Overview

Dataset statistics

Number of variables63
Number of observations1462
Missing cells10181
Missing cells (%)11.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory728.3 KiB
Average record size in memory510.1 B

Variable types

Text11
Numeric6
Categorical45
DateTime1

Alerts

last_load_dttm has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (85.7%)Imbalance
updategbn is highly imbalanced (95.8%)Imbalance
updatedt is highly imbalanced (91.4%)Imbalance
opnsvcnm is highly imbalanced (86.3%)Imbalance
sitepostno is highly imbalanced (96.7%)Imbalance
rdnpostno is highly imbalanced (90.6%)Imbalance
uptaenm is highly imbalanced (54.7%)Imbalance
sitetel is highly imbalanced (91.6%)Imbalance
gaspdtsortnm is highly imbalanced (96.7%)Imbalance
gassortnm is highly imbalanced (96.7%)Imbalance
upchnm is highly imbalanced (96.7%)Imbalance
suprulesctn is highly imbalanced (96.7%)Imbalance
spyvolt is highly imbalanced (96.7%)Imbalance
ltchgcn is highly imbalanced (96.7%)Imbalance
exmran is highly imbalanced (96.7%)Imbalance
prdsiz is highly imbalanced (96.7%)Imbalance
baelt is highly imbalanced (96.7%)Imbalance
baeesbplc is highly imbalanced (96.7%)Imbalance
offtelno is highly imbalanced (91.6%)Imbalance
ofear is highly imbalanced (96.7%)Imbalance
bsnsopeningprearrymd is highly imbalanced (96.7%)Imbalance
wrkpgrdsrvsenm is highly imbalanced (96.6%)Imbalance
wrkptelno is highly imbalanced (96.7%)Imbalance
useobj is highly imbalanced (94.8%)Imbalance
dsnrspvsnsortnm is highly imbalanced (96.7%)Imbalance
equnm is highly imbalanced (96.7%)Imbalance
equcap is highly imbalanced (96.7%)Imbalance
stanm is highly imbalanced (96.7%)Imbalance
faciluseyn is highly imbalanced (96.7%)Imbalance
realcapt is highly imbalanced (96.7%)Imbalance
cobgbnnm is highly imbalanced (96.7%)Imbalance
instrstoroomar is highly imbalanced (96.7%)Imbalance
motpowersortnm is highly imbalanced (96.7%)Imbalance
cyprpdtfacil is highly imbalanced (96.7%)Imbalance
capt is highly imbalanced (96.7%)Imbalance
saveequloc is highly imbalanced (96.7%)Imbalance
scoalar is highly imbalanced (96.7%)Imbalance
permcn is highly imbalanced (96.7%)Imbalance
prdsenm is highly imbalanced (93.2%)Imbalance
frequ is highly imbalanced (96.7%)Imbalance
cgpar is highly imbalanced (96.7%)Imbalance
rlservlnennm is highly imbalanced (96.7%)Imbalance
tregascap is highly imbalanced (96.7%)Imbalance
rdnwhladdr has 306 (20.9%) missing valuesMissing
dcbymd has 986 (67.4%) missing valuesMissing
clgstdt has 1332 (91.1%) missing valuesMissing
clgenddt has 1332 (91.1%) missing valuesMissing
ropnymd has 1388 (94.9%) missing valuesMissing
x has 241 (16.5%) missing valuesMissing
y has 241 (16.5%) missing valuesMissing
usemet has 1435 (98.2%) missing valuesMissing
sygrglstcnt has 1439 (98.4%) missing valuesMissing
bmonuseqy has 1439 (98.4%) missing valuesMissing
mgtno is highly skewed (γ1 = -28.18003615)Skewed
apvpermymd is highly skewed (γ1 = -28.10698368)Skewed

Reproduction

Analysis started2024-04-16 04:11:38.348805
Analysis finished2024-04-16 04:11:40.064514
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

Distinct1460
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2024-04-16T13:11:40.491750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length3
Mean length3.2831737
Min length1

Characters and Unicode

Total characters4800
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1459 ?
Unique (%)99.8%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
압축산소의 3
 
0.2%
이동식 3
 
0.2%
경우 3
 
0.2%
1371 1
 
0.1%
958 1
 
0.1%
976 1
 
0.1%
975 1
 
0.1%
974 1
 
0.1%
973 1
 
0.1%
972 1
 
0.1%
Other values (1454) 1454
98.9%
2024-04-16T13:11:41.213526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 907
18.9%
2 515
10.7%
3 503
10.5%
7 419
8.7%
4 406
8.5%
8 402
8.4%
0 400
8.3%
5 400
8.3%
6 399
8.3%
9 389
8.1%
Other values (25) 60
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4740
98.8%
Other Letter 41
 
0.9%
Dash Punctuation 9
 
0.2%
Space Separator 8
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
Other values (11) 11
26.8%
Decimal Number
ValueCountFrequency (%)
1 907
19.1%
2 515
10.9%
3 503
10.6%
7 419
8.8%
4 406
8.6%
8 402
8.5%
0 400
8.4%
5 400
8.4%
6 399
8.4%
9 389
8.2%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4759
99.1%
Hangul 41
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
Other values (11) 11
26.8%
Common
ValueCountFrequency (%)
1 907
19.1%
2 515
10.8%
3 503
10.6%
7 419
8.8%
4 406
8.5%
8 402
8.4%
0 400
8.4%
5 400
8.4%
6 399
8.4%
9 389
8.2%
Other values (4) 19
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4759
99.1%
Hangul 41
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 907
19.1%
2 515
10.8%
3 503
10.6%
7 419
8.8%
4 406
8.5%
8 402
8.4%
0 400
8.4%
5 400
8.4%
6 399
8.4%
9 389
8.2%
Other values (4) 19
 
0.4%
Hangul
ValueCountFrequency (%)
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
Other values (11) 11
26.8%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)1.1%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean3337556.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:41.548048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13300000
median3340000
Q33380000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation42045.089
Coefficient of variation (CV)0.012597566
Kurtosis-1.0598843
Mean3337556.6
Median Absolute Deviation (MAD)40000
Skewness-0.17695447
Sum4.86282 × 109
Variance1.7677895 × 109
MonotonicityNot monotonic
2024-04-16T13:11:41.860930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3390000 204
14.0%
3340000 151
10.3%
3290000 116
 
7.9%
3350000 113
 
7.7%
3400000 102
 
7.0%
3310000 97
 
6.6%
3360000 97
 
6.6%
3320000 90
 
6.2%
3300000 87
 
6.0%
3330000 85
 
5.8%
Other values (6) 315
21.5%
ValueCountFrequency (%)
3250000 24
 
1.6%
3260000 38
 
2.6%
3270000 51
 
3.5%
3280000 67
4.6%
3290000 116
7.9%
3300000 87
6.0%
3310000 97
6.6%
3320000 90
6.2%
3330000 85
5.8%
3340000 151
10.3%
ValueCountFrequency (%)
3400000 102
7.0%
3390000 204
14.0%
3380000 63
 
4.3%
3370000 72
 
4.9%
3360000 97
6.6%
3350000 113
7.7%
3340000 151
10.3%
3330000 85
5.8%
3320000 90
6.2%
3310000 97
6.6%

mgtno
Real number (ℝ)

SKEWED 

Distinct618
Distinct (%)42.4%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean1.996286 × 1018
Minimum1.195339 × 1018
Maximum2.02134 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:42.284849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.195339 × 1018
5-th percentile1.976339 × 1018
Q11.992337 × 1018
median1.99534 × 1018
Q32.003329 × 1018
95-th percentile2.0135342 × 1018
Maximum2.02134 × 1018
Range8.2600101 × 1017
Interquartile range (IQR)1.0992 × 1016

Descriptive statistics

Standard deviation2.3229928 × 1016
Coefficient of variation (CV)0.011636573
Kurtosis971.76133
Mean1.996286 × 1018
Median Absolute Deviation (MAD)4.998999 × 1015
Skewness-28.180036
Sum-5.9969095 × 1018
Variance5.3962956 × 1032
MonotonicityNot monotonic
2024-04-16T13:11:42.642743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2003332005901499904 18
 
