Overview

Dataset statistics

Number of variables44
Number of observations5193
Missing cells5101
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 MiB
Average record size in memory357.0 B

Variable types

Numeric5
Text10
Categorical27
DateTime1
Boolean1

Alerts

opnsvcid is highly imbalanced (74.7%)Imbalance
clgstdt is highly imbalanced (80.2%)Imbalance
clgenddt is highly imbalanced (80.2%)Imbalance
ropnymd is highly imbalanced (80.2%)Imbalance
bdngownsenm is highly imbalanced (70.2%)Imbalance
fctyowkepcnt is highly imbalanced (60.5%)Imbalance
fctypdtjobepcnt is highly imbalanced (60.5%)Imbalance
fctysiljobepcnt is highly imbalanced (60.5%)Imbalance
wtrsplyfacilsenm is highly imbalanced (56.4%)Imbalance
maneipcnt is highly imbalanced (56.3%)Imbalance
multusnupsoyn is highly imbalanced (98.9%)Imbalance
lvsenm is highly imbalanced (58.7%)Imbalance
hoffepcnt is highly imbalanced (65.8%)Imbalance
wmeipcnt is highly imbalanced (76.4%)Imbalance
trdpjubnsenm is highly imbalanced (66.1%)Imbalance
jtupsomainedf is highly imbalanced (80.2%)Imbalance
jtupsoasgnno is highly imbalanced (80.2%)Imbalance
totepnum is highly imbalanced (60.6%)Imbalance
homepage is highly imbalanced (80.2%)Imbalance
last_load_dttm is highly imbalanced (56.4%)Imbalance
sitepostno has 181 (3.5%) missing valuesMissing
rdnwhladdr has 848 (16.3%) missing valuesMissing
dcbymd has 3342 (64.4%) missing valuesMissing
x has 218 (4.2%) missing valuesMissing
y has 218 (4.2%) missing valuesMissing
sitetel has 250 (4.8%) missing valuesMissing
faciltotscp is highly skewed (γ1 = 38.43720447)Skewed
skey has unique valuesUnique
faciltotscp has 2182 (42.0%) zerosZeros

Reproduction

Analysis started2024-04-16 10:38:22.367255
Analysis finished2024-04-16 10:38:24.137432
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct5193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3314.4113
Minimum1
Maximum11655
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-04-16T19:38:24.191859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile260.6
Q11299
median2597
Q33895
95-th percentile11395.4
Maximum11655
Range11654
Interquartile range (IQR)2596

Descriptive statistics

Standard deviation3010.5899
Coefficient of variation (CV)0.90833322
Kurtosis1.8535447
Mean3314.4113
Median Absolute Deviation (MAD)1298
Skewness1.6108486
Sum17211738
Variance9063651.6
MonotonicityNot monotonic
2024-04-16T19:38:24.296191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 1
 
< 0.1%
3449 1
 
< 0.1%
3466 1
 
< 0.1%
3465 1
 
< 0.1%
3464 1
 
< 0.1%
3463 1
 
< 0.1%
3462 1
 
< 0.1%
3461 1
 
< 0.1%
3460 1
 
< 0.1%
3459 1
 
< 0.1%
Other values (5183) 5183
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
11655 1
< 0.1%
11654 1
< 0.1%
11653 1
< 0.1%
11652 1
< 0.1%
11651 1
< 0.1%
11650 1
< 0.1%
11649 1
< 0.1%
11648 1
< 0.1%
11647 1
< 0.1%
11646 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3334560
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-04-16T19:38:24.386399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3340000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39923.896
Coefficient of variation (CV)0.011972763
Kurtosis-0.87783263
Mean3334560
Median Absolute Deviation (MAD)30000
Skewness-0.16789555
Sum1.731637 × 1010
Variance1.5939175 × 109
MonotonicityNot monotonic
2024-04-16T19:38:24.477118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3360000 732
14.1%
3340000 525
10.1%
3290000 446
8.6%
3330000 441
8.5%
3390000 398
 
7.7%
3300000 338
 
6.5%
3400000 335
 
6.5%
3310000 316
 
6.1%
3350000 312
 
6.0%
3320000 310
 
6.0%
Other values (6) 1040
20.0%
ValueCountFrequency (%)
3250000 83
 
1.6%
3260000 181
 
3.5%
3270000 154
 
3.0%
3280000 197
 
3.8%
3290000 446
8.6%
3300000 338
6.5%
3310000 316
6.1%
3320000 310
6.0%
3330000 441
8.5%
3340000 525
10.1%
ValueCountFrequency (%)
3400000 335
6.5%
3390000 398
7.7%
3380000 170
 
3.3%
3370000 255
 
4.9%
3360000 732
14.1%
3350000 312
6.0%
3340000 525
10.1%
3330000 441
8.5%
3320000 310
6.0%
3310000 316
6.1%

mgtno
Text

Distinct5013
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
2024-04-16T19:38:24.633645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters114246
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4882 ?
Unique (%)94.0%

Sample

1st row3250000-105-1992-00010
2nd row3250000-105-1998-00011
3rd row3250000-105-1998-00012
4th row3250000-105-1998-00013
5th row3250000-105-1998-00014
ValueCountFrequency (%)
3280000-105-2018-00004 3
 
0.1%
3290000-105-2019-00004 3
 
0.1%
3250000-105-2019-00002 3
 
0.1%
3360000-120-2019-00019 3
 
0.1%
3360000-105-2019-00009 3
 
0.1%
3370000-105-2020-00008 3
 
0.1%
3300000-105-2019-00010 3
 
0.1%
3370000-105-2020-00009 3
 
0.1%
3290000-120-2020-00001 3
 
0.1%
3370000-120-2020-00002 3
 
0.1%
Other values (5003) 5163
99.4%
2024-04-16T19:38:24.894297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52087
45.6%
- 15579
 
13.6%
1 10782
 
9.4%
3 10759
 
9.4%
2 8303
 
7.3%
5 6438
 
5.6%
9 3279
 
2.9%
6 2043
 
1.8%
4 2008
 
1.8%
8 1524
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98667
86.4%
Dash Punctuation 15579
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52087
52.8%
1 10782
 
10.9%
3 10759
 
10.9%
2 8303
 
8.4%
5 6438
 
6.5%
9 3279
 
3.3%
6 2043
 
2.1%
4 2008
 
2.0%
8 1524
 
1.5%
7 1444
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 15579
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 114246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52087
45.6%
- 15579
 
13.6%
1 10782
 
9.4%
3 10759
 
9.4%
2 8303
 
7.3%
5 6438
 
5.6%
9 3279
 
2.9%
6 2043
 
1.8%
4 2008
 
1.8%
8 1524
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52087
45.6%
- 15579
 
13.6%
1 10782
 
9.4%
3 10759
 
9.4%
2 8303
 
7.3%
5 6438
 
5.6%
9 3279
 
2.9%
6 2043
 
1.8%
4 2008
 
1.8%
8 1524
 
1.3%

opnsvcid
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
07_21_02_P
4973 
07_21_01_P
 
220

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_21_02_P
2nd row07_21_02_P
3rd row07_21_02_P
4th row07_21_02_P
5th row07_21_02_P

Common Values

ValueCountFrequency (%)
07_21_02_P 4973
95.8%
07_21_01_P 220
 
4.2%

Length

2024-04-16T19:38:25.001358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:25.077057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_21_02_p 4973
95.8%
07_21_01_p 220
 
4.2%

updategbn
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
I
4328 
U
865 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4328
83.3%
U 865
 
16.7%

Length

2024-04-16T19:38:25.155634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:25.225222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4328
83.3%
u 865
 
16.7%
Distinct536
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
Minimum2018-08-31 23:59:59
Maximum2022-12-10 02:40:00
2024-04-16T19:38:25.309178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T19:38:25.418099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
3937 
집단급식소
1036 
위탁급식영업
 
220

Length

Max length6
Median length4
Mean length4.2842288
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> 3937
75.8%
집단급식소 1036
 
19.9%
위탁급식영업 220
 
4.2%

Length

2024-04-16T19:38:25.525446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:25.614472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3937
75.8%
집단급식소 1036
 
19.9%
위탁급식영업 220
 
4.2%

bplcnm
Text

Distinct4351
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
2024-04-16T19:38:25.824396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length8.2851916
Min length2

