Overview

Dataset statistics

Number of variables34
Number of observations10000
Missing cells18684
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 MiB
Average record size in memory283.0 B

Variable types

Text12
Numeric3
Categorical18
DateTime1

Alerts

updategbn is highly imbalanced (94.7%)Imbalance
clgstdt is highly imbalanced (91.9%)Imbalance
clgenddt is highly imbalanced (91.7%)Imbalance
ropnymd is highly imbalanced (81.7%)Imbalance
dtlstatenm is highly imbalanced (67.4%)Imbalance
uptaenm is highly imbalanced (64.9%)Imbalance
bdngdngnum is highly imbalanced (75.9%)Imbalance
puprsenm is highly imbalanced (97.0%)Imbalance
bupnm is highly imbalanced (81.7%)Imbalance
insurjnyncode is highly imbalanced (54.4%)Imbalance
drmkcobnm is highly imbalanced (85.4%)Imbalance
ldercnt is highly imbalanced (60.7%)Imbalance
memcolltotstfnum is highly imbalanced (92.3%)Imbalance
sitepostno has 5427 (54.3%) missing valuesMissing
sitewhladdr has 120 (1.2%) missing valuesMissing
rdnwhladdr has 271 (2.7%) missing valuesMissing
dcbymd has 7063 (70.6%) missing valuesMissing
x has 301 (3.0%) missing valuesMissing
y has 301 (3.0%) missing valuesMissing
sitetel has 332 (3.3%) missing valuesMissing
bdngyarea has 4864 (48.6%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -63.3238542)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 21:57:46.595544
Analysis finished2024-04-17 21:57:48.720471
Duration2.12 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
2024-04-18T06:57:48.973684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.1701
Min length1

Characters and Unicode

Total characters41701
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 row487
2nd row9596
3rd row6664
4th row5723
5th row7497
ValueCountFrequency (%)
487 1
 
< 0.1%
1877 1
 
< 0.1%
10030 1
 
< 0.1%
689 1
 
< 0.1%
6016 1
 
< 0.1%
11989 1
 
< 0.1%
3978 1
 
< 0.1%
12636 1
 
< 0.1%
13370 1
 
< 0.1%
784 1
 
< 0.1%
Other values (9991) 9991
99.9%
2024-04-18T06:57:49.423573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7038
16.9%
2 4592
11.0%
3 4032
9.7%
5 3763
9.0%
4 3742
9.0%
7 3731
8.9%
0 3713
8.9%
6 3711
8.9%
9 3701
8.9%
8 3669
8.8%
Other values (9) 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41692
> 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 7038
16.9%
2 4592
11.0%
3 4032
9.7%
5 3763
9.0%
4 3742
9.0%
7 3731
8.9%
0 3713
8.9%
6 3711
8.9%
9 3701
8.9%
8 3669
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 41693
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7038
16.9%
2 4592
11.0%
3 4032
9.7%
5 3763
9.0%
4 3742
9.0%
7 3731
8.9%
0 3713
8.9%
6 3711
8.9%
9 3701
8.9%
8 3669
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 41701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7038
16.9%
2 4592
11.0%
3 4032
9.7%
5 3763
9.0%
4 3742
9.0%
7 3731
8.9%
0 3713
8.9%
6 3711
8.9%
9 3701
8.9%
8 3669
8.8%
Other values (9) 9
 
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct233
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3734221.2
Minimum614853
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:57:49.552514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum614853
5-th percentile3200000
Q13300000
median3360000
Q33930000
95-th percentile5530000
Maximum6520000
Range5905147
Interquartile range (IQR)630000

Descriptive statistics

Standard deviation740181.43
Coefficient of variation (CV)0.19821574
Kurtosis2.4949295
Mean3734221.2
Median Absolute Deviation (MAD)80000
Skewness1.8051486
Sum3.7342212 × 1010
Variance5.4786854 × 1011
MonotonicityNot monotonic
2024-04-18T06:57:49.680662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3300000 627
 
6.3%
3290000 578
 
5.8%
3330000 533
 
5.3%
3310000 516
 
5.2%
3340000 487
 
4.9%
3350000 420
 
4.2%
3390000 392
 
3.9%
3320000 362
 
3.6%
3370000 294
 
2.9%
3380000 241
 
2.4%
Other values (223) 5550
55.5%
ValueCountFrequency (%)
614853 1
 
< 0.1%
3000000 16
0.2%
3010000 19
0.2%
3020000 17
0.2%
3030000 28
0.3%
3040000 24
0.2%
3050000 25
0.2%
3060000 18
0.2%
3070000 19
0.2%
3080000 12
0.1%
ValueCountFrequency (%)
6520000 23
 
0.2%
6510000 86
0.9%
6470000 2
 
< 0.1%
6460000 1
 
< 0.1%
6440000 1
 
< 0.1%
6430000 1
 
< 0.1%
6420000 1
 
< 0.1%
6260000 5
 
0.1%
5710000 106
1.1%
5700000 5
 
0.1%

mgtno
Text

Distinct1851
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T06:57:49.878932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length20.0023
Min length15

Characters and Unicode

Total characters200023
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

Unique702 ?
Unique (%)7.0%

Sample

1st rowCDFH3301052009000006
2nd rowCDFH3301022019000004
3rd rowCDFH3301082012000001
4th rowCDFH3301082004000009
5th rowCDFH3301082019000001
ValueCountFrequency (%)
cdfh3301082019000001 130
 
1.3%
cdfh3301082019000002 106
 
1.1%
cdfh3301022020000001 102
 
1.0%
cdfh3301082020000001 98
 
1.0%
cdfh3301062019000001 91
 
0.9%
cdfh3301022020000003 90
 
0.9%
cdfh3301052019000001 90
 
0.9%
cdfh3301022019000001 89
 
0.9%
cdfh3301022020000002 84
 
0.8%
cdfh3301082020000003 82
 
0.8%
Other values (1845) 9042
90.4%
2024-04-18T06:57:50.236626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81800
40.9%
3 22194
 
11.1%
1 19989
 
10.0%
2 16023
 
8.0%
C 9988
 
5.0%
F 9988
 
5.0%
H 9988
 
5.0%
D 9988
 
5.0%
9 5759
 
2.9%
8 5173
 
2.6%
Other values (21) 9133
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160018
80.0%
Uppercase Letter 39952
 
20.0%
Dash Punctuation 31
 
< 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 81800
51.1%
3 22194
 
13.9%
1 19989
 
12.5%
2 16023
 
10.0%
9 5759
 
3.6%
8 5173
 
3.2%
6 3588
 
2.2%
5 2667
 
1.7%
4 1599
 
1.0%
7 1226
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 9988
25.0%
F 9988
25.0%
H 9988
25.0%
D 9988
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
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 160056
80.0%
Latin 39952
 
20.0%
Hangul 15
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81800
51.1%
3 22194
 
13.9%
1 19989
 
12.5%
2 16023
 
10.0%
9 5759
 
3.6%
8 5173
 
3.2%
6 3588
 
2.2%
5 2667
 
1.7%
4 1599
 
1.0%
7 1226
 
0.8%
Other values (4) 38
 
< 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 9988
25.0%
F 9988
25.0%
H 9988
25.0%
D 9988
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200008
> 99.9%
Hangul 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81800
40.9%
3 22194
 
11.1%
1 19989
 
10.0%
2 16023
 
8.0%
C 9988
 
5.0%
F 9988
 
5.0%
H 9988
 
5.0%
D 9988
 
5.0%
9 5759
 
2.9%
8 5173
 
2.6%
Other values (8) 9118
 
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

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10_32_01_P
3458 
10_41_01_P
2565 
10_42_01_P
2276 
10_31_01_P
1292 
10_35_01_P
 
205
Other values (9)
 
204

Length

Max length10
Median length10
Mean length9.9995
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row10_31_01_P
2nd row10_41_01_P
3rd row10_32_01_P
4th row10_32_01_P
5th row10_32_01_P

Common Values

ValueCountFrequency (%)
10_32_01_P 3458
34.6%
10_41_01_P 2565
25.7%
10_42_01_P 2276
22.8%
10_31_01_P 1292
 
12.9%
10_35_01_P 205
 
2.1%
10_37_01_P 54
 
0.5%
10_39_01_P 45
 
0.4%
10_33_02_P 41
 
0.4%
10_33_01_P 20
 
0.2%
10_34_01_P 16
 
0.2%
Other values (4) 28
 
0.3%

Length

2024-04-18T06:57:50.360038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10_32_01_p 3458
34.6%
10_41_01_p 2565
25.7%
10_42_01_p 2276
22.8%
10_31_01_p 1292
 
