Overview

Dataset statistics

Number of variables34
Number of observations7243
Missing cells9859
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory276.0 B

Variable types

Text11
Numeric4
Categorical17
DateTime2

Alerts

updategbn is highly imbalanced (92.1%)Imbalance
opnsvcnm is highly imbalanced (82.5%)Imbalance
clgstdt is highly imbalanced (97.2%)Imbalance
clgenddt is highly imbalanced (97.2%)Imbalance
ropnymd is highly imbalanced (94.6%)Imbalance
trdstatenm is highly imbalanced (53.4%)Imbalance
dtlstatenm is highly imbalanced (57.7%)Imbalance
uptaenm is highly imbalanced (81.7%)Imbalance
bdngdngnum is highly imbalanced (71.7%)Imbalance
puprsenm is highly imbalanced (97.5%)Imbalance
bupnm is highly imbalanced (91.7%)Imbalance
insurjnyncode is highly imbalanced (55.8%)Imbalance
drmkcobnm is highly imbalanced (91.7%)Imbalance
ldercnt is highly imbalanced (69.1%)Imbalance
memcolltotstfnum is highly imbalanced (97.0%)Imbalance
sitepostno has 1765 (24.4%) missing valuesMissing
sitewhladdr has 142 (2.0%) missing valuesMissing
rdnwhladdr has 349 (4.8%) missing valuesMissing
dcbymd has 3911 (54.0%) missing valuesMissing
x has 133 (1.8%) missing valuesMissing
y has 133 (1.8%) missing valuesMissing
sitetel has 77 (1.1%) missing valuesMissing
bdngyarea has 3334 (46.0%) missing valuesMissing
opnsfteamcode is highly skewed (γ1 = -21.73078664)Skewed
rdnpostno is highly skewed (γ1 = 81.77481657)Skewed
apvpermymd is highly skewed (γ1 = -59.00451209)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 21:54:42.889010
Analysis finished2024-04-17 21:54:45.156064
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

UNIQUE 

Distinct7243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
2024-04-18T06:54:45.462851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length3.8867872
Min length1

Characters and Unicode

Total characters28152
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

Unique7243 ?
Unique (%)100.0%

Sample

1st row4
2nd row5
3rd row6
4th row7
5th row8
ValueCountFrequency (%)
4 1
 
< 0.1%
4994 1
 
< 0.1%
4846 1
 
< 0.1%
4845 1
 
< 0.1%
4844 1
 
< 0.1%
4843 1
 
< 0.1%
4842 1
 
< 0.1%
4841 1
 
< 0.1%
4840 1
 
< 0.1%
4839 1
 
< 0.1%
Other values (7234) 7234
99.9%
2024-04-18T06:54:45.936136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3533
12.5%
3 3281
11.7%
2 3259
11.6%
4 3210
11.4%
5 3209
11.4%
6 2967
10.5%
7 2234
7.9%
8 2153
7.6%
0 2150
7.6%
9 2147
7.6%
Other values (9) 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28143
> 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 3533
12.6%
3 3281
11.7%
2 3259
11.6%
4 3210
11.4%
5 3209
11.4%
6 2967
10.5%
7 2234
7.9%
8 2153
7.7%
0 2150
7.6%
9 2147
7.6%
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 28144
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3533
12.6%
3 3281
11.7%
2 3259
11.6%
4 3210
11.4%
5 3209
11.4%
6 2967
10.5%
7 2234
7.9%
8 2153
7.6%
0 2150
7.6%
9 2147
7.6%
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 28152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3533
12.5%
3 3281
11.7%
2 3259
11.6%
4 3210
11.4%
5 3209
11.4%
6 2967
10.5%
7 2234
7.9%
8 2153
7.6%
0 2150
7.6%
9 2147
7.6%
Other values (9) 9
 
< 0.1%

opnsfteamcode
Real number (ℝ)

SKEWED 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326832.1
Minimum614853
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size63.8 KiB
2024-04-18T06:54:46.044064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum614853
5-th percentile3260000
Q13300000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range2785147
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation50178.135
Coefficient of variation (CV)0.015082858
Kurtosis1176.9932
Mean3326832.1
Median Absolute Deviation (MAD)30000
Skewness-21.730787
Sum2.4096245 × 1010
Variance2.5178452 × 109
MonotonicityNot monotonic
2024-04-18T06:54:46.136184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3300000 835
11.5%
3290000 771
10.6%
3330000 704
9.7%
3310000 695
9.6%
3340000 614
8.5%
3350000 589
8.1%
3390000 507
 
7.0%
3320000 482
 
6.7%
3370000 410
 
5.7%
3380000 319
 
4.4%
Other values (7) 1317
18.2%
ValueCountFrequency (%)
614853 1
 
< 0.1%
3250000 205
 
2.8%
3260000 188
 
2.6%
3270000 184
 
2.5%
3280000 237
 
3.3%
3290000 771
10.6%
3300000 835
11.5%
3310000 695
9.6%
3320000 482
6.7%
3330000 704
9.7%
ValueCountFrequency (%)
3400000 277
 
3.8%
3390000 507
7.0%
3380000 319
4.4%
3370000 410
5.7%
3360000 225
 
3.1%
3350000 589
8.1%
3340000 614
8.5%
3330000 704
9.7%
3320000 482
6.7%
3310000 695
9.6%

mgtno
Text

Distinct1781
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
2024-04-18T06:54:46.303729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length20.001105
Min length20

Characters and Unicode

Total characters144868
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

Unique694 ?
Unique (%)9.6%

Sample

1st rowCDFH3301051997000002
2nd rowCDFH3301051999000001
3rd rowCDFH3301052003000001
4th rowCDFH3301052003000002
5th rowCDFH3301052004000001
ValueCountFrequency (%)
cdfh3301062019000002 17
 
0.2%
cdfh3301082017000001 16
 
0.2%
cdfh3301082009000001 16
 
0.2%
cdfh3301082008000001 16
 
0.2%
cdfh3301082009000003 16
 
0.2%
cdfh3301082009000005 16
 
0.2%
cdfh3301082009000006 16
 
0.2%
cdfh3301062004000001 16
 
0.2%
cdfh3301082010000002 16
 
0.2%
cdfh3301082003000002 16
 
0.2%
Other values (1775) 7086
97.8%
2024-04-18T06:54:46.624657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59014
40.7%
3 16518
 
11.4%
1 14362
 
9.9%
2 9519
 
6.6%
C 7242
 
5.0%
D 7242
 
5.0%
F 7242
 
5.0%
H 7242
 
5.0%
9 4474
 
3.1%
8 4456
 
3.1%
Other values (21) 7557
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 115877
80.0%
Uppercase Letter 28968
 
20.0%
Other Letter 15
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 1
 
< 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 59014
50.9%
3 16518
 
14.3%
1 14362
 
12.4%
2 9519
 
8.2%
9 4474
 
3.9%
8 4456
 
3.8%
6 2640
 
2.3%
5 2218
 
1.9%
4 1450
 
1.3%
7 1226
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 7242
25.0%
D 7242
25.0%
F 7242
25.0%
H 7242
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 115885
80.0%
Latin 28968
 
20.0%
Hangul 15
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59014
50.9%
3 16518
 
14.3%
1 14362
 
12.4%
2 9519
 
8.2%
9 4474
 
3.9%
8 4456
 
3.8%
6 2640
 
2.3%
5 2218
 
1.9%
4 1450
 
1.3%
7 1226
 
1.1%
Other values (4) 8
 
< 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 7242
25.0%
D 7242
25.0%
F 7242
25.0%
H 7242
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144853
> 99.9%
Hangul 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59014
40.7%
3 16518
 
11.4%
1 14362
 
9.9%
2 9519
 
6.6%
C 7242
 
5.0%
D 7242
 
5.0%
F 7242
 
5.0%
H 7242
 
5.0%
9 4474
 
3.1%
8 4456
 
3.1%
Other values (8) 7542
 
5.2%
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

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
10_32_01_P
3053 
10_41_01_P
1734 
10_42_01_P
1394 
10_31_01_P
920 
10_35_01_P
 