Characters and Unicode

Total characters43025
Distinct characters634
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3748 ?
Unique (%)72.2%

Sample

1st row한국은행 부산본부
2nd row남성초등학교
3rd row보수초등학교
4th row봉래초등학교
5th row부산삼육초등학교
ValueCountFrequency (%)
어린이집 153
 
2.4%
주식회사 65
 
1.0%
의료법인 53
 
0.8%
구내식당 38
 
0.6%
사회복지법인 33
 
0.5%
요양병원 19
 
0.3%
유치원 19
 
0.3%
집단급식소 18
 
0.3%
부산광역시 16
 
0.3%
부경대학교 15
 
0.2%
Other values (4646) 5897
93.2%
2024-04-16T19:38:26.154782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1599
 
3.7%
1478
 
3.4%
1312
 
3.0%
1268
 
2.9%
1268
 
2.9%
1139
 
2.6%
1090
 
2.5%
1022
 
2.4%
) 1003
 
2.3%
( 994
 
2.3%
Other values (624) 30852
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39289
91.3%
Space Separator 1139
 
2.6%
Close Punctuation 1003
 
2.3%
Open Punctuation 994
 
2.3%
Uppercase Letter 341
 
0.8%
Decimal Number 180
 
0.4%
Other Punctuation 49
 
0.1%
Lowercase Letter 27
 
0.1%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1599
 
4.1%
1478
 
3.8%
1312
 
3.3%
1268
 
3.2%
1268
 
3.2%
1090
 
2.8%
1022
 
2.6%
924
 
2.4%
922
 
2.3%
788
 
2.0%
Other values (572) 27618
70.3%
Uppercase Letter
ValueCountFrequency (%)
S 42
12.3%
K 41
12.0%
T 27
 
7.9%
C 27
 
7.9%
N 24
 
7.0%
B 24
 
7.0%
A 20
 
5.9%
G 16
 
4.7%
I 16
 
4.7%
L 15
 
4.4%
Other values (13) 89
26.1%
Decimal Number
ValueCountFrequency (%)
2 75
41.7%
1 43
23.9%
3 30
 
16.7%
4 13
 
7.2%
5 8
 
4.4%
6 4
 
2.2%
0 3
 
1.7%
9 2
 
1.1%
7 2
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
e 9
33.3%
i 5
18.5%
w 4
14.8%
s 3
 
11.1%
k 2
 
7.4%
h 1
 
3.7%
a 1
 
3.7%
r 1
 
3.7%
f 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 20
40.8%
, 10
20.4%
& 7
 
14.3%
· 6
 
12.2%
/ 5
 
10.2%
! 1
 
2.0%
Space Separator
ValueCountFrequency (%)
1139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1003
100.0%
Open Punctuation
ValueCountFrequency (%)
( 994
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39289
91.3%
Common 3368
 
7.8%
Latin 368
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1599
 
4.1%
1478
 
3.8%
1312
 
3.3%
1268
 
3.2%
1268
 
3.2%
1090
 
2.8%
1022
 
2.6%
924
 
2.4%
922
 
2.3%
788
 
2.0%
Other values (572) 27618
70.3%
Latin
ValueCountFrequency (%)
S 42
 
11.4%
K 41
 
11.1%
T 27
 
7.3%
C 27
 
7.3%
N 24
 
6.5%
B 24
 
6.5%
A 20
 
5.4%
G 16
 
4.3%
I 16
 
4.3%
L 15
 
4.1%
Other values (22) 116
31.5%
Common
ValueCountFrequency (%)
1139
33.8%
) 1003
29.8%
( 994
29.5%
2 75
 
2.2%
1 43
 
1.3%
3 30
 
0.9%
. 20
 
0.6%
4 13
 
0.4%
, 10
 
0.3%
5 8
 
0.2%
Other values (10) 33
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39289
91.3%
ASCII 3730
 
8.7%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1599
 
4.1%
1478
 
3.8%
1312
 
3.3%
1268
 
3.2%
1268
 
3.2%
1090
 
2.8%
1022
 
2.6%
924
 
2.4%
922
 
2.3%
788
 
2.0%
Other values (572) 27618
70.3%
ASCII
ValueCountFrequency (%)
1139
30.5%
) 1003
26.9%
( 994
26.6%
2 75
 
2.0%
1 43
 
1.2%
S 42
 
1.1%
K 41
 
1.1%
3 30
 
0.8%
T 27
 
0.7%
C 27
 
0.7%
Other values (41) 309
 
8.3%
None
ValueCountFrequency (%)
· 6
100.0%

sitepostno
Text

MISSING 

Distinct766
Distinct (%)15.3%
Missing181
Missing (%)3.5%
Memory size40.7 KiB
2024-04-16T19:38:26.424562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters30072
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

Unique123 ?
Unique (%)2.5%

Sample

1st row600091
2nd row600091
3rd row600803
4th row600811
5th row600810
ValueCountFrequency (%)
618819 88
 
1.8%
618230 84
 
1.7%
618817 69
 
1.4%
618820 61
 
1.2%
618818 60
 
1.2%
604836 52
 
1.0%
618220 42
 
0.8%
618280 37
 
0.7%
618814 33
 
0.7%
618250 32
 
0.6%
Other values (756) 4454
88.9%
2024-04-16T19:38:26.777974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 6100
20.3%
8 5482
18.2%
1 5012
16.7%
0 4643
15.4%
2 2321
 
7.7%
4 1922
 
6.4%
3 1455
 
4.8%
7 1308
 
4.3%
9 1170
 
3.9%
5 641
 
2.1%
Other values (5) 18
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30054
99.9%
Other Letter 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 6100
20.3%
8 5482
18.2%
1 5012
16.7%
0 4643
15.4%
2 2321
 
7.7%
4 1922
 
6.4%
3 1455
 
4.8%
7 1308
 
4.4%
9 1170
 
3.9%
5 641
 
2.1%
Other Letter
ValueCountFrequency (%)
6
33.3%
3
16.7%
3
16.7%
3
16.7%
3
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 30054
99.9%
Hangul 18
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 6100
20.3%
8 5482
18.2%
1 5012
16.7%
0 4643
15.4%
2 2321
 
7.7%
4 1922
 
6.4%
3 1455
 
4.8%
7 1308
 
4.4%
9 1170
 
3.9%
5 641
 
2.1%
Hangul
ValueCountFrequency (%)
6
33.3%
3
16.7%
3
16.7%
3
16.7%
3
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30054
99.9%
Hangul 18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 6100
20.3%
8 5482
18.2%
1 5012
16.7%
0 4643
15.4%
2 2321
 
7.7%
4 1922
 
6.4%
3 1455
 
4.8%
7 1308
 
4.4%
9 1170
 
3.9%
5 641
 
2.1%
Hangul
ValueCountFrequency (%)
6
33.3%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
Distinct4367
Distinct (%)84.3%
Missing12
Missing (%)0.2%
Memory size40.7 KiB
2024-04-16T19:38:27.031971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length57
Mean length24.192434
Min length15

Characters and Unicode

Total characters125341
Distinct characters447
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3763 ?
Unique (%)72.6%

Sample

1st row부산광역시 중구 대청동1가 44-0번지
2nd row부산광역시 중구 대청동1가 10번지
3rd row부산광역시 중구 보수동1가 50-1번지
4th row부산광역시 중구 영주동 580-0번지
5th row부산광역시 중구 영주동 63-31번지
ValueCountFrequency (%)
부산광역시 5181
 
22.2%
강서구 730
 
3.1%
사하구 524
 
2.2%
부산진구 445
 
1.9%
해운대구 441
 
1.9%
사상구 398
 
1.7%
동래구 341
 
1.5%
기장군 334
 
1.4%
남구 316
 
1.4%
북구 310
 
1.3%
Other values (4907) 14311
61.3%
2024-04-16T19:38:27.416224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23308
18.6%
6246
 
5.0%
6021
 
4.8%
5800
 
4.6%
1 5337
 
4.3%
5311
 
4.2%
5237
 
4.2%
5187
 
4.1%
5079
 
4.1%
4693
 
3.7%
Other values (437) 53122
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74322
59.3%
Space Separator 23308
 
