Overview

Dataset statistics

Number of variables47
Number of observations4921
Missing cells7366
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 MiB
Average record size in memory382.0 B

Variable types

Numeric6
Text7
Categorical30
DateTime2
Boolean2

Alerts

opnsvcid has constant value ""Constant
multusnupsoyn has constant value ""Constant
balhansilyn has constant value ""Constant
last_load_dttm has constant value ""Constant
updategbn is highly imbalanced (69.5%)Imbalance
opnsvcnm is highly imbalanced (62.4%)Imbalance
clgstdt is highly imbalanced (93.6%)Imbalance
clgenddt is highly imbalanced (93.6%)Imbalance
ropnymd is highly imbalanced (93.6%)Imbalance
trdstatenm is highly imbalanced (52.5%)Imbalance
uptaenm is highly imbalanced (94.3%)Imbalance
sitetel is highly imbalanced (96.2%)Imbalance
bdngownsenm is highly imbalanced (61.3%)Imbalance
bdngunderflrcnt is highly imbalanced (53.3%)Imbalance
maneipcnt is highly imbalanced (81.4%)Imbalance
useunderendflr is highly imbalanced (60.6%)Imbalance
useunderstflr is highly imbalanced (51.4%)Imbalance
yangsilcnt is highly imbalanced (50.1%)Imbalance
wmeipcnt is highly imbalanced (79.5%)Imbalance
yoksilcnt is highly imbalanced (50.1%)Imbalance
sntuptaenm is highly imbalanced (94.3%)Imbalance
cndpermstymd is highly imbalanced (96.5%)Imbalance
cndpermntwhy is highly imbalanced (95.8%)Imbalance
cndpermendymd is highly imbalanced (96.5%)Imbalance
abedcnt is highly imbalanced (69.6%)Imbalance
rdnpostno has 2660 (54.1%) missing valuesMissing
rdnwhladdr has 2604 (52.9%) missing valuesMissing
dcbymd has 1447 (29.4%) missing valuesMissing
x has 314 (6.4%) missing valuesMissing
y has 314 (6.4%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -27.02724059)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:46:11.406130
Analysis finished2024-04-17 01:46:12.989456
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct4921
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2504.2969
Minimum1
Maximum7075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:13.043829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247
Q11231
median2461
Q33691
95-th percentile4675
Maximum7075
Range7074
Interquartile range (IQR)2460

Descriptive statistics

Standard deviation1512.2391
Coefficient of variation (CV)0.60385777
Kurtosis-0.53538157
Mean2504.2969
Median Absolute Deviation (MAD)1230
Skewness0.2910144
Sum12323645
Variance2286867.2
MonotonicityNot monotonic
2024-04-17T10:46:13.150504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
3278 1
 
< 0.1%
3285 1
 
< 0.1%
3284 1
 
< 0.1%
3283 1
 
< 0.1%
3282 1
 
< 0.1%
3281 1
 
< 0.1%
3280 1
 
< 0.1%
3279 1
 
< 0.1%
3277 1
 
< 0.1%
Other values (4911) 4911
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 (%)
7075 1
< 0.1%
7072 1
< 0.1%
7040 1
< 0.1%
7021 1
< 0.1%
7017 1
< 0.1%
7016 1
< 0.1%
7013 1
< 0.1%
7010 1
< 0.1%
6996 1
< 0.1%
6993 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324478.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:13.259021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40374.487
Coefficient of variation (CV)0.012144607
Kurtosis-0.94033682
Mean3324478.8
Median Absolute Deviation (MAD)30000
Skewness0.061591459
Sum1.635976 × 1010
Variance1.6300992 × 109
MonotonicityNot monotonic
2024-04-17T10:46:13.351760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 510
10.4%
3340000 503
10.2%
3300000 417
 
8.5%
3320000 410
 
8.3%
3330000 392
 
8.0%
3350000 378
 
7.7%
3390000 336
 
6.8%
3370000 328
 
6.7%
3310000 322
 
6.5%
3380000 282
 
5.7%
Other values (6) 1043
21.2%
ValueCountFrequency (%)
3250000 165
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 210
4.3%
3290000 510
10.4%
3300000 417
8.5%
3310000 322
6.5%
3320000 410
8.3%
3330000 392
8.0%
3340000 503
10.2%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 336
6.8%
3380000 282
5.7%
3370000 328
6.7%
3360000 88
 
1.8%
3350000 378
7.7%
3340000 503
10.2%
3330000 392
8.0%
3320000 410
8.3%
3310000 322
6.5%

mgtno
Text

Distinct4885
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-17T10:46:13.527403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108262
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4864 ?
Unique (%)98.8%

Sample

1st row3250000-203-1980-00478
2nd row3250000-203-2005-00004
3rd row3250000-203-2005-00005
4th row3250000-203-1972-00443
5th row3250000-203-2005-00001
ValueCountFrequency (%)
3320000-203-2019-00001 3
 
0.1%
3330000-203-2019-00002 3
 
0.1%
3260000-203-2019-00003 3
 
0.1%
3290000-203-2020-00004 3
 
0.1%
3390000-203-2019-00006 3
 
0.1%
3290000-203-2020-00002 3
 
0.1%
3290000-203-2019-00003 3
 
0.1%
3320000-203-2018-00006 3
 
0.1%
3390000-203-2017-00003 3
 
0.1%
3280000-203-2018-00003 3
 
0.1%
Other values (4875) 4891
99.4%
2024-04-17T10:46:13.792471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43252
40.0%
3 15454
 
14.3%
- 14763
 
13.6%
2 10882
 
10.1%
1 6163
 
5.7%
9 6046
 
5.6%
8 2662
 
2.5%
7 2440
 
2.3%
4 2334
 
2.2%
6 2136
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93499
86.4%
Dash Punctuation 14763
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43252
46.3%
3 15454
 
16.5%
2 10882
 
11.6%
1 6163
 
6.6%
9 6046
 
6.5%
8 2662
 
2.8%
7 2440
 
2.6%
4 2334
 
2.5%
6 2136
 
2.3%
5 2130
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14763
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43252
40.0%
3 15454
 
14.3%
- 14763
 
13.6%
2 10882
 
10.1%
1 6163
 
5.7%
9 6046
 
5.6%
8 2662
 
2.5%
7 2440
 
2.3%
4 2334
 
2.2%
6 2136
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43252
40.0%
3 15454
 
14.3%
- 14763
 
13.6%
2 10882
 
10.1%
1 6163
 
5.7%
9 6046
 
5.6%
8 2662
 
2.5%
7 2440
 
2.3%
4 2334
 
2.2%
6 2136
 
2.0%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
05_19_01_P
4921 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 4921
100.0%

Length

2024-04-17T10:46:13.904495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:13.974824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4921
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
I
4653 
U
 