12.9%
10_35_01_p 205
 
2.1%
10_37_01_p 54
 
0.5%
10_39_01_p 45
 
0.4%
10_33_02_p 41
 
0.4%
10_33_01_p 20
 
0.2%
10_34_01_p 16
 
0.2%
Other values (4) 28
 
0.3%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9897 
U
 
102
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 9897
99.0%
U 102
 
1.0%
부산광역시 부산진구 중앙대로 923-1, 2층 (양정동) 1
 
< 0.1%

Length

2024-04-18T06:57:50.456990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:57:50.536924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9897
98.9%
u 102
 
1.0%
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%
Distinct598
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-12-05 00:00:00
Maximum2021-01-02 00:23:15
2024-04-18T06:57:50.640654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:57:50.768410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5086 
체력단련장업
1387 
체육도장업
1336 
당구장업
1221 
골프연습장업
656 
Other values (9)
 
314

Length

Max length7
Median length4
Mean length4.5572
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5086
50.9%
체력단련장업 1387
 
13.9%
체육도장업 1336
 
13.4%
당구장업 1221
 
12.2%
골프연습장업 656
 
6.6%
수영장업 136
 
1.4%
썰매장업 45
 
0.4%
무도학원업 41
 
0.4%
종합체육시설업 34
 
0.3%
무도장업 20
 
0.2%
Other values (4) 38
 
0.4%

Length

2024-04-18T06:57:50.881549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5086
50.9%
체력단련장업 1387
 
13.9%
체육도장업 1336
 
13.4%
당구장업 1221
 
12.2%
골프연습장업 656
 
6.6%
수영장업 136
 
1.4%
썰매장업 45
 
0.4%
무도학원업 41
 
0.4%
종합체육시설업 34
 
0.3%
무도장업 20
 
0.2%
Other values (4) 38
 
0.4%

bplcnm
Text

Distinct7563
Distinct (%)75.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T06:57:51.168222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length7.2417242
Min length1

Characters and Unicode

Total characters72410
Distinct characters870
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6208 ?
Unique (%)62.1%

Sample

1st row신평스크린골프
2nd row강한아이 태권도장
3rd row스타당구장클럽
4th rowOK당구클럽
5th row킹 당구장
ValueCountFrequency (%)
당구장 365
 
2.5%
당구클럽 313
 
2.1%
합기도 183
 
1.2%
태권도 166
 
1.1%
휘트니스 151
 
1.0%
태권도장 137
 
0.9%
gym 119
 
0.8%
골프 94
 
0.6%
용인대 86
 
0.6%
스크린골프 74
 
0.5%
Other values (7825) 12957
88.5%
2024-04-18T06:57:51.588217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4646
 
6.4%
3322
 
4.6%
3278
 
4.5%
3043
 
4.2%
2994
 
4.1%
1863
 
2.6%
1465
 
2.0%
1450
 
2.0%
1281
 
1.8%
1169
 
1.6%
Other values (860) 47899
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60763
83.9%
Space Separator 4646
 
6.4%
Uppercase Letter 3978
 
5.5%
Lowercase Letter 1274
 
1.8%
Decimal Number 630
 
0.9%
Close Punctuation 400
 
0.6%
Open Punctuation 393
 
0.5%
Other Punctuation 258
 
0.4%
Dash Punctuation 51
 
0.1%
Math Symbol 8
 
< 0.1%
Other values (4) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3322
 
5.5%
3278
 
5.4%
3043
 
5.0%
2994
 
4.9%
1863
 
3.1%
1465
 
2.4%
1450
 
2.4%
1281
 
2.1%
1169
 
1.9%
1148
 
1.9%
Other values (772) 39750
65.4%
Uppercase Letter
ValueCountFrequency (%)
G 364
 
9.2%
M 313
 
7.9%
T 301
 
7.6%
S 278
 
7.0%
P 248
 
6.2%
A 220
 
5.5%
Y 214
 
5.4%
O 196
 
4.9%
K 185
 
4.7%
I 175
 
4.4%
Other values (16) 1484
37.3%
Lowercase Letter
ValueCountFrequency (%)
e 123
 
9.7%
i 119
 
9.3%
o 109
 
8.6%
n 108
 
8.5%
a 80
 
6.3%
t 80
 
6.3%
s 76
 
6.0%
y 72
 
5.7%
m 68
 
5.3%
r 67
 
5.3%
Other values (15) 372
29.2%
Decimal Number
ValueCountFrequency (%)
2 176
27.9%
1 100
15.9%
3 69
 
11.0%
0 66
 
10.5%
5 52
 
8.3%
4 51
 
8.1%
7 38
 
6.0%
9 29
 
4.6%
8 27
 
4.3%
6 22
 
3.5%
Other Punctuation
ValueCountFrequency (%)
& 99
38.4%
. 94
36.4%
, 22
 
8.5%
' 17
 
6.6%
: 9
 
3.5%
· 6
 
2.3%
/ 4
 
1.6%
# 3
 
1.2%
? 3
 
1.2%
1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 4
50.0%
1
 
12.5%
< 1
 
12.5%
> 1
 
12.5%
~ 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 399
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 392
99.7%
[ 1
 
0.3%
Other Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Letter Number
ValueCountFrequency (%)
4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60759
83.9%
Common 6390
 
8.8%
Latin 5256
 
7.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3322
 
5.5%
3278
 
5.4%
3043
 
5.0%
2994
 
4.9%
1863
 
3.1%
1465
 
2.4%
1450
 
2.4%
1281
 
2.1%
1169
 
1.9%
1148
 
1.9%
Other values (768) 39746
65.4%
Latin
ValueCountFrequency (%)
G 364
 
6.9%
M 313
 
6.0%
T 301
 
5.7%
S 278
 
5.3%
P 248
 
4.7%
A 220
 
4.2%
Y 214
 
4.1%
O 196
 
3.7%
K 185
 
3.5%
I 175
 
3.3%
Other values (42) 2762
52.5%
Common
ValueCountFrequency (%)
4646
72.7%
) 399
 
6.2%
( 392
 
6.1%
2 176
 
2.8%
1 100
 
1.6%
& 99
 
1.5%
. 94
 
1.5%
3 69
 
1.1%
0 66
 
1.0%
5 52
 
0.8%
Other values (25) 297
 
4.6%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60758
83.9%
ASCII 11631
 
16.1%
None 9
 
< 0.1%
CJK 5
 
< 0.1%
Number Forms 4
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4646
39.9%
) 399
 
3.4%
( 392
 
3.4%
G 364
 
3.1%
M 313
 
2.7%
T 301
 
2.6%
S 278
 
2.4%
P 248
 
2.1%
A 220
 
1.9%
Y 214
 
1.8%
Other values (70) 4256
36.6%
Hangul
ValueCountFrequency (%)
3322
 
5.5%
3278
 
5.4%
3043
 
5.0%
2994
 
4.9%
1863
 
3.1%
1465
 
2.4%
1450
 
2.4%
1281
 
2.1%
1169
 
1.9%
1148
 
1.9%
Other values (767) 39745
65.4%
None
ValueCountFrequency (%)
· 6
66.7%
1
 
11.1%
1
 
11.1%
1
 
11.1%
Number Forms
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct812
Distinct (%)17.8%
Missing5427
Missing (%)54.3%
Memory size156.2 KiB
2024-04-18T06:57:51.865989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters27438
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

Unique250 ?
Unique (%)5.5%

Sample

1st row604834
2nd row지번우편번호
3rd row619963
4th row604842
5th row617833
ValueCountFrequency (%)
지번우편번호 506
 
11.1%
608805 47
 
1.0%
604851 45
 
1.0%
607815 37
 
0.8%
616852 37
 
0.8%
609839 36
 
0.8%
608810 34
 
0.7%
607804 31
 
0.7%
619963 31
 
0.7%
619903 28
 
0.6%
Other values (802) 3741
81.8%
2024-04-18T06:57:52.251472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 4969
18.1%
8 4300
15.7%
0 4075
14.9%
1 3621
13.2%
2 1754
 
6.4%
4 1434
 
5.2%
7 1373
 
5.0%
3 1294
 
4.7%
1012
 
3.7%
9 920
 
3.4%
Other values (6) 2686
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24397
88.9%
Other Letter 3036
 
11.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 4969
20.4%
8 4300
17.6%
0 4075
16.7%
1 3621
14.8%
2 1754
 
