Overview

Dataset statistics

Number of variables79
Number of observations10000
Missing cells511626
Missing cells (%)64.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 MiB
Average record size in memory670.0 B

Variable types

Unsupported40
Numeric5
Text20
Categorical10
DateTime2
Boolean2

Alerts

bdngsrvnm has constant value ""Constant
cnstyarea has constant value ""Constant
culwrkrsenm has constant value ""Constant
afc has constant value ""Constant
shpcnt has constant value ""Constant
jtupsomainedf has constant value ""Constant
nearenvnm has constant value ""Constant
jisgnumlay has constant value ""Constant
undernumlay has constant value ""Constant
totnumlay has constant value ""Constant
opnsvcid is highly imbalanced (73.4%)Imbalance
updategbn is highly imbalanced (99.1%)Imbalance
dtlstatenm is highly imbalanced (50.9%)Imbalance
sitetel is highly imbalanced (99.5%)Imbalance
wtrsplyfacilsenm is highly imbalanced (60.1%)Imbalance
multusnupsoyn is highly imbalanced (84.5%)Imbalance
lvsenm is highly imbalanced (52.0%)Imbalance
culphyedcobnm is highly imbalanced (98.8%)Imbalance
trdpjubnsenm is highly imbalanced (54.0%)Imbalance
opnsvcnm has 9984 (99.8%) missing valuesMissing
sitepostno has 144 (1.4%) missing valuesMissing
rdnwhladdr has 3698 (37.0%) missing valuesMissing
dcbymd has 3989 (39.9%) missing valuesMissing
clgstdt has 10000 (100.0%) missing valuesMissing
clgenddt has 10000 (100.0%) missing valuesMissing
ropnymd has 10000 (100.0%) missing valuesMissing
x has 406 (4.1%) missing valuesMissing
y has 405 (4.0%) missing valuesMissing
stroomcnt has 10000 (100.0%) missing valuesMissing
bdngownsenm has 10000 (100.0%) missing valuesMissing
bdngsrvnm has 9999 (> 99.9%) missing valuesMissing
cnstyarea has 9999 (> 99.9%) missing valuesMissing
fctyowkepcnt has 9994 (99.9%) missing valuesMissing
fctypdtjobepcnt has 9995 (> 99.9%) missing valuesMissing
fctysiljobepcnt has 9995 (> 99.9%) missing valuesMissing
svnsr has 10000 (100.0%) missing valuesMissing
plninsurstdt has 10000 (100.0%) missing valuesMissing
plninsurenddt has 10000 (100.0%) missing valuesMissing
maneipcnt has 6507 (65.1%) missing valuesMissing
playutscntdtl has 10000 (100.0%) missing valuesMissing
playfacilcnt has 10000 (100.0%) missing valuesMissing
stagear has 10000 (100.0%) missing valuesMissing
culwrkrsenm has 9998 (> 99.9%) missing valuesMissing
geicpfacilen has 10000 (100.0%) missing valuesMissing
bcfacilen has 10000 (100.0%) missing valuesMissing
isream has 9994 (99.9%) missing valuesMissing
insurorgnm has 10000 (100.0%) missing valuesMissing
insurstdt has 10000 (100.0%) missing valuesMissing
insurenddt has 10000 (100.0%) missing valuesMissing
hoffepcnt has 9995 (> 99.9%) missing valuesMissing
afc has 9999 (> 99.9%) missing valuesMissing
shpinfo has 10000 (100.0%) missing valuesMissing
shpcnt has 9999 (> 99.9%) missing valuesMissing
shptottons has 10000 (100.0%) missing valuesMissing
facilscp has 9998 (> 99.9%) missing valuesMissing
facilar has 9998 (> 99.9%) missing valuesMissing
infoben has 10000 (100.0%) missing valuesMissing
wmeipcnt has 6483 (64.8%) missing valuesMissing
engstntrnmnm has 9996 (> 99.9%) missing valuesMissing
engstntrnmaddr has 9997 (> 99.9%) missing valuesMissing
monam has 9995 (> 99.9%) missing valuesMissing
dispenen has 10000 (100.0%) missing valuesMissing
capt has 9997 (> 99.9%) missing valuesMissing
jtupsomainedf has 9999 (> 99.9%) missing valuesMissing
jtupsoasgnno has 9998 (> 99.9%) missing valuesMissing
mnfactreartclcn has 10000 (100.0%) missing valuesMissing
chaircnt has 10000 (100.0%) missing valuesMissing
nearenvnm has 9999 (> 99.9%) missing valuesMissing
jisgnumlay has 9999 (> 99.9%) missing valuesMissing
regnsenm has 9998 (> 99.9%) missing valuesMissing
undernumlay has 9999 (> 99.9%) missing valuesMissing
totepnum has 10000 (100.0%) missing valuesMissing
totnumlay has 9999 (> 99.9%) missing valuesMissing
homepage has 10000 (100.0%) missing valuesMissing
meetsamtimesygstf has 10000 (100.0%) missing valuesMissing
opnsfteamcode is highly skewed (γ1 = 80.3298487)Skewed
sitepostno is highly skewed (γ1 = -24.38656834)Skewed
rdnpostno is highly skewed (γ1 = 99.9899995)Skewed
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
opnsvcnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
dcbymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
clgstdt is an unsupported type, check if it needs cleaning or further analysisUnsupported
clgenddt is an unsupported type, check if it needs cleaning or further analysisUnsupported
ropnymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
trdstatenm is an unsupported type, check if it needs cleaning or further analysisUnsupported
y is an unsupported type, check if it needs cleaning or further analysisUnsupported
stroomcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
bdngownsenm is an unsupported type, check if it needs cleaning or further analysisUnsupported
fctyowkepcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
fctypdtjobepcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
fctysiljobepcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
svnsr is an unsupported type, check if it needs cleaning or further analysisUnsupported
plninsurstdt is an unsupported type, check if it needs cleaning or further analysisUnsupported
plninsurenddt is an unsupported type, check if it needs cleaning or further analysisUnsupported
maneipcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
playutscntdtl is an unsupported type, check if it needs cleaning or further analysisUnsupported
playfacilcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
stagear is an unsupported type, check if it needs cleaning or further analysisUnsupported
geicpfacilen is an unsupported type, check if it needs cleaning or further analysisUnsupported
bcfacilen is an unsupported type, check if it needs cleaning or further analysisUnsupported
isream is an unsupported type, check if it needs cleaning or further analysisUnsupported
insurorgnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
insurstdt is an unsupported type, check if it needs cleaning or further analysisUnsupported
insurenddt is an unsupported type, check if it needs cleaning or further analysisUnsupported
hoffepcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
shpinfo is an unsupported type, check if it needs cleaning or further analysisUnsupported
shptottons is an unsupported type, check if it needs cleaning or further analysisUnsupported
faciltotscp is an unsupported type, check if it needs cleaning or further analysisUnsupported
infoben is an unsupported type, check if it needs cleaning or further analysisUnsupported
wmeipcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
monam is an unsupported type, check if it needs cleaning or further analysisUnsupported
dispenen is an unsupported type, check if it needs cleaning or further analysisUnsupported
mnfactreartclcn is an unsupported type, check if it needs cleaning or further analysisUnsupported
chaircnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
totepnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
homepage is an unsupported type, check if it needs cleaning or further analysisUnsupported
meetsamtimesygstf is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 15:24:28.792583
Analysis finished2024-04-17 15:24:30.836970
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

opnsfteamcode
Real number (ℝ)

SKEWED 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3318384.1
Minimum3050000
Maximum20140605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T00:24:30.887744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3050000
5-th percentile3250000
Q13280000
median3310000
Q33350000
95-th percentile3390000
Maximum20140605
Range17090605
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation181671.31
Coefficient of variation (CV)0.054746921
Kurtosis7364.8804
Mean3318384.1
Median Absolute Deviation (MAD)40000
Skewness80.329849
Sum3.3183841 × 1010
Variance3.3004464 × 1010
MonotonicityNot monotonic
2024-04-18T00:24:30.983098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3250000 1605
16.1%
3290000 1241
12.4%
3330000 1240
12.4%
3300000 748
 