268

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 4653
94.6%
U 268
 
5.4%

Length

2024-04-17T10:46:14.047913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:14.121560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4653
94.6%
u 268
 
5.4%
Distinct254
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-27 02:40:00
2024-04-17T10:46:14.202509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:14.317411image/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 size38.6 KiB
<NA>
4563 
이용업
 
358

Length

Max length4
Median length4
Mean length3.9272506
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> 4563
92.7%
이용업 358
 
7.3%

Length

2024-04-17T10:46:14.424177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:14.498827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4563
92.7%
이용업 358
 
7.3%

bplcnm
Text

Distinct3313
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-17T10:46:14.718090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7593985
Min length1

Characters and Unicode

Total characters23421
Distinct characters566
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2621 ?
Unique (%)53.3%

Sample

1st row태양탕구내
2nd row국사 이용원
3rd row녹수탕구내이용원
4th row부산호텔이용원
5th row터프가위 이용원
ValueCountFrequency (%)
이용원 364
 
6.4%
구내 53
 
0.9%
컷트실 50
 
0.9%
구내이용원 40
 
0.7%
현대 35
 
0.6%
제일 28
 
0.5%
우리 28
 
0.5%
태후사랑 24
 
0.4%
블루클럽 24
 
0.4%
현대이용원 23
 
0.4%
Other values (3166) 5027
88.3%
2024-04-17T10:46:15.080688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2085
 
8.9%
2016
 
8.6%
1925
 
8.2%
977
 
4.2%
840
 
3.6%
788
 
3.4%
585
 
2.5%
476
 
2.0%
401
 
1.7%
392
 
1.7%
Other values (556) 12936
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22168
94.7%
Space Separator 788
 
3.4%
Uppercase Letter 157
 
0.7%
Lowercase Letter 116
 
0.5%
Close Punctuation 65
 
0.3%
Open Punctuation 65
 
0.3%
Decimal Number 36
 
0.2%
Other Punctuation 19
 
0.1%
Dash Punctuation 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2085
 
9.4%
2016
 
9.1%
1925
 
8.7%
977
 
4.4%
840
 
3.8%
585
 
2.6%
476
 
2.1%
401
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (497) 12129
54.7%
Uppercase Letter
ValueCountFrequency (%)
B 20
12.7%
E 14
 
8.9%
O 14
 
8.9%
R 13
 
8.3%
S 12
 
7.6%
H 12
 
7.6%
M 8
 
5.1%
A 8
 
5.1%
L 7
 
4.5%
P 7
 
4.5%
Other values (12) 42
26.8%
Lowercase Letter
ValueCountFrequency (%)
e 14
12.1%
r 13
11.2%
i 10
 
8.6%
s 9
 
7.8%
h 9
 
7.8%
a 8
 
6.9%
o 7
 
6.0%
k 7
 
6.0%
u 7
 
6.0%
b 7
 
6.0%
Other values (8) 25
21.6%
Decimal Number
ValueCountFrequency (%)
2 11
30.6%
8 10
27.8%
1 8
22.2%
5 3
 
8.3%
9 2
 
5.6%
3 1
 
2.8%
4 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 9
47.4%
& 4
21.1%
, 2
 
10.5%
# 1
 
5.3%
· 1
 
5.3%
: 1
 
5.3%
' 1
 
5.3%
Space Separator
ValueCountFrequency (%)
788
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22165
94.6%
Common 980
 
4.2%
Latin 273
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2085
 
9.4%
2016
 
9.1%
1925
 
8.7%
977
 
4.4%
840
 
3.8%
585
 
2.6%
476
 
2.1%
401
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (494) 12126
54.7%
Latin
ValueCountFrequency (%)
B 20
 
7.3%
e 14
 
5.1%
E 14
 
5.1%
O 14
 
5.1%
R 13
 
4.8%
r 13
 
4.8%
S 12
 
4.4%
H 12
 
4.4%
i 10
 
3.7%
s 9
 
3.3%
Other values (30) 142
52.0%
Common
ValueCountFrequency (%)
788
80.4%
) 65
 
6.6%
( 65
 
6.6%
2 11
 
1.1%
8 10
 
1.0%
. 9
 
0.9%
1 8
 
0.8%
- 6
 
0.6%
& 4
 
0.4%
5 3
 
0.3%
Other values (9) 11
 
1.1%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22165
94.6%
ASCII 1252
 
5.3%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2085
 
9.4%
2016
 
9.1%
1925
 
8.7%
977
 
4.4%
840
 
3.8%
585
 
2.6%
476
 
2.1%
401
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (494) 12126
54.7%
ASCII
ValueCountFrequency (%)
788
62.9%
) 65
 
5.2%
( 65
 
5.2%
B 20
 
1.6%
e 14
 
1.1%
E 14
 
1.1%
O 14
 
1.1%
R 13
 
1.0%
r 13
 
1.0%
S 12
 
1.0%
Other values (48) 234
 
18.7%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

sitepostno
Real number (ℝ)

Distinct775
Distinct (%)15.8%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610459.1
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:15.201892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601812
Q1606063
median609854
Q3614827
95-th percentile617833
Maximum619953
Range19942
Interquartile range (IQR)8764

Descriptive statistics

Standard deviation5298.2985
Coefficient of variation (CV)0.0086792032
Kurtosis-1.0238968
Mean610459.1
Median Absolute Deviation (MAD)4961
Skewness-0.18907422
Sum2.9894182 × 109
Variance28071967
MonotonicityNot monotonic
2024-04-17T10:46:15.555105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
607833 33
 
0.7%
601829 28
 
0.6%
616801 28
 
0.6%
612847 27
 
0.5%
604851 27
 
0.5%
617818 24
 
0.5%
607826 24
 
0.5%
616807 23
 
0.5%
604813 22
 
0.4%
611803 22
 
0.4%
Other values (765) 4639
94.3%
(Missing) 24
 
0.5%
ValueCountFrequency (%)
600011 2
 
< 0.1%
600012 8
0.2%
600013 2
 
< 0.1%
600014 2
 
< 0.1%
600015 1
 
< 0.1%
600021 4
0.1%
600022 3
 
0.1%
600023 3
 
0.1%
600024 1
 
< 0.1%
600025 4
0.1%
ValueCountFrequency (%)
619953 3
 
0.1%
619952 6
0.1%
619951 5
 
0.1%
619950 1
 
< 0.1%
619913 3
 
0.1%
619912 5
 
0.1%
619911 6
0.1%
619906 9
0.2%
619905 14
0.3%
619904 2
 
< 0.1%
Distinct4298
Distinct (%)87.4%
Missing3
Missing (%)0.1%
Memory size38.6 KiB
2024-04-17T10:46:15.827289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length24.691541
Min length7

