Overview

Dataset statistics

Number of variables47
Number of observations1816
Missing cells1613
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory677.6 KiB
Average record size in memory382.1 B

Variable types

Numeric6
Text8
Categorical29
DateTime2
Boolean2

Alerts

opnsvcid has constant value ""Constant
last_load_dttm has constant value ""Constant
clgstdt is highly imbalanced (89.9%)Imbalance
clgenddt is highly imbalanced (89.9%)Imbalance
ropnymd is highly imbalanced (89.9%)Imbalance
uptaenm is highly imbalanced (63.1%)Imbalance
maneipcnt is highly imbalanced (89.4%)Imbalance
multusnupsoyn is highly imbalanced (86.6%)Imbalance
useunderendflr is highly imbalanced (57.5%)Imbalance
useunderstflr is highly imbalanced (50.3%)Imbalance
wmeipcnt is highly imbalanced (90.2%)Imbalance
yoksilcnt is highly imbalanced (52.9%)Imbalance
sntuptaenm is highly imbalanced (63.1%)Imbalance
cndpermstymd is highly imbalanced (93.2%)Imbalance
cndpermntwhy is highly imbalanced (93.2%)Imbalance
cndpermendymd is highly imbalanced (93.2%)Imbalance
rdnwhladdr has 618 (34.0%) missing valuesMissing
dcbymd has 829 (45.6%) missing valuesMissing
x has 75 (4.1%) missing valuesMissing
y has 75 (4.1%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 08:11:08.666788
Analysis finished2024-04-16 08:11:09.721711
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct1816
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean913.76817
Minimum3
Maximum2216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:09.776827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile93.75
Q1456.75
median910.5
Q31364.25
95-th percentile1727.25
Maximum2216
Range2213
Interquartile range (IQR)907.5

Descriptive statistics

Standard deviation530.74429
Coefficient of variation (CV)0.58083035
Kurtosis-1.1019979
Mean913.76817
Median Absolute Deviation (MAD)454
Skewness0.051591554
Sum1659403
Variance281689.5
MonotonicityNot monotonic
2024-04-16T17:11:09.886029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
0.1%
1195 1
 
0.1%
1221 1
 
0.1%
1220 1
 
0.1%
1219 1
 
0.1%
1218 1
 
0.1%
1217 1
 
0.1%
1216 1
 
0.1%
1215 1
 
0.1%
1214 1
 
0.1%
Other values (1806) 1806
99.4%
ValueCountFrequency (%)
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%
11 1
0.1%
12 1
0.1%
ValueCountFrequency (%)
2216 1
0.1%
2150 1
0.1%
2143 1
0.1%
2136 1
0.1%
2131 1
0.1%
2104 1
0.1%
2102 1
0.1%
2101 1
0.1%
2100 1
0.1%
2097 1
0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322984.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:09.977382image/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 deviation39907.769
Coefficient of variation (CV)0.012009616
Kurtosis-0.91104909
Mean3322984.6
Median Absolute Deviation (MAD)30000
Skewness0.13525679
Sum6.03454 × 109
Variance1.5926301 × 109
MonotonicityNot monotonic
2024-04-16T17:11:10.069708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 222
12.2%
3340000 171
9.4%
3300000 164
9.0%
3330000 159
8.8%
3310000 148
 
8.1%
3370000 131
 
7.2%
3320000 123
 
6.8%
3350000 116
 
6.4%
3380000 112
 
6.2%
3270000 93
 
5.1%
Other values (6) 377
20.8%
ValueCountFrequency (%)
3250000 62
 
3.4%
3260000 72
 
4.0%
3270000 93
5.1%
3280000 74
 
4.1%
3290000 222
12.2%
3300000 164
9.0%
3310000 148
8.1%
3320000 123
6.8%
3330000 159
8.8%
3340000 171
9.4%
ValueCountFrequency (%)
3400000 45
 
2.5%
3390000 93
5.1%
3380000 112
6.2%
3370000 131
7.2%
3360000 31
 
1.7%
3350000 116
6.4%
3340000 171
9.4%
3330000 159
8.8%
3320000 123
6.8%
3310000 148
8.1%

mgtno
Text

Distinct1807
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-16T17:11:10.247967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39952
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

Unique1802 ?
Unique (%)99.2%

Sample

1st row3250000-202-2002-00001
2nd row3250000-202-1985-00156
3rd row3250000-202-2001-00013
4th row3250000-202-2007-00001
5th row3250000-202-1988-00159
ValueCountFrequency (%)
3350000-202-2019-00001 3
 
0.2%
3310000-202-2020-00001 3
 
0.2%
3280000-202-2020-00001 3
 
0.2%
3360000-202-2019-00003 3
 
0.2%
3370000-202-2018-00003 2
 
0.1%
3340000-202-2001-00002 1
 
0.1%
3340000-202-2005-00006 1
 
0.1%
3340000-202-1989-01027 1
 
0.1%
3340000-202-1990-00795 1
 
0.1%
3340000-202-1991-01023 1
 
0.1%
Other values (1797) 1797
99.0%
2024-04-16T17:11:10.527620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15401
38.5%
2 5652
 
14.1%
- 5448
 
13.6%
3 3941
 
9.9%
1 2748
 
6.9%
9 2542
 
6.4%
8 1144
 
2.9%
4 944
 
2.4%
7 837
 
2.1%
5 695
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34504
86.4%
Dash Punctuation 5448
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15401
44.6%
2 5652
 
16.4%
3 3941
 
11.4%
1 2748
 
8.0%
9 2542
 
7.4%
8 1144
 
3.3%
4 944
 
2.7%
7 837
 
2.4%
5 695
 
2.0%
6 600
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15401
38.5%
2 5652
 
14.1%
- 5448
 
13.6%
3 3941
 
9.9%
1 2748
 
6.9%
9 2542
 
6.4%
8 1144
 
2.9%
4 944
 
2.4%
7 837
 
2.1%
5 695
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15401
38.5%
2 5652
 
14.1%
- 5448
 
13.6%
3 3941
 
9.9%
1 2748
 
6.9%
9 2542
 
6.4%
8 1144
 
2.9%
4 944
 
2.4%
7 837
 
2.1%
5 695
 
1.7%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
11_44_01_P
1816 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 1816
100.0%

Length

2024-04-16T17:11:10.639452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:10.709400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1816
100.0%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
I
1516 
U
300 

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 1516
83.5%
U 300
 
16.5%

Length

2024-04-16T17:11:10.782434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:10.858175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1516
83.5%
u 300
 
16.5%
Distinct188
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-03-31 02:40:00
2024-04-16T17:11:10.940232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T17:11:11.049113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1509 
목욕장업
307 

Length

Max length4
Median length4
Mean length4
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> 1509
83.1%
목욕장업 307
 
16.9%

Length

2024-04-16T17:11:11.156408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:11.236483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1509
83.1%
목욕장업 307
 
16.9%

bplcnm
Text

Distinct1135
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-16T17:11:11.479837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length3
Mean length4.1349119
Min length2