18.6%
Decimal Number 22870
 
18.2%
Dash Punctuation 3927
 
3.1%
Uppercase Letter 457
 
0.4%
Open Punctuation 166
 
0.1%
Close Punctuation 164
 
0.1%
Other Punctuation 105
 
0.1%
Lowercase Letter 19
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6246
 
8.4%
6021
 
8.1%
5800
 
7.8%
5311
 
7.1%
5237
 
7.0%
5187
 
7.0%
5079
 
6.8%
4693
 
6.3%
4156
 
5.6%
1187
 
1.6%
Other values (383) 25405
34.2%
Uppercase Letter
ValueCountFrequency (%)
B 155
33.9%
T 132
28.9%
K 24
 
5.3%
A 23
 
5.0%
L 19
 
4.2%
S 17
 
3.7%
C 16
 
3.5%
I 15
 
3.3%
H 13
 
2.8%
N 7
 
1.5%
Other values (12) 36
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 5337
23.3%
2 2789
12.2%
3 2376
10.4%
5 2176
9.5%
4 2112
 
9.2%
0 1765
 
7.7%
6 1742
 
7.6%
7 1680
 
7.3%
8 1548
 
6.8%
9 1345
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 78
74.3%
: 10
 
9.5%
. 7
 
6.7%
@ 3
 
2.9%
& 3
 
2.9%
/ 3
 
2.9%
· 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
42.1%
i 4
21.1%
l 2
 
10.5%
c 2
 
10.5%
k 1
 
5.3%
s 1
 
5.3%
o 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
( 165
99.4%
[ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 163
99.4%
] 1
 
0.6%
Space Separator
ValueCountFrequency (%)
23308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3927
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74322
59.3%
Common 50541
40.3%
Latin 478
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6246
 
8.4%
6021
 
8.1%
5800
 
7.8%
5311
 
7.1%
5237
 
7.0%
5187
 
7.0%
5079
 
6.8%
4693
 
6.3%
4156
 
5.6%
1187
 
1.6%
Other values (383) 25405
34.2%
Latin
ValueCountFrequency (%)
B 155
32.4%
T 132
27.6%
K 24
 
5.0%
A 23
 
4.8%
L 19
 
4.0%
S 17
 
3.6%
C 16
 
3.3%
I 15
 
3.1%
H 13
 
2.7%
e 8
 
1.7%
Other values (20) 56
 
11.7%
Common
ValueCountFrequency (%)
23308
46.1%
1 5337
 
10.6%
- 3927
 
7.8%
2 2789
 
5.5%
3 2376
 
4.7%
5 2176
 
4.3%
4 2112
 
4.2%
0 1765
 
3.5%
6 1742
 
3.4%
7 1680
 
3.3%
Other values (14) 3329
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74322
59.3%
ASCII 51016
40.7%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23308
45.7%
1 5337
 
10.5%
- 3927
 
7.7%
2 2789
 
5.5%
3 2376
 
4.7%
5 2176
 
4.3%
4 2112
 
4.1%
0 1765
 
3.5%
6 1742
 
3.4%
7 1680
 
3.3%
Other values (42) 3804
 
7.5%
Hangul
ValueCountFrequency (%)
6246
 
8.4%
6021
 
8.1%
5800
 
7.8%
5311
 
7.1%
5237
 
7.0%
5187
 
7.0%
5079
 
6.8%
4693
 
6.3%
4156
 
5.6%
1187
 
1.6%
Other values (383) 25405
34.2%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Distinct1438
Distinct (%)27.9%
Missing30
Missing (%)0.6%
Memory size40.7 KiB
2024-04-16T19:38:27.669235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0023242
Min length5

Characters and Unicode

Total characters25827
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

Unique534 ?
Unique (%)10.3%

Sample

1st row48949
2nd row48926
3rd row48962
4th row48922
5th row48910
ValueCountFrequency (%)
48947 883
 
17.1%
46742 63
 
1.2%
46753 46
 
0.9%
46754 42
 
0.8%
46757 39
 
0.8%
46752 34
 
0.7%
46755 33
 
0.6%
46751 31
 
0.6%
46744 25
 
0.5%
47340 24
 
0.5%
Other values (1428) 3943
76.4%
2024-04-16T19:38:28.016438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 7412
28.7%
7 3454
13.4%
8 2720
 
10.5%
9 2501
 
9.7%
6 2387
 
9.2%
0 1764
 
6.8%
5 1591
 
6.2%
2 1520
 
5.9%
3 1229
 
4.8%
1 1207
 
4.7%
Other values (7) 42
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25785
99.8%
Other Letter 42
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 7412
28.7%
7 3454
13.4%
8 2720
 
10.5%
9 2501
 
9.7%
6 2387
 
9.3%
0 1764
 
6.8%
5 1591
 
6.2%
2 1520
 
5.9%
3 1229
 
4.8%
1 1207
 
4.7%
Other Letter
ValueCountFrequency (%)
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 25785
99.8%
Hangul 42
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
4 7412
28.7%
7 3454
13.4%
8 2720
 
10.5%
9 2501
 
9.7%
6 2387
 
9.3%
0 1764
 
6.8%
5 1591
 
6.2%
2 1520
 
5.9%
3 1229
 
4.8%
1 1207
 
4.7%
Hangul
ValueCountFrequency (%)
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25785
99.8%
Hangul 42
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 7412
28.7%
7 3454
13.4%
8 2720
 
10.5%
9 2501
 
9.7%
6 2387
 
9.3%
0 1764
 
6.8%
5 1591
 
6.2%
2 1520
 
5.9%
3 1229
 
4.8%
1 1207
 
4.7%
Hangul
ValueCountFrequency (%)
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%
6
14.3%

rdnwhladdr
Text

MISSING 

Distinct3703
Distinct (%)85.2%
Missing848
Missing (%)16.3%
Memory size40.7 KiB
2024-04-16T19:38:28.302980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length51
Mean length28.974453
Min length5

Characters and Unicode

Total characters125894
Distinct characters493
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3236 ?
Unique (%)74.5%

Sample

1st row부산광역시 중구 대청로 112 (대청동1가)
2nd row부산광역시 중구 샘길 14 (대청동1가)
3rd row부산광역시 중구 흑교로 74 (보수동1가)
4th row부산광역시 중구 대영로226번길 15 (영주동)
5th row부산광역시 중구 초량상로5번길 28 (영주동)
ValueCountFrequency (%)
부산광역시 4342
 
17.8%
강서구 620
 
2.5%
1층 421
 
1.7%
사하구 420
 
1.7%
해운대구 382
 
1.6%
부산진구 338
 
1.4%
동래구 309
 
1.3%
사상구 288
 
1.2%
기장군 288
 
1.2%
금정구 270
 
1.1%
Other values (3691) 16737
68.6%
2024-04-16T19:38:28.710692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20087
 
16.0%
5888
 
4.7%
5377
 
4.3%
5086
 
4.0%
4547
 
3.6%
4526
 
3.6%
4347
 
3.5%
4293
 
3.4%
( 4218
 
3.4%
) 4216
 
3.3%
Other values (483) 63309
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76594
60.8%
Space Separator 20087
 
16.0%
Decimal Number 18048
 
14.3%
Open Punctuation 4218
 
3.4%
Close Punctuation 4216
 
3.3%
Other Punctuation 1919
 
1.5%
Dash Punctuation 548
 
0.4%
Uppercase Letter 234
 
0.2%
Lowercase Letter 19
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5888
 
7.7%
5377
 
7.0%
5086
 
6.6%
4547
 
5.9%
4526
 
5.9%
4347
 
5.7%
4293
 
5.6%
4209
 
5.5%
1896
 
2.5%
1873
 
2.4%
Other values (430) 34552
45.1%
Uppercase Letter
ValueCountFrequency (%)
B 45
19.2%
C 25
10.7%
A 25
10.7%
K 24
10.3%
S 17
 
7.3%
H 15
 
6.4%
L 11
 
4.7%
N 10
 
4.3%
E 10
 
4.3%
I 9
 
3.8%
Other values (12) 43
18.4%
Decimal Number
ValueCountFrequency (%)
1 4072
22.6%
2 2579
14.3%
3 2059
11.4%
4 1628
 