Characters and Unicode

Total characters121433
Distinct characters368
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3833 ?
Unique (%)77.9%

Sample

1st row부산광역시 중구 남포동6가 115-5번지 (지하1층)
2nd row부산광역시 중구 신창동1가 35-2번지 (2층)
3rd row부산광역시 중구 신창동2가 21-2번지 (2층)
4th row부산광역시 중구 동광동2가 12-1번지 외11필지
5th row부산광역시 중구 중앙동4가 78-20번지 (1층)
ValueCountFrequency (%)
부산광역시 4917
 
22.3%
t통b반 768
 
3.5%
부산진구 510
 
2.3%
사하구 505
 
2.3%
동래구 417
 
1.9%
북구 412
 
1.9%
해운대구 392
 
1.8%
금정구 378
 
1.7%
사상구 336
 
1.5%
연제구 326
 
1.5%
Other values (4636) 13101
59.4%
2024-04-17T10:46:16.231078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21935
18.1%
5835
 
4.8%
5787
 
4.8%
5786
 
4.8%
5086
 
4.2%
1 5081
 
4.2%
5049
 
4.2%
4990
 
4.1%
4942
 
4.1%
4923
 
4.1%
Other values (358) 52019
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69475
57.2%
Decimal Number 23443
 
19.3%
Space Separator 21935
 
18.1%
Dash Punctuation 4464
 
3.7%
Uppercase Letter 1586
 
1.3%
Open Punctuation 220
 
0.2%
Close Punctuation 219
 
0.2%
Other Punctuation 89
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5835
 
8.4%
5787
 
8.3%
5786
 
8.3%
5086
 
7.3%
5049
 
7.3%
4990
 
7.2%
4942
 
7.1%
4923
 
7.1%
4792
 
6.9%
952
 
1.4%
Other values (326) 21333
30.7%
Uppercase Letter
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
C 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
F 2
 
0.1%
P 2
 
0.1%
L 2
 
0.1%
O 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5081
21.7%
2 3168
13.5%
3 2712
11.6%
4 2240
9.6%
5 2181
9.3%
6 1722
 
7.3%
0 1713
 
7.3%
8 1658
 
7.1%
7 1604
 
6.8%
9 1364
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 77
86.5%
@ 6
 
6.7%
/ 3
 
3.4%
. 2
 
2.2%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
21935
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4464
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69473
57.2%
Common 50372
41.5%
Latin 1586
 
1.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5835
 
8.4%
5787
 
8.3%
5786
 
8.3%
5086
 
7.3%
5049
 
7.3%
4990
 
7.2%
4942
 
7.1%
4923
 
7.1%
4792
 
6.9%
952
 
1.4%
Other values (325) 21331
30.7%
Common
ValueCountFrequency (%)
21935
43.5%
1 5081
 
10.1%
- 4464
 
8.9%
2 3168
 
6.3%
3 2712
 
5.4%
4 2240
 
4.4%
5 2181
 
4.3%
6 1722
 
3.4%
0 1713
 
3.4%
8 1658
 
3.3%
Other values (10) 3498
 
6.9%
Latin
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
C 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
F 2
 
0.1%
P 2
 
0.1%
L 2
 
0.1%
O 1
 
0.1%
Other values (2) 2
 
0.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69473
57.2%
ASCII 51958
42.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21935
42.2%
1 5081
 
9.8%
- 4464
 
8.6%
2 3168
 
6.1%
3 2712
 
5.2%
4 2240
 
4.3%
5 2181
 
4.2%
6 1722
 
3.3%
0 1713
 
3.3%
8 1658
 
3.2%
Other values (22) 5084
 
9.8%
Hangul
ValueCountFrequency (%)
5835
 
8.4%
5787
 
8.3%
5786
 
8.3%
5086
 
7.3%
5049
 
7.3%
4990
 
7.2%
4942
 
7.1%
4923
 
7.1%
4792
 
6.9%
952
 
1.4%
Other values (325) 21331
30.7%
CJK
ValueCountFrequency (%)
2
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1152
Distinct (%)51.0%
Missing2660
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean47831.628
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:16.348499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46243
Q147008
median47795
Q348738
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1730

Descriptive statistics

Standard deviation1013.899
Coefficient of variation (CV)0.021197251
Kurtosis-1.1233748
Mean47831.628
Median Absolute Deviation (MAD)801
Skewness0.021750593
Sum1.0814731 × 108
Variance1027991.3
MonotonicityNot monotonic
2024-04-17T10:46:16.462181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 13
 
0.3%
49256 12
 
0.2%
49476 9
 
0.2%
46219 9
 
0.2%
49228 8
 
0.2%
48501 7
 
0.1%
46321 7
 
0.1%
48099 7
 
0.1%
49217 7
 
0.1%
47603 7
 
0.1%
Other values (1142) 2175
44.2%
(Missing) 2660
54.1%
ValueCountFrequency (%)
46002 3
0.1%
46007 2
< 0.1%
46008 1
 
< 0.1%
46013 1
 
< 0.1%
46015 3
0.1%
46017 2
< 0.1%
46019 1
 
< 0.1%
46020 1
 
< 0.1%
46021 1
 
< 0.1%
46022 2
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 2
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49518 5
0.1%
49516 1
 
< 0.1%
49515 4
0.1%
49514 1
 
< 0.1%
49511 6
0.1%
49509 1
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct2200
Distinct (%)95.0%
Missing2604
Missing (%)52.9%
Memory size38.6 KiB
2024-04-17T10:46:16.761884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.658179
Min length17

Characters and Unicode

Total characters66401
Distinct characters389
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2106 ?
Unique (%)90.9%

Sample

1st row부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)
2nd row부산광역시 중구 광복로43번길 12, 2층 (신창동2가)
3rd row부산광역시 중구 중구로 90, 3층 (대청동4가)
4th row부산광역시 중구 동영로 18 (동광동5가)
5th row부산광역시 중구 동영로 11, 1층 (동광동5가)
ValueCountFrequency (%)
부산광역시 2317
 
18.0%
부산진구 273
 
2.1%
1층 268
 
2.1%
동래구 223
 
1.7%
사하구 220
 
1.7%
사상구 192
 
1.5%
금정구 181
 
1.4%
해운대구 177
 
1.4%
남구 162
 
1.3%
북구 154
 
1.2%
Other values (2602) 8731
67.7%
2024-04-17T10:46:17.187018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10584
 
15.9%
3009
 
4.5%
2833
 
4.3%
2793
 
4.2%
1 2497
 
3.8%
2427
 
3.7%
2422
 
3.6%
2399
 
3.6%
2321
 
3.5%
( 2285
 
3.4%
Other values (379) 32831
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39639
59.7%
Space Separator 10584
 