1.2%
2000329001301499904 18
 
1.2%
1994336001301499904 18
 
1.2%
1993339001501499904 15
 
1.0%
1994333001501200128 13
 
0.9%
1999329001301200128 13
 
0.9%
1994339001501499904 12
 
0.8%
2001335001501200128 9
 
0.6%
1992339001501499904 9
 
0.6%
1994331001601200128 9
 
0.6%
Other values (608) 1323
90.5%
ValueCountFrequency (%)
1195339001501499904 1
 
0.1%
1967334001701499904 1
 
0.1%
1968331001601499904 1
 
0.1%
1969325001401200128 1
 
0.1%
1970335001501200128 1
 
0.1%
1971325001401200128 3
0.2%
1971334001701200128 1
 
0.1%
1971337006901200128 1
 
0.1%
1972331001601200128 1
 
0.1%
1973334001701200128 2
0.1%
ValueCountFrequency (%)
2021340010901499904 2
0.1%
2021339010902099968 1
0.1%
2021336014502200064 1
0.1%
2021336014502099968 1
0.1%
2021332010702200064 1
0.1%
2020340010912199936 1
0.1%
2020340010902200064 1
0.1%
2020340010902099968 2
0.1%
2020339009112199936 1
0.1%
2020339009102099968 2
0.1%

opnsvcid
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
09_28_08_P
1406 
09_28_05_P
 
28
09_28_14_P
 
23
<NA>
 
5

Length

Max length10
Median length10
Mean length9.9794802
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 1406
96.2%
09_28_05_P 28
 
1.9%
09_28_14_P 23
 
1.6%
<NA> 5
 
0.3%

Length

2024-04-16T13:11:42.930618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:43.141131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_08_p 1406
96.2%
09_28_05_p 28
 
1.9%
09_28_14_p 23
 
1.6%
na 5
 
0.3%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
I
1452 
U
 
5
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0102599
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1452
99.3%
U 5
 
0.3%
<NA> 5
 
0.3%

Length

2024-04-16T13:11:43.346716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:43.491386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1452
99.3%
u 5
 
0.3%
na 5
 
0.3%

updatedt
Categorical

IMBALANCE 

Distinct46
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2018-08-31 23:59:59.0
1401 
170
 
3
2019-10-06 00:22:43.0
 
3
2019-09-29 02:22:39.0
 
3
2020-09-06 00:23:13.0
 
2
Other values (41)
 
50

Length

Max length21
Median length21
Mean length20.93844
Min length2

Unique

Unique32 ?
Unique (%)2.2%

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

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 1401
95.8%
170 3
 
0.2%
2019-10-06 00:22:43.0 3
 
0.2%
2019-09-29 02:22:39.0 3
 
0.2%
2020-09-06 00:23:13.0 2
 
0.1%
2021-02-24 00:23:01.0 2
 
0.1%
2019-10-05 00:22:54.0 2
 
0.1%
2020-01-09 00:23:25.0 2
 
0.1%
2018-09-06 11:43:53.0 2
 
0.1%
2020-10-01 00:23:11.0 2
 
0.1%
Other values (36) 40
 
2.7%

Length

2024-04-16T13:11:43.664963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 1401
48.0%
23:59:59.0 1401
48.0%
02:22:39.0 3
 
0.1%
02:40:00.0 3
 
0.1%
00:23:06.0 3
 
0.1%
00:23:13.0 3
 
0.1%
00:23:09.0 3
 
0.1%
00:23:22.0 3
 
0.1%
170 3
 
0.1%
2019-09-29 3
 
0.1%
Other values (72) 93
 
3.2%

opnsvcnm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1408 
고압가스업
 
28
특정고압가스업
 
23
석유판매업
 
3

Length

Max length7
Median length4
Mean length4.0683995
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> 1408
96.3%
고압가스업 28
 
1.9%
특정고압가스업 23
 
1.6%
석유판매업 3
 
0.2%

Length

2024-04-16T13:11:43.856100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:44.022947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1408
96.3%
고압가스업 28
 
1.9%
특정고압가스업 23
 
1.6%
석유판매업 3
 
0.2%

bplcnm
Text

Distinct1162
Distinct (%)79.8%
Missing5
Missing (%)0.3%
Memory size11.6 KiB
2024-04-16T13:11:44.336406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length6.9142073
Min length4

Characters and Unicode

Total characters10074
Distinct characters371
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

Unique1000 ?
Unique (%)68.6%

Sample

1st row고려주유소
2nd row영신석유
3rd row남포석유상사
4th row강남주유소
5th row에스씨(주) 제일주유소
ValueCountFrequency (%)
직영 11
 
0.7%
현대석유 10
 
0.6%
주)os에너지 8
 
0.5%
유성석유 8
 
0.5%
삼성석유 8
 
0.5%
대동석유 8
 
0.5%
제일석유 7
 
0.4%
금성석유 7
 
0.4%
부산석유 7
 
0.4%
경동석유 7
 
0.4%
Other values (1221) 1563
95.1%
2024-04-16T13:11:44.766535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1292
 
12.8%
936
 
9.3%
643
 
6.4%
613
 
6.1%
( 350
 
3.5%
) 350
 
3.5%
220
 
2.2%
218
 
2.2%
195
 
1.9%
189
 
1.9%
Other values (361) 5068
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8911
88.5%
Open Punctuation 352
 
3.5%
Close Punctuation 352
 
3.5%
Uppercase Letter 202
 
2.0%
Space Separator 187
 
1.9%
Lowercase Letter 31
 
0.3%
Decimal Number 27
 
0.3%
Other Punctuation 7
 
0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1292
 
14.5%
936
 
10.5%
643
 
7.2%
613
 
6.9%
220
 
2.5%
218
 
2.4%
195
 
2.2%
189
 
2.1%
182
 
2.0%
133
 
1.5%
Other values (321) 4290
48.1%
Uppercase Letter
ValueCountFrequency (%)
S 81
40.1%
K 62
30.7%
C 13
 
6.4%
O 11
 
5.4%
G 8
 
4.0%
I 8
 
4.0%
H 4
 
2.0%
T 3
 
1.5%
P 3
 
1.5%
L 2
 
1.0%
Other values (5) 7
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
s 9
29.0%
k 7
22.6%
e 4
12.9%
l 3
 
9.7%
f 3
 
9.7%
c 2
 
6.5%
m 1
 
3.2%
h 1
 
3.2%
o 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 9
33.3%
2 8
29.6%
9 3
 
11.1%
3 2
 
7.4%
0 2
 
7.4%
8 2
 
7.4%
6 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
. 2
28.6%
, 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 350
99.4%
[ 2
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 350
99.4%
] 2
 
0.6%
Space Separator
ValueCountFrequency (%)
187
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8916
88.5%
Common 925
 
9.2%
Latin 233
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1292
 
14.5%
936
 
10.5%
643
 
7.2%
613
 
6.9%
220
 
2.5%
218
 
2.4%
195
 
2.2%
189
 
2.1%
182
 
2.0%
133
 
1.5%
Other values (322) 4295
48.2%
Latin
ValueCountFrequency (%)
S 81
34.8%
K 62
26.6%
C 13
 
5.6%
O 11
 
4.7%
s 9
 
3.9%
G 8
 
3.4%
I 8
 
3.4%
k 7
 
3.0%
H 4
 
1.7%
e 4
 
1.7%
Other values (14) 26
 
11.2%
Common
ValueCountFrequency (%)
( 350
37.8%
) 350
37.8%
187
20.2%
1 9
 
1.0%
2 8
 
0.9%
& 4
 
0.4%
9 3
 
0.3%
3 2
 
0.2%
0 2
 
0.2%
8 2
 
0.2%
Other values (5) 8
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8911
88.5%
ASCII 1158
 
11.5%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1292
 
14.5%
936
 
10.5%
643
 
7.2%
613
 
6.9%
220
 
2.5%
218
 
2.4%
195
 
2.2%
189
 
2.1%
182
 
2.0%
133
 
1.5%
Other values (321) 4290
48.1%
ASCII
ValueCountFrequency (%)
( 350
30.2%
) 350
30.2%
187
16.1%
S 81
 
7.0%
K 62
 
5.4%
C 13
 
1.1%
O 11
 
0.9%
s 9
 
0.8%
1 9
 
0.8%
2 8
 
0.7%
Other values (29) 78
 
6.7%
None
ValueCountFrequency (%)
5
100.0%

sitepostno
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
지번우편번호
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
지번우편번호 5
 
