Overview

Dataset statistics

Number of variables70
Number of observations10000
Missing cells449082
Missing cells (%)64.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 MiB
Average record size in memory577.0 B

Variable types

Numeric9
Text19
Categorical7
DateTime2
Unsupported33

Alerts

ropnymd has constant value ""Constant
sitetel has constant value ""Constant
etcepcnt has constant value ""Constant
astnepnum has constant value ""Constant
facilmngnum has constant value ""Constant
mitmdcdepnm has constant value ""Constant
mitmdcasgntype has constant value ""Constant
batrar has constant value ""Constant
metrbosassrnm has constant value ""Constant
qutnownernum has constant value ""Constant
epcnt has constant value ""Constant
medextritemscn has constant value ""Constant
medextritemscnnm has constant value ""Constant
totepnum has constant value ""Constant
frstasgnymd has constant value ""Constant
updategbn is highly imbalanced (98.0%)Imbalance
opnsvcnm is highly imbalanced (99.5%)Imbalance
dtlstatenm is highly imbalanced (55.6%)Imbalance
metrorgassrnm is highly imbalanced (56.5%)Imbalance
sitepostno has 3353 (33.5%) missing valuesMissing
sitewhladdr has 895 (8.9%) missing valuesMissing
rdnpostno has 2142 (21.4%) missing valuesMissing
rdnwhladdr has 867 (8.7%) missing valuesMissing
dcbymd has 5807 (58.1%) missing valuesMissing
clgstdt has 9935 (99.4%) missing valuesMissing
clgenddt has 9935 (99.4%) missing valuesMissing
ropnymd has 9999 (> 99.9%) missing valuesMissing
x has 851 (8.5%) missing valuesMissing
y has 851 (8.5%) missing valuesMissing
nursecnt has 9973 (99.7%) missing valuesMissing
nursaidcnt has 9973 (99.7%) missing valuesMissing
bdnglayercnt has 9975 (99.8%) missing valuesMissing
emercargen has 5971 (59.7%) missing valuesMissing
emercarspec has 5971 (59.7%) missing valuesMissing
rescnt has 9996 (> 99.9%) missing valuesMissing
pomfacilar has 9989 (99.9%) missing valuesMissing
etcstfcnt has 9993 (99.9%) missing valuesMissing
etcepcnt has 9999 (> 99.9%) missing valuesMissing
mmknurmar has 9980 (99.8%) missing valuesMissing
btrmar has 9992 (99.9%) missing valuesMissing
btpnum has 9988 (99.9%) missing valuesMissing
sicbnum has 5968 (59.7%) missing valuesMissing
astnepnum has 9999 (> 99.9%) missing valuesMissing
ofear has 9986 (99.9%) missing valuesMissing
warmar has 9989 (99.9%) missing valuesMissing
facilmngnum has 9999 (> 99.9%) missing valuesMissing
pharmtrdar has 7317 (73.2%) missing valuesMissing
nutrcnt has 9989 (99.9%) missing valuesMissing
bbrmar has 9973 (99.7%) missing valuesMissing
babyrglstnum has 9970 (99.7%) missing valuesMissing
mitmdcdepnm has 9999 (> 99.9%) missing valuesMissing
mitmdcasgntype has 9999 (> 99.9%) missing valuesMissing
batrar has 9999 (> 99.9%) missing valuesMissing
metrbosassrnm has 9999 (> 99.9%) missing valuesMissing
metrpnum has 5972 (59.7%) missing valuesMissing
pgrmar has 9974 (99.7%) missing valuesMissing
pwnmrglstnum has 9970 (99.7%) missing valuesMissing
hstrmnum has 5968 (59.7%) missing valuesMissing
qutnownernum has 9999 (> 99.9%) missing valuesMissing
joriwontoilar has 9986 (99.9%) missing valuesMissing
epcnt has 9999 (> 99.9%) missing valuesMissing
jisgnumlay has 9980 (99.8%) missing valuesMissing
asgnymd has 7315 (73.2%) missing valuesMissing
asgncancelymd has 9646 (96.5%) missing valuesMissing
undernumlay has 9993 (99.9%) missing valuesMissing
medextritemscn has 9999 (> 99.9%) missing valuesMissing
medextritemscnnm has 9999 (> 99.9%) missing valuesMissing
totar has 5968 (59.7%) missing valuesMissing
totepnum has 9999 (> 99.9%) missing valuesMissing
frstasgnymd has 9999 (> 99.9%) missing valuesMissing
copnum has 9987 (99.9%) missing valuesMissing
storetrdar has 5074 (50.7%) missing valuesMissing
pmtbednum has 9629 (96.3%) missing valuesMissing
opnsfteamcode is highly skewed (γ1 = 26.13097118)Skewed
skey has unique valuesUnique
mgtno has unique valuesUnique
sitepostno is an unsupported type, check if it needs cleaning or further analysisUnsupported
dcbymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
trdstatenm is an unsupported type, check if it needs cleaning or further analysisUnsupported
nursecnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
nursaidcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
bdnglayercnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
emercargen is an unsupported type, check if it needs cleaning or further analysisUnsupported
emercarspec is an unsupported type, check if it needs cleaning or further analysisUnsupported
rescnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
pomfacilar is an unsupported type, check if it needs cleaning or further analysisUnsupported
etcstfcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
mmknurmar is an unsupported type, check if it needs cleaning or further analysisUnsupported
btrmar is an unsupported type, check if it needs cleaning or further analysisUnsupported
btpnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
sicbnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
ofear is an unsupported type, check if it needs cleaning or further analysisUnsupported
warmar is an unsupported type, check if it needs cleaning or further analysisUnsupported
pharmtrdar is an unsupported type, check if it needs cleaning or further analysisUnsupported
nutrcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
bbrmar is an unsupported type, check if it needs cleaning or further analysisUnsupported
babyrglstnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
metrpnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
pgrmar is an unsupported type, check if it needs cleaning or further analysisUnsupported
pwnmrglstnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
hstrmnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
joriwontoilar is an unsupported type, check if it needs cleaning or further analysisUnsupported
jisgnumlay is an unsupported type, check if it needs cleaning or further analysisUnsupported
asgnymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
undernumlay is an unsupported type, check if it needs cleaning or further analysisUnsupported
totar is an unsupported type, check if it needs cleaning or further analysisUnsupported
copnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
storetrdar is an unsupported type, check if it needs cleaning or further analysisUnsupported
pmtbednum is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 21:50:40.450808
Analysis finished2024-04-16 21:50:42.238061
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8356.543
Minimum563
Maximum16082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:42.290912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum563
5-th percentile1358.95
Q14429.25
median8382.5
Q312273.25
95-th percentile15318.1
Maximum16082
Range15519
Interquartile range (IQR)7844