9.0%
5 1512
 
8.4%
6 1471
 
8.2%
7 1356
 
7.5%
0 1320
 
7.3%
9 1086
 
6.0%
8 965
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
42.1%
c 3
 
15.8%
l 2
 
10.5%
b 2
 
10.5%
i 1
 
5.3%
k 1
 
5.3%
s 1
 
5.3%
o 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 1900
99.0%
. 5
 
0.3%
: 5
 
0.3%
@ 3
 
0.2%
& 3
 
0.2%
/ 2
 
0.1%
· 1
 
0.1%
Space Separator
ValueCountFrequency (%)
20087
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 548
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76594
60.8%
Common 49046
39.0%
Latin 254
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5888
 
7.7%
5377
 
7.0%
5086
 
6.6%
4547
 
5.9%
4526
 
5.9%
4347
 
5.7%
4293
 
5.6%
4209
 
5.5%
1896
 
2.5%
1873
 
2.4%
Other values (430) 34552
45.1%
Latin
ValueCountFrequency (%)
B 45
17.7%
C 25
 
9.8%
A 25
 
9.8%
K 24
 
9.4%
S 17
 
6.7%
H 15
 
5.9%
L 11
 
4.3%
N 10
 
3.9%
E 10
 
3.9%
I 9
 
3.5%
Other values (21) 63
24.8%
Common
ValueCountFrequency (%)
20087
41.0%
( 4218
 
8.6%
) 4216
 
8.6%
1 4072
 
8.3%
2 2579
 
5.3%
3 2059
 
4.2%
, 1900
 
3.9%
4 1628
 
3.3%
5 1512
 
3.1%
6 1471
 
3.0%
Other values (12) 5304
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76594
60.8%
ASCII 49298
39.2%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20087
40.7%
( 4218
 
8.6%
) 4216
 
8.6%
1 4072
 
8.3%
2 2579
 
5.2%
3 2059
 
4.2%
, 1900
 
3.9%
4 1628
 
3.3%
5 1512
 
3.1%
6 1471
 
3.0%
Other values (41) 5556
 
11.3%
Hangul
ValueCountFrequency (%)
5888
 
7.7%
5377
 
7.0%
5086
 
6.6%
4547
 
5.9%
4526
 
5.9%
4347
 
5.7%
4293
 
5.6%
4209
 
5.5%
1896
 
2.5%
1873
 
2.4%
Other values (430) 34552
45.1%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

apvpermymd
Real number (ℝ)

Distinct3070
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087060
Minimum19670101
Maximum20220923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-04-16T19:38:28.820691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19670101
5-th percentile19930474
Q120030418
median20090408
Q320160219
95-th percentile20210713
Maximum20220923
Range550822
Interquartile range (IQR)129801

Descriptive statistics

Standard deviation86682.644
Coefficient of variation (CV)0.0043153476
Kurtosis0.35906919
Mean20087060
Median Absolute Deviation (MAD)60598
Skewness-0.60019108
Sum1.043121 × 1011
Variance7.5138807 × 109
MonotonicityNot monotonic
2024-04-16T19:38:28.928700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19900518 29
 
0.6%
19900330 25
 
0.5%
19980427 24
 
0.5%
19870528 18
 
0.3%
19900612 17
 
0.3%
20000529 17
 
0.3%
19980511 16
 
0.3%
20190719 15
 
0.3%
19900326 14
 
0.3%
19890622 14
 
0.3%
Other values (3060) 5004
96.4%
ValueCountFrequency (%)
19670101 1
 
< 0.1%
19690901 1
 
< 0.1%
19691120 1
 
< 0.1%
19701015 1
 
< 0.1%
19710518 1
 
< 0.1%
19740116 3
0.1%
19740201 1
 
< 0.1%
19750101 1
 
< 0.1%
19760101 1
 
< 0.1%
19760110 1
 
< 0.1%
ValueCountFrequency (%)
20220923 2
< 0.1%
20220920 2
< 0.1%
20220919 1
 
< 0.1%
20220908 2
< 0.1%
20220907 2
< 0.1%
20220906 2
< 0.1%
20220905 1
 
< 0.1%
20220902 4
0.1%
20220831 2
< 0.1%
20220826 4
0.1%

dcbymd
Text

MISSING 

Distinct1284
Distinct (%)69.4%
Missing3342
Missing (%)64.4%
Memory size40.7 KiB
2024-04-16T19:38:29.132854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6931388
Min length4

Characters and Unicode

Total characters14240
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

Unique985 ?
Unique (%)53.2%

Sample

1st row20130724
2nd row20160331
3rd row20131122
4th row20051219
5th row20170530
ValueCountFrequency (%)
폐업일자 142
 
7.7%
20180704 11
 
0.6%
19960615 10
 
0.5%
20100608 8
 
0.4%
20040624 7
 
0.4%
20070322 6
 
0.3%
20140829 5
 
0.3%
20170228 5
 
0.3%
20080325 5
 
0.3%
20150901 4
 
0.2%
Other values (1274) 1648
89.0%
2024-04-16T19:38:29.454240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4299
30.2%
2 3056
21.5%
1 2572
18.1%
3 603
 
4.2%
4 567
 
4.0%
7 552
 
3.9%
6 539
 
3.8%
5 512
 
3.6%
8 493
 
3.5%
9 479
 
3.4%
Other values (4) 568
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13672
96.0%
Other Letter 568
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4299
31.4%
2 3056
22.4%
1 2572
18.8%
3 603
 
4.4%
4 567
 
4.1%
7 552
 
4.0%
6 539
 
3.9%
5 512
 
3.7%
8 493
 
3.6%
9 479
 
3.5%
Other Letter
ValueCountFrequency (%)
142
25.0%
142
25.0%
142
25.0%
142
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13672
96.0%
Hangul 568
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4299
31.4%
2 3056
22.4%
1 2572
18.8%
3 603
 
4.4%
4 567
 
4.1%
7 552
 
4.0%
6 539
 
3.9%
5 512
 
3.7%
8 493
 
3.6%
9 479
 
3.5%
Hangul
ValueCountFrequency (%)
142
25.0%
142
25.0%
142
25.0%
142
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13672
96.0%
Hangul 568
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4299
31.4%
2 3056
22.4%
1 2572
18.8%
3 603
 
4.4%
4 567
 
4.1%
7 552
 
4.0%
6 539
 
3.9%
5 512
 
3.7%
8 493
 
3.6%
9 479
 
3.5%
Hangul
ValueCountFrequency (%)
142
25.0%
142
25.0%
142
25.0%
142
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
휴업시작일자
 
160

Length

Max length6
Median length4
Mean length4.0616214
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> 5033
96.9%
휴업시작일자 160
 
3.1%

Length

2024-04-16T19:38:29.571997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:29.660793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
휴업시작일자 160
 
3.1%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
휴업종료일자
 
160

Length

Max length6
Median length4
Mean length4.0616214
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> 5033
96.9%
휴업종료일자 160
 
3.1%

Length

2024-04-16T19:38:29.748222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:29.829539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
휴업종료일자 160
 
3.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
재개업일자
 
160

Length

Max length5
Median length4
Mean length4.0308107
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> 5033
96.9%
재개업일자 160
 
3.1%

Length

2024-04-16T19:38:29.908339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:29.981893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
재개업일자 160
 
3.1%

trdstatenm
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
01
2451 
02
1486 
영업/정상
1021 
폐업
 
223
<NA>
 
10

Length

Max length5
Median length2
Mean length2.5944541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02
2nd row01
3rd row01
4th row01
5th row02

Common Values

ValueCountFrequency (%)
01 2451
47.2%
02 1486
28.6%
영업/정상 1021
19.7%
폐업 223
 
4.3%
<NA> 10
 
0.2%
영업상태 2
 
< 0.1%

Length

2024-04-16T19:38:30.062213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:30.149763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 2451
47.2%
02 1486
28.6%
영업/정상 1021
19.7%
폐업 223
 
4.3%
na 10
 
0.2%
영업상태 2
 
< 0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
영업
3484 
폐업
1709 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3484
67.1%
폐업 1709
32.9%

Length

2024-04-16T19:38:30.265870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:30.353629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3484
67.1%
폐업 1709
32.9%

x
Text

MISSING 

Distinct4026
Distinct (%)80.9%
Missing218
Missing (%)4.2%
Memory size40.7 KiB
2024-04-16T19:38:30.548553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.96603
Min length7