95
Other values (5)
 
47

Length

Max length10
Median length10
Mean length9.9993097
Min length5

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
10_32_01_P 3053
42.2%
10_41_01_P 1734
23.9%
10_42_01_P 1394
19.2%
10_31_01_P 920
 
12.7%
10_35_01_P 95
 
1.3%
10_37_01_P 34
 
0.5%
10_33_02_P 8
 
0.1%
10_39_01_P 3
 
< 0.1%
47213 1
 
< 0.1%
10_33_01_P 1
 
< 0.1%

Length

2024-04-18T06:54:46.742512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:46.847856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_32_01_p 3053
42.2%
10_41_01_p 1734
23.9%
10_42_01_p 1394
19.2%
10_31_01_p 920
 
12.7%
10_35_01_p 95
 
1.3%
10_37_01_p 34
 
0.5%
10_33_02_p 8
 
0.1%
10_39_01_p 3
 
< 0.1%
47213 1
 
< 0.1%
10_33_01_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
I
7120 
U
 
122
부산광역시 부산진구 중앙대로 923-1, 2층 (양정동)
 
1

Length

Max length31
Median length1
Mean length1.0041419
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 7120
98.3%
U 122
 
1.7%
부산광역시 부산진구 중앙대로 923-1, 2층 (양정동) 1
 
< 0.1%

Length

2024-04-18T06:54:46.988082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:47.094143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7120
98.2%
u 122
 
1.7%
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%
Distinct293
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
Minimum2013-12-05 00:00:00
Maximum2021-04-01 02:40:00
2024-04-18T06:54:47.198935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:54:47.336287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
6663 
체력단련장업
 
199
당구장업
 
131
체육도장업
 
131
골프연습장업
 
89
Other values (5)
 
30

Length

Max length7
Median length4
Mean length4.1012012
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> 6663
92.0%
체력단련장업 199
 
2.7%
당구장업 131
 
1.8%
체육도장업 131
 
1.8%
골프연습장업 89
 
1.2%
수영장업 12
 
0.2%
무도학원업 8
 
0.1%
종합체육시설업 6
 
0.1%
썰매장업 3
 
< 0.1%
무도장업 1
 
< 0.1%

Length

2024-04-18T06:54:47.452131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:47.583540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6663
92.0%
체력단련장업 199
 
2.7%
당구장업 131
 
1.8%
체육도장업 131
 
1.8%
골프연습장업 89
 
1.2%
수영장업 12
 
0.2%
무도학원업 8
 
0.1%
종합체육시설업 6
 
0.1%
썰매장업 3
 
< 0.1%
무도장업 1
 
< 0.1%

bplcnm
Text

Distinct5445
Distinct (%)75.2%
Missing1
Missing (%)< 0.1%
Memory size56.7 KiB
2024-04-18T06:54:47.852689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length6.6561723
Min length1

Characters and Unicode

Total characters48204
Distinct characters753
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

Unique4557 ?
Unique (%)62.9%

Sample

1st row광복실내골프연습장
2nd row마린골프연습장
3rd row포시즌 골프연습장
4th row에스에스 골프연습장
5th row가나다라골프연습장
ValueCountFrequency (%)
당구장 253
 
2.7%
당구클럽 239
 
2.6%
태권도 115
 
1.2%
휘트니스 83
 
0.9%
태권도장 63
 
0.7%
골프 53
 
0.6%
스크린골프 43
 
0.5%
헬스 39
 
0.4%
골프연습장 35
 
0.4%
스크린 34
 
0.4%
Other values (5511) 8390
89.8%
2024-04-18T06:54:48.261726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2976
 
6.2%
2943
 
6.1%
2730
 
5.7%
2171
 
4.5%
2105
 
4.4%
1181
 
2.5%
1180
 
2.4%
1098
 
2.3%
986
 
2.0%
914
 
1.9%
Other values (743) 29920
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42679
88.5%
Space Separator 2105
 
4.4%
Uppercase Letter 1927
 
4.0%
Lowercase Letter 469
 
1.0%
Decimal Number 388
 
0.8%
Close Punctuation 233
 
0.5%
Open Punctuation 232
 
0.5%
Other Punctuation 141
 
0.3%
Dash Punctuation 15
 
< 0.1%
Letter Number 6
 
< 0.1%
Other values (4) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2976
 
7.0%
2943
 
6.9%
2730
 
6.4%
2171
 
5.1%
1181
 
2.8%
1180
 
2.8%
1098
 
2.6%
986
 
2.3%
914
 
2.1%
866
 
2.0%
Other values (660) 25634
60.1%
Uppercase Letter
ValueCountFrequency (%)
M 145
 
7.5%
S 136
 
7.1%
G 133
 
6.9%
P 127
 
6.6%
T 123
 
6.4%
A 118
 
6.1%
K 117
 
6.1%
I 102
 
5.3%
O 102
 
5.3%
J 97
 
5.0%
Other values (16) 727
37.7%
Lowercase Letter
ValueCountFrequency (%)
e 48
 
10.2%
i 47
 
10.0%
o 45
 
9.6%
n 41
 
8.7%
s 33
 
7.0%
l 29
 
6.2%
a 28
 
6.0%
r 23
 
4.9%
t 23
 
4.9%
y 22
 
4.7%
Other values (15) 130
27.7%
Decimal Number
ValueCountFrequency (%)
2 139
35.8%
0 64
16.5%
1 59
15.2%
3 29
 
7.5%
5 28
 
7.2%
7 23
 
5.9%
4 20
 
5.2%
8 14
 
3.6%
9 7
 
1.8%
6 5
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 64
45.4%
& 53
37.6%
, 8
 
5.7%
· 5
 
3.5%
' 4
 
2.8%
# 2
 
1.4%
: 2
 
1.4%
2
 
1.4%
/ 1
 
0.7%
Letter Number
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
1
 
25.0%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
2105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 233
100.0%
Open Punctuation
ValueCountFrequency (%)
( 232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42676
88.5%
Common 3123
 
6.5%
Latin 2402
 
5.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2976
 
7.0%
2943
 
6.9%
2730
 
6.4%
2171
 
5.1%
1181
 
2.8%
1180
 
2.8%
1098
 
2.6%
986
 
2.3%
914
 
2.1%
866
 
2.0%
Other values (657) 25631
60.1%
Latin
ValueCountFrequency (%)
M 145
 
6.0%
S 136
 
5.7%
G 133
 
5.5%
P 127
 
5.3%
T 123
 
5.1%
A 118
 
4.9%
K 117
 
4.9%
I 102
 
4.2%
O 102
 
4.2%
J 97
 
4.0%
Other values (43) 1202
50.0%
Common
ValueCountFrequency (%)
2105
67.4%
) 233
 
7.5%
( 232
 
7.4%
2 139
 
4.5%
0 64
 
2.0%
. 64
 
2.0%
1 59
 
1.9%
& 53
 
1.7%
3 29
 
0.9%
5 28
 
0.9%
Other values (20) 117
 
3.7%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42676
88.5%
ASCII 5507
 
11.4%
None 8
 
< 0.1%
Number Forms 6
 
< 0.1%
CJK 3
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Specials 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2976
 
7.0%
2943
 
6.9%
2730
 
6.4%
2171
 
5.1%
1181
 
2.8%
1180
 
2.8%
1098
 
2.6%
986
 
2.3%
914
 
2.1%
866
 
2.0%
Other values (657) 25631
60.1%
ASCII
ValueCountFrequency (%)
2105
38.2%
) 233
 
4.2%
( 232
 
4.2%
M 145
 
2.6%
2 139
 
2.5%
S 136
 
2.5%
G 133
 
2.4%
P 127
 
2.3%
T 123
 
2.2%
A 118
 
2.1%
Other values (64) 2016
36.6%
None
ValueCountFrequency (%)
· 5
62.5%
2
 
25.0%
1
 
12.5%
Number Forms
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Specials
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct871
Distinct (%)15.9%
Missing1765
Missing (%)24.4%
Memory size56.7 KiB
2024-04-18T06:54:48.521997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters32868
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

Unique234 ?
Unique (%)4.3%

Sample

1st row600092
2nd row600100
3rd row600092
4th row600031
5th row600816
ValueCountFrequency (%)
지번우편번호 73
 