7.5%
3350000 636
 
6.4%
3390000 574
 
5.7%
3320000 519
 
5.2%
3380000 510
 
5.1%
3310000 501
 
5.0%
3340000 495
 
5.0%
Other values (20) 1931
19.3%
ValueCountFrequency (%)
3050000 1
 
< 0.1%
3130000 1
 
< 0.1%
3180000 1
 
< 0.1%
3250000 1605
16.1%
3260000 281
 
2.8%
3270000 419
 
4.2%
3280000 242
 
2.4%
3290000 1241
12.4%
3300000 748
7.5%
3310000 501
 
5.0%
ValueCountFrequency (%)
20140605 1
< 0.1%
5670000 2
< 0.1%
5540000 1
< 0.1%
5350000 1
< 0.1%
5340000 1
< 0.1%
4090000 1
< 0.1%
3990000 1
< 0.1%
3900000 1
< 0.1%
3660000 2
< 0.1%
3620000 1
< 0.1%

mgtno
Text

Distinct9998
Distinct (%)> 99.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T00:24:31.208343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.9978
Min length20

Characters and Unicode

Total characters219956
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9997 ?
Unique (%)> 99.9%

Sample

1st row3360000-104-2014-00027
2nd row3370000-104-2016-00023
3rd row3340000-104-2010-00030
4th row3300000-104-2002-00025
5th row3300000-104-2012-00019
ValueCountFrequency (%)
cdfi3261032012000001 2
 
< 0.1%
3290000-104-2011-00177 1
 
< 0.1%
3320000-104-2017-00088 1
 
< 0.1%
3390000-104-1986-02827 1
 
< 0.1%
3270000-104-2010-00017 1
 
< 0.1%
3330000-104-2018-00140 1
 
< 0.1%
3290000-104-2014-00025 1
 
< 0.1%
3300000-104-1982-00309 1
 
< 0.1%
3320000-104-2013-00025 1
 
< 0.1%
3290000-104-2004-00030 1
 
< 0.1%
Other values (9988) 9988
99.9%
2024-04-18T00:24:31.706059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86530
39.3%
- 29964
 
13.6%
1 24992
 
11.4%
3 21015
 
9.6%
2 15818
 
7.2%
4 13400
 
6.1%
9 9308
 
4.2%
5 5839
 
2.7%
8 4649
 
2.1%
7 4414
 
2.0%
Other values (5) 4027
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189948
86.4%
Dash Punctuation 29964
 
13.6%
Uppercase Letter 44
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86530
45.6%
1 24992
 
13.2%
3 21015
 
11.1%
2 15818
 
8.3%
4 13400
 
7.1%
9 9308
 
4.9%
5 5839
 
3.1%
8 4649
 
2.4%
7 4414
 
2.3%
6 3983
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
C 11
25.0%
D 11
25.0%
F 11
25.0%
I 11
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 29964
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 219912
> 99.9%
Latin 44
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86530
39.3%
- 29964
 
13.6%
1 24992
 
11.4%
3 21015
 
9.6%
2 15818
 
7.2%
4 13400
 
6.1%
9 9308
 
4.2%
5 5839
 
2.7%
8 4649
 
2.1%
7 4414
 
2.0%
Latin
ValueCountFrequency (%)
C 11
25.0%
D 11
25.0%
F 11
25.0%
I 11
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 219956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86530
39.3%
- 29964
 
13.6%
1 24992
 
11.4%
3 21015
 
9.6%
2 15818
 
7.2%
4 13400
 
6.1%
9 9308
 
4.2%
5 5839
 
2.7%
8 4649
 
2.1%
7 4414
 
2.0%
Other values (5) 4027
 
1.8%

opnsvcid
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_24_05_P
8825 
07_24_04_P
1163 
07_24_03_P
 
11
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9994
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row07_24_05_P
2nd row07_24_05_P
3rd row07_24_05_P
4th row07_24_05_P
5th row07_24_05_P

Common Values

ValueCountFrequency (%)
07_24_05_P 8825
88.2%
07_24_04_P 1163
 
11.6%
07_24_03_P 11
 
0.1%
<NA> 1
 
< 0.1%

Length

2024-04-18T00:24:31.826504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:31.913314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_24_05_p 8825
88.2%
07_24_04_p 1163
 
11.6%
07_24_03_p 11
 
0.1%
na 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9987 
U
 
12
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0003
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 9987
99.9%
U 12
 
0.1%
<NA> 1
 
< 0.1%

Length

2024-04-18T00:24:31.995891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:32.069707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9987
99.9%
u 12
 
0.1%
na 1
 
< 0.1%

updatedt
Date

Distinct6
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2018-10-21 02:37:41
2024-04-18T00:24:32.132534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:24:32.207100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

opnsvcnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9984
Missing (%)99.8%
Memory size156.2 KiB

bplcnm
Text

Distinct8771
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T00:24:32.454065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length6.2798
Min length1

Characters and Unicode

Total characters62798
Distinct characters1036
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8049 ?
Unique (%)80.5%

Sample

1st row까페가야
2nd row피자토모
3rd row그릴피아
4th row스넥바
5th row(주)롤뺑브레드
ValueCountFrequency (%)
카페 66
 
0.5%
gs25 64
 
0.5%
롯데리아 45
 
0.4%
coffee 44
 
0.4%
미니스톱 40
 
0.3%
스타벅스 36
 
0.3%
씨유 34
 
0.3%
커피 32
 
0.3%
세븐일레븐 23
 
0.2%
cafe 23
 
0.2%
Other values (9295) 11792
96.7%
2024-04-18T00:24:32.832788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2216
 
3.5%
점 2042
 
3.3%
스 1923
 
3.1%
피 1429
 
2.3%
이 1300
 
2.1%
커 1221
 
1.9%
리 1126
 
1.8%
) 968
 
1.5%
( 961
 
1.5%
아 704
 
1.1%
Other values (1026) 48908
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53197
84.7%
Space Separator 2216
 
3.5%
Uppercase Letter 2165
 
3.4%
Lowercase Letter 2024
 
3.2%
Decimal Number 1040
 
1.7%
Close Punctuation 972
 
1.5%
Open Punctuation 965
 
1.5%
Other Punctuation 175
 
0.3%
Dash Punctuation 35
 
0.1%
Modifier Symbol 3
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2042
 
3.8%
스 1923
 
3.6%
피 1429
 
2.7%
이 1300
 
2.4%
커 1221
 
2.3%
리 1126
 
2.1%
아 704
 
1.3%
카 688
 
1.3%
산 685
 
1.3%
다 675
 
1.3%
Other values (939) 41404
77.8%
Lowercase Letter
ValueCountFrequency (%)
e 360
17.8%
a 214
10.6%
o 209
10.3%
f 187
9.2%
c 137
 
6.8%
n 105
 
5.2%
i 96
 
4.7%
r 93
 
4.6%
s 87
 
4.3%
t 84
 
4.2%
Other values (16) 452
22.3%
Uppercase Letter
ValueCountFrequency (%)
C 295
13.6%
S 240
11.1%
G 212
 
9.8%
P 153
 
7.1%
E 150
 
6.9%
O 121
 
5.6%
T 110
 
5.1%
F 101
 
4.7%
A 101
 
4.7%
B 97
 
4.5%
Other values (16) 585
27.0%
Other Punctuation
ValueCountFrequency (%)
& 56
32.0%
. 44
25.1%
, 24
13.7%
' 15
 
8.6%
! 9
 
5.1%
: 8
 
4.6%
/ 7
 
4.0%
· 3
 
1.7%
? 2
 
1.1%
" 2
 
1.1%
Other values (4) 5
 
2.9%
Decimal Number
ValueCountFrequency (%)
2 300
28.8%
5 238
22.9%
1 137
13.2%
0 93
 
8.9%
3 70
 
6.7%
9 62
 
6.0%
8 43
 
4.1%
7 40
 
3.8%
4 32
 
3.1%
6 25
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 968
99.6%
] 4
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 961
99.6%
[ 4
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
2216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Other Symbol
ValueCountFrequency (%)
� 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53183
84.7%
Common 5411
 
