
 
4.1%
C 19
 
3.7%
R 19
 
3.7%
Other values (36) 184
35.8%
Common
ValueCountFrequency (%)
1250
79.0%
2 99
 
6.3%
1 39
 
2.5%
( 34
 
2.1%
) 34
 
2.1%
0 32
 
2.0%
. 27
 
1.7%
3 16
 
1.0%
- 9
 
0.6%
8 9
 
0.6%
Other values (10) 34
 
2.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28002
93.0%
ASCII 2096
 
7.0%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3318
 
11.8%
3294
 
11.8%
3286
 
11.7%
3271
 
11.7%
3240
 
11.6%
413
 
1.5%
319
 
1.1%
281
 
1.0%
213
 
0.8%
205
 
0.7%
Other values (627) 10162
36.3%
ASCII
ValueCountFrequency (%)
1250
59.6%
2 99
 
4.7%
O 56
 
2.7%
K 49
 
2.3%
S 40
 
1.9%
1 39
 
1.9%
P 36
 
1.7%
B 35
 
1.7%
( 34
 
1.6%
) 34
 
1.6%
Other values (55) 424
 
20.2%
CJK
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct365
Distinct (%)24.9%
Missing3013
Missing (%)67.3%
Memory size35.1 KiB
2024-04-17T06:12:59.699842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters8796
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 (%)9.5%

Sample

1st row600023
2nd row600046
3rd row600045
4th row600092
5th row600060
ValueCountFrequency (%)
609839 81
 
5.5%
지번우편번호 45
 
3.1%
614847 35
 
2.4%
609848 31
 
2.1%
614846 21
 
1.4%
609843 20
 
1.4%
609837 19
 
1.3%
614853 19
 
1.3%
607833 18
 
1.2%
614845 18
 
1.2%
Other values (355) 1159
79.1%
2024-04-17T06:13:00.057989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1658
18.8%
0 1535
17.5%
8 1419
16.1%
1 1022
11.6%
4 783
8.9%
9 641
 
7.3%
2 454
 
5.2%
3 441
 
5.0%
7 366
 
4.2%
5 207
 
2.4%
Other values (5) 270
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8526
96.9%
Other Letter 270
 
3.1%

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 (%)
90
33.3%
45
16.7%
45
16.7%
45
16.7%
45
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 8526
96.9%
Hangul 270
 
3.1%

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 (%)
90
33.3%
45
16.7%
45
16.7%
45
16.7%
45
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8526
96.9%
Hangul 270
 
3.1%

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 (%)
90
33.3%
45
16.7%
45
16.7%
45
16.7%
45
16.7%
Distinct3862
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2024-04-17T06:13:00.326029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length46
Mean length23.710873
Min length8

Characters and Unicode

Total characters106201
Distinct characters271
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

Unique3339 ?
Unique (%)74.5%

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 4477
23.6%
금정구 688
 
3.6%
부산진구 574
 
3.0%
동래구 459
 
2.4%
해운대구 435
 
2.3%
사상구 352
 
1.9%
북구 338
 
1.8%
사하구 316
 
1.7%
지하1층 262
 
1.4%
수영구 260
 
1.4%
Other values (3970) 10796
56.9%
2024-04-17T06:13:00.740593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18888
17.8%
5438
 
5.1%
5359
 
5.0%
5157
 
4.9%
1 4746
 
4.5%
4718
 
4.4%
4575
 
4.3%
4562
 
4.3%
4480
 
4.2%
4477
 
4.2%
Other values (261) 43801
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60947
57.4%
Decimal Number 21465
 
20.2%
Space Separator 18888
 
17.8%
Dash Punctuation 4299
 
4.0%
Open Punctuation 272
 
0.3%
Close Punctuation 272
 
0.3%
Other Punctuation 32
 
< 0.1%
Uppercase Letter 22
 
< 0.1%
Math Symbol 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5438
 
8.9%
5359
 
8.8%
5157
 
8.5%
4718
 
7.7%
4575
 
7.5%
4562
 
7.5%
4480
 
7.4%
4477
 
7.3%
4355
 
7.1%
954
 
1.6%
Other values (231) 16872
27.7%
Decimal Number
ValueCountFrequency (%)
1 4746
22.1%
2 3138
14.6%
3 2368
11.0%
4 2168
10.1%
5 1822
 
8.5%
6 1570
 
7.3%
0 1568
 
7.3%
7 1375
 
6.4%
8 1374
 
6.4%
9 1336
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 9
40.9%
A 4
18.2%
S 2
 
9.1%
C 2
 
9.1%
D 2
 
9.1%
K 1
 
4.5%
G 1
 
4.5%
N 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 20
62.5%
. 7
 
21.9%
/ 3
 
9.4%
@ 1
 
3.1%
& 1
 
3.1%
Space Separator
ValueCountFrequency (%)
18888
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 272
100.0%
Close Punctuation
ValueCountFrequency (%)
) 272
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60947
57.4%
Common 45230
42.6%
Latin 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5438
 
8.9%
5359
 
8.8%
5157
 
8.5%
4718
 
7.7%
4575
 
7.5%
4562
 
7.5%
4480
 
7.4%
4477
 
7.3%
4355
 
7.1%
954
 
1.6%
Other values (231) 16872
27.7%
Common
ValueCountFrequency (%)
18888
41.8%
1 4746
 
10.5%
- 4299
 
9.5%
2 3138
 
6.9%
3 2368
 
5.2%
4 2168
 
4.8%
5 1822
 
4.0%
6 1570
 
3.5%
0 1568
 
3.5%
7 1375
 
3.0%
Other values (10) 3288
 
7.3%
Latin
ValueCountFrequency (%)
B 9
37.5%
A 4
16.7%
S 2
 
8.3%
C 2
 
8.3%
D 2
 
8.3%
K 1
 
4.2%
1
 
4.2%
G 1
 
4.2%
g 1
 
4.2%
N 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60947
57.4%
ASCII 45253
42.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18888
41.7%
1 4746
 
10.5%
- 4299
 
9.5%
2 3138
 
6.9%
3 2368
 
5.2%
4 2168
 
4.8%
5 1822
 
4.0%
6 1570
 
3.5%
0 1568
 
3.5%
7 1375
 
3.0%
Other values (19) 3311
 
7.3%
Hangul
ValueCountFrequency (%)
5438
 
8.9%
5359
 
8.8%
5157
 
8.5%
4718
 
7.7%
4575
 
7.5%
4562
 
7.5%
4480
 
7.4%
4477
 
7.3%
4355
 
7.1%
954
 
1.6%
Other values (231) 16872
27.7%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Text

MISSING 

Distinct876
Distinct (%)37.8%
Missing2161
Missing (%)48.2%
Memory size35.1 KiB
2024-04-17T06:13:01.027030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1177739
Min length5