1.3%
608805 66
 
1.2%
616852 53
 
1.0%
604851 52
 
0.9%
609839 49
 
0.9%
619963 43
 
0.8%
608810 42
 
0.8%
607815 41
 
0.7%
619903 39
 
0.7%
619905 39
 
0.7%
Other values (861) 4981
90.9%
2024-04-18T06:54:48.934031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 6628
20.2%
8 5710
17.4%
0 5428
16.5%
1 4835
14.7%
2 2307
 
7.0%
4 1888
 
5.7%
7 1787
 
5.4%
3 1715
 
5.2%
9 1268
 
3.9%
5 862
 
2.6%
Other values (6) 440
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32428
98.7%
Other Letter 438
 
1.3%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 6628
20.4%
8 5710
17.6%
0 5428
16.7%
1 4835
14.9%
2 2307
 
7.1%
4 1888
 
5.8%
7 1787
 
5.5%
3 1715
 
5.3%
9 1268
 
3.9%
5 862
 
2.7%
Other Letter
ValueCountFrequency (%)
146
33.3%
73
16.7%
73
16.7%
73
16.7%
73
16.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32430
98.7%
Hangul 438
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 6628
20.4%
8 5710
17.6%
0 5428
16.7%
1 4835
14.9%
2 2307
 
7.1%
4 1888
 
5.8%
7 1787
 
5.5%
3 1715
 
5.3%
9 1268
 
3.9%
5 862
 
2.7%
Hangul
ValueCountFrequency (%)
146
33.3%
73
16.7%
73
16.7%
73
16.7%
73
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32430
98.7%
Hangul 438
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 6628
20.4%
8 5710
17.6%
0 5428
16.7%
1 4835
14.9%
2 2307
 
7.1%
4 1888
 
5.8%
7 1787
 
5.5%
3 1715
 
5.3%
9 1268
 
3.9%
5 862
 
2.7%
Hangul
ValueCountFrequency (%)
146
33.3%
73
16.7%
73
16.7%
73
16.7%
73
16.7%

sitewhladdr
Text

MISSING 

Distinct6045
Distinct (%)85.1%
Missing142
Missing (%)2.0%
Memory size56.7 KiB
2024-04-18T06:54:49.246733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length51
Mean length25.149134
Min length14

Characters and Unicode

Total characters178584
Distinct characters461
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

Unique5238 ?
Unique (%)73.8%

Sample

1st row부산광역시 중구 대청동2가 34-1번지
2nd row부산광역시 중구 중앙동4가 79-1번지 마린센터 지하107호,110호
3rd row부산광역시 중구 대창동2가 36-5번지
4th row부산광역시 중구 대청동2가 7-1번지 5층
5th row부산광역시 중구 신창동3가 13-1번지
ValueCountFrequency (%)
부산광역시 7101
 
21.6%
동래구 835
 
2.5%
부산진구 770
 
2.3%
해운대구 694
 
2.1%
남구 683
 
2.1%
금정구 586
 
1.8%
사하구 571
 
1.7%
사상구 501
 
1.5%
북구 478
 
1.5%
3층 461
 
1.4%
Other values (6323) 20258
61.5%
2024-04-18T06:54:49.681656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32436
18.2%
8413
 
4.7%
8386
 
4.7%
8342
 
4.7%
1 7555
 
4.2%
7292
 
4.1%
7272
 
4.1%
7172
 
4.0%
7106
 
4.0%
7076
 
4.0%
Other values (451) 77534
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102761
57.5%
Decimal Number 36126
 
20.2%
Space Separator 32436
 
18.2%
Dash Punctuation 6401
 
3.6%
Uppercase Letter 252
 
0.1%
Other Punctuation 243
 
0.1%
Open Punctuation 161
 
0.1%
Close Punctuation 160
 
0.1%
Math Symbol 36
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8413
 
8.2%
8386
 
8.2%
8342
 
8.1%
7292
 
7.1%
7272
 
7.1%
7172
 
7.0%
7106
 
6.9%
7076
 
6.9%
6814
 
6.6%
1815
 
1.8%
Other values (400) 33073
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 70
27.8%
A 28
 
11.1%
S 19
 
7.5%
C 16
 
6.3%
K 14
 
5.6%
I 13
 
5.2%
E 10
 
4.0%
Z 9
 
3.6%
G 8
 
3.2%
N 8
 
3.2%
Other values (12) 57
22.6%
Decimal Number
ValueCountFrequency (%)
1 7555
20.9%
2 5146
14.2%
3 4353
12.0%
4 3637
10.1%
5 3229
8.9%
0 2871
 
7.9%
6 2538
 
7.0%
7 2514
 
7.0%
8 2250
 
6.2%
9 2033
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 197
81.1%
. 24
 
9.9%
/ 7
 
2.9%
@ 7
 
2.9%
& 3
 
1.2%
? 2
 
0.8%
2
 
0.8%
· 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
s 1
 
14.3%
b 1
 
14.3%
k 1
 
14.3%
g 1
 
14.3%
Space Separator
ValueCountFrequency (%)
32436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6401
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%
Math Symbol
ValueCountFrequency (%)
~ 36
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102760
57.5%
Common 75563
42.3%
Latin 260
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8413
 
8.2%
8386
 
8.2%
8342
 
8.1%
7292
 
7.1%
7272
 
7.1%
7172
 
7.0%
7106
 
6.9%
7076
 
6.9%
6814
 
6.6%
1815
 
1.8%
Other values (399) 33072
32.2%
Latin
ValueCountFrequency (%)
B 70
26.9%
A 28
 
10.8%
S 19
 
7.3%
C 16
 
6.2%
K 14
 
5.4%
I 13
 
5.0%
E 10
 
3.8%
Z 9
 
3.5%
G 8
 
3.1%
N 8
 
3.1%
Other values (18) 65
25.0%
Common
ValueCountFrequency (%)
32436
42.9%
1 7555
 
10.0%
- 6401
 
8.5%
2 5146
 
6.8%
3 4353
 
5.8%
4 3637
 
4.8%
5 3229
 
4.3%
0 2871
 
3.8%
6 2538
 
3.4%
7 2514
 
3.3%
Other values (13) 4883
 
6.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102760
57.5%
ASCII 75819
42.5%
None 3
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32436
42.8%
1 7555
 
10.0%
- 6401
 
8.4%
2 5146
 
6.8%
3 4353
 
5.7%
4 3637
 
4.8%
5 3229
 
4.3%
0 2871
 
3.8%
6 2538
 
3.3%
7 2514
 
3.3%
Other values (38) 5139
 
6.8%
Hangul
ValueCountFrequency (%)
8413
 
8.2%
8386
 
8.2%
8342
 
8.1%
7292
 
7.1%
7272
 
7.1%
7172
 
7.0%
7106
 
6.9%
7076
 
6.9%
6814
 
6.6%
1815
 
1.8%
Other values (399) 33072
32.2%
None
ValueCountFrequency (%)
2
66.7%
· 1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

SKEWED 

Distinct1165
Distinct (%)16.1%
Missing9
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean48443.248
Minimum13
Maximum619962
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size63.8 KiB
2024-04-18T06:54:49.804297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile46278
Q147794.25
median48947
Q348947
95-th percentile49005.05
Maximum619962
Range619949
Interquartile range (IQR)1152.75

Descriptive statistics

Standard deviation6807.6406
Coefficient of variation (CV)0.14052816
Kurtosis6870.8435
Mean48443.248
Median Absolute Deviation (MAD)0
Skewness81.774817
Sum3.5043846 × 108
Variance46343971
MonotonicityNot monotonic
2024-04-18T06:54:49.948381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 4065
56.1%
46726 59
 