7.2%
4 1434
 
5.9%
7 1373
 
5.6%
3 1294
 
5.3%
9 920
 
3.8%
5 657
 
2.7%
Other Letter
ValueCountFrequency (%)
1012
33.3%
506
16.7%
506
16.7%
506
16.7%
506
16.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24402
88.9%
Hangul 3036
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 4969
20.4%
8 4300
17.6%
0 4075
16.7%
1 3621
14.8%
2 1754
 
7.2%
4 1434
 
5.9%
7 1373
 
5.6%
3 1294
 
5.3%
9 920
 
3.8%
5 657
 
2.7%
Hangul
ValueCountFrequency (%)
1012
33.3%
506
16.7%
506
16.7%
506
16.7%
506
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24402
88.9%
Hangul 3036
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 4969
20.4%
8 4300
17.6%
0 4075
16.7%
1 3621
14.8%
2 1754
 
7.2%
4 1434
 
5.9%
7 1373
 
5.6%
3 1294
 
5.3%
9 920
 
3.8%
5 657
 
2.7%
Hangul
ValueCountFrequency (%)
1012
33.3%
506
16.7%
506
16.7%
506
16.7%
506
16.7%

sitewhladdr
Text

MISSING 

Distinct8250
Distinct (%)83.5%
Missing120
Missing (%)1.2%
Memory size156.2 KiB
2024-04-18T06:57:52.533767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length51
Mean length25.473583
Min length4

Characters and Unicode

Total characters251679
Distinct characters647
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

Unique7043 ?
Unique (%)71.3%

Sample

1st row부산광역시 사하구 신평동 452-23번지 6층
2nd row대구광역시 수성구 두산동 101-19번지
3rd row부산광역시 기장군 정관읍 매학리 748-6번지 정관테라스 311~313호
4th row부산광역시 사하구 장림동 1124-11번지
5th row경기도 양주시 남면 신산리 282-4번지
ValueCountFrequency (%)
부산광역시 5280
 
11.0%
경기도 1351
 
2.8%
서울특별시 751
 
1.6%
동래구 627
 
1.3%
남구 595
 
1.2%
부산진구 577
 
1.2%
해운대구 523
 
1.1%
북구 489
 
1.0%
2층 470
 
1.0%
사하구 450
 
0.9%
Other values (11563) 36741
76.8%
2024-04-18T06:57:53.339071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47167
 
18.7%
10688
 
4.2%
9768
 
3.9%
1 9751
 
3.9%
9379
 
3.7%
8729
 
3.5%
8210
 
3.3%
- 8180
 
3.3%
7341
 
2.9%
6673
 
2.7%
Other values (637) 125793
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147373
58.6%
Decimal Number 47651
 
18.9%
Space Separator 47167
 
18.7%
Dash Punctuation 8180
 
3.3%
Uppercase Letter 585
 
0.2%
Other Punctuation 294
 
0.1%
Open Punctuation 139
 
0.1%
Close Punctuation 138
 
0.1%
Lowercase Letter 82
 
< 0.1%
Math Symbol 61
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10688
 
7.3%
9768
 
6.6%
9379
 
6.4%
8729
 
5.9%
8210
 
5.6%
7341
 
5.0%
6673
 
4.5%
6506
 
4.4%
6199
 
4.2%
3404
 
2.3%
Other values (565) 70476
47.8%
Uppercase Letter
ValueCountFrequency (%)
B 115
19.7%
S 44
 
7.5%
A 41
 
7.0%
I 39
 
6.7%
K 38
 
6.5%
E 36
 
6.2%
C 31
 
5.3%
P 28
 
4.8%
T 25
 
4.3%
W 20
 
3.4%
Other values (16) 168
28.7%
Lowercase Letter
ValueCountFrequency (%)
e 22
26.8%
l 8
 
9.8%
r 7
 
8.5%
u 7
 
8.5%
a 5
 
6.1%
o 5
 
6.1%
t 5
 
6.1%
c 4
 
4.9%
i 4
 
4.9%
s 3
 
3.7%
Other values (8) 12
14.6%
Decimal Number
ValueCountFrequency (%)
1 9751
20.5%
2 6553
13.8%
3 5468
11.5%
4 4598
9.6%
5 4285
9.0%
0 3924
8.2%
6 3665
 
7.7%
7 3485
 
7.3%
8 3141
 
6.6%
9 2781
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 230
78.2%
. 28
 
9.5%
? 14
 
4.8%
/ 7
 
2.4%
& 7
 
2.4%
@ 5
 
1.7%
· 2
 
0.7%
1
 
0.3%
Letter Number
ValueCountFrequency (%)
6
66.7%
1
 
11.1%
1
 
11.1%
1
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 60
98.4%
+ 1
 
1.6%
Space Separator
ValueCountFrequency (%)
47167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147373
58.6%
Common 103630
41.2%
Latin 676
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10688
 
7.3%
9768
 
6.6%
9379
 
6.4%
8729
 
5.9%
8210
 
5.6%
7341
 
5.0%
6673
 
4.5%
6506
 
4.4%
6199
 
4.2%
3404
 
2.3%
Other values (565) 70476
47.8%
Latin
ValueCountFrequency (%)
B 115
17.0%
S 44
 
6.5%
A 41
 
6.1%
I 39
 
5.8%
K 38
 
5.6%
E 36
 
5.3%
C 31
 
4.6%
P 28
 
4.1%
T 25
 
3.7%
e 22
 
3.3%
Other values (38) 257
38.0%
Common
ValueCountFrequency (%)
47167
45.5%
1 9751
 
9.4%
- 8180
 
7.9%
2 6553
 
6.3%
3 5468
 
5.3%
4 4598
 
4.4%
5 4285
 
4.1%
0 3924
 
3.8%
6 3665
 
3.5%
7 3485
 
3.4%
Other values (14) 6554
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147373
58.6%
ASCII 104294
41.4%
Number Forms 9
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47167
45.2%
1 9751
 
9.3%
- 8180
 
7.8%
2 6553
 
6.3%
3 5468
 
5.2%
4 4598
 
4.4%
5 4285
 
4.1%
0 3924
 
3.8%
6 3665
 
3.5%
7 3485
 
3.3%
Other values (56) 7218
 
6.9%
Hangul
ValueCountFrequency (%)
10688
 
7.3%
9768
 
6.6%
9379
 
6.4%
8729
 
5.9%
8210
 
5.6%
7341
 
5.0%
6673
 
4.5%
6506
 
4.4%
6199
 
4.2%
3404
 
2.3%
Other values (565) 70476
47.8%
Number Forms
ValueCountFrequency (%)
6
66.7%
1
 
11.1%
1
 
11.1%
1
 
11.1%
None
ValueCountFrequency (%)
· 2
66.7%
1
33.3%
Distinct3906
Distinct (%)39.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T06:57:53.697320image/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

Unique2462 ?
Unique (%)24.6%

Sample

1st row48947
2nd row42171
3rd row48947
4th row49476
5th row11404
ValueCountFrequency (%)
48947 3098
31.0%
46726 44
 
0.4%
46759 16
 
0.2%
48111 15
 
0.2%
46764 14
 
0.1%
46230 14
 
0.1%
46015 13
 
0.1%
11901 13
 
0.1%
10905 12
 
0.1%
10071 12
 
0.1%
Other values (3896) 6748
67.5%
2024-04-18T06:57:54.191635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11340
22.7%
7 6266
12.5%
8 5905
11.8%
9 5342
10.7%
1 4449
 
8.9%
2 3622
 
7.2%
0 3407
 
6.8%
6 3301
 
6.6%
5 3282
 
6.6%
3 3073
 
6.1%
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 11340
22.7%
7 6266
12.5%
8 5905
11.8%
9 5342
10.7%
1 4449
 
8.9%
2 3622
 
7.2%
0 3407
 
6.8%
6 3301
 
6.6%
5 3282
 
6.6%
3 3073
 
6.1%
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 11340
22.7%
7 6266
12.5%
8 5905
11.8%
9 5342
10.7%
1 4449
 
8.9%
2 3622
 
7.2%
0 3407
 
6.8%
6 3301
 
6.6%
5 3282
 
6.6%
3 3073
 
6.1%
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 11340
22.7%
7 6266
12.5%
8 5905
11.8%
9 5342
10.7%
1 4449
 
8.9%
2 3622
 
7.2%
0 3407
 
6.8%
6 3301
 
6.6%
5 3282
 
6.6%
3 3073
 
6.1%
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 

Distinct8431
Distinct (%)86.7%
Missing271
Missing (%)2.7%
Memory size156.2 KiB
2024-04-18T06:57:54.532803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length63
Mean length31.062596
Min length3