Characters and Unicode

Total characters11863
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique432 ?
Unique (%)18.6%

Sample

1st row48964
2nd row48977
3rd row48953
4th row48917
5th row600051
ValueCountFrequency (%)
49431 28
 
1.2%
47865 24
 
1.0%
48106 24
 
1.0%
47736 24
 
1.0%
47006 22
 
0.9%
48953 22
 
0.9%
46576 21
 
0.9%
48280 21
 
0.9%
47551 20
 
0.9%
48095 20
 
0.9%
Other values (866) 2092
90.3%
2024-04-17T06:13:01.412274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2683
22.6%
6 1425
12.0%
8 1412
11.9%
7 1193
10.1%
0 1078
9.1%
9 886
 
7.5%
5 879
 
7.4%
2 837
 
7.1%
1 829
 
7.0%
3 634
 
5.3%
Other values (7) 7
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11856
99.9%
Other Letter 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2683
22.6%
6 1425
12.0%
8 1412
11.9%
7 1193
10.1%
0 1078
9.1%
9 886
 
7.5%
5 879
 
7.4%
2 837
 
7.1%
1 829
 
7.0%
3 634
 
5.3%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 11856
99.9%
Hangul 7
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2683
22.6%
6 1425
12.0%
8 1412
11.9%
7 1193
10.1%
0 1078
9.1%
9 886
 
7.5%
5 879
 
7.4%
2 837
 
7.1%
1 829
 
7.0%
3 634
 
5.3%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11856
99.9%
Hangul 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2683
22.6%
6 1425
12.0%
8 1412
11.9%
7 1193
10.1%
0 1078
9.1%
9 886
 
7.5%
5 879
 
7.4%
2 837
 
7.1%
1 829
 
7.0%
3 634
 
5.3%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

rdnwhladdr
Text

MISSING 

Distinct3779
Distinct (%)91.8%
Missing363
Missing (%)8.1%
Memory size35.1 KiB
2024-04-17T06:13:01.683278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length26.87415
Min length18

Characters and Unicode

Total characters110614
Distinct characters332
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3486 ?
Unique (%)84.7%

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 4116
 
19.0%
금정구 663
 
3.1%
부산진구 527
 
2.4%
동래구 445
 
2.1%
해운대구 422
 
1.9%
지하1층 372
 
1.7%
사상구 333
 
1.5%
북구 257
 
1.2%
수영구 254
 
1.2%
남구 247
 
1.1%
Other values (2382) 14035
64.8%
2024-04-17T06:13:02.064219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19063
 
17.2%
5095
 
4.6%
5037
 
4.6%
5024
 
4.5%
4382
 
4.0%
4286
 
3.9%
4255
 
3.8%
4116
 
3.7%
( 4034
 
3.6%
) 4034
 
3.6%
Other values (322) 51288
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66289
59.9%
Space Separator 19063
 
17.2%
Decimal Number 15521
 
14.0%
Open Punctuation 4034
 
3.6%
Close Punctuation 4034
 
3.6%
Other Punctuation 1044
 
0.9%
Dash Punctuation 610
 
0.6%
Uppercase Letter 12
 
< 0.1%
Math Symbol 6
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5095
 
7.7%
5037
 
7.6%
5024
 
7.6%
4382
 
6.6%
4286
 
6.5%
4255
 
6.4%
4116
 
6.2%
3986
 
6.0%
1882
 
2.8%
1801
 
2.7%
Other values (301) 26425
39.9%
Decimal Number
ValueCountFrequency (%)
1 3444
22.2%
2 2277
14.7%
3 1703
11.0%
4 1382
8.9%
5 1337
 
8.6%
6 1206
 
7.8%
7 1133
 
7.3%
9 1052
 
6.8%
0 1002
 
6.5%
8 985
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
B 6
50.0%
A 3
25.0%
K 2
 
16.7%
S 1
 
8.3%
Space Separator
ValueCountFrequency (%)
19063
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4034
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4034
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1044
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 610
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66289
59.9%
Common 44312
40.1%
Latin 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5095
 
7.7%
5037
 
7.6%
5024
 
7.6%
4382
 
6.6%
4286
 
6.5%
4255
 
6.4%
4116
 
6.2%
3986
 
6.0%
1882
 
2.8%
1801
 
2.7%
Other values (301) 26425
39.9%
Common
ValueCountFrequency (%)
19063
43.0%
( 4034
 
9.1%
) 4034
 
9.1%
1 3444
 
7.8%
2 2277
 
5.1%
3 1703
 
3.8%
4 1382
 
3.1%
5 1337
 
3.0%
6 1206
 
2.7%
7 1133
 
2.6%
Other values (6) 4699
 
10.6%
Latin
ValueCountFrequency (%)
B 6
46.2%
A 3
23.1%
K 2
 
15.4%
1
 
7.7%
S 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66289
59.9%
ASCII 44324
40.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19063
43.0%
( 4034
 
9.1%
) 4034
 
9.1%
1 3444
 
7.8%
2 2277
 
5.1%
3 1703
 
3.8%
4 1382
 
3.1%
5 1337
 
3.0%
6 1206
 
2.7%
7 1133
 
2.6%
Other values (10) 4711
 
10.6%
Hangul
ValueCountFrequency (%)
5095
 
7.7%
5037
 
7.6%
5024
 
7.6%
4382
 
6.6%
4286
 
6.5%
4255
 
6.4%
4116
 
6.2%
3986
 
6.0%
1882
 
2.8%
1801
 
2.7%
Other values (301) 26425
39.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

Distinct2627
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20014907
Minimum19000101
Maximum20210310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:13:02.179207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19000101
5-th percentile19931118
Q119971217
median20010317
Q320031216
95-th percentile20160106
Maximum20210310
Range1210209
Interquartile range (IQR)59999

Descriptive statistics

Standard deviation62679.291
Coefficient of variation (CV)0.0031316304
Kurtosis15.803196
Mean20014907
Median Absolute Deviation (MAD)29996
Skewness0.0026067979
Sum8.9646768 × 1010
Variance3.9286936 × 109
MonotonicityNot monotonic
2024-04-17T06:13:02.301891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021210 66
 
