Overview

Dataset statistics

Number of variables34
Number of observations10000
Missing cells18886
Missing cells (%)5.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 MiB
Average record size in memory283.0 B

Variable types

Text12
Numeric3
Categorical17
DateTime2

Alerts

updategbn is highly imbalanced (94.2%)Imbalance
clgstdt is highly imbalanced (90.7%)Imbalance
clgenddt is highly imbalanced (90.3%)Imbalance
ropnymd is highly imbalanced (81.2%)Imbalance
trdstatenm is highly imbalanced (52.6%)Imbalance
dtlstatenm is highly imbalanced (67.7%)Imbalance
uptaenm is highly imbalanced (65.0%)Imbalance
bdngdngnum is highly imbalanced (75.8%)Imbalance
puprsenm is highly imbalanced (96.9%)Imbalance
bupnm is highly imbalanced (87.1%)Imbalance
insurjnyncode is highly imbalanced (54.9%)Imbalance
drmkcobnm is highly imbalanced (87.0%)Imbalance
ldercnt is highly imbalanced (60.2%)Imbalance
memcolltotstfnum is highly imbalanced (92.0%)Imbalance
sitepostno has 5514 (55.1%) missing valuesMissing
sitewhladdr has 102 (1.0%) missing valuesMissing
rdnwhladdr has 257 (2.6%) missing valuesMissing
dcbymd has 7081 (70.8%) missing valuesMissing
x has 313 (3.1%) missing valuesMissing
y has 313 (3.1%) missing valuesMissing
sitetel has 428 (4.3%) missing valuesMissing
bdngyarea has 4874 (48.7%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -63.48806711)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 21:53:10.742386
Analysis finished2024-04-17 21:53:13.203854
Duration2.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T06:53:13.471400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.1902
Min length1

Characters and Unicode

Total characters41902
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row5656
2nd row9058
3rd row4948
4th row1527
5th row4257
ValueCountFrequency (%)
5656 1
 
< 0.1%
11548 1
 
< 0.1%
12945 1
 
< 0.1%
4146 1
 
< 0.1%
9293 1
 
< 0.1%
11277 1
 
< 0.1%
5883 1
 
< 0.1%
12699 1
 
< 0.1%
10456 1
 
< 0.1%
3087 1
 
< 0.1%
Other values (9991) 9991
99.9%
2024-04-18T06:53:13.910740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7133
17.0%
2 4510
10.8%
3 4210
10.0%
5 3818
9.1%
4 3760
9.0%
8 3708
8.8%
9 3703
8.8%
0 3691
8.8%
7 3680
8.8%
6 3680
8.8%
Other values (9) 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41893
> 99.9%
Lowercase Letter 5
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7133
17.0%
2 4510
10.8%
3 4210
10.0%
5 3818
9.1%
4 3760
9.0%
8 3708
8.9%
9 3703
8.8%
0 3691
8.8%
7 3680
8.8%
6 3680
8.8%
Lowercase Letter
ValueCountFrequency (%)
t 1
20.0%
u 1
20.0%
d 1
20.0%
i 1
20.0%
o 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
T 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41894
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7133
17.0%
2 4510
10.8%
3 4210
10.0%
5 3818
9.1%
4 3760
9.0%
8 3708
8.9%
9 3703
8.8%
0 3691
8.8%
7 3680
8.8%
6 3680
8.8%
Latin
ValueCountFrequency (%)
P 1
12.5%
T 1
12.5%
S 1
12.5%
t 1
12.5%
u 1
12.5%
d 1
12.5%
i 1
12.5%
o 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7133
17.0%
2 4510
10.8%
3 4210
10.0%
5 3818
9.1%
4 3760
9.0%
8 3708
8.8%
9 3703
8.8%
0 3691
8.8%
7 3680
8.8%
6 3680
8.8%
Other values (9) 9
 
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct233
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3743439.5
Minimum614853
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:53:14.040097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum614853
5-th percentile3200000
Q13300000
median3370000
Q33940000
95-th percentile5540000
Maximum6520000
Range5905147
Interquartile range (IQR)640000

Descriptive statistics

Standard deviation746895.42
Coefficient of variation (CV)0.19952117
Kurtosis2.4165498
Mean3743439.5
Median Absolute Deviation (MAD)100000
Skewness1.7826497
Sum3.7434395 × 1010
Variance5.5785277 × 1011
MonotonicityNot monotonic
2024-04-18T06:53:14.150698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3300000 607
 
6.1%
3290000 542
 
5.4%
3330000 521
 
5.2%
3310000 505
 
5.1%
3340000 468
 
4.7%
3350000 419
 
4.2%
3390000 370
 
3.7%
3320000 346
 
3.5%
3370000 300
 
3.0%
3380000 241
 
2.4%
Other values (223) 5681
56.8%
ValueCountFrequency (%)
614853 1
 
< 0.1%
3000000 20
0.2%
3010000 20
0.2%
3020000 15
0.1%
3030000 28
0.3%
3040000 25
0.2%
3050000 26
0.3%
3060000 15
0.1%
3070000 20
0.2%
3080000 14
0.1%
ValueCountFrequency (%)
6520000 28
 
0.3%
6510000 87
0.9%
6470000 3
 
< 0.1%
6460000 1
 
< 0.1%
6450000 1
 
< 0.1%
6440000 1
 
< 0.1%
6430000 1
 
< 0.1%
6420000 1
 
< 0.1%
6260000 6
 
0.1%
5710000 104
1.0%

mgtno
Text

Distinct1842
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T06:53:14.356978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length20.0029
Min length15

Characters and Unicode

Total characters200029
Distinct characters31
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

Unique697 ?
Unique (%)7.0%

Sample

1st rowCDFH3301082006000001
2nd rowCDFH3301022019000006
3rd rowCDFH3301081998000013
4th rowCDFH3301062016000001
5th rowCDFH3301082003000068
ValueCountFrequency (%)
cdfh3301082019000001 129
 
1.3%
cdfh3301082019000002 106
 
1.1%
cdfh3301082020000001 101
 
1.0%
cdfh3301022020000001 98
 
1.0%
cdfh3301022019000001 92
 
0.9%
cdfh3301062019000001 90
 
0.9%
cdfh3301082019000003 87
 
0.9%
cdfh3301022020000002 82
 
0.8%
cdfh3301022020000003 81
 
0.8%
cdfh3301082020000003 78
 
0.8%
Other values (1836) 9060
90.6%
2024-04-18T06:53:14.716699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81839
40.9%
3 22154
 
11.1%
1 20096
 
10.0%
2 16168
 
8.1%
C 9985
 
5.0%
F 9985
 
5.0%
H 9985
 
5.0%
D 9985
 
5.0%
9 5588
 
2.8%
8 5117
 
2.6%
Other values (21) 9127
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160027
80.0%
Uppercase Letter 39940
 
20.0%
Dash Punctuation 40
 
< 0.1%
Other Letter 15
 
< 0.1%
Space Separator 5
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%
Decimal Number
ValueCountFrequency (%)
0 81839
51.1%
3 22154
 
13.8%
1 20096
 
12.6%
2 16168
 
10.1%
9 5588
 
3.5%
8 5117
 
3.2%
6 3685
 
2.3%
5 2609
 
1.6%
4 1575
 
1.0%
7 1196
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 9985
25.0%
F 9985
25.0%
H 9985
25.0%
D 9985
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 160074
80.0%
Latin 39940
 
20.0%
Hangul 15
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81839
51.1%
3 22154
 
13.8%
1 20096
 
12.6%
2 16168
 
10.1%
9 5588
 
3.5%
8 5117
 
3.2%
6 3685
 
2.3%
5 2609
 
1.6%
4 1575
 
1.0%
7 1196
 
0.7%
Other values (4) 47
 
< 0.1%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%
Latin
ValueCountFrequency (%)
C 9985
25.0%
F 9985
25.0%
H 9985
25.0%
D 9985
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200014
> 99.9%
Hangul 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81839
40.9%
3 22154
 
11.1%
1 20096
 
10.0%
2 16168
 
8.1%
C 9985
 
5.0%
F 9985
 
5.0%
H 9985
 
5.0%
D 9985
 
5.0%
9 5588
 
2.8%
8 5117
 
2.6%
Other values (8) 9112
 
4.6%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%

opnsvcid
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10_32_01_P
3399 
10_41_01_P
2542 
10_42_01_P
2395 
10_31_01_P
1260 
10_35_01_P
 
197
Other values (10)
 
207

Length

Max length10
Median length10
Mean length9.9995
Min length5

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row10_32_01_P
2nd row10_41_01_P
3rd row10_32_01_P
4th row10_42_01_P
5th row10_32_01_P

Common Values

ValueCountFrequency (%)
10_32_01_P 3399
34.0%
10_41_01_P 2542
25.4%
10_42_01_P 2395
23.9%
10_31_01_P 1260
 