Characters and Unicode

Total characters7509
Distinct characters384
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

Unique888 ?
Unique (%)48.9%

Sample

1st row옥샘탕
2nd row금수탕
3rd row백록담
4th row유나목욕탕
5th row녹수탕
ValueCountFrequency (%)
사우나 23
 
1.2%
청수탕 21
 
1.1%
현대탕 21
 
1.1%
옥천탕 19
 
1.0%
산수탕 15
 
0.8%
천수탕 15
 
0.8%
목욕탕 15
 
0.8%
장수탕 14
 
0.7%
정수탕 13
 
0.7%
평화탕 13
 
0.7%
Other values (1190) 1799
91.4%
2024-04-16T17:11:11.848068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1368
 
18.2%
301
 
4.0%
226
 
3.0%
181
 
2.4%
177
 
2.4%
165
 
2.2%
155
 
2.1%
153
 
2.0%
122
 
1.6%
117
 
1.6%
Other values (374) 4544
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7230
96.3%
Space Separator 153
 
2.0%
Close Punctuation 39
 
0.5%
Open Punctuation 36
 
0.5%
Decimal Number 20
 
0.3%
Uppercase Letter 20
 
0.3%
Lowercase Letter 7
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1368
 
18.9%
301
 
4.2%
226
 
3.1%
181
 
2.5%
177
 
2.4%
165
 
2.3%
155
 
2.1%
122
 
1.7%
117
 
1.6%
111
 
1.5%
Other values (350) 4307
59.6%
Uppercase Letter
ValueCountFrequency (%)
G 5
25.0%
L 4
20.0%
O 2
 
10.0%
M 2
 
10.0%
B 1
 
5.0%
Y 1
 
5.0%
A 1
 
5.0%
W 1
 
5.0%
F 1
 
5.0%
S 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
d 1
14.3%
u 1
14.3%
r 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 11
55.0%
4 9
45.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7229
96.3%
Common 252
 
3.4%
Latin 27
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1368
 
18.9%
301
 
4.2%
226
 
3.1%
181
 
2.5%
177
 
2.4%
165
 
2.3%
155
 
2.1%
122
 
1.7%
117
 
1.6%
111
 
1.5%
Other values (349) 4306
59.6%
Latin
ValueCountFrequency (%)
G 5
18.5%
L 4
14.8%
o 2
 
7.4%
O 2
 
7.4%
n 2
 
7.4%
M 2
 
7.4%
B 1
 
3.7%
Y 1
 
3.7%
A 1
 
3.7%
W 1
 
3.7%
Other values (6) 6
22.2%
Common
ValueCountFrequency (%)
153
60.7%
) 39
 
15.5%
( 36
 
14.3%
2 11
 
4.4%
4 9
 
3.6%
- 2
 
0.8%
, 1
 
0.4%
. 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7229
96.3%
ASCII 279
 
3.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1368
 
18.9%
301
 
4.2%
226
 
3.1%
181
 
2.5%
177
 
2.4%
165
 
2.3%
155
 
2.1%
122
 
1.7%
117
 
1.6%
111
 
1.5%
Other values (349) 4306
59.6%
ASCII
ValueCountFrequency (%)
153
54.8%
) 39
 
14.0%
( 36
 
12.9%
2 11
 
3.9%
4 9
 
3.2%
G 5
 
1.8%
L 4
 
1.4%
o 2
 
0.7%
O 2
 
0.7%
n 2
 
0.7%
Other values (14) 16
 
5.7%
CJK
ValueCountFrequency (%)
1
100.0%

sitepostno
Real number (ℝ)

Distinct629
Distinct (%)34.7%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean610435.01
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:11.967436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601811
Q1606813
median611800
Q3614820.5
95-th percentile617834
Maximum619953
Range19942
Interquartile range (IQR)8007.5

Descriptive statistics

Standard deviation5156.9346
Coefficient of variation (CV)0.0084479667
Kurtosis-0.91027746
Mean610435.01
Median Absolute Deviation (MAD)3961
Skewness-0.20817228
Sum1.1054978 × 109
Variance26593975
MonotonicityNot monotonic
2024-04-16T17:11:12.080540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604851 15
 
0.8%
612846 12
 
0.7%
612847 12
 
0.7%
607833 10
 
0.6%
608828 10
 
0.6%
608808 10
 
0.6%
614822 10
 
0.6%
613805 9
 
0.5%
607826 9
 
0.5%
607832 9
 
0.5%
Other values (619) 1705
93.9%
ValueCountFrequency (%)
600011 1
 
0.1%
600012 1
 
0.1%
600017 1
 
0.1%
600021 1
 
0.1%
600022 4
0.2%
600023 1
 
0.1%
600025 1
 
0.1%
600032 1
 
0.1%
600042 1
 
0.1%
600044 1
 
0.1%
ValueCountFrequency (%)
619953 2
 
0.1%
619952 3
0.2%
619951 4
0.2%
619913 1
 
0.1%
619912 2
 
0.1%
619911 2
 
0.1%
619906 3
0.2%
619905 5
0.3%
619904 3
0.2%
619903 7
0.4%
Distinct1726
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-16T17:11:12.325065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length24.601322
Min length17

Characters and Unicode

Total characters44676
Distinct characters274
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

Unique1652 ?
Unique (%)91.0%

Sample

1st row부산광역시 중구 창선동1가 9-9번지
2nd row부산광역시 중구 중앙동4가 78-2번지
3rd row부산광역시 중구 대청동1가 34-1번지
4th row부산광역시 중구 신창동1가 5-1번지 (5~8층)
5th row부산광역시 중구 신창동2가 21-2번지
ValueCountFrequency (%)
부산광역시 1816
 
22.4%
t통b반 335
 
4.1%
부산진구 222
 
2.7%
사하구 171
 
2.1%
동래구 164
 
2.0%
해운대구 159
 
2.0%
남구 148
 
1.8%
연제구 131
 
1.6%
북구 123
 
1.5%
금정구 116
 
1.4%
Other values (2148) 4707
58.2%
2024-04-16T17:11:12.700613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8064
18.0%
2167
 
4.9%
2161
 
4.8%
2113
 
4.7%
1 1909
 
4.3%
1886
 
4.2%
1837
 
4.1%
1829
 
4.1%
1818
 
4.1%
1728
 
3.9%
Other values (264) 19164
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25188
56.4%
Decimal Number 8809
 
19.7%
Space Separator 8064
 
18.0%
Dash Punctuation 1688
 
3.8%
Uppercase Letter 683
 
1.5%
Other Punctuation 114
 
0.3%
Open Punctuation 61
 
0.1%
Close Punctuation 61
 
0.1%
Math Symbol 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2167
 
8.6%
2161
 
8.6%
2113
 
8.4%
1886
 
7.5%
1837
 
7.3%
1829
 
7.3%
1818
 
7.2%
1728
 
6.9%
1658
 
6.6%
386
 
1.5%
Other values (238) 7605
30.2%
Decimal Number
ValueCountFrequency (%)
1 1909
21.7%
2 1140
12.9%
3 993
11.3%
4 890
10.1%
5 785
8.9%
6 684
 