Characters and Unicode

Total characters302208
Distinct characters700
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

Unique7460 ?
Unique (%)76.7%

Sample

1st row부산광역시 사하구 하신중앙로 176 (신평동,6층)
2nd row대구광역시 수성구 동대구로15길 23, 5층 (두산동)
3rd row부산광역시 기장군 정관면 정관로 595, 1동 6층 311~313호 (정관테라스)
4th row부산광역시 사하구 하신중앙로22번길 9 (장림동)
5th row경기도 양주시 남면 개나리길 76
ValueCountFrequency (%)
부산광역시 5131
 
8.5%
경기도 1350
 
2.2%
2층 1304
 
2.2%
3층 1031
 
1.7%
서울특별시 751
 
1.2%
동래구 589
 
1.0%
4층 571
 
0.9%
남구 569
 
0.9%
부산진구 562
 
0.9%
해운대구 521
 
0.9%
Other values (10936) 47964
79.5%
2024-04-18T06:57:55.002695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52713
 
17.4%
11571
 
3.8%
9933
 
3.3%
1 9340
 
3.1%
9285
 
3.1%
( 8864
 
2.9%
) 8862
 
2.9%
8247
 
2.7%
, 8079
 
2.7%
2 7931
 
2.6%
Other values (690) 167383
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174085
57.6%
Space Separator 52713
 
17.4%
Decimal Number 47077
 
15.6%
Open Punctuation 8867
 
2.9%
Close Punctuation 8865
 
2.9%
Other Punctuation 8170
 
2.7%
Dash Punctuation 1412
 
0.5%
Uppercase Letter 685
 
0.2%
Math Symbol 240
 
0.1%
Lowercase Letter 85
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11571
 
6.6%
9933
 
5.7%
9285
 
5.3%
8247
 
4.7%
7530
 
4.3%
6767
 
3.9%
6489
 
3.7%
6073
 
3.5%
5087
 
2.9%
3666
 
2.1%
Other values (617) 99437
57.1%
Uppercase Letter
ValueCountFrequency (%)
B 205
29.9%
A 56
 
8.2%
S 46
 
6.7%
K 40
 
5.8%
I 37
 
5.4%
C 35
 
5.1%
E 32
 
4.7%
T 25
 
3.6%
P 25
 
3.6%
R 21
 
3.1%
Other values (16) 163
23.8%
Lowercase Letter
ValueCountFrequency (%)
e 21
24.7%
l 8
 
9.4%
r 7
 
8.2%
u 7
 
8.2%
a 5
 
5.9%
i 5
 
5.9%
o 5
 
5.9%
t 5
 
5.9%
c 5
 
5.9%
b 5
 
5.9%
Other values (6) 12
14.1%
Decimal Number
ValueCountFrequency (%)
1 9340
19.8%
2 7931
16.8%
3 5963
12.7%
0 4986
10.6%
4 4487
9.5%
5 3676
 
7.8%
6 3121
 
6.6%
7 2814
 
6.0%
8 2461
 
5.2%
9 2298
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 8079
98.9%
. 41
 
0.5%
? 19
 
0.2%
· 10
 
0.1%
& 8
 
0.1%
@ 5
 
0.1%
/ 4
 
< 0.1%
* 3
 
< 0.1%
1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
6
66.7%
1
 
11.1%
1
 
11.1%
1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 8864
> 99.9%
[ 3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8862
> 99.9%
] 3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 239
99.6%
+ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
52713
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1412
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174085
57.6%
Common 127344
42.1%
Latin 779
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11571
 
6.6%
9933
 
5.7%
9285
 
5.3%
8247
 
4.7%
7530
 
4.3%
6767
 
3.9%
6489
 
3.7%
6073
 
3.5%
5087
 
2.9%
3666
 
2.1%
Other values (617) 99437
57.1%
Latin
ValueCountFrequency (%)
B 205
26.3%
A 56
 
7.2%
S 46
 
5.9%
K 40
 
5.1%
I 37
 
4.7%
C 35
 
4.5%
E 32
 
4.1%
T 25
 
3.2%
P 25
 
3.2%
R 21
 
2.7%
Other values (36) 257
33.0%
Common
ValueCountFrequency (%)
52713
41.4%
1 9340
 
7.3%
( 8864
 
7.0%
) 8862
 
7.0%
, 8079
 
6.3%
2 7931
 
6.2%
3 5963
 
4.7%
0 4986
 
3.9%
4 4487
 
3.5%
5 3676
 
2.9%
Other values (17) 12443
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174085
57.6%
ASCII 128103
42.4%
None 11
 
< 0.1%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52713
41.1%
1 9340
 
7.3%
( 8864
 
6.9%
) 8862
 
6.9%
, 8079
 
6.3%
2 7931
 
6.2%
3 5963
 
4.7%
0 4986
 
3.9%
4 4487
 
3.5%
5 3676
 
2.9%
Other values (57) 13202
 
10.3%
Hangul
ValueCountFrequency (%)
11571
 
6.6%
9933
 
5.7%
9285
 
5.3%
8247
 
4.7%
7530
 
4.3%
6767
 
3.9%
6489
 
3.7%
6073
 
3.5%
5087
 
2.9%
3666
 
2.1%
Other values (617) 99437
57.1%
None
ValueCountFrequency (%)
· 10
90.9%
1
 
9.1%
Number Forms
ValueCountFrequency (%)
6
66.7%
1
 
11.1%
1
 
11.1%
1
 
11.1%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3818
Distinct (%)38.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20116728
Minimum388631.59
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:57:55.130952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum388631.59
5-th percentile19950914
Q120040909
median20180111
Q320191115
95-th percentile20201006
Maximum20201231
Range19812599
Interquartile range (IQR)150206

Descriptive statistics

Standard deviation239715.74
Coefficient of variation (CV)0.011916239
Kurtosis4905.3419
Mean20116728
Median Absolute Deviation (MAD)20918
Skewness-63.323854
Sum2.0114717 × 1011
Variance5.7463635 × 1010
MonotonicityNot monotonic
2024-04-18T06:57:55.275739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030204.0 98
 
1.0%
20030206.0 54
 
0.5%
20030203.0 40
 
0.4%
20030205.0 30
 
0.3%
20200214.0 26
 
0.3%
20200515.0 26
 
0.3%
20190405.0 26
 
0.3%
20190215.0 26
 
0.3%
20190118.0 26
 
0.3%
20200417.0 26
 
0.3%
Other values (3808) 9621
96.2%
ValueCountFrequency (%)
388631.593406 1
< 0.1%
10001126.0 1
< 0.1%
19711022.0 1
< 0.1%
19720503.0 2
< 0.1%
19750416.0 1
< 0.1%
19750503.0 1
< 0.1%
19751001.0 1
< 0.1%
19770203.0 1
< 0.1%
19790830.0 1
< 0.1%
19790919.0 1
< 0.1%
ValueCountFrequency (%)
20201231.0 8
0.1%
20201230.0 10
0.1%
20201229.0 9
0.1%
20201228.0 10
0.1%
20201224.0 4
 
< 0.1%
20201223.0 9
0.1%
20201222.0 9
0.1%
20201221.0 4
 
< 0.1%
20201220.0 1
 
< 0.1%
20201219.0 1
 
< 0.1%

dcbymd
Text

MISSING 

Distinct1501
Distinct (%)51.1%
Missing7063
Missing (%)70.6%
Memory size156.2 KiB
2024-04-18T06:57:55.569098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8
Mean length7.3149472
Min length4

Characters and Unicode

Total characters21484
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

Unique1133 ?
Unique (%)38.6%

Sample

1st row폐업일자
2nd row20140804
3rd row20041025
4th row폐업일자
5th row20040330
ValueCountFrequency (%)
폐업일자 506
 
17.2%
20180302 75
 
2.6%
20040504 43
 
1.5%
20151231 40
 
1.4%
20140411 37
 
1.3%
20070801 31
 
1.1%
20030613 23
 
0.8%
20021212 19
 
0.6%
20061215 16
 
0.5%
20121231 15
 
0.5%
Other values (1491) 2132
72.6%
2024-04-18T06:57:55.926628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6392
29.8%
2 4031
18.8%
1 3806
17.7%
3 980
 