12.6%
10_35_01_P 197
 
2.0%
10_37_01_P 49
 
0.5%
10_33_02_P 43
 
0.4%
10_39_01_P 41
 
0.4%
10_34_01_P 27
 
0.3%
10_33_01_P 19
 
0.2%
Other values (5) 28
 
0.3%

Length

2024-04-18T06:53:14.837230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10_32_01_p 3399
34.0%
10_41_01_p 2542
25.4%
10_42_01_p 2395
23.9%
10_31_01_p 1260
 
12.6%
10_35_01_p 197
 
2.0%
10_37_01_p 49
 
0.5%
10_33_02_p 43
 
0.4%
10_39_01_p 41
 
0.4%
10_34_01_p 27
 
0.3%
10_33_01_p 19
 
0.2%
Other values (5) 28
 
0.3%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9884 
U
 
115
부산광역시 부산진구 중앙대로 923-1, 2층 (양정동)
 
1

Length

Max length31
Median length1
Mean length1.003
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 9884
98.8%
U 115
 
1.1%
부산광역시 부산진구 중앙대로 923-1, 2층 (양정동) 1
 
< 0.1%

Length

2024-04-18T06:53:14.936820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:15.021601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9884
98.8%
u 115
 
1.1%
부산광역시 1
 
< 0.1%
부산진구 1
 
< 0.1%
중앙대로 1
 
< 0.1%
923-1 1
 
< 0.1%
2층 1
 
< 0.1%
양정동 1
 
< 0.1%
Distinct626
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-12-05 00:00:00
Maximum2021-01-31 00:23:03
2024-04-18T06:53:15.130930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:53:15.251921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4936 
체력단련장업
1493 
체육도장업
1343 
당구장업
1247 
골프연습장업
659 
Other values (10)
 
322

Length

Max length7
Median length4
Mean length4.5806
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4936
49.4%
체력단련장업 1493
 
14.9%
체육도장업 1343
 
13.4%
당구장업 1247
 
12.5%
골프연습장업 659
 
6.6%
수영장업 138
 
1.4%
무도학원업 43
 
0.4%
썰매장업 41
 
0.4%
종합체육시설업 33
 
0.3%
빙상장업 27
 
0.3%
Other values (5) 40
 
0.4%

Length

2024-04-18T06:53:15.364709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4936
49.4%
체력단련장업 1493
 
14.9%
체육도장업 1343
 
13.4%
당구장업 1247
 
12.5%
골프연습장업 659
 
6.6%
수영장업 138
 
1.4%
무도학원업 43
 
0.4%
썰매장업 41
 
0.4%
종합체육시설업 33
 
0.3%
빙상장업 27
 
0.3%
Other values (5) 40
 
0.4%

bplcnm
Text

Distinct7580
Distinct (%)75.8%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T06:53:15.643661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length7.250325
Min length1

Characters and Unicode

Total characters72496
Distinct characters864
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6200 ?
Unique (%)62.0%

Sample

1st row패밀리당구장
2nd rowTEAM MAD
3rd row은실당구장
4th row점핑캣 바이 메디핏
5th row포커스당구장
ValueCountFrequency (%)
당구장 367
 
2.5%
당구클럽 313
 
2.1%
태권도 175
 
1.2%
휘트니스 159
 
1.1%
합기도 159
 
1.1%
태권도장 135
 
0.9%
gym 118
 
0.8%
골프 92
 
0.6%
용인대 88
 
0.6%
스크린골프 79
 
0.5%
Other values (7860) 12934
88.5%
2024-04-18T06:53:16.055945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4621
 
6.4%
3257
 
4.5%
3201
 
4.4%
3031
 
4.2%
2960
 
4.1%
1841
 
2.5%
1462
 
2.0%
1447
 
2.0%
1243
 
1.7%
1116
 
1.5%
Other values (854) 48317
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60607
83.6%
Space Separator 4621
 
6.4%
Uppercase Letter 4182
 
5.8%
Lowercase Letter 1334
 
1.8%
Decimal Number 545
 
0.8%
Close Punctuation 432
 
0.6%
Open Punctuation 424
 
0.6%
Other Punctuation 272
 
0.4%
Dash Punctuation 58
 
0.1%
Math Symbol 10
 
< 0.1%
Other values (4) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3257
 
5.4%
3201
 
5.3%
3031
 
5.0%
2960
 
4.9%
1841
 
3.0%
1462
 
2.4%
1447
 
2.4%
1243
 
2.1%
1116
 
1.8%
1116
 
1.8%
Other values (765) 39933
65.9%
Uppercase Letter
ValueCountFrequency (%)
G 379
 
9.1%
M 346
 
8.3%
T 318
 
7.6%
S 289
 
6.9%
P 259
 
6.2%
A 235
 
5.6%
Y 220
 
5.3%
O 216
 
5.2%
I 196
 
4.7%
K 194
 
4.6%
Other values (16) 1530
36.6%
Lowercase Letter
ValueCountFrequency (%)
i 134
 
10.0%
e 127
 
9.5%
n 118
 
8.8%
o 108
 
8.1%
t 78
 
5.8%
l 77
 
5.8%
y 76
 
5.7%
a 76
 
5.7%
r 75
 
5.6%
s 73
 
5.5%
Other values (16) 392
29.4%
Decimal Number
ValueCountFrequency (%)
2 163
29.9%
1 97
17.8%
3 62
 
11.4%
0 45
 
8.3%
4 42
 
7.7%
5 42
 
7.7%
7 27
 
5.0%
9 27
 
5.0%
8 21
 
3.9%
6 19
 
3.5%
Other Punctuation
ValueCountFrequency (%)
& 100
36.8%
. 100
36.8%
? 19
 
7.0%
' 16
 
5.9%
, 14
 
5.1%
: 10
 
3.7%
· 7
 
2.6%
# 3
 
1.1%
/ 2
 
0.7%
1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 6
60.0%
~ 1
 
10.0%
1
 
10.0%
< 1
 
10.0%
> 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 431
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 423
99.8%
[ 1
 
0.2%
Letter Number
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4621
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60604
83.6%
Common 6367
 
8.8%
Latin 5522
 
7.6%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3257
 
5.4%
3201
 
5.3%
3031
 
5.0%
2960
 
4.9%
1841
 
3.0%
1462
 
2.4%
1447
 
2.4%
1243
 
2.1%
1116
 
1.8%
1116
 
1.8%
Other values (762) 39930
65.9%
Latin
ValueCountFrequency (%)
G 379
 
6.9%
M 346
 
6.3%
T 318
 
5.8%
S 289
 
5.2%
P 259
 
4.7%
A 235
 
4.3%
Y 220
 
4.0%
O 216
 
3.9%
I 196
 
3.5%
K 194
 
3.5%
Other values (44) 2870
52.0%
Common
ValueCountFrequency (%)
4621
72.6%
) 431
 
6.8%
( 423
 
6.6%
2 163
 
2.6%
& 100
 
1.6%
. 100
 
1.6%
1 97
 
1.5%
3 62
 
1.0%
- 58
 
0.9%
0 45
 
0.7%
Other values (25) 267
 
4.2%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60603
83.6%
ASCII 11871
 
16.4%
None 9
 
< 0.1%
Number Forms 6
 
< 0.1%
CJK 3
 
< 0.1%
Arrows 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Specials 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4621
38.9%
) 431
 
3.6%
( 423
 
3.6%
G 379
 
3.2%
M 346
 
2.9%
T 318
 
2.7%
S 289
 
2.4%
P 259
 
2.2%
A 235
 
2.0%
Y 220
 
1.9%
Other values (71) 4350
36.6%
Hangul
ValueCountFrequency (%)
3257
 
5.4%
3201
 
5.3%
3031
 
5.0%
2960
 
4.9%
1841
 
3.0%
1462
 
2.4%
1447
 
2.4%
1243
 
2.1%
1116
 
1.8%
1116
 
1.8%
Other values (761) 39929
65.9%
None
ValueCountFrequency (%)
· 7
77.8%
1
 
11.1%
1
 
11.1%
Number Forms
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
Arrows
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Specials
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct796
Distinct (%)17.7%
Missing5514
Missing (%)55.1%
Memory size156.2 KiB
2024-04-18T06:53:16.393472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters26916
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)5.5%

Sample

1st row604813
2nd row608813
3rd row611702
4th row지번우편번호
5th row604840
ValueCountFrequency (%)
지번우편번호 523
 
11.7%
608805 51
 
1.1%
616852 45
 
1.0%
604851 36
 
0.8%
609839 34
 
0.8%
619903 32
 
0.7%
607815 32
 
0.7%
607804 31
 
0.7%
608810 31
 
0.7%
619963 28
 
0.6%
Other values (786) 3643
81.2%
2024-04-18T06:53:16.801436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 4862
18.1%
8 4178
15.5%
0 4013
14.9%
1 3508
13.0%
2 1703
 