1.5%
20021211 60
 
1.3%
20021205 38
 
0.8%
20021206 26
 
0.6%
19921013 25
 
0.6%
20021207 23
 
0.5%
19990630 20
 
0.4%
19990716 9
 
0.2%
19990702 9
 
0.2%
19930923 7
 
0.2%
Other values (2617) 4196
93.7%
ValueCountFrequency (%)
19000101 1
 
< 0.1%
19920112 1
 
< 0.1%
19920710 1
 
< 0.1%
19920711 2
 
< 0.1%
19920713 7
0.2%
19920905 1
 
< 0.1%
19920907 2
 
< 0.1%
19920917 2
 
< 0.1%
19920919 1
 
< 0.1%
19920926 1
 
< 0.1%
ValueCountFrequency (%)
20210310 1
< 0.1%
20210218 1
< 0.1%
20210115 2
< 0.1%
20201230 1
< 0.1%
20201012 1
< 0.1%
20200917 1
< 0.1%
20200907 1
< 0.1%
20200804 1
< 0.1%
20200625 1
< 0.1%
20200622 1
< 0.1%

dcbymd
Text

MISSING 

Distinct1432
Distinct (%)74.4%
Missing2553
Missing (%)57.0%
Memory size35.1 KiB
2024-04-17T06:13:02.540560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9231568
Min length4

Characters and Unicode

Total characters15260
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

Unique1129 ?
Unique (%)58.6%

Sample

1st row20040901
2nd row20050216
3rd row20071116
4th row20070227
5th row20120207
ValueCountFrequency (%)
폐업일자 37
 
1.9%
20071126 24
 
1.2%
20040317 16
 
0.8%
20081217 9
 
0.5%
20140703 8
 
0.4%
20100219 8
 
0.4%
20151228 7
 
0.4%
20140325 7
 
0.4%
20170530 7
 
0.4%
20000214 7
 
0.4%
Other values (1422) 1796
93.3%
2024-04-17T06:13:02.891092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5243
34.4%
2 3118
20.4%
1 2753
18.0%
3 713
 
4.7%
7 677
 
4.4%
6 590
 
3.9%
5 522
 
3.4%
4 513
 
3.4%
8 501
 
3.3%
9 482
 
3.2%
Other values (4) 148
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15112
99.0%
Other Letter 148
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5243
34.7%
2 3118
20.6%
1 2753
18.2%
3 713
 
4.7%
7 677
 
4.5%
6 590
 
3.9%
5 522
 
3.5%
4 513
 
3.4%
8 501
 
3.3%
9 482
 
3.2%
Other Letter
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15112
99.0%
Hangul 148
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5243
34.7%
2 3118
20.6%
1 2753
18.2%
3 713
 
4.7%
7 677
 
4.5%
6 590
 
3.9%
5 522
 
3.5%
4 513
 
3.4%
8 501
 
3.3%
9 482
 
3.2%
Hangul
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15112
99.0%
Hangul 148
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5243
34.7%
2 3118
20.6%
1 2753
18.2%
3 713
 
4.7%
7 677
 
4.5%
6 590
 
3.9%
5 522
 
3.5%
4 513
 
3.4%
8 501
 
3.3%
9 482
 
3.2%
Hangul
ValueCountFrequency (%)
37
25.0%
37
25.0%
37
25.0%
37
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4432 
휴업시작일자
 
45
20120827
 
1
20091029
 
1

Length

Max length8
Median length4
Mean length4.0218799
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4432
99.0%
휴업시작일자 45
 
1.0%
20120827 1
 
< 0.1%
20091029 1
 
< 0.1%

Length

2024-04-17T06:13:03.007505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:03.094448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4432
99.0%
휴업시작일자 45
 
1.0%
20120827 1
 
< 0.1%
20091029 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4432 
휴업종료일자
 
45
20150824
 
1
20091104
 
1

Length

Max length8
Median length4
Mean length4.0218799
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4432
99.0%
휴업종료일자 45
 
1.0%
20150824 1
 
< 0.1%
20091104 1
 
< 0.1%

Length

2024-04-17T06:13:03.187269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:03.272560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4432
99.0%
휴업종료일자 45
 
1.0%
20150824 1
 
< 0.1%
20091104 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
재개업일자
 
45

Length

Max length5
Median length4
Mean length4.0100469
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> 4434
99.0%
재개업일자 45
 
1.0%

Length

2024-04-17T06:13:03.354986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:03.436884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
재개업일자 45
 
1.0%

trdstatenm
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
13
2240 
03
1728 
영업/정상
 
179
35
 
133
31
 
97
Other values (7)
 
102

Length

Max length14
Median length2
Mean length2.1279303
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 2240
50.0%
03 1728
38.6%
영업/정상 179
 
4.0%
35 133
 
3.0%
31 97
 
2.2%
폐업 44
 
1.0%
30 30
 
0.7%
25 13
 
0.3%
33 10
 
0.2%
취소/말소/만료/정지/중지 3
 
0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T06:13:03.520830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13 2240
50.0%
03 1728
38.6%
영업/정상 179
 
4.0%
35 133
 
3.0%
31 97
 
2.2%
폐업 44
 
1.0%
30 30
 
0.7%
25 13
 
0.3%
33 10
 
0.2%
취소/말소/만료/정지/중지 3
 
0.1%
Other values (2) 2
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
영업중
2419 
폐업
1772 
직권말소
 
135
등록취소
 
98
허가취소
 
30
Other values (4)
 
25

Length

Max length5
Median length3
Mean length2.6684528
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2419
54.0%
폐업 1772
39.6%
직권말소 135
 
3.0%
등록취소 98
 
2.2%
허가취소 30
 
0.7%
영업정지 13
 
0.3%
지정취소 10
 
0.2%
휴업 1
 
< 0.1%
영업장폐쇄 1
 
< 0.1%

Length

2024-04-17T06:13:03.613801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:03.705546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2419
54.0%
폐업 1772
39.6%
직권말소 135
 
3.0%
등록취소 98
 
2.2%
허가취소 30
 
0.7%
영업정지 13
 
0.3%
지정취소 10
 
0.2%
휴업 1
 
< 0.1%
영업장폐쇄 1
 
< 0.1%

x
Real number (ℝ)

MISSING 

Distinct3639
Distinct (%)84.3%
Missing160
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean388541.8
Minimum366871.98
Maximum407056.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:13:03.811855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366871.98
5-th percentile380122.68
Q1384810.51
median389389.83
Q3391502.99
95-th percentile398244.49
Maximum407056.36
Range40184.38
Interquartile range (IQR)6692.4738

Descriptive statistics

Standard deviation5424.9442
Coefficient of variation (CV)0.013962318
Kurtosis0.50203213
Mean388541.8
Median Absolute Deviation (MAD)3088.5822
Skewness0.041740225
Sum1.678112 × 109
Variance29430020
MonotonicityNot monotonic
2024-04-17T06:13:03.922056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
398274.390064 7
 