4.6%
4 746
 
3.5%
9 734
 
3.4%
7 729
 
3.4%
8 716
 
3.3%
5 715
 
3.3%
6 608
 
2.8%
Other values (6) 2027
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19457
90.6%
Other Letter 2024
 
9.4%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6392
32.9%
2 4031
20.7%
1 3806
19.6%
3 980
 
5.0%
4 746
 
3.8%
9 734
 
3.8%
7 729
 
3.7%
8 716
 
3.7%
5 715
 
3.7%
6 608
 
3.1%
Other Letter
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19460
90.6%
Hangul 2024
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6392
32.8%
2 4031
20.7%
1 3806
19.6%
3 980
 
5.0%
4 746
 
3.8%
9 734
 
3.8%
7 729
 
3.7%
8 716
 
3.7%
5 715
 
3.7%
6 608
 
3.1%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19460
90.6%
Hangul 2024
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6392
32.8%
2 4031
20.7%
1 3806
19.6%
3 980
 
5.0%
4 746
 
3.8%
9 734
 
3.8%
7 729
 
3.7%
8 716
 
3.7%
5 715
 
3.7%
6 608
 
3.1%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
506
25.0%
506
25.0%
506
25.0%
506
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9481 
휴업시작일자
 
506
20180808
 
2
20091112
 
1
20140115112341
 
1
Other values (9)
 
9

Length

Max length14
Median length4
Mean length4.107
Min length4

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9481
94.8%
휴업시작일자 506
 
5.1%
20180808 2
 
< 0.1%
20091112 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20090701 1
 
< 0.1%
20030108 1
 
< 0.1%
20130122 1
 
< 0.1%
20180701 1
 
< 0.1%
20070801 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

Length

2024-04-18T06:57:56.049626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9481
94.8%
휴업시작일자 506
 
5.1%
20180808 2
 
< 0.1%
20091112 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20090701 1
 
< 0.1%
20030108 1
 
< 0.1%
20130122 1
 
< 0.1%
20180701 1
 
< 0.1%
20070801 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9482 
휴업종료일자
 
506
20190630
 
2
20100530
 
1
20110630
 
1
Other values (8)
 
8

Length

Max length8
Median length4
Mean length4.106
Min length4

Unique

Unique10 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9482
94.8%
휴업종료일자 506
 
5.1%
20190630 2
 
< 0.1%
20100530 1
 
< 0.1%
20110630 1
 
< 0.1%
20031231 1
 
< 0.1%
20130714 1
 
< 0.1%
20181231 1
 
< 0.1%
20421031 1
 
< 0.1%
20190410 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-04-18T06:57:56.168421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9482
94.8%
휴업종료일자 506
 
5.1%
20190630 2
 
< 0.1%
20100530 1
 
< 0.1%
20110630 1
 
< 0.1%
20031231 1
 
< 0.1%
20130714 1
 
< 0.1%
20181231 1
 
< 0.1%
20421031 1
 
< 0.1%
20190410 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9493 
재개업일자
 
506
051-123-1234
 
1

Length

Max length12
Median length4
Mean length4.0514
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9493
94.9%
재개업일자 506
 
5.1%
051-123-1234 1
 
< 0.1%

Length

2024-04-18T06:57:56.328394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:57:56.421154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9493
94.9%
재개업일자 506
 
5.1%
051-123-1234 1
 
< 0.1%

trdstatenm
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
4840 
13
2556 
03
2212 
35
 
298
<NA>
 
60
Other values (5)
 
34

Length

Max length5
Median length2
Mean length3.4651
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row13
2nd row영업/정상
3rd row03
4th row13
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 4840
48.4%
13 2556
25.6%
03 2212
22.1%
35 298
 
3.0%
<NA> 60
 
0.6%
02 12
 
0.1%
폐업 8
 
0.1%
영업상태 8
 
0.1%
1 5
 
0.1%
32 1
 
< 0.1%

Length

2024-04-18T06:57:56.524867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:57:56.628733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 4840
48.4%
13 2556
25.6%
03 2212
22.1%
35 298
 
3.0%
na 60
 
0.6%
02 12
 
0.1%
폐업 8
 
0.1%
영업상태 8
 
0.1%
1 5
 
< 0.1%
32 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
7455 
폐업
2220 
직권말소
 
298
휴업
 
12
영업
 
11
Other values (3)
 
4

Length

Max length4
Median length3
Mean length2.8058
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 7455
74.6%
폐업 2220
 
22.2%
직권말소 298
 
3.0%
휴업 12
 
0.1%
영업 11
 
0.1%
<NA> 2
 
< 0.1%
??? 1
 
< 0.1%
신고취소 1
 
< 0.1%

Length

2024-04-18T06:57:56.745182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:57:56.849101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 7455
74.6%
폐업 2220
 
22.2%
직권말소 298
 
3.0%
휴업 12
 
0.1%
영업 11
 
0.1%
na 2
 
< 0.1%
1
 
< 0.1%
신고취소 1
 
< 0.1%

x
Text

MISSING 

Distinct7421
Distinct (%)76.5%
Missing301
Missing (%)3.0%
Memory size156.2 KiB
2024-04-18T06:57:57.055769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.955253
Min length2

Characters and Unicode

Total characters193546
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

Unique5836 ?
Unique (%)60.2%

Sample

1st row378982.41534000000
2nd row346505.142589
3rd row398148.88781000000
4th row379223.08310900000
5th row197737.191958709
ValueCountFrequency (%)
좌표정보(x 32
 
0.3%
380613.87795500000 9
 
0.1%
385599.32170700000 7
 
0.1%
395308.61045334 7
 
0.1%
390129.64468900000 6
 
0.1%
384635.84456700000 6
 
0.1%
202115.873649386 6
 
0.1%
393357.80475400000 6
 
0.1%
397730.36167600000 6
 
0.1%
389736.93768600000 6
 
0.1%
Other values (7411) 9608
99.1%
2024-04-18T06:57:57.409233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35501
18.3%
0 34828
18.0%
3 16628
8.6%
8 14092
 
7.3%
9 13006
 
6.7%
2 12906
 
6.7%
1 12903
 
6.7%
7 11467
 
5.9%
4 11153
 
5.8%
5 10891
 
5.6%
Other values (11) 20171
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148261
76.6%
Space Separator 35501
 
18.3%
Other Punctuation 9558
 
4.9%
Other Letter 130
 
0.1%
Close Punctuation 32
 
< 0.1%
Uppercase Letter 32
 
< 0.1%
Open Punctuation 32
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34828
23.5%
3 16628
11.2%
8 14092
9.5%
9 13006
 
8.8%
2 12906
 
8.7%
1 12903
 
8.7%
7 11467
 
7.7%
4 11153
 
7.5%
5 10891
 
7.3%
6 10387
 
7.0%
Other Letter
ValueCountFrequency (%)
32
24.6%
32
24.6%
32
24.6%
32
24.6%
1
 
0.8%
1
 
0.8%
Space Separator
ValueCountFrequency (%)
35501
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9558
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193384
99.9%
Hangul 130
 
0.1%
Latin 32
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
35501
18.4%
0 34828
18.0%
3 16628
8.6%
8 14092
 
7.3%
9 13006
 
6.7%
2 12906
 
6.7%
1 12903
 
6.7%
7 11467
 
5.9%
4 11153
 
5.8%
5 10891
 
5.6%
Other values (4) 20009
10.3%
Hangul
ValueCountFrequency (%)
32
24.6%
32
24.6%
32
24.6%
32
24.6%
1
 
0.8%
1
 
0.8%
Latin
ValueCountFrequency (%)
X 32
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193416
99.9%
Hangul 130
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35501
18.4%
0 34828
18.0%
3 16628
8.6%
8 14092
 
7.3%
9 13006
 
6.7%
2 12906
 
6.7%
1 12903
 
6.7%
7 11467
 
5.9%
4 11153
 
5.8%
5 10891
 
5.6%
Other values (5) 20041
10.4%
Hangul
ValueCountFrequency (%)
32
24.6%
32
24.6%
32
24.6%
32
24.6%
1
 
0.8%
1
 
0.8%

y
Text

MISSING 

Distinct7421
Distinct (%)76.5%
Missing301
Missing (%)3.0%
Memory size156.2 KiB
2024-04-18T06:57:57.626039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.955666
Min length6

Characters and Unicode

Total characters193550
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

Unique5837 ?
Unique (%)60.2%

Sample

1st row179343.76951600000
2nd row260939.303626
3rd row204835.03089600000
4th row177887.50772000000
5th row488189.146586042
ValueCountFrequency (%)
좌표정보(y 32
 