6.3%
4 1402
 
5.2%
7 1305
 
4.8%
3 1239
 
4.6%
1046
 
3.9%
9 925
 
3.4%
Other values (6) 2735
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23774
88.3%
Other Letter 3138
 
11.7%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 4862
20.5%
8 4178
17.6%
0 4013
16.9%
1 3508
14.8%
2 1703
 
7.2%
4 1402
 
5.9%
7 1305
 
5.5%
3 1239
 
5.2%
9 925
 
3.9%
5 639
 
2.7%
Other Letter
ValueCountFrequency (%)
1046
33.3%
523
16.7%
523
16.7%
523
16.7%
523
16.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23778
88.3%
Hangul 3138
 
11.7%

Most frequent character per script

Common
ValueCountFrequency (%)
6 4862
20.4%
8 4178
17.6%
0 4013
16.9%
1 3508
14.8%
2 1703
 
7.2%
4 1402
 
5.9%
7 1305
 
5.5%
3 1239
 
5.2%
9 925
 
3.9%
5 639
 
2.7%
Hangul
ValueCountFrequency (%)
1046
33.3%
523
16.7%
523
16.7%
523
16.7%
523
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23778
88.3%
Hangul 3138
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 4862
20.4%
8 4178
17.6%
0 4013
16.9%
1 3508
14.8%
2 1703
 
7.2%
4 1402
 
5.9%
7 1305
 
5.5%
3 1239
 
5.2%
9 925
 
3.9%
5 639
 
2.7%
Hangul
ValueCountFrequency (%)
1046
33.3%
523
16.7%
523
16.7%
523
16.7%
523
16.7%

sitewhladdr
Text

MISSING 

Distinct8243
Distinct (%)83.3%
Missing102
Missing (%)1.0%
Memory size156.2 KiB
2024-04-18T06:53:17.143378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length49
Mean length25.41665
Min length4

Characters and Unicode

Total characters251574
Distinct characters651
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6990 ?
Unique (%)70.6%

Sample

1st row부산광역시 사하구 괴정동 580-13번지 2층
2nd row경상북도 포항시 남구 오천읍 원리 893-107번지
3rd row부산광역시 남구 대연동 1752-16번지
4th row부산광역시 해운대구 중동 1519-3번지
5th row부산광역시 부산진구 양정동 350-70번지
ValueCountFrequency (%)
부산광역시 5178
 
10.8%
경기도 1387
 
2.9%
서울특별시 772
 
1.6%
동래구 606
 
1.3%
남구 578
 
1.2%
부산진구 542
 
1.1%
해운대구 512
 
1.1%
북구 465
 
1.0%
2층 459
 
1.0%
사하구 440
 
0.9%
Other values (11602) 36991
77.2%
2024-04-18T06:53:17.588812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47261
 
18.8%
10677
 
4.2%
1 9841
 
3.9%
9793
 
3.9%
9225
 
3.7%
8578
 
3.4%
- 8174
 
3.2%
8134
 
3.2%
7209
 
2.9%
6627
 
2.6%
Other values (641) 126055
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147259
58.5%
Decimal Number 47557
 
18.9%
Space Separator 47261
 
18.8%
Dash Punctuation 8174
 
3.2%
Uppercase Letter 570
 
0.2%
Other Punctuation 329
 
0.1%
Open Punctuation 134
 
0.1%
Close Punctuation 133
 
0.1%
Lowercase Letter 82
 
< 0.1%
Math Symbol 66
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10677
 
7.3%
9793
 
6.7%
9225
 
6.3%
8578
 
5.8%
8134
 
5.5%
7209
 
4.9%
6627
 
4.5%
6373
 
4.3%
6128
 
4.2%
3471
 
2.4%
Other values (569) 71044
48.2%
Uppercase Letter
ValueCountFrequency (%)
B 110
19.3%
S 43
 
7.5%
A 42
 
7.4%
I 39
 
6.8%
K 38
 
6.7%
E 34
 
6.0%
T 26
 
4.6%
P 24
 
4.2%
C 24
 
4.2%
L 19
 
3.3%
Other values (16) 171
30.0%
Lowercase Letter
ValueCountFrequency (%)
e 23
28.0%
l 8
 
9.8%
o 7
 
8.5%
r 6
 
7.3%
c 6
 
7.3%
i 4
 
4.9%
w 4
 
4.9%
a 4
 
4.9%
y 4
 
4.9%
u 4
 
4.9%
Other values (7) 12
14.6%
Decimal Number
ValueCountFrequency (%)
1 9841
20.7%
2 6551
13.8%
3 5415
11.4%
4 4470
9.4%
5 4317
9.1%
0 3891
 
8.2%
6 3721
 
7.8%
7 3491
 
7.3%
8 3076
 
6.5%
9 2784
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 216
65.7%
? 73
 
22.2%
. 18
 
5.5%
& 7
 
2.1%
@ 6
 
1.8%
/ 4
 
1.2%
2
 
0.6%
· 2
 
0.6%
' 1
 
0.3%
Letter Number
ValueCountFrequency (%)
4
44.4%
3
33.3%
1
 
11.1%
1
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 65
98.5%
+ 1
 
1.5%
Space Separator
ValueCountFrequency (%)
47261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147258
58.5%
Common 103654
41.2%
Latin 661
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10677
 
7.3%
9793
 
6.7%
9225
 
6.3%
8578
 
5.8%
8134
 
5.5%
7209
 
4.9%
6627
 
4.5%
6373
 
4.3%
6128
 
4.2%
3471
 
2.4%
Other values (568) 71043
48.2%
Latin
ValueCountFrequency (%)
B 110
16.6%
S 43
 
6.5%
A 42
 
6.4%
I 39
 
5.9%
K 38
 
5.7%
E 34
 
5.1%
T 26
 
3.9%
P 24
 
3.6%
C 24
 
3.6%
e 23
 
3.5%
Other values (37) 258
39.0%
Common
ValueCountFrequency (%)
47261
45.6%
1 9841
 
9.5%
- 8174
 
7.9%
2 6551
 
6.3%
3 5415
 
5.2%
4 4470
 
4.3%
5 4317
 
4.2%
0 3891
 
3.8%
6 3721
 
3.6%
7 3491
 
3.4%
Other values (15) 6522
 
6.3%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147258
58.5%
ASCII 104302
41.5%
Number Forms 9
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47261
45.3%
1 9841
 
9.4%
- 8174
 
7.8%
2 6551
 
6.3%
3 5415
 
5.2%
4 4470
 
4.3%
5 4317
 
4.1%
0 3891
 
3.7%
6 3721
 
3.6%
7 3491
 
3.3%
Other values (56) 7170
 
6.9%
Hangul
ValueCountFrequency (%)
10677
 
7.3%
9793
 
6.7%
9225
 
6.3%
8578
 
5.8%
8134
 
5.5%
7209
 
4.9%
6627
 
4.5%
6373
 
4.3%
6128
 
4.2%
3471
 
2.4%
Other values (568) 71043
48.2%
Number Forms
ValueCountFrequency (%)
4
44.4%
3
33.3%
1
 
11.1%
1
 
11.1%
None
ValueCountFrequency (%)
2
50.0%
· 2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct3926
Distinct (%)39.3%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T06:53:18.294737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9999
Min length2

Characters and Unicode

Total characters49994
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2456 ?
Unique (%)24.6%

Sample

1st row48947
2nd row37883
3rd row48947
4th row48114
5th row47222
ValueCountFrequency (%)
48947 3031
30.3%
46726 33
 
0.3%
46759 20
 
0.2%
46764 16
 
0.2%
10071 14
 
0.1%
48515 12
 
0.1%
48111 12
 
0.1%
46008 11
 
0.1%
48059 11
 
0.1%
46015 11
 
0.1%
Other values (3916) 6828
68.3%
2024-04-18T06:53:18.705813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11179
22.4%
7 6246
12.5%
8 5849
11.7%
9 5336
10.7%
1 4492
9.0%
2 3685
 
7.4%
0 3436
 
6.9%
6 3364
 
6.7%
5 3267
 
6.5%
3 3133
 
6.3%
Other values (7) 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49987
> 99.9%
Other Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11179
22.4%
7 6246
12.5%
8 5849
11.7%
9 5336
10.7%
1 4492
9.0%
2 3685
 
7.4%
0 3436
 
6.9%
6 3364
 
6.7%
5 3267
 
6.5%
3 3133
 
6.3%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 49987
> 99.9%
Hangul 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11179
22.4%
7 6246
12.5%
8 5849
11.7%
9 5336
10.7%
1 4492
9.0%
2 3685
 