7.8%
7 649
 
7.4%
8 610
 
6.9%
0 608
 
6.9%
9 541
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 335
49.0%
A 2
 
0.3%
G 1
 
0.1%
I 1
 
0.1%
L 1
 
0.1%
W 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
@ 1
 
0.9%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
8064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1688
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25188
56.4%
Common 18804
42.1%
Latin 684
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2167
 
8.6%
2161
 
8.6%
2113
 
8.4%
1886
 
7.5%
1837
 
7.3%
1829
 
7.3%
1818
 
7.2%
1728
 
6.9%
1658
 
6.6%
386
 
1.5%
Other values (238) 7605
30.2%
Common
ValueCountFrequency (%)
8064
42.9%
1 1909
 
10.2%
- 1688
 
9.0%
2 1140
 
6.1%
3 993
 
5.3%
4 890
 
4.7%
5 785
 
4.2%
6 684
 
3.6%
7 649
 
3.5%
8 610
 
3.2%
Other values (8) 1392
 
7.4%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 335
49.0%
A 2
 
0.3%
G 1
 
0.1%
I 1
 
0.1%
L 1
 
0.1%
1
 
0.1%
W 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25188
56.4%
ASCII 19487
43.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8064
41.4%
1 1909
 
9.8%
- 1688
 
8.7%
2 1140
 
5.9%
3 993
 
5.1%
4 890
 
4.6%
5 785
 
4.0%
6 684
 
3.5%
7 649
 
3.3%
8 610
 
3.1%
Other values (15) 2075
 
10.6%
Hangul
ValueCountFrequency (%)
2167
 
8.6%
2161
 
8.6%
2113
 
8.4%
1886
 
7.5%
1837
 
7.3%
1829
 
7.3%
1818
 
7.2%
1728
 
6.9%
1658
 
6.6%
386
 
1.5%
Other values (238) 7605
30.2%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

Distinct877
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48267.277
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:13.030974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46317.75
Q147566.5
median48814
Q348947
95-th percentile49323.25
Maximum49523
Range3521
Interquartile range (IQR)1380.5

Descriptive statistics

Standard deviation935.9393
Coefficient of variation (CV)0.019390762
Kurtosis-0.55181229
Mean48267.277
Median Absolute Deviation (MAD)394
Skewness-0.84026849
Sum87653375
Variance875982.38
MonotonicityNot monotonic
2024-04-16T17:11:13.134442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 670
36.9%
48099 8
 
0.4%
47709 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
48531 4
 
0.2%
47142 4
 
0.2%
46308 4
 
0.2%
47712 4
 
0.2%
46275 4
 
0.2%
Other values (867) 1099
60.5%
ValueCountFrequency (%)
46002 1
0.1%
46008 1
0.1%
46015 1
0.1%
46017 1
0.1%
46020 1
0.1%
46032 1
0.1%
46033 1
0.1%
46036 2
0.1%
46037 2
0.1%
46040 1
0.1%
ValueCountFrequency (%)
49523 1
0.1%
49522 1
0.1%
49521 1
0.1%
49518 2
0.1%
49515 2
0.1%
49511 2
0.1%
49506 1
0.1%
49505 1
0.1%
49504 1
0.1%
49503 2
0.1%

rdnwhladdr
Text

MISSING 

Distinct1175
Distinct (%)98.1%
Missing618
Missing (%)34.0%
Memory size14.3 KiB
2024-04-16T17:11:13.445757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.48414
Min length20

Characters and Unicode

Total characters32926
Distinct characters334
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1158 ?
Unique (%)96.7%

Sample

1st row부산광역시 중구 광복로55번길 14-2 (창선동1가)
2nd row부산광역시 중구 광복중앙로 25 (신창동1가)
3rd row부산광역시 중구 광복로43번길 12 (신창동2가)
4th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
5th row부산광역시 중구 비프광장로 20, 10층 (남포동6가)
ValueCountFrequency (%)
부산광역시 1198
 
19.1%
부산진구 154
 
2.5%
남구 104
 
1.7%
해운대구 103
 
1.6%
사하구 100
 
1.6%
동래구 99
 
1.6%
연제구 85
 
1.4%
금정구 77
 
1.2%
북구 75
 
1.2%
사상구 71
 
1.1%
Other values (1712) 4211
67.1%
2024-04-16T17:11:13.887771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5080
 
15.4%
1521
 
4.6%
1454
 
4.4%
1452
 
4.4%
1265
 
3.8%
1257
 
3.8%
1227
 
3.7%
1201
 
3.6%
) 1184
 
3.6%
( 1184
 
3.6%
Other values (324) 16101
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19833
60.2%
Space Separator 5080
 
15.4%
Decimal Number 5070
 
15.4%
Close Punctuation 1187
 
3.6%
Open Punctuation 1187
 
3.6%
Other Punctuation 345
 
1.0%
Dash Punctuation 199
 
0.6%
Math Symbol 12
 
< 0.1%
Uppercase Letter 12
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1521
 
7.7%
1454
 
7.3%
1452
 
7.3%
1265
 
6.4%
1257
 
6.3%
1227
 
6.2%
1201
 
6.1%
1142
 
5.8%
709
 
3.6%
667
 
3.4%
Other values (296) 7938
40.0%
Decimal Number
ValueCountFrequency (%)
1 1147
22.6%
2 723
14.3%
3 626
12.3%
5 442
 
8.7%
4 434
 
8.6%
6 394
 
7.8%
0 380
 
7.5%
7 353
 
7.0%
9 287
 
5.7%
8 284
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
41.7%
A 4
33.3%
W 1
 
8.3%
I 1
 
8.3%
G 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 339
98.3%
* 3
 
0.9%
. 2
 
0.6%
@ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1184
99.7%
] 3
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1184
99.7%
[ 3
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 11
91.7%
1
 
8.3%
Space Separator
ValueCountFrequency (%)
5080
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19833
60.2%
Common 13080
39.7%
Latin 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1521
 
7.7%
1454
 
7.3%
1452
 
7.3%
1265
 
6.4%
1257
 
6.3%
1227
 
6.2%
1201
 
6.1%
1142
 
5.8%
709
 
3.6%
667
 
3.4%
Other values (296) 7938
40.0%
Common
ValueCountFrequency (%)
5080
38.8%
) 1184
 
9.1%
( 1184
 
9.1%
1 1147
 
8.8%
2 723
 
5.5%
3 626
 
4.8%
5 442
 
3.4%
4 434
 
3.3%
6 394
 
3.0%
0 380
 
2.9%
Other values (12) 1486
 
11.4%
Latin
ValueCountFrequency (%)
B 5
38.5%
A 4
30.8%
W 1
 
7.7%
I 1
 
7.7%
G 1
 
7.7%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19833
60.2%
ASCII 13091
39.8%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5080
38.8%
) 1184
 