8.6%
Latin 4190
 
6.7%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2042
 
3.8%
스 1923
 
3.6%
피 1429
 
2.7%
이 1300
 
2.4%
커 1221
 
2.3%
리 1126
 
2.1%
아 704
 
1.3%
카 688
 
1.3%
산 685
 
1.3%
다 675
 
1.3%
Other values (927) 41390
77.8%
Latin
ValueCountFrequency (%)
e 360
 
8.6%
C 295
 
7.0%
S 240
 
5.7%
a 214
 
5.1%
G 212
 
5.1%
o 209
 
5.0%
f 187
 
4.5%
P 153
 
3.7%
E 150
 
3.6%
c 137
 
3.3%
Other values (43) 2033
48.5%
Common
ValueCountFrequency (%)
2216
41.0%
) 968
17.9%
( 961
17.8%
2 300
 
5.5%
5 238
 
4.4%
1 137
 
2.5%
0 93
 
1.7%
3 70
 
1.3%
9 62
 
1.1%
& 56
 
1.0%
Other values (24) 310
 
5.7%
Han
ValueCountFrequency (%)
人 2
14.3%
愛 2
14.3%
花 1
7.1%
茶 1
7.1%
顔 1
7.1%
觀 1
7.1%
色 1
7.1%
味 1
7.1%
好 1
7.1%
安 1
7.1%
Other values (2) 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53181
84.7%
ASCII 9594
 
15.3%
CJK 13
 
< 0.1%
None 4
 
< 0.1%
Specials 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2216
23.1%
) 968
 
10.1%
( 961
 
10.0%
e 360
 
3.8%
2 300
 
3.1%
C 295
 
3.1%
S 240
 
2.5%
5 238
 
2.5%
a 214
 
2.2%
G 212
 
2.2%
Other values (73) 3590
37.4%
Hangul
ValueCountFrequency (%)
점 2042
 
3.8%
스 1923
 
3.6%
피 1429
 
2.7%
이 1300
 
2.4%
커 1221
 
2.3%
리 1126
 
2.1%
아 704
 
1.3%
카 688
 
1.3%
산 685
 
1.3%
다 675
 
1.3%
Other values (925) 41388
77.8%
None
ValueCountFrequency (%)
· 3
75.0%
＆ 1
 
25.0%
Specials
ValueCountFrequency (%)
� 2
100.0%
CJK
ValueCountFrequency (%)
人 2
15.4%
愛 2
15.4%
花 1
7.7%
顔 1
7.7%
觀 1
7.7%
色 1
7.7%
味 1
7.7%
好 1
7.7%
安 1
7.7%
林 1
7.7%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
50.0%
ㅍ 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
茶 1
100.0%

sitepostno
Real number (ℝ)

MISSING  SKEWED 

Distinct845
Distinct (%)8.6%
Missing144
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean609401.9
Minimum121889
Maximum703848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T00:24:32.950207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum121889
5-th percentile600044
Q1604822
median611070
Q3614817
95-th percentile617837
Maximum703848
Range581959
Interquartile range (IQR)9995

Descriptive statistics

Standard deviation11946.559
Coefficient of variation (CV)0.019603745
Kurtosis878.70108
Mean609401.9
Median Absolute Deviation (MAD)3783
Skewness-24.386568
Sum6.0062651 × 109
Variance1.4272028 × 108
MonotonicityNot monotonic
2024-04-18T00:24:33.048595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020.0 318
 
3.2%
600045.0 119
 
1.2%
614847.0 104
 
1.0%
614845.0 87
 
0.9%
614846.0 82
 
0.8%
609839.0 82
 
0.8%
600046.0 82
 
0.8%
600806.0 75
 
0.8%
607804.0 75
 
0.8%
616852.0 73
 
0.7%
Other values (835) 8759
87.6%
(Missing) 144
 
1.4%
ValueCountFrequency (%)
121889.0 1
< 0.1%
130851.0 1
< 0.1%
150095.0 1
< 0.1%
302834.0 2
< 0.1%
394015.453851 1
< 0.1%
415808.0 1
< 0.1%
423849.0 1
< 0.1%
464873.0 1
< 0.1%
472842.0 1
< 0.1%
500887.0 1
< 0.1%
ValueCountFrequency (%)
703848.0 1
 
< 0.1%
664823.0 1
 
< 0.1%
642832.0 1
 
< 0.1%
630857.0 1
 
< 0.1%
621901.0 1
 
< 0.1%
619953.0 19
0.2%
619952.0 7
 
0.1%
619951.0 21
0.2%
619913.0 7
 
0.1%
619912.0 16
0.2%

sitewhladdr
Text

Distinct8406
Distinct (%)84.2%
Missing18
Missing (%)0.2%
Memory size156.2 KiB
2024-04-18T00:24:33.297101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length58
Mean length25.455119
Min length13

Characters and Unicode

Total characters254093
Distinct characters508
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7653 ?
Unique (%)76.7%

Sample

1st row부산광역시 강서구 지사동 1190-7번지
2nd row부산광역시 연제구 연산동 1805-6번지
3rd row부산광역시 사하구 신평동 165-3번지 (장평로 303)
4th row부산광역시 동래구 온천동 137-0 번지
5th row부산광역시 동래구 명륜동 529-4번지
ValueCountFrequency (%)
부산광역시 9966
 
21.6%
중구 1605
 
3.5%
부산진구 1241
 
2.7%
해운대구 1234
 
2.7%
동래구 748
 
1.6%
금정구 635
 
1.4%
1층 631
 
1.4%
우동 606
 
1.3%
사상구 574
 
1.2%
북구 519
 
1.1%
Other values (8394) 28305
61.4%
2024-04-18T00:24:33.666146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45655
18.0%
부 12738
 
5.0%
1 12067
 
4.7%
산 11863
 
4.7%
동 11541
 
4.5%
지 11051
 
4.3%
광 10428
 
4.1%
시 10171
 
4.0%
번 10025
 
3.9%
역 10012
 
3.9%
Other values (498) 108542
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147380
58.0%
Decimal Number 49757
 
19.6%
Space Separator 45655
 
18.0%
Dash Punctuation 8705
 
3.4%
Open Punctuation 794
 
0.3%
Close Punctuation 792
 
0.3%
Other Punctuation 601
 
0.2%
Uppercase Letter 351
 
0.1%
Math Symbol 32
 
< 0.1%
Lowercase Letter 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 12738
 
8.6%
산 11863
 
8.0%
동 11541
 
7.8%
지 11051
 
7.5%
광 10428
 
7.1%
시 10171
 
6.9%
번 10025
 
6.8%
역 10012
 
6.8%
구 9888
 
6.7%
가 2245
 
1.5%
Other values (442) 47418
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 91
25.9%
A 77
21.9%
S 34
 
9.7%
G 25
 
7.1%
C 25
 
7.1%
K 17
 
4.8%
D 12
 
3.4%
L 11
 
3.1%
E 10
 
2.8%
T 7
 
2.0%
Other values (15) 42
12.0%
Decimal Number
ValueCountFrequency (%)
1 12067
24.3%
2 7073
14.2%
3 5366
10.8%
4 4583
 
9.2%
5 4462
 
9.0%
0 4104
 
8.2%
6 3350
 
6.7%
7 3116
 
6.3%
9 2844
 
5.7%
8 2792
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
e 9
37.5%
c 5
20.8%
p 3
 
12.5%
m 1
 
4.2%
v 1
 
4.2%
q 1
 
4.2%
k 1
 
4.2%
d 1
 
4.2%
b 1
 
4.2%
u 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 548
91.2%
. 32
 
5.3%
@ 13
 
2.2%
/ 7
 
1.2%
' 1
 
0.2%
Space Separator
ValueCountFrequency (%)
45655
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8705
100.0%
Open Punctuation
ValueCountFrequency (%)
( 794
100.0%
Close Punctuation
ValueCountFrequency (%)
) 792
100.0%
Math Symbol
ValueCountFrequency (%)
~ 32
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147380
58.0%
Common 106336
41.8%
Latin 377
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 12738
 
8.6%
산 11863
 
8.0%
동 11541
 
7.8%
지 11051
 
7.5%
광 10428
 
7.1%
시 10171
 
6.9%
번 10025
 
6.8%
역 10012
 
6.8%
구 9888
 
6.7%
가 2245
 
1.5%
Other values (442) 47418
32.2%
Latin
ValueCountFrequency (%)
B 91
24.1%
A 77
20.4%
S 34
 
9.0%
G 25
 
6.6%
C 25
 
6.6%
K 17
 
4.5%
D 12
 
3.2%
L 11
 
2.9%
E 10
 
2.7%
e 9
 
2.4%
Other values (26) 66
17.5%
Common
ValueCountFrequency (%)
45655
42.9%
1 12067
 