Characters and Unicode

Total characters99331
Distinct characters19
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

Unique3351 ?
Unique (%)67.4%

Sample

1st row385292.68193300000
2nd row385491.91116300000
3rd row384584.74633900000
4th row385676.15914800000
5th row385436.10017500000
ValueCountFrequency (%)
385474.303751383 17
 
0.3%
좌표정보(x 13
 
0.3%
389751.93732600000 10
 
0.2%
385742.94460500000 7
 
0.1%
382234.98696200000 7
 
0.1%
373462.31341600000 6
 
0.1%
386672.326492828 6
 
0.1%
392222.63567800000 6
 
0.1%
398074.127570382 5
 
0.1%
372030.10777100000 5
 
0.1%
Other values (4016) 4893
98.4%
2024-04-16T19:38:31.074887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20194
20.3%
16854
17.0%
3 10231
10.3%
8 7812
 
7.9%
9 6967
 
7.0%
7 5579
 
5.6%
1 5476
 
5.5%
6 5476
 
5.5%
4 5281
 
5.3%
2 5241
 
5.3%
Other values (9) 10220
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77497
78.0%
Space Separator 16854
 
17.0%
Other Punctuation 4889
 
4.9%
Other Letter 52
 
0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20194
26.1%
3 10231
13.2%
8 7812
 
10.1%
9 6967
 
9.0%
7 5579
 
7.2%
1 5476
 
7.1%
6 5476
 
7.1%
4 5281
 
6.8%
2 5241
 
6.8%
5 5240
 
6.8%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Space Separator
ValueCountFrequency (%)
16854
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4889
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99266
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20194
20.3%
16854
17.0%
3 10231
10.3%
8 7812
 
7.9%
9 6967
 
7.0%
7 5579
 
5.6%
1 5476
 
5.5%
6 5476
 
5.5%
4 5281
 
5.3%
2 5241
 
5.3%
Other values (4) 10155
10.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
X 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99279
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20194
20.3%
16854
17.0%
3 10231
10.3%
8 7812
 
7.9%
9 6967
 
7.0%
7 5579
 
5.6%
1 5476
 
5.5%
6 5476
 
5.5%
4 5281
 
5.3%
2 5241
 
5.3%
Other values (5) 10168
10.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

y
Text

MISSING 

Distinct4025
Distinct (%)80.9%
Missing218
Missing (%)4.2%
Memory size40.7 KiB
2024-04-16T19:38:31.308164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.96603
Min length7

Characters and Unicode

Total characters99331
Distinct characters19
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

Unique3349 ?
Unique (%)67.3%

Sample

1st row180361.43835300000
2nd row180721.27754500000
3rd row180738.18132800000
4th row181391.55498800000
5th row181550.22326000000
ValueCountFrequency (%)
184379.476337941 17
 
0.3%
좌표정보(y 13
 
0.3%
195491.51978200000 10
 
0.2%
185162.38057300000 7
 
0.1%
188009.54573200000 7
 
0.1%
182038.85873800000 6
 
0.1%
184336.34946900000 6
 
0.1%
177707.834399007 6
 
0.1%
179747.69058500000 5
 
0.1%
182087.26132000000 5
 
0.1%
Other values (4015) 4893
98.4%
2024-04-16T19:38:31.617766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20136
20.3%
16817
16.9%
1 10017
10.1%
8 7895
 
7.9%
9 6696
 
6.7%
7 6546
 
6.6%
5 5296
 
5.3%
4 5277
 
5.3%
2 5263
 
5.3%
3 5209
 
5.2%
Other values (9) 10179
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77534
78.1%
Space Separator 16817
 
16.9%
Other Punctuation 4889
 
4.9%
Other Letter 52
 
0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20136
26.0%
1 10017
12.9%
8 7895
 
10.2%
9 6696
 
8.6%
7 6546
 
8.4%
5 5296
 
6.8%
4 5277
 
6.8%
2 5263
 
6.8%
3 5209
 
6.7%
6 5199
 
6.7%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Space Separator
ValueCountFrequency (%)
16817
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4889
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99266
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20136
20.3%
16817
16.9%
1 10017
10.1%
8 7895
 
8.0%
9 6696
 
6.7%
7 6546
 
6.6%
5 5296
 
5.3%
4 5277
 
5.3%
2 5263
 
5.3%
3 5209
 
5.2%
Other values (4) 10114
10.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
Y 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99279
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20136
20.3%
16817
16.9%
1 10017
10.1%
8 7895
 
8.0%
9 6696
 
6.7%
7 6546
 
6.6%
5 5296
 
5.3%
4 5277
 
5.3%
2 5263
 
5.3%
3 5209
 
5.2%
Other values (5) 10127
10.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

lastmodts
Real number (ℝ)

Distinct4202
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0161763 × 1013
Minimum1.9990209 × 1013
Maximum2.0221208 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-04-16T19:38:31.736675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990209 × 1013
5-th percentile2.0040217 × 1013
Q12.0170105 × 1013
median2.0170822 × 1013
Q32.0180817 × 1013
95-th percentile2.0220516 × 1013
Maximum2.0221208 × 1013
Range2.309991 × 1011
Interquartile range (IQR)1.0711999 × 1010

Descriptive statistics

Standard deviation5.0316662 × 1010
Coefficient of variation (CV)0.002495648
Kurtosis1.9925991
Mean2.0161763 × 1013
Median Absolute Deviation (MAD)9.8819031 × 109
Skewness-1.5228046
Sum1.0470003 × 1017
Variance2.5317665 × 1021
MonotonicityNot monotonic
2024-04-16T19:38:31.843636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170822192441 224
 
4.3%
20170822191707 191
 
3.7%
20170822191632 110
 
2.1%
20170822191614 55
 
1.1%
20020830000000 52
 
1.0%
20010725000000 19
 
0.4%
20170822192708 13
 
0.3%
20020226000000 11
 
0.2%
20170822194227 10
 
0.2%
20020625000000 10
 
0.2%
Other values (4192) 4498
86.6%
ValueCountFrequency (%)
19990209000000 1
 
< 0.1%
19990304000000 8
0.2%
19990318000000 6
0.1%
19990326000000 1
 
< 0.1%
19990406000000 4
0.1%
19990415000000 2
 
< 0.1%
19990519000000 1
 
< 0.1%
19990708000000 1
 
< 0.1%
19990723000000 1
 
< 0.1%
19990814000000 1
 
< 0.1%
ValueCountFrequency (%)
20221208103909 1
< 0.1%
20221208103732 1
< 0.1%
20220923105342 1
< 0.1%
20220923094546 2
< 0.1%
20220922111635 1
< 0.1%
20220921152041 1
< 0.1%
20220921143437 1
< 0.1%
20220920173042 1
< 0.1%
20220920171522 1
< 0.1%
20220920164053 1
< 0.1%

uptaenm
Categorical

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
어린이집
1276 
집단급식소
1255 
산업체
811 
학교
726 
병원
492 
Other values (7)
633 

Length

Max length8
Median length6
Mean length3.8222607
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소
2nd row학교
3rd row학교
4th row학교
5th row집단급식소

Common Values

ValueCountFrequency (%)
어린이집 1276
24.6%
집단급식소 1255
24.2%
산업체 811
15.6%
학교 726
14.0%
병원 492
 
9.5%
사회복지시설 236
 
4.5%
위탁급식영업 220
 
4.2%
공공기관 110
 
2.1%
기타 집단급식소 44
 
0.8%
기숙사 16
 
0.3%
Other values (2) 7
 
0.1%

Length

2024-04-16T19:38:31.972041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 1299
24.8%
어린이집 1276
24.4%
산업체 811
15.5%
학교 726
13.9%
병원 492
 
9.4%
사회복지시설 236
 
4.5%
위탁급식영업 220
 
4.2%
공공기관 110
 
2.1%
기타 44
 
0.8%
기숙사 16
 
0.3%
Other values (2) 7
 
0.1%

sitetel
Text

MISSING 

Distinct609
Distinct (%)12.3%
Missing250
Missing (%)4.8%
Memory size40.7 KiB
2024-04-16T19:38:32.230978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.830063
Min length3

Characters and Unicode

Total characters58476
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique548 ?
Unique (%)11.1%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 4184
69.1%
051 616
 