9.0%
( 1184
 
9.0%
1 1147
 
8.8%
2 723
 
5.5%
3 626
 
4.8%
5 442
 
3.4%
4 434
 
3.3%
6 394
 
3.0%
0 380
 
2.9%
Other values (16) 1497
 
11.4%
Hangul
ValueCountFrequency (%)
1521
 
7.7%
1454
 
7.3%
1452
 
7.3%
1265
 
6.4%
1257
 
6.3%
1227
 
6.2%
1201
 
6.1%
1142
 
5.8%
709
 
3.6%
667
 
3.4%
Other values (296) 7938
40.0%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

Distinct1522
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19910285
Minimum19540131
Maximum20210316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:14.009101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700487
Q119830522
median19901204
Q320010344
95-th percentile20110110
Maximum20210316
Range670185
Interquartile range (IQR)179822

Descriptive statistics

Standard deviation123469.51
Coefficient of variation (CV)0.0062012928
Kurtosis-0.35331655
Mean19910285
Median Absolute Deviation (MAD)80902
Skewness-0.049082429
Sum3.6157078 × 1010
Variance1.524472 × 1010
MonotonicityNot monotonic
2024-04-16T17:11:14.119867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.8%
20001130 9
 
0.5%
19921202 8
 
0.4%
19971227 6
 
0.3%
19960710 6
 
0.3%
20000420 5
 
0.3%
19830304 5
 
0.3%
19820928 5
 
0.3%
20030115 5
 
0.3%
19630610 4
 
0.2%
Other values (1512) 1748
96.3%
ValueCountFrequency (%)
19540131 1
 
0.1%
19601210 3
 
0.2%
19630108 1
 
0.1%
19630109 3
 
0.2%
19630110 15
0.8%
19630610 4
 
0.2%
19631001 1
 
0.1%
19640211 1
 
0.1%
19640915 1
 
0.1%
19641015 1
 
0.1%
ValueCountFrequency (%)
20210316 1
 
0.1%
20201013 1
 
0.1%
20200924 1
 
0.1%
20200908 1
 
0.1%
20200827 1
 
0.1%
20200708 1
 
0.1%
20200703 3
0.2%
20200624 1
 
0.1%
20200619 3
0.2%
20200514 1
 
0.1%

dcbymd
Text

MISSING 

Distinct811
Distinct (%)82.2%
Missing829
Missing (%)45.6%
Memory size14.3 KiB
2024-04-16T17:11:14.362342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9189463
Min length4

Characters and Unicode

Total characters7816
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

Unique698 ?
Unique (%)70.7%

Sample

1st row20070612
2nd row20120221
3rd row20140401
4th row20131227
5th row20030703
ValueCountFrequency (%)
폐업일자 20
 
2.0%
20050121 12
 
1.2%
20051017 7
 
0.7%
20001130 7
 
0.7%
20170310 5
 
0.5%
20030401 5
 
0.5%
20141030 4
 
0.4%
20030122 4
 
0.4%
20120621 4
 
0.4%
20180102 3
 
0.3%
Other values (801) 916
92.8%
2024-04-16T17:11:14.716766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2611
33.4%
2 1605
20.5%
1 1400
17.9%
9 356
 
4.6%
3 350
 
4.5%
7 299
 
3.8%
5 294
 
3.8%
6 280
 
3.6%
8 277
 
3.5%
4 264
 
3.4%
Other values (4) 80
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7736
99.0%
Other Letter 80
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2611
33.8%
2 1605
20.7%
1 1400
18.1%
9 356
 
4.6%
3 350
 
4.5%
7 299
 
3.9%
5 294
 
3.8%
6 280
 
3.6%
8 277
 
3.6%
4 264
 
3.4%
Other Letter
ValueCountFrequency (%)
20
25.0%
20
25.0%
20
25.0%
20
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7736
99.0%
Hangul 80
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2611
33.8%
2 1605
20.7%
1 1400
18.1%
9 356
 
4.6%
3 350
 
4.5%
7 299
 
3.9%
5 294
 
3.8%
6 280
 
3.6%
8 277
 
3.6%
4 264
 
3.4%
Hangul
ValueCountFrequency (%)
20
25.0%
20
25.0%
20
25.0%
20
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7736
99.0%
Hangul 80
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2611
33.8%
2 1605
20.7%
1 1400
18.1%
9 356
 
4.6%
3 350
 
4.5%
7 299
 
3.9%
5 294
 
3.8%
6 280
 
3.6%
8 277
 
3.6%
4 264
 
3.4%
Hangul
ValueCountFrequency (%)
20
25.0%
20
25.0%
20
25.0%
20
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1792 
휴업시작일자
 
24

Length

Max length6
Median length4
Mean length4.0264317
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> 1792
98.7%
휴업시작일자 24
 
1.3%

Length

2024-04-16T17:11:14.837929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:14.922939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1792
98.7%
휴업시작일자 24
 
1.3%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1792 
휴업종료일자
 
24

Length

Max length6
Median length4
Mean length4.0264317
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> 1792
98.7%
휴업종료일자 24
 
1.3%

Length

2024-04-16T17:11:15.011699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:15.098055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1792
98.7%
휴업종료일자 24
 
1.3%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1792 
재개업일자
 
24

Length

Max length5
Median length4
Mean length4.0132159
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> 1792
98.7%
재개업일자 24
 
1.3%

Length

2024-04-16T17:11:15.194056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:15.277983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1792
98.7%
재개업일자 24
 
1.3%

trdstatenm
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
02
925 
01
584 
영업/정상
263 
폐업
 
42
<NA>
 
2

Length

Max length5
Median length2
Mean length2.436674
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01
2nd row02
3rd row02
4th row02
5th row01

Common Values

ValueCountFrequency (%)
02 925
50.9%
01 584
32.2%
영업/정상 263
 
14.5%
폐업 42
 
2.3%
<NA> 2
 
0.1%

Length

2024-04-16T17:11:15.358699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:15.447676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 925
50.9%
01 584
32.2%
영업/정상 263
 
14.5%
폐업 42
 
2.3%
na 2
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
967 
영업
849 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 967
53.2%
영업 849
46.8%

Length

2024-04-16T17:11:15.536639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:15.622383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 967
53.2%
영업 849
46.8%

x
Text

MISSING 

Distinct1670
Distinct (%)95.9%
Missing75
Missing (%)4.1%
Memory size14.3 KiB
2024-04-16T17:11:15.794274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.992533
Min length7

Characters and Unicode

Total characters34807
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

Unique1612 ?
Unique (%)92.6%

Sample

1st row385089.38491100000
2nd row385793.29931
3rd row385208.257554
4th row385157.86566400000
5th row385086.62014400000
ValueCountFrequency (%)
387810.283167969 4
 
0.2%
389727.58350700000 4
 
0.2%
389394.976154 4
 
0.2%
390974.056399381 4
 
0.2%
391906.711100 3
 
0.2%
386099.535234 3
 
0.2%
370674.351397752 3
 
0.2%
386501.470234 3
 
0.2%
390237.659277726 3
 
0.2%
379480.101157 2
 
0.1%
Other values (1660) 1708
98.1%
2024-04-16T17:11:16.082460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6801
19.5%
0 6261
18.0%
3 3533
10.2%
8 2869
8.2%
9 2522
 