0.8%
46759 24
 
0.3%
46764 20
 
0.3%
48111 17
 
0.2%
46015 17
 
0.2%
46061 16
 
0.2%
46230 15
 
0.2%
46765 15
 
0.2%
48106 14
 
0.2%
Other values (1155) 2972
41.0%
ValueCountFrequency (%)
13 1
 
< 0.1%
46004 3
 
< 0.1%
46006 1
 
< 0.1%
46007 1
 
< 0.1%
46008 13
0.2%
46011 1
 
< 0.1%
46012 8
0.1%
46013 2
 
< 0.1%
46014 2
 
< 0.1%
46015 17
0.2%
ValueCountFrequency (%)
619962 1
 
< 0.1%
49524 1
 
< 0.1%
49523 1
 
< 0.1%
49521 8
0.1%
49520 1
 
< 0.1%
49519 1
 
< 0.1%
49518 4
0.1%
49516 3
 
< 0.1%
49515 1
 
< 0.1%
49514 2
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct6256
Distinct (%)90.7%
Missing349
Missing (%)4.8%
Memory size56.7 KiB
2024-04-18T06:54:50.260390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length55
Mean length29.315057
Min length3

Characters and Unicode

Total characters202098
Distinct characters529
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

Unique5737 ?
Unique (%)83.2%

Sample

1st row부산광역시 중구 광복중앙로 28-1 (대청동2가)
2nd row부산광역시 중구 충장대로9번길 52, 지1층 (중앙동4가, 마린센터빌딩)
3rd row부산광역시 중구 중앙대로 133 (대창동2가)
4th row부산광역시 중구 대청로 107, 5층 (대청동2가)
5th row부산광역시 중구 광복로35번길 18 (신창동3가)
ValueCountFrequency (%)
부산광역시 6893
 
17.8%
동래구 789
 
2.0%
부산진구 753
 
1.9%
해운대구 686
 
1.8%
남구 652
 
1.7%
사하구 597
 
1.5%
금정구 571
 
1.5%
사상구 475
 
1.2%
북구 463
 
1.2%
3층 461
 
1.2%
Other values (4852) 26400
68.1%
2024-04-18T06:54:50.760452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34615
 
17.1%
8826
 
4.4%
8289
 
4.1%
8248
 
4.1%
7296
 
3.6%
7266
 
3.6%
6997
 
3.5%
6899
 
3.4%
6805
 
3.4%
( 6782
 
3.4%
Other values (519) 100075
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118678
58.7%
Space Separator 34615
 
17.1%
Decimal Number 29663
 
14.7%
Open Punctuation 6784
 
3.4%
Close Punctuation 6782
 
3.4%
Other Punctuation 4448
 
2.2%
Dash Punctuation 819
 
0.4%
Uppercase Letter 245
 
0.1%
Math Symbol 43
 
< 0.1%
Lowercase Letter 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8826
 
7.4%
8289
 
7.0%
8248
 
6.9%
7296
 
6.1%
7266
 
6.1%
6997
 
5.9%
6899
 
5.8%
6805
 
5.7%
3133
 
2.6%
2556
 
2.2%
Other values (458) 52363
44.1%
Uppercase Letter
ValueCountFrequency (%)
B 87
35.5%
A 23
 
9.4%
S 20
 
8.2%
K 18
 
7.3%
C 14
 
5.7%
I 12
 
4.9%
E 8
 
3.3%
P 6
 
2.4%
N 6
 
2.4%
G 6
 
2.4%
Other values (13) 45
18.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
20.0%
s 3
15.0%
b 3
15.0%
k 2
10.0%
a 2
10.0%
l 1
 
5.0%
z 1
 
5.0%
w 1
 
5.0%
i 1
 
5.0%
v 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 5937
20.0%
2 4778
16.1%
3 3739
12.6%
4 2825
9.5%
0 2585
8.7%
5 2442
8.2%
6 2149
 
7.2%
7 1867
 
6.3%
8 1739
 
5.9%
9 1602
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 4408
99.1%
. 18
 
0.4%
@ 6
 
0.1%
/ 4
 
0.1%
· 3
 
0.1%
& 3
 
0.1%
* 2
 
< 0.1%
2
 
< 0.1%
? 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6782
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6780
> 99.9%
] 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
34615
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 819
100.0%
Math Symbol
ValueCountFrequency (%)
~ 43
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118677
58.7%
Common 83154
41.1%
Latin 266
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8826
 
7.4%
8289
 
7.0%
8248
 
6.9%
7296
 
6.1%
7266
 
6.1%
6997
 
5.9%
6899
 
5.8%
6805
 
5.7%
3133
 
2.6%
2556
 
2.2%
Other values (457) 52362
44.1%
Latin
ValueCountFrequency (%)
B 87
32.7%
A 23
 
8.6%
S 20
 
7.5%
K 18
 
6.8%
C 14
 
5.3%
I 12
 
4.5%
E 8
 
3.0%
P 6
 
2.3%
N 6
 
2.3%
G 6
 
2.3%
Other values (25) 66
24.8%
Common
ValueCountFrequency (%)
34615
41.6%
( 6782
 
8.2%
) 6780
 
8.2%
1 5937
 
7.1%
2 4778
 
5.7%
, 4408
 
5.3%
3 3739
 
4.5%
4 2825
 
3.4%
0 2585
 
3.1%
5 2442
 
2.9%
Other values (16) 8263
 
9.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118677
58.7%
ASCII 83414
41.3%
None 5
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34615
41.5%
( 6782
 
8.1%
) 6780
 
8.1%
1 5937
 
7.1%
2 4778
 
5.7%
, 4408
 
5.3%
3 3739
 
4.5%
4 2825
 
3.4%
0 2585
 
3.1%
5 2442
 
2.9%
Other values (48) 8523
 
10.2%
Hangul
ValueCountFrequency (%)
8826
 
7.4%
8289
 
7.0%
8248
 
6.9%
7296
 
6.1%
7266
 
6.1%
6997
 
5.9%
6899
 
5.8%
6805
 
5.7%
3133
 
2.6%
2556
 
2.2%
Other values (457) 52362
44.1%
None
ValueCountFrequency (%)
· 3
60.0%
2
40.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct4255
Distinct (%)58.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20053214
Minimum388631.59
Maximum20210325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size63.8 KiB
2024-04-18T06:54:50.885606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum388631.59
5-th percentile19921102
Q120000413
median20051208
Q320120106
95-th percentile20190503
Maximum20210325
Range19821693
Interquartile range (IQR)119693.25

Descriptive statistics

Standard deviation272260.34
Coefficient of variation (CV)0.013576893
Kurtosis4015.3671
Mean20053214
Median Absolute Deviation (MAD)59621.5
Skewness-59.004512
Sum1.4522538 × 1011
Variance7.4125693 × 1010
MonotonicityNot monotonic
2024-04-18T06:54:51.014672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030204.0 124
 
1.7%
20030206.0 66
 
0.9%
20030203.0 55
 
0.8%
20030205.0 36
 
0.5%
19890731.0 31
 
0.4%
20030123.0 21
 
0.3%
20030124.0 19
 
0.3%
20030210.0 12
 
0.2%
19891116.0 12
 
0.2%
20191213.0 11
 
0.2%
Other values (4245) 6855
94.6%
ValueCountFrequency (%)
388631.593406 1
< 0.1%
10001126.0 1
< 0.1%
19711022.0 1
< 0.1%
19720503.0 2
< 0.1%
19730112.0 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%
ValueCountFrequency (%)
20210325.0 1
< 0.1%
20210324.0 1
< 0.1%
20210323.0 2
< 0.1%
20210322.0 1
< 0.1%
20210319.0 2
< 0.1%
20210316.0 2
< 0.1%
20210312.0 2
< 0.1%
20210311.0 1
< 0.1%
20210310.0 2
< 0.1%
20210309.0 1
< 0.1%

dcbymd
Text

MISSING 

Distinct1867
Distinct (%)56.0%
Missing3911
Missing (%)54.0%
Memory size56.7 KiB
2024-04-18T06:54:51.357919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8
Mean length7.9147659
Min length4

Characters and Unicode

Total characters26372
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

Unique1319 ?
Unique (%)39.6%

Sample

1st row20020727
2nd row20040228
3rd row20130408
4th row20150608
5th row20070605
ValueCountFrequency (%)
20180302 96
 
2.9%
폐업일자 74
 
2.2%
20040504 65
 
2.0%
20140411 54
 
1.6%
20151231 51
 
1.5%
20070801 39
 
1.2%
20030613 28
 
0.8%
20021212 24
 
0.7%
20061215 20
 
0.6%
20180703 19
 
0.6%
Other values (1857) 2862
85.9%
2024-04-18T06:54:51.756941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8573
32.5%
2 5333
20.2%
1 5099
19.3%
3 1299
 