11.3%
- 8705
 
8.2%
2 7073
 
6.7%
3 5366
 
5.0%
4 4583
 
4.3%
5 4462
 
4.2%
0 4104
 
3.9%
6 3350
 
3.2%
7 3116
 
2.9%
Other values (10) 7855
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147380
58.0%
ASCII 106711
42.0%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45655
42.8%
1 12067
 
11.3%
- 8705
 
8.2%
2 7073
 
6.6%
3 5366
 
5.0%
4 4583
 
4.3%
5 4462
 
4.2%
0 4104
 
3.8%
6 3350
 
3.1%
7 3116
 
2.9%
Other values (45) 8230
 
7.7%
Hangul
ValueCountFrequency (%)
부 12738
 
8.6%
산 11863
 
8.0%
동 11541
 
7.8%
지 11051
 
7.5%
광 10428
 
7.1%
시 10171
 
6.9%
번 10025
 
6.8%
역 10012
 
6.8%
구 9888
 
6.7%
가 2245
 
1.5%
Other values (442) 47418
32.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

rdnpostno
Real number (ℝ)

SKEWED 

Distinct1386
Distinct (%)13.9%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.016484 × 109
Minimum2555
Maximum2.0160324 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T00:24:33.778576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2555
5-th percentile46268.4
Q147736
median48947
Q348947
95-th percentile49109.3
Maximum2.0160324 × 1013
Range2.0160324 × 1013
Interquartile range (IQR)1211

Descriptive statistics

Standard deviation2.016234 × 1011
Coefficient of variation (CV)99.987607
Kurtosis9998
Mean2.016484 × 109
Median Absolute Deviation (MAD)209
Skewness99.989999
Sum2.0160807 × 1013
Variance4.0651997 × 1022
MonotonicityNot monotonic
2024-04-18T00:24:33.886867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 3852
38.5%
48058 176
 
1.8%
48060 175
 
1.8%
48953 84
 
0.8%
48944 67
 
0.7%
48983 66
 
0.7%
47285 58
 
0.6%
48059 57
 
0.6%
48977 55
 
0.5%
48980 48
 
0.5%
Other values (1376) 5360
53.6%
ValueCountFrequency (%)
2555 1
 
< 0.1%
4006 1
 
< 0.1%
7285 1
 
< 0.1%
10113 1
 
< 0.1%
12193 1
 
< 0.1%
12800 1
 
< 0.1%
14306 1
 
< 0.1%
35204 2
< 0.1%
41835 1
 
< 0.1%
46004 3
< 0.1%
ValueCountFrequency (%)
20160324134003 1
 
< 0.1%
61024 1
 
< 0.1%
51495 1
 
< 0.1%
51230 1
 
< 0.1%
50905 1
 
< 0.1%
49525 3
< 0.1%
49524 4
< 0.1%
49523 1
 
< 0.1%
49522 3
< 0.1%
49521 6
0.1%

rdnwhladdr
Text

MISSING 

Distinct5778
Distinct (%)91.7%
Missing3698
Missing (%)37.0%
Memory size156.2 KiB
2024-04-18T00:24:34.195874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length53
Mean length31.764995
Min length8

Characters and Unicode

Total characters200183
Distinct characters556
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5513 ?
Unique (%)87.5%

Sample

1st row부산광역시 강서구 과학산단로334번다길 54 (지사동)
2nd row부산광역시 연제구 연수로 232, 2층 (연산동)
3rd row부산광역시 사하구 장평로 303 (신평동,(장평로 303))
4th row부산광역시 동래구 충렬대로 186 (명륜동)
5th row부산광역시 서구 구덕로148번길 2 (토성동5가)
ValueCountFrequency (%)
부산광역시 6286
 
16.2%
1층 1578
 
4.1%
해운대구 981
 
2.5%
중구 977
 
2.5%
부산진구 702
 
1.8%
우동 521
 
1.3%
금정구 419
 
1.1%
동래구 406
 
1.0%
2층 373
 
1.0%
남구 356
 
0.9%
Other values (5180) 26103
67.4%
2024-04-18T00:24:34.622640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32420
 
16.2%
1 8771
 
4.4%
부 8228
 
4.1%
동 7861
 
3.9%
산 7566
 
3.8%
광 7031
 
3.5%
시 6791
 
3.4%
구 6430
 
3.2%
역 6333
 
3.2%
( 6311
 
3.2%
Other values (546) 102441
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116847
58.4%
Space Separator 32420
 
16.2%
Decimal Number 30390
 
15.2%
Open Punctuation 6312
 
3.2%
Close Punctuation 6307
 
3.2%
Other Punctuation 5626
 
2.8%
Dash Punctuation 1119
 
0.6%
Uppercase Letter 1069
 
0.5%
Math Symbol 64
 
< 0.1%
Lowercase Letter 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 8228
 
7.0%
동 7861
 
6.7%
산 7566
 
6.5%
광 7031
 
6.0%
시 6791
 
5.8%
구 6430
 
5.5%
역 6333
 
5.4%
로 6137
 
5.3%
대 3588
 
3.1%
층 3304
 
2.8%
Other values (483) 53578
45.9%
Uppercase Letter
ValueCountFrequency (%)
A 254
23.8%
C 197
18.4%
E 176
16.5%
P 167
15.6%
B 108
10.1%
S 40
 
3.7%
G 27
 
2.5%
K 22
 
2.1%
D 19
 
1.8%
N 16
 
1.5%
Other values (15) 43
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
29.6%
c 4
14.8%
p 3
 
11.1%
b 2
 
7.4%
s 2
 
7.4%
g 1
 
3.7%
k 1
 
3.7%
y 1
 
3.7%
m 1
 
3.7%
v 1
 
3.7%
Other values (3) 3
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 8771
28.9%
2 4584
15.1%
3 3100
 
10.2%
5 2521
 
8.3%
0 2459
 
8.1%
4 2441
 
8.0%
6 1952
 
6.4%
7 1761
 
5.8%
9 1449
 
4.8%
8 1352
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 5582
99.2%
. 23
 
0.4%
@ 11
 
0.2%
· 4
 
0.1%
/ 4
 
0.1%
' 1
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6311
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6306
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
32420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1119
100.0%
Math Symbol
ValueCountFrequency (%)
~ 64
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116847
58.4%
Common 82238
41.1%
Latin 1098
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 8228
 
7.0%
동 7861
 
6.7%
산 7566
 
6.5%
광 7031
 
6.0%
시 6791
 
5.8%
구 6430
 
5.5%
역 6333
 
5.4%
로 6137
 
5.3%
대 3588
 
3.1%
층 3304
 
2.8%
Other values (483) 53578
45.9%
Latin
ValueCountFrequency (%)
A 254
23.1%
C 197
17.9%
E 176
16.0%
P 167
15.2%
B 108
9.8%
S 40
 
3.6%
G 27
 
2.5%
K 22
 
2.0%
D 19
 
1.7%
N 16
 
1.5%
Other values (29) 72
 
6.6%
Common
ValueCountFrequency (%)
32420
39.4%
1 8771
 
10.7%
( 6311
 
7.7%
) 6306
 
7.7%
, 5582
 
6.8%
2 4584
 
5.6%
3 3100
 
3.8%
5 2521
 
3.1%
0 2459
 
3.0%
4 2441
 
3.0%
Other values (14) 7743
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116847
58.4%
ASCII 83330
41.6%
None 4
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32420
38.9%
1 8771
 
10.5%
( 6311
 
7.6%
) 6306
 
7.6%
, 5582
 
6.7%
2 4584
 
5.5%
3 3100
 
3.7%
5 2521
 
3.0%
0 2459
 
3.0%
4 2441
 
2.9%
Other values (51) 8835
 
10.6%
Hangul
ValueCountFrequency (%)
부 8228
 
7.0%
동 7861
 
6.7%
산 7566
 
6.5%
광 7031
 
6.0%
시 6791
 
5.8%
구 6430
 
5.5%
역 6333
 
5.4%
로 6137
 
5.3%
대 3588
 
3.1%
층 3304
 
2.8%
Other values (483) 53578
45.9%
None
ValueCountFrequency (%)
· 4
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)< 0.1%
Memory size156.2 KiB

dcbymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3989
Missing (%)39.9%
Memory size156.2 KiB

clgstdt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

clgenddt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

ropnymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

trdstatenm
Unsupported

REJECTED  UNSUPPORTED 

Missing19
Missing (%)0.2%
Memory size156.2 KiB

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6011 
영업
3979 
영업중
 
6
<NA>
 
4

Length

Max length4
Median length2
Mean length2.0014
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6011
60.1%
영업 3979
39.8%
영업중 6
 