Descriptive statistics

Standard deviation4497.142
Coefficient of variation (CV)0.53815818
Kurtosis-1.2151588
Mean8356.543
Median Absolute Deviation (MAD)3917.5
Skewness-0.0041860928
Sum83565430
Variance20224286
MonotonicityNot monotonic
2024-04-17T06:50:42.430414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15975 1
 
< 0.1%
4732 1
 
< 0.1%
11205 1
 
< 0.1%
12424 1
 
< 0.1%
10811 1
 
< 0.1%
9911 1
 
< 0.1%
1042 1
 
< 0.1%
675 1
 
< 0.1%
10819 1
 
< 0.1%
10874 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
563 1
< 0.1%
564 1
< 0.1%
565 1
< 0.1%
566 1
< 0.1%
569 1
< 0.1%
570 1
< 0.1%
571 1
< 0.1%
572 1
< 0.1%
573 1
< 0.1%
576 1
< 0.1%
ValueCountFrequency (%)
16082 1
< 0.1%
16080 1
< 0.1%
16079 1
< 0.1%
16077 1
< 0.1%
16076 1
< 0.1%
16075 1
< 0.1%
16074 1
< 0.1%
16073 1
< 0.1%
16071 1
< 0.1%
16069 1
< 0.1%

opnsfteamcode
Real number (ℝ)

SKEWED 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3328298
Minimum3250000
Maximum6260000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:42.535379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum6260000
Range3010000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation77314.041
Coefficient of variation (CV)0.023229302
Kurtosis934.59286
Mean3328298
Median Absolute Deviation (MAD)30000
Skewness26.130971
Sum3.328298 × 1010
Variance5.9774609 × 109
MonotonicityNot monotonic
2024-04-17T06:50:42.619301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3290000 1309
13.1%
3350000 1184
11.8%
3330000 1138
11.4%
3340000 914
9.1%
3300000 776
7.8%
3310000 717
7.2%
3320000 602
 