10.2%
전화번호 71
 
1.2%
831 21
 
0.3%
02 13
 
0.2%
055 12
 
0.2%
070 11
 
0.2%
727 8
 
0.1%
302 7
 
0.1%
250 7
 
0.1%
Other values (807) 1104
 
18.2%
2024-04-16T19:38:32.546111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13731
23.5%
2 8967
15.3%
3 8841
15.1%
- 8368
14.3%
0 5626
9.6%
5 5328
 
9.1%
4 4594
 
7.9%
1135
 
1.9%
7 480
 
0.8%
6 397
 
0.7%
Other values (6) 1009
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48689
83.3%
Dash Punctuation 8368
 
14.3%
Space Separator 1135
 
1.9%
Other Letter 284
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13731
28.2%
2 8967
18.4%
3 8841
18.2%
0 5626
11.6%
5 5328
 
10.9%
4 4594
 
9.4%
7 480
 
1.0%
6 397
 
0.8%
8 383
 
0.8%
9 342
 
0.7%
Other Letter
ValueCountFrequency (%)
71
25.0%
71
25.0%
71
25.0%
71
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 8368
100.0%
Space Separator
ValueCountFrequency (%)
1135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58192
99.5%
Hangul 284
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13731
23.6%
2 8967
15.4%
3 8841
15.2%
- 8368
14.4%
0 5626
9.7%
5 5328
 
9.2%
4 4594
 
7.9%
1135
 
2.0%
7 480
 
0.8%
6 397
 
0.7%
Other values (2) 725
 
1.2%
Hangul
ValueCountFrequency (%)
71
25.0%
71
25.0%
71
25.0%
71
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58192
99.5%
Hangul 284
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13731
23.6%
2 8967
15.4%
3 8841
15.2%
- 8368
14.4%
0 5626
9.7%
5 5328
 
9.2%
4 4594
 
7.9%
1135
 
2.0%
7 480
 
0.8%
6 397
 
0.7%
Other values (2) 725
 
1.2%
Hangul
ValueCountFrequency (%)
71
25.0%
71
25.0%
71
25.0%
71
25.0%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4637 
자가
 
388
건물소유구분명
 
159
임대
 
9

Length

Max length7
Median length4
Mean length3.9389563
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> 4637
89.3%
자가 388
 
7.5%
건물소유구분명 159
 
3.1%
임대 9
 
0.2%

Length

2024-04-16T19:38:32.669183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:32.762676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4637
89.3%
자가 388
 
7.5%
건물소유구분명 159
 
3.1%
임대 9
 
0.2%

fctyowkepcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4525 
0
581 
공장사무직종업원수
 
87

Length

Max length9
Median length4
Mean length3.7481225
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> 4525
87.1%
0 581
 
11.2%
공장사무직종업원수 87
 
1.7%

Length

2024-04-16T19:38:32.897190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:33.053142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4525
87.1%
0 581
 
11.2%
공장사무직종업원수 87
 
1.7%

fctypdtjobepcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4525 
0
581 
공장생산직종업원수
 
87

Length

Max length9
Median length4
Mean length3.7481225
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> 4525
87.1%
0 581
 
11.2%
공장생산직종업원수 87
 
1.7%

Length

2024-04-16T19:38:33.164262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:33.248114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4525
87.1%
0 581
 
11.2%
공장생산직종업원수 87
 
1.7%

fctysiljobepcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4525 
0
581 
공장판매직종업원수
 
87

Length

Max length9
Median length4
Mean length3.7481225
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> 4525
87.1%
0 581
 
11.2%
공장판매직종업원수 87
 
1.7%

Length

2024-04-16T19:38:33.335678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:33.420695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4525
87.1%
0 581
 
11.2%
공장판매직종업원수 87
 
1.7%

wtrsplyfacilsenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
상수도전용
2952 
<NA>
2049 
급수시설구분명
 
109
지하수전용
 
57
상수도(음용)지하수(주방용)겸용
 
21
Other values (2)
 
5

Length

Max length19
Median length5
Mean length4.7013287
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2952
56.8%
<NA> 2049
39.5%
급수시설구분명 109
 
2.1%
지하수전용 57
 
1.1%
상수도(음용)지하수(주방용)겸용 21
 
0.4%
간이상수도 3
 
0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%

Length

2024-04-16T19:38:33.517982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:33.629557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2952
56.8%
na 2049
39.4%
급수시설구분명 109
 
2.1%
지하수전용 57
 
1.1%
상수도(음용)지하수(주방용)겸용 21
 
0.4%
간이상수도 3
 
0.1%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4002 
0
1098 
남성종사자수
 
87
1
 
6

Length

Max length6
Median length4
Mean length3.395725
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4002
77.1%
0 1098
 
21.1%
남성종사자수 87
 
1.7%
1 6
 
0.1%

Length

2024-04-16T19:38:33.747943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:33.846577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4002
77.1%
0 1098
 
21.1%
남성종사자수 87
 
1.7%
1 6
 
0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size10.3 KiB
False
5187 
True
 
5
(Missing)
 
1
ValueCountFrequency (%)
False 5187
99.9%
True 5
 
0.1%
(Missing) 1
 
< 0.1%
2024-04-16T19:38:33.938945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

lvsenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4017 
기타
965 
등급구분명
 
159
자율
 
51
우수
 
1

Length

Max length5
Median length4
Mean length3.638937
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4017
77.4%
기타 965
 
18.6%
등급구분명 159
 
3.1%
자율 51
 
1.0%
우수 1
 
< 0.1%

Length

2024-04-16T19:38:34.036288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:34.124139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4017
77.4%
기타 965
 
18.6%
등급구분명 159
 
3.1%
자율 51
 
1.0%
우수 1
 
< 0.1%

isream
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
3002 
0
2131 
보증액
 
60

Length

Max length4
Median length4
Mean length2.7573657
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> 3002
57.8%
0 2131
41.0%
보증액 60
 
1.2%

Length

2024-04-16T19:38:34.214439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:34.308054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3002
57.8%
0 2131
41.0%
보증액 60
 
1.2%

hoffepcnt
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
0
2923 
<NA>
1921 
1
 
107
2
 
61
본사종업원수
 
60
Other values (14)
 
121

Length

Max length6
Median length1
Mean length2.169844
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2923
56.3%
<NA> 1921
37.0%
1 107
 
2.1%
2 61
 
1.2%
본사종업원수 60
 
1.2%
3 39
 
0.8%
4 25
 
0.5%
5 19
 
0.4%
6 13
 
0.3%
8 7
 
0.1%
Other values (9) 18
 
0.3%

Length

2024-04-16T19:38:34.398838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2923
56.3%
na 1921
37.0%
1 107
 
2.1%
2 61
 
1.2%
본사종업원수 60
 
1.2%
3 39
 
0.8%
4 25
 
0.5%
5 19
 
0.4%
6 13
 
0.3%
8 7
 
0.1%
Other values (9) 18
 
0.3%

faciltotscp
Real number (ℝ)

SKEWED  ZEROS 

Distinct2061
Distinct (%)39.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean55.760326
Minimum0
Maximum17067
Zeros2182
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-04-16T19:38:34.501472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11.5
Q343.2125
95-th percentile221.2405
Maximum17067
Range17067
Interquartile range (IQR)43.2125

Descriptive statistics

Standard deviation313.98497
Coefficient of variation (CV)5.6309745
Kurtosis1874.8764
Mean55.760326
Median Absolute Deviation (MAD)11.5
Skewness38.437204
Sum289507.61
Variance98586.563
MonotonicityNot monotonic
2024-04-16T19:38:34.619853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2182
42.0%
12.0 22
 
0.4%
18.0 17
 
0.3%
30.0 16
 
0.3%
20.0 14
 
0.3%
25.0 14
 
0.3%
8.0 11
 
0.2%
70.0 10
 
0.2%
40.0 10
 
0.2%
24.0 9
 
0.2%
Other values (2051) 2887
55.6%
ValueCountFrequency (%)
0.0 2182
42.0%
1.0 1
 
< 0.1%
1.38 1
 
< 0.1%
2.08 2
 
< 0.1%
2.39 1
 
< 0.1%
3.0 2
 
< 0.1%
3.2 1
 
< 0.1%
3.22 1
 
< 0.1%
3.37 1
 
< 0.1%
3.62 1
 
< 0.1%
ValueCountFrequency (%)
17067.0 1
< 0.1%
10058.04 1
< 0.1%
4950.0 1
< 0.1%
3623.63 1
< 0.1%
2491.24 2
< 0.1%
2115.5 1
< 0.1%
1914.0 1
< 0.1%
1887.0 1
< 0.1%
1534.5 2
< 0.1%
1434.0 1
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
3983 
0
1084 
여성종사자수
 