7.2%
7 1947
 
5.6%
2 1873
 
5.4%
4 1830
 
5.3%
5 1814
 
5.2%
1 1809
 
5.2%
Other values (9) 3548
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26259
75.4%
Space Separator 6801
 
19.5%
Other Punctuation 1740
 
5.0%
Other Letter 4
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6261
23.8%
3 3533
13.5%
8 2869
10.9%
9 2522
9.6%
7 1947
 
7.4%
2 1873
 
7.1%
4 1830
 
7.0%
5 1814
 
6.9%
1 1809
 
6.9%
6 1801
 
6.9%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
6801
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1740
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34802
> 99.9%
Hangul 4
 
< 0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6801
19.5%
0 6261
18.0%
3 3533
10.2%
8 2869
8.2%
9 2522
 
7.2%
7 1947
 
5.6%
2 1873
 
5.4%
4 1830
 
5.3%
5 1814
 
5.2%
1 1809
 
5.2%
Other values (4) 3543
10.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34803
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6801
19.5%
0 6261
18.0%
3 3533
10.2%
8 2869
8.2%
9 2522
 
7.2%
7 1947
 
5.6%
2 1873
 
5.4%
4 1830
 
5.3%
5 1814
 
5.2%
1 1809
 
5.2%
Other values (5) 3544
10.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

y
Text

MISSING 

Distinct1670
Distinct (%)95.9%
Missing75
Missing (%)4.1%
Memory size14.3 KiB
2024-04-16T17:11:16.269389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.992533
Min length7

Characters and Unicode

Total characters34807
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

Unique1612 ?
Unique (%)92.6%

Sample

1st row180062.56761800000
2nd row180910.386636
3rd row180108.034984
4th row180248.21457300000
5th row180119.33406400000
ValueCountFrequency (%)
179178.742589729 4
 
0.2%
191654.34294400000 4
 
0.2%
193519.152183 4
 
0.2%
182797.894969615 4
 
0.2%
189495.497384 3
 
0.2%
181890.404844 3
 
0.2%
184448.198703368 3
 
0.2%
189887.738381 3
 
0.2%
195579.465881184 3
 
0.2%
177881.672180 2
 
0.1%
Other values (1660) 1708
98.1%
2024-04-16T17:11:16.553698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6788
19.5%
0 6228
17.9%
1 3550
10.2%
8 2769
8.0%
9 2408
 
6.9%
7 2239
 
6.4%
6 1880
 
5.4%
4 1843
 
5.3%
3 1840
 
5.3%
2 1768
 
5.1%
Other values (9) 3494
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26272
75.5%
Space Separator 6788
 
19.5%
Other Punctuation 1740
 
5.0%
Other Letter 4
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6228
23.7%
1 3550
13.5%
8 2769
10.5%
9 2408
 
9.2%
7 2239
 
8.5%
6 1880
 
7.2%
4 1843
 
7.0%
3 1840
 
7.0%
2 1768
 
6.7%
5 1747
 
6.6%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
6788
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1740
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34802
> 99.9%
Hangul 4
 
< 0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6788
19.5%
0 6228
17.9%
1 3550
10.2%
8 2769
8.0%
9 2408
 
6.9%
7 2239
 
6.4%
6 1880
 
5.4%
4 1843
 
5.3%
3 1840
 
5.3%
2 1768
 
5.1%
Other values (4) 3489
10.0%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34803
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6788
19.5%
0 6228
17.9%
1 3550
10.2%
8 2769
8.0%
9 2408
 
6.9%
7 2239
 
6.4%
6 1880
 
5.4%
4 1843
 
5.3%
3 1840
 
5.3%
2 1768
 
5.1%
Other values (5) 3490
10.0%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

lastmodts
Real number (ℝ)

Distinct1485
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0113855 × 1013
Minimum1.999021 × 1013
Maximum2.0210329 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-16T17:11:16.668843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020422 × 1013
Q12.0041208 × 1013
median2.0121018 × 1013
Q32.0170731 × 1013
95-th percentile2.0201047 × 1013
Maximum2.0210329 × 1013
Range2.2011911 × 1011
Interquartile range (IQR)1.2952313 × 1011

Descriptive statistics

Standard deviation6.4478505 × 1010
Coefficient of variation (CV)0.0032056762
Kurtosis-1.3153059
Mean2.0113855 × 1013
Median Absolute Deviation (MAD)5.9694993 × 1010
Skewness-0.19456287
Sum3.6526761 × 1016
Variance4.1574777 × 1021
MonotonicityNot monotonic
2024-04-16T17:11:16.793396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030409000000 29
 
1.6%
20020418000000 27
 
1.5%
20040318000000 15
 
0.8%
20050415000000 14
 
0.8%
20031217000000 12
 
0.7%
20030303000000 12
 
0.7%
20040324000000 11
 
0.6%
20020422000000 10
 
0.6%
20041208000000 9
 
0.5%
20030722000000 8
 
0.4%
Other values (1475) 1669
91.9%
ValueCountFrequency (%)
19990210000000 2
 
0.1%
19990212000000 1
 
0.1%
19990302000000 7
0.4%
19990310000000 6
0.3%
19990315000000 1
 
0.1%
19990325000000 2
 
0.1%
19990420000000 2
 
0.1%
19990421000000 7
0.4%
19990422000000 1
 
0.1%
19990427000000 1
 
0.1%
ValueCountFrequency (%)
20210329113559 1
0.1%
20210326155252 1
0.1%
20210326153452 1
0.1%
20210326140305 1
0.1%
20210325153422 1
0.1%
20210325134216 1
0.1%
20210324100549 1
0.1%
20210323162348 1
0.1%
20210323140801 1
0.1%
20210323131238 1
0.1%

uptaenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
공동탕업
1537 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
78
한증막업
 
35
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.715859
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1537
84.6%
목욕장업 기타 155
 
8.5%
공동탕업+찜질시설서비스영업 78
 
4.3%
한증막업 35
 
1.9%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-16T17:11:16.901410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:16.985655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1537
78.0%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 78
 
4.0%
한증막업 35
 
1.8%
찜질시설서비스영업 11
 
0.6%
Distinct99
Distinct (%)5.5%
Missing9
Missing (%)0.5%
Memory size14.3 KiB
2024-04-16T17:11:17.216160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.963475
Min length4

Characters and Unicode

Total characters21618
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

Unique96 ?
Unique (%)5.3%

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 1706
87.6%
051 95
 
4.9%
962 3
 
0.2%
4011 3
 
0.2%
204 2
 
0.1%
7667 2
 
0.1%
667 2
 
0.1%
271 2
 
0.1%
5437413 1
 
0.1%
8900 1
 
0.1%
Other values (130) 130
 
6.7%
2024-04-16T17:11:17.564615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5298
24.5%
3 3483
16.1%
2 3479
16.1%
- 3412
15.8%
0 1884
 