15.9%
Decimal Number 10110
 
15.2%
Open Punctuation 2285
 
3.4%
Close Punctuation 2285
 
3.4%
Other Punctuation 1033
 
1.6%
Dash Punctuation 425
 
0.6%
Uppercase Letter 38
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3009
 
7.6%
2833
 
7.1%
2793
 
7.0%
2427
 
6.1%
2422
 
6.1%
2399
 
6.1%
2321
 
5.9%
2236
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (350) 16733
42.2%
Decimal Number
ValueCountFrequency (%)
1 2497
24.7%
2 1539
15.2%
3 1181
11.7%
4 862
 
8.5%
5 819
 
8.1%
0 714
 
7.1%
6 697
 
6.9%
7 656
 
6.5%
8 593
 
5.9%
9 552
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 18
47.4%
T 7
 
18.4%
A 6
 
15.8%
S 2
 
5.3%
C 1
 
2.6%
F 1
 
2.6%
K 1
 
2.6%
P 1
 
2.6%
E 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 1020
98.7%
@ 5
 
0.5%
/ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10584
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2285
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 425
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39639
59.7%
Common 26724
40.2%
Latin 38
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3009
 
7.6%
2833
 
7.1%
2793
 
7.0%
2427
 
6.1%
2422
 
6.1%
2399
 
6.1%
2321
 
5.9%
2236
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (350) 16733
42.2%
Common
ValueCountFrequency (%)
10584
39.6%
1 2497
 
9.3%
( 2285
 
8.6%
) 2285
 
8.6%
2 1539
 
5.8%
3 1181
 
4.4%
, 1020
 
3.8%
4 862
 
3.2%
5 819
 
3.1%
0 714
 
2.7%
Other values (10) 2938
 
11.0%
Latin
ValueCountFrequency (%)
B 18
47.4%
T 7
 
18.4%
A 6
 
15.8%
S 2
 
5.3%
C 1
 
2.6%
F 1
 
2.6%
K 1
 
2.6%
P 1
 
2.6%
E 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39639
59.7%
ASCII 26762
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10584
39.5%
1 2497
 
9.3%
( 2285
 
8.5%
) 2285
 
8.5%
2 1539
 
5.8%
3 1181
 
4.4%
, 1020
 
3.8%
4 862
 
3.2%
5 819
 
3.1%
0 714
 
2.7%
Other values (19) 2976
 
11.1%
Hangul
ValueCountFrequency (%)
3009
 
7.6%
2833
 
7.1%
2793
 
7.0%
2427
 
6.1%
2422
 
6.1%
2399
 
6.1%
2321
 
5.9%
2236
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (350) 16733
42.2%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3624
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19958752
Minimum9710223
Maximum20210222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:17.312438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691125
Q119880104
median19980428
Q320051220
95-th percentile20170821
Maximum20210222
Range10499999
Interquartile range (IQR)171116

Descriptive statistics

Standard deviation201129.61
Coefficient of variation (CV)0.010077264
Kurtosis1369.4257
Mean19958752
Median Absolute Deviation (MAD)89999
Skewness-27.027241
Sum9.8217021 × 1010
Variance4.0453119 × 1010
MonotonicityNot monotonic
2024-04-17T10:46:17.432599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19660301 35
 
0.7%
19770830 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
19630630 9
 
0.2%
20030224 9
 
0.2%
20030410 7
 
0.1%
19721129 7
 
0.1%
20030213 6
 
0.1%
Other values (3614) 4764
96.8%
ValueCountFrequency (%)
9710223 1
 
< 0.1%
19300722 1
 
< 0.1%
19610922 1
 
< 0.1%
19621202 1
 
< 0.1%
19630110 6
0.1%
19630522 1
 
< 0.1%
19630525 1
 
< 0.1%
19630529 4
0.1%
19630601 1
 
< 0.1%
19630622 1
 
< 0.1%
ValueCountFrequency (%)
20210222 2
< 0.1%
20210208 1
< 0.1%
20210202 2
< 0.1%
20210201 1
< 0.1%
20210129 2
< 0.1%
20210125 1
< 0.1%
20210122 2
< 0.1%
20210119 1
< 0.1%
20210107 1
< 0.1%
20201217 2
< 0.1%

dcbymd
Text

MISSING 

Distinct2159
Distinct (%)62.1%
Missing1447
Missing (%)29.4%
Memory size38.6 KiB
2024-04-17T10:46:17.698084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9597006
Min length4

Characters and Unicode

Total characters27652
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

Unique1534 ?
Unique (%)44.2%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
20030715 58
 
1.7%
20050214 41
 
1.2%
20031213 36
 
1.0%
폐업일자 35
 
1.0%
20030305 33
 
0.9%
20020222 33
 
0.9%
20030221 32
 
0.9%
20030101 17
 
0.5%
20051011 16
 
0.5%
20061226 13
 
0.4%
Other values (2149) 3160
91.0%
2024-04-17T10:46:18.081512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9742
35.2%
2 5733
20.7%
1 4541
16.4%
3 1407
 
5.1%
5 1256
 
4.5%
9 1158
 
4.2%
4 1002
 
3.6%
7 947
 
3.4%
6 898
 
3.2%
8 828
 
3.0%
Other values (4) 140
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27512
99.5%
Other Letter 140
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9742
35.4%
2 5733
20.8%
1 4541
16.5%
3 1407
 
5.1%
5 1256
 
4.6%
9 1158
 
4.2%
4 1002
 
3.6%
7 947
 
3.4%
6 898
 
3.3%
8 828
 
3.0%
Other Letter
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27512
99.5%
Hangul 140
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9742
35.4%
2 5733
20.8%
1 4541
16.5%
3 1407
 
5.1%
5 1256
 
4.6%
9 1158
 
4.2%
4 1002
 
3.6%
7 947
 
3.4%
6 898
 
3.3%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27512
99.5%
Hangul 140
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9742
35.4%
2 5733
20.8%
1 4541
16.5%
3 1407
 
5.1%
5 1256
 
4.6%
9 1158
 
4.2%
4 1002
 
3.6%
7 947
 
3.4%
6 898
 
3.3%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4884 
휴업시작일자
 
37

Length

Max length6
Median length4
Mean length4.0150376
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> 4884
99.2%
휴업시작일자 37
 
0.8%

Length

2024-04-17T10:46:18.206055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:18.287354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4884
99.2%
휴업시작일자 37
 
0.8%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4884 
휴업종료일자
 
37

Length

Max length6
Median length4
Mean length4.0150376
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> 4884
99.2%
휴업종료일자 37
 
0.8%

Length

2024-04-17T10:46:18.379472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:18.459179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4884
99.2%
휴업종료일자 37
 
0.8%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4884 
재개업일자
 
37

Length

Max length5
Median length4
Mean length4.0075188
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> 4884
99.2%
재개업일자 37
 