4.9%
4 1033
 
3.9%
9 997
 
3.8%
7 988
 
3.7%
8 966
 
3.7%
5 952
 
3.6%
6 833
 
3.2%
Other values (6) 299
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26073
98.9%
Other Letter 296
 
1.1%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8573
32.9%
2 5333
20.5%
1 5099
19.6%
3 1299
 
5.0%
4 1033
 
4.0%
9 997
 
3.8%
7 988
 
3.8%
8 966
 
3.7%
5 952
 
3.7%
6 833
 
3.2%
Other Letter
ValueCountFrequency (%)
74
25.0%
74
25.0%
74
25.0%
74
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26076
98.9%
Hangul 296
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8573
32.9%
2 5333
20.5%
1 5099
19.6%
3 1299
 
5.0%
4 1033
 
4.0%
9 997
 
3.8%
7 988
 
3.8%
8 966
 
3.7%
5 952
 
3.7%
6 833
 
3.2%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
74
25.0%
74
25.0%
74
25.0%
74
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26076
98.9%
Hangul 296
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8573
32.9%
2 5333
20.5%
1 5099
19.6%
3 1299
 
5.0%
4 1033
 
4.0%
9 997
 
3.8%
7 988
 
3.8%
8 966
 
3.7%
5 952
 
3.7%
6 833
 
3.2%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
74
25.0%
74
25.0%
74
25.0%
74
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7153 
휴업시작일자
 
75
20180808
 
2
20180701
 
1
20090701
 
1
Other values (11)
 
11

Length

Max length14
Median length4
Mean length4.0298219
Min length4

Unique

Unique13 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7153
98.8%
휴업시작일자 75
 
1.0%
20180808 2
 
< 0.1%
20180701 1
 
< 0.1%
20090701 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20070801 1
 
< 0.1%
20030108 1
 
< 0.1%
20171025 1
 
< 0.1%
20130122 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2024-04-18T06:54:51.886764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7153
98.8%
휴업시작일자 75
 
1.0%
20180808 2
 
< 0.1%
20180701 1
 
< 0.1%
20090701 1
 
< 0.1%
20140115112341 1
 
< 0.1%
20070801 1
 
< 0.1%
20030108 1
 
< 0.1%
20171025 1
 
< 0.1%
20130122 1
 
< 0.1%
Other values (6) 6
 
0.1%

clgenddt
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7154 
휴업종료일자
 
75
20190630
 
2
20181231
 
1
20110630
 
1
Other values (10)
 
10

Length

Max length8
Median length4
Mean length4.0284413
Min length4

Unique

Unique12 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7154
98.8%
휴업종료일자 75
 
1.0%
20190630 2
 
< 0.1%
20181231 1
 
< 0.1%
20110630 1
 
< 0.1%
20421031 1
 
< 0.1%
20031231 1
 
< 0.1%
20181025 1
 
< 0.1%
20130714 1
 
< 0.1%
20100123 1
 
< 0.1%
Other values (5) 5
 
0.1%

Length

2024-04-18T06:54:52.008013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7154
98.8%
휴업종료일자 75
 
1.0%
20190630 2
 
< 0.1%
20181231 1
 
< 0.1%
20110630 1
 
< 0.1%
20421031 1
 
< 0.1%
20031231 1
 
< 0.1%
20181025 1
 
< 0.1%
20130714 1
 
< 0.1%
20100123 1
 
< 0.1%
Other values (5) 5
 
0.1%

ropnymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7167 
재개업일자
 
75
051-123-1234
 
1

Length

Max length12
Median length4
Mean length4.0114593
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> 7167
99.0%
재개업일자 75
 
1.0%
051-123-1234 1
 
< 0.1%

Length

2024-04-18T06:54:52.125048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:52.227926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7167
99.0%
재개업일자 75
 
1.0%
051-123-1234 1
 
< 0.1%

trdstatenm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
13
3281 
03
2962 
영업/정상
561 
35
402 
02
 
14
Other values (6)
 
23

Length

Max length8
Median length2
Mean length2.2356758
Min length2

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row03
2nd row13
3rd row03
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 3281
45.3%
03 2962
40.9%
영업/정상 561
 
7.7%
35 402
 
5.6%
02 14
 
0.2%
폐업 11
 
0.2%
<NA> 8
 
0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
제외/삭제/전출 1
 
< 0.1%

Length

2024-04-18T06:54:52.331824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13 3281
45.3%
03 2962
40.9%
영업/정상 561
 
7.7%
35 402
 
5.6%
02 14
 
0.2%
폐업 11
 
0.2%
na 8
 
0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
제외/삭제/전출 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
영업중
3849 
폐업
2973 
직권말소
402 
휴업
 
14
<NA>
 
2
Other values (3)
 
3

Length

Max length4
Median length3
Mean length2.6435179
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 3849
53.1%
폐업 2973
41.0%
직권말소 402
 
5.6%
휴업 14
 
0.2%
<NA> 2
 
< 0.1%
신고취소 1
 
< 0.1%
지정취소 1
 
< 0.1%
전출 1
 
< 0.1%

Length

2024-04-18T06:54:52.442509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:52.563020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 3849
53.1%
폐업 2973
41.0%
직권말소 402
 
5.6%
휴업 14
 
0.2%
na 2
 
< 0.1%
신고취소 1
 
< 0.1%
지정취소 1
 
< 0.1%
전출 1
 
< 0.1%

x
Text

MISSING 

Distinct5091
Distinct (%)71.6%
Missing133
Missing (%)1.8%
Memory size56.7 KiB
2024-04-18T06:54:52.771798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.993812
Min length2

Characters and Unicode

Total characters142156
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

Unique3733 ?
Unique (%)52.5%

Sample

1st row385198.60018500000
2nd row385898.66824500000
3rd row385707.34088600000
4th row385250.02502800000
5th row385004.37293600000
ValueCountFrequency (%)
380613.87795500000 11
 
0.2%
373579.04761500000 9
 
0.1%
390129.64468900000 8
 
0.1%
393357.80475400000 8
 
0.1%
395308.61045334 8
 
0.1%
383255.80791500000 7
 
0.1%
392607.54573000000 7
 
0.1%
385599.32170700000 7
 
0.1%
387962.62914200000 7
 
0.1%
387811.67602200000 7
 
0.1%
Other values (5081) 7031
98.9%
2024-04-18T06:54:53.476470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38397
27.0%
17836
12.5%
3 14010
 
9.9%
8 11235
 
7.9%
9 9853
 
6.9%
7 7830
 
5.5%
1 7529
 
5.3%
2 7300
 
5.1%
4 7231
 
5.1%
5 7078
 
5.0%
Other values (11) 13857
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 117272
82.5%
Space Separator 17836
 
12.5%
Other Punctuation 7032
 
4.9%
Other Letter 10
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38397
32.7%
3 14010
 
11.9%
8 11235
 
9.6%
9 9853
 
8.4%
7 7830
 
6.7%
1 7529
 
6.4%
2 7300
 
6.2%
4 7231
 
6.2%
5 7078
 
6.0%
6 6809
 
5.8%
Other Letter
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%
Space Separator
ValueCountFrequency (%)
17836
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7032
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 142144
> 99.9%
Hangul 10
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38397
27.0%
17836
12.5%
3 14010
 
9.9%
8 11235
 
7.9%
9 9853
 
6.9%
7 7830
 
5.5%
1 7529
 
5.3%
2 7300
 
5.1%
4 7231
 
5.1%
5 7078
 
5.0%
Other values (4) 13845
 
9.7%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%
Latin
ValueCountFrequency (%)
X 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142146
> 99.9%
Hangul 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38397
27.0%
17836
12.5%
3 14010
 
9.9%
8 11235
 
7.9%
9 9853
 
6.9%
7 7830
 
5.5%
1 7529
 
5.3%
2 7300
 
5.1%
4 7231
 
5.1%
5 7078
 
5.0%
Other values (5) 13847
 
9.7%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
2
20.0%
1
10.0%
1
10.0%

y
Text

MISSING 

Distinct5090
Distinct (%)71.6%
Missing133
Missing (%)1.8%
Memory size56.7 KiB
2024-04-18T06:54:53.716069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.994374
Min length6