0.3%

Length

2024-04-16T13:11:44.929787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:45.274297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
지번우편번호 5
 
0.3%
Distinct1361
Distinct (%)93.6%
Missing8
Missing (%)0.5%
Memory size11.6 KiB
2024-04-16T13:11:45.848676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length65
Mean length24.088721
Min length14

Characters and Unicode

Total characters35025
Distinct characters214
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

Unique1283 ?
Unique (%)88.2%

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 1450
 
23.2%
사상구 197
 
3.2%
사하구 151
 
2.4%
부산진구 118
 
1.9%
금정구 111
 
1.8%
남구 99
 
1.6%
기장군 99
 
1.6%
강서구 97
 
1.6%
북구 93
 
1.5%
동래구 90
 
1.4%
Other values (1719) 3736
59.9%
2024-04-16T13:11:46.495544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6237
17.8%
1685
 
4.8%
1647
 
4.7%
1589
 
4.5%
1 1529
 
4.4%
1510
 
4.3%
1487
 
4.2%
1459
 
4.2%
1452
 
4.1%
1442
 
4.1%
Other values (204) 14988
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19763
56.4%
Decimal Number 7312
 
20.9%
Space Separator 6237
 
17.8%
Dash Punctuation 1436
 
4.1%
Other Punctuation 184
 
0.5%
Close Punctuation 38
 
0.1%
Open Punctuation 38
 
0.1%
Uppercase Letter 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1685
 
8.5%
1647
 
8.3%
1589
 
8.0%
1510
 
7.6%
1487
 
7.5%
1459
 
7.4%
1452
 
7.3%
1442
 
7.3%
1431
 
7.2%
385
 
1.9%
Other values (176) 5676
28.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
11.8%
N 2
11.8%
S 2
11.8%
E 2
11.8%
M 2
11.8%
O 1
5.9%
L 1
5.9%
K 1
5.9%
V 1
5.9%
I 1
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
1 1529
20.9%
2 1010
13.8%
3 795
10.9%
4 755
10.3%
5 676
9.2%
8 530
 
7.2%
7 527
 
7.2%
0 523
 
7.2%
6 496
 
6.8%
9 471
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 183
99.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
6237
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1436
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19763
56.4%
Common 15245
43.5%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1685
 
8.5%
1647
 
8.3%
1589
 
8.0%
1510
 
7.6%
1487
 
7.5%
1459
 
7.4%
1452
 
7.3%
1442
 
7.3%
1431
 
7.2%
385
 
1.9%
Other values (176) 5676
28.7%
Common
ValueCountFrequency (%)
6237
40.9%
1 1529
 
10.0%
- 1436
 
9.4%
2 1010
 
6.6%
3 795
 
5.2%
4 755
 
5.0%
5 676
 
4.4%
8 530
 
3.5%
7 527
 
3.5%
0 523
 
3.4%
Other values (6) 1227
 
8.0%
Latin
ValueCountFrequency (%)
A 2
11.8%
N 2
11.8%
S 2
11.8%
E 2
11.8%
M 2
11.8%
O 1
5.9%
L 1
5.9%
K 1
5.9%
V 1
5.9%
I 1
5.9%
Other values (2) 2
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19763
56.4%
ASCII 15262
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6237
40.9%
1 1529
 
10.0%
- 1436
 
9.4%
2 1010
 
6.6%
3 795
 
5.2%
4 755
 
4.9%
5 676
 
4.4%
8 530
 
3.5%
7 527
 
3.5%
0 523
 
3.4%
Other values (18) 1244
 
8.2%
Hangul
ValueCountFrequency (%)
1685
 
8.5%
1647
 
8.3%
1589
 
8.0%
1510
 
7.6%
1487
 
7.5%
1459
 
7.4%
1452
 
7.3%
1442
 
7.3%
1431
 
7.2%
385
 
1.9%
Other values (176) 5676
28.7%

rdnpostno
Categorical

IMBALANCE 

Distinct49
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
48947
1392 
<NA>
 
8
46754
 
4
46996
 
3
46028
 
3
Other values (44)
 
52

Length

Max length7
Median length5
Mean length4.995896
Min length4

Unique

Unique38 ?
Unique (%)2.6%

Sample

1st row48947
2nd row48947
3rd row48947
4th row48947
5th row48947

Common Values

ValueCountFrequency (%)
48947 1392
95.2%
<NA> 8
 
0.5%
46754 4
 
0.3%
46996 3
 
0.2%
46028 3
 
0.2%
46753 3
 
0.2%
49426 3
 
0.2%
46718 2
 
0.1%
46985 2
 
0.1%
48496 2
 
0.1%
Other values (39) 40
 
2.7%

Length

2024-04-16T13:11:46.706134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
48947 1392
95.2%
na 8
 
0.5%
46754 4
 
0.3%
46996 3
 
0.2%
46028 3
 
0.2%
46753 3
 
0.2%
49426 3
 
0.2%
46058 2
 
0.1%
48496 2
 
0.1%
46985 2
 
0.1%
Other values (39) 40
 
2.7%

rdnwhladdr
Text

MISSING 

Distinct1101
Distinct (%)95.2%
Missing306
Missing (%)20.9%
Memory size11.6 KiB
2024-04-16T13:11:47.156866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length25.226644
Min length2

Characters and Unicode

Total characters29162
Distinct characters265
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

Unique1054 ?
Unique (%)91.2%

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 1150
 
19.7%
사상구 145
 
2.5%
부산진구 104
 
1.8%
사하구 104
 
1.8%
금정구 98
 
1.7%
기장군 89
 
1.5%
강서구 87
 
1.5%
해운대구 76
 
1.3%
남구 76
 
1.3%
동래구 74
 
1.3%
Other values (1330) 3830
65.7%
2024-04-16T13:11:47.887128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4920
 
16.9%
1367
 
4.7%
1358
 
4.7%
1313
 
4.5%
1205
 
4.1%
1175
 
4.0%
1152
 
4.0%
1137
 
3.9%
1121
 
3.8%
) 1086
 
3.7%
Other values (255) 13328
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17697
60.7%
Space Separator 4920
 
16.9%
Decimal Number 4142
 
14.2%
Close Punctuation 1086
 
3.7%
Open Punctuation 1086
 
3.7%
Dash Punctuation 127
 
0.4%
Other Punctuation 95
 
0.3%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1367
 
7.7%
1358
 
7.7%
1313
 
7.4%
1205
 
6.8%
1175
 
6.6%
1152
 
6.5%
1137
 
6.4%
1121
 
6.3%
550
 
3.1%
326
 
1.8%
Other values (233) 6993
39.5%
Decimal Number
ValueCountFrequency (%)
1 855
20.6%
2 582
14.1%
3 470
11.3%
4 362
8.7%
5 351
8.5%
7 338
 
8.2%
6 317
 
7.7%
0 315
 
7.6%
8 282
 
6.8%
9 270
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
N 2
22.2%
A 2
22.2%
O 1
11.1%
S 1
11.1%
E 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 94
98.9%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
4920
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1086
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1086
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17697
60.7%
Common 11456
39.3%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1367
 
7.7%
1358
 
7.7%
1313
 
7.4%
1205
 
6.8%
1175
 
6.6%
1152
 
6.5%
1137
 
6.4%
1121
 
6.3%
550
 
3.1%
326
 
1.8%
Other values (233) 6993
39.5%
Common
ValueCountFrequency (%)
4920
42.9%
) 1086
 
9.5%
( 1086
 
9.5%
1 855
 
7.5%
2 582
 
5.1%
3 470
 
4.1%
4 362
 
3.2%
5 351
 
3.1%
7 338
 
3.0%
6 317
 
2.8%
Other values (6) 1089
 
9.5%
Latin
ValueCountFrequency (%)
M 2
22.2%
N 2
22.2%
A 2
22.2%
O 1
11.1%
S 1
11.1%
E 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17697
60.7%
ASCII 11465
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4920
42.9%
) 1086
 