0.8%

Length

2024-04-17T10:46:18.538482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:18.613573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4884
99.2%
재개업일자 37
 
0.8%

trdstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
02
3330 
01
1233 
영업/정상
 
245
폐업
 
108
영업상태
 
3

Length

Max length5
Median length2
Mean length2.151392
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02

Common Values

ValueCountFrequency (%)
02 3330
67.7%
01 1233
 
25.1%
영업/정상 245
 
5.0%
폐업 108
 
2.2%
영업상태 3
 
0.1%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:46:18.693018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:18.796173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
67.7%
01 1233
 
25.1%
영업/정상 245
 
5.0%
폐업 108
 
2.2%
영업상태 3
 
0.1%
na 2
 
< 0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3439 
영업
1482 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3439
69.9%
영업 1482
30.1%

Length

2024-04-17T10:46:18.887885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:18.961431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3439
69.9%
영업 1482
30.1%

x
Text

MISSING 

Distinct4000
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.6 KiB
2024-04-17T10:46:19.152460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991535
Min length7

Characters and Unicode

Total characters92101
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3511 ?
Unique (%)76.2%

Sample

1st row384763.36249800000
2nd row385005.25775
3rd row385086.62014400000
4th row385447.404485
5th row385737.436336
ValueCountFrequency (%)
382169.305404 5
 
0.1%
389415.20340442 5
 
0.1%
392357.064184 4
 
0.1%
379140.640735214 4
 
0.1%
378522.108153 4
 
0.1%
384473.209419 4
 
0.1%
391721.655503 4
 
0.1%
384080.85541900000 4
 
0.1%
388076.092919 4
 
0.1%
385517.559896 4
 
0.1%
Other values (3990) 4565
99.1%
2024-04-17T10:46:19.466979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20916
22.7%
0 14711
16.0%
3 9413
10.2%
8 7429
 
8.1%
9 6191
 
6.7%
7 4973
 
5.4%
1 4847
 
5.3%
5 4805
 
5.2%
6 4752
 
5.2%
2 4735
 
5.1%
Other values (9) 9329
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66560
72.3%
Space Separator 20916
 
22.7%
Other Punctuation 4604
 
5.0%
Other Letter 12
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14711
22.1%
3 9413
14.1%
8 7429
11.2%
9 6191
9.3%
7 4973
 
7.5%
1 4847
 
7.3%
5 4805
 
7.2%
6 4752
 
7.1%
2 4735
 
7.1%
4 4704
 
7.1%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Space Separator
ValueCountFrequency (%)
20916
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4604
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92086
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
20916
22.7%
0 14711
16.0%
3 9413
10.2%
8 7429
 
8.1%
9 6191
 
6.7%
7 4973
 
5.4%
1 4847
 
5.3%
5 4805
 
5.2%
6 4752
 
5.2%
2 4735
 
5.1%
Other values (4) 9314
10.1%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Latin
ValueCountFrequency (%)
X 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92089
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20916
22.7%
0 14711
16.0%
3 9413
10.2%
8 7429
 
8.1%
9 6191
 
6.7%
7 4973
 
5.4%
1 4847
 
5.3%
5 4805
 
5.2%
6 4752
 
5.2%
2 4735
 
5.1%
Other values (5) 9317
10.1%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

y
Text

MISSING 

Distinct4000
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.6 KiB
2024-04-17T10:46:19.684276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991535
Min length7

Characters and Unicode

Total characters92101
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3511 ?
Unique (%)76.2%

Sample

1st row179706.64036800000
2nd row179998.796394
3rd row180119.33406400000
4th row179824.590338
5th row180816.22011
ValueCountFrequency (%)
191928.498233 5
 
0.1%
193131.590860807 5
 
0.1%
185295.821253 4
 
0.1%
180128.072887035 4
 
0.1%
179922.534172 4
 
0.1%
179378.899808 4
 
0.1%
192875.131262 4
 
0.1%
179983.87155900000 4
 
0.1%
177016.065925 4
 
0.1%
179676.666539 4
 
0.1%
Other values (3990) 4565
99.1%
2024-04-17T10:46:19.989849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20871
22.7%
0 14499
15.7%
1 9459
10.3%
8 7148
 
7.8%
9 6449
 
7.0%
7 5535
 
6.0%
2 4862
 
5.3%
3 4737
 
5.1%
4 4687
 
5.1%
6 4618
 
5.0%
Other values (9) 9236
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66605
72.3%
Space Separator 20871
 
22.7%
Other Punctuation 4604
 
5.0%
Other Letter 12
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14499
21.8%
1 9459
14.2%
8 7148
10.7%
9 6449
9.7%
7 5535
 
8.3%
2 4862
 
7.3%
3 4737
 
7.1%
4 4687
 
7.0%
6 4618
 
6.9%
5 4611
 
6.9%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Space Separator
ValueCountFrequency (%)
20871
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4604
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92086
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
20871
22.7%
0 14499
15.7%
1 9459
10.3%
8 7148
 
7.8%
9 6449
 
7.0%
7 5535
 
6.0%
2 4862
 
5.3%
3 4737
 
5.1%
4 4687
 
5.1%
6 4618
 
5.0%
Other values (4) 9221
10.0%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Latin
ValueCountFrequency (%)
Y 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92089
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20871
22.7%
0 14499
15.7%
1 9459
10.3%
8 7148
 
7.8%
9 6449
 
7.0%
7 5535
 
6.0%
2 4862
 
5.3%
3 4737
 
5.1%
4 4687
 
5.1%
6 4618
 
5.0%
Other values (5) 9224
10.0%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

lastmodts
Real number (ℝ)

Distinct3197
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0087578 × 1013
Minimum1.9990218 × 1013
Maximum2.0210225 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-17T10:46:20.112168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990624 × 1013
Q12.0031001 × 1013
median2.007082 × 1013
Q32.0131121 × 1013
95-th percentile2.019093 × 1013
Maximum2.0210225 × 1013
Range2.2000717 × 1011
Interquartile range (IQR)1.0012017 × 1011

Descriptive statistics

Standard deviation6.127821 × 1010
Coefficient of variation (CV)0.0030505525
Kurtosis-1.160894
Mean2.0087578 × 1013
Median Absolute Deviation (MAD)4.0609094 × 1010
Skewness0.30254171
Sum9.8850971 × 1016
Variance3.7550191 × 1021
MonotonicityNot monotonic
2024-04-17T10:46:20.222928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 63
 