0.1%
<NA> 4
 
< 0.1%

Length

2024-04-18T00:24:34.740584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:34.820009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6011
60.1%
영업 3979
39.8%
영업중 6
 
0.1%
na 4
 
< 0.1%

x
Real number (ℝ)

MISSING 

Distinct7171
Distinct (%)74.7%
Missing406
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean388001.53
Minimum175704.53
Maximum408252.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T00:24:34.912775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum175704.53
5-th percentile379919.34
Q1384833.11
median387743.23
Q3391582.09
95-th percentile398177.76
Maximum408252.77
Range232548.23
Interquartile range (IQR)6748.9855

Descriptive statistics

Standard deviation8173.3679
Coefficient of variation (CV)0.021065298
Kurtosis273.46555
Mean388001.53
Median Absolute Deviation (MAD)3154.8914
Skewness-11.961152
Sum3.7224867 × 109
Variance66803943
MonotonicityNot monotonic
2024-04-18T00:24:35.031959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394606.582838 129
 
1.3%
394015.453851 107
 
1.1%
385717.579204 68
 
0.7%
387443.214568 52
 
0.5%
385031.067292 32
 
0.3%
387612.492814 32
 
0.3%
387613.573156 30
 
0.3%
393787.86262 27
 
0.3%
389523.288257 23
 
0.2%
389173.570969 22
 
0.2%
Other values (7161) 9072
90.7%
(Missing) 406
 
4.1%
ValueCountFrequency (%)
175704.533721103 1
< 0.1%
188598.600783 1
< 0.1%
189400.704318891 1
< 0.1%
189835.868160807 1
< 0.1%
191164.349860721 1
< 0.1%
204081.282117393 1
< 0.1%
228920.722830276 1
< 0.1%
232440.396943765 1
< 0.1%
234729.708066 2
< 0.1%
289027.871120612 1
< 0.1%
ValueCountFrequency (%)
408252.767077 1
< 0.1%
407842.679078 1
< 0.1%
407827.905111 1
< 0.1%
407817.759035 1
< 0.1%
407665.640005 1
< 0.1%
407603.019866 1
< 0.1%
407076.234671 1
< 0.1%
407071.768163 1
< 0.1%
407035.27809 1
< 0.1%
407025.985224 1
< 0.1%

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing405
Missing (%)4.0%
Memory size156.2 KiB

lastmodts
Real number (ℝ)

Distinct8031
Distinct (%)80.3%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0109671 × 1013
Minimum1.9990211 × 1013
Maximum2.0181019 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T00:24:35.156617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0000228 × 1013
Q12.0040604 × 1013
median2.0130716 × 1013
Q32.0170412 × 1013
95-th percentile2.0180626 × 1013
Maximum2.0181019 × 1013
Range1.9080811 × 1011
Interquartile range (IQR)1.2980838 × 1011

Descriptive statistics

Standard deviation6.4795935 × 1010
Coefficient of variation (CV)0.003222128
Kurtosis-1.2357487
Mean2.0109671 × 1013
Median Absolute Deviation (MAD)4.0407059 × 1010
Skewness-0.54440526
Sum2.0101627 × 1017
Variance4.1985132 × 1021
MonotonicityNot monotonic
2024-04-18T00:24:35.263035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020228000000 111
 
1.1%
20020827000000 73
 
0.7%
19990318000000 70
 
0.7%
20010803000000 59
 
0.6%
20010823000000 58
 
0.6%
20020110000000 48
 
0.5%
19990317000000 39
 
0.4%
20020225000000 35
 
0.4%
20011224000000 33
 
0.3%
20011221000000 32
 
0.3%
Other values (8021) 9438
94.4%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990225000000 1
 
< 0.1%
19990303000000 9
0.1%
19990304000000 10
0.1%
19990305000000 18
0.2%
19990308000000 4
 
< 0.1%
19990309000000 1
 
< 0.1%
19990310000000 2
 
< 0.1%
19990311000000 2
 
< 0.1%
19990312000000 6
 
0.1%
ValueCountFrequency (%)
20181019105253 1
< 0.1%
20181019104705 1
< 0.1%
20181019104536 1
< 0.1%
20181019104150 1
< 0.1%
20181019103921 1
< 0.1%
20181018115357 1
< 0.1%
20181018113348 1
< 0.1%
20181018110317 1
< 0.1%
20181017121857 1
< 0.1%
20181017120317 1
< 0.1%

uptaenm
Categorical

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
2176 
다방
1618 
일반조리판매
1557 
기타 휴게음식점
1289 
과자점
1012 
Other values (33)
2348 

Length

Max length15
Median length10
Mean length4.0579
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row기타 휴게음식점
2nd row기타 휴게음식점
3rd row일반조리판매
4th row일반조리판매
5th row커피숍

Common Values

ValueCountFrequency (%)
커피숍 2176
21.8%
다방 1618
16.2%
일반조리판매 1557
15.6%
기타 휴게음식점 1289
12.9%
과자점 1012
10.1%
패스트푸드 633
 
6.3%
한식 537
 
5.4%
경양식 225
 
2.2%
편의점 213
 
2.1%
푸드트럭 106
 
1.1%
Other values (28) 634
 
6.3%

Length

2024-04-18T00:24:35.369787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2176
19.3%
다방 1618
14.3%
일반조리판매 1557
13.8%
기타 1361
12.1%
휴게음식점 1289
11.4%
과자점 1012
9.0%
패스트푸드 633
 
5.6%
한식 537
 
4.8%
경양식 225
 
2.0%
편의점 213
 
1.9%
Other values (28) 668
 
5.9%

sitetel
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
051-123-1234
9996 
<NA>
 
4

Length

Max length12
Median length12
Mean length11.9968
Min length4

Unique

Unique0 ?
Unique (%)0.0%

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 9996
> 99.9%
<NA> 4
 
< 0.1%

Length

2024-04-18T00:24:35.465172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:35.536535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 9996
> 99.9%
na 4
 
< 0.1%

stroomcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

bdngownsenm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

bdngsrvnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:35.617501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row근린생활시설
ValueCountFrequency (%)
근린생활시설 1
100.0%
2024-04-18T00:24:35.800211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
근 1
16.7%
린 1
16.7%
생 1
16.7%
활 1
16.7%
시 1
16.7%
설 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
근 1
16.7%
린 1
16.7%
생 1
16.7%
활 1
16.7%
시 1
16.7%
설 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
근 1
16.7%
린 1
16.7%
생 1
16.7%
활 1
16.7%
시 1
16.7%
설 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
근 1
16.7%
린 1
16.7%
생 1
16.7%
활 1
16.7%
시 1
16.7%
설 1
16.7%

cnstyarea
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size97.7 KiB
False
 
1
(Missing)
9999 
ValueCountFrequency (%)
False 1
 
< 0.1%
(Missing) 9999
> 99.9%
2024-04-18T00:24:35.874211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

fctyowkepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9994
Missing (%)99.9%
Memory size156.2 KiB

fctypdtjobepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB

fctysiljobepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB

wtrsplyfacilsenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5270 
상수도전용
4696 
지하수전용
 
17
간이상수도
 
11
상수도(음용)지하수(주방용)겸용
 
4

Length

Max length19
Median length4
Mean length4.4806
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5270
52.7%
상수도전용 4696
47.0%
지하수전용 17
 
0.2%
간이상수도 11
 
0.1%
상수도(음용)지하수(주방용)겸용 4
 
< 0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%

Length

2024-04-18T00:24:35.948355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:36.028905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5270
52.7%
상수도전용 4696
46.9%
지하수전용 17
 
0.2%
간이상수도 11
 
0.1%
상수도(음용)지하수(주방용)겸용 4
 
< 0.1%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%

svnsr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

plninsurstdt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

plninsurenddt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

maneipcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6507
Missing (%)65.1%
Memory size156.2 KiB

playutscntdtl
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

playfacilcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size97.7 KiB
False
9772 
True
 