9.5%
( 1086
 
9.5%
1 855
 
7.5%
2 582
 
5.1%
3 470
 
4.1%
4 362
 
3.2%
5 351
 
3.1%
7 338
 
2.9%
6 317
 
2.8%
Other values (12) 1098
 
9.6%
Hangul
ValueCountFrequency (%)
1367
 
7.7%
1358
 
7.7%
1313
 
7.4%
1205
 
6.8%
1175
 
6.6%
1152
 
6.5%
1137
 
6.4%
1121
 
6.3%
550
 
3.1%
326
 
1.8%
Other values (233) 6993
39.5%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct1157
Distinct (%)79.4%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean19960200
Minimum11951106
Maximum20210222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:48.543665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11951106
5-th percentile19760884
Q119921027
median19951010
Q320030721
95-th percentile20133015
Maximum20210222
Range8259116
Interquartile range (IQR)109694

Descriptive statistics

Standard deviation232490.64
Coefficient of variation (CV)0.011647711
Kurtosis968.37463
Mean19960200
Median Absolute Deviation (MAD)50509
Skewness-28.106984
Sum2.9082012 × 1010
Variance5.4051898 × 1010
MonotonicityNot monotonic
2024-04-16T13:11:48.745788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19760513 44
 
3.0%
19940708 19
 
1.3%
19931207 18
 
1.2%
19950915 10
 
0.7%
20031106 7
 
0.5%
19931130 7
 
0.5%
20031104 6
 
0.4%
19941130 5
 
0.3%
19911218 4
 
0.3%
19931213 4
 
0.3%
Other values (1147) 1333
91.2%
(Missing) 5
 
0.3%
ValueCountFrequency (%)
11951106 1
0.1%
19670513 1
0.1%
19680830 1
0.1%
19690520 1
0.1%
19701214 1
0.1%
19710603 1
0.1%
19710609 1
0.1%
19710705 1
0.1%
19710722 1
0.1%
19710924 1
0.1%
ValueCountFrequency (%)
20210222 2
0.1%
20210218 1
0.1%
20210128 1
0.1%
20210107 2
0.1%
20201229 2
0.1%
20201228 2
0.1%
20201222 1
0.1%
20201110 1
0.1%
20201106 2
0.1%
20201028 1
0.1%

dcbymd
Text

MISSING 

Distinct393
Distinct (%)82.6%
Missing986
Missing (%)67.4%
Memory size11.6 KiB
2024-04-16T13:11:49.217277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9579832
Min length4

Characters and Unicode

Total characters3788
Distinct characters14
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

Unique347 ?
Unique (%)72.9%

Sample

1st row20080506
2nd row20160616
3rd row20151126
4th row20101230
5th row20081107
ValueCountFrequency (%)
20111114 11
 
2.3%
20120510 10
 
2.1%
20111031 10
 
2.1%
20120511 8
 
1.7%
폐업일자 5
 
1.1%
20120508 3
 
0.6%
20051125 3
 
0.6%
20120308 3
 
0.6%
20130607 2
 
0.4%
20081110 2
 
0.4%
Other values (383) 419
88.0%
2024-04-16T13:11:49.749407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1240
32.7%
2 795
21.0%
1 790
20.9%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 135
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Other values (4) 20
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3768
99.5%
Other Letter 20
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1240
32.9%
2 795
21.1%
1 790
21.0%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 135
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Other Letter
ValueCountFrequency (%)
5
25.0%
5
25.0%
5
25.0%
5
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3768
99.5%
Hangul 20
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1240
32.9%
2 795
21.1%
1 790
21.0%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 135
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Hangul
ValueCountFrequency (%)
5
25.0%
5
25.0%
5
25.0%
5
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3768
99.5%
Hangul 20
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1240
32.9%
2 795
21.1%
1 790
21.0%
3 177
 
4.7%
8 148
 
3.9%
5 139
 
3.7%
4 135
 
3.6%
9 118
 
3.1%
7 116
 
3.1%
6 110
 
2.9%
Hangul
ValueCountFrequency (%)
5
25.0%
5
25.0%
5
25.0%
5
25.0%

clgstdt
Text

MISSING 

Distinct122
Distinct (%)93.8%
Missing1332
Missing (%)91.1%
Memory size11.6 KiB
2024-04-16T13:11:50.100438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9230769
Min length6

Characters and Unicode

Total characters1030
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

Unique117 ?
Unique (%)90.0%

Sample

1st row20120501
2nd row20121101
3rd row20141121
4th row20141120
5th row20130121
ValueCountFrequency (%)
휴업시작일자 5
 
3.8%
20130301 2
 
1.5%
20100301 2
 
1.5%
20140701 2
 
1.5%
20110101 2
 
1.5%
20150701 1
 
0.8%
20160309 1
 
0.8%
20120901 1
 
0.8%
20140221 1
 
0.8%
20110517 1
 
0.8%
Other values (112) 112
86.2%
2024-04-16T13:11:50.634211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 322
31.3%
1 254
24.7%
2 209
20.3%
3 45
 
4.4%
7 38
 
3.7%
4 34
 
3.3%
5 28
 
2.7%
9 28
 
2.7%
6 24
 
2.3%
8 18
 
1.7%
Other values (6) 30
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
97.1%
Other Letter 30
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 322
32.2%
1 254
25.4%
2 209
20.9%
3 45
 
4.5%
7 38
 
3.8%
4 34
 
3.4%
5 28
 
2.8%
9 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%
Other Letter
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
97.1%
Hangul 30
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 322
32.2%
1 254
25.4%
2 209
20.9%
3 45
 
4.5%
7 38
 
3.8%
4 34
 
3.4%
5 28
 
2.8%
9 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%
Hangul
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
97.1%
Hangul 30
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 322
32.2%
1 254
25.4%
2 209
20.9%
3 45
 
4.5%
7 38
 
3.8%
4 34
 
3.4%
5 28
 
2.8%
9 28
 
2.8%
6 24
 
2.4%
8 18
 
1.8%
Hangul
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

clgenddt
Text

MISSING 

Distinct110
Distinct (%)84.6%
Missing1332
Missing (%)91.1%
Memory size11.6 KiB
2024-04-16T13:11:50.938996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9230769
Min length6

Characters and Unicode

Total characters1030
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

Unique95 ?
Unique (%)73.1%

Sample

1st row20121231
2nd row20121130
3rd row20150228
4th row20150920
5th row20140120
ValueCountFrequency (%)
휴업종료일자 5
 
3.8%
20131231 3
 
2.3%
20120430 3
 
2.3%
20170630 2
 
1.5%
20121130 2
 
1.5%
20100831 2
 
1.5%
20151231 2
 
1.5%
20131130 2
 
1.5%
20160630 2
 
1.5%
20091231 2
 
1.5%
Other values (100) 105
80.8%
2024-04-16T13:11:51.483351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 301
29.2%
1 241
23.4%
2 195
18.9%
3 97
 
9.4%
5 38
 
3.7%
8 32
 
3.1%
4 28
 
2.7%
6 25
 
2.4%
9 23
 
2.2%
7 20
 
1.9%
Other values (6) 30
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
97.1%
Other Letter 30
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 301
30.1%
1 241
24.1%
2 195
19.5%
3 97
 
9.7%
5 38
 
3.8%
8 32
 
3.2%
4 28
 
2.8%
6 25
 
2.5%
9 23
 
2.3%
7 20
 
2.0%
Other Letter
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
97.1%
Hangul 30
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 301
30.1%
1 241
24.1%
2 195
19.5%
3 97
 
9.7%
5 38
 
3.8%
8 32
 
3.2%
4 28
 
2.8%
6 25
 
2.5%
9 23
 
2.3%
7 20
 
2.0%
Hangul
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
97.1%
Hangul 30
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 301
30.1%
1 241
24.1%
2 195
19.5%
3 97
 
9.7%
5 38
 
3.8%
8 32
 
3.2%
4 28
 
2.8%
6 25
 
2.5%
9 23
 
2.3%
7 20
 
2.0%
Hangul
ValueCountFrequency (%)
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%
5
16.7%

ropnymd
Text

MISSING 

Distinct69
Distinct (%)93.2%
Missing1388
Missing (%)94.9%
Memory size11.6 KiB
2024-04-16T13:11:51.758417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.7972973
Min length5

Characters and Unicode

Total characters577
Distinct characters15
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

Unique67 ?
Unique (%)90.5%

Sample

1st row20130204
2nd row20121227
3rd row20120806
4th row20140925
5th row20150302
ValueCountFrequency (%)
재개업일자 5
 