1.3%
20070501000000 54
 
1.1%
20030311000000 38
 
0.8%
20031215000000 38
 
0.8%
20020424000000 38
 
0.8%
20030502000000 37
 
0.8%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20060707000000 34
 
0.7%
20030221000000 33
 
0.7%
Other values (3187) 4517
91.8%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 11
0.2%
19990303000000 12
0.2%
19990304000000 20
0.4%
19990308000000 17
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20210225165407 1
< 0.1%
20210225132112 1
< 0.1%
20210225131906 2
< 0.1%
20210222140400 1
< 0.1%
20210222131454 1
< 0.1%
20210222104030 1
< 0.1%
20210219212929 1
< 0.1%
20210219150112 1
< 0.1%
20210219144328 1
< 0.1%
20210218101602 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
일반이용업
4857 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079252
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4857
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:20.328039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:20.411974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4857
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

sitetel
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
051-123-1234
4830 
<NA>
 
59
전화번호
 
8
051 7526956
 
3
051 5571626
 
1
Other values (20)
 
20

Length

Max length12
Median length12
Mean length11.888234
Min length4

Unique

Unique21 ?
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 4830
98.2%
<NA> 59
 
1.2%
전화번호 8
 
0.2%
051 7526956 3
 
0.1%
051 5571626 1
 
< 0.1%
051 243 3920 1
 
< 0.1%
051412 8217 1
 
< 0.1%
051803 9900 1
 
< 0.1%
051 896 7133 1
 
< 0.1%
051 807 0341 1
 
< 0.1%
Other values (15) 15
 
0.3%

Length

2024-04-17T10:46:20.521447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 4830
97.5%
na 59
 
1.2%
051 20
 
0.4%
전화번호 8
 
0.2%
7526956 3
 
0.1%
895 1
 
< 0.1%
893 1
 
< 0.1%
2964 1
 
< 0.1%
7519410 1
 
< 0.1%
7582957 1
 
< 0.1%
Other values (27) 27
 
0.5%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3968 
임대
906 
건물소유구분명
 
25
자가
 
22

Length

Max length7
Median length4
Mean length3.6380817
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3968
80.6%
임대 906
 
18.4%
건물소유구분명 25
 
0.5%
자가 22
 
0.4%

Length

2024-04-17T10:46:20.632428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:20.727489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3968
80.6%
임대 906
 
18.4%
건물소유구분명 25
 
0.5%
자가 22
 
0.4%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
1768 
0
1173 
3
481 
4
420 
2
402 
Other values (29)
677 

Length

Max length6
Median length1
Mean length2.0975412
Min length1

Unique

Unique9 ?
Unique (%)0.2%

Sample

1st row1
2nd row3
3rd row4
4th row16
5th row6

Common Values

ValueCountFrequency (%)
<NA> 1768
35.9%
0 1173
23.8%
3 481
 
9.8%
4 420
 
8.5%
2 402
 
8.2%
5 236
 
4.8%
1 165
 
3.4%
6 83
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 110
 
2.2%

Length

2024-04-17T10:46:20.834796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1768
35.9%
0 1173
23.8%
3 481
 
9.8%
4 420
 
8.5%
2 402
 
8.2%
5 236
 
4.8%
1 165
 
3.4%
6 83
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 110
 
2.2%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2284 
0
1660 
1
838 
2
 
87
3
 
21
Other values (7)
 
31

Length

Max length6
Median length1
Mean length2.3960577
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2284
46.4%
0 1660
33.7%
1 838
 
17.0%
2 87
 
1.8%
3 21
 
0.4%
5 15
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
건물지하층수 3
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T10:46:20.934135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2284
46.4%
0 1660
33.7%
1 838
 
17.0%
2 87
 
1.8%
3 21
 
0.4%
5 15
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
건물지하층수 3
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4540 
0
 
345
1
 
32
남성종사자수
 
3
2
 
1

Length

Max length6
Median length4
Mean length3.7707783
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4540
92.3%
0 345
 
7.0%
1 32
 
0.7%
남성종사자수 3
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T10:46:21.026910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:21.101924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4540
92.3%
0 345
 
7.0%
1 32
 
0.7%
남성종사자수 3
 
0.1%
2 1
 
< 0.1%

multusnupsoyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4921 
ValueCountFrequency (%)
False 4921
100.0%
2024-04-17T10:46:21.168184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4921 
ValueCountFrequency (%)
False 4921
100.0%
2024-04-17T10:46:21.221735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2782 
1
747 
0
540 
2
464 
3
 
214
Other values (8)
 
174

Length

Max length6
Median length4
Mean length2.7189596
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 2782
56.5%
1 747
 
15.2%
0 540
 
11.0%
2 464
 
9.4%
3 214
 
4.3%
4 78
 
1.6%
5 46
 
0.9%
사용끝지상층 22
 
0.4%
6 15
 
0.3%
7 7
 
0.1%
Other values (3) 6
 
0.1%

Length

2024-04-17T10:46:21.301126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2782
56.5%
1 747
 
15.2%
0 540
 
11.0%
2 464
 
9.4%
3 214
 
4.3%
4 78
 
1.6%
5 46
 
0.9%
사용끝지상층 22
 
0.4%
6 15
 
0.3%
7 7
 
0.1%
Other values (3) 6
 
0.1%

useunderendflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3769 
0
852 
1
 
261
사용끝지하층
 
33
2
 
5

Length

Max length6
Median length4
Mean length3.3312335
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3769
76.6%
0 852
 
17.3%
1 261
 
5.3%
사용끝지하층 33
 
0.7%
2 5
 
0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:46:21.397950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:21.482873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3769
76.6%
0 852
 
17.3%
1 261
 
5.3%
사용끝지하층 33
 
0.7%
2 5
 
0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2160 
0
969 
1
852 
2
494 
3
253 
Other values (10)
 
193

Length

Max length7
Median length1
Mean length2.3363138
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 2160
43.9%
0 969
19.7%
1 852
 
17.3%
2 494
 
10.0%
3 253
 
5.1%
4 86
 
1.7%
5 56
 
1.1%
6 19
 
0.4%
사용시작지상층 15
 
0.3%
7 5
 
0.1%
Other values (5) 12
 
0.2%

Length

2024-04-17T10:46:21.576765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2160
43.9%
0 969
19.7%
1 852
 
17.3%
2 494
 
10.0%
3 253
 
5.1%
4 86
 
1.7%
5 56
 
1.1%
6 19
 
0.4%
사용시작지상층 15
 
0.3%
7 5
 
0.1%
Other values (5) 12
 
0.2%

useunderstflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3111 
0
1460 
1
 
307
사용시작지하층
 
28
2
 
14

Length

Max length7
Median length4
Mean length2.9309084
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3111
63.2%
0 1460
29.7%
1 307
 
6.2%
사용시작지하층 28
 
0.6%
2 14
 
0.3%
22 1
 
< 0.1%

Length

2024-04-17T10:46:21.681118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:21.768598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3111
63.2%
0 1460
29.7%
1 307
 