224
(Missing)
 
4
ValueCountFrequency (%)
False 9772
97.7%
True 224
 
2.2%
(Missing) 4
 
< 0.1%
2024-04-18T00:24:36.100531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

lvsenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6143 
기타
3143 
자율
699 
지도
 
9
우수
 
5

Length

Max length4
Median length4
Mean length3.2285
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> 6143
61.4%
기타 3143
31.4%
자율 699
 
7.0%
지도 9
 
0.1%
우수 5
 
0.1%
갑 1
 
< 0.1%

Length

2024-04-18T00:24:36.173796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:36.251832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6143
61.4%
기타 3143
31.4%
자율 699
 
7.0%
지도 9
 
0.1%
우수 5
 
< 0.1%
갑 1
 
< 0.1%

stagear
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

culwrkrsenm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:36.336794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관광사업
2nd row관광사업
ValueCountFrequency (%)
관광사업 2
100.0%
2024-04-18T00:24:36.507188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 2
25.0%
광 2
25.0%
사 2
25.0%
업 2
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 2
25.0%
광 2
25.0%
사 2
25.0%
업 2
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 2
25.0%
광 2
25.0%
사 2
25.0%
업 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 2
25.0%
광 2
25.0%
사 2
25.0%
업 2
25.0%

culphyedcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9989 
외국인전용유흥음식점업
 
11

Length

Max length11
Median length4
Mean length4.0077
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> 9989
99.9%
외국인전용유흥음식점업 11
 
0.1%

Length

2024-04-18T00:24:36.606177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:36.678228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9989
99.9%
외국인전용유흥음식점업 11
 
0.1%

geicpfacilen
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

bcfacilen
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

isream
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9994
Missing (%)99.9%
Memory size156.2 KiB

insurorgnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

insurstdt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

insurenddt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

hoffepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB

afc
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:36.726339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타
ValueCountFrequency (%)
기타 1
100.0%
2024-04-18T00:24:36.896786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

shpinfo
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

shpcnt
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:37.014288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
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

Unique1 ?
Unique (%)100.0%

Sample

1st row기타 휴게음식점
ValueCountFrequency (%)
기타 1
50.0%
휴게음식점 1
50.0%
2024-04-18T00:24:37.209081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
12.5%
타 1
12.5%
1
12.5%
휴 1
12.5%
게 1
12.5%
음 1
12.5%
식 1
12.5%
점 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
87.5%
Space Separator 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
14.3%
타 1
14.3%
휴 1
14.3%
게 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
87.5%
Common 1
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
14.3%
타 1
14.3%
휴 1
14.3%
게 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
87.5%
ASCII 1
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
14.3%
타 1
14.3%
휴 1
14.3%
게 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
ASCII
ValueCountFrequency (%)
1
100.0%

shptottons
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

facilscp
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:37.329495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row192
2nd row419
ValueCountFrequency (%)
192 1
50.0%
419 1
50.0%
2024-04-18T00:24:37.511131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
33.3%
9 2
33.3%
2 1
16.7%
4 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
33.3%
9 2
33.3%
2 1
16.7%
4 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
33.3%
9 2
33.3%
2 1
16.7%
4 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
33.3%
9 2
33.3%
2 1
16.7%
4 1
16.7%

facilar
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:37.829814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters10
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

Unique2 ?
Unique (%)100.0%

Sample

1st row192.03
2nd row418.65
ValueCountFrequency (%)
192.03 1
50.0%
418.65 1
50.0%
2024-04-18T00:24:37.999877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
16.7%
. 2
16.7%
9 1
8.3%
2 1
8.3%
0 1
8.3%
3 1
8.3%
4 1
8.3%
8 1
8.3%
6 1
8.3%
5 1
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
83.3%
Other Punctuation 2
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
20.0%
9 1
10.0%
2 1
10.0%
0 1
10.0%
3 1
10.0%
4 1
10.0%
8 1
10.0%
6 1
10.0%
5 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
16.7%
. 2
16.7%
9 1
8.3%
2 1
8.3%
0 1
8.3%
3 1
8.3%
4 1
8.3%
8 1
8.3%
6 1
8.3%
5 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
16.7%
. 2
16.7%
9 1
8.3%
2 1
8.3%
0 1
8.3%
3 1
8.3%
4 1
8.3%
8 1
8.3%
6 1
8.3%
5 1
8.3%

faciltotscp
Unsupported

REJECTED  UNSUPPORTED 

Missing15
Missing (%)0.1%
Memory size156.2 KiB

infoben
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

wmeipcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6483
Missing (%)64.8%
Memory size156.2 KiB

engstntrnmnm
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:38.116265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length6.5
Mean length8.25
Min length5

Characters and Unicode

Total characters33
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowMANILA
2nd rowANGELES
3rd rowMANHATTAN NIGHT
4th rowKings
ValueCountFrequency (%)
manila 1
20.0%
angeles 1
20.0%
manhattan 1
20.0%
night 1
20.0%
kings 1
20.0%
2024-04-18T00:24:38.314539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 6
18.2%
N 5
15.2%
T 3
9.1%
M 2
 
6.1%
I 2
 
6.1%
L 2
 
6.1%
G 2
 
6.1%
E 2
 
6.1%
H 2
 
6.1%
S 1
 
3.0%
Other values (6) 6
18.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 28
84.8%
Lowercase Letter 4
 
12.1%
Space Separator 1
 
3.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 6
21.4%
N 5
17.9%
T 3
10.7%
M 2
 
7.1%
I 2
 
7.1%
L 2
 
7.1%
G 2
 
7.1%
E 2
 
7.1%
H 2
 
7.1%
S 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
i 1
25.0%
n 1
25.0%
g 1
25.0%
s 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
97.0%
Common 1
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 6
18.8%
N 5
15.6%
T 3
9.4%
M 2
 
6.2%
I 2
 
6.2%
L 2
 
6.2%
G 2
 
6.2%
E 2
 
6.2%
H 2
 
6.2%
S 1
 
3.1%
Other values (5) 5
15.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 6
18.2%
N 5
15.2%
T 3
9.1%
M 2
 
6.1%
I 2
 
6.1%
L 2
 
6.1%
G 2
 
6.1%
E 2
 
6.1%
H 2
 
6.1%
S 1
 
3.0%
Other values (6) 6
18.2%

engstntrnmaddr
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:38.419748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length37
Mean length37.333333
Min length37

Characters and Unicode

Total characters112
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowA PLEASURE RESTAURANT FOR A FOREIGNER
2nd rowA PLEASURE RESTAURANT FOR A FOREIGNER
3rd rowA pleasure restaurant for a foreigner
ValueCountFrequency (%)
a 6
33.3%
pleasure 3
16.7%
restaurant 3
16.7%
for 3
16.7%
foreigner 3
16.7%
2024-04-18T00:24:38.623622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
14.3%
R 12
 
10.7%
A 11
 
9.8%
E 10
 
8.9%
r 6
 
5.4%
e 5
 
4.5%
F 4
 
3.6%
O 4
 
3.6%
N 4
 
3.6%
T 4
 
3.6%
Other values (17) 36
32.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 65
58.0%
Lowercase Letter 31
27.7%
Space Separator 16
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 12
18.5%
A 11
16.9%
E 10
15.4%
F 4
 
6.2%
O 4
 
6.2%
N 4
 
6.2%
T 4
 
6.2%
U 4
 
6.2%
S 4
 
6.2%
G 2
 
3.1%
Other values (3) 6
9.2%
Lowercase Letter
ValueCountFrequency (%)
r 6
19.4%
e 5
16.1%
a 4
12.9%
u 2
 
6.5%
n 2
 
6.5%
t 2
 
6.5%
f 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
l 1
 
3.2%
Other values (3) 3
9.7%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 96
85.7%
Common 16
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 12
 
12.5%
A 11
 
11.5%
E 10
 
10.4%
r 6
 
6.2%
e 5
 
5.2%
F 4
 
4.2%
O 4
 
4.2%
N 4
 
4.2%
T 4
 
4.2%
U 4
 
4.2%
Other values (16) 32
33.3%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
14.3%
R 12
 
