Overview

Dataset statistics

Number of variables63
Number of observations1474
Missing cells5888
Missing cells (%)6.3%
Duplicate rows3
Duplicate rows (%)0.2%
Total size in memory725.6 KiB
Average record size in memory504.1 B

Variable types

Text15
Categorical47
DateTime1

Alerts

last_load_dttm has constant value ""Constant
Dataset has 3 (0.2%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (85.5%)Imbalance
updategbn is highly imbalanced (90.7%)Imbalance
opnsvcnm is highly imbalanced (82.1%)Imbalance
sitepostno is highly imbalanced (92.3%)Imbalance
uptaenm is highly imbalanced (53.4%)Imbalance
sitetel is highly imbalanced (92.1%)Imbalance
gaspdtsortnm is highly imbalanced (89.2%)Imbalance
gassortnm is highly imbalanced (89.2%)Imbalance
upchnm is highly imbalanced (89.2%)Imbalance
suprulesctn is highly imbalanced (89.2%)Imbalance
spyvolt is highly imbalanced (89.2%)Imbalance
ltchgcn is highly imbalanced (89.2%)Imbalance
exmran is highly imbalanced (89.2%)Imbalance
prdsiz is highly imbalanced (89.2%)Imbalance
baelt is highly imbalanced (89.2%)Imbalance
baeesbplc is highly imbalanced (89.2%)Imbalance
offtelno is highly imbalanced (82.6%)Imbalance
ofear is highly imbalanced (89.2%)Imbalance
bsnsopeningprearrymd is highly imbalanced (89.2%)Imbalance
wrkpgrdsrvsenm is highly imbalanced (91.9%)Imbalance
wrkptelno is highly imbalanced (89.2%)Imbalance
useobj is highly imbalanced (93.0%)Imbalance
usemet is highly imbalanced (93.2%)Imbalance
dsnrspvsnsortnm is highly imbalanced (90.1%)Imbalance
equnm is highly imbalanced (90.1%)Imbalance
equcap is highly imbalanced (90.1%)Imbalance
stanm is highly imbalanced (90.1%)Imbalance
sygrglstcnt is highly imbalanced (93.9%)Imbalance
faciluseyn is highly imbalanced (90.1%)Imbalance
realcapt is highly imbalanced (90.1%)Imbalance
cobgbnnm is highly imbalanced (90.1%)Imbalance
instrstoroomar is highly imbalanced (90.1%)Imbalance
motpowersortnm is highly imbalanced (90.1%)Imbalance
bmonuseqy is highly imbalanced (93.9%)Imbalance
cyprpdtfacil is highly imbalanced (90.1%)Imbalance
capt is highly imbalanced (90.1%)Imbalance
saveequloc is highly imbalanced (90.1%)Imbalance
scoalar is highly imbalanced (90.1%)Imbalance
permcn is highly imbalanced (90.1%)Imbalance
prdsenm is highly imbalanced (90.1%)Imbalance
frequ is highly imbalanced (90.1%)Imbalance
cgpar is highly imbalanced (90.1%)Imbalance
rlservlnennm is highly imbalanced (90.1%)Imbalance
tregascap is highly imbalanced (90.1%)Imbalance
rdnpostno has 23 (1.6%) missing valuesMissing
rdnwhladdr has 309 (21.0%) missing valuesMissing
dcbymd has 979 (66.4%) missing valuesMissing
clgstdt has 1326 (90.0%) missing valuesMissing
clgenddt has 1326 (90.0%) missing valuesMissing
ropnymd has 1383 (93.8%) missing valuesMissing
x has 243 (16.5%) missing valuesMissing
y has 243 (16.5%) missing valuesMissing
last_load_dttm has 15 (1.0%) missing valuesMissing

Reproduction

Analysis started2024-04-16 04:11:16.161022
Analysis finished2024-04-16 04:11:17.573652
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

Distinct1470
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2024-04-16T13:11:17.848320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length3
Mean length3.3229308
Min length1

Characters and Unicode

Total characters4898
Distinct characters45
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

Unique1467 ?
Unique (%)99.5%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
압축산소의 3
 
0.2%
이동식 3
 
0.2%
958 3
 
0.2%
경우 3
 
0.2%
사용처 2
 
0.1%
용호동 2
 
0.1%
사무실주소 2
 
0.1%
분포로 2
 
0.1%
115a동 2
 
0.1%
503호 2
 
0.1%
Other values (1468) 1468
98.4%
2024-04-16T13:11:18.469168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 912
18.6%
2 516
10.5%
3 506
10.3%
7 427
8.7%
0 410
8.4%
4 407
8.3%
5 407
8.3%
8 405
8.3%
6 400
8.2%
9 400
8.2%
Other values (35) 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4790
97.8%
Other Letter 73
 
1.5%
Space Separator 18
 
0.4%
Dash Punctuation 9
 
0.2%
Other Punctuation 4
 
0.1%
Uppercase Letter 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
9.6%
5
 
6.8%
5
 
6.8%
4
 
5.5%
4
 
5.5%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
Other values (19) 33
45.2%
Decimal Number
ValueCountFrequency (%)
1 912
19.0%
2 516
10.8%
3 506
10.6%
7 427
8.9%
0 410
8.6%
4 407
8.5%
5 407
8.5%
8 405
8.5%
6 400
8.4%
9 400
8.4%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
: 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4823
98.5%
Hangul 73
 
1.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
9.6%
5
 
6.8%
5
 
6.8%
4
 
5.5%
4
 
5.5%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
Other values (19) 33
45.2%
Common
ValueCountFrequency (%)
1 912
18.9%
2 516
10.7%
3 506
10.5%
7 427
8.9%
0 410
8.5%
4 407
8.4%
5 407
8.4%
8 405
8.4%
6 400
8.3%
9 400
8.3%
Other values (5) 33
 
0.7%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4825
98.5%
Hangul 73
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 912
18.9%
2 516
10.7%
3 506
10.5%
7 427
8.8%
0 410
8.5%
4 407
8.4%
5 407
8.4%
8 405
8.4%
6 400
8.3%
9 400
8.3%
Other values (6) 35
 
0.7%
Hangul
ValueCountFrequency (%)
7
 
9.6%
5
 
6.8%
5
 
6.8%
4
 
5.5%
4
 
5.5%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
3
 
4.1%
Other values (19) 33
45.2%

opnsfteamcode
Categorical

Distinct18
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
3390000
204 
3340000
154 
3290000
116 
3350000
113 
3400000
102 
Other values (13)
785 

Length

Max length8
Median length7
Mean length6.9871099
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3250000
2nd row3250000
3rd row3250000
4th row3250000
5th row3250000

Common Values

ValueCountFrequency (%)
3390000 204
13.8%
3340000 154
10.4%
3290000 116
 
7.9%
3350000 113
 
7.7%
3400000 102
 
6.9%
3310000 99
 
6.7%
3360000 98
 
6.6%
3320000 90
 
6.1%
3300000 87
 
5.9%
3330000 85
 
5.8%
Other values (8) 326
22.1%

Length

2024-04-16T13:11:18.596318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3390000 204
13.8%
3340000 154
10.4%
3290000 116
 
7.9%
3350000 113
 
7.7%
3400000 102
 
6.9%
3310000 99
 
6.7%
3360000 98
 
6.6%
3320000 90
 
6.1%
3300000 87
 
5.9%
3330000 85
 
5.8%
Other values (8) 326
22.1%

mgtno
Text

Distinct1457
Distinct (%)99.3%
Missing7
Missing (%)0.5%
Memory size11.6 KiB
2024-04-16T13:11:18.782803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length18.978187
Min length3

Characters and Unicode

Total characters27841
Distinct characters13
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

Unique1449 ?
Unique (%)98.8%

Sample

1st row1987325001401500001
2nd row1971325001401200003
3rd row1971325001401200004
4th row1976325001401500001
5th row1976325001401500004
ValueCountFrequency (%)
2019339009112200024 3
 
0.2%
2019334008012200010 3
 
0.2%
2021340010901500002 2
 
0.1%
2020340010902100002 2
 
0.1%
2021334013102200001 2
 
0.1%
2020331011912200001 2
 
0.1%
설비명 2
 
0.1%
2021331011912200001 2
 
0.1%
1995336001301500005 1
 
0.1%
2007336006901500003 1
 
0.1%
Other values (1447) 1447
98.6%
2024-04-16T13:11:19.090854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10968
39.4%
1 4428
15.9%
3 3263
 
11.7%
2 2438
 
8.8%
9 2246
 
8.1%
5 1697
 
6.1%
4 942
 
3.4%
6 718
 
2.6%
8 579
 
2.1%
7 556
 
2.0%
Other values (3) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27835
> 99.9%
Other Letter 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10968
39.4%
1 4428
15.9%
3 3263
 
11.7%
2 2438
 
8.8%
9 2246
 
8.1%
5 1697
 
6.1%
4 942
 
3.4%
6 718
 
2.6%
8 579
 
2.1%
7 556
 
2.0%
Other Letter
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 27835
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10968
39.4%
1 4428
15.9%
3 3263
 