6.2%
사용시작지하층 28
 
0.6%
2 14
 
0.3%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3430 
0
1488 
세탁기수
 
3

Length

Max length4
Median length4
Mean length3.0928673
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3430
69.7%
0 1488
30.2%
세탁기수 3
 
0.1%

Length

2024-04-17T10:46:21.865261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:21.946639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3430
69.7%
0 1488
30.2%
세탁기수 3
 
0.1%

yangsilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2761 
0
2156 
양실수
 
3
38
 
1

Length

Max length4
Median length4
Mean length2.6846169
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2761
56.1%
0 2156
43.8%
양실수 3
 
0.1%
38 1
 
< 0.1%

Length

2024-04-17T10:46:22.032571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:22.112916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2761
56.1%
0 2156
43.8%
양실수 3
 
0.1%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4551 
0
 
350
1
 
17
여성종사자수
 
3

Length

Max length6
Median length4
Mean length3.7774843
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> 4551
92.5%
0 350
 
7.1%
1 17
 
0.3%
여성종사자수 3
 
0.1%

Length

2024-04-17T10:46:22.196945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:22.273372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4551
92.5%
0 350
 
7.1%
1 17
 
0.3%
여성종사자수 3
 
0.1%

yoksilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2761 
0
2156 
욕실수
 
3
2
 
1

Length

Max length4
Median length4
Mean length2.6844137
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2761
56.1%
0 2156
43.8%
욕실수 3
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T10:46:22.372679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:22.456920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2761
56.1%
0 2156
43.8%
욕실수 3
 
0.1%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
일반이용업
4857 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079252
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4857
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:22.561733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:22.942555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4857
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

chaircnt
Categorical

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2
1329 
3
883 
<NA>
615 
4
591 
0
339 
Other values (12)
1164 

Length

Max length4
Median length1
Mean length1.3844747
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row4
3rd row2
4th row7
5th row4

Common Values

ValueCountFrequency (%)
2 1329
27.0%
3 883
17.9%
<NA> 615
12.5%
4 591
12.0%
0 339
 
6.9%
1 327
 
6.6%
5 263
 
5.3%
6 180
 
3.7%
7 170
 
3.5%
8 111
 
2.3%
Other values (7) 113
 
2.3%

Length

2024-04-17T10:46:23.027673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1329
27.0%
3 883
17.9%
na 615
12.5%
4 591
12.0%
0 339
 
6.9%
1 327
 
6.6%
5 263
 
5.3%
6 180
 
3.7%
7 170
 
3.5%
8 111
 
2.3%
Other values (7) 113
 
2.3%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4882 
조건부허가시작일자
 
37
20050520
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0392197
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row20050520
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4882
99.2%
조건부허가시작일자 37
 
0.8%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:46:23.125567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:23.202036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4882
99.2%
조건부허가시작일자 37
 
0.8%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4883 
조건부허가신고사유
 
37
가설건축물
 
1

Length

Max length9
Median length4
Mean length4.0377972
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4883
99.2%
조건부허가신고사유 37
 
0.8%
가설건축물 1
 
< 0.1%

Length

2024-04-17T10:46:23.288874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:23.373369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4883
99.2%
조건부허가신고사유 37
 
0.8%
가설건축물 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4882 
조건부허가종료일자
 
37
20060425
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0392197
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row20060425
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4882
99.2%
조건부허가종료일자 37
 
0.8%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:46:23.479918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:23.560663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4882
99.2%
조건부허가종료일자 37
 
0.8%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

abedcnt
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3631 
0
1279 
2
 
4
침대수
 
3
3
 
2
Other values (2)
 
2

Length

Max length4
Median length4
Mean length3.2147937
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3631
73.8%
0 1279
 
26.0%
2 4
 
0.1%
침대수 3
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T10:46:23.648688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:23.745244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3631
73.8%
0 1279
 
26.0%
2 4
 
0.1%
침대수 3
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2762 
0
2156 
한실수
 
3

Length

Max length4
Median length4
Mean length2.6850234
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2762
56.1%
0 2156
43.8%
한실수 3
 
0.1%

Length

2024-04-17T10:46:23.840132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:23.921320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2762
56.1%
0 2156
43.8%
한실수 3
 
0.1%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3613 
0
1305 
회수건조수
 
3

Length

Max length5
Median length4
Mean length3.2050396
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3613
73.4%
0 1305
 
26.5%
회수건조수 3
 
0.1%

Length

2024-04-17T10:46:24.014991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:24.103699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3613
73.4%
0 1305
 