0.3%
175596.00351700000 9
 
0.1%
187606.00717200000 7
 
0.1%
186564.639113751 7
 
0.1%
432560.215153888 6
 
0.1%
197260.59223600000 6
 
0.1%
179672.44601600000 6
 
0.1%
187408.08665500000 6
 
0.1%
191368.48905300000 6
 
0.1%
191804.07825600000 6
 
0.1%
Other values (7411) 9608
99.1%
2024-04-18T06:57:57.965225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35384
18.3%
0 34033
17.6%
1 17000
8.8%
4 13790
 
7.1%
8 13477
 
7.0%
9 12820
 
6.6%
7 11687
 
6.0%
2 11613
 
6.0%
3 11599
 
6.0%
5 11151
 
5.8%
Other values (17) 20996
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148294
76.6%
Space Separator 35384
 
18.3%
Other Punctuation 9556
 
4.9%
Other Letter 134
 
0.1%
Dash Punctuation 79
 
< 0.1%
Close Punctuation 39
 
< 0.1%
Uppercase Letter 32
 
< 0.1%
Open Punctuation 32
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34033
22.9%
1 17000
11.5%
4 13790
9.3%
8 13477
 
9.1%
9 12820
 
8.6%
7 11687
 
7.9%
2 11613
 
7.8%
3 11599
 
7.8%
5 11151
 
7.5%
6 11124
 
7.5%
Other Letter
ValueCountFrequency (%)
32
23.9%
32
23.9%
32
23.9%
32
23.9%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 32
82.1%
] 7
 
17.9%
Space Separator
ValueCountFrequency (%)
35384
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193384
99.9%
Hangul 134
 
0.1%
Latin 32
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
35384
18.3%
0 34033
17.6%
1 17000
8.8%
4 13790
 
7.1%
8 13477
 
7.0%
9 12820
 
6.6%
7 11687
 
6.0%
2 11613
 
6.0%
3 11599
 
6.0%
5 11151
 
5.8%
Other values (6) 20830
10.8%
Hangul
ValueCountFrequency (%)
32
23.9%
32
23.9%
32
23.9%
32
23.9%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
Latin
ValueCountFrequency (%)
Y 32
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193416
99.9%
Hangul 134
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35384
18.3%
0 34033
17.6%
1 17000
8.8%
4 13790
 
7.1%
8 13477
 
7.0%
9 12820
 
6.6%
7 11687
 
6.0%
2 11613
 
6.0%
3 11599
 
6.0%
5 11151
 
5.8%
Other values (7) 20862
10.8%
Hangul
ValueCountFrequency (%)
32
23.9%
32
23.9%
32
23.9%
32
23.9%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%

lastmodts
Real number (ℝ)

Distinct8968
Distinct (%)89.7%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0160041 × 1013
Minimum2.0021018 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:57:58.086700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0051206 × 1013
Q12.013122 × 1013
median2.0180803 × 1013
Q32.0191119 × 1013
95-th percentile2.0201012 × 1013
Maximum2.0201231 × 1013
Range1.8021304 × 1011
Interquartile range (IQR)5.9898976 × 1010

Descriptive statistics

Standard deviation4.673904 × 1010
Coefficient of variation (CV)0.0023184001
Kurtosis0.69159219
Mean2.0160041 × 1013
Median Absolute Deviation (MAD)1.9698532 × 1010
Skewness-1.2863568
Sum2.0156009 × 1017
Variance2.1845379 × 1021
MonotonicityNot monotonic
2024-04-18T06:57:58.206965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021018132120 44
 
0.4%
20181102180811 3
 
< 0.1%
20200117173212 3
 
< 0.1%
20200110104259 3
 
< 0.1%
20190118172044 3
 
< 0.1%
20181026201158 3
 
< 0.1%
20190215153923 3
 
< 0.1%
20200703161035 3
 
< 0.1%
20200103104113 3
 
< 0.1%
20190628090643 3
 
< 0.1%
Other values (8958) 9927
99.3%
ValueCountFrequency (%)
20021018132120 44
0.4%
20021226152409 1
 
< 0.1%
20021226155826 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%
ValueCountFrequency (%)
20201231174652 1
< 0.1%
20201231162730 1
< 0.1%
20201231162134 1
< 0.1%
20201231152809 1
< 0.1%
20201231150358 1
< 0.1%
20201231142755 1
< 0.1%
20201231142738 1
< 0.1%
20201231091959 1
< 0.1%
20201230175009 1
< 0.1%
20201230172408 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8050 
태권도
 
715
합기도
 
483
업태구분명
 
350
권투
 
183
Other values (5)
 
219

Length

Max length5
Median length4
Mean length3.8373
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8050
80.5%
태권도 715
 
7.1%
합기도 483
 
4.8%
업태구분명 350
 
3.5%
권투 183
 
1.8%
유도 116
 
1.2%
검도 65
 
0.7%
레슬링 21
 
0.2%
우슈 15
 
0.1%
야구종목 2
 
< 0.1%

Length

2024-04-18T06:57:58.337066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:57:58.435126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8050
80.5%
태권도 715
 
7.1%
합기도 483
 
4.8%
업태구분명 350
 
3.5%
권투 183
 
1.8%
유도 116
 
1.2%
검도 65
 
0.7%
레슬링 21
 
0.2%
우슈 15
 
0.1%
야구종목 2
 
< 0.1%

sitetel
Text

MISSING 

Distinct160
Distinct (%)1.7%
Missing332
Missing (%)3.3%
Memory size156.2 KiB
2024-04-18T06:57:58.705742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.959764
Min length4

Characters and Unicode

Total characters115627
Distinct characters15
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

Unique141 ?
Unique (%)1.5%

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 9451
97.8%
전화번호 42
 
0.4%
031-794-9998 2
 
< 0.1%
055-350-7000 2
 
< 0.1%
053-852-7989 2
 
< 0.1%
031-946-6330 2
 
< 0.1%
02-736-3676 2
 
< 0.1%
054-971-9861 2
 
< 0.1%
02-717-9618 2
 
< 0.1%
0313226490 2
 
< 0.1%
Other values (150) 159
 
1.6%
2024-04-18T06:57:59.108469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28515
24.7%
- 19228
16.6%
3 19124
16.5%
2 19102
16.5%
0 9775
 
8.5%
5 9621
 
8.3%
4 9570
 
8.3%
6 156
 
0.1%
9 133
 
0.1%
7 128
 
0.1%
Other values (5) 275
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96231
83.2%
Dash Punctuation 19228
 
16.6%
Other Letter 168
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28515
29.6%
3 19124
19.9%
2 19102
19.9%
0 9775
 
10.2%
5 9621
 
10.0%
4 9570
 
9.9%
6 156
 
0.2%
9 133
 
0.1%
7 128
 
0.1%
8 107
 
0.1%
Other Letter
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 19228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 115459
99.9%
Hangul 168
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 28515
24.7%
- 19228
16.7%
3 19124
16.6%
2 19102
16.5%
0 9775
 
8.5%
5 9621
 
8.3%
4 9570
 
8.3%
6 156
 
0.1%
9 133
 
0.1%
7 128
 
0.1%
Hangul
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115459
99.9%
Hangul 168
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28515
24.7%
- 19228
16.7%
3 19124
16.6%
2 19102
16.5%
0 9775
 
8.5%
5 9621
 
8.3%
4 9570
 
8.3%
6 156
 
0.1%
9 133
 
0.1%
7 128
 
0.1%
Hangul
ValueCountFrequency (%)
42
25.0%
42
25.0%
42
25.0%
42
25.0%

bdngdngnum
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7975 
1
1274 
건축물동수
 
430
0
 
236
2
 
38
Other values (15)
 
47

Length

Max length5
Median length4
Mean length3.5658
Min length1

Unique

Unique10 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7975
79.8%
1 1274
 
12.7%
건축물동수 430
 
4.3%
0 236
 
2.4%
2 38
 
0.4%
3 12
 
0.1%
4 8
 
0.1%
6 8
 
0.1%
5 7
 
0.1%
39 2
 
< 0.1%
Other values (10) 10
 
0.1%

Length

2024-04-18T06:57:59.244553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7975
79.8%
1 1274
 
12.7%
건축물동수 430
 
4.3%
0 236
 
2.4%
2 38
 
0.4%
3 12
 
0.1%
4 8
 
0.1%
6 8
 
0.1%
5 7
 
0.1%
39 2
 
< 0.1%
Other values (10) 10
 
0.1%

bdngyarea
Text

MISSING 

Distinct3713
Distinct (%)72.3%
Missing4864
Missing (%)48.6%
Memory size156.2 KiB
2024-04-18T06:57:59.586804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.581581
Min length1