8.7%
5 1871
 
8.7%
4 1768
 
8.2%
143
 
0.7%
6 82
 
0.4%
7 67
 
0.3%
Other values (6) 131
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18059
83.5%
Dash Punctuation 3412
 
15.8%
Space Separator 143
 
0.7%
Other Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5298
29.3%
3 3483
19.3%
2 3479
19.3%
0 1884
 
10.4%
5 1871
 
10.4%
4 1768
 
9.8%
6 82
 
0.5%
7 67
 
0.4%
9 65
 
0.4%
8 62
 
0.3%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3412
100.0%
Space Separator
ValueCountFrequency (%)
143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21614
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5298
24.5%
3 3483
16.1%
2 3479
16.1%
- 3412
15.8%
0 1884
 
8.7%
5 1871
 
8.7%
4 1768
 
8.2%
143
 
0.7%
6 82
 
0.4%
7 67
 
0.3%
Other values (2) 127
 
0.6%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21614
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5298
24.5%
3 3483
16.1%
2 3479
16.1%
- 3412
15.8%
0 1884
 
8.7%
5 1871
 
8.7%
4 1768
 
8.2%
143
 
0.7%
6 82
 
0.4%
7 67
 
0.3%
Other values (2) 127
 
0.6%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1398 
자가
273 
임대
 
128
건물소유구분명
 
17

Length

Max length7
Median length4
Mean length3.5864537
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1398
77.0%
자가 273
 
15.0%
임대 128
 
7.0%
건물소유구분명 17
 
0.9%

Length

2024-04-16T17:11:17.667114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:17.749088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1398
77.0%
자가 273
 
15.0%
임대 128
 
7.0%
건물소유구분명 17
 
0.9%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
462 
0
322 
3
300 
4
208 
5
133 
Other values (30)
391 

Length

Max length6
Median length1
Mean length1.8122247
Min length1

Unique

Unique11 ?
Unique (%)0.6%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row9
5th row4

Common Values

ValueCountFrequency (%)
<NA> 462
25.4%
0 322
17.7%
3 300
16.5%
4 208
11.5%
5 133
 
7.3%
2 133
 
7.3%
6 51
 
2.8%
7 48
 
2.6%
8 29
 
1.6%
1 25
 
1.4%
Other values (25) 105
 
5.8%

Length

2024-04-16T17:11:17.838599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 462
25.4%
0 322
17.7%
3 300
16.5%
4 208
11.5%
5 133
 
7.3%
2 133
 
7.3%
6 51
 
2.8%
7 48
 
2.6%
8 29
 
1.6%
1 25
 
1.4%
Other values (25) 105
 
5.8%

bdngunderflrcnt
Categorical

Distinct10
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
703 
0
510 
1
461 
2
77 
3
 
29
Other values (5)
 
36

Length

Max length6
Median length1
Mean length2.1640969
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 703
38.7%
0 510
28.1%
1 461
25.4%
2 77
 
4.2%
3 29
 
1.6%
4 16
 
0.9%
5 9
 
0.5%
6 9
 
0.5%
7 1
 
0.1%
건물지하층수 1
 
0.1%

Length

2024-04-16T17:11:17.928540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:18.021833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 703
38.7%
0 510
28.1%
1 461
25.4%
2 77
 
4.2%
3 29
 
1.6%
4 16
 
0.9%
5 9
 
0.5%
6 9
 
0.5%
7 1
 
0.1%
건물지하층수 1
 
0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1749 
0
 
47
남성종사자수
 
15
1
 
3
4
 
1

Length

Max length6
Median length4
Mean length3.9306167
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1749
96.3%
0 47
 
2.6%
남성종사자수 15
 
0.8%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-16T17:11:18.124757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:18.205849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1749
96.3%
0 47
 
2.6%
남성종사자수 15
 
0.8%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1782 
True
 
34
ValueCountFrequency (%)
False 1782
98.1%
True 34
 
1.9%
2024-04-16T17:11:18.280623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size3.7 KiB
False
1360 
True
454 
(Missing)
 
2
ValueCountFrequency (%)
False 1360
74.9%
True 454
 
25.0%
(Missing) 2
 
0.1%
2024-04-16T17:11:18.342762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct14
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
790 
2
383 
3
208 
0
158 
1
92 
Other values (9)
185 

Length

Max length6
Median length1
Mean length2.3265419
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row8
5th row4

Common Values

ValueCountFrequency (%)
<NA> 790
43.5%
2 383
21.1%
3 208
 
11.5%
0 158
 
8.7%
1 92
 
5.1%
4 84
 
4.6%
5 48
 
2.6%
6 21
 
1.2%
7 11
 
0.6%
사용끝지상층 7
 
0.4%
Other values (4) 14
 
0.8%

Length

2024-04-16T17:11:18.444139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 790
43.5%
2 383
21.1%
3 208
 
11.5%
0 158
 
8.7%
1 92
 
5.1%
4 84
 
4.6%
5 48
 
2.6%
6 21
 
1.2%
7 11
 
0.6%
사용끝지상층 7
 
0.4%
Other values (4) 14
 
0.8%

useunderendflr
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1232 
0
483 
1
 
69
2
 
21
사용끝지하층
 
7
Other values (2)
 
4

Length

Max length6
Median length4
Mean length3.0545154
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1232
67.8%
0 483
 
26.6%
1 69
 
3.8%
2 21
 
1.2%
사용끝지하층 7
 
0.4%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-16T17:11:18.534037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:18.621670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1232
67.8%
0 483
 
26.6%
1 69
 
3.8%
2 21
 
1.2%
사용끝지하층 7
 
0.4%
3 3
 
0.2%
4 1
 
0.1%

usejisgstflr
Categorical

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
652 
1
368 
0
327 
2
302 
3
79 
Other values (7)
88 

Length

Max length7
Median length1
Mean length2.0919604
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row5
5th row2

Common Values

ValueCountFrequency (%)
<NA> 652
35.9%
1 368
20.3%
0 327
18.0%
2 302
16.6%
3 79
 
4.4%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
0.7%
8 4
 
0.2%
사용시작지상층 4
 
0.2%
Other values (2) 5
 
0.3%

Length

2024-04-16T17:11:18.717420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 652
35.9%
1 368
20.3%
0 327
18.0%
2 302
16.6%
3 79
 
4.4%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
0.7%
8 4
 
0.2%
사용시작지상층 4
 
0.2%
Other values (2) 5
 
0.3%

useunderstflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
974 
0
745 
1
 
80
2
 
9
사용시작지하층
 
5

Length

Max length7
Median length4
Mean length2.6255507
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 974
53.6%
0 745
41.0%
1 80
 
4.4%
2 9
 
0.5%
사용시작지하층 5
 
0.3%
3 3
 
0.2%

Length

2024-04-16T17:11:18.817946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:18.928541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 974
53.6%
0 745
41.0%
1 80
 