7.4%
0 3436
 
6.9%
6 3364
 
6.7%
5 3267
 
6.5%
3 3133
 
6.3%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49987
> 99.9%
Hangul 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11179
22.4%
7 6246
12.5%
8 5849
11.7%
9 5336
10.7%
1 4492
9.0%
2 3685
 
7.4%
0 3436
 
6.9%
6 3364
 
6.7%
5 3267
 
6.5%
3 3133
 
6.3%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

rdnwhladdr
Text

MISSING 

Distinct8407
Distinct (%)86.3%
Missing257
Missing (%)2.6%
Memory size156.2 KiB
2024-04-18T06:53:19.010573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length61
Mean length31.077389
Min length3

Characters and Unicode

Total characters302787
Distinct characters707
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7388 ?
Unique (%)75.8%

Sample

1st row부산광역시 사하구 낙동대로323번길 18 (괴정동,2층)
2nd row경상북도 포항시 남구 오천읍 남원로 85-75, 3층
3rd row부산광역시 남구 수영로196번길 9 (대연동)
4th row부산광역시 해운대구 좌동순환로433번길 30, 상가동 지하층 101호 (중동, 해운대힐스테이트위브)
5th row부산광역시 부산진구 양지로5번길 48 (양정동)
ValueCountFrequency (%)
부산광역시 5028
 
8.3%
경기도 1384
 
2.3%
2층 1331
 
2.2%
3층 1034
 
1.7%
서울특별시 772
 
1.3%
동래구 578
 
1.0%
4층 558
 
0.9%
남구 557
 
0.9%
부산진구 534
 
0.9%
해운대구 505
 
0.8%
Other values (11023) 48248
79.7%
2024-04-18T06:53:19.471117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52857
 
17.5%
11561
 
3.8%
9925
 
3.3%
1 9340
 
3.1%
9274
 
3.1%
( 8861
 
2.9%
) 8859
 
2.9%
8162
 
2.7%
, 8106
 
2.7%
2 8055
 
2.7%
Other values (697) 167787
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174380
57.6%
Space Separator 52857
 
17.5%
Decimal Number 47149
 
15.6%
Open Punctuation 8863
 
2.9%
Close Punctuation 8861
 
2.9%
Other Punctuation 8256
 
2.7%
Dash Punctuation 1370
 
0.5%
Uppercase Letter 697
 
0.2%
Math Symbol 249
 
0.1%
Lowercase Letter 96
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11561
 
6.6%
9925
 
5.7%
9274
 
5.3%
8162
 
4.7%
7397
 
4.2%
6737
 
3.9%
6350
 
3.6%
6005
 
3.4%
5100
 
2.9%
3693
 
2.1%
Other values (622) 100176
57.4%
Uppercase Letter
ValueCountFrequency (%)
B 207
29.7%
A 59
 
8.5%
S 46
 
6.6%
K 41
 
5.9%
I 39
 
5.6%
E 33
 
4.7%
C 27
 
3.9%
T 27
 
3.9%
P 22
 
3.2%
N 20
 
2.9%
Other values (16) 176
25.3%
Lowercase Letter
ValueCountFrequency (%)
e 24
25.0%
l 8
 
8.3%
o 7
 
7.3%
c 6
 
6.2%
b 6
 
6.2%
a 6
 
6.2%
i 6
 
6.2%
r 6
 
6.2%
w 5
 
5.2%
t 4
 
4.2%
Other values (7) 18
18.8%
Decimal Number
ValueCountFrequency (%)
1 9340
19.8%
2 8055
17.1%
3 5969
12.7%
0 4984
10.6%
4 4481
9.5%
5 3682
 
7.8%
6 3113
 
6.6%
7 2797
 
5.9%
8 2500
 
5.3%
9 2228
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 8106
98.2%
? 93
 
1.1%
. 26
 
0.3%
· 9
 
0.1%
& 8
 
0.1%
@ 6
 
0.1%
/ 3
 
< 0.1%
* 2
 
< 0.1%
2
 
< 0.1%
' 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
4
44.4%
3
33.3%
1
 
11.1%
1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 8861
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8859
> 99.9%
] 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 248
99.6%
+ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
52857
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1370
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174379
57.6%
Common 127605
42.1%
Latin 802
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11561
 
6.6%
9925
 
5.7%
9274
 
5.3%
8162
 
4.7%
7397
 
4.2%
6737
 
3.9%
6350
 
3.6%
6005
 
3.4%
5100
 
2.9%
3693
 
2.1%
Other values (621) 100175
57.4%
Latin
ValueCountFrequency (%)
B 207
25.8%
A 59
 
7.4%
S 46
 
5.7%
K 41
 
5.1%
I 39
 
4.9%
E 33
 
4.1%
C 27
 
3.4%
T 27
 
3.4%
e 24
 
3.0%
P 22
 
2.7%
Other values (37) 277
34.5%
Common
ValueCountFrequency (%)
52857
41.4%
1 9340
 
7.3%
( 8861
 
6.9%
) 8859
 
6.9%
, 8106
 
6.4%
2 8055
 
6.3%
3 5969
 
4.7%
0 4984
 
3.9%
4 4481
 
3.5%
5 3682
 
2.9%
Other values (18) 12411
 
9.7%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174379
57.6%
ASCII 128387
42.4%
None 11
 
< 0.1%
Number Forms 9
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52857
41.2%
1 9340
 
7.3%
( 8861
 
6.9%
) 8859
 
6.9%
, 8106
 
6.3%
2 8055
 
6.3%
3 5969
 
4.6%
0 4984
 
3.9%
4 4481
 
3.5%
5 3682
 
2.9%
Other values (59) 13193
 
10.3%
Hangul
ValueCountFrequency (%)
11561
 
6.6%
9925
 
5.7%
9274
 
5.3%
8162
 
4.7%
7397
 
4.2%
6737
 
3.9%
6350
 
3.6%
6005
 
3.4%
5100
 
2.9%
3693
 
2.1%
Other values (621) 100175
57.4%
None
ValueCountFrequency (%)
· 9
81.8%
2
 
18.2%
Number Forms
ValueCountFrequency (%)
4
44.4%
3
33.3%
1
 
11.1%
1
 
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3775
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20119101
Minimum388631.59
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:53:19.594022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum388631.59
5-th percentile19951198
Q120050223
median20181026
Q320191206
95-th percentile20201104
Maximum20210129
Range19821497
Interquartile range (IQR)140983.25

Descriptive statistics

Standard deviation239533.36
Coefficient of variation (CV)0.011905769
Kurtosis4922.3278
Mean20119101
Median Absolute Deviation (MAD)20100
Skewness-63.488067
Sum2.0119101 × 1011
Variance5.7376231 × 1010
MonotonicityNot monotonic
2024-04-18T06:53:19.744983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030204.0 100
 
1.0%
20030206.0 44
 
0.4%
20030203.0 43
 
0.4%
20191115.0 26
 
0.3%
20191213.0 26
 
0.3%
20181116.0 26
 
0.3%
20190215.0 25
 
0.2%
20181130.0 25
 
0.2%
20191220.0 25
 
0.2%
20191018.0 25
 
0.2%
Other values (3765) 9635
96.4%
ValueCountFrequency (%)
388631.593406 1
< 0.1%
10001126.0 1
< 0.1%
19720503.0 1
< 0.1%
19750416.0 1
< 0.1%
19750503.0 1
< 0.1%
19750519.0 1
< 0.1%
19751001.0 1
< 0.1%
19770203.0 1
< 0.1%
19790919.0 1
< 0.1%
19800709.0 2
< 0.1%
ValueCountFrequency (%)
20210129.0 12
0.1%
20210128.0 7
0.1%
20210127.0 7
0.1%
20210126.0 4
 
< 0.1%
20210125.0 6
0.1%
20210122.0 12
0.1%
20210121.0 8
0.1%
20210120.0 8
0.1%
20210119.0 8
0.1%
20210118.0 6
0.1%

dcbymd
Text

MISSING 

Distinct1509
Distinct (%)51.7%
Missing7081
Missing (%)70.8%
Memory size156.2 KiB
2024-04-18T06:53:20.033580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8
Mean length7.2874272
Min length4

Characters and Unicode

Total characters21272
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

Unique1156 ?
Unique (%)39.6%

Sample

1st row20111213
2nd row19991216
3rd row20171106
4th row20180302
5th row폐업일자
ValueCountFrequency (%)
폐업일자 523
 
17.9%
20180302 65
 
2.2%
20040504 52
 
1.8%
20151231 41
 
1.4%
20140411 37
 
1.3%
20070801 27
 
0.9%
20030613 20
 
0.7%
20021212 18
 
0.6%
20061215 16
 
0.5%
20121231 15
 
0.5%
Other values (1499) 2105
72.1%
2024-04-18T06:53:20.410187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6304
29.6%
2 3950
18.6%
1 3742
17.6%
3 975
 