11.7%
2 2438
 
8.8%
9 2246
 
8.1%
5 1697
 
6.1%
4 942
 
3.4%
6 718
 
2.6%
8 579
 
2.1%
7 556
 
2.0%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27835
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10968
39.4%
1 4428
15.9%
3 3263
 
11.7%
2 2438
 
8.8%
9 2246
 
8.1%
5 1697
 
6.1%
4 942
 
3.4%
6 718
 
2.6%
8 579
 
2.1%
7 556
 
2.0%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%

opnsvcid
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
09_28_08_P
1407 
09_28_05_P
 
31
09_28_14_P
 
27
<NA>
 
7
설비용량
 
2

Length

Max length10
Median length10
Mean length9.963365
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_08_P
2nd row09_28_08_P
3rd row09_28_08_P
4th row09_28_08_P
5th row09_28_08_P

Common Values

ValueCountFrequency (%)
09_28_08_P 1407
95.5%
09_28_05_P 31
 
2.1%
09_28_14_P 27
 
1.8%
<NA> 7
 
0.5%
설비용량 2
 
0.1%

Length

2024-04-16T13:11:19.228688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:19.340187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_08_p 1407
95.5%
09_28_05_p 31
 
2.1%
09_28_14_p 27
 
1.8%
na 7
 
0.5%
설비용량 2
 
0.1%

updategbn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
I
1439 
U
 
26
<NA>
 
7
소속국가명
 
2

Length

Max length5
Median length1
Mean length1.0196744
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1439
97.6%
U 26
 
1.8%
<NA> 7
 
0.5%
소속국가명 2
 
0.1%

Length

2024-04-16T13:11:19.466359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:19.561539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1439
97.6%
u 26
 
1.8%
na 7
 
0.5%
소속국가명 2
 
0.1%
Distinct64
Distinct (%)4.4%
Missing3
Missing (%)0.2%
Memory size11.6 KiB
2024-04-16T13:11:19.766961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length20.923182
Min length1

Characters and Unicode

Total characters30778
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)2.8%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0
ValueCountFrequency (%)
2018-08-31 1380
47.0%
23:59:59.0 1380
47.0%
02:40:00.0 24
 
0.8%
00:22:59.0 5
 
0.2%
2021-03-19 4
 
0.1%
2021-03-31 4
 
0.1%
2019-10-06 3
 
0.1%
02:22:39.0 3
 
0.1%
00:23:00.0 3
 
0.1%
2021-03-28 3
 
0.1%
Other values (90) 127
 
4.3%
2024-04-16T13:11:20.121013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4682
15.2%
2 3082
10.0%
- 2930
9.5%
: 2930
9.5%
1 2912
9.5%
3 2857
9.3%
9 2810
9.1%
5 2790
9.1%
8 2775
9.0%
1465
 
4.8%
Other values (4) 1545
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21988
71.4%
Other Punctuation 4395
 
14.3%
Dash Punctuation 2930
 
9.5%
Space Separator 1465
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4682
21.3%
2 3082
14.0%
1 2912
13.2%
3 2857
13.0%
9 2810
12.8%
5 2790
12.7%
8 2775
12.6%
4 48
 
0.2%
6 21
 
0.1%
7 11
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 2930
66.7%
. 1465
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2930
100.0%
Space Separator
ValueCountFrequency (%)
1465
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30778
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4682
15.2%
2 3082
10.0%
- 2930
9.5%
: 2930
9.5%
1 2912
9.5%
3 2857
9.3%
9 2810
9.1%
5 2790
9.1%
8 2775
9.0%
1465
 
4.8%
Other values (4) 1545
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30778
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4682
15.2%
2 3082
10.0%
- 2930
9.5%
: 2930
9.5%
1 2912
9.5%
3 2857
9.3%
9 2810
9.1%
5 2790
9.1%
8 2775
9.0%
1465
 
4.8%
Other values (4) 1545
 
5.0%

opnsvcnm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1389 
고압가스업
 
31
특정고압가스업
 
27
석유판매업
 
25
 
2

Length

Max length7
Median length4
Mean length4.0888738
Min length1

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> 1389
94.2%
고압가스업 31
 
2.1%
특정고압가스업 27
 
1.8%
석유판매업 25
 
1.7%
2
 
0.1%

Length

2024-04-16T13:11:20.245159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:20.338770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1389
94.2%
고압가스업 31
 
2.1%
특정고압가스업 27
 
1.8%
석유판매업 25
 
1.7%
2
 
0.1%

bplcnm
Text

Distinct1169
Distinct (%)79.7%
Missing7
Missing (%)0.5%
Memory size11.6 KiB
2024-04-16T13:11:20.550583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length6.9631902
Min length4

Characters and Unicode

Total characters10215
Distinct characters376
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1004 ?
Unique (%)68.4%

Sample

1st row고려주유소
2nd row영신석유
3rd row남포석유상사
4th row강남주유소
5th row에스씨(주) 제일주유소
ValueCountFrequency (%)
직영 11
 
0.7%
현대석유 10
 
0.6%
유성석유 8
 
0.5%
대동석유 8
 
0.5%
삼성석유 8
 
0.5%
주)os에너지 8
 
0.5%
동남석유 7
 
0.4%
경동석유 7
 
0.4%
제일석유 7
 
0.4%
금성석유 7
 
0.4%
Other values (1230) 1577
95.1%
2024-04-16T13:11:20.908369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1296
 
12.7%
947
 
9.3%
647
 
6.3%
616
 
6.0%
( 361
 
3.5%
) 361
 
3.5%
221
 
2.2%
219
 
2.1%
199
 
1.9%
191
 
1.9%
Other values (366) 5157
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9023
88.3%
Open Punctuation 363
 
3.6%
Close Punctuation 363
 
3.6%
Uppercase Letter 204
 
2.0%
Space Separator 191
 
1.9%
Lowercase Letter 31
 
0.3%
Decimal Number 28
 
0.3%
Other Punctuation 7
 
0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1296
 
14.4%
947
 
10.5%
647
 
7.2%
616
 
6.8%
221
 
2.4%
219
 
2.4%
199
 
2.2%
189
 
2.1%
182
 
2.0%
135
 
1.5%
Other values (326) 4372
48.5%
Uppercase Letter
ValueCountFrequency (%)
S 82
40.2%
K 62
30.4%
C 13
 
6.4%
O 12
 
5.9%
G 8
 
3.9%
I 8
 
3.9%
H 4
 
2.0%
T 3
 
1.5%
P 3
 
1.5%
L 2
 
1.0%
Other values (5) 7
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
s 9
29.0%
k 7
22.6%
e 4
12.9%
f 3
 
9.7%
l 3
 
9.7%
c 2
 
6.5%
o 1
 
3.2%
m 1
 
3.2%
h 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
2 9
32.1%
1 9
32.1%
9 3
 
10.7%
0 2
 
7.1%
3 2
 
7.1%
8 2
 
7.1%
6 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
. 2
28.6%
, 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 361
99.4%
[ 2
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 361
99.4%
] 2
 
0.6%
Space Separator
ValueCountFrequency (%)
191
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9028
88.4%
Common 952
 
9.3%
Latin 235
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1296
 
14.4%
947
 
10.5%
647
 
7.2%
616
 
6.8%
221
 
2.4%
219
 
2.4%
199
 
2.2%
189
 
2.1%
182
 
2.0%
135
 
1.5%
Other values (327) 4377
48.5%
Latin
ValueCountFrequency (%)
S 82
34.9%
K 62
26.4%
C 13
 
5.5%
O 12
 
5.1%
s 9
 
3.8%
G 8
 
3.4%
I 8
 
3.4%
k 7
 
3.0%
e 4
 
1.7%
H 4
 
1.7%
Other values (14) 26
 
11.1%
Common
ValueCountFrequency (%)
( 361
37.9%
) 361
37.9%
191
20.1%
2 9
 
0.9%
1 9
 
0.9%
& 4
 
0.4%
9 3
 
0.3%
0 2
 
0.2%
3 2
 
0.2%
[ 2
 
0.2%
Other values (5) 8
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9023
88.3%
ASCII 1187
 
11.6%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1296
 
14.4%
947
 
10.5%
647
 
7.2%
616
 
6.8%
221
 
2.4%
219
 
2.4%
199
 
2.2%
189
 
2.1%
182
 
2.0%
135
 
1.5%
Other values (326) 4372
48.5%
ASCII
ValueCountFrequency (%)
( 361
30.4%
) 361
30.4%
191
16.1%
S 82
 
6.9%
K 62
 
5.2%
C 13
 
1.1%
O 12
 
1.0%
2 9
 
0.8%
1 9
 
0.8%
s 9
 
0.8%
Other values (29) 78
 
6.6%
None
ValueCountFrequency (%)
5
100.0%

sitepostno
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1451 
지번우편번호
 
21
업종구분명
 
2

Length

Max length6
Median length4
Mean length4.0298507
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> 1451
98.4%
지번우편번호 21
 
1.4%
업종구분명 2
 
0.1%

Length

2024-04-16T13:11:21.035069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:21.133179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1451
98.4%
지번우편번호 21
 