Characters and Unicode

Total characters28667
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

Unique3179 ?
Unique (%)61.9%

Sample

1st row5172.17
2nd row건축물연면적
3rd row274.87
4th row744.06
5th row184.97
ValueCountFrequency (%)
건축물연면적 288
 
5.6%
0 233
 
4.5%
1 58
 
1.1%
150 27
 
0.5%
160 22
 
0.4%
120 16
 
0.3%
140 15
 
0.3%
99 10
 
0.2%
165 9
 
0.2%
158 9
 
0.2%
Other values (3703) 4449
86.6%
2024-04-18T06:58:00.047931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3921
13.7%
1 3446
12.0%
2 2558
8.9%
4 2446
8.5%
9 2296
8.0%
3 2231
7.8%
8 2168
7.6%
6 2123
7.4%
5 2051
7.2%
7 2002
7.0%
Other values (7) 3425
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23018
80.3%
Other Punctuation 3921
 
13.7%
Other Letter 1728
 
6.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3446
15.0%
2 2558
11.1%
4 2446
10.6%
9 2296
10.0%
3 2231
9.7%
8 2168
9.4%
6 2123
9.2%
5 2051
8.9%
7 2002
8.7%
0 1697
7.4%
Other Letter
ValueCountFrequency (%)
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3921
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26939
94.0%
Hangul 1728
 
6.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3921
14.6%
1 3446
12.8%
2 2558
9.5%
4 2446
9.1%
9 2296
8.5%
3 2231
8.3%
8 2168
8.0%
6 2123
7.9%
5 2051
7.6%
7 2002
7.4%
Hangul
ValueCountFrequency (%)
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26939
94.0%
Hangul 1728
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3921
14.6%
1 3446
12.8%
2 2558
9.5%
4 2446
9.1%
9 2296
8.5%
3 2231
8.3%
8 2168
8.0%
6 2123
7.9%
5 2051
7.6%
7 2002
7.4%
Hangul
ValueCountFrequency (%)
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%
288
16.7%

puprsenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
사립
9920 
<NA>
 
51
공사립구분명
 
15
공립
 
12
??
 
1

Length

Max length19
Median length2
Mean length2.0179
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 9920
99.2%
<NA> 51
 
0.5%
공사립구분명 15
 
0.1%
공립 12
 
0.1%
?? 1
 
< 0.1%
2021-01-04 21:24:28 1
 
< 0.1%

Length

2024-04-18T06:58:00.178169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:00.269098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 9920
99.2%
na 51
 
0.5%
공사립구분명 15
 
0.1%
공립 12
 
0.1%
1
 
< 0.1%
2021-01-04 1
 
< 0.1%
21:24:28 1
 
< 0.1%

culphyedcobnm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
당구장업
3458 
체육도장업
2565 
체력단련장업
2275 
골프연습장업
1291 
수영장업
 
205
Other values (9)
 
206

Length

Max length7
Median length6
Mean length4.9745
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 3458
34.6%
체육도장업 2565
25.7%
체력단련장업 2275
22.8%
골프연습장업 1291
 
12.9%
수영장업 205
 
2.1%
<NA> 47
 
0.5%
썰매장업 45
 
0.4%
무도학원업 41
 
0.4%
골프장 22
 
0.2%
무도장업 20
 
0.2%
Other values (4) 31
 
0.3%

Length

2024-04-18T06:58:00.408929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당구장업 3458
34.6%
체육도장업 2565
25.7%
체력단련장업 2275
22.8%
골프연습장업 1291
 
12.9%
수영장업 205
 
2.1%
na 47
 
0.5%
썰매장업 45
 
0.4%
무도학원업 41
 
0.4%
골프장 22
 
0.2%
무도장업 20
 
0.2%
Other values (4) 31
 
0.3%

bupnm
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9494 
법인명
 
505
다산베아채컨트리클러(주) 대표 이애자
 
1

Length

Max length20
Median length4
Mean length3.9511
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9494
94.9%
법인명 505
 
5.1%
다산베아채컨트리클러(주) 대표 이애자 1
 
< 0.1%

Length

2024-04-18T06:58:00.537667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:00.637065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9494
94.9%
법인명 505
 
5.0%
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>
7790 
0
1416 
 
457
Y
 
319
1
 
18

Length

Max length4
Median length4
Mean length3.337
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7790
77.9%
0 1416
 
14.2%
457
 
4.6%
Y 319
 
3.2%
1 18
 
0.2%

Length

2024-04-18T06:58:00.725782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:00.808684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7790
77.9%
0 1416
 
14.2%
457
 
4.6%
y 319
 
3.2%
1 18
 
0.2%

drmkcobnm
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9493 
세부업종명
 
505
일반대중
 
1
없음
 
1

Length

Max length5
Median length4
Mean length4.0503
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9493
94.9%
세부업종명 505
 
5.1%
일반대중 1
 
< 0.1%
없음 1
 
< 0.1%

Length

2024-04-18T06:58:00.903201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:01.003229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9493
94.9%
세부업종명 505
 
5.1%
일반대중 1
 
< 0.1%
없음 1
 
< 0.1%

ldercnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7201 
1
1904 
2
 
411
지도자수
 
337
0
 
137
Other values (4)
 
10

Length

Max length4
Median length4
Mean length3.2614
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7201
72.0%
1 1904
 
19.0%
2 411
 
4.1%
지도자수 337
 
3.4%
0 137
 
1.4%
3 6
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-18T06:58:01.125333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:01.232484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7201
72.0%
1 1904
 
19.0%
2 411
 
4.1%
지도자수 337
 
3.4%
0 137
 
1.4%
3 6
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

memcolltotstfnum
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9444 
회원모집총인원
 
506
50
 
6
30
 
6
100
 
5
Other values (19)
 
33

Length

Max length7
Median length4
Mean length4.1431
Min length1

Unique

Unique12 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9444
94.4%
회원모집총인원 506
 
5.1%
50 6
 
0.1%
30 6
 
0.1%
100 5
 
0.1%
60 4
 
< 0.1%
40 4
 
< 0.1%
200 3
 
< 0.1%
0 3
 
< 0.1%
150 3
 
< 0.1%
Other values (14) 16
 
0.2%

Length

2024-04-18T06:58:01.336240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9444
94.4%
회원모집총인원 506
 
5.1%
50 6
 
0.1%
30 6
 
0.1%
100 5
 
< 0.1%
60 4
 
< 0.1%
40 4
 
< 0.1%
150 3
 
< 0.1%
0 3
 
< 0.1%
200 3
 
< 0.1%
Other values (14) 16
 
0.2%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-01-04 21:24:28
4432 
2021-01-04 21:24:29
3063 
2021-01-04 21:24:30
2503 
<NA>
 
2

Length

Max length19
Median length19
Mean length18.997
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-04 21:24:28
2nd row2021-01-04 21:24:29
3rd row2021-01-04 21:24:29
4th row2021-01-04 21:24:28
5th row2021-01-04 21:24:29

Common Values

ValueCountFrequency (%)
2021-01-04 21:24:28 4432
44.3%
2021-01-04 21:24:29 3063
30.6%
2021-01-04 21:24:30 2503
25.0%
<NA> 2
 
< 0.1%

Length

2024-04-18T06:58:01.445696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:58:01.550848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-04 9998
50.0%
21:24:28 4432
22.2%
21:24:29 3063
 