4.6%
4 768
 
3.6%
7 724
 
3.4%
8 713
 
3.4%
5 708
 
3.3%
9 702
 
3.3%
6 591
 
2.8%
Other values (6) 2095
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19177
90.2%
Other Letter 2092
 
9.8%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6304
32.9%
2 3950
20.6%
1 3742
19.5%
3 975
 
5.1%
4 768
 
4.0%
7 724
 
3.8%
8 713
 
3.7%
5 708
 
3.7%
9 702
 
3.7%
6 591
 
3.1%
Other Letter
ValueCountFrequency (%)
523
25.0%
523
25.0%
523
25.0%
523
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19180
90.2%
Hangul 2092
 
9.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6304
32.9%
2 3950
20.6%
1 3742
19.5%
3 975
 
5.1%
4 768
 
4.0%
7 724
 
3.8%
8 713
 
3.7%
5 708
 
3.7%
9 702
 
3.7%
6 591
 
3.1%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
523
25.0%
523
25.0%
523
25.0%
523
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19180
90.2%
Hangul 2092
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6304
32.9%
2 3950
20.6%
1 3742
19.5%
3 975
 
5.1%
4 768
 
4.0%
7 724
 
3.8%
8 713
 
3.7%
5 708
 
3.7%
9 702
 
3.7%
6 591
 
3.1%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
523
25.0%
523
25.0%
523
25.0%
523
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9470 
휴업시작일자
 
522
20130122
 
1
20091112
 
1
20180701
 
1
Other values (5)
 
5

Length

Max length14
Median length4
Mean length4.1082
Min length4

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9470
94.7%
휴업시작일자 522
 
5.2%
20130122 1
 
< 0.1%
20091112 1
 
< 0.1%
20180701 1
 
< 0.1%
20180808 1
 
< 0.1%
20180525 1
 
< 0.1%
20200828 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20070801 1
 
< 0.1%

Length

2024-04-18T06:53:20.535313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:20.646334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9470
94.7%
휴업시작일자 522
 
5.2%
20130122 1
 
< 0.1%
20091112 1
 
< 0.1%
20180701 1
 
< 0.1%
20180808 1
 
< 0.1%
20180525 1
 
< 0.1%
20200828 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20070801 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9471 
휴업종료일자
 
522
20130714
 
1
20100530
 
1
20181231
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.1072
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9471
94.7%
휴업종료일자 522
 
5.2%
20130714 1
 
< 0.1%
20100530 1
 
< 0.1%
20181231 1
 
< 0.1%
20190630 1
 
< 0.1%
20230524 1
 
< 0.1%
20210228 1
 
< 0.1%
20421031 1
 
< 0.1%

Length

2024-04-18T06:53:20.768620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:20.867335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9471
94.7%
휴업종료일자 522
 
5.2%
20130714 1
 
< 0.1%
20100530 1
 
< 0.1%
20181231 1
 
< 0.1%
20190630 1
 
< 0.1%
20230524 1
 
< 0.1%
20210228 1
 
< 0.1%
20421031 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9476 
재개업일자
 
523
051-123-1234
 
1

Length

Max length12
Median length4
Mean length4.0531
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> 9476
94.8%
재개업일자 523
 
5.2%
051-123-1234 1
 
< 0.1%

Length

2024-04-18T06:53:20.985960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:21.078275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9476
94.8%
재개업일자 523
 
5.2%
051-123-1234 1
 
< 0.1%

trdstatenm
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
4990 
13
2447 
03
2189 
35
 
286
<NA>
 
57
Other values (7)
 
31

Length

Max length14
Median length5
Mean length3.5106
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row03
2nd row영업/정상
3rd row03
4th row03
5th row35

Common Values

ValueCountFrequency (%)
영업/정상 4990
49.9%
13 2447
24.5%
03 2189
21.9%
35 286
 
2.9%
<NA> 57
 
0.6%
폐업 8
 
0.1%
영업상태 8
 
0.1%
1 6
 
0.1%
02 6
 
0.1%
휴업 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-18T06:53:21.175761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업/정상 4990
49.9%
13 2447
24.5%
03 2189
21.9%
35 286
 
2.9%
na 57
 
0.6%
폐업 8
 
0.1%
영업상태 8
 
0.1%
1 6
 
0.1%
02 6
 
0.1%
휴업 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
7488 
폐업
2197 
직권말소
 
287
영업
 
14
휴업
 
7
Other values (3)
 
7

Length

Max length4
Median length3
Mean length2.8071
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 7488
74.9%
폐업 2197
 
22.0%
직권말소 287
 
2.9%
영업 14
 
0.1%
휴업 7
 
0.1%
??? 5
 
0.1%
<NA> 1
 
< 0.1%
신고취소 1
 
< 0.1%

Length

2024-04-18T06:53:21.296837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:21.435817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 7488
74.9%
폐업 2197
 
22.0%
직권말소 287
 
2.9%
영업 14
 
0.1%
휴업 7
 
0.1%
5
 
< 0.1%
na 1
 
< 0.1%
신고취소 1
 
< 0.1%

x
Text

MISSING 

Distinct7423
Distinct (%)76.6%
Missing313
Missing (%)3.1%
Memory size156.2 KiB
2024-04-18T06:53:21.655724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.948488
Min length2

Characters and Unicode

Total characters193241
Distinct characters21
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

Unique5835 ?
Unique (%)60.2%

Sample

1st row380662.18976300000
2nd row416511.192333945
3rd row390325.48550100000
4th row398933.34447400000
5th row388683.20273300000
ValueCountFrequency (%)
좌표정보(x 37
 
0.4%
380613.87795500000 8
 
0.1%
385599.32170700000 7
 
0.1%
161426.029955154 7
 
0.1%
373579.04761500000 6
 
0.1%
392607.54573000000 6
 
0.1%
192565.493522349 6
 
0.1%
202115.873649386 6
 
0.1%
393357.80475400000 6
 
0.1%
276579.535612042 6
 
0.1%
Other values (7413) 9592
99.0%
2024-04-18T06:53:22.017116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35673
18.5%
0 34320
17.8%
3 16512
8.5%
8 14100
 
7.3%
9 13103
 
6.8%
1 12995
 
6.7%
2 12974
 
6.7%
7 11299
 
5.8%
4 11114
 
5.8%
5 11002
 
5.7%
Other values (11) 20149
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147760
76.5%
Space Separator 35673
 
18.5%
Other Punctuation 9547
 
4.9%
Other Letter 150
 
0.1%
Close Punctuation 37
 
< 0.1%
Uppercase Letter 37
 
< 0.1%
Open Punctuation 37
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34320
23.2%
3 16512
11.2%
8 14100
9.5%
9 13103
 
8.9%
1 12995
 
8.8%
2 12974
 
8.8%
7 11299
 
7.6%
4 11114
 
7.5%
5 11002
 
7.4%
6 10341
 
7.0%
Other Letter
ValueCountFrequency (%)
37
24.7%
37
24.7%
37
24.7%
37
24.7%
1
 
0.7%
1
 
0.7%
Space Separator
ValueCountFrequency (%)
35673
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9547
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193054
99.9%
Hangul 150
 
0.1%
Latin 37
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
35673
18.5%
0 34320
17.8%
3 16512
8.6%
8 14100
 
7.3%
9 13103
 
6.8%
1 12995
 
6.7%
2 12974
 
6.7%
7 11299
 
5.9%
4 11114
 
5.8%
5 11002
 
5.7%
Other values (4) 19962
10.3%
Hangul
ValueCountFrequency (%)
37
24.7%
37
24.7%
37
24.7%
37
24.7%
1
 
0.7%
1
 
0.7%
Latin
ValueCountFrequency (%)
X 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193091
99.9%
Hangul 150
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35673
18.5%
0 34320
17.8%
3 16512
8.6%
8 14100
 
7.3%
9 13103
 
6.8%
1 12995
 
6.7%
2 12974
 
6.7%
7 11299
 
5.9%
4 11114
 
5.8%
5 11002
 
5.7%
Other values (5) 19999
10.4%
Hangul
ValueCountFrequency (%)
37
24.7%
37
24.7%
37
24.7%
37
24.7%
1
 
0.7%
1
 
0.7%

y
Text

MISSING 

Distinct7422
Distinct (%)76.6%
Missing313
Missing (%)3.1%
Memory size156.2 KiB
2024-04-18T06:53:22.248406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.948901
Min length6

Characters and Unicode

Total characters193245
Distinct characters27
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5833 ?
Unique (%)60.2%

Sample

1st row179887.72661300000
2nd row276742.095980593
3rd row184007.03908700000
4th row187515.39674200000
5th row188087.90348500000
ValueCountFrequency (%)
좌표정보(y 37
 