1.4%
업종구분명 2
 
0.1%
Distinct1370
Distinct (%)93.6%
Missing10
Missing (%)0.7%
Memory size11.6 KiB
2024-04-16T13:11:21.390181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length65
Mean length24.058743
Min length7

Characters and Unicode

Total characters35222
Distinct characters224
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

Unique1290 ?
Unique (%)88.1%

Sample

1st row부산광역시 중구 중앙동5가 70번지
2nd row부산광역시 중구 영주동 73-11번지
3rd row부산광역시 중구 대청동4가 31-17번지
4th row부산광역시 중구 중앙동4가 82-8번지
5th row부산광역시 중구 영주동 556-3외10필지번지
ValueCountFrequency (%)
부산광역시 1458
 
23.2%
사상구 197
 
3.1%
사하구 154
 
2.4%
부산진구 118
 
1.9%
금정구 111
 
1.8%
남구 101
 
1.6%
기장군 99
 
1.6%
강서구 98
 
1.6%
북구 93
 
1.5%
동래구 90
 
1.4%
Other values (1735) 3767
59.9%
2024-04-16T13:11:21.820526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6278
17.8%
1695
 
4.8%
1657
 
4.7%
1599
 
4.5%
1 1540
 
4.4%
1495
 
4.2%
1489
 
4.2%
1467
 
4.2%
1460
 
4.1%
1450
 
4.1%
Other values (214) 15092
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19868
56.4%
Decimal Number 7354
 
20.9%
Space Separator 6278
 
17.8%
Dash Punctuation 1443
 
4.1%
Other Punctuation 184
 
0.5%
Close Punctuation 38
 
0.1%
Open Punctuation 38
 
0.1%
Uppercase Letter 19
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1695
 
8.5%
1657
 
8.3%
1599
 
8.0%
1495
 
7.5%
1489
 
7.5%
1467
 
7.4%
1460
 
7.3%
1450
 
7.3%
1410
 
7.1%
388
 
2.0%
Other values (186) 5758
29.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
21.1%
M 2
10.5%
N 2
10.5%
S 2
10.5%
E 2
10.5%
O 1
 
5.3%
K 1
 
5.3%
V 1
 
5.3%
W 1
 
5.3%
I 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 1540
20.9%
2 1014
13.8%
3 796
10.8%
4 756
10.3%
5 685
9.3%
8 534
 
7.3%
7 530
 
7.2%
0 526
 
7.2%
6 500
 
6.8%
9 473
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 183
99.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
6278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1443
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19868
56.4%
Common 15335
43.5%
Latin 19
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1695
 
8.5%
1657
 
8.3%
1599
 
8.0%
1495
 
7.5%
1489
 
7.5%
1467
 
7.4%
1460
 
7.3%
1450
 
7.3%
1410
 
7.1%
388
 
2.0%
Other values (186) 5758
29.0%
Common
ValueCountFrequency (%)
6278
40.9%
1 1540
 
10.0%
- 1443
 
9.4%
2 1014
 
6.6%
3 796
 
5.2%
4 756
 
4.9%
5 685
 
4.5%
8 534
 
3.5%
7 530
 
3.5%
0 526
 
3.4%
Other values (6) 1233
 
8.0%
Latin
ValueCountFrequency (%)
A 4
21.1%
M 2
10.5%
N 2
10.5%
S 2
10.5%
E 2
10.5%
O 1
 
5.3%
K 1
 
5.3%
V 1
 
5.3%
W 1
 
5.3%
I 1
 
5.3%
Other values (2) 2
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19868
56.4%
ASCII 15354
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6278
40.9%
1 1540
 
10.0%
- 1443
 
9.4%
2 1014
 
6.6%
3 796
 
5.2%
4 756
 
4.9%
5 685
 
4.5%
8 534
 
3.5%
7 530
 
3.5%
0 526
 
3.4%
Other values (18) 1252
 
8.2%
Hangul
ValueCountFrequency (%)
1695
 
8.5%
1657
 
8.3%
1599
 
8.0%
1495
 
7.5%
1489
 
7.5%
1467
 
7.4%
1460
 
7.3%
1450
 
7.3%
1410
 
7.1%
388
 
2.0%
Other values (186) 5758
29.0%

rdnpostno
Text

MISSING 

Distinct53
Distinct (%)3.7%
Missing23
Missing (%)1.6%
Memory size11.6 KiB
2024-04-16T13:11:21.988304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0165403
Min length5

Characters and Unicode

Total characters7279
Distinct characters22
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

Unique39 ?
Unique (%)2.7%

Sample

1st row48947
2nd row48947
3rd row48947
4th row48947
5th row48947
ValueCountFrequency (%)
48947 1371
94.5%
도로명우편번호 11
 
0.8%
46754 4
 
0.3%
46753 3
 
0.2%
46028 3
 
0.2%
49426 3
 
0.2%
46996 3
 
0.2%
46058 2
 
0.1%
49522 2
 
0.1%
원동력종류명 2
 
0.1%
Other values (43) 47
 
3.2%
2024-04-16T13:11:22.262142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2828
38.9%
8 1403
19.3%
9 1403
19.3%
7 1403
19.3%
6 51
 
0.7%
2 29
 
0.4%
5 25
 
0.3%
0 18
 
0.2%
3 16
 
0.2%
1 14
 
0.2%
Other values (12) 89
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7190
98.8%
Other Letter 89
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
14.6%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
2
 
2.2%
2
 
2.2%
2
 
2.2%
Other values (2) 4
 
4.5%
Decimal Number
ValueCountFrequency (%)
4 2828
39.3%
8 1403
19.5%
9 1403
19.5%
7 1403
19.5%
6 51
 
0.7%
2 29
 
0.4%
5 25
 
0.3%
0 18
 
0.3%
3 16
 
0.2%
1 14
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 7190
98.8%
Hangul 89
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
14.6%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
2
 
2.2%
2
 
2.2%
2
 
2.2%
Other values (2) 4
 
4.5%
Common
ValueCountFrequency (%)
4 2828
39.3%
8 1403
19.5%
9 1403
19.5%
7 1403
19.5%
6 51
 
0.7%
2 29
 
0.4%
5 25
 
0.3%
0 18
 
0.3%
3 16
 
0.2%
1 14
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7190
98.8%
Hangul 89
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2828
39.3%
8 1403
19.5%
9 1403
19.5%
7 1403
19.5%
6 51
 
0.7%
2 29
 
0.4%
5 25
 
0.3%
0 18
 
0.3%
3 16
 
0.2%
1 14
 
0.2%
Hangul
ValueCountFrequency (%)
13
14.6%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
11
12.4%
2
 
2.2%
2
 
2.2%
2
 
2.2%
Other values (2) 4
 
4.5%

rdnwhladdr
Text

MISSING 

Distinct1106
Distinct (%)94.9%
Missing309
Missing (%)21.0%
Memory size11.6 KiB
2024-04-16T13:11:22.569924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length25.206009
Min length2

Characters and Unicode

Total characters29365
Distinct characters271
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

Unique1056 ?
Unique (%)90.6%

Sample

1st row부산광역시 중구 대청로 153 (중앙동5가)
2nd row부산광역시 중구 중앙대로 120 (중앙동4가)
3rd row부산광역시 중구 중구로 194 (영주동)
4th row부산광역시 중구 보수대로 62 (부평동4가)
5th row부산광역시 중구 보동길 10 (보수동1가)
ValueCountFrequency (%)
부산광역시 1156
 
19.7%
사상구 145
 
2.5%
사하구 106
 
1.8%
부산진구 104
 
1.8%
금정구 98
 
1.7%
기장군 89
 
1.5%
강서구 88
 
1.5%
남구 78
 
1.3%
해운대구 76
 
1.3%
동래구 74
 
1.3%
Other values (1338) 3859
65.7%
2024-04-16T13:11:23.010431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4951
 
16.9%
1375
 
4.7%
1366
 
4.7%
1321
 
4.5%
1211
 
4.1%
1181
 
4.0%
1158
 
3.9%
1143
 
3.9%
1128
 
3.8%
) 1092
 
3.7%
Other values (261) 13439
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17832
60.7%
Space Separator 4951
 
16.9%
Decimal Number 4162
 
14.2%
Close Punctuation 1092
 
3.7%
Open Punctuation 1092
 
3.7%
Dash Punctuation 127
 
0.4%
Other Punctuation 100
 
0.3%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1375
 
7.7%
1366
 
7.7%
1321
 
7.4%
1211
 
6.8%
1181
 
6.6%
1158
 
6.5%
1143
 
6.4%
1128
 
6.3%
557
 
3.1%
326
 
1.8%
Other values (239) 7066
39.6%
Decimal Number
ValueCountFrequency (%)
1 863
20.7%
2 582
14.0%
3 470
11.3%
4 363
8.7%
5 355
8.5%
7 338
 