4.4%
2 9
 
0.5%
사용시작지하층 5
 
0.3%
3 3
 
0.2%

washmccnt
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1235 
0
578 
세탁기수
 
3

Length

Max length4
Median length4
Mean length3.0451542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1235
68.0%
0 578
31.8%
세탁기수 3
 
0.2%

Length

2024-04-16T17:11:19.048043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:19.153693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1235
68.0%
0 578
31.8%
세탁기수 3
 
0.2%

yangsilcnt
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
972 
0
843 
양실수
 
1

Length

Max length4
Median length4
Mean length2.6068282
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 972
53.5%
0 843
46.4%
양실수 1
 
0.1%

Length

2024-04-16T17:11:19.262869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:19.358354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 972
53.5%
0 843
46.4%
양실수 1
 
0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1749 
0
 
47
여성종사자수
 
15
2
 
2
1
 
1
Other values (2)
 
2

Length

Max length6
Median length4
Mean length3.9306167
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1749
96.3%
0 47
 
2.6%
여성종사자수 15
 
0.8%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-16T17:11:19.439821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:19.530060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1749
96.3%
0 47
 
2.6%
여성종사자수 15
 
0.8%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

yoksilcnt
Categorical

IMBALANCE 

Distinct19
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
639 
0
592 
2
472 
6
 
28
4
 
27
Other values (14)
 
58

Length

Max length4
Median length1
Mean length2.064978
Min length1

Unique

Unique6 ?
Unique (%)0.3%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row2
5th row0

Common Values

ValueCountFrequency (%)
<NA> 639
35.2%
0 592
32.6%
2 472
26.0%
6 28
 
1.5%
4 27
 
1.5%
1 19
 
1.0%
8 13
 
0.7%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
Other values (9) 12
 
0.7%

Length

2024-04-16T17:11:19.868433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 639
35.2%
0 592
32.6%
2 472
26.0%
6 28
 
1.5%
4 27
 
1.5%
1 19
 
1.0%
8 13
 
0.7%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
Other values (9) 12
 
0.7%

sntuptaenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
공동탕업
1537 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
78
한증막업
 
35
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.715859
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1537
84.6%
목욕장업 기타 155
 
8.5%
공동탕업+찜질시설서비스영업 78
 
4.3%
한증막업 35
 
1.9%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-16T17:11:19.963048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.047057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1537
78.0%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 78
 
4.0%
한증막업 35
 
1.8%
찜질시설서비스영업 11
 
0.6%

chaircnt
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
972 
0
842 
의자수
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.6068282
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 972
53.5%
0 842
46.4%
의자수 1
 
0.1%
2 1
 
0.1%

Length

2024-04-16T17:11:20.141390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.223098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 972
53.5%
0 842
46.4%
의자수 1
 
0.1%
2 1
 
0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1791 
조건부허가시작일자
 
24
20190501
 
1

Length

Max length9
Median length4
Mean length4.0682819
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> 1791
98.6%
조건부허가시작일자 24
 
1.3%
20190501 1
 
0.1%

Length

2024-04-16T17:11:20.320540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.403761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1791
98.6%
조건부허가시작일자 24
 
1.3%
20190501 1
 
0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1791 
조건부허가신고사유
 
24
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
 
1

Length

Max length36
Median length4
Mean length4.0837004
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> 1791
98.6%
조건부허가신고사유 24
 
1.3%
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고 1
 
0.1%

Length

2024-04-16T17:11:20.490232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.572598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1791
98.5%
조건부허가신고사유 24
 
1.3%
건축과-16824(2019.4.15),가설건축물 1
 
0.1%
존치기간연장 1
 
0.1%
신고 1
 
0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1791 
조건부허가종료일자
 
24
20210421
 
1

Length

Max length9
Median length4
Mean length4.0682819
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> 1791
98.6%
조건부허가종료일자 24
 
1.3%
20210421 1
 
0.1%

Length

2024-04-16T17:11:20.658635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.737365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1791
98.6%
조건부허가종료일자 24
 
1.3%
20210421 1
 
0.1%

abedcnt
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1262 
0
550 
침대수
 
4

Length

Max length4
Median length4
Mean length3.089207
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1262
69.5%
0 550
30.3%
침대수 4
 
0.2%

Length

2024-04-16T17:11:20.825659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:20.914260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1262
69.5%
0 550
30.3%
침대수 4
 
0.2%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
972 
0
843 
한실수
 
1

Length

Max length4
Median length4
Mean length2.6068282
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 972
53.5%
0 843
46.4%
한실수 1
 
0.1%

Length

2024-04-16T17:11:21.000980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:21.084256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 972
53.5%
0 843
46.4%
한실수 1
 
0.1%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1261 
0
551 
회수건조수
 
4

Length

Max length5
Median length4
Mean length3.0919604
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1261
69.4%
0 551
30.3%
회수건조수 4
 
0.2%

Length

2024-04-16T17:11:21.172765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:21.271945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1261
69.4%
0 551
30.3%
회수건조수 4
 