15.3%
21:24:30 2503
 
12.5%
na 2
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
4904873340000CDFH330105200900000610_31_01_PI2018-08-31 23:59:59.0<NA>신평스크린골프604834부산광역시 사하구 신평동 452-23번지 6층48947부산광역시 사하구 하신중앙로 176 (신평동,6층)20090702.0<NA><NA><NA><NA>13영업중378982.41534000000179343.7695160000020110218160552<NA>051-123-123415172.17사립골프연습장업<NA><NA><NA><NA><NA>2021-01-04 21:24:28
959695963460000CDFH330102201900000410_41_01_PI2019-10-06 00:22:43.0체육도장업강한아이 태권도장지번우편번호대구광역시 수성구 두산동 101-19번지42171대구광역시 수성구 동대구로15길 23, 5층 (두산동)20191004.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중346505.142589260939.30362620191004173000태권도051-123-1234건축물동수건축물연면적사립체육도장업법인명세부업종명지도자수회원모집총인원2021-01-04 21:24:29
666466643400000CDFH330108201200000110_32_01_PI2018-08-31 23:59:59.0<NA>스타당구장클럽619963부산광역시 기장군 정관읍 매학리 748-6번지 정관테라스 311~313호48947부산광역시 기장군 정관면 정관로 595, 1동 6층 311~313호 (정관테라스)20120720.020140804<NA><NA><NA>03폐업398148.88781000000204835.0308960000020140805093239<NA>051-123-1234<NA><NA>사립당구장업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
572457233340000CDFH330108200400000910_32_01_PI2018-08-31 23:59:59.0<NA>OK당구클럽604842부산광역시 사하구 장림동 1124-11번지49476부산광역시 사하구 하신중앙로22번길 9 (장림동)20040908.0<NA><NA><NA><NA>13영업중379223.08310900000177887.5077200000020180514102706<NA>051-123-1234<NA>274.87사립당구장업<NA><NA><NA><NA><NA>2021-01-04 21:24:28
749774975590000CDFH330108201900000110_32_01_PI2019-01-11 02:20:45.0당구장업킹 당구장<NA>경기도 양주시 남면 신산리 282-4번지11404경기도 양주시 남면 개나리길 7620190109.0<NA><NA><NA><NA>영업/정상영업중197737.191958709488189.14658604220190109183720<NA>051-123-1234<NA>744.06사립당구장업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
753375335690000CDFH330102201900000110_41_01_PI2019-01-13 02:20:47.0체육도장업글로벌 태권도장<NA>세종특별자치시 보람동 628-7번지 아리랑빌딩30150세종특별자치시 남세종로 458, 아리랑빌딩 7층 703, 704호 (보람동)20190111.0<NA><NA><NA><NA>영업/정상영업중225874.474982199330726.25011740620190111152003태권도051-123-1234<NA><NA>사립체육도장업<NA><NA><NA>1<NA>2021-01-04 21:24:29
643364303390000CDFH330108199800000210_32_01_PI2018-08-31 23:59:59.0<NA>88당구장617833부산광역시 사상구 주례동 74-18번지48947부산광역시 사상구 가야대로366번길 16 (주례동)19980507.020041025<NA><NA><NA>03폐업383396.74964600000185622.6673090000020090219153207<NA>051-123-1234<NA>184.97사립당구장업<NA>0<NA><NA><NA>2021-01-04 21:24:29
10055100543610000CDFH330102201900000710_41_01_PI2019-11-23 00:23:21.0체육도장업블랙벨트태권도장지번우편번호광주광역시 남구 방림동 106-14번지61678광주광역시 남구 천변좌로520번길 10, 3층 (방림동)20191121.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중192734.565419181725.05311920191121142442태권도051-123-1234건축물동수건축물연면적사립체육도장업법인명세부업종명1회원모집총인원2021-01-04 21:24:30
628562813380000CDFH330108201700000110_32_01_PI2018-08-31 23:59:59.0<NA>와우당구클럽<NA>부산광역시 수영구 남천동 11-10번지 5층48307부산광역시 수영구 남천동로9번길 41, 5층 (남천동, 인재빌딩)20170418.0<NA><NA><NA><NA>13영업중392366.21074000000185179.9267440000020170814103920<NA>051-123-1234<NA><NA>사립당구장업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
914291424010000CDFH330111201900000110_33_02_PI2019-07-11 02:21:33.0무도학원업차&케이댄스학원(Cha&K Dance Academy)<NA>경기도 시흥시 정왕동 1728-16번지 정임프라자15036경기도 시흥시 서촌상가2길 15, 정임프라자 4층 402호 (정왕동)20190709.0<NA><NA><NA><NA>영업/정상영업중176311.236451956427203.26120908620190709102329<NA>051-123-1234<NA><NA>사립무도학원업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
682768315070000CDFH330105201800000210_31_01_PI2018-10-24 02:37:17.0골프연습장업CM골프연습장<NA>경상북도 안동시 풍천면 갈전리 1296번지 603호36759경상북도 안동시 풍천면 검무로 10-15, 603호20181022.0<NA><NA><NA><NA><NA>영업중333731.041353004342653.45576816320181022111325<NA>051-123-1234<NA>12365.29사립골프연습장업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
533653343320000CDFH330108201100000510_32_01_PI2018-08-31 23:59:59.0<NA>태평양당구장616093부산광역시 북구 구포동 1241-18번지 지하48947부산광역시 북구 시랑로 171 (구포동,지하)20110602.020130613<NA><NA><NA>03폐업383429.49025800000190696.8484570000020130613170652<NA>051-123-12341<NA>사립당구장업<NA><NA><NA><NA><NA>2021-01-04 21:24:28
341434113370000CDFH330102199800000210_41_01_PI2018-08-31 23:59:59.0<NA>명성체육관611802부산광역시 연제구 거제동 92-4번지48947부산광역시 연제구 중앙대로1235번길 41, 3층 (거제동, 양지빌딩)19980825.0<NA><NA><NA><NA>13영업중389184.21552700000190882.8564650000020111227113005<NA>051-123-1234<NA><NA>사립체육도장업<NA>0<NA><NA><NA>2021-01-04 21:24:28
148014783330000CDFH330106201600000710_42_01_PI2018-08-31 23:59:59.0<NA>맑은샘 휘트니스<NA><NA>48012부산광역시 해운대구 신반송로 149 (반송동)20160524.0<NA><NA><NA><NA>13영업중39678419436020180831150157<NA>051-123-1234<NA><NA>사립체력단련장업<NA><NA><NA><NA><NA>2021-01-04 21:24:28
11242112425690000CDFH330102202000000610_41_01_PI2020-03-29 00:23:21.0체육도장업합기도 천지관 충효체육관<NA>세종특별자치시 고운동 1720번지 에셀프라자30063세종특별자치시 마음로 70, 에셀프라자 607호 (고운동)20200327.0<NA><NA><NA><NA>영업/정상영업중220924.898119405333809.160074620200327170551합기도051-123-1234<NA>9996.7사립체육도장업<NA><NA><NA>1<NA>2021-01-04 21:24:30
10565105653470000CDFH330102202000000110_41_01_PI2020-01-16 00:23:36.0체육도장업닐스벅태권도<NA>대구광역시 달서구 도원동 1436-4번지42833대구광역시 달서구 한실로 89, 3층 (도원동)20200114.0<NA><NA><NA><NA>영업/정상영업중338820.811082257416.78725220200114090207태권도051-123-1234<NA><NA>사립체육도장업<NA><NA><NA>1<NA>2021-01-04 21:24:30
11225112253920000CDFH330102202000000110_41_01_PI2020-03-27 00:23:21.0체육도장업지행 무도 합기도<NA>경기도 동두천시 지행동 719-1번지 개림프라자 702호11350경기도 동두천시 중앙로 110-13, 개림프라자 702호 (지행동)20200325.0<NA><NA><NA><NA>영업/정상영업중204594.477167302487641.90137839920200325105734합기도051-123-1234<NA>6697.13사립체육도장업<NA><NA><NA><NA><NA>2021-01-04 21:24:30
747674763530000CDFH330102201900000110_41_01_PI2019-01-09 02:20:58.0체육도장업경희대 찬 태권도장<NA>인천광역시 남동구 서창동 691-2번지 4층 405~6호21614인천광역시 남동구 서창남순환로215번길 17, 4층 405~6호 (서창동)20190107.0<NA><NA><NA><NA>영업/정상영업중177584.32186028435875.95014166920190107161250태권도051-123-1234<NA>16856.64사립체육도장업<NA><NA><NA><NA><NA>2021-01-04 21:24:29
512751263310000CDFH330108199200000210_32_01_PI2018-08-31 23:59:59.0<NA>경당구장608812부산광역시 남구 대연동 773-6번지48947<NA>19921005.020000715<NA><NA><NA>03폐업<NA><NA>20030129132331<NA>051-123-1234<NA>72.26사립당구장업<NA>0<NA><NA><NA>2021-01-04 21:24:28
10224102244090000CDFH330106201900001410_42_01_PI2019-12-11 00:23:26.0체력단련장업A GYM<NA>경기도 김포시 감정동 554-5번지 김포시산림조합10104경기도 김포시 중봉1로 10, 김포시산림조합 2층 (감정동)20191209.0<NA><NA><NA><NA>영업/정상영업중173373.033147273457823.16815090120191209181613<NA>051-123-1234<NA>1908사립체력단련장업<NA><NA><NA><NA><NA>2021-01-04 21:24:30