0.2%
400040.894217 6
 
0.1%
389360.993759525 6
 
0.1%
389728.19289 6
 
0.1%
390213.710876 4
 
0.1%
389721.407882 4
 
0.1%
389696.692089 4
 
0.1%
391433.745629 4
 
0.1%
389950.493773 4
 
0.1%
389937.682201 4
 
0.1%
Other values (3629) 4270
95.3%
(Missing) 160
 
3.6%
ValueCountFrequency (%)
366871.978797 1
 
< 0.1%
366932.944608323 1
 
< 0.1%
367026.301422 1
 
< 0.1%
367102.197209 1
 
< 0.1%
367304.813751 1
 
< 0.1%
367318.0 1
 
< 0.1%
367442.579602 1
 
< 0.1%
367952.521843 1
 
< 0.1%
370628.91266584 1
 
< 0.1%
371173.79944234 3
0.1%
ValueCountFrequency (%)
407056.358343 1
< 0.1%
406982.053033795 1
< 0.1%
405468.503509 1
< 0.1%
404789.464768 1
< 0.1%
404342.989262 1
< 0.1%
403992.731466 1
< 0.1%
403402.552422 1
< 0.1%
403359.895968 1
< 0.1%
403358.775164 1
< 0.1%
403354.407089 1
< 0.1%

y
Real number (ℝ)

MISSING 

Distinct3639
Distinct (%)84.3%
Missing160
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean188732.77
Minimum169966
Maximum207502.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:13:04.031486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169966
5-th percentile179356.06
Q1185676.47
median188527.18
Q3192443.16
95-th percentile197579.83
Maximum207502.68
Range37536.68
Interquartile range (IQR)6766.6808

Descriptive statistics

Standard deviation5479.9087
Coefficient of variation (CV)0.029035279
Kurtosis-0.1554864
Mean188732.77
Median Absolute Deviation (MAD)3538.1191
Skewness-0.10698668
Sum8.1513685 × 108
Variance30029399
MonotonicityNot monotonic
2024-04-17T06:13:04.138660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188234.669067 7
 
0.2%
188878.919838 6
 
0.1%
191580.392783184 6
 
0.1%
199652.82883 6
 
0.1%
196413.484994 4
 
0.1%
199685.898254 4
 
0.1%
199628.375312 4
 
0.1%
193209.184885 4
 
0.1%
189897.709484 4
 
0.1%
189887.816266 4
 
0.1%
Other values (3629) 4270
95.3%
(Missing) 160
 
3.6%
ValueCountFrequency (%)
169966.0 1
< 0.1%
170258.891853 1
< 0.1%
173951.800373379 1
< 0.1%
174116.582659 1
< 0.1%
174218.886733 2
< 0.1%
174239.281871 1
< 0.1%
174245.961147 1
< 0.1%
174251.931196 1
< 0.1%
174255.765265 1
< 0.1%
174262.843299 1
< 0.1%
ValueCountFrequency (%)
207502.680474 1
< 0.1%
206821.489013 1
< 0.1%
206411.480935 1
< 0.1%
206087.0 1
< 0.1%
205909.135145 1
< 0.1%
205677.509518 1
< 0.1%
205412.205917 1
< 0.1%
205366.770002161 1
< 0.1%
205170.989861484 1
< 0.1%
205029.710207 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct4268
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0126395 × 1013
Minimum2.0021018 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:13:04.246018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0040316 × 1013
Q12.0091222 × 1013
median2.0130807 × 1013
Q32.0170314 × 1013
95-th percentile2.0181207 × 1013
Maximum2.0210429 × 1013
Range1.8941108 × 1011
Interquartile range (IQR)7.9092547 × 1010

Descriptive statistics

Standard deviation4.5497656 × 1010
Coefficient of variation (CV)0.0022605964
Kurtosis-0.69735392
Mean2.0126395 × 1013
Median Absolute Deviation (MAD)3.9513968 × 1010
Skewness-0.36914127
Sum9.0146125 × 1016
Variance2.0700367 × 1021
MonotonicityNot monotonic
2024-04-17T06:13:04.378366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030127161348 90
 
2.0%
20180108090959 63
 
1.4%
20021018125445 39
 
0.9%
20190222141604 3
 
0.1%
20180108090340 3
 
0.1%
20191108115420 3
 
0.1%
20200221140721 3
 
0.1%
20200313092650 3
 
0.1%
20190704100853 3
 
0.1%
20210311103343 3
 
0.1%
Other values (4258) 4266
95.2%
ValueCountFrequency (%)
20021018125445 39
0.9%
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 (%)
20210429205922 1
< 0.1%
20210429103049 1
< 0.1%
20210428130720 1
< 0.1%
20210428101447 1
< 0.1%
20210427203645 1
< 0.1%
20210427162838 1
< 0.1%
20210426134702 1
< 0.1%
20210426114551 1
< 0.1%
20210423153613 1
< 0.1%
20210423152213 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
업태구분명
 
45

Length

Max length5
Median length4
Mean length4.0100469
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> 4434
99.0%
업태구분명 45
 
1.0%

Length

2024-04-17T06:13:04.515035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:04.594700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
업태구분명 45
 
1.0%
Distinct52
Distinct (%)1.2%
Missing38
Missing (%)0.8%
Memory size35.1 KiB
2024-04-17T06:13:04.741226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.936951
Min length4

Characters and Unicode

Total characters53012
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)1.1%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 4374
98.5%
전화번호 17
 
0.4%
051)524-0966 1
 
< 0.1%
051-853-0759 1
 
< 0.1%
782-9517 1
 
< 0.1%
704-2111 1
 
< 0.1%
784-0670 1
 
< 0.1%
293-2039 1
 
< 0.1%
201-5591 1
 
< 0.1%
051-317-0711 1
 
< 0.1%
Other values (42) 42
 
0.9%
2024-04-17T06:13:05.023690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13175
24.9%
- 8806
16.6%
3 8789
16.6%
2 8783
16.6%
5 4437
 
8.4%
0 4423
 
8.3%
4 4398
 
8.3%
7 47
 
0.1%
8 35
 
0.1%
9 25
 
< 0.1%
Other values (6) 94
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44135
83.3%
Dash Punctuation 8806
 
16.6%
Other Letter 68
 
0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13175
29.9%
3 8789
19.9%
2 8783
19.9%
5 4437
 
10.1%
0 4423
 
10.0%
4 4398
 
10.0%
7 47
 
0.1%
8 35
 
0.1%
9 25
 
0.1%
6 23
 
0.1%
Other Letter
ValueCountFrequency (%)
17
25.0%
17
25.0%
17
25.0%
17
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 8806
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52944
99.9%
Hangul 68
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13175
24.9%
- 8806
16.6%
3 8789
16.6%
2 8783
16.6%
5 4437
 