6.8%
20131101 2
 
2.7%
20151230 1
 
1.4%
20111216 1
 
1.4%
20150921 1
 
1.4%
20150213 1
 
1.4%
20121227 1
 
1.4%
20160630 1
 
1.4%
20170915 1
 
1.4%
20131223 1
 
1.4%
Other values (59) 59
79.7%
2024-04-16T13:11:52.285978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 161
27.9%
1 146
25.3%
2 116
20.1%
3 29
 
5.0%
7 21
 
3.6%
5 21
 
3.6%
6 21
 
3.6%
4 13
 
2.3%
9 13
 
2.3%
8 11
 
1.9%
Other values (5) 25
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 552
95.7%
Other Letter 25
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 161
29.2%
1 146
26.4%
2 116
21.0%
3 29
 
5.3%
7 21
 
3.8%
5 21
 
3.8%
6 21
 
3.8%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%
Other Letter
ValueCountFrequency (%)
5
20.0%
5
20.0%
5
20.0%
5
20.0%
5
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552
95.7%
Hangul 25
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 161
29.2%
1 146
26.4%
2 116
21.0%
3 29
 
5.3%
7 21
 
3.8%
5 21
 
3.8%
6 21
 
3.8%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%
Hangul
ValueCountFrequency (%)
5
20.0%
5
20.0%
5
20.0%
5
20.0%
5
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
95.7%
Hangul 25
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 161
29.2%
1 146
26.4%
2 116
21.0%
3 29
 
5.3%
7 21
 
3.8%
5 21
 
3.8%
6 21
 
3.8%
4 13
 
2.4%
9 13
 
2.4%
8 11
 
2.0%
Hangul
ValueCountFrequency (%)
5
20.0%
5
20.0%
5
20.0%
5
20.0%
5
20.0%

trdstatenm
Categorical

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
03
728 
01
396 
07
202 
06
 
49
영업/정상
 
48
Other values (5)
 
39

Length

Max length5
Median length2
Mean length2.1053352
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
03 728
49.8%
01 396
27.1%
07 202
 
13.8%
06 49
 
3.4%
영업/정상 48
 
3.3%
02 17
 
1.2%
05 11
 
0.8%
<NA> 5
 
0.3%
휴업 3
 
0.2%
폐업 3
 
0.2%

Length

2024-04-16T13:11:52.454988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:52.619331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03 728
49.8%
01 396
27.1%
07 202
 
13.8%
06 49
 
3.4%
영업/정상 48
 
3.3%
02 17
 
1.2%
05 11
 
0.8%
na 5
 
0.3%
휴업 3
 
0.2%
폐업 3
 
0.2%

dtlstatenm
Categorical

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
폐지
730 
신규등록
397 
영업개시
202 
휴지사업재개
 
49
영업중
 
28
Other values (5)
 
56

Length

Max length6
Median length4
Mean length3.0492476
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐지 730
49.9%
신규등록 397
27.2%
영업개시 202
 
13.8%
휴지사업재개 49
 
3.4%
영업중 28
 
1.9%
<NA> 18
 
1.2%
등록취소 17
 
1.2%
사업휴지 11
 
0.8%
휴업처리 9
 
0.6%
폐업처리 1
 
0.1%

Length

2024-04-16T13:11:52.812684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:52.986114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 730
49.9%
신규등록 397
27.2%
영업개시 202
 
13.8%
휴지사업재개 49
 
3.4%
영업중 28
 
1.9%
na 18
 
1.2%
등록취소 17
 
1.2%
사업휴지 11
 
0.8%
휴업처리 9
 
0.6%
폐업처리 1
 
0.1%

x
Real number (ℝ)

MISSING 

Distinct1127
Distinct (%)92.3%
Missing241
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean386955.57
Minimum196927.02
Maximum414452.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:53.162134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196927.02
5-th percentile376612.08
Q1381613.33
median387533.53
Q3391323.93
95-th percentile401475.67
Maximum414452.29
Range217525.27
Interquartile range (IQR)9710.6081

Descriptive statistics

Standard deviation10592.081
Coefficient of variation (CV)0.027372862
Kurtosis164.04484
Mean386955.57
Median Absolute Deviation (MAD)4742.9548
Skewness-9.2170099
Sum4.7247275 × 108
Variance1.1219219 × 108
MonotonicityNot monotonic
2024-04-16T13:11:53.326434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380555.507067 7
 
0.5%
380466.311026 4
 
0.3%
380049.564034 4
 
0.3%
401610.251182 4
 
0.3%
401260.939933773 4
 
0.3%
378941.360932275 3
 
0.2%
380601.909148 3
 
0.2%
380698.816484 3
 
0.2%
387026.846462 3
 
0.2%
379230.336838 3
 
0.2%
Other values (1117) 1183
80.9%
(Missing) 241
 
16.5%
ValueCountFrequency (%)
196927.0175008227 1
0.1%
199437.033749 1
0.1%
364854.947557 1
0.1%
365157.276407 1
0.1%
365455.524851569 1
0.1%
365782.797443 1
0.1%
365838.0 1
0.1%
366339.309102189 1
0.1%
367081.793936 1
0.1%
367285.588628 1
0.1%
ValueCountFrequency (%)
414452.291392 1
0.1%
408081.163488 1
0.1%
405441.683435 1
0.1%
405279.50792 1
0.1%
405010.191484 1
0.1%
405005.945957 1
0.1%
404945.002048 1
0.1%
404894.66518892 1
0.1%
404845.005058575 2
0.1%
404714.408108 1
0.1%

y
Real number (ℝ)

MISSING 

Distinct1127
Distinct (%)92.3%
Missing241
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean188243.37
Minimum171205.31
Maximum444923.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:53.659360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171205.31
5-th percentile177962.49
Q1183183.3
median187347.19
Q3191895.74
95-th percentile198948.29
Maximum444923.62
Range273718.31
Interquartile range (IQR)8712.4421

Descriptive statistics

Standard deviation12229.392
Coefficient of variation (CV)0.064965859
Kurtosis262.59832
Mean188243.37
Median Absolute Deviation (MAD)4343.2363
Skewness13.502953
Sum2.2984516 × 108
Variance1.4955804 × 108
MonotonicityNot monotonic
2024-04-16T13:11:53.826557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185892.189846 7
 
0.5%
186728.833884 4
 
0.3%
192699.524522 4
 
0.3%
197494.09608 4
 
0.3%
190226.561613539 4
 
0.3%
180290.445444695 3
 
0.2%
185931.104017 3
 
0.2%
184448.503185 3
 
0.2%
184926.539418 3
 
0.2%
178079.690806 3
 
0.2%
Other values (1117) 1183
80.9%
(Missing) 241
 
16.5%
ValueCountFrequency (%)
171205.308829 1
0.1%
171756.862255 1
0.1%
174551.635641826 1
0.1%
174566.274611 1
0.1%
174765.307900471 1
0.1%
174834.884307 1
0.1%
174905.004109 2
0.1%
174952.642268 1
0.1%
174984.169803 2
0.1%
174986.670647 1
0.1%
ValueCountFrequency (%)
444923.620551 1
0.1%
417522.3015143956 1
0.1%
288208.11694 1
0.1%
212131.011122 1
0.1%
211893.965608 1
0.1%
211392.6938 1
0.1%
210713.627656158 1
0.1%
210517.397739759 2
0.1%
210019.846393 1
0.1%
208445.06831 1
0.1%

lastmodts
Real number (ℝ)

Distinct1414
Distinct (%)97.0%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean2.0135276 × 1013
Minimum2.0000614 × 1013
Maximum2.0210222 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2024-04-16T13:11:54.113204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0000614 × 1013
5-th percentile2.0060313 × 1013
Q12.0091222 × 1013
median2.0151015 × 1013
Q32.018022 × 1013
95-th percentile2.0180825 × 1013
Maximum2.0210222 × 1013
Range2.0960816 × 1011
Interquartile range (IQR)8.899802 × 1010

Descriptive statistics

Standard deviation4.6849049 × 1010
Coefficient of variation (CV)0.002326715
Kurtosis-0.68792812
Mean2.0135276 × 1013
Median Absolute Deviation (MAD)2.9687013 × 1010
Skewness-0.64094357
Sum2.9337098 × 1016
Variance2.1948334 × 1021
MonotonicityNot monotonic
2024-04-16T13:11:54.427394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031106000000 6
 