10.7%
A 11
 
9.8%
E 10
 
8.9%
r 6
 
5.4%
e 5
 
4.5%
F 4
 
3.6%
O 4
 
3.6%
N 4
 
3.6%
T 4
 
3.6%
Other values (17) 36
32.1%

trdpjubnsenm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5805 
기타
3497 
주택가주변
 
349
아파트지역
 
159
유흥업소밀집지역
 
140
Other values (3)
 
50

Length

Max length8
Median length4
Mean length3.4268
Min length2

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> 5805
58.1%
기타 3497
35.0%
주택가주변 349
 
3.5%
아파트지역 159
 
1.6%
유흥업소밀집지역 140
 
1.4%
학교정화(상대) 34
 
0.3%
학교정화(절대) 10
 
0.1%
결혼예식장주변 6
 
0.1%

Length

2024-04-18T00:24:38.723043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:24:38.807709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5805
58.1%
기타 3497
35.0%
주택가주변 349
 
3.5%
아파트지역 159
 
1.6%
유흥업소밀집지역 140
 
1.4%
학교정화(상대 34
 
0.3%
학교정화(절대 10
 
0.1%
결혼예식장주변 6
 
0.1%

monam
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB

sntuptaenm
Categorical

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
2176 
다방
1618 
일반조리판매
1557 
기타 휴게음식점
1289 
과자점
1012 
Other values (33)
2348 

Length

Max length15
Median length10
Mean length4.0579
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row기타 휴게음식점
2nd row기타 휴게음식점
3rd row일반조리판매
4th row일반조리판매
5th row커피숍

Common Values

ValueCountFrequency (%)
커피숍 2176
21.8%
다방 1618
16.2%
일반조리판매 1557
15.6%
기타 휴게음식점 1289
12.9%
과자점 1012
10.1%
패스트푸드 633
 
6.3%
한식 537
 
5.4%
경양식 225
 
2.2%
편의점 213
 
2.1%
푸드트럭 106
 
1.1%
Other values (28) 634
 
6.3%

Length

2024-04-18T00:24:38.906145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2176
19.3%
다방 1618
14.3%
일반조리판매 1557
13.8%
기타 1361
12.1%
휴게음식점 1289
11.4%
과자점 1012
9.0%
패스트푸드 633
 
5.6%
한식 537
 
4.8%
경양식 225
 
2.0%
편의점 213
 
1.9%
Other values (28) 668
 
5.9%

dispenen
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

capt
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:39.014313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row20000000
2nd row50000000
3rd row60000000
ValueCountFrequency (%)
20000000 1
33.3%
50000000 1
33.3%
60000000 1
33.3%
2024-04-18T00:24:39.207039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
87.5%
2 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
87.5%
2 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
87.5%
2 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
87.5%
2 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%

jtupsomainedf
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:39.294281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row전통차
ValueCountFrequency (%)
전통차 1
100.0%
2024-04-18T00:24:39.460163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 1
33.3%
통 1
33.3%
차 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1
33.3%
통 1
33.3%
차 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1
33.3%
통 1
33.3%
차 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 1
33.3%
통 1
33.3%
차 1
33.3%

jtupsoasgnno
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:39.573335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length10
Min length1

Characters and Unicode

Total characters20
Distinct characters9
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2
2nd row2021-01-05 10:18:17
ValueCountFrequency (%)
2 1
33.3%
2021-01-05 1
33.3%
10:18:17 1
33.3%
2024-04-18T00:24:39.775156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
25.0%
0 4
20.0%
2 3
15.0%
- 2
 
10.0%
: 2
 
10.0%
5 1
 
5.0%
1
 
5.0%
8 1
 
5.0%
7 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
75.0%
Dash Punctuation 2
 
10.0%
Other Punctuation 2
 
10.0%
Space Separator 1
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
33.3%
0 4
26.7%
2 3
20.0%
5 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
: 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
25.0%
0 4
20.0%
2 3
15.0%
- 2
 
10.0%
: 2
 
10.0%
5 1
 
5.0%
1
 
5.0%
8 1
 
5.0%
7 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
25.0%
0 4
20.0%
2 3
15.0%
- 2
 
10.0%
: 2
 
10.0%
5 1
 
5.0%
1
 
5.0%
8 1
 
5.0%
7 1
 
5.0%

mnfactreartclcn
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

chaircnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

nearenvnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:39.882863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row유흥업소밀집지역
ValueCountFrequency (%)
유흥업소밀집지역 1
100.0%
2024-04-18T00:24:40.071616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 1
12.5%
흥 1
12.5%
업 1
12.5%
소 1
12.5%
밀 1
12.5%
집 1
12.5%
지 1
12.5%
역 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 1
12.5%
흥 1
12.5%
업 1
12.5%
소 1
12.5%
밀 1
12.5%
집 1
12.5%
지 1
12.5%
역 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 1
12.5%
흥 1
12.5%
업 1
12.5%
소 1
12.5%
밀 1
12.5%
집 1
12.5%
지 1
12.5%
역 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 1
12.5%
흥 1
12.5%
업 1
12.5%
소 1
12.5%
밀 1
12.5%
집 1
12.5%
지 1
12.5%
역 1
12.5%

jisgnumlay
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:40.126934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2024-04-18T00:24:40.262628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

regnsenm
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:40.366471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row중심상업지역
2nd row일반상업지역
ValueCountFrequency (%)
중심상업지역 1
50.0%
일반상업지역 1
50.0%
2024-04-18T00:24:40.560113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 2
16.7%
업 2
16.7%
지 2
16.7%
역 2
16.7%
중 1
8.3%
심 1
8.3%
일 1
8.3%
반 1
8.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 2
16.7%
업 2
16.7%
지 2
16.7%
역 2
16.7%
중 1
8.3%
심 1
8.3%
일 1
8.3%
반 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 2
16.7%
업 2
16.7%
지 2
16.7%
역 2
16.7%
중 1
8.3%
심 1
8.3%
일 1
8.3%
반 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 2
16.7%
업 2
16.7%
지 2
16.7%
역 2
16.7%
중 1
8.3%
심 1
8.3%
일 1
8.3%
반 1
8.3%

undernumlay
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:40.617159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1
ValueCountFrequency (%)
1 1
100.0%
2024-04-18T00:24:40.753272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
100.0%

totepnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

totnumlay
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T00:24:40.808805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2024-04-18T00:24:40.974488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