8.4%
0 4423
 
8.4%
4 4398
 
8.3%
7 47
 
0.1%
8 35
 
0.1%
9 25
 
< 0.1%
Other values (2) 26
 
< 0.1%
Hangul
ValueCountFrequency (%)
17
25.0%
17
25.0%
17
25.0%
17
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52944
99.9%
Hangul 68
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13175
24.9%
- 8806
16.6%
3 8789
16.6%
2 8783
16.6%
5 4437
 
8.4%
0 4423
 
8.4%
4 4398
 
8.3%
7 47
 
0.1%
8 35
 
0.1%
9 25
 
< 0.1%
Other values (2) 26
 
< 0.1%
Hangul
ValueCountFrequency (%)
17
25.0%
17
25.0%
17
25.0%
17
25.0%

bdngsrvnm
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2988 
근린생활시설
1446 
건물용도명
 
27
문화시설
 
4
사무실
 
3
Other values (9)
 
11

Length

Max length7
Median length4
Mean length4.6514847
Min length2

Unique

Unique7 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2988
66.7%
근린생활시설 1446
32.3%
건물용도명 27
 
0.6%
문화시설 4
 
0.1%
사무실 3
 
0.1%
단독주택 2
 
< 0.1%
기타 2
 
< 0.1%
호텔 1
 
< 0.1%
환경위생시설 1
 
< 0.1%
교육연구시설 1
 
< 0.1%
Other values (4) 4
 
0.1%

Length

2024-04-17T06:13:05.132475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2988
66.7%
근린생활시설 1446
32.3%
건물용도명 27
 
0.6%
문화시설 4
 
0.1%
사무실 3
 
0.1%
단독주택 2
 
< 0.1%
기타 2
 
< 0.1%
호텔 1
 
< 0.1%
환경위생시설 1
 
< 0.1%
교육연구시설 1
 
< 0.1%
Other values (4) 4
 
0.1%

perplaformsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
공연장형태구분명
 
45

Length

Max length8
Median length4
Mean length4.0401875
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> 4434
99.0%
공연장형태구분명 45
 
1.0%

Length

2024-04-17T06:13:05.225747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:05.306787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
공연장형태구분명 45
 
1.0%

bfgameocptectcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
기존게임업외업종명
 
45

Length

Max length9
Median length4
Mean length4.0502344
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> 4434
99.0%
기존게임업외업종명 45
 
1.0%

Length

2024-04-17T06:13:05.382845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:05.458050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
기존게임업외업종명 45
 
1.0%

noroomcnt
Categorical

Distinct44
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
1416 
5
548 
6
469 
4
416 
7
398 
Other values (39)
1232 

Length

Max length5
Median length1
Mean length2.0814914
Min length1

Unique

Unique8 ?
Unique (%)0.2%

Sample

1st row3
2nd row3
3rd row5
4th row5
5th row9

Common Values

ValueCountFrequency (%)
<NA> 1416
31.6%
5 548
 
12.2%
6 469
 
10.5%
4 416
 
9.3%
7 398
 
8.9%
8 307
 
6.9%
9 184
 
4.1%
10 128
 
2.9%
3 100
 
2.2%
11 82
 
1.8%
Other values (34) 431
 
9.6%

Length

2024-04-17T06:13:05.543297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1416
31.6%
5 548
 
12.2%
6 469
 
10.5%
4 416
 
9.3%
7 398
 
8.9%
8 307
 
6.9%
9 184
 
4.1%
10 128
 
2.9%
3 100
 
2.2%
11 82
 
1.8%
Other values (34) 431
 
9.6%

culwrkrsenm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
유통관련업
4479 

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 4479
100.0%

Length

2024-04-17T06:13:05.637626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:05.707989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 4479
100.0%

culphyedcobnm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
노래연습장업
4479 

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 4479
100.0%

Length

2024-04-17T06:13:05.780973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:05.852303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장업 4479
100.0%

souarfacilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3577 
Y
844 
<NA>
 
41
 
17

Length

Max length4
Median length1
Mean length1.0274615
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3577
79.9%
Y 844
 
18.8%
<NA> 41
 
0.9%
17
 
0.4%

Length

2024-04-17T06:13:05.927975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:06.009800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3577
79.9%
y 844
 
18.8%
na 41
 
0.9%
17
 
0.4%

vdoretornm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
비디오재생기명
 
45

Length

Max length7
Median length4
Mean length4.0301407
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> 4434
99.0%
비디오재생기명 45
 
1.0%

Length

2024-04-17T06:13:06.095400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:06.171479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
비디오재생기명 45
 
1.0%

emerstairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3792 
Y
627 
<NA>
 
43
 
17

Length

Max length4
Median length1
Mean length1.0288011
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3792
84.7%
Y 627
 
14.0%
<NA> 43
 
1.0%
17
 
0.4%

Length

2024-04-17T06:13:06.509821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:06.594170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3792
84.7%
y 627
 
14.0%
na 43
 
1.0%
17
 
0.4%

emexyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3894 
Y
527 
<NA>
 
41
 
17

Length

Max length4
Median length1
Mean length1.0274615
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3894
86.9%
Y 527
 
11.8%
<NA> 41
 
0.9%
17
 
0.4%

Length

2024-04-17T06:13:06.694489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:06.775798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3894
86.9%
y 527
 
11.8%
na 41
 
0.9%
17
 
0.4%

firefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
 
45

Length

Max length4
Median length4
Mean length3.9698593
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> 4434
99.0%
45
 
1.0%

Length

2024-04-17T06:13:06.871989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:06.947668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
45
 
1.0%

facilar
Real number (ℝ)

MISSING  ZEROS 

Distinct2594
Distinct (%)74.2%
Missing984
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean148.34767
Minimum0
Maximum1645.35
Zeros47
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-04-17T06:13:07.045872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile66
Q1100.91
median132.12
Q3176.13
95-th percentile282.017
Maximum1645.35
Range1645.35
Interquartile range (IQR)75.22

Descriptive statistics

Standard deviation79.385891
Coefficient of variation (CV)0.53513408
Kurtosis44.772301
Mean148.34767
Median Absolute Deviation (MAD)34.07
Skewness3.8552606
Sum518475.09
Variance6302.1196
MonotonicityNot monotonic
2024-04-17T06:13:07.167254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 47
 