0.4%
20060123000000 5
 
0.3%
20000810000000 5
 
0.3%
20060313000000 3
 
0.2%
20191004134109 3
 
0.2%
20070404000000 3
 
0.2%
20190927153558 3
 
0.2%
20061116000000 3
 
0.2%
20040623000000 3
 
0.2%
20000811000000 3
 
0.2%
Other values (1404) 1420
97.1%
(Missing) 5
 
0.3%
ValueCountFrequency (%)
20000614000000 1
 
0.1%
20000809000000 1
 
0.1%
20000810000000 5
0.3%
20000811000000 3
0.2%
20020624000000 1
 
0.1%
20020830000000 2
 
0.1%
20020924000000 1
 
0.1%
20021102000000 1
 
0.1%
20021109000000 2
 
0.1%
20021113000000 1
 
0.1%
ValueCountFrequency (%)
20210222164953 1
0.1%
20210222162221 1
0.1%
20210218102518 1
0.1%
20210204101623 1
0.1%
20210128154358 1
0.1%
20210110174725 2
0.1%
20201229180303 1
0.1%
20201229175241 1
0.1%
20201228131913 1
0.1%
20201228131853 1
0.1%

uptaenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
일반판매소
725 
주유소
609 
용제판매소
 
69
<NA>
 
23
제조
 
22
Other values (5)
 
14

Length

Max length19
Median length5
Mean length4.1395349
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반판매소 725
49.6%
주유소 609
41.7%
용제판매소 69
 
4.7%
<NA> 23
 
1.6%
제조 22
 
1.5%
저장소 6
 
0.4%
2021-03-01 05:14:03 4
 
0.3%
항공유판매소 2
 
0.1%
부생연료유판매소 1
 
0.1%
업태구분명 1
 
0.1%

Length

2024-04-16T13:11:54.644524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:54.883182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반판매소 725
49.5%
주유소 609
41.5%
용제판매소 69
 
4.7%
na 23
 
1.6%
제조 22
 
1.5%
저장소 6
 
0.4%
2021-03-01 4
 
0.3%
05:14:03 4
 
0.3%
항공유판매소 2
 
0.1%
부생연료유판매소 1
 
0.1%

sitetel
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
051-123-1234
1437 
<NA>
 
22
전화번호
 
3

Length

Max length12
Median length12
Mean length11.863201
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 1437
98.3%
<NA> 22
 
1.5%
전화번호 3
 
0.2%

Length

2024-04-16T13:11:55.124630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:55.345901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 1437
98.3%
na 22
 
1.5%
전화번호 3
 
0.2%

gaspdtsortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
가스용품종류명
 
5

Length

Max length7
Median length4
Mean length4.0102599
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> 1457
99.7%
가스용품종류명 5
 
0.3%

Length

2024-04-16T13:11:55.576617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:55.842987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
가스용품종류명 5
 
0.3%

gassortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
가스종류명
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
가스종류명 5
 
0.3%

Length

2024-04-16T13:11:56.061971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:56.183204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
가스종류명 5
 
0.3%

upchnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
거래처
 
5

Length

Max length4
Median length4
Mean length3.99658
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> 1457
99.7%
거래처 5
 
0.3%

Length

2024-04-16T13:11:56.449066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:56.693808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
거래처 5
 
0.3%

suprulesctn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
공급규정내용
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
공급규정내용 5
 
0.3%

Length

2024-04-16T13:11:56.956656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:57.222063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
공급규정내용 5
 
0.3%

spyvolt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
공급전압
 
5

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> 1457
99.7%
공급전압 5
 
0.3%

Length

2024-04-16T13:11:57.480942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:57.692924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
공급전압 5
 
0.3%

ltchgcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
길이변경내용
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
길이변경내용 5
 
0.3%

Length

2024-04-16T13:11:57.977180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:58.235811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
길이변경내용 5
 
0.3%

exmran
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
면제범위
 
5

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> 1457
99.7%
면제범위 5
 
0.3%

Length

2024-04-16T13:11:58.489086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:58.726012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
면제범위 5
 
0.3%

prdsiz
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
물품규격
 
5

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> 1457
99.7%
물품규격 5
 
0.3%

Length

2024-04-16T13:11:58.932548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:59.069300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
물품규격 5
 
0.3%

baelt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
배관길이
 
5

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> 1457
99.7%
배관길이 5
 
0.3%

Length

2024-04-16T13:11:59.393129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:11:59.645651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
배관길이 5
 
0.3%

baeesbplc
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
배관설치장소
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
배관설치장소 5
 
0.3%

Length

2024-04-16T13:11:59.913005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:00.034583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
배관설치장소 5
 
0.3%

offtelno
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
051-123-1234
1437 
<NA>
 
22
사무소전화번호
 
3

Length

Max length12
Median length12
Mean length11.869357
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 1437
98.3%
<NA> 22
 
1.5%
사무소전화번호 3
 
0.2%

Length

2024-04-16T13:12:00.187455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:00.340683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 1437
98.3%
na 22
 
1.5%
사무소전화번호 3
 
0.2%

ofear
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
사무실면적
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
사무실면적 5
 
0.3%

Length

2024-04-16T13:12:00.931454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:01.057734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
사무실면적 5
 
0.3%

bsnsopeningprearrymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
사업개시예정일자
 
5

Length

Max length8
Median length4
Mean length4.0136799
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> 1457
99.7%
사업개시예정일자 5
 
0.3%

Length

2024-04-16T13:12:01.211026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:01.345764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
사업개시예정일자 5
 
0.3%

wrkpgrdsrvsenm
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1454 
사업장부지용도구분명
 
5
기타
 
3

Length

Max length10
Median length4
Mean length4.0164159
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> 1454
99.5%
사업장부지용도구분명 5
 
0.3%
기타 3
 
0.2%

Length

2024-04-16T13:12:01.494690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:01.622614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1454
99.5%
사업장부지용도구분명 5
 
0.3%
기타 3
 
0.2%

wrkptelno
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
사업장전화번호
 
5

Length

Max length7
Median length4
Mean length4.0102599
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> 1457
99.7%
사업장전화번호 5
 
0.3%

Length

2024-04-16T13:12:01.779160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:01.910207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
사업장전화번호 5
 
0.3%

useobj
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1435 
의료용
 
13
사용목적
 
4
절단용
 
2
Ru chemical 제조
 
2
Other values (6)
 
6

Length

Max length14
Median length4
Mean length4.0150479
Min length3

Unique

Unique6 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1435
98.2%
의료용 13
 
0.9%
사용목적 4
 
0.3%
절단용 2
 
0.1%
Ru chemical 제조 2
 
0.1%
의료용(호흡용) 1
 
0.1%
의료용 산소 1
 
0.1%
의료용 산소공급용 1
 
0.1%
절단작업용 1
 
0.1%
용접 및 절단 1
 
0.1%

Length

2024-04-16T13:12:02.071938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1435
97.6%
의료용 15
 
1.0%
사용목적 4
 
0.3%
절단용 2
 
0.1%
ru 2
 
0.1%
chemical 2
 
0.1%
제조 2
 
0.1%
용접 2
 
0.1%
의료용(호흡용 1
 
0.1%
산소 1
 
0.1%
Other values (5) 5
 
0.3%

usemet
Text

MISSING 

Distinct15
Distinct (%)55.6%
Missing1435
Missing (%)98.2%
Memory size11.6 KiB
2024-04-16T13:12:02.292886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length7.962963
Min length2

Characters and Unicode

Total characters215
Distinct characters61
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)33.3%

Sample

1st row용기보관실
2nd row액화산소 용기보관
3rd row의료용 액화 및 압축 산소
4th row의료용
5th row의료용
ValueCountFrequency (%)
의료용 5
 
8.6%
산소 4
 
6.9%
사용 4
 
6.9%
사용방법 4
 
6.9%
액화산소의 3
 
5.2%
경우 3
 
5.2%
배관 3
 
5.2%
연결하여 3
 
5.2%
용기보관 2
 
3.4%
2
 
3.4%
Other values (21) 25
43.1%
2024-04-16T13:12:02.707144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
14.4%
21
 
9.8%
10
 
4.7%
10
 
4.7%
10
 
4.7%
9
 
4.2%
7
 
3.3%
7
 
3.3%
5
 
2.3%
5
 
2.3%
Other values (51) 100
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
75.3%
Space Separator 31
 