8.1%
0 319
 
7.7%
6 319
 
7.7%
8 283
 
6.8%
9 270
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
N 2
22.2%
A 2
22.2%
M 2
22.2%
O 1
11.1%
S 1
11.1%
E 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 99
99.0%
/ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
4951
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1092
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17832
60.7%
Common 11524
39.2%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1375
 
7.7%
1366
 
7.7%
1321
 
7.4%
1211
 
6.8%
1181
 
6.6%
1158
 
6.5%
1143
 
6.4%
1128
 
6.3%
557
 
3.1%
326
 
1.8%
Other values (239) 7066
39.6%
Common
ValueCountFrequency (%)
4951
43.0%
) 1092
 
9.5%
( 1092
 
9.5%
1 863
 
7.5%
2 582
 
5.1%
3 470
 
4.1%
4 363
 
3.1%
5 355
 
3.1%
7 338
 
2.9%
0 319
 
2.8%
Other values (6) 1099
 
9.5%
Latin
ValueCountFrequency (%)
N 2
22.2%
A 2
22.2%
M 2
22.2%
O 1
11.1%
S 1
11.1%
E 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17832
60.7%
ASCII 11533
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4951
42.9%
) 1092
 
9.5%
( 1092
 
9.5%
1 863
 
7.5%
2 582
 
5.0%
3 470
 
4.1%
4 363
 
3.1%
5 355
 
3.1%
7 338
 
2.9%
0 319
 
2.8%
Other values (12) 1108
 
9.6%
Hangul
ValueCountFrequency (%)
1375
 
7.7%
1366
 
7.7%
1321
 
7.4%
1211
 
6.8%
1181
 
6.6%
1158
 
6.5%
1143
 
6.4%
1128
 
6.3%
557
 
3.1%
326
 
1.8%
Other values (239) 7066
39.6%
Distinct1163
Distinct (%)79.3%
Missing7
Missing (%)0.5%
Memory size11.6 KiB
2024-04-16T13:11:23.243245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9986367
Min length7

Characters and Unicode

Total characters11734
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

Unique994 ?
Unique (%)67.8%

Sample

1st row19870812
2nd row19710722
3rd row19710924
4th row19760503
5th row19760513
ValueCountFrequency (%)
19760513 44
 
3.0%
19940708 19
 
1.3%
19931207 18
 
1.2%
19950915 10
 
0.7%
19931130 7
 
0.5%
20031106 7
 
0.5%
20031104 6
 
0.4%
19941130 5
 
0.3%
19931209 4
 
0.3%
19911218 4
 
0.3%
Other values (1153) 1343
91.5%
2024-04-16T13:11:23.570940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2815
24.0%
1 2496
21.3%
9 1984
16.9%
2 1583
13.5%
3 585
 
5.0%
8 530
 
4.5%
7 458
 
3.9%
4 451
 
3.8%
6 431
 
3.7%
5 387
 
3.3%
Other values (7) 14
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11720
99.9%
Other Letter 14
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2815
24.0%
1 2496
21.3%
9 1984
16.9%
2 1583
13.5%
3 585
 
5.0%
8 530
 
4.5%
7 458
 
3.9%
4 451
 
3.8%
6 431
 
3.7%
5 387
 
3.3%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 11720
99.9%
Hangul 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2815
24.0%
1 2496
21.3%
9 1984
16.9%
2 1583
13.5%
3 585
 
5.0%
8 530
 
4.5%
7 458
 
3.9%
4 451
 
3.8%
6 431
 
3.7%
5 387
 
3.3%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11720
99.9%
Hangul 14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2815
24.0%
1 2496
21.3%
9 1984
16.9%
2 1583
13.5%
3 585
 
5.0%
8 530
 
4.5%
7 458
 
3.9%
4 451
 
3.8%
6 431
 
3.7%
5 387
 
3.3%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

dcbymd
Text

MISSING 

Distinct395
Distinct (%)79.8%
Missing979
Missing (%)66.4%
Memory size11.6 KiB
2024-04-16T13:11:23.848731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.810101
Min length3

Characters and Unicode

Total characters3866
Distinct characters16
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

Unique348 ?
Unique (%)70.3%

Sample

1st row20080506
2nd row20160616
3rd row20151126
4th row20101230
5th row20081107
ValueCountFrequency (%)
폐업일자 21
 
4.2%
20111114 11
 
2.2%
20111031 10
 
2.0%
20120510 10
 
2.0%
20120511 8
 
1.6%
20051125 3
 
0.6%
20120508 3
 
0.6%
20120308 3
 
0.6%
20170116 2
 
0.4%
20081009 2
 
0.4%
Other values (385) 422
85.3%
2024-04-16T13:11:24.239281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1244
32.2%
2 798
20.6%
1 790
20.4%
3 177
 
4.6%
8 148
 
3.8%
5 139
 
3.6%
4 136
 
3.5%
9 118
 
3.1%
7 116
 
3.0%
6 110
 
2.8%
Other values (6) 90
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3776
97.7%
Other Letter 90
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1244
32.9%
2 798
21.1%
1 790
20.9%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 136
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Other Letter
ValueCountFrequency (%)
23
25.6%
21
23.3%
21
23.3%
21
23.3%
2
 
2.2%
2
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3776
97.7%
Hangul 90
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1244
32.9%
2 798
21.1%
1 790
20.9%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 136
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Hangul
ValueCountFrequency (%)
23
25.6%
21
23.3%
21
23.3%
21
23.3%
2
 
2.2%
2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3776
97.7%
Hangul 90
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1244
32.9%
2 798
21.1%
1 790
20.9%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 136
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Hangul
ValueCountFrequency (%)
23
25.6%
21
23.3%
21
23.3%
21
23.3%
2
 
2.2%
2
 
2.2%

clgstdt
Text

MISSING 

Distinct124
Distinct (%)83.8%
Missing1326
Missing (%)90.0%
Memory size11.6 KiB
2024-04-16T13:11:24.489361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.7027027
Min length6

Characters and Unicode

Total characters1140
Distinct characters22
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

Unique118 ?
Unique (%)79.7%

Sample

1st row20120501
2nd row휴업시작일자
3rd row20121101
4th row20141121
5th row20141120
ValueCountFrequency (%)
휴업시작일자 20
 
13.5%
20100301 2
 
1.4%
20110101 2
 
1.4%
20130301 2
 
1.4%
저장설비위치 2
 
1.4%
20140701 2
 
1.4%
20100513 1
 
0.7%
20140221 1
 
0.7%
20110517 1
 
0.7%
20141230 1
 
0.7%
Other values (114) 114
77.0%
2024-04-16T13:11:24.846435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 325
28.5%
1 256
22.5%
2 211
18.5%
3 46
 
4.0%
7 38
 
3.3%
4 34
 
3.0%
9 28
 
2.5%
5 28
 
2.5%
6 24
 
2.1%
20
 
1.8%
Other values (12) 130
 
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1008
88.4%
Other Letter 132
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Other values (2) 4
 
3.0%
Decimal Number
ValueCountFrequency (%)
0 325
32.2%
1 256
25.4%
2 211
20.9%
3 46
 
4.6%
7 38
 
3.8%
4 34
 
3.4%
9 28
 
2.8%
5 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1008
88.4%
Hangul 132
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Other values (2) 4
 
3.0%
Common
ValueCountFrequency (%)
0 325
32.2%
1 256
25.4%
2 211
20.9%
3 46
 
4.6%
7 38
 
3.8%
4 34
 
3.4%
9 28
 
2.8%
5 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1008
88.4%
Hangul 132
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 325
32.2%
1 256
25.4%
2 211
20.9%
3 46
 
4.6%
7 38
 
3.8%
4 34
 
3.4%
9 28
 
2.8%
5 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%
Hangul
ValueCountFrequency (%)
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
20
15.2%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Other values (2) 4
 
3.0%

clgenddt
Text

MISSING 

Distinct112
Distinct (%)75.7%
Missing1326
Missing (%)90.0%
Memory size11.6 KiB
2024-04-16T13:11:25.090839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6891892
Min length5

Characters and Unicode

Total characters1138
Distinct characters21
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

Unique96 ?
Unique (%)64.9%

Sample

1st row20121231
2nd row휴업종료일자
3rd row20121130
4th row20150228
5th row20150920
ValueCountFrequency (%)
휴업종료일자 20
 
13.5%
20120430 3
 
2.0%
20131231 3
 
2.0%
저탄장면적 2
 
1.4%
20150630 2
 
1.4%
20100831 2
 
1.4%
20151231 2
 
1.4%
20140930 2
 
1.4%
20170630 2
 
1.4%
20160630 2
 
1.4%
Other values (102) 108
73.0%
2024-04-16T13:11:25.446087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 304
26.7%
1 242
21.3%
2 199
17.5%
3 98
 
8.6%
5 37
 
3.3%
8 31
 
2.7%
4 28
 
2.5%
6 26
 
2.3%
9 23
 
2.0%
20
 
1.8%
Other values (11) 130
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1008
88.6%
Other Letter 130
 
11.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Decimal Number
ValueCountFrequency (%)
0 304
30.2%
1 242
24.0%
2 199
19.7%
3 98
 