Characters and Unicode

Total characters142160
Distinct characters25
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

Unique3733 ?
Unique (%)52.5%

Sample

1st row180287.48839500000
2nd row181213.88172000000
3rd row181152.27052700000
4th row180424.29203400000
5th row180162.69448800000
ValueCountFrequency (%)
175596.00351700000 11
 
0.2%
178017.84297300000 9
 
0.1%
197260.59223600000 8
 
0.1%
191804.07825600000 8
 
0.1%
186564.639113751 8
 
0.1%
190262.68201300000 7
 
0.1%
188403.67614400000 7
 
0.1%
187606.00717200000 7
 
0.1%
194331.52968600000 7
 
0.1%
183803.94132300000 7
 
0.1%
Other values (5080) 7031
98.9%
2024-04-18T06:54:54.033944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38202
26.9%
17810
12.5%
1 14319
 
10.1%
8 10980
 
7.7%
9 9818
 
6.9%
7 8297
 
5.8%
6 7339
 
5.2%
4 7250
 
5.1%
5 7103
 
5.0%
. 7032
 
4.9%
Other values (15) 14010
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 117298
82.5%
Space Separator 17810
 
12.5%
Other Punctuation 7032
 
4.9%
Other Letter 14
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38202
32.6%
1 14319
 
12.2%
8 10980
 
9.4%
9 9818
 
8.4%
7 8297
 
7.1%
6 7339
 
6.3%
4 7250
 
6.2%
5 7103
 
6.1%
3 7000
 
6.0%
2 6990
 
6.0%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
Space Separator
ValueCountFrequency (%)
17810
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7032
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 142144
> 99.9%
Hangul 14
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38202
26.9%
17810
12.5%
1 14319
 
10.1%
8 10980
 
7.7%
9 9818
 
6.9%
7 8297
 
5.8%
6 7339
 
5.2%
4 7250
 
5.1%
5 7103
 
5.0%
. 7032
 
4.9%
Other values (4) 13994
 
9.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
Latin
ValueCountFrequency (%)
Y 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142146
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38202
26.9%
17810
12.5%
1 14319
 
10.1%
8 10980
 
7.7%
9 9818
 
6.9%
7 8297
 
5.8%
6 7339
 
5.2%
4 7250
 
5.1%
5 7103
 
5.0%
. 7032
 
4.9%
Other values (5) 13996
 
9.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
1
7.1%

lastmodts
Real number (ℝ)

Distinct7055
Distinct (%)97.4%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.013215 × 1013
Minimum2.0021018 × 1013
Maximum2.021033 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size63.8 KiB
2024-04-18T06:54:54.160107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0031124 × 1013
Q12.0110113 × 1013
median2.0140527 × 1013
Q32.017053 × 1013
95-th percentile2.0191213 × 1013
Maximum2.021033 × 1013
Range1.8931205 × 1011
Interquartile range (IQR)6.0416968 × 1010

Descriptive statistics

Standard deviation4.7623766 × 1010
Coefficient of variation (CV)0.0023655579
Kurtosis-0.52418426
Mean2.013215 × 1013
Median Absolute Deviation (MAD)3.0204977 × 1010
Skewness-0.60084992
Sum1.457769 × 1017
Variance2.2680231 × 1021
MonotonicityNot monotonic
2024-04-18T06:54:54.300764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021018132120 62
 
0.9%
20191018101519 3
 
< 0.1%
20191108144420 3
 
< 0.1%
20191115090310 3
 
< 0.1%
20191115140601 3
 
< 0.1%
20191129084358 3
 
< 0.1%
20191213211336 3
 
< 0.1%
20191213161234 3
 
< 0.1%
20191213170840 3
 
< 0.1%
20181026201158 3
 
< 0.1%
Other values (7045) 7152
98.7%
ValueCountFrequency (%)
20021018132120 62
0.9%
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 (%)
20210330181444 1
< 0.1%
20210330180642 1
< 0.1%
20210330170343 1
< 0.1%
20210329175907 1
< 0.1%
20210329175843 1
< 0.1%
20210329175812 1
< 0.1%
20210329175737 1
< 0.1%
20210329175641 1
< 0.1%
20210329151549 1
< 0.1%
20210329143126 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
6634 
태권도
 
372
업태구분명
 
55
권투
 
52
유도
 
40
Other values (4)
 
90

Length

Max length5
Median length4
Mean length3.9123291
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6634
91.6%
태권도 372
 
5.1%
업태구분명 55
 
0.8%
권투 52
 
0.7%
유도 40
 
0.6%
합기도 38
 
0.5%
검도 37
 
0.5%
레슬링 8
 
0.1%
우슈 7
 
0.1%

Length

2024-04-18T06:54:54.420310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:54.527981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6634
91.6%
태권도 372
 
5.1%
업태구분명 55
 
0.8%
권투 52
 
0.7%
유도 40
 
0.6%
합기도 38
 
0.5%
검도 37
 
0.5%
레슬링 8
 
0.1%
우슈 7
 
0.1%

sitetel
Text

MISSING 

Distinct107
Distinct (%)1.5%
Missing77
Missing (%)1.1%
Memory size56.7 KiB
2024-04-18T06:54:54.781425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.96302
Min length4

Characters and Unicode

Total characters85727
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)1.3%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 7027
98.1%
전화번호 24
 
0.3%
051-905-0444 2
 
< 0.1%
051-731-1469 2
 
< 0.1%
051-582-8779 2
 
< 0.1%
051-925-0909 2
 
< 0.1%
051-723-5896 2
 
< 0.1%
051-747-0336 2
 
< 0.1%
051-911-0202 2
 
< 0.1%
051)515-1369 2
 
< 0.1%
Other values (97) 99
 
1.4%
2024-04-18T06:54:55.155606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21259
24.8%
- 14259
16.6%
3 14144
16.5%
2 14128
16.5%
0 7227
 
8.4%
5 7191
 
8.4%
4 7089
 
8.3%
7 104
 
0.1%
8 83
 
0.1%
9 75
 
0.1%
Other values (7) 168
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71369
83.3%
Dash Punctuation 14259
 
16.6%
Other Letter 96
 
0.1%
Close Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21259
29.8%
3 14144
19.8%
2 14128
19.8%
0 7227
 
10.1%
5 7191
 
10.1%
4 7089
 
9.9%
7 104
 
0.1%
8 83
 
0.1%
9 75
 
0.1%
6 69
 
0.1%
Other Letter
ValueCountFrequency (%)
24
25.0%
24
25.0%
24
25.0%
24
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14259
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85631
99.9%
Hangul 96
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21259
24.8%
- 14259
16.7%
3 14144
16.5%
2 14128
16.5%
0 7227
 
8.4%
5 7191
 
8.4%
4 7089
 
8.3%
7 104
 
0.1%
8 83
 
0.1%
9 75
 
0.1%
Other values (3) 72
 
0.1%
Hangul
ValueCountFrequency (%)
24
25.0%
24
25.0%
24
25.0%
24
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85631
99.9%
Hangul 96
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21259
24.8%
- 14259
16.7%
3 14144
16.5%
2 14128
16.5%
0 7227
 
8.4%
5 7191
 
8.4%
4 7089
 
8.3%
7 104
 
0.1%
8 83
 
0.1%
9 75
 
0.1%
Other values (3) 72
 
0.1%
Hangul
ValueCountFrequency (%)
24
25.0%
24
25.0%
24
25.0%
24
25.0%

bdngdngnum
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
5778 
1
1039 
0
 
309
건축물동수
 
72
2
 
24
Other values (6)
 
21

Length

Max length5
Median length4
Mean length3.433384
Min length1

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> 5778
79.8%
1 1039
 
14.3%
0 309
 
4.3%
건축물동수 72
 
1.0%
2 24
 
0.3%
3 8
 
0.1%
4 6
 
0.1%
5 4
 
0.1%
302 1
 
< 0.1%
12 1
 
< 0.1%

Length

2024-04-18T06:54:55.294669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5778
79.8%
1 1039
 