14.4%
Lowercase Letter 18
 
8.4%
Uppercase Letter 2
 
0.9%
Other Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21
 
13.0%
10
 
6.2%
10
 
6.2%
10
 
6.2%
9
 
5.6%
7
 
4.3%
7
 
4.3%
5
 
3.1%
5
 
3.1%
4
 
2.5%
Other values (39) 74
45.7%
Lowercase Letter
ValueCountFrequency (%)
c 4
22.2%
u 2
11.1%
h 2
11.1%
a 2
11.1%
e 2
11.1%
m 2
11.1%
i 2
11.1%
l 2
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
75.3%
Common 33
 
15.3%
Latin 20
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21
 
13.0%
10
 
6.2%
10
 
6.2%
10
 
6.2%
9
 
5.6%
7
 
4.3%
7
 
4.3%
5
 
3.1%
5
 
3.1%
4
 
2.5%
Other values (39) 74
45.7%
Latin
ValueCountFrequency (%)
c 4
20.0%
u 2
10.0%
R 2
10.0%
h 2
10.0%
a 2
10.0%
e 2
10.0%
m 2
10.0%
i 2
10.0%
l 2
10.0%
Common
ValueCountFrequency (%)
31
93.9%
/ 1
 
3.0%
, 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
75.3%
ASCII 53
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
58.5%
c 4
 
7.5%
u 2
 
3.8%
R 2
 
3.8%
h 2
 
3.8%
a 2
 
3.8%
e 2
 
3.8%
m 2
 
3.8%
i 2
 
3.8%
l 2
 
3.8%
Other values (2) 2
 
3.8%
Hangul
ValueCountFrequency (%)
21
 
13.0%
10
 
6.2%
10
 
6.2%
10
 
6.2%
9
 
5.6%
7
 
4.3%
7
 
4.3%
5
 
3.1%
5
 
3.1%
4
 
2.5%
Other values (39) 74
45.7%

dsnrspvsnsortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
설계감리업종류명
 
5

Length

Max length8
Median length4
Mean length4.0136799
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> 1457
99.7%
설계감리업종류명 5
 
0.3%

Length

2024-04-16T13:12:02.881530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:03.020100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
설계감리업종류명 5
 
0.3%

equnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
설비명
 
5

Length

Max length4
Median length4
Mean length3.99658
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> 1457
99.7%
설비명 5
 
0.3%

Length

2024-04-16T13:12:03.148322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:03.280580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
설비명 5
 
0.3%

equcap
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
설비용량
 
5

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> 1457
99.7%
설비용량 5
 
0.3%

Length

2024-04-16T13:12:03.424270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:03.558120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
설비용량 5
 
0.3%

stanm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
소속국가명
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
소속국가명 5
 
0.3%

Length

2024-04-16T13:12:03.718150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:03.862712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
소속국가명 5
 
0.3%

sygrglstcnt
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing1439
Missing (%)98.4%
Memory size11.6 KiB
2024-04-16T13:12:04.041031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.6086957
Min length1

Characters and Unicode

Total characters60
Distinct characters12
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

Unique8 ?
Unique (%)34.8%

Sample

1st row135
2nd row400
3rd row650
4th row135
5th row100
ValueCountFrequency (%)
0 5
21.7%
수용정원수 4
17.4%
135 2
 
8.7%
100 2
 
8.7%
230 2
 
8.7%
400 1
 
4.3%
650 1
 
4.3%
172 1
 
4.3%
2 1
 
4.3%
6 1
 
4.3%
Other values (3) 3
13.0%
2024-04-16T13:12:04.461299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
25.0%
8
13.3%
2 6
 
10.0%
1 5
 
8.3%
4
 
6.7%
4
 
6.7%
4
 
6.7%
3 4
 
6.7%
5 3
 
5.0%
4 3
 
5.0%
Other values (2) 4
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
66.7%
Other Letter 20
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
37.5%
2 6
 
15.0%
1 5
 
12.5%
3 4
 
10.0%
5 3
 
7.5%
4 3
 
7.5%
6 2
 
5.0%
7 2
 
5.0%
Other Letter
ValueCountFrequency (%)
8
40.0%
4
20.0%
4
20.0%
4
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40
66.7%
Hangul 20
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
37.5%
2 6
 
15.0%
1 5
 
12.5%
3 4
 
10.0%
5 3
 
7.5%
4 3
 
7.5%
6 2
 
5.0%
7 2
 
5.0%
Hangul
ValueCountFrequency (%)
8
40.0%
4
20.0%
4
20.0%
4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
66.7%
Hangul 20
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
37.5%
2 6
 
15.0%
1 5
 
12.5%
3 4
 
10.0%
5 3
 
7.5%
4 3
 
7.5%
6 2
 
5.0%
7 2
 
5.0%
Hangul
ValueCountFrequency (%)
8
40.0%
4
20.0%
4
20.0%
4
20.0%

faciluseyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
 
5

Length

Max length4
Median length4
Mean length3.9897401
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> 1457
99.7%
5
 
0.3%

Length

2024-04-16T13:12:04.666753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:04.915021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
5
 
0.3%

realcapt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
실질자본금
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
실질자본금 5
 
0.3%

Length

2024-04-16T13:12:05.102304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:05.301389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
실질자본금 5
 
0.3%

cobgbnnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
업종구분명
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
업종구분명 5
 
0.3%

Length

2024-04-16T13:12:05.498986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:05.667552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
업종구분명 5
 
0.3%

instrstoroomar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
용기저장실면적
 
5

Length

Max length7
Median length4
Mean length4.0102599
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> 1457
99.7%
용기저장실면적 5
 
0.3%

Length

2024-04-16T13:12:05.880296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:06.125685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
용기저장실면적 5
 
0.3%

motpowersortnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
원동력종류명
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
원동력종류명 5
 
0.3%

Length

2024-04-16T13:12:06.359881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:06.577139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
원동력종류명 5
 
0.3%

bmonuseqy
Text

MISSING 

Distinct14
Distinct (%)60.9%
Missing1439
Missing (%)98.4%
Memory size11.6 KiB
2024-04-16T13:12:06.785674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.4782609
Min length2

Characters and Unicode

Total characters80
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

Unique9 ?
Unique (%)39.1%

Sample

1st row760
2nd row2000
3rd row1600
4th row3000
5th row1000
ValueCountFrequency (%)
월사용량 4
17.4%
1000 3
13.0%
650 3
13.0%
3000 2
8.7%
336 2
8.7%
760 1
 
4.3%
2000 1
 
4.3%
1600 1
 
4.3%
672 1
 
4.3%
1360 1
 
4.3%
Other values (4) 4
17.4%
2024-04-16T13:12:07.352075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29
36.2%
6 9
 
11.2%
3 7
 
8.8%
1 6
 
7.5%
5 5
 
6.2%
4
 
5.0%
4
 
5.0%
4
 
5.0%
4
 
5.0%
2 3
 
3.8%
Other values (3) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
80.0%
Other Letter 16
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29
45.3%
6 9
 
14.1%
3 7
 
10.9%
1 6
 
9.4%
5 5
 
7.8%
2 3
 
4.7%
7 2
 
3.1%
8 2
 
3.1%
4 1
 
1.6%
Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
4
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
80.0%
Hangul 16
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29
45.3%
6 9
 
14.1%
3 7
 
10.9%
1 6
 
9.4%
5 5
 
7.8%
2 3
 
4.7%
7 2
 
3.1%
8 2
 
3.1%
4 1
 
1.6%
Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
80.0%
Hangul 16
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29
45.3%
6 9
 
14.1%
3 7
 
10.9%
1 6
 
9.4%
5 5
 
7.8%
2 3
 
4.7%
7 2
 
3.1%
8 2
 
3.1%
4 1
 
1.6%
Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
4
25.0%

cyprpdtfacil
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
윤전기생산시설
 
5

Length

Max length7
Median length4
Mean length4.0102599
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> 1457
99.7%
윤전기생산시설 5
 
0.3%

Length

2024-04-16T13:12:07.649438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:07.864655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
윤전기생산시설 5
 
0.3%

capt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
자본금
 
5

Length

Max length4
Median length4
Mean length3.99658
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> 1457
99.7%
자본금 5
 
0.3%

Length

2024-04-16T13:12:08.101782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:08.351985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
자본금 5
 