9.7%
5 37
 
3.7%
8 31
 
3.1%
4 28
 
2.8%
6 26
 
2.6%
9 23
 
2.3%
7 20
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1008
88.6%
Hangul 130
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Common
ValueCountFrequency (%)
0 304
30.2%
1 242
24.0%
2 199
19.7%
3 98
 
9.7%
5 37
 
3.7%
8 31
 
3.1%
4 28
 
2.8%
6 26
 
2.6%
9 23
 
2.3%
7 20
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1008
88.6%
Hangul 130
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 304
30.2%
1 242
24.0%
2 199
19.7%
3 98
 
9.7%
5 37
 
3.7%
8 31
 
3.1%
4 28
 
2.8%
6 26
 
2.6%
9 23
 
2.3%
7 20
 
2.0%
Hangul
ValueCountFrequency (%)
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
20
15.4%
2
 
1.5%
2
 
1.5%
2
 
1.5%
2
 
1.5%

ropnymd
Text

MISSING 

Distinct69
Distinct (%)75.8%
Missing1383
Missing (%)93.8%
Memory size11.6 KiB
2024-04-16T13:11:25.653498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.3076923
Min length5

Characters and Unicode

Total characters665
Distinct characters22
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

Unique66 ?
Unique (%)72.5%

Sample

1st row20130204
2nd row재개업일자
3rd row20121227
4th row20120806
5th row20140925
ValueCountFrequency (%)
재개업일자 21
 
23.1%
전기사업허가조건 2
 
2.2%
20131101 2
 
2.2%
20151230 1
 
1.1%
20081001 1
 
1.1%
20170915 1
 
1.1%
20120806 1
 
1.1%
20110722 1
 
1.1%
20150213 1
 
1.1%
20151102 1
 
1.1%
Other values (59) 59
64.8%
2024-04-16T13:11:26.006307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
23.9%
1 144
21.7%
2 115
17.3%
3 27
 
4.1%
23
 
3.5%
21
 
3.2%
7 21
 
3.2%
21
 
3.2%
21
 
3.2%
21
 
3.2%
Other values (12) 92
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 544
81.8%
Other Letter 121
 
18.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
19.0%
21
17.4%
21
17.4%
21
17.4%
21
17.4%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (2) 4
 
3.3%
Decimal Number
ValueCountFrequency (%)
0 159
29.2%
1 144
26.5%
2 115
21.1%
3 27
 
5.0%
7 21
 
3.9%
6 21
 
3.9%
5 20
 
3.7%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 544
81.8%
Hangul 121
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
19.0%
21
17.4%
21
17.4%
21
17.4%
21
17.4%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (2) 4
 
3.3%
Common
ValueCountFrequency (%)
0 159
29.2%
1 144
26.5%
2 115
21.1%
3 27
 
5.0%
7 21
 
3.9%
6 21
 
3.9%
5 20
 
3.7%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 544
81.8%
Hangul 121
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
29.2%
1 144
26.5%
2 115
21.1%
3 27
 
5.0%
7 21
 
3.9%
6 21
 
3.9%
5 20
 
3.7%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%
Hangul
ValueCountFrequency (%)
23
19.0%
21
17.4%
21
17.4%
21
17.4%
21
17.4%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (2) 4
 
3.3%

trdstatenm
Categorical

Distinct11
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
03
728 
01
382 
07
196 
영업/정상
73 
06
 
48
Other values (6)
 
47

Length

Max length5
Median length2
Mean length2.1621438
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01
2nd row03
3rd row03
4th row03
5th row01

Common Values

ValueCountFrequency (%)
03 728
49.4%
01 382
25.9%
07 196
 
13.3%
영업/정상 73
 
5.0%
06 48
 
3.3%
02 17
 
1.2%
05 11
 
0.7%
<NA> 7
 
0.5%
휴업 6
 
0.4%
폐업 4
 
0.3%

Length

2024-04-16T13:11:26.135861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
03 728
49.4%
01 382
25.9%
07 196
 
13.3%
영업/정상 73
 
5.0%
06 48
 
3.3%
02 17
 
1.2%
05 11
 
0.7%
na 7
 
0.5%
휴업 6
 
0.4%
폐업 4
 
0.3%

dtlstatenm
Categorical

Distinct12
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
폐지
731 
신규등록
396 
영업개시
202 
휴지사업재개
 
48
영업중
 
31
Other values (7)
 
66

Length

Max length7
Median length6
Mean length3.0569878
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row신규등록
2nd row폐지
3rd row폐지
4th row폐지
5th row신규등록

Common Values

ValueCountFrequency (%)
폐지 731
49.6%
신규등록 396
26.9%
영업개시 202
 
13.7%
휴지사업재개 48
 
3.3%
영업중 31
 
2.1%
<NA> 20
 
1.4%
등록취소 17
 
1.2%
사업휴지 13
 
0.9%
휴업처리 10
 
0.7%
상세영업상태명 3
 
0.2%
Other values (2) 3
 
0.2%

Length

2024-04-16T13:11:26.242440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐지 731
49.6%
신규등록 396
26.9%
영업개시 202
 
13.7%
휴지사업재개 48
 
3.3%
영업중 31
 
2.1%
na 20
 
1.4%
등록취소 17
 
1.2%
사업휴지 13
 
0.9%
휴업처리 10
 
0.7%
상세영업상태명 3
 
0.2%
Other values (2) 3
 
0.2%

x
Text

MISSING 

Distinct1133
Distinct (%)92.0%
Missing243
Missing (%)16.5%
Memory size11.6 KiB
2024-04-16T13:11:26.391889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.965069
Min length5

Characters and Unicode

Total characters24577
Distinct characters24
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

Unique1057 ?
Unique (%)85.9%

Sample

1st row385717.11248000000
2nd row385732.61555200000
3rd row385535.93263200000
4th row384385.56369900000
5th row384822.48508100000
ValueCountFrequency (%)
380555.507067 7
 
0.6%
401260.939933773 4
 
0.3%
380049.56403400000 4
 
0.3%
380466.31102600000 4
 
0.3%
401610.25118200000 4
 
0.3%
380601.90914800000 3
 
0.2%
387026.84646200000 3
 
0.2%
392414.04586400000 3
 
0.2%
377192.966387666 3
 
0.2%
379230.336838 3
 
0.2%
Other values (1123) 1193
96.9%
2024-04-16T13:11:26.675087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6658
27.1%
3066
12.5%
3 2441
 
9.9%
8 1867
 
7.6%
9 1572
 
6.4%
7 1329
 
5.4%
2 1306
 
5.3%
1 1302
 
5.3%
6 1278
 
5.2%
5 1259
 
5.1%
Other values (14) 2499
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20270
82.5%
Space Separator 3066
 
12.5%
Other Punctuation 1224
 
5.0%
Other Letter 14
 
0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6658
32.8%
3 2441
 
12.0%
8 1867
 
9.2%
9 1572
 
7.8%
7 1329
 
6.6%
2 1306
 
6.4%
1 1302
 
6.4%
6 1278
 
6.3%
5 1259
 
6.2%
4 1258
 
6.2%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
Space Separator
ValueCountFrequency (%)
3066
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1224
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24562
99.9%
Hangul 14
 
0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6658
27.1%
3066
12.5%
3 2441
 
9.9%
8 1867
 
7.6%
9 1572
 
6.4%
7 1329
 
5.4%
2 1306
 
5.3%
1 1302
 
5.3%
6 1278
 
5.2%
5 1259
 
5.1%
Other values (4) 2484
 
10.1%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24563
99.9%
Hangul 14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6658
27.1%
3066
12.5%
3 2441
 
9.9%
8 1867
 
7.6%
9 1572
 
6.4%
7 1329
 
5.4%
2 1306
 
5.3%
1 1302
 
5.3%
6 1278
 
5.2%
5 1259
 
5.1%
Other values (5) 2485
 
10.1%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
1
7.1%
1
7.1%
1
7.1%
1
7.1%

y
Text

MISSING 

Distinct1133
Distinct (%)92.0%
Missing243
Missing (%)16.5%
Memory size11.6 KiB
2024-04-16T13:11:26.839214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.969943
Min length7

Characters and Unicode

Total characters24583
Distinct characters27
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

Unique1057 ?
Unique (%)85.9%

Sample

1st row180436.91578300000
2nd row180996.84119400000
3rd row181386.83062300000
4th row180259.73166600000
5th row180570.89765900000
ValueCountFrequency (%)
185892.189846 7
 
0.6%
190226.561613539 4
 
0.3%
192699.52452200000 4
 
0.3%
186728.83388400000 4
 
0.3%
197494.09608000000 4
 
0.3%
185931.10401700000 3
 
0.2%
184926.53941800000 3
 
0.2%
188680.60868200000 3
 
0.2%
187698.349116734 3
 
0.2%
178079.690806 3
 
0.2%
Other values (1123) 1193
96.9%
2024-04-16T13:11:27.112908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6537
26.6%
3075
12.5%
1 2411
 
9.8%
8 1977
 
8.0%
9 1635
 
6.7%
7 1377
 
5.6%
2 1329
 
5.4%
5 1309
 
5.3%
3 1246
 
5.1%
. 1224
 
5.0%
Other values (17) 2463
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20261
82.4%
Space Separator 3075
 