0.2%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2021-04-01 05:11:03
Maximum2021-04-01 05:11:03
2024-04-16T17:11:21.357479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T17:11:21.446707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0332500003250000-202-2002-0000111_44_01_PI2018-08-31 23:59:59.0<NA>옥샘탕600051부산광역시 중구 창선동1가 9-9번지48947부산광역시 중구 광복로55번길 14-2 (창선동1가)20020513<NA><NA><NA><NA>01영업385089.38491100000180062.5676180000020180724131551공동탕업+찜질시설서비스영업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-04-01 05:11:03
1432500003250000-202-1985-0015611_44_01_PI2018-08-31 23:59:59.0<NA>금수탕600816부산광역시 중구 중앙동4가 78-2번지48947<NA>1985040920070612<NA><NA><NA>02폐업385793.29931180910.38663620041116000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:11:03
2532500003250000-202-2001-0001311_44_01_PI2018-08-31 23:59:59.0<NA>백록담600091부산광역시 중구 대청동1가 34-1번지48947<NA>2001111620120221<NA><NA><NA>02폐업385208.257554180108.03498420120227093749공동탕업+찜질시설서비스영업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업+찜질시설서비스영업<NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:11:03
3632500003250000-202-2007-0000111_44_01_PI2018-08-31 23:59:59.0<NA>유나목욕탕600061부산광역시 중구 신창동1가 5-1번지 (5~8층)48948부산광역시 중구 광복중앙로 25 (신창동1가)2007040620140401<NA><NA><NA>02폐업385157.86566400000180248.2145730000020130208113918공동탕업+찜질시설서비스영업051-123-1234자가93<NA>NY805000<NA>2공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-04-01 05:11:03
4732500003250000-202-1988-0015911_44_01_PI2018-08-31 23:59:59.0<NA>녹수탕600062부산광역시 중구 신창동2가 21-2번지48947부산광역시 중구 광복로43번길 12 (신창동2가)19880913<NA><NA><NA><NA>01영업385086.62014400000180119.3340640000020130208111503공동탕업051-123-1234임대41<NA>NN402000<NA>0공동탕업0<NA><NA><NA>0002021-04-01 05:11:03
5832500003250000-202-1960-0014411_44_01_PU2018-11-30 02:40:00.0목욕장업금강스파600808부산광역시 중구 부평동3가 22-1번지 외 2필지48976부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)19601210<NA><NA><NA><NA>영업/정상영업384542.121201746179994.20210389820181128093116공동탕업+찜질시설서비스영업051-123-1234<NA>51<NA>NN515100<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-04-01 05:11:03
6932500003250000-202-2009-0000111_44_01_PI2018-08-31 23:59:59.0<NA>오투(O2)600046부산광역시 중구 남포동6가 85번지 (10층)48981부산광역시 중구 비프광장로 20, 10층 (남포동6가)2009022320131227<NA><NA><NA>02폐업384892.63184400000179895.5128170000020130208114221공동탕업+찜질시설서비스영업051-123-1234임대104<NA>NY10010000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-04-01 05:11:03
71032500003250000-202-1984-0015411_44_01_PI2018-08-31 23:59:59.0<NA>영진사우나600045부산광역시 중구 남포동5가 88번지48947<NA>1984020120030703<NA><NA><NA>02폐업384910.466574179447.22650620030703000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:11:03
81132500003250000-202-1984-0015211_44_01_PI2018-08-31 23:59:59.0<NA>거북목욕탕600110부산광역시 중구 영주동 292-10번지48916부산광역시 중구 영주로 20 (영주동)19840217<NA><NA><NA><NA>01영업385241.59002600000181147.1401790000020130208111357공동탕업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업0<NA><NA><NA>0002021-04-01 05:11:03
91232500003250000-202-1973-0015011_44_01_PI2018-08-31 23:59:59.0<NA>부원탕600101부산광역시 중구 대창동1가 54-2번지48947<NA>1973011220051013<NA><NA><NA>02폐업<NA><NA>20040531000000공동탕업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:11:03
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1806209733300003330000-202-2020-0000111_44_01_PU2021-03-25 02:40:00.0목욕장업(주)호텔롯데 시그니엘 부산612010부산광역시 해운대구 중동 1829 엘시티48099부산광역시 해운대구 달맞이길 30, 포디움동 6층 602호 (중동, 엘시티)20200624폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업좌표정보(X)좌표정보(Y)20210323125848목욕장업 기타05192210000건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0006목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:11:03
1807210032800003280000-202-2020-0000111_44_01_PU2021-01-20 02:40:00.0목욕장업김천탕606822부산광역시 영도구 청학동 252-13649014부산광역시 영도구 청학로 62 (청학동)[*미고시]20200703<NA><NA><NA><NA>영업/정상영업387810.283167969179178.74258972920210118091801목욕장업 기타051 962 4011<NA>00<NA>NY302000<NA>2목욕장업 기타0<NA><NA><NA>0002021-04-01 05:11:03
1808210132800003280000-202-2020-0000111_44_01_PU2021-01-20 02:40:00.0목욕장업김천탕606822부산광역시 영도구 청학동 252-13649014부산광역시 영도구 청학로 62 (청학동)[*미고시]20200703<NA><NA><NA><NA>영업/정상영업387810.283167969179178.74258972920210118091801목욕장업 기타051 962 4011<NA>00<NA>NY302000<NA>2목욕장업 기타0<NA><NA><NA>0002021-04-01 05:11:03
1809210232800003280000-202-2020-0000111_44_01_PU2021-01-20 02:40:00.0목욕장업김천탕606822부산광역시 영도구 청학동 252-13649014부산광역시 영도구 청학로 62 (청학동)[*미고시]20200703<NA><NA><NA><NA>영업/정상영업387810.283167969179178.74258972920210118091801목욕장업 기타051 962 4011<NA>00<NA>NY302000<NA>2목욕장업 기타0<NA><NA><NA>0002021-04-01 05:11:03
1810210432900003290000-202-2020-0000111_44_01_PU2020-08-08 02:40:00.0목욕장업우성스마트사우나614859부산광역시 부산진구 연지동 42-4 연지우성스마트시티뷰47123부산광역시 부산진구 동평로 269, 2층 201호 (연지동, 연지우성스마트시티뷰)20200708<NA><NA><NA><NA>영업/정상영업387301.611272345187722.85966300320200806111714공동탕업051-123-1234<NA>2110NN20200002공동탕업0<NA><NA><NA>0002021-04-01 05:11:03
1811213133100003310000-202-2020-0000211_44_01_PU2020-10-15 02:40:00.0목욕장업(주)벽승 명성사우나608830부산광역시 남구 용당동 564-5 한신문화타운 2층48535부산광역시 남구 유엔평화로 150, 한신문화타운 2층 (용당동)20200827<NA><NA><NA><NA>영업/정상영업391103.422349355182446.17047299120201013154141공동탕업<NA>자가410NN2<NA>2<NA>0002공동탕업0<NA><NA><NA>0002021-04-01 05:11:03
1812213633300003330000-202-2020-0000211_44_01_PU2021-01-27 02:40:00.0목욕장업(주)조선호텔앤리조트 그랜드조선 부산 사우나612846부산광역시 해운대구 중동 1405-16 그랜드 조선 부산48099부산광역시 해운대구 해운대해변로 292, 그랜드 조선 부산 6층 (중동)20200908<NA><NA><NA><NA>영업/정상영업397022.971550345186692.0646219620210125144914목욕장업 기타<NA><NA>000NN<NA><NA>6<NA>0006목욕장업 기타0<NA><NA><NA>0002021-04-01 05:11:03
1813214334000003400000-202-2020-0000211_44_01_PU2021-02-04 02:40:00.0목욕장업월내탕619951부산광역시 기장군 장안읍 월내리 132-4946037부산광역시 기장군 장안읍 해맞이로 368, 3~4층20200924<NA><NA><NA><NA>영업/정상영업406982.053033795205366.77000216120210202173923공동탕업<NA><NA>000NN4<NA>3<NA>0000공동탕업0<NA><NA><NA>0002021-04-01 05:11:03
1814215032700003270000-202-2020-0000111_44_01_PU2020-11-12 02:40:00.0목욕장업주)더스포 현대백화점 부산점 별관 현대휘트니스601803부산광역시 동구 범일동 62-26048734부산광역시 동구 범일일길 47, 현대휘트니스센터 지하1층 (범일동)20201013<NA><NA><NA><NA>영업/정상영업387485.832510158184380.86148619420201110135045공동탕업+찜질시설서비스영업051 667 0098<NA>520NY<NA>2<NA>20004공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-04-01 05:11:03
1815221632900003290000-202-2021-0000111_44_01_PI2021-03-18 00:22:59.0목욕장업약수탕614842부산광역시 부산진구 부전동 393-2747248부산광역시 부산진구 새싹로 50-1, 지하1층 (부전동)20210316폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업387262.574745332186696.2031794620210316155345목욕장업 기타전화번호임대510NN사용끝지상층1사용시작지상층10000목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:11:03