1.0%
99.0 46
 
1.0%
82.5 25
 
0.6%
132.0 24
 
0.5%
165.0 20
 
0.4%
125.4 16
 
0.4%
92.4 16
 
0.4%
115.5 15
 
0.3%
66.0 14
 
0.3%
122.1 14
 
0.3%
Other values (2584) 3258
72.7%
(Missing) 984
 
22.0%
ValueCountFrequency (%)
0.0 47
1.0%
1.2 1
 
< 0.1%
11.05 1
 
< 0.1%
14.4 1
 
< 0.1%
17.48 1
 
< 0.1%
26.0 1
 
< 0.1%
26.5 1
 
< 0.1%
33.06 1
 
< 0.1%
34.6 1
 
< 0.1%
36.16 1
 
< 0.1%
ValueCountFrequency (%)
1645.35 1
 
< 0.1%
781.54 1
 
< 0.1%
760.22 4
0.1%
717.37 1
 
< 0.1%
687.61 1
 
< 0.1%
630.0 1
 
< 0.1%
626.76 1
 
< 0.1%
621.36 1
 
< 0.1%
612.86 1
 
< 0.1%
559.41 1
 
< 0.1%

soundfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
 
45

Length

Max length4
Median length4
Mean length3.9698593
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> 4434
99.0%
45
 
1.0%

Length

2024-04-17T06:13:07.268035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:07.344756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
45
 
1.0%

autochaairyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3399 
Y
1013 
<NA>
 
48
 
19

Length

Max length4
Median length1
Mean length1.03215
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3399
75.9%
Y 1013
 
22.6%
<NA> 48
 
1.1%
19
 
0.4%

Length

2024-04-17T06:13:07.425747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:07.509185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3399
75.9%
y 1013
 
22.6%
na 48
 
1.1%
19
 
0.4%

prvdgathinnm
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4433 
제공게임물명
 
45
전체이용가
 
1

Length

Max length6
Median length4
Mean length4.020317
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> 4433
99.0%
제공게임물명 45
 
1.0%
전체이용가 1
 
< 0.1%

Length

2024-04-17T06:13:07.610156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:07.705528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4433
99.0%
제공게임물명 45
 
1.0%
전체이용가 1
 
< 0.1%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
제작취급품목내용
 
45

Length

Max length8
Median length4
Mean length4.0401875
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> 4434
99.0%
제작취급품목내용 45
 
1.0%

Length

2024-04-17T06:13:07.820578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:07.906733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
제작취급품목내용 45
 
1.0%

lghtfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
 
45

Length

Max length4
Median length4
Mean length3.9698593
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> 4434
99.0%
45
 
1.0%

Length

2024-04-17T06:13:07.986907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:08.063384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
45
 
1.0%

lghtfacilinillu
Text

MISSING 

Distinct97
Distinct (%)11.8%
Missing3656
Missing (%)81.6%
Memory size35.1 KiB
2024-04-17T06:13:08.220430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2685298
Min length2

Characters and Unicode

Total characters1867
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

Unique57 ?
Unique (%)6.9%

Sample

1st row40
2nd row44
3rd row38
4th row80
5th row45
ValueCountFrequency (%)
60 352
42.8%
35 141
17.1%
40 47
 
5.7%
30 40
 
4.9%
조명시설조도 34
 
4.1%
50 22
 
2.7%
100 12
 
1.5%
45 11
 
1.3%
48 8
 
1.0%
80 8
 
1.0%
Other values (87) 148
18.0%
2024-04-17T06:13:08.518501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 520
27.9%
6 376
20.1%
5 230
12.3%
3 206
 
11.0%
4 112
 
6.0%
68
 
3.6%
1 68
 
3.6%
7 40
 
2.1%
8 37
 
2.0%
2 37
 
2.0%
Other values (6) 173
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1651
88.4%
Other Letter 204
 
10.9%
Other Punctuation 12
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 520
31.5%
6 376
22.8%
5 230
13.9%
3 206
 
12.5%
4 112
 
6.8%
1 68
 
4.1%
7 40
 
2.4%
8 37
 
2.2%
2 37
 
2.2%
9 25
 
1.5%
Other Letter
ValueCountFrequency (%)
68
33.3%
34
16.7%
34
16.7%
34
16.7%
34
16.7%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1663
89.1%
Hangul 204
 
10.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 520
31.3%
6 376
22.6%
5 230
13.8%
3 206
 
12.4%
4 112
 
6.7%
1 68
 
4.1%
7 40
 
2.4%
8 37
 
2.2%
2 37
 
2.2%
9 25
 
1.5%
Hangul
ValueCountFrequency (%)
68
33.3%
34
16.7%
34
16.7%
34
16.7%
34
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1663
89.1%
Hangul 204
 
10.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 520
31.3%
6 376
22.6%
5 230
13.8%
3 206
 
12.4%
4 112
 
6.7%
1 68
 
4.1%
7 40
 
2.4%
8 37
 
2.2%
2 37
 
2.2%
9 25
 
1.5%
Hangul
ValueCountFrequency (%)
68
33.3%
34
16.7%
34
16.7%
34
16.7%
34
16.7%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3371 
주택가주변
500 
기타
 
265
유흥업소밀집지역
 
190
학교정화(상대)
 
76
Other values (3)
 
77

Length

Max length8
Median length4
Mean length4.2487162
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3371
75.3%
주택가주변 500
 
11.2%
기타 265
 
5.9%
유흥업소밀집지역 190
 
4.2%
학교정화(상대) 76
 
1.7%
주변환경명 42
 
0.9%
아파트지역 34
 
0.8%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T06:13:08.629283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:08.736439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3371
75.3%
주택가주변 500
 
11.2%
기타 265
 
5.9%
유흥업소밀집지역 190
 
4.2%
학교정화(상대 76
 
1.7%
주변환경명 42
 
0.9%
아파트지역 34
 
0.8%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2656 
2
505 
3
395 
5
327 
4
 
213
Other values (17)
383 

Length

Max length4
Median length4
Mean length2.8046439
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2656
59.3%
2 505
 
11.3%
3 395
 
8.8%
5 327
 
7.3%
4 213
 
4.8%
6 81
 
1.8%
1 79
 
1.8%
0 56
 
1.3%
8 41
 
0.9%
7 40
 
0.9%
Other values (12) 86
 
1.9%

Length

2024-04-17T06:13:08.841332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2656
59.3%
2 505
 
11.3%
3 395
 
8.8%
5 327
 
7.3%
4 213
 
4.8%
6 81
 
1.8%
1 79
 
1.8%
0 56
 
1.3%
8 41
 
0.9%
7 40
 
0.9%
Other values (12) 86
 
1.9%

regnsenm
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3276 
주거지역
358 
준주거지역
 
277
일반주거지역
 
213
일반상업지역
 
169
Other values (8)
 
186

Length

Max length6
Median length4
Mean length4.2592096
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> 3276
73.1%
주거지역 358
 
8.0%
준주거지역 277
 
6.2%
일반주거지역 213
 
4.8%
일반상업지역 169
 
3.8%
상업지역 108
 
2.4%
지역구분명 35
 
0.8%
근린상업지역 26
 
0.6%
자연녹지지역 10
 
0.2%
중심상업지역 4
 
0.1%
Other values (3) 3
 
0.1%

Length

2024-04-17T06:13:08.944347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3276
73.1%
주거지역 358
 