12.5%
Other Punctuation 1224
 
5.0%
Other Letter 20
 
0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
1
5.0%
1
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
0 6537
32.3%
1 2411
 
11.9%
8 1977
 
9.8%
9 1635
 
8.1%
7 1377
 
6.8%
2 1329
 
6.6%
5 1309
 
6.5%
3 1246
 
6.1%
4 1224
 
6.0%
6 1216
 
6.0%
Space Separator
ValueCountFrequency (%)
3075
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1224
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24562
99.9%
Hangul 20
 
0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6537
26.6%
3075
12.5%
1 2411
 
9.8%
8 1977
 
8.0%
9 1635
 
6.7%
7 1377
 
5.6%
2 1329
 
5.4%
5 1309
 
5.3%
3 1246
 
5.1%
. 1224
 
5.0%
Other values (4) 2442
 
9.9%
Hangul
ValueCountFrequency (%)
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
1
5.0%
1
5.0%
Other values (2) 2
10.0%
Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24563
99.9%
Hangul 20
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6537
26.6%
3075
12.5%
1 2411
 
9.8%
8 1977
 
8.0%
9 1635
 
6.7%
7 1377
 
5.6%
2 1329
 
5.4%
5 1309
 
5.3%
3 1246
 
5.1%
. 1224
 
5.0%
Other values (5) 2443
 
9.9%
Hangul
ValueCountFrequency (%)
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
2
10.0%
1
5.0%
1
5.0%
Other values (2) 2
10.0%
Distinct1421
Distinct (%)96.9%
Missing7
Missing (%)0.5%
Memory size11.6 KiB
2024-04-16T13:11:27.308356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.989093
Min length6

Characters and Unicode

Total characters20522
Distinct characters16
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

Unique1392 ?
Unique (%)94.9%

Sample

1st row20171121112913
2nd row20091126141034
3rd row20080506160124
4th row20160616152334
5th row20171121112951
ValueCountFrequency (%)
20031106000000 6
 
0.4%
20000810000000 5
 
0.3%
20060123000000 5
 
0.3%
20191004134109 3
 
0.2%
20061116000000 3
 
0.2%
20040623000000 3
 
0.2%
20070404000000 3
 
0.2%
20000811000000 3
 
0.2%
20190927153558 3
 
0.2%
20060313000000 3
 
0.2%
Other values (1411) 1430
97.5%
2024-04-16T13:11:27.619091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5504
26.8%
1 4530
22.1%
2 3591
17.5%
5 1230
 
6.0%
3 1184
 
5.8%
4 1127
 
5.5%
7 948
 
4.6%
8 935
 
4.6%
6 790
 
3.8%
9 671
 
3.3%
Other values (6) 12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20510
99.9%
Other Letter 12
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5504
26.8%
1 4530
22.1%
2 3591
17.5%
5 1230
 
6.0%
3 1184
 
5.8%
4 1127
 
5.5%
7 948
 
4.6%
8 935
 
4.6%
6 790
 
3.9%
9 671
 
3.3%
Other Letter
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 20510
99.9%
Hangul 12
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5504
26.8%
1 4530
22.1%
2 3591
17.5%
5 1230
 
6.0%
3 1184
 
5.8%
4 1127
 
5.5%
7 948
 
4.6%
8 935
 
4.6%
6 790
 
3.9%
9 671
 
3.3%
Hangul
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20510
99.9%
Hangul 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5504
26.8%
1 4530
22.1%
2 3591
17.5%
5 1230
 
6.0%
3 1184
 
5.8%
4 1127
 
5.5%
7 948
 
4.6%
8 935
 
4.6%
6 790
 
3.9%
9 671
 
3.3%
Hangul
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%

uptaenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
일반판매소
725 
주유소
610 
용제판매소
 
69
제조
 
25
<NA>
 
25
Other values (5)
 
20

Length

Max length19
Median length5
Mean length4.1567164
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row주유소
2nd row일반판매소
3rd row일반판매소
4th row주유소
5th row주유소

Common Values

ValueCountFrequency (%)
일반판매소 725
49.2%
주유소 610
41.4%
용제판매소 69
 
4.7%
제조 25
 
1.7%
<NA> 25
 
1.7%
저장소 6
 
0.4%
2021-04-01 05:14:03 6
 
0.4%
업태구분명 5
 
0.3%
항공유판매소 2
 
0.1%
부생연료유판매소 1
 
0.1%

Length

2024-04-16T13:11:27.738324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:27.837098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반판매소 725
49.0%
주유소 610
41.2%
용제판매소 69
 
4.7%
제조 25
 
1.7%
na 25
 
1.7%
저장소 6
 
0.4%
2021-04-01 6
 
0.4%
05:14:03 6
 
0.4%
업태구분명 5
 
0.3%
항공유판매소 2
 
0.1%

sitetel
Categorical

IMBALANCE 

Distinct22
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
051-123-1234
1416 
<NA>
 
27
전화번호
 
12
051-244-5151
 
1
051 646 5182
 
1
Other values (17)
 
17

Length

Max length12
Median length12
Mean length11.784261
Min length4

Unique

Unique19 ?
Unique (%)1.3%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 1416
96.1%
<NA> 27
 
1.8%
전화번호 12
 
0.8%
051-244-5151 1
 
0.1%
051 646 5182 1
 
0.1%
051 647 5185 1
 
0.1%
051 3413500 1
 
0.1%
051 3373100 1
 
0.1%
051 2631678 1
 
0.1%
051 264 5184 1
 
0.1%
Other values (12) 12
 
0.8%

Length

2024-04-16T13:11:27.951866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 1416
94.6%
na 27
 
1.8%
051 16
 
1.1%
전화번호 12
 
0.8%
9712035 1
 
0.1%
532 1
 
0.1%
8911400 1
 
0.1%
5083 1
 
0.1%
728 1
 
0.1%
3285311 1
 
0.1%
Other values (20) 20
 
1.3%

gaspdtsortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
가스용품종류명
 
21

Length

Max length7
Median length4
Mean length4.0427408
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> 1453
98.6%
가스용품종류명 21
 
1.4%

Length

2024-04-16T13:11:28.053999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:28.152495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
가스용품종류명 21
 
1.4%

gassortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
가스종류명
 
21

Length

Max length5
Median length4
Mean length4.0142469
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> 1453
98.6%
가스종류명 21
 
1.4%

Length

2024-04-16T13:11:28.243109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:28.327761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
가스종류명 21
 
1.4%

upchnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
거래처
 
21

Length

Max length4
Median length4
Mean length3.9857531
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> 1453
98.6%
거래처 21
 
1.4%

Length

2024-04-16T13:11:28.429858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:28.517226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
거래처 21
 
1.4%

suprulesctn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
공급규정내용
 
21

Length

Max length6
Median length4
Mean length4.0284939
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> 1453
98.6%
공급규정내용 21
 
1.4%

Length

2024-04-16T13:11:28.610958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:28.697062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
공급규정내용 21
 
1.4%

spyvolt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
공급전압
 
21

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1453
98.6%
공급전압 21
 
1.4%

Length

2024-04-16T13:11:28.776765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.088526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
공급전압 21
 
1.4%

ltchgcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
길이변경내용
 
21

Length

Max length6
Median length4
Mean length4.0284939
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> 1453
98.6%
길이변경내용 21
 
1.4%

Length

2024-04-16T13:11:29.177124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.266732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
길이변경내용 21
 
1.4%

exmran
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
면제범위
 
21

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1453
98.6%
면제범위 21
 
1.4%

Length

2024-04-16T13:11:29.355475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.435301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
면제범위 21
 
1.4%

prdsiz
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
물품규격
 
21

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1453
98.6%
물품규격 21
 
1.4%

Length

2024-04-16T13:11:29.517999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.598444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
물품규격 21
 
1.4%

baelt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
배관길이
 
21

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1453
98.6%
배관길이 21
 
1.4%

Length

2024-04-16T13:11:29.683261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.775198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
배관길이 21
 
1.4%

baeesbplc
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
배관설치장소
 
21

Length

Max length6
Median length4
Mean length4.0284939
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> 1453
98.6%
배관설치장소 21
 
1.4%

Length

2024-04-16T13:11:29.876312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:29.966046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
배관설치장소 21
 
1.4%

offtelno
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
051-123-1234
1416 
<NA>
 
39
사무소전화번호
 
19

Length

Max length12
Median length12
Mean length11.723881
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 1416
96.1%
<NA> 39
 
2.6%
사무소전화번호 19
 
1.3%

Length

2024-04-16T13:11:30.061197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:30.148750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 1416
96.1%
na 39
 
2.6%
사무소전화번호 19
 
1.3%

ofear
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
사무실면적
 
21

Length

Max length5
Median length4
Mean length4.0142469
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> 1453
98.6%
사무실면적 21
 
1.4%

Length

2024-04-16T13:11:30.252554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:30.337144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
사무실면적 21
 