87
3
 
7
5
 
6
Other values (11)
 
26

Length

Max length6
Median length4
Mean length3.3857115
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3983
76.7%
0 1084
 
20.9%
여성종사자수 87
 
1.7%
3 7
 
0.1%
5 6
 
0.1%
2 5
 
0.1%
9 4
 
0.1%
4 4
 
0.1%
8 3
 
0.1%
6 2
 
< 0.1%
Other values (6) 8
 
0.2%

Length

2024-04-16T19:38:34.722362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3983
76.7%
0 1084
 
20.9%
여성종사자수 87
 
1.7%
3 7
 
0.1%
5 6
 
0.1%
2 5
 
0.1%
9 4
 
0.1%
4 4
 
0.1%
8 3
 
0.1%
6 2
 
< 0.1%
Other values (6) 8
 
0.2%

trdpjubnsenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4017 
기타
985 
영업장주변구분명
 
159
주택가주변
 
15
학교정화(상대)
 
9
Other values (2)
 
8

Length

Max length8
Median length4
Mean length3.7579434
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4017
77.4%
기타 985
 
19.0%
영업장주변구분명 159
 
3.1%
주택가주변 15
 
0.3%
학교정화(상대) 9
 
0.2%
학교정화(절대) 6
 
0.1%
아파트지역 2
 
< 0.1%

Length

2024-04-16T19:38:34.816608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:34.919810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4017
77.4%
기타 985
 
19.0%
영업장주변구분명 159
 
3.1%
주택가주변 15
 
0.3%
학교정화(상대 9
 
0.2%
학교정화(절대 6
 
0.1%
아파트지역 2
 
< 0.1%

monam
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
3002 
0
2131 
월세액
 
60

Length

Max length4
Median length4
Mean length2.7573657
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> 3002
57.8%
0 2131
41.0%
월세액 60
 
1.2%

Length

2024-04-16T19:38:35.023856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:35.104981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3002
57.8%
0 2131
41.0%
월세액 60
 
1.2%

sntuptaenm
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
어린이집
1274 
집단급식소
1255 
산업체
812 
학교
727 
병원
492 
Other values (8)
633 

Length

Max length8
Median length6
Mean length3.8220682
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row집단급식소
2nd row학교
3rd row학교
4th row학교
5th row집단급식소

Common Values

ValueCountFrequency (%)
어린이집 1274
24.5%
집단급식소 1255
24.2%
산업체 812
15.6%
학교 727
14.0%
병원 492
 
9.5%
사회복지시설 237
 
4.6%
위탁급식영업 220
 
4.2%
공공기관 108
 
2.1%
기타 집단급식소 44
 
0.8%
기숙사 16
 
0.3%
Other values (3) 8
 
0.2%

Length

2024-04-16T19:38:35.191318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 1299
24.8%
어린이집 1274
24.3%
산업체 812
15.5%
학교 727
13.9%
병원 492
 
9.4%
사회복지시설 237
 
4.5%
위탁급식영업 220
 
4.2%
공공기관 108
 
2.1%
기타 44
 
0.8%
기숙사 16
 
0.3%
Other values (3) 8
 
0.2%

jtupsomainedf
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
전통업소주된음식
 
160

Length

Max length8
Median length4
Mean length4.1232428
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> 5033
96.9%
전통업소주된음식 160
 
3.1%

Length

2024-04-16T19:38:35.292551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:35.375125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
전통업소주된음식 160
 
3.1%

jtupsoasgnno
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
전통업소지정번호
 
160

Length

Max length8
Median length4
Mean length4.1232428
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> 5033
96.9%
전통업소지정번호 160
 
3.1%

Length

2024-04-16T19:38:35.476874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:35.572906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
전통업소지정번호 160
 
3.1%

totepnum
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
4526 
0
580 
총종업원수
 
87

Length

Max length5
Median length4
Mean length3.6816869
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> 4526
87.2%
0 580
 
11.2%
총종업원수 87
 
1.7%

Length

2024-04-16T19:38:35.700304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:35.862071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4526
87.2%
0 580
 
11.2%
총종업원수 87
 
1.7%

homepage
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
<NA>
5033 
홈페이지
 
160

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> 5033
96.9%
홈페이지 160
 
3.1%

Length

2024-04-16T19:38:35.969455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:36.042191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5033
96.9%
홈페이지 160
 
3.1%

last_load_dttm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.7 KiB
2023-07-01 05:16:03
4727 
2023-07-01 05:16:04
 
466

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-01 05:16:03
2nd row2023-07-01 05:16:03
3rd row2023-07-01 05:16:03
4th row2023-07-01 05:16:03
5th row2023-07-01 05:16:03

Common Values

ValueCountFrequency (%)
2023-07-01 05:16:03 4727
91.0%
2023-07-01 05:16:04 466
 
9.0%

Length

2024-04-16T19:38:36.119323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:38:36.190436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-01 5193
50.0%
05:16:03 4727
45.5%
05:16:04 466
 