8.0%
준주거지역 277
 
6.2%
일반주거지역 213
 
4.8%
일반상업지역 169
 
3.8%
상업지역 108
 
2.4%
지역구분명 35
 
0.8%
근린상업지역 26
 
0.6%
자연녹지지역 10
 
0.2%
중심상업지역 4
 
0.1%
Other values (3) 3
 
0.1%

undernumlay
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2614 
1
1674 
2
 
73
0
 
69
지하층수
 
30
Other values (6)
 
19

Length

Max length4
Median length4
Mean length2.7711543
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> 2614
58.4%
1 1674
37.4%
2 73
 
1.6%
0 69
 
1.5%
지하층수 30
 
0.7%
3 11
 
0.2%
5 3
 
0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%

Length

2024-04-17T06:13:09.045182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2614
58.4%
1 1674
37.4%
2 73
 
1.6%
0 69
 
1.5%
지하층수 30
 
0.7%
3 11
 
0.2%
5 3
 
0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%

bgroomcnt
Categorical

IMBALANCE 

Distinct43
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2741 
1
476 
2
432 
3
 
190
4
 
86
Other values (38)
554 

Length

Max length5
Median length4
Mean length2.9118107
Min length1

Unique

Unique7 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2741
61.2%
1 476
 
10.6%
2 432
 
9.6%
3 190
 
4.2%
4 86
 
1.9%
0 71
 
1.6%
5 51
 
1.1%
7 48
 
1.1%
8 44
 
1.0%
10 37
 
0.8%
Other values (33) 303
 
6.8%

Length

2024-04-17T06:13:09.145251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2741
61.2%
1 476
 
10.6%
2 432
 
9.6%
3 190
 
4.2%
4 86
 
1.9%
0 71
 
1.6%
5 51
 
1.1%
7 48
 
1.1%
8 44
 
1.0%
10 37
 
0.8%
Other values (33) 303
 
6.8%

bgroomyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3130 
Y
1293 
<NA>
 
36
 
20

Length

Max length4
Median length1
Mean length1.0241125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3130
69.9%
Y 1293
28.9%
<NA> 36
 
0.8%
20
 
0.4%

Length

2024-04-17T06:13:09.244043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:09.328923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3130
69.9%
y 1293
28.9%
na 36
 
0.8%
20
 
0.4%

totgasyscnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
총게임기수
 
45

Length

Max length5
Median length4
Mean length4.0100469
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> 4434
99.0%
총게임기수 45
 
1.0%

Length

2024-04-17T06:13:09.410738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:09.512130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
총게임기수 45
 
1.0%

totnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2684 
5
493 
3
279 
4
 
251
6
 
177
Other values (21)
595 

Length

Max length4
Median length4
Mean length2.8327752
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2684
59.9%
5 493
 
11.0%
3 279
 
6.2%
4 251
 
5.6%
6 177
 
4.0%
1 161
 
3.6%
2 77
 
1.7%
7 72
 
1.6%
0 57
 
1.3%
8 54
 
1.2%
Other values (16) 174
 
3.9%

Length

2024-04-17T06:13:09.598480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2684
59.9%
5 493
 
11.0%
3 279
 
6.2%
4 251
 
5.6%
6 177
 
4.0%
1 161
 
3.6%
2 77
 
1.7%
7 72
 
1.6%
0 57
 
1.3%
8 54
 
1.2%
Other values (16) 174
 
3.9%

frstregts
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
최초등록시점
 
45

Length

Max length6
Median length4
Mean length4.0200938
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> 4434
99.0%
최초등록시점 45
 
1.0%

Length

2024-04-17T06:13:09.699359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:09.794418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
최초등록시점 45
 
1.0%

pasgbreth
Categorical

IMBALANCE 

Distinct46
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3635 
1.2
414 
1
 
212
1.5
 
56
통로너비
 
35
Other values (41)
 
127

Length

Max length4
Median length4
Mean length3.7240455
Min length1

Unique

Unique23 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3635
81.2%
1.2 414
 
9.2%
1 212
 
4.7%
1.5 56
 
1.3%
통로너비 35
 
0.8%
1.3 22
 
0.5%
1.6 20
 
0.4%
1.4 17
 
0.4%
2 6
 
0.1%
1.1 5
 
0.1%
Other values (36) 57
 
1.3%

Length

2024-04-17T06:13:09.902480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3635
81.2%
1.2 414
 
9.2%
1 212
 
4.7%
1.5 56
 
1.3%
통로너비 35
 
0.8%
1.3 22
 
0.5%
1.6 20
 
0.4%
1.4 17
 
0.4%
2 6
 
0.1%
1.1 5
 
0.1%
Other values (36) 57
 
1.3%

speclghtyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
N
3502 
Y
904 
<NA>
 
53
 
20

Length

Max length4
Median length1
Mean length1.035499
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 3502
78.2%
Y 904
 
20.2%
<NA> 53
 
1.2%
20
 
0.4%

Length

2024-04-17T06:13:10.018046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:10.109833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 3502
78.2%
y 904
 
20.2%
na 53
 
1.2%
20
 
0.4%

cnvefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
 
45

Length

Max length4
Median length4
Mean length3.9698593
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> 4434
99.0%
45
 
1.0%

Length

2024-04-17T06:13:10.196134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:10.271449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
45
 
1.0%

actlnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4434 
품목명
 
45

Length

Max length4
Median length4
Mean length3.9899531
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> 4434
99.0%
품목명 45
 
1.0%

Length

2024-04-17T06:13:10.350533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:10.424205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4434
99.0%
품목명 45
 
1.0%

last_load_dttm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2021-05-01 05:15:03
4420 
2021-05-01 05:15:04
 
59

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01 05:15:03
2nd row2021-05-01 05:15:03
3rd row2021-05-01 05:15:03
4th row2021-05-01 05:15:03
5th row2021-05-01 05:15:03

Common Values

ValueCountFrequency (%)
2021-05-01 05:15:03 4420
98.7%
2021-05-01 05:15:04 59
 
1.3%

Length

2024-04-17T06:13:10.500581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:13:10.579619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 4479
50.0%
05:15:03 4420
49.3%
05:15:04 59
 