26.5%
회수건조수 3
 
0.1%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2021-03-01 05:25:03
Maximum2021-03-01 05:25:03
2024-04-17T10:46:24.170497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:24.243122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0532500003250000-203-1980-0047805_19_01_PI2018-08-31 23:59:59.0<NA>태양탕구내600046부산광역시 중구 남포동6가 115-5번지 (지하1층)48982부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)1980120220180501<NA><NA><NA>02폐업384763.36249800000179706.6403680000020180501090321일반이용업051-123-1234임대11<NA>NN010100<NA>0일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
1632500003250000-203-2005-0000405_19_01_PI2018-08-31 23:59:59.0<NA>국사 이용원600061부산광역시 중구 신창동1가 35-2번지 (2층)<NA><NA>2005052020121212<NA><NA><NA>02폐업385005.25775179998.79639420050520000000일반이용업051-123-1234<NA>3<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업420050520가설건축물20060425<NA><NA><NA>2021-03-01 05:25:03
2732500003250000-203-2005-0000505_19_01_PI2018-08-31 23:59:59.0<NA>녹수탕구내이용원600062부산광역시 중구 신창동2가 21-2번지 (2층)48947부산광역시 중구 광복로43번길 12, 2층 (신창동2가)2005053120151228<NA><NA><NA>02폐업385086.62014400000180119.3340640000020130208134228일반이용업051-123-1234<NA>41<NA>NN202000<NA>0일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
3832500003250000-203-1972-0044305_19_01_PI2018-08-31 23:59:59.0<NA>부산호텔이용원600022부산광역시 중구 동광동2가 12-1번지 외11필지<NA><NA>1972103120121212<NA><NA><NA>02폐업385447.404485179824.59033820060306000000일반이용업051-123-1234임대161<NA>NN3<NA>3<NA><NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2021-03-01 05:25:03
4932500003250000-203-2005-0000105_19_01_PI2018-08-31 23:59:59.0<NA>터프가위 이용원600816부산광역시 중구 중앙동4가 78-20번지 (1층)<NA><NA>2005011920080710<NA><NA><NA>02폐업385737.436336180816.2201120050119000000일반이용업051-123-1234<NA>61<NA>NN1<NA>1<NA><NA><NA><NA><NA>일반이용업4<NA><NA><NA><NA><NA><NA>2021-03-01 05:25:03
51032500003250000-203-2005-0000205_19_01_PI2018-08-31 23:59:59.0<NA>알지 이용원600816부산광역시 중구 중앙동4가 84-26번지 (지하1층)<NA><NA>2005031420060201<NA><NA><NA>02폐업385685.971895180523.35229820050314000000일반이용업051-123-1234<NA>51<NA>NN<NA>1<NA>1<NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2021-03-01 05:25:03
61132500003250000-203-1989-0051705_19_01_PI2018-08-31 23:59:59.0<NA>남성H전문600800부산광역시 중구 대청동4가 85-1번지 (3층)48933부산광역시 중구 중구로 90, 3층 (대청동4가)19890928<NA><NA><NA><NA>01영업385152.87363900000180604.3028620000020171110105721일반이용업051-123-1234임대41<NA>NN303000<NA>0일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
71232500003250000-203-2002-0001005_19_01_PI2018-08-31 23:59:59.0<NA>미도이용원600807부산광역시 중구 부평동2가 27-4번지<NA><NA>2002052320090805<NA><NA><NA>02폐업384647.050294179711.51617220070117000000일반이용업051-123-1234임대4<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업6<NA><NA><NA><NA><NA><NA>2021-03-01 05:25:03
81332500003250000-203-1979-0046105_19_01_PI2018-08-31 23:59:59.0<NA>부남600025부산광역시 중구 동광동5가 12-165번지48921부산광역시 중구 동영로 18 (동광동5가)19790623<NA><NA><NA><NA>01영업385465.80651300000181014.9432670000020131230110555일반이용업051-123-1234임대31<NA>NN101000<NA>0일반이용업5<NA><NA><NA>0002021-03-01 05:25:03
91432500003250000-203-1979-0046205_19_01_PI2018-08-31 23:59:59.0<NA>부전600025부산광역시 중구 동광동5가 13-68번지 (1층)48918부산광역시 중구 동영로 11, 1층 (동광동5가)19791231<NA><NA><NA><NA>01영업385407.17813300000180988.5592120000020130208125257일반이용업051-123-1234임대10<NA>NN101000<NA>0일반이용업4<NA><NA><NA>0002021-03-01 05:25:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
4911699333400003340000-203-1990-0123805_19_01_PI2021-01-24 00:23:04.0이용업용정탕이용원604804부산광역시 사하구 감천동 315-1849451부산광역시 사하구 암남공원로 533, 용정탕 내 1층 (감천동)19900224<NA><NA><NA><NA>영업/정상영업383375.171266665177569.99449158620210122143959일반이용업051 7526956<NA>141<NA>NN505000<NA>0일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
4912699632900003290000-203-2021-0000305_19_01_PI2021-01-27 00:23:03.0이용업로제바버샵614866부산광역시 부산진구 전포동 683-847294부산광역시 부산진구 동천로 72, 지하1층 (전포동)20210125<NA><NA><NA><NA>영업/정상영업387869.713042656185948.09186152720210125135513일반이용업<NA>임대410NN<NA>1<NA>10000일반이용업3<NA><NA><NA>0002021-03-01 05:25:03
4913701032800003280000-203-2021-0000105_19_01_PU2021-02-27 02:40:00.0이용업긱스(geeks)606042부산광역시 영도구 영선동2가 44-249056부산광역시 영도구 영선대로 67 (영선동2가)2021012920210225<NA><NA><NA>폐업폐업386100.884001403178372.43703474920210225131906일반이용업<NA><NA>000NN1<NA>1<NA>0000일반이용업4<NA><NA><NA>0002021-03-01 05:25:03
4914701332800003280000-203-2021-0000105_19_01_PU2021-02-27 02:40:00.0이용업긱스(geeks)606042부산광역시 영도구 영선동2가 44-249056부산광역시 영도구 영선대로 67 (영선동2가)2021012920210225<NA><NA><NA>폐업폐업386100.884001403178372.43703474920210225131906일반이용업<NA><NA>000NN1<NA>1<NA>0000일반이용업4<NA><NA><NA>0002021-03-01 05:25:03
4915701634000003400000-203-2021-0000105_19_01_PU2021-02-27 02:40:00.0이용업모티브이용원619873부산광역시 기장군 철마면 송정리 5 S&T모티브46002부산광역시 기장군 철마면 여락송정로 363 (S&T모티브)20210201폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업394117.140328901202127.10701502120210225165407일반이용업전화번호건물소유구분명310NN10100000일반이용업3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-03-01 05:25:03
4916701733500003350000-203-2021-0000105_19_01_PI2021-02-04 00:23:03.0이용업평화탕이발소609858부산광역시 금정구 서동 118-6 평화목욕탕46321부산광역시 금정구 금사로 48, 평화목욕탕 2층 (서동)20210202폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업391985.955861303192950.81183939820210202100028일반이용업전화번호건물소유구분명301NN2사용끝지하층2사용시작지하층0000일반이용업1조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-03-01 05:25:03
4917702132800003280000-203-2021-0000205_19_01_PI2021-02-04 00:23:03.0이용업남성컷트606809부산광역시 영도구 동삼동 510-27 영도벽산비치타운49115부산광역시 영도구 와치로 266, 1층 102호 (동삼동, 영도벽산비치타운)20210202<NA><NA><NA><NA>영업/정상영업388701.801553182177051.00346612720210202165924일반이용업<NA><NA>100NN10100000일반이용업3<NA><NA><NA>0002021-03-01 05:25:03
4918704033900003390000-203-2021-0000105_19_01_PU2021-02-20 02:40:00.0이용업새미랑이용원617806부산광역시 사상구 괘법동 274-4 새미랑해수온천탕46965부산광역시 사상구 광장로93번길 67, 새미랑해수온천탕 2층 (괘법동)20210208<NA><NA><NA><NA>영업/정상영업380795.367553997186940.60195567520210218101602일반이용업<NA><NA>000NN20200000일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
4919707232900003290000-203-2021-0000405_19_01_PI2021-02-24 00:23:01.0이용업올멋614817부산광역시 부산진구 당감동 238-5347182부산광역시 부산진구 백양대로60번길 34, 1층 (당감동)20210222<NA><NA><NA><NA>영업/정상영업386028.073030716186868.3391381420210222104030일반이용업<NA>임대200NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-03-01 05:25:03
4920707533700003370000-203-2021-0000105_19_01_PI2021-02-24 00:23:01.0이용업머스마611812부산광역시 연제구 연산동 488-3547570부산광역시 연제구 고분로242번길 34, 101호 (연산동)20210222<NA><NA><NA><NA>영업/정상영업391987.811458421189111.23857948920210222140400일반이용업<NA>임대400NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-03-01 05:25:03