14.3%
0 309
 
4.3%
건축물동수 72
 
1.0%
2 24
 
0.3%
3 8
 
0.1%
4 6
 
0.1%
5 4
 
0.1%
302 1
 
< 0.1%
12 1
 
< 0.1%

bdngyarea
Text

MISSING 

Distinct2887
Distinct (%)73.9%
Missing3334
Missing (%)46.0%
Memory size56.7 KiB
2024-04-18T06:54:55.593177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.1383986
Min length1

Characters and Unicode

Total characters20086
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

Unique2543 ?
Unique (%)65.1%

Sample

1st row20120.65
2nd row4130.27
3rd row1155.7
4th row5404.88
5th row8245.54
ValueCountFrequency (%)
0 306
 
7.8%
1 85
 
2.2%
건축물연면적 47
 
1.2%
150 36
 
0.9%
160 25
 
0.6%
120 23
 
0.6%
140 16
 
0.4%
99 14
 
0.4%
158 12
 
0.3%
165 11
 
0.3%
Other values (2877) 3334
85.3%
2024-04-18T06:54:56.047747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2948
14.7%
1 2827
14.1%
2 1924
9.6%
9 1664
8.3%
4 1638
8.2%
3 1572
7.8%
8 1530
7.6%
5 1474
7.3%
0 1429
7.1%
6 1415
7.0%
Other values (7) 1665
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16856
83.9%
Other Punctuation 2948
 
14.7%
Other Letter 282
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2827
16.8%
2 1924
11.4%
9 1664
9.9%
4 1638
9.7%
3 1572
9.3%
8 1530
9.1%
5 1474
8.7%
0 1429
8.5%
6 1415
8.4%
7 1383
8.2%
Other Letter
ValueCountFrequency (%)
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2948
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19804
98.6%
Hangul 282
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2948
14.9%
1 2827
14.3%
2 1924
9.7%
9 1664
8.4%
4 1638
8.3%
3 1572
7.9%
8 1530
7.7%
5 1474
7.4%
0 1429
7.2%
6 1415
7.1%
Hangul
ValueCountFrequency (%)
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19804
98.6%
Hangul 282
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2948
14.9%
1 2827
14.3%
2 1924
9.7%
9 1664
8.4%
4 1638
8.3%
3 1572
7.9%
8 1530
7.7%
5 1474
7.4%
0 1429
7.2%
6 1415
7.1%
Hangul
ValueCountFrequency (%)
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%
47
16.7%

puprsenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
사립
7201 
<NA>
 
33
공립
 
6
공사립구분명
 
2
2021-04-01 05:22:03
 
1

Length

Max length19
Median length2
Mean length2.0125639
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 7201
99.4%
<NA> 33
 
0.5%
공립 6
 
0.1%
공사립구분명 2
 
< 0.1%
2021-04-01 05:22:03 1
 
< 0.1%

Length

2024-04-18T06:54:56.175619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:56.272618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 7201
99.4%
na 33
 
0.5%
공립 6
 
0.1%
공사립구분명 2
 
< 0.1%
2021-04-01 1
 
< 0.1%
05:22:03 1
 
< 0.1%

culphyedcobnm
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
당구장업
3053 
체육도장업
1734 
체력단련장업
1393 
골프연습장업
920 
수영장업
 
95
Other values (5)
 
48

Length

Max length7
Median length6
Mean length4.8800221
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 3053
42.2%
체육도장업 1734
23.9%
체력단련장업 1393
19.2%
골프연습장업 920
 
12.7%
수영장업 95
 
1.3%
<NA> 34
 
0.5%
무도학원업 8
 
0.1%
썰매장업 3
 
< 0.1%
문화체육업종명 2
 
< 0.1%
무도장업 1
 
< 0.1%

Length

2024-04-18T06:54:56.375763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:56.482666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 3053
42.2%
체육도장업 1734
23.9%
체력단련장업 1393
19.2%
골프연습장업 920
 
12.7%
수영장업 95
 
1.3%
na 34
 
0.5%
무도학원업 8
 
0.1%
썰매장업 3
 
< 0.1%
문화체육업종명 2
 
< 0.1%
무도장업 1
 
< 0.1%

bupnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7168 
법인명
 
75

Length

Max length4
Median length4
Mean length3.9896452
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7168
99.0%
법인명 75
 
1.0%

Length

2024-04-18T06:54:56.603068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:56.683414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7168
99.0%
법인명 75
 
1.0%

insurjnyncode
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
5189 
0
1858 
Y
 
102
 
73
1
 
21

Length

Max length4
Median length4
Mean length3.1492475
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5189
71.6%
0 1858
 
25.7%
Y 102
 
1.4%
73
 
1.0%
1 21
 
0.3%

Length

2024-04-18T06:54:56.788494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:56.900105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5189
71.6%
0 1858
 
25.7%
y 102
 
1.4%
73
 
1.0%
1 21
 
0.3%

drmkcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7168 
세부업종명
 
75

Length

Max length5
Median length4
Mean length4.0103548
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7168
99.0%
세부업종명 75
 
1.0%

Length

2024-04-18T06:54:57.001777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:57.086545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7168
99.0%
세부업종명 75
 
1.0%

ldercnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
5799 
1
1033 
2
 
182
0
 
178
지도자수
 
44
Other values (4)
 
7

Length

Max length4
Median length4
Mean length3.4201298
Min length1

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> 5799
80.1%
1 1033
 
14.3%
2 182
 
2.5%
0 178
 
2.5%
지도자수 44
 
0.6%
3 4
 
0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-18T06:54:57.175593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:54:57.278612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5799
80.1%
1 1033
 
14.3%
2 182
 
2.5%
0 178
 
2.5%
지도자수 44
 
0.6%
3 4
 
0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%

memcolltotstfnum
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
<NA>
7148 
회원모집총인원
 
75
60
 
3
100
 
2
20
 
2
Other values (11)
 
13

Length

Max length7
Median length4
Mean length4.0260942
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7148
98.7%
회원모집총인원 75
 
1.0%
60 3
 
< 0.1%
100 2
 
< 0.1%
20 2
 
< 0.1%
50 2
 
< 0.1%
30 2
 
< 0.1%
300 1
 
< 0.1%
70 1
 
< 0.1%
400 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2024-04-18T06:54:57.394551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7148
98.7%
회원모집총인원 75
 