0.4%
175596.00351700000 8
 
0.1%
443010.928764189 7
 
0.1%
187606.00717200000 7
 
0.1%
191804.07825600000 6
 
0.1%
177095.68296500000 6
 
0.1%
437231.71060133 6
 
0.1%
197920.382594183 6
 
0.1%
444312.914685658 6
 
0.1%
177965.93694600000 6
 
0.1%
Other values (7412) 9592
99.0%
2024-04-18T06:53:22.620744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35542
18.4%
0 33380
17.3%
1 16832
8.7%
4 13859
 
7.2%
8 13452
 
7.0%
9 12815
 
6.6%
2 11793
 
6.1%
7 11776
 
6.1%
3 11598
 
6.0%
6 11171
 
5.8%
Other values (17) 21027
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147801
76.5%
Space Separator 35542
 
18.4%
Other Punctuation 9545
 
4.9%
Other Letter 154
 
0.1%
Dash Punctuation 83
 
< 0.1%
Close Punctuation 46
 
< 0.1%
Uppercase Letter 37
 
< 0.1%
Open Punctuation 37
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33380
22.6%
1 16832
11.4%
4 13859
9.4%
8 13452
9.1%
9 12815
 
8.7%
2 11793
 
8.0%
7 11776
 
8.0%
3 11598
 
7.8%
6 11171
 
7.6%
5 11125
 
7.5%
Other Letter
ValueCountFrequency (%)
37
24.0%
37
24.0%
37
24.0%
37
24.0%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 37
80.4%
] 9
 
19.6%
Space Separator
ValueCountFrequency (%)
35542
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9545
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193054
99.9%
Hangul 154
 
0.1%
Latin 37
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
35542
18.4%
0 33380
17.3%
1 16832
8.7%
4 13859
 
7.2%
8 13452
 
7.0%
9 12815
 
6.6%
2 11793
 
6.1%
7 11776
 
6.1%
3 11598
 
6.0%
6 11171
 
5.8%
Other values (6) 20836
10.8%
Hangul
ValueCountFrequency (%)
37
24.0%
37
24.0%
37
24.0%
37
24.0%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
Latin
ValueCountFrequency (%)
Y 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193091
99.9%
Hangul 154
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35542
18.4%
0 33380
17.3%
1 16832
8.7%
4 13859
 
7.2%
8 13452
 
7.0%
9 12815
 
6.6%
2 11793
 
6.1%
7 11776
 
6.1%
3 11598
 
6.0%
6 11171
 
5.8%
Other values (7) 20873
10.8%
Hangul
ValueCountFrequency (%)
37
24.0%
37
24.0%
37
24.0%
37
24.0%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%
1
 
0.6%

lastmodts
Real number (ℝ)

Distinct8957
Distinct (%)89.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0161095 × 1013
Minimum2.0021018 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:53:22.769900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0051226 × 1013
Q12.0140112 × 1013
median2.0181026 × 1013
Q32.0191212 × 1013
95-th percentile2.0201106 × 1013
Maximum2.0210129 × 1013
Range1.8911104 × 1011
Interquartile range (IQR)5.1100574 × 1010

Descriptive statistics

Standard deviation4.6798891 × 1010
Coefficient of variation (CV)0.0023212475
Kurtosis0.72209247
Mean2.0161095 × 1013
Median Absolute Deviation (MAD)1.9591002 × 1010
Skewness-1.2963449
Sum2.0159079 × 1017
Variance2.1901362 × 1021
MonotonicityNot monotonic
2024-04-18T06:53:22.901972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021018132120 40
 
0.4%
20200508141537 3
 
< 0.1%
20200725111244 3
 
< 0.1%
20190308090843 3
 
< 0.1%
20190412165254 3
 
< 0.1%
20181130195857 3
 
< 0.1%
20191129084655 3
 
< 0.1%
20200619091732 3
 
< 0.1%
20200221152607 3
 
< 0.1%
20200515095318 3
 
< 0.1%
Other values (8947) 9932
99.3%
ValueCountFrequency (%)
20021018132120 40
0.4%
20021226152409 1
 
< 0.1%
20021226160855 1
 
< 0.1%
20021226163050 1
 
< 0.1%
20021227103144 1
 
< 0.1%
20021227115048 1
 
< 0.1%
20021227135543 1
 
< 0.1%
20021227140112 1
 
< 0.1%
20021227140309 1
 
< 0.1%
20021227141903 1
 
< 0.1%
ValueCountFrequency (%)
20210129173709 2
< 0.1%
20210129162648 1
< 0.1%
20210129155701 1
< 0.1%
20210129151032 1
< 0.1%
20210129140505 2
< 0.1%
20210129102229 2
< 0.1%
20210129095305 1
< 0.1%
20210129091007 1
< 0.1%
20210129090328 1
< 0.1%
20210128175854 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8058 
태권도
 
722
합기도
 
454
업태구분명
 
364
권투
 
186
Other values (5)
 
216

Length

Max length5
Median length4
Mean length3.8407
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8058
80.6%
태권도 722
 
7.2%
합기도 454
 
4.5%
업태구분명 364
 
3.6%
권투 186
 
1.9%
유도 118
 
1.2%
검도 64
 
0.6%
레슬링 19
 
0.2%
우슈 13
 
0.1%
야구종목 2
 
< 0.1%

Length

2024-04-18T06:53:23.030581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:23.138754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8058
80.6%
태권도 722
 
7.2%
합기도 454
 
4.5%
업태구분명 364
 
3.6%
권투 186
 
1.9%
유도 118
 
1.2%
검도 64
 
0.6%
레슬링 19
 
0.2%
우슈 13
 
0.1%
야구종목 2
 
< 0.1%

sitetel
Text

MISSING 

Distinct210
Distinct (%)2.2%
Missing428
Missing (%)4.3%
Memory size156.2 KiB
2024-04-18T06:53:23.505224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.94672
Min length4

Characters and Unicode

Total characters114354
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

Unique181 ?
Unique (%)1.9%

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 9279
96.9%
전화번호 56
 
0.6%
055-574-1600 4
 
< 0.1%
474-2429 2
 
< 0.1%
02-406-0285 2
 
< 0.1%
02-736-3676 2
 
< 0.1%
031-768-7911 2
 
< 0.1%
031-794-9998 2
 
< 0.1%
031-232-7990 2
 
< 0.1%
0545566161 2
 
< 0.1%
Other values (200) 219
 
2.3%
2024-04-18T06:53:23.966303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28073
24.5%
- 19003
16.6%
3 18856
16.5%
2 18829
16.5%
0 9696
 
8.5%
5 9528
 
8.3%
4 9472
 
8.3%
6 200
 
0.2%
7 175
 
0.2%
9 151
 
0.1%
Other values (6) 371
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95126
83.2%
Dash Punctuation 19003
 
16.6%
Other Letter 224
 
0.2%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28073
29.5%
3 18856
19.8%
2 18829
19.8%
0 9696
 
10.2%
5 9528
 
10.0%
4 9472
 
10.0%
6 200
 
0.2%
7 175
 
0.2%
9 151
 
0.2%
8 146
 
0.2%
Other Letter
ValueCountFrequency (%)
56
25.0%
56
25.0%
56
25.0%
56
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 19003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 114130
99.8%
Hangul 224
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 28073
24.6%
- 19003
16.7%
3 18856
16.5%
2 18829
16.5%
0 9696
 
8.5%
5 9528
 
8.3%
4 9472
 
8.3%
6 200
 
0.2%
7 175
 
0.2%
9 151
 
0.1%
Other values (2) 147
 
0.1%
Hangul
ValueCountFrequency (%)
56
25.0%
56
25.0%
56
25.0%
56
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114130
99.8%
Hangul 224
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28073
24.6%
- 19003
16.7%
3 18856
16.5%
2 18829
16.5%
0 9696
 
8.5%
5 9528
 
8.3%
4 9472
 
8.3%
6 200
 
0.2%
7 175
 
0.2%
9 151
 
0.1%
Other values (2) 147
 
0.1%
Hangul
ValueCountFrequency (%)
56
25.0%
56
25.0%
56
25.0%
56
25.0%

bdngdngnum
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7967 
1
1277 
건축물동수
 
451
0
 
224
2
 
35
Other values (15)
 
46

Length

Max length5
Median length4
Mean length3.572
Min length1

Unique

Unique10 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7967
79.7%
1 1277
 
12.8%
건축물동수 451
 
4.5%
0 224
 
2.2%
2 35
 
0.4%
5 10
 
0.1%
3 9
 
0.1%
4 8
 
0.1%
6 6
 
0.1%
39 3
 
< 0.1%
Other values (10) 10
 
0.1%

Length

2024-04-18T06:53:24.114961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7967
79.7%
1 1277
 