4.5%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmfctyowkepcntfctypdtjobepcntfctysiljobepcntwtrsplyfacilsenmmaneipcntmultusnupsoynlvsenmisreamhoffepcntfaciltotscpwmeipcnttrdpjubnsenmmonamsntuptaenmjtupsomainedfjtupsoasgnnototepnumhomepagelast_load_dttm
0432500003250000-105-1992-0001007_21_02_PI2018-08-31 23:59:59.0<NA>한국은행 부산본부600091부산광역시 중구 대청동1가 44-0번지48949부산광역시 중구 대청로 112 (대청동1가)1992051520130724<NA><NA><NA>02폐업385292.68193300000180361.4383530000020130410154359집단급식소051-123-1234<NA><NA><NA><NA><NA>0N기타<NA>00.00기타<NA>집단급식소<NA><NA><NA><NA>2023-07-01 05:16:03
1532500003250000-105-1998-0001107_21_02_PI2018-08-31 23:59:59.0<NA>남성초등학교600091부산광역시 중구 대청동1가 10번지48926부산광역시 중구 샘길 14 (대청동1가)19980420<NA><NA><NA><NA>01영업385491.91116300000180721.2775450000020170706095724학교051-123-1234<NA><NA><NA><NA>상수도전용<NA>N기타<NA>0163.24<NA>기타<NA>학교<NA><NA><NA><NA>2023-07-01 05:16:03
2632500003250000-105-1998-0001207_21_02_PI2018-08-31 23:59:59.0<NA>보수초등학교600803부산광역시 중구 보수동1가 50-1번지48962부산광역시 중구 흑교로 74 (보수동1가)19980427<NA><NA><NA><NA>01영업384584.74633900000180738.1813280000020171027155552학교051-123-1234<NA><NA><NA><NA>상수도전용0N기타<NA>00.00기타<NA>학교<NA><NA><NA><NA>2023-07-01 05:16:03
3732500003250000-105-1998-0001307_21_02_PI2018-08-31 23:59:59.0<NA>봉래초등학교600811부산광역시 중구 영주동 580-0번지48922부산광역시 중구 대영로226번길 15 (영주동)19980427<NA><NA><NA><NA>01영업385676.15914800000181391.5549880000020170706095902학교051-123-1234<NA><NA><NA><NA>상수도전용0N기타<NA>0669.50기타<NA>학교<NA><NA><NA><NA>2023-07-01 05:16:03
4832500003250000-105-1998-0001407_21_02_PI2018-08-31 23:59:59.0<NA>부산삼육초등학교600810부산광역시 중구 영주동 63-31번지48910부산광역시 중구 초량상로5번길 28 (영주동)1998061920160331<NA><NA><NA>02폐업385436.10017500000181550.2232600000020150306113242집단급식소051-123-1234<NA><NA><NA><NA><NA><NA>N기타<NA>026.07<NA>기타<NA>집단급식소<NA><NA><NA><NA>2023-07-01 05:16:03
5932500003250000-105-1987-0000307_21_02_PI2018-08-31 23:59:59.0<NA>서라벌호텔직원식당600091부산광역시 중구 대청동1가 25-1번지48932부산광역시 중구 복병산길6번길 13 (대청동1가)1987062720131122<NA><NA><NA>02폐업385388.78044100000180457.9554980000020120127155127집단급식소051-123-1234<NA><NA><NA><NA><NA><NA>N기타<NA>00.0<NA>기타<NA>집단급식소<NA><NA><NA><NA>2023-07-01 05:16:03
61032500003250000-105-1987-0000707_21_02_PU2022-01-25 02:40:00.0집단급식소(재)천주교부산교구메리놀병원 집단급식소600800부산광역시 중구 대청동4가 12-048972부산광역시 중구 중구로 121 (대청동4가)19870627<NA><NA><NA><NA>영업/정상영업385245.491143612180646.52458601920220123145053병원051 4612398<NA>000상수도전용0N기타000.00기타0병원<NA><NA>0<NA>2023-07-01 05:16:03
71132500003250000-105-2018-0000307_21_02_PU2022-03-12 02:40:00.0집단급식소중구종합사회복지관600800부산광역시 중구 대청동4가 75-748904부산광역시 중구 망양로 309, 1층 (대청동4가)20180903<NA><NA><NA><NA>영업/정상영업384855.504330647180405.84014340420220310135631사회복지시설051 464 3137<NA><NA><NA><NA><NA><NA>N<NA>0053.5<NA><NA>0사회복지시설<NA><NA><NA><NA>2023-07-01 05:16:03
81232500003250000-105-2018-0000207_21_02_PU2022-01-25 02:40:00.0집단급식소휘림한방병원600714부산광역시 중구 중앙동6가 12 국제빌딩48942부산광역시 중구 중앙대로 26, 국제빌딩 5층 (중앙동6가)20180821<NA><NA><NA><NA>영업/정상영업385666.280865059179774.15839628120220123150109병원051 517 0050<NA>000상수도전용0N<NA>00118.080<NA>0병원<NA><NA>0<NA>2023-07-01 05:16:03
91332500003250000-105-1987-0000207_21_02_PU2022-01-25 02:40:00.0집단급식소코모도호텔600811부산광역시 중구 영주동 742-1348912부산광역시 중구 중구로 151 (영주동)19870627<NA><NA><NA><NA>영업/정상영업385475.543050054180776.20098975220220123152419산업체051 4669101<NA>000상수도전용0N기타000.00기타0산업체<NA><NA>0<NA>2023-07-01 05:16:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmfctyowkepcntfctypdtjobepcntfctysiljobepcntwtrsplyfacilsenmmaneipcntmultusnupsoynlvsenmisreamhoffepcntfaciltotscpwmeipcnttrdpjubnsenmmonamsntuptaenmjtupsomainedfjtupsoasgnnototepnumhomepagelast_load_dttm
51831130832900003290000-105-2021-0000307_21_02_PI2021-03-13 00:23:00.0집단급식소가람푸드614820부산광역시 부산진구 부암동 520-3<NA><NA>20210311<NA><NA><NA><NA>영업/정상영업385455.045842706187581.78844008920210311151130산업체<NA><NA><NA><NA><NA><NA><NA>N<NA>000.0<NA><NA>0산업체<NA><NA><NA><NA>2023-07-01 05:16:04
51841130933000003300000-105-2021-0000307_21_02_PU2022-08-28 02:40:00.0집단급식소주영어린이집607807부산광역시 동래구 명장동 302-147762부산광역시 동래구 시실로211번길 51, 1층 (명장동)20210312<NA><NA><NA><NA>영업/정상영업391146.135779306191937.45394777320220826171135어린이집<NA><NA>000상수도전용0N<NA>0013.50<NA>0어린이집<NA><NA>0<NA>2023-07-01 05:16:04
51851131033000003300000-105-2021-0000307_21_02_PU2022-08-28 02:40:00.0집단급식소주영어린이집607807부산광역시 동래구 명장동 302-147762부산광역시 동래구 시실로211번길 51, 1층 (명장동)20210312<NA><NA><NA><NA>영업/정상영업391146.135779306191937.45394777320220826171135어린이집<NA><NA>000상수도전용0N<NA>0013.50<NA>0어린이집<NA><NA>0<NA>2023-07-01 05:16:04
51861131133500003350000-105-2021-0000107_21_02_PU2021-11-06 02:40:00.0집단급식소다움병원609370부산광역시 금정구 두구동 298-2 동래병원46208부산광역시 금정구 체육공원로 608, 동래병원 (두구동)20210315<NA><NA><NA><NA>영업/정상영업392039.11769823201548.57090518520211104110047병원<NA><NA>000지하수전용0N<NA>0078.90<NA>0병원<NA><NA>0<NA>2023-07-01 05:16:04
51871131233200003320000-105-2021-0000207_21_02_PU2021-03-20 02:40:00.0집단급식소현대여울림유치원616751부산광역시 북구 구포동 1103-2 현대아파트46651부산광역시 북구 백양대로 1003 (구포동, 현대아파트)20210316<NA><NA><NA><NA>영업/정상영업381432.330084105190402.18326276720210318100509어린이집<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>70.39<NA><NA><NA>어린이집<NA><NA><NA><NA>2023-07-01 05:16:04
51881131332800003280000-105-2021-0000407_21_02_PU2021-04-01 02:40:00.0집단급식소영도구장애인복지관606809부산광역시 영도구 동삼동 516-1 영도어울림문화공원49114부산광역시 영도구 함지로79번길 6 (동삼동)20210318<NA><NA><NA><NA>영업/정상영업388368.918455131177053.82282152720210330161101사회복지시설051 403 6060<NA><NA><NA><NA><NA><NA>N<NA><NA><NA>0.0<NA><NA><NA>사회복지시설<NA><NA><NA><NA>2023-07-01 05:16:04
51891132033600003360000-120-2021-0000307_21_01_PI2021-04-02 00:22:59.0위탁급식영업동헌레미콘 구내식당618230부산광역시 강서구 지사동 134-246749부산광역시 강서구 명동길 47 (지사동)20210331폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업367732.539887136183873.58753598920210331151833위탁급식영업전화번호건물소유구분명공장사무직종업원수공장생산직종업원수공장판매직종업원수급수시설구분명남성종사자수N등급구분명보증액본사종업원수0.0여성종사자수영업장주변구분명월세액위탁급식영업전통업소주된음식전통업소지정번호총종업원수홈페이지2023-07-01 05:16:04
51901132132800003280000-105-2021-0000607_21_02_PU2022-04-28 02:40:00.0집단급식소라발스호텔 직원식당606061부산광역시 영도구 봉래동1가 29 라발스 호텔 부산49033부산광역시 영도구 봉래나루로 82, 라발스 호텔 부산 2층 (봉래동1가)20210331<NA><NA><NA><NA>영업/정상영업385874.95130923179172.63914377120220426114639산업체051 293 1624<NA><NA><NA><NA><NA><NA>N<NA>0072.38<NA><NA>0산업체<NA><NA><NA><NA>2023-07-01 05:16:04
51911132233400003340000-105-2021-0000207_21_02_PU2021-04-14 02:40:00.0집단급식소사하뷰웰어린이집604838부산광역시 사하구 신평동 669 사하 뷰웰49418부산광역시 사하구 신산북로43번길 59 (신평동, 사하 뷰웰)20210331<NA><NA><NA><NA>영업/정상영업379738.857250898179113.16188729820210412115140어린이집<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>11.75<NA><NA><NA>어린이집<NA><NA><NA><NA>2023-07-01 05:16:04
51921132333600003360000-105-2021-0000707_21_02_PI2021-04-02 00:22:59.0집단급식소(주)동헌레미콘618230부산광역시 강서구 지사동 134-246749부산광역시 강서구 명동길 47 (지사동)20210331<NA><NA><NA><NA>영업/정상영업367732.539887136183873.58753598920210331152105산업체051 972 8701<NA><NA><NA><NA><NA><NA>N<NA>000.0<NA><NA>0산업체<NA><NA><NA><NA>2023-07-01 05:16:04