0.7%

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>13영업중384596.826401180453.4854820141107112320<NA>051-123-1234근린생활시설<NA><NA>3유통관련업노래연습장업N<NA>NN<NA>80.0<NA>N<NA><NA><NA><NA><NA>2<NA><NA><NA>N<NA>4<NA><NA>N<NA><NA>2021-05-01 05:15:03
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>03폐업385501.481869180233.23297120040901144719<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>2021-05-01 05:15:03
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>2021-05-01 05:15:03
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>13영업중384754.709218180131.91871220170314174221<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>2021-05-01 05:15:03
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>13영업중385220.72387179923.53241620120720110231<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>2021-05-01 05:15:03
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>30허가취소384971.190995179770.98985220051118121659<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>2021-05-01 05:15:03
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>03폐업385198.600185180287.48839520071116142528<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>2021-05-01 05:15:03
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>03폐업385094.073829180302.16355820070227174949<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>2021-05-01 05:15:03
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>13영업중385130.565493181318.91374620170206111033<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>2021-05-01 05:15:03
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>35직권말소385175.335201180057.55882620120504141048<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>2021-05-01 05:15:03
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446959773380000CDFF324205202000000103_09_01_PU2021-01-17 02:40:00.0노래연습장업락휴코인노래연습장 광안비치점<NA>부산광역시 수영구 광안동 203-18 광안동 AK빌딩48303부산광역시 수영구 남천바다로 31-1, 광안동 AK빌딩 1~2층 (광안동)20200625<NA><NA><NA><NA>영업/정상영업중392578.296641185333.16535520210115104709<NA><NA><NA><NA><NA>19유통관련업노래연습장업<NA><NA><NA><NA><NA>166.62<NA><NA><NA><NA><NA>175.8<NA><NA><NA><NA>19Y<NA><NA><NA><NA><NA><NA><NA>2021-05-01 05:15:04
447060403360000CDFF324205202000000103_09_01_PI2020-08-06 00:23:14.0노래연습장업전대장 노래연습장지번우편번호부산광역시 강서구 신호동 317-21 나은빌딩46760부산광역시 강서구 신호산단1로72번길 11, 나은빌딩 4층 401, 402호 (신호동)20200804폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중370628.912666177548.09171320200804182906업태구분명051-123-1234건물용도명공연장형태구분명기존게임업외업종명6유통관련업노래연습장업N비디오재생기명NN232.94N제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수N총게임기수총층수최초등록시점통로너비N품목명2021-05-01 05:15:04
447160853290000CDFF324205202000000203_09_01_PI2020-09-09 00:23:12.0노래연습장업OX COIN 노래연습장 부전동점지번우편번호부산광역시 부산진구 부전동 394-16 201~202호47253부산광역시 부산진구 새싹로 30, 201~202호 (부전동, 경동파크타워)20200907폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387381.306373186540.20508520200907183442업태구분명051-123-1234근린생활시설공연장형태구분명기존게임업외업종명15유통관련업노래연습장업N비디오재생기명NN115.65N제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수15N총게임기수총층수최초등록시점통로너비N품목명2021-05-01 05:15:04
447260953290000CDFF324205202000000303_09_01_PI2020-09-19 00:23:12.0노래연습장업Angel's 코인노래연습장지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워 903호47296부산광역시 부산진구 중앙대로 672, 삼정타워 903호 (부전동)20200917폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820200917102830업태구분명051-123-1234건물용도명공연장형태구분명기존게임업외업종명30유통관련업노래연습장업N비디오재생기명NN254.51N제공게임물명제작취급품목내용41주변환경명지상층수일반상업지역지하층수30N총게임기수총층수최초등록시점통로너비N품목명2021-05-01 05:15:04
447361133320000CDFF324205202000000103_09_01_PI2020-10-14 00:23:10.0노래연습장업오엑스 코인노래연습장 금곡점<NA>부산광역시 북구 금곡동 72-3 라현빌딩46505부산광역시 북구 금곡대로638번길 9-7, 라현빌딩 5층 (금곡동)20201012<NA><NA><NA><NA>영업/정상영업중383380.662691197972.56341720201012171611<NA><NA>근린생활시설<NA><NA>10유통관련업노래연습장업Y<NA>YY<NA>82.6<NA><NA><NA><NA><NA>56<NA><NA><NA><NA>10Y<NA><NA><NA><NA><NA><NA><NA>2021-05-01 05:15:04
447461753370000CDFF324205202000000103_09_01_PU2021-03-18 02:40:00.0노래연습장업하늘 노래연습장지번우편번호부산광역시 연제구 연산동 619-3 대원빌딩47551부산광역시 연제구 고분로13번길 42, 대원빌딩 3층 (연산동)20201230폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중389861.32572189580.52333420210316161418업태구분명전화번호근린생활시설공연장형태구분명기존게임업외업종명8유통관련업노래연습장업Y비디오재생기명YY225.9제공게임물명제작취급품목내용40주변환경명3지역구분명지하층수청소년실수총게임기수총층수최초등록시점1.2품목명2021-05-01 05:15:04
447561833380000CDFF324205202100000103_09_01_PI2021-01-17 00:23:04.0노래연습장업오엑스 코인노래연습장 수영교차로점지번우편번호부산광역시 수영구 광안동 1059-25 세은빌딩48242부산광역시 수영구 연수로 386, 2층 (광안동)20210115폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392319.421408187620.90260920210115104635업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명10유통관련업노래연습장업비디오재생기명84.24제공게임물명제작취급품목내용1076주변환경명지상층수지역구분명지하층수10Y총게임기수총층수최초등록시점통로너비품목명2021-05-01 05:15:04
447661843380000CDFF324205202100000103_09_01_PI2021-01-17 00:23:04.0노래연습장업오엑스 코인노래연습장 수영교차로점지번우편번호부산광역시 수영구 광안동 1059-25 세은빌딩48242부산광역시 수영구 연수로 386, 2층 (광안동)20210115폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392319.421408187620.90260920210115104635업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명10유통관련업노래연습장업비디오재생기명84.24제공게임물명제작취급품목내용1076주변환경명지상층수지역구분명지하층수10Y총게임기수총층수최초등록시점통로너비품목명2021-05-01 05:15:04
447762093380000CDFF324205202100000203_09_01_PI2021-03-13 00:23:00.0노래연습장업커플라운지 노래연습장지번우편번호부산광역시 수영구 민락동 179-11 테마타워 701호48284부산광역시 수영구 광안해변로 237, 테마타워 701호 (민락동)20210310폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393101.663018186009.73323420210311172640업태구분명051-757-9448건물용도명공연장형태구분명기존게임업외업종명6유통관련업노래연습장업비디오재생기명158.49제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수6Y총게임기수총층수최초등록시점통로너비품목명2021-05-01 05:15:04
447862053330000CDFF324205202100000103_09_01_PI2021-02-20 00:23:02.0노래연습장업백프로(100%) 노래연습장지번우편번호부산광역시 해운대구 좌동 1465-1 5층48106부산광역시 해운대구 세실로69번길 11, 5층 (좌동)20210218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중398186.779312187949.89754320210218161715업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명5유통관련업노래연습장업비디오재생기명203.65제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수최초등록시점통로너비품목명2021-05-01 05:15:04