12.8%
건축물동수 451
 
4.5%
0 224
 
2.2%
2 35
 
0.4%
5 10
 
0.1%
3 9
 
0.1%
4 8
 
0.1%
6 6
 
0.1%
39 3
 
< 0.1%
Other values (10) 10
 
0.1%

bdngyarea
Text

MISSING 

Distinct3735
Distinct (%)72.9%
Missing4874
Missing (%)48.7%
Memory size156.2 KiB
2024-04-18T06:53:24.433230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.597737
Min length1

Characters and Unicode

Total characters28694
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3201 ?
Unique (%)62.4%

Sample

1st row588.64
2nd row882.33
3rd row131.67
4th row160
5th row56293.45
ValueCountFrequency (%)
건축물연면적 307
 
6.0%
0 220
 
4.3%
1 58
 
1.1%
150 24
 
0.5%
160 16
 
0.3%
120 16
 
0.3%
140 11
 
0.2%
99 11
 
0.2%
198 9
 
0.2%
158 8
 
0.2%
Other values (3725) 4446
86.7%
2024-04-18T06:53:24.920091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3916
13.6%
1 3386
11.8%
2 2473
8.6%
4 2431
8.5%
9 2380
8.3%
3 2218
7.7%
8 2192
7.6%
6 2121
7.4%
5 2074
7.2%
7 1974
6.9%
Other values (7) 3529
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22936
79.9%
Other Punctuation 3916
 
13.6%
Other Letter 1842
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3386
14.8%
2 2473
10.8%
4 2431
10.6%
9 2380
10.4%
3 2218
9.7%
8 2192
9.6%
6 2121
9.2%
5 2074
9.0%
7 1974
8.6%
0 1687
7.4%
Other Letter
ValueCountFrequency (%)
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26852
93.6%
Hangul 1842
 
6.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3916
14.6%
1 3386
12.6%
2 2473
9.2%
4 2431
9.1%
9 2380
8.9%
3 2218
8.3%
8 2192
8.2%
6 2121
7.9%
5 2074
7.7%
7 1974
7.4%
Hangul
ValueCountFrequency (%)
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26852
93.6%
Hangul 1842
 
6.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3916
14.6%
1 3386
12.6%
2 2473
9.2%
4 2431
9.1%
9 2380
8.9%
3 2218
8.3%
8 2192
8.2%
6 2121
7.9%
5 2074
7.7%
7 1974
7.4%
Hangul
ValueCountFrequency (%)
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%
307
16.7%

puprsenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
사립
9919 
<NA>
 
50
공사립구분명
 
13
공립
 
12
??
 
5

Length

Max length19
Median length2
Mean length2.0169
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 9919
99.2%
<NA> 50
 
0.5%
공사립구분명 13
 
0.1%
공립 12
 
0.1%
?? 5
 
0.1%
2021-02-01 05:22:03 1
 
< 0.1%

Length

2024-04-18T06:53:25.044546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:25.133682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 9919
99.2%
na 50
 
0.5%
공사립구분명 13
 
0.1%
공립 12
 
0.1%
5
 
< 0.1%
2021-02-01 1
 
< 0.1%
05:22:03 1
 
< 0.1%

culphyedcobnm
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
당구장업
3398 
체육도장업
2542 
체력단련장업
2394 
골프연습장업
1257 
수영장업
 
197
Other values (11)
 
212

Length

Max length7
Median length6
Mean length4.9895
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row당구장업
2nd row체육도장업
3rd row당구장업
4th row체력단련장업
5th row당구장업

Common Values

ValueCountFrequency (%)
당구장업 3398
34.0%
체육도장업 2542
25.4%
체력단련장업 2394
23.9%
골프연습장업 1257
 
12.6%
수영장업 197
 
2.0%
<NA> 43
 
0.4%
무도학원업 43
 
0.4%
썰매장업 41
 
0.4%
빙상장업 27
 
0.3%
골프장 21
 
0.2%
Other values (6) 37
 
0.4%

Length

2024-04-18T06:53:25.247544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당구장업 3398
34.0%
체육도장업 2542
25.4%
체력단련장업 2394
23.9%
골프연습장업 1257
 
12.6%
수영장업 197
 
2.0%
na 43
 
0.4%
무도학원업 43
 
0.4%
썰매장업 41
 
0.4%
빙상장업 27
 
0.3%
골프장 21
 
0.2%
Other values (5) 37
 
0.4%

bupnm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9475 
법인명
 
522
삼성물산 주식회사 대표이사 최치훈
 
1
경원개발주식회사
 
1
다산베아채컨트리클러(주) 대표 이애자
 
1

Length

Max length20
Median length4
Mean length3.9512
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9475
94.8%
법인명 522
 
5.2%
삼성물산 주식회사 대표이사 최치훈 1
 
< 0.1%
경원개발주식회사 1
 
< 0.1%
다산베아채컨트리클러(주) 대표 이애자 1
 
< 0.1%

Length

2024-04-18T06:53:25.365356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:25.451273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9475
94.7%
법인명 522
 
5.2%
삼성물산 1
 
< 0.1%
주식회사 1
 
< 0.1%
대표이사 1
 
< 0.1%
최치훈 1
 
< 0.1%
경원개발주식회사 1
 
< 0.1%
다산베아채컨트리클러(주 1
 
< 0.1%
대표 1
 
< 0.1%
이애자 1
 
< 0.1%

insurjnyncode
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7826 
0
1379 
 
476
Y
 
304
1
 
15

Length

Max length4
Median length4
Mean length3.3478
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7826
78.3%
0 1379
 
13.8%
476
 
4.8%
Y 304
 
3.0%
1 15
 
0.1%

Length

2024-04-18T06:53:25.580404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:25.671408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7826
78.3%
0 1379
 
13.8%
476
 
4.8%
y 304
 
3.0%
1 15
 
0.1%

drmkcobnm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9473 
세부업종명
 
522
없음
 
2
회원제
 
2
일반대중
 
1

Length

Max length5
Median length4
Mean length4.0516
Min length2

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> 9473
94.7%
세부업종명 522
 
5.2%
없음 2
 
< 0.1%
회원제 2
 
< 0.1%
일반대중 1
 
< 0.1%

Length

2024-04-18T06:53:25.763941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:25.850976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9473
94.7%
세부업종명 522
 
5.2%
없음 2
 
< 0.1%
회원제 2
 
< 0.1%
일반대중 1
 
< 0.1%

ldercnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7128 
1
1970 
2
 
422
지도자수
 
341
0
 
127
Other values (4)
 
12

Length

Max length4
Median length4
Mean length3.2407
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7128
71.3%
1 1970
 
19.7%
2 422
 
4.2%
지도자수 341
 
3.4%
0 127
 
1.3%
3 8
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-18T06:53:25.955122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:53:26.073096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7128
71.3%
1 1970
 
19.7%
2 422
 
4.2%
지도자수 341
 
3.4%
0 127
 
1.3%
3 8
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

memcolltotstfnum
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9430 
회원모집총인원
 
519
50
 
6
100
 
6
30
 
4
Other values (18)
 
35

Length

Max length7
Median length4
Mean length4.1471
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9430
94.3%
회원모집총인원 519
 
5.2%
50 6
 
0.1%
100 6
 
0.1%
30 4
 
< 0.1%
60 4
 
< 0.1%
150 3
 
< 0.1%
1 3
 
< 0.1%
20 3
 
< 0.1%
0 3
 
< 0.1%
Other values (13) 19
 
0.2%

Length

2024-04-18T06:53:26.262812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9430
94.3%
회원모집총인원 519
 