homepage
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

meetsamtimesygstf
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

last_load_dttm
Date

Distinct7
Distinct (%)0.1%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2021-01-05 10:18:14
Maximum2021-01-05 10:18:20
2024-04-18T00:24:41.072520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:24:41.152778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmcnstyareafctyowkepcntfctypdtjobepcntfctysiljobepcntwtrsplyfacilsenmsvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynlvsenmstagearculwrkrsenmculphyedcobnmgeicpfacilenbcfacilenisreaminsurorgnminsurstdtinsurenddthoffepcntafcshpinfoshpcntshptottonsfacilscpfacilarfaciltotscpinfobenwmeipcntengstntrnmnmengstntrnmaddrtrdpjubnsenmmonamsntuptaenmdispenencaptjtupsomainedfjtupsoasgnnomnfactreartclcnchaircntnearenvnmjisgnumlayregnsenmundernumlaytotepnumtotnumlayhomepagemeetsamtimesygstflast_load_dttm
165491654433600003360000-104-2014-0002707_24_05_PI2018-08-31 23:59:59.0NaN까페가야618230.0부산광역시 강서구 지사동 1190-7번지46743부산광역시 강서구 과학산단로334번다길 54 (지사동)2014102120141022.0<NA><NA><NA>2폐업367280.655734185220.91372220141021102732기타 휴게음식점051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>0.0<NA>NaN<NA><NA><NA>NaN기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
168601685733700003370000-104-2016-0002307_24_05_PI2018-08-31 23:59:59.0NaN피자토모611833.0부산광역시 연제구 연산동 1805-6번지47616부산광역시 연제구 연수로 232, 2층 (연산동)2016052720170607.0<NA><NA><NA>2폐업390940.392975188331.68517320170607145445기타 휴게음식점051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>40.22<NA>NaN<NA><NA><NA>NaN기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
137401374033400003340000-104-2010-0003007_24_05_PI2018-08-31 23:59:59.0NaN그릴피아604835.0부산광역시 사하구 신평동 165-3번지 (장평로 303)49418부산광역시 사하구 장평로 303 (신평동,(장평로 303))2010092820130603.0<NA><NA><NA>2.0폐업379953.406334179219.4200480000020101006152445일반조리판매051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>21.37<NA>NaN<NA><NA><NA>NaN일반조리판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:17
5335739733000003300000-104-2002-0002507_24_05_PI2018-08-31 23:59:59.0NaN스넥바607832.0부산광역시 동래구 온천동 137-0 번지48947<NA>20021125.020090515<NA><NA><NA>02폐업<NA>NaN20060120000000일반조리판매051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>14.85<NA>0<NA><NA><NA>NaN일반조리판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
6426642033000003300000-104-2012-0001907_24_05_PI2018-08-31 23:59:59.0NaN(주)롤뺑브레드607804.0부산광역시 동래구 명륜동 529-4번지47815부산광역시 동래구 충렬대로 186 (명륜동)20120417.0NaN<NA><NA><NA>01영업389416.624855191640.19955420180503170016커피숍051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>88.77<NA>NaN<NA><NA><NA>NaN커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
143101430933400003340000-104-1997-0013007_24_05_PI2018-08-31 23:59:59.0NaN을숙도다방604852.0부산광역시 사하구 하단동 525-8번지48947<NA>1997101420050330.0<NA><NA><NA>2.0폐업379132.550819180685.23350019990315000000다방051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>0.0<NA><NA>N기타<NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>107.35<NA>0.0<NA><NA>기타NaN다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
159361593333500003350000-104-2005-0003407_24_05_PI2018-08-31 23:59:59.0NaN700즉석삼각김밥609839.0부산광역시 금정구 장전동 414-26번지 (102호)48947<NA>2005091420080701.0<NA><NA><NA>2.0폐업390060.780557194712.38947620070510000000패스트푸드051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>0.0<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>28.84<NA>0.0<NA><NA><NA>NaN패스트푸드<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
1213121232600003260000-104-1988-0188607_24_05_PI2018-08-31 23:59:59.0NaN동원602055.0부산광역시 서구 토성동5가 23-9번지49246부산광역시 서구 구덕로148번길 2 (토성동5가)19881109.020140422<NA><NA><NA>02폐업384273.44687179846.60646520140404183128다방051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N기타<NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>67.36<NA>NaN<NA><NA>기타NaN다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:14
4256425532900003290000-104-2012-0010607_24_05_PI2018-08-31 23:59:59.0NaNThe Crepe (더크레페)614847.0부산광역시 부산진구 부전동 256-6번지47286부산광역시 부산진구 서면로 56, 1층 (부전동)20120913.020150709<NA><NA><NA>02폐업387541.140307186341.52095320131120155923커피숍051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>11.5<NA>NaN<NA><NA><NA>NaN커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
27327732500003250000-104-2017-0002207_24_05_PI2018-08-31 23:59:59.0NaN카페진정성600017.0부산광역시 중구 중앙동7가 1-2번지48944부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데백화점광복점)20170502.020170531<NA><NA><NA>02폐업385717.579204179899.41227620170531163111백화점051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>9.91<NA>NaN<NA><NA><NA>NaN백화점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:14
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmcnstyareafctyowkepcntfctypdtjobepcntfctysiljobepcntwtrsplyfacilsenmsvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynlvsenmstagearculwrkrsenmculphyedcobnmgeicpfacilenbcfacilenisreaminsurorgnminsurstdtinsurenddthoffepcntafcshpinfoshpcntshptottonsfacilscpfacilarfaciltotscpinfobenwmeipcntengstntrnmnmengstntrnmaddrtrdpjubnsenmmonamsntuptaenmdispenencaptjtupsomainedfjtupsoasgnnomnfactreartclcnchaircntnearenvnmjisgnumlayregnsenmundernumlaytotepnumtotnumlayhomepagemeetsamtimesygstflast_load_dttm
5176517132900003290000-104-2016-0002407_24_05_PI2018-08-31 23:59:59.0NaN카페비835614867.0부산광역시 부산진구 전포동 673-13번지47293부산광역시 부산진구 서전로46번길 10-5, 1층 (전포동)20160310.0NaN<NA><NA><NA>01영업388127.797706186473.77223420160310145927커피숍051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>49.92<NA>NaN<NA><NA><NA>NaN커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
8636862833100003310000-104-2015-0001507_24_05_PI2018-08-31 23:59:59.0NaN더벤티 용호점608833.0부산광역시 남구 용호동 370-15번지48528부산광역시 남구 동명로 133 (용호동)20150313NaN<NA><NA><NA>1.0영업392494.342768182434.8768450000020180712125222커피숍051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>26.23<NA>NaN<NA><NA><NA>NaN커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:16
155131550633500003350000-104-2012-0001907_24_05_PI2018-08-31 23:59:59.0NaN레몬트리609817.0부산광역시 금정구 부곡동 63-11번지46275부산광역시 금정구 수림로 6, 102동 지하 1층 1호 (부곡동, SK아파트 )2012032820141229.0<NA><NA><NA>2.0폐업390421.585487195678.8862010000020120507172307커피숍051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>35.75<NA>NaN<NA><NA><NA>NaN커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
6205619932900003290000-104-1990-0536507_24_05_PI2018-08-31 23:59:59.0NaN자유시간614846.0부산광역시 부산진구 부전동 242-27번지48947<NA>19900223.019980427<NA><NA><NA>02폐업387534.087673186200.3107719990623000000다방051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N기타<NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>111.22<NA>NaN<NA><NA>기타NaN다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
160761608133500003350000-104-2017-0000907_24_05_PI2018-08-31 23:59:59.0NaN명랑시대쌀핫도그남산점609813.0부산광역시 금정구 남산동 20-12번지46219부산광역시 금정구 팔송로 19 (남산동)20170206NaN<NA><NA><NA>1.0영업390214.872876199277.4703850000020170607171106패스트푸드051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>24.64<NA>NaN<NA><NA><NA>NaN패스트푸드<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:18
6470646433000003300000-104-2015-0005207_24_05_PI2018-08-31 23:59:59.0NaN자농의 뜨락607804.0부산광역시 동래구 명륜동 506-3번지47737부산광역시 동래구 충렬대로 197 (명륜동)20150904.0NaN<NA><NA><NA>01영업389523.288257191773.06106220170222151743기타 휴게음식점051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>18.03<NA>NaN<NA><NA><NA>NaN기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:15
236962372932500003250000-101-2004-0003707_24_04_PI2018-08-31 23:59:59.0NaN세인트루이스600816.0부산광역시 중구 중앙동4가 84-26번지 .1층48947<NA>2004052520110210.0<NA><NA><NA>2폐업385685.971895180523.35229820110302130658김밥(도시락)051-123-1234<NA><NA><NA><NA>NaNNaNNaN상수도전용<NA><NA><NA>0.0<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>80.68<NA>0.0<NA><NA><NA>NaN김밥(도시락)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:20
214572144932500003250000-101-2004-0006307_24_04_PI2018-08-31 23:59:59.0NaN가야면옥600031.0부산광역시 중구 광복동1가 6-7번지 (1층일부)48947부산광역시 중구 광복로85번길 5-10, 1층 (광복동1가, 1층일부)2004082720151208.0<NA><NA><NA>2폐업385448.754998179977.32822820130227164536분식051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>0.0<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>97.14<NA>0.0<NA><NA><NA>NaN분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:20
1613161232600003260000-104-2012-0001407_24_05_PI2018-08-31 23:59:59.0NaN신불떡볶이 대신점602825.0부산광역시 서구 서대신동3가 256번지49225부산광역시 서구 망양로 34 (서대신동3가)20121218.0NaN<NA><NA><NA>01영업383606.577292181535.46427120170516172100기타 휴게음식점051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>28.22<NA>NaN<NA><NA><NA>NaN기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:14
110501105333300003330000-104-2017-0032807_24_05_PI2018-08-31 23:59:59.0NaNCafe B.612704.0부산광역시 해운대구 우동 1500번지 벡스코48060부산광역시 해운대구 APEC로 55 (우동)2017112420171202.0<NA><NA><NA>2.0폐업394606.582838187941.1514610000020171204113351기타 휴게음식점051-123-1234<NA><NA><NA><NA>NaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA>N<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>0.0<NA>NaN<NA><NA><NA>NaN기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-05 10:18:17