1.4%

bsnsopeningprearrymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
사업개시예정일자
 
21

Length

Max length8
Median length4
Mean length4.0569878
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> 1453
98.6%
사업개시예정일자 21
 
1.4%

Length

2024-04-16T13:11:30.430941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:30.520880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
사업개시예정일자 21
 
1.4%

wrkpgrdsrvsenm
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1450 
사업장부지용도구분명
 
21
기타
 
3

Length

Max length10
Median length4
Mean length4.0814111
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> 1450
98.4%
사업장부지용도구분명 21
 
1.4%
기타 3
 
0.2%

Length

2024-04-16T13:11:30.620196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:30.713188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1450
98.4%
사업장부지용도구분명 21
 
1.4%
기타 3
 
0.2%

wrkptelno
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1453 
사업장전화번호
 
21

Length

Max length7
Median length4
Mean length4.0427408
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> 1453
98.6%
사업장전화번호 21
 
1.4%

Length

2024-04-16T13:11:30.848121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:30.937767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1453
98.6%
사업장전화번호 21
 
1.4%

useobj
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1431 
사용목적
 
16
의료용
 
13
절단용
 
2
Ru chemical 제조
 
2
Other values (9)
 
10

Length

Max length15
Median length4
Mean length4.0339213
Min length3

Unique

Unique8 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1431
97.1%
사용목적 16
 
1.1%
의료용 13
 
0.9%
절단용 2
 
0.1%
Ru chemical 제조 2
 
0.1%
강재절단, 압접용 2
 
0.1%
의료용(호흡용) 1
 
0.1%
의료용 산소 1
 
0.1%
의료용 산소공급용 1
 
0.1%
절단작업용 1
 
0.1%
Other values (4) 4
 
0.3%

Length

2024-04-16T13:11:31.025668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1431
96.0%
사용목적 16
 
1.1%
의료용 15
 
1.0%
절단용 2
 
0.1%
ru 2
 
0.1%
chemical 2
 
0.1%
제조 2
 
0.1%
강재절단 2
 
0.1%
압접용 2
 
0.1%
용접 2
 
0.1%
Other values (14) 14
 
0.9%

usemet
Categorical

IMBALANCE 

Distinct19
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1431 
사용방법
 
16
의료용
 
4
산소
 
3
액화산소의 경우 배관 연결하여 사용
 
3
Other values (14)
 
17

Length

Max length22
Median length4
Mean length4.0915875
Min length2

Unique

Unique11 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1431
97.1%
사용방법 16
 
1.1%
의료용 4
 
0.3%
산소 3
 
0.2%
액화산소의 경우 배관 연결하여 사용 3
 
0.2%
강재절단, 압접용 2
 
0.1%
Ru chemical 제조 2
 
0.1%
의료용산소 2
 
0.1%
용기보관 1
 
0.1%
용기보관실 1
 
0.1%
Other values (9) 9
 
0.6%

Length

2024-04-16T13:11:31.139337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1431
94.6%
사용방법 16
 
1.1%
의료용 5
 
0.3%
산소 4
 
0.3%
사용 4
 
0.3%
액화산소의 3
 
0.2%
경우 3
 
0.2%
배관 3
 
0.2%
연결하여 3
 
0.2%
제조 2
 
0.1%
Other values (30) 38
 
2.5%

dsnrspvsnsortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
설계감리업종류명
 
19

Length

Max length8
Median length4
Mean length4.0515604
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> 1455
98.7%
설계감리업종류명 19
 
1.3%

Length

2024-04-16T13:11:31.256559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:31.347569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
설계감리업종류명 19
 
1.3%

equnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
설비명
 
19

Length

Max length4
Median length4
Mean length3.9871099
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> 1455
98.7%
설비명 19
 
1.3%

Length

2024-04-16T13:11:31.438423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:31.523253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
설비명 19
 
1.3%

equcap
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
설비용량
 
19

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1455
98.7%
설비용량 19
 
1.3%

Length

2024-04-16T13:11:31.602821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:31.681756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
설비용량 19
 
1.3%

stanm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
소속국가명
 
19

Length

Max length5
Median length4
Mean length4.0128901
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> 1455
98.7%
소속국가명 19
 
1.3%

Length

2024-04-16T13:11:31.764850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:31.846061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
소속국가명 19
 
1.3%

sygrglstcnt
Categorical

IMBALANCE 

Distinct16
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1437 
수용정원수
 
16
0
 
5
135
 
2
100
 
2
Other values (11)
 
12

Length

Max length5
Median length4
Mean length3.9837178
Min length1

Unique

Unique10 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1437
97.5%
수용정원수 16
 
1.1%
0 5
 
0.3%
135 2
 
0.1%
100 2
 
0.1%
230 2
 
0.1%
400 1
 
0.1%
650 1
 
0.1%
172 1
 
0.1%
2 1
 
0.1%
Other values (6) 6
 
0.4%

Length

2024-04-16T13:11:31.940324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1437
97.5%
수용정원수 16
 
1.1%
0 5
 
0.3%
135 2
 
0.1%
100 2
 
0.1%
230 2
 
0.1%
400 1
 
0.1%
650 1
 
0.1%
172 1
 
0.1%
2 1
 
0.1%
Other values (6) 6
 
0.4%

faciluseyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
 
19

Length

Max length4
Median length4
Mean length3.9613297
Min length1

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> 1455
98.7%
19
 
1.3%

Length

2024-04-16T13:11:32.047048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:32.130824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
19
 
1.3%

realcapt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
실질자본금
 
19

Length

Max length5
Median length4
Mean length4.0128901
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> 1455
98.7%
실질자본금 19
 
1.3%

Length

2024-04-16T13:11:32.214705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:32.304096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
실질자본금 19
 
1.3%

cobgbnnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
업종구분명
 
19

Length

Max length5
Median length4
Mean length4.0128901
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> 1455
98.7%
업종구분명 19
 
1.3%

Length

2024-04-16T13:11:32.398367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:32.493314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
업종구분명 19
 
1.3%

instrstoroomar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
용기저장실면적
 
19

Length

Max length7
Median length4
Mean length4.0386703
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> 1455
98.7%
용기저장실면적 19
 
1.3%

Length

2024-04-16T13:11:32.593232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:32.688413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
용기저장실면적 19
 
1.3%

motpowersortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
원동력종류명
 
19

Length

Max length6
Median length4
Mean length4.0257802
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> 1455
98.7%
원동력종류명 19
 
1.3%

Length

2024-04-16T13:11:32.802814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:32.915158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
원동력종류명 19
 
1.3%

bmonuseqy
Categorical

IMBALANCE 

Distinct17
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1437 
월사용량
 
16
1000
 
3
650
 
3
3000
 
2
Other values (12)
 
13

Length

Max length4
Median length4
Mean length3.990502
Min length2

Unique

Unique11 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1437
97.5%
월사용량 16
 
1.1%
1000 3
 
0.2%
650 3
 
0.2%
3000 2
 
0.1%
336 2
 
0.1%
50 1
 
0.1%
140 1
 
0.1%
15 1
 
0.1%
480 1
 
0.1%
Other values (7) 7
 
0.5%

Length

2024-04-16T13:11:33.017944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1437
97.5%
월사용량 16
 
1.1%
1000 3
 
0.2%
650 3
 
0.2%
3000 2
 
0.1%
336 2
 
0.1%
672 1
 
0.1%
1600 1
 
0.1%
2000 1
 
0.1%
760 1
 
0.1%
Other values (7) 7
 
0.5%

cyprpdtfacil
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
윤전기생산시설
 
19

Length

Max length7
Median length4
Mean length4.0386703
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> 1455
98.7%
윤전기생산시설 19
 
1.3%

Length

2024-04-16T13:11:33.135175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:33.233517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
윤전기생산시설 19
 
1.3%

capt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
자본금
 
19

Length

Max length4
Median length4
Mean length3.9871099
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> 1455
98.7%
자본금 19
 
1.3%

Length

2024-04-16T13:11:33.327937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:33.428181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
자본금 19
 
1.3%

saveequloc
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
저장설비위치
 
19

Length

Max length6
Median length4
Mean length4.0257802
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> 1455
98.7%
저장설비위치 19
 
1.3%

Length

2024-04-16T13:11:33.533387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:33.633084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
저장설비위치 19
 
1.3%

scoalar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
저탄장면적
 
19

Length

Max length5
Median length4
Mean length4.0128901
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> 1455
98.7%
저탄장면적 19
 
1.3%

Length

2024-04-16T13:11:33.728492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:33.822718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
저탄장면적 19
 
1.3%

permcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
전기사업허가조건
 
19

Length

Max length8
Median length4
Mean length4.0515604
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> 1455
98.7%
전기사업허가조건 19
 
1.3%

Length

2024-04-16T13:11:33.929422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:34.024162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
전기사업허가조건 19
 
1.3%

prdsenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1433 
제조구분명
 
16
냉동
 
16
충전
 
7
일반
 
2

Length

Max length5
Median length4
Mean length3.9769335
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> 1433
97.2%
제조구분명 16
 