5.2%
50 6
 
0.1%
100 6
 
0.1%
30 4
 
< 0.1%
60 4
 
< 0.1%
150 3
 
< 0.1%
1 3
 
< 0.1%
20 3
 
< 0.1%
0 3
 
< 0.1%
Other values (13) 19
 
0.2%
Distinct3
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2021-02-01 05:22:03
Maximum2021-02-01 05:22:05
2024-04-18T06:53:26.356793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:53:26.453595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
565856563340000CDFH330108200600000110_32_01_PI2018-08-31 23:59:59.0<NA>패밀리당구장604813부산광역시 사하구 괴정동 580-13번지 2층48947부산광역시 사하구 낙동대로323번길 18 (괴정동,2층)20060127.020111213<NA><NA><NA>03폐업380662.18976300000179887.7266130000020111213161740<NA>051-123-12341588.64사립당구장업<NA><NA><NA><NA><NA>2021-02-01 05:22:04
905890585020000CDFH330102201900000610_41_01_PI2019-06-30 02:21:24.0체육도장업TEAM MAD<NA>경상북도 포항시 남구 오천읍 원리 893-107번지37883경상북도 포항시 남구 오천읍 남원로 85-75, 3층20190628.0<NA><NA><NA><NA>영업/정상영업중416511.192333945276742.09598059320190628181641우슈051-123-1234<NA>882.33사립체육도장업<NA><NA><NA>1<NA>2021-02-01 05:22:04
495149483310000CDFH330108199800001310_32_01_PI2018-08-31 23:59:59.0<NA>은실당구장608813부산광역시 남구 대연동 1752-16번지48947부산광역시 남구 수영로196번길 9 (대연동)19981026.019991216<NA><NA><NA>03폐업390325.48550100000184007.0390870000020030130144723<NA>051-123-1234<NA>131.67사립당구장업<NA>0<NA><NA><NA>2021-02-01 05:22:04
152915273330000CDFH330106201600000110_42_01_PI2018-08-31 23:59:59.0<NA>점핑캣 바이 메디핏<NA>부산광역시 해운대구 중동 1519-3번지48114부산광역시 해운대구 좌동순환로433번길 30, 상가동 지하층 101호 (중동, 해운대힐스테이트위브)20160224.020171106<NA><NA><NA>03폐업398933.34447400000187515.3967420000020171106173510<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA><NA><NA>2021-02-01 05:22:03
426442573290000CDFH330108200300006810_32_01_PI2018-08-31 23:59:59.0<NA>포커스당구장<NA>부산광역시 부산진구 양정동 350-70번지47222부산광역시 부산진구 양지로5번길 48 (양정동)20030206.020180302<NA><NA><NA>35직권말소388683.20273300000188087.9034850000020180302131320<NA>051-123-1234<NA>160사립당구장업<NA><NA><NA><NA><NA>2021-02-01 05:22:03
916991693240000CDFH330102201900000510_41_01_PI2019-07-13 02:21:44.0체육도장업캡틴복싱클럽<NA>서울특별시 강동구 천호동 393-43번지 신성빌딩05330서울특별시 강동구 구천면로 250, 신성빌딩 5층 (천호동)20190711.0<NA><NA><NA><NA>영업/정상영업중211552.085729225448928.78821000320190711114410권투051-123-1234<NA><NA>사립체육도장업<NA><NA><NA><NA><NA>2021-02-01 05:22:04
741074103220000CDFH330106201800004410_42_01_PI2019-01-02 02:20:35.0체력단련장업로그짐<NA>서울특별시 강남구 대치동 890-59번지 롯데골드로즈206193서울특별시 강남구 선릉로86길 31, 롯데골드로즈2 2층 214호 (대치동)20181231.0<NA><NA><NA><NA>영업/정상영업중204536.822020513444660.78426933920181231173759<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA><NA><NA>2021-02-01 05:22:04
187718763370000CDFH330106201500000410_42_01_PI2018-08-31 23:59:59.0<NA>국제휘트니스611702부산광역시 연제구 거제동 76-2번지 국제빌딩 지하 1층47505부산광역시 연제구 중앙대로 1217 (거제동)20150604.0<NA><NA><NA><NA>13영업중389429.27576400000190832.8620450000020180511110439<NA>051-123-1234<NA>56293.45사립체력단련장업<NA><NA><NA><NA><NA>2021-02-01 05:22:03
11308113084190000CDFH330101202000000110_35_01_PI2020-04-05 00:23:35.0수영장업그랑블루 어린이수영장지번우편번호강원도 원주시 반곡동 1779번지26457강원도 원주시 늘품로 213 (반곡동)20200403.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중285466.853903742426139.54250013920200403130216업태구분명051-123-1234건축물동수665사립수영장업법인명Y세부업종명2회원모집총인원2021-02-01 05:22:05
801280123120000CDFH330106201900000410_42_01_PI2019-03-10 02:21:45.0체력단련장업아이소포스짐<NA>서울특별시 서대문구 창천동 31-92번지 J-Tower03776서울특별시 서대문구 명물길 19, J-Tower 나동 7층 (창천동)20190308.0<NA><NA><NA><NA>영업/정상영업중194425.547743193450629.48797848120190308201343<NA>051-123-1234<NA>1826사립체력단련장업<NA><NA><NA><NA><NA>2021-02-01 05:22:04
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
910991093780000CDFH330106201900001710_42_01_PI2019-07-07 02:21:30.0체력단련장업동네헬스<NA>경기도 성남시 수정구 태평동 3475번지 태광빌딩13291경기도 성남시 수정구 탄리로 86, 태광빌딩 3층 (태평동)20190705.0<NA><NA><NA><NA>영업/정상영업중211933.203385395437948.67171088420190705172010<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA>1<NA>2021-02-01 05:22:04
11488114883940000CDFH330102202000001010_41_01_PI2020-04-23 00:23:20.0체육도장업KM GYM 합기도 킥복싱<NA>경기도 고양시 일산동구 식사동 1582-1번지 502호10324경기도 고양시 일산동구 위시티로 32, 502호 (식사동)20200421.0<NA><NA><NA><NA>영업/정상영업중<NA><NA>20200421143413합기도051-123-1234<NA><NA>사립체육도장업<NA><NA><NA><NA><NA>2021-02-01 05:22:05
131813133310000CDFH330106201400000410_42_01_PI2018-08-31 23:59:59.0<NA>엑스피 바디 스튜디오608043부산광역시 남구 문현동 405-6번지 3층48415부산광역시 남구 수영로 19, 3층 (문현동)20140723.0<NA><NA><NA><NA>13영업중388655.07386500000184283.0939470000020140723135609<NA>051-123-12341836.75사립체력단련장업<NA><NA><NA>1<NA>2021-02-01 05:22:03
228622893290000CDFH330102200300006710_41_01_PI2018-08-31 23:59:59.0<NA>팀레전드 수양 태권도장<NA>부산광역시 부산진구 개금동 540-240번지 가동 2층47387부산광역시 부산진구 엄광로 36-3 (개금동)20030204.020161121<NA><NA><NA>35직권말소384087.24600000000185374.3413850000020161121174943태권도051-123-1234<NA><NA>사립체육도장업<NA><NA><NA><NA><NA>2021-02-01 05:22:03
730973073350000CDFH330108201800000410_32_01_PI2018-12-19 02:20:21.0당구장업작당당구장<NA>부산광역시 금정구 부곡동 394-13번지 2층46311부산광역시 금정구 동현로16번길 95, 2층 (부곡동)20181217.0<NA><NA><NA><NA>영업/정상영업중390000.711703439193171.52823851720181217130049<NA>051-123-1234<NA>468.26사립당구장업<NA><NA><NA><NA><NA>2021-02-01 05:22:04
3614433330000CDFH330105200700000810_31_01_PI2018-08-31 23:59:59.0<NA>왕스크린612020부산광역시 해운대구 우동 1498번지48947부산광역시 해운대구 센텀동로 9 (우동)20071228.020090413<NA><NA><NA>03폐업394318.43300500000188115.3502870000020090414173839<NA>051-123-1234<NA><NA>사립골프연습장업<NA>0<NA><NA><NA>2021-02-01 05:22:03
272427233320000CDFH330102199600000410_41_01_PI2018-08-31 23:59:59.0<NA>무진2체육관616845부산광역시 북구 화명동 741-4번지 난애빌딩 501호48947부산광역시 북구 화명대로 92, 501호 (화명동,난애빌딩)19960711.020080731<NA><NA><NA>03폐업383714.72476200000194939.0909740000020080731171321<NA>051-123-1234<NA><NA>사립체육도장업<NA>0<NA><NA><NA>2021-02-01 05:22:03
12005120054230000CDFH330105202000000110_31_01_PI2020-07-05 00:23:17.0골프연습장업금호 썬라이즈스크린골프<NA>강원도 속초시 금호동 482-18 삼성홈프레스티지224837강원도 속초시 청초호반로 291, 삼성홈프레스티지2 2층 202~204호 (금호동)20200703.0<NA><NA><NA><NA>영업/정상영업중339107.157800369523290.12640144920200703095746<NA>051-123-1234<NA>23614.23사립골프연습장업<NA><NA><NA><NA><NA>2021-02-01 05:22:05
146414623320000CDFH330106201300000110_42_01_PI2018-08-31 23:59:59.0<NA>펀앤조이616852부산광역시 북구 화명동 2271-5번지46524부산광역시 북구 화명대로 17, 4층 402호 (화명동, 목양프라자)20131030.0<NA><NA><NA><NA>13영업중382994.91711300000195062.6103210000020170110155053<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA>1<NA>2021-02-01 05:22:03
148114793330000CDFH330106201600001010_42_01_PI2018-08-31 23:59:59.0<NA>레이짐<NA>부산광역시 해운대구 우동 1507번지48060부산광역시 해운대구 센텀3로 32, 215호 (우동, 트럼프월드센텀2)20161214.0<NA><NA><NA><NA>13영업중394428.63864400000187692.2816950000020161214163941<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA><NA><NA>2021-02-01 05:22:03