0.3%

saveequloc
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
저장설비위치
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
저장설비위치 5
 
0.3%

Length

2024-04-16T13:12:08.581439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:08.820548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
저장설비위치 5
 
0.3%

scoalar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
저탄장면적
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
저탄장면적 5
 
0.3%

Length

2024-04-16T13:12:09.075129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:09.280625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
저탄장면적 5
 
0.3%

permcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
전기사업허가조건
 
5

Length

Max length8
Median length4
Mean length4.0136799
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> 1457
99.7%
전기사업허가조건 5
 
0.3%

Length

2024-04-16T13:12:09.537171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:09.765947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
전기사업허가조건 5
 
0.3%

prdsenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1436 
냉동
 
15
충전
 
5
제조구분명
 
4
일반
 
2

Length

Max length5
Median length4
Mean length3.9726402
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> 1436
98.2%
냉동 15
 
1.0%
충전 5
 
0.3%
제조구분명 4
 
0.3%
일반 2
 
0.1%

Length

2024-04-16T13:12:10.040859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:10.299376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1436
98.2%
냉동 15
 
1.0%
충전 5
 
0.3%
제조구분명 4
 
0.3%
일반 2
 
0.1%

frequ
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
주파수
 
5

Length

Max length4
Median length4
Mean length3.99658
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> 1457
99.7%
주파수 5
 
0.3%

Length

2024-04-16T13:12:10.563238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:10.814914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
주파수 5
 
0.3%

cgpar
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
차고지면적
 
5

Length

Max length5
Median length4
Mean length4.00342
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> 1457
99.7%
차고지면적 5
 
0.3%

Length

2024-04-16T13:12:11.069956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:11.359001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
차고지면적 5
 
0.3%

rlservlnennm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
철도인입선유무명
 
5

Length

Max length8
Median length4
Mean length4.0136799
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> 1457
99.7%
철도인입선유무명 5
 
0.3%

Length

2024-04-16T13:12:11.670971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:11.937195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
철도인입선유무명 5
 
0.3%

tregascap
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1457 
취급가스용량
 
5

Length

Max length6
Median length4
Mean length4.0068399
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> 1457
99.7%
취급가스용량 5
 
0.3%

Length

2024-04-16T13:12:12.259350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:12:12.555815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1457
99.7%
취급가스용량 5
 
0.3%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing9
Missing (%)0.6%
Memory size11.6 KiB
Minimum2021-03-01 05:14:03
Maximum2021-03-01 05:14:03
2024-04-16T13:12:12.788326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:12:13.018459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm
013250000198732500140149990409_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>01신규등록385717.11248180436.91578320171121112913주유소051-123-1234<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>2021-03-01 05:14:03
123250000197132500140120012809_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>2021-03-01 05:14:03
233250000197132500140120012809_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>2021-03-01 05:14:03
343250000197632500140149990409_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>03폐지385732.615552180996.84119420160616152334주유소051-123-1234<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>2021-03-01 05:14:03
453250000197632500140149990409_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>01신규등록385535.932632181386.83062320171121112951주유소051-123-1234<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>2021-03-01 05:14:03
563250000198532500140149990409_28_08_PI2018-08-31 23:59:59.0<NA>남포주유소<NA>부산광역시 중구 부평동4가 32-2, 33, 34-6번지48947부산광역시 중구 보수대로 62 (부평동4가)198511112015112620120501201212312013020403폐지384385.563699180259.73166620151126164419주유소051-123-1234<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>2021-03-01 05:14:03
673250000199632500140120012809_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>01신규등록384822.485081180570.89765920171121113216일반판매소051-123-1234<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>2021-03-01 05:14:03
783250000199932500140120012809_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>2021-03-01 05:14:03
893250000199932500140120012809_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>2021-03-01 05:14:03
9103250000200032500830149990409_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>01신규등록385748.217464180936.60088220171122112647용제판매소051-123-1234<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>2021-03-01 05:14:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm
145276283360000202033601451219993609_28_14_PI2020-12-31 00:23:05.0특정고압가스업(주)웨스코일렉트로드<NA>부산광역시 강서구 송정동 1567-746753부산광역시 강서구 녹산산단261로39번길 2 (송정동)20201229<NA><NA><NA><NA>휴업휴업처리368241.740656178629.71874420201229175241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Ru chemical 제조Ru chemical 제조<NA><NA><NA><NA>20<NA><NA><NA><NA><NA>15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:14:03
145376333360000202033601451219993609_28_14_PI2020-12-31 00:23:05.0특정고압가스업(주)웨스코일렉트로드<NA>부산광역시 강서구 송정동 1567-746753부산광역시 강서구 녹산산단261로39번길 2 (송정동)2020122920201229<NA><NA><NA>폐업폐업처리368241.740656178629.71874420201229180303<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Ru chemical 제조Ru chemical 제조<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1454---새올대장 오류로 재등록--<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>
1455(2020-3360145-12-2-00004호)<NA><NA><NA><NA>20<NA><NA><NA><NA><NA>15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 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>
145676733400000202134001090149990409_28_08_PU2021-01-12 02:40:00.0석유판매업월드주유소<NA>부산광역시 기장군 기장읍 서부리 429 월드주유소46058부산광역시 기장군 기장읍 반송로 1559, 월드주유소2021010720210108<NA><NA><NA>폐업폐지401101.655236196595.9164820210110174725주유소<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>2021-03-01 05:14:03
145776803400000202134001090149990409_28_08_PU2021-01-12 02:40:00.0석유판매업월드주유소<NA>부산광역시 기장군 기장읍 서부리 429 월드주유소46058부산광역시 기장군 기장읍 반송로 1559, 월드주유소2021010720210108<NA><NA><NA>폐업폐지401101.655236196595.9164820210110174725주유소<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>2021-03-01 05:14:03
145877873320000202133201070220006409_28_05_PI2021-01-30 00:23:03.0고압가스업부산광역시소방학교<NA>부산광역시 북구 금곡동 1910 부산광역시종합연수원46510부산광역시 북구 효열로 256, 부산광역시종합연수원 (금곡동)20210128<NA><NA><NA><NA>영업/정상영업중383904.330877198402.36246320210128154358제조<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>충전<NA><NA><NA><NA>2021-03-01 05:14:03
145978823390000202133901090209996809_28_05_PI2021-02-20 00:23:02.0고압가스업(주)부성철강산업지번우편번호부산광역시 사상구 감전동 948-8도로명우편번호도로명주소20210218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중379834.799717185012.31984120210218102518저장소전화번호가스용품종류명가스종류명거래처공급규정내용공급전압길이변경내용면제범위물품규격배관길이배관설치장소사무소전화번호사무실면적사업개시예정일자사업장부지용도구분명사업장전화번호사용목적사용방법설계감리업종류명설비명설비용량소속국가명수용정원수실질자본금업종구분명용기저장실면적원동력종류명월사용량윤전기생산시설자본금저장설비위치저탄장면적전기사업허가조건제조구분명주파수차고지면적철도인입선유무명취급가스용량2021-03-01 05:14:03
146078953360000202133601450209996809_28_05_PI2021-02-24 00:23:01.0고압가스업삼성전기(주) 부산사업장<NA>부산광역시 강서구 송정동 1623-246754부산광역시 강서구 녹산산업중로 333 (송정동)20210222<NA><NA><NA><NA>영업/정상영업중369169.33014178979.3199420210222162221제조<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>2021-03-01 05:14:03
146178983360000202133601450220006409_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/정상영업중365455.524852185355.8980520210222164953제조<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>2021-03-01 05:14:03

Duplicate rows

Most frequently occurring

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelgaspdtsortnmgassortnmupchnmsuprulesctnspyvoltltchgcnexmranprdsizbaeltbaeesbplcofftelnoofearbsnsopeningprearrymdwrkpgrdsrvsenmwrkptelnouseobjusemetdsnrspvsnsortnmequnmequcapstanmsygrglstcntfaciluseynrealcaptcobgbnnminstrstoroomarmotpowersortnmbmonuseqycyprpdtfacilcaptsaveequlocscoalarpermcnprdsenmfrequcgparrlservlnennmtregascaplast_load_dttm# duplicates
0압축산소의 경우 이동식<NA><NA><NA><NA>170<NA><NA><NA><NA><NA>500<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 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