1.0%
60 3
 
< 0.1%
100 2
 
< 0.1%
20 2
 
< 0.1%
50 2
 
< 0.1%
30 2
 
< 0.1%
300 1
 
< 0.1%
70 1
 
< 0.1%
400 1
 
< 0.1%
Other values (6) 6
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size56.7 KiB
Minimum2021-04-01 05:22:03
Maximum2021-04-01 05:22:04
2024-04-18T06:54:57.493981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:54:57.583195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
043250000CDFH330105199700000210_31_01_PI2018-08-31 23:59:59.0<NA>광복실내골프연습장600092부산광역시 중구 대청동2가 34-1번지48947부산광역시 중구 광복중앙로 28-1 (대청동2가)19971211.020020727<NA><NA><NA>03폐업385198.60018500000180287.4883950000020040727102048<NA>051-123-1234<NA><NA>사립골프연습장업<NA>0<NA><NA><NA>2021-04-01 05:22:03
153250000CDFH330105199900000110_31_01_PI2018-08-31 23:59:59.0<NA>마린골프연습장<NA>부산광역시 중구 중앙동4가 79-1번지 마린센터 지하107호,110호48936부산광역시 중구 충장대로9번길 52, 지1층 (중앙동4가, 마린센터빌딩)19990513.0<NA><NA><NA><NA>13영업중385898.66824500000181213.8817200000020170124143354<NA>051-123-1234<NA>20120.65사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
263250000CDFH330105200300000110_31_01_PI2018-08-31 23:59:59.0<NA>포시즌 골프연습장600100부산광역시 중구 대창동2가 36-5번지48947부산광역시 중구 중앙대로 133 (대창동2가)20030305.020040228<NA><NA><NA>03폐업385707.34088600000181152.2705270000020040709121811<NA>051-123-1234<NA><NA>사립골프연습장업<NA>0<NA><NA><NA>2021-04-01 05:22:03
373250000CDFH330105200300000210_31_01_PI2018-08-31 23:59:59.0<NA>에스에스 골프연습장<NA>부산광역시 중구 대청동2가 7-1번지 5층48933부산광역시 중구 대청로 107, 5층 (대청동2가)20031124.0<NA><NA><NA><NA>13영업중385250.02502800000180424.2920340000020161205154150<NA>051-123-1234<NA>4130.27사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
483250000CDFH330105200400000110_31_01_PI2018-08-31 23:59:59.0<NA>가나다라골프연습장<NA>부산광역시 중구 신창동3가 13-1번지48946부산광역시 중구 광복로35번길 18 (신창동3가)20040413.0<NA><NA><NA><NA>13영업중385004.37293600000180162.6944880000020180202153954<NA>051-123-1234<NA>1155.7사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
593250000CDFH330105200400000210_31_01_PI2018-08-31 23:59:59.0<NA>테일러메이드 실내골프 연습장600092부산광역시 중구 대청동2가 34-1번지48947부산광역시 중구 광복중앙로 28-1 (대청동2가)20040727.020130408<NA><NA><NA>35직권말소385198.60018500000180287.4883950000020130408094631<NA>051-123-1234<NA><NA>사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
6103250000CDFH330105200400000310_31_01_PI2018-08-31 23:59:59.0<NA>(주)이지알앤에스 실내골프연습장600031부산광역시 중구 광복동1가 7번지48947부산광역시 중구 광복로85번길 5-10 (광복동1가)20040811.020150608<NA><NA><NA>03폐업385448.75499800000179977.3282280000020150608132227<NA>051-123-1234<NA><NA>사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
7113250000CDFH330105200500000110_31_01_PI2018-08-31 23:59:59.0<NA>리드 실내골프연습장600816부산광역시 중구 중앙동4가 76-23번지48947부산광역시 중구 중앙대로 148 (중앙동4가)20050328.020070605<NA><NA><NA>03폐업385805.96072100000181267.3847210000020070605140559<NA>051-123-1234<NA><NA>사립골프연습장업<NA>0<NA><NA><NA>2021-04-01 05:22:03
8123250000CDFH330105201400000210_31_01_PI2018-08-31 23:59:59.0<NA>우리동네스크린골프<NA>부산광역시 중구 동광동2가 1번지48955부산광역시 중구 광복로97번길 26-2, 2층 (동광동2가)20140429.0<NA><NA><NA><NA>13영업중385546.63989500000180191.5029580000020180126153016<NA>051-123-1234<NA>5404.88사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
9133250000CDFH330105201400000310_31_01_PI2018-08-31 23:59:59.0<NA>광복스크린600042부산광역시 중구 남포동2가 25-10번지48954부산광역시 중구 구덕로34번길 4 (남포동2가)20140508.0<NA><NA><NA><NA>13영업중385314.95814000000179888.7646780000020161125110922<NA>051-123-1234<NA>8245.54사립골프연습장업<NA><NA><NA><NA><NA>2021-04-01 05:22:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngdngnumbdngyareapuprsenmculphyedcobnmbupnminsurjnyncodedrmkcobnmldercntmemcolltotstfnumlast_load_dttm
7233137933280000CDFH330102202100000110_41_01_PI2021-03-07 00:23:00.0체육도장업크로스멀티짐(CROSS MULTI GYM)지번우편번호부산광역시 영도구 동삼동 219-61 장원빌라49092부산광역시 영도구 동삼서로 52, 지하1층 (동삼동, 장원빌라)20210305.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중388729.846932294177945.50785130820210305143730유도051-996-6565건축물동수건축물연면적사립체육도장업법인명세부업종명2회원모집총인원2021-04-01 05:22:04
7234137943280000CDFH330102202100000110_41_01_PI2021-03-07 00:23:00.0체육도장업크로스멀티짐(CROSS MULTI GYM)지번우편번호부산광역시 영도구 동삼동 219-61 장원빌라49092부산광역시 영도구 동삼서로 52, 지하1층 (동삼동, 장원빌라)20210305.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중388729.846932294177945.50785130820210305143730유도051-996-6565건축물동수건축물연면적사립체육도장업법인명세부업종명2회원모집총인원2021-04-01 05:22:04
7235137953380000CDFH330106202100000110_42_01_PI2021-03-11 00:23:00.0체력단련장업비기닝하루지번우편번호부산광역시 수영구 남천동 3-4 세진빌딩48304부산광역시 수영구 남천바다로 34, 세진빌딩 5층 (남천동)20210309.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392569.973712727185302.93129763120210309085632업태구분명전화번호건축물동수건축물연면적사립체력단련장업법인명세부업종명1회원모집총인원2021-04-01 05:22:04
7236137963360000CDFH330102202100000210_41_01_PI2021-03-12 00:23:00.0체육도장업기품태권도지번우편번호부산광역시 강서구 신호동 215-1546759부산광역시 강서구 신호산단2로27번길 3, 채움더테라스 상가동 2층 202,203호 (신호동)20210310.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중371179.51398421178017.34667939120210310131708태권도051-973-7002건축물동수건축물연면적사립체육도장업법인명세부업종명지도자수회원모집총인원2021-04-01 05:22:04
7237137973330000CDFH330106202100000610_42_01_PI2021-03-12 00:23:00.0체력단련장업워너짐 반여<NA>부산광역시 해운대구 반여동 1199-11 센텀대림아파트 상가12동 지하1~5호48038부산광역시 해운대구 선수촌로 95, 상가12동 지하1층 1~5호 (반여동, 센텀대림아파트)20210310.0<NA><NA><NA><NA>영업/정상영업중392834.111355574191144.53043606420210310093400<NA>051-531-1516<NA>2404.06사립체력단련장업<NA><NA><NA><NA><NA>2021-04-01 05:22:04
7238137983350000CDFH330106202100000210_42_01_PI2021-03-13 00:23:00.0체력단련장업마이너짐지번우편번호부산광역시 금정구 구서동 1013-546235부산광역시 금정구 금샘로 419, 2층 (구서동)20210311.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중389597.400218161197663.50314821520210311115544업태구분명전화번호건축물동수558.67사립체력단련장업법인명세부업종명1회원모집총인원2021-04-01 05:22:04
7239137993370000CDFH330102202100000110_41_01_PI2021-03-14 00:23:00.0체육도장업GTI태권도지번우편번호부산광역시 연제구 연산동 2027-2447608부산광역시 연제구 황령산로605번길 35, 2층 (연산동)20210312.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중389597.015225215187856.75804528520210312115913태권도전화번호건축물동수건축물연면적사립체육도장업법인명세부업종명1회원모집총인원2021-04-01 05:22:04
7240138003370000CDFH330102202100000110_41_01_PI2021-03-14 00:23:00.0체육도장업GTI태권도지번우편번호부산광역시 연제구 연산동 2027-2447608부산광역시 연제구 황령산로605번길 35, 2층 (연산동)20210312.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중389597.015225215187856.75804528520210312115913태권도전화번호건축물동수건축물연면적사립체육도장업법인명세부업종명1회원모집총인원2021-04-01 05:22:04
7241138013400000CDFH330106202100000410_42_01_PI2021-03-18 00:22:59.0체력단련장업운동J GYM지번우편번호부산광역시 기장군 정관읍 매학리 717-1 스타빌딩 3층 306호46015부산광역시 기장군 정관읍 정관로 579, 스타빌딩 306호20210316.0폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중397914.744296503204614.4023687620210316161825업태구분명전화번호113040.64사립체력단련장업법인명세부업종명1회원모집총인원2021-04-01 05:22:04
7242137783340000CDFH330108202100000210_32_01_PI2021-02-24 00:23:01.0당구장업해오름 당구클럽<NA>부산광역시 사하구 다대동 1552-549506부산광역시 사하구 다대로 694-2, 5층 (다대동)20210222.0<NA><NA><NA><NA>영업/정상영업중379257.467705859173968.57461559120210222090253<NA><NA><NA><NA>사립당구장업<NA><NA><NA><NA><NA>2021-04-01 05:22:04