1.1%
냉동 16
 
1.1%
충전 7
 
0.5%
일반 2
 
0.1%

Length

2024-04-16T13:11:34.121504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:34.243609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1433
97.2%
제조구분명 16
 
1.1%
냉동 16
 
1.1%
충전 7
 
0.5%
일반 2
 
0.1%

frequ
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
주파수
 
19

Length

Max length4
Median length4
Mean length3.9871099
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> 1455
98.7%
주파수 19
 
1.3%

Length

2024-04-16T13:11:34.394270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:34.505422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
주파수 19
 
1.3%

cgpar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
차고지면적
 
19

Length

Max length5
Median length4
Mean length4.0128901
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> 1455
98.7%
차고지면적 19
 
1.3%

Length

2024-04-16T13:11:34.618377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:35.045745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
차고지면적 19
 
1.3%

rlservlnennm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
철도인입선유무명
 
19

Length

Max length8
Median length4
Mean length4.0515604
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> 1455
98.7%
철도인입선유무명 19
 
1.3%

Length

2024-04-16T13:11:35.174576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:35.308872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
철도인입선유무명 19
 
1.3%

tregascap
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1455 
취급가스용량
 
19

Length

Max length6
Median length4
Mean length4.0257802
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> 1455
98.7%
취급가스용량 19
 
1.3%

Length

2024-04-16T13:11:35.469399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:35.599182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1455
98.7%
취급가스용량 19
 
1.3%

last_load_dttm
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing15
Missing (%)1.0%
Memory size11.6 KiB
Minimum2021-04-01 05:14:03
Maximum2021-04-01 05:14:03
2024-04-16T13:11:35.695658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:11:35.799916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm
013250000198732500140150000109_28_08_PI2018-08-31 23:59:59.0<NA>고려주유소<NA>부산광역시 중구 중앙동5가 70번지48947부산광역시 중구 대청로 153 (중앙동5가)19870812<NA><NA><NA><NA>01신규등록385717.11248000000180436.9157830000020171121112913주유소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
123250000197132500140120000309_28_08_PI2018-08-31 23:59:59.0<NA>영신석유<NA>부산광역시 중구 영주동 73-11번지48947<NA>19710722<NA><NA><NA><NA>03폐지<NA><NA>20091126141034일반판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
233250000197132500140120000409_28_08_PI2018-08-31 23:59:59.0<NA>남포석유상사<NA>부산광역시 중구 대청동4가 31-17번지48947<NA>1971092420080506<NA><NA><NA>03폐지<NA><NA>20080506160124일반판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
343250000197632500140150000109_28_08_PI2018-08-31 23:59:59.0<NA>강남주유소<NA>부산광역시 중구 중앙동4가 82-8번지48947부산광역시 중구 중앙대로 120 (중앙동4가)1976050320160616<NA><NA><NA>03폐지385732.61555200000180996.8411940000020160616152334주유소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
453250000197632500140150000409_28_08_PI2018-08-31 23:59:59.0<NA>에스씨(주) 제일주유소<NA>부산광역시 중구 영주동 556-3외10필지번지48947부산광역시 중구 중구로 194 (영주동)19760513<NA><NA><NA><NA>01신규등록385535.93263200000181386.8306230000020171121112951주유소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
563250000198532500140150000109_28_08_PI2018-08-31 23:59:59.0<NA>남포주유소<NA>부산광역시 중구 부평동4가 32-2, 33, 34-6번지48947부산광역시 중구 보수대로 62 (부평동4가)198511112015112620120501201212312013020403폐지384385.56369900000180259.7316660000020151126164419주유소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
673250000199632500140120000909_28_08_PI2018-08-31 23:59:59.0<NA>유성석유<NA>부산광역시 중구 보수동1가 60-108번지48947부산광역시 중구 보동길 10 (보수동1가)19990826<NA><NA><NA><NA>01신규등록384822.48508100000180570.8976590000020171121113216일반판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
783250000199932500140120001009_28_08_PI2018-08-31 23:59:59.0<NA>영창석유<NA>부산광역시 중구 보수동1가 60-113번지48947<NA>1999102620101230<NA><NA><NA>03폐지<NA><NA>20101230163642일반판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
893250000199932500140120001109_28_08_PI2018-08-31 23:59:59.0<NA>영동석유<NA>부산광역시 중구 영주동 470-10,17번지48947<NA>1999122420081107<NA><NA><NA>03폐지<NA><NA>20081107141354일반판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
9103250000200032500830150000209_28_08_PI2018-08-31 23:59:59.0<NA>동륭케미칼(주)부산영업소<NA>부산광역시 중구 중앙동4가 84-1번지48938부산광역시 중구 충장대로5번길 26, 3층 303호 (중앙동4가)20000607<NA><NA><NA><NA>01신규등록385748.21746400000180936.6008820000020171122112647용제판매소051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm
1464사무실주소: 분포로 115A동 503호설계감리업종류명설비명설비용량소속국가명0실질자본금업종구분명용기저장실면적원동력종류명160윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
146579013310000202133101191220000109_28_14_PI2021-03-14 00:23:00.0특정고압가스업(주)우인건설지번우편번호부산광역시 남구 용호동 957-1 힐탑탑플레이스 A동 115호48515부산광역시 남구 분포로 115, 힐탑탑플레이스 (용호동)20210312폐업일자휴업시작일자휴업종료일자재개업일자영업/정상상세영업상태명392515.689667818183481.9411185720210312164859업태구분명전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호강재절단, 압접용강재절단, 압접용<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1466사용처: 용호동 958<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1467사무실주소: 분포로 115A동 503호설계감리업종류명설비명설비용량소속국가명0실질자본금업종구분명용기저장실면적원동력종류명160윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
146879023380000202133800821220000109_28_14_PI2021-03-25 00:22:59.0특정고압가스업성진프라자지번우편번호부산광역시 수영구 민락동 181-204 성진회센터48283부산광역시 수영구 민락수변로 5, 성진회센터 (민락동)20210323폐업일자휴업시작일자휴업종료일자재개업일자영업/정상상세영업상태명393462.263967573186081.95920260520210323110820업태구분명전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호건물내 물고기 산소용건물내 물고기 산소용설계감리업종류명설비명설비용량소속국가명10실질자본금업종구분명용기저장실면적원동력종류명840윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03
146979033340000202133401310220000109_28_05_PI2021-03-28 00:22:59.0고압가스업부산해양경찰청(다대파출소)지번우편번호부산광역시 사하구 다대동 680-5 부산해양경찰서 다대파출소49522부산광역시 사하구 다대동로 10, 부산해양경찰서 다대파출소 (다대동)20210326폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중379811.419557726174605.58332103720210326163004제조전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호사용목적사용방법설계감리업종류명설비명설비용량소속국가명수용정원수실질자본금업종구분명용기저장실면적원동력종류명월사용량윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건충전주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03
147079043340000202133401310220000109_28_05_PI2021-03-28 00:22:59.0고압가스업부산해양경찰청(다대파출소)지번우편번호부산광역시 사하구 다대동 680-5 부산해양경찰서 다대파출소49522부산광역시 사하구 다대동로 10, 부산해양경찰서 다대파출소 (다대동)20210326폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중379811.419557726174605.58332103720210326163004제조전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호사용목적사용방법설계감리업종류명설비명설비용량소속국가명수용정원수실질자본금업종구분명용기저장실면적원동력종류명월사용량윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건충전주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03
147179053360000202133601450150000109_28_08_PI2021-03-31 00:22:59.0석유판매업(주)OS에너지 OS신항주유소지번우편번호부산광역시 강서구 미음동 1652-246747부산광역시 강서구 가락대로 845 (미음동)20210325폐업일자휴업시작일자휴업종료일자재개업일자영업/정상신규등록좌표정보(X)좌표정보(Y)20210329130535주유소전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호사용목적사용방법설계감리업종류명설비명설비용량소속국가명수용정원수실질자본금업종구분명용기저장실면적원동력종류명월사용량윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03
147279063340000202033401310220000109_28_05_PI2021-03-31 00:22:59.0고압가스업대선조선(주) 다대공장<NA>부산광역시 사하구 다대동 1553<NA><NA>20200323<NA><NA><NA><NA>영업/정상영업중381613.325457691174551.63564182620210329163814제조<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>냉동<NA><NA><NA><NA>2021-04-01 05:14:03
147378983360000202133601450220000109_28_05_PI2021-02-24 00:23:01.0고압가스업(주)더켐뱅크<NA>부산광역시 강서구 지사동 1406-1<NA><NA>20210222<NA><NA><NA><NA>영업/정상영업중365455.524851569185355.89804967820210222164953제조<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>냉동<NA><NA><NA><NA>2021-04-01 05:14:03

Duplicate rows

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skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm# duplicates
2압축산소의 경우 이동식<NA><NA><NA><NA>170<NA><NA><NA><NA><NA>500<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:14:03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3
0사무실주소: 분포로 115A동 503호설계감리업종류명설비명설비용량소속국가명0실질자본금업종구분명용기저장실면적원동력종류명160윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-04-01 05:14:03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
1사용처: 용호동 958<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2