6.0%
3370000 583
 
5.8%
3380000 556
 
5.6%
3390000 458
 
4.6%
Other values (12) 1763
17.6%
ValueCountFrequency (%)
3250000 288
 
2.9%
3260000 342
 
3.4%
3270000 331
 
3.3%
3280000 261
 
2.6%
3290000 1309
13.1%
3300000 776
7.8%
3310000 717
7.2%
3320000 602
6.0%
3330000 1138
11.4%
3340000 914
9.1%
ValueCountFrequency (%)
6260000 4
 
< 0.1%
5540000 1
 
< 0.1%
5120000 1
 
< 0.1%
4820000 1
 
< 0.1%
3780000 1
 
< 0.1%
3600000 1
 
< 0.1%
3400000 339
3.4%
3390000 458
4.6%
3380000 556
5.6%
3370000 583
5.8%

mgtno
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:42.784731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length24.9972
Min length18

Characters and Unicode

Total characters249972
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowPHMD120183400013084000005
2nd rowPHMD120003350024084000031
3rd rowPHMD120133320045084000002
4th rowPHMH320173320045087500013
5th rowPHMD120093270022084000003
ValueCountFrequency (%)
phmd120183400013084000005 1
 
< 0.1%
phma220123290024021200001 1
 
< 0.1%
phma120003290024041100006 1
 
< 0.1%
phmd119863250021084000002 1
 
< 0.1%
phmh320173360024087500006 1
 
< 0.1%
phmd120153270022084000008 1
 
< 0.1%
phmh320143340025087500013 1
 
< 0.1%
phmh320123310024087500064 1
 
< 0.1%
phma220053380023021200001 1
 
< 0.1%
phma120073320045041200002 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T06:50:43.062659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81266
32.5%
1 31095
 
12.4%
2 26448
 
10.6%
3 24539
 
9.8%
4 17030
 
6.8%
H 11963
 
4.8%
P 9996
 
4.0%
M 9996
 
4.0%
8 8014
 
3.2%
5 7077
 
2.8%
Other values (6) 22548
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 209988
84.0%
Uppercase Letter 39984
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81266
38.7%
1 31095
 
14.8%
2 26448
 
12.6%
3 24539
 
11.7%
4 17030
 
8.1%
8 8014
 
3.8%
5 7077
 
3.4%
9 6614
 
3.1%
7 5190
 
2.5%
6 2715
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
H 11963
29.9%
P 9996
25.0%
M 9996
25.0%
A 5316
13.3%
D 2684
 
6.7%
B 29
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 209988
84.0%
Latin 39984
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81266
38.7%
1 31095
 
14.8%
2 26448
 
12.6%
3 24539
 
11.7%
4 17030
 
8.1%
8 8014
 
3.8%
5 7077
 
3.4%
9 6614
 
3.1%
7 5190
 
2.5%
6 2715
 
1.3%
Latin
ValueCountFrequency (%)
H 11963
29.9%
P 9996
25.0%
M 9996
25.0%
A 5316
13.3%
D 2684
 
6.7%
B 29
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81266
32.5%
1 31095
 
12.4%
2 26448
 
10.6%
3 24539
 
9.8%
4 17030
 
6.8%
H 11963
 
4.8%
P 9996
 
4.0%
M 9996
 
4.0%
8 8014
 
3.2%
5 7077
 
2.8%
Other values (6) 22548
 
9.0%

opnsvcid
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
01_01_02_P
4946 
01_01_06_P
2684 
01_01_05_P
1967 
01_01_01_P
 
353
01_01_04_P
 
29
Other values (2)
 
21

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_01_06_P
2nd row01_01_06_P
3rd row01_01_06_P
4th row01_01_05_P
5th row01_01_06_P

Common Values

ValueCountFrequency (%)
01_01_02_P 4946
49.5%
01_01_06_P 2684
26.8%
01_01_05_P 1967
 
19.7%
01_01_01_P 353
 
3.5%
01_01_04_P 29
 
0.3%
01_01_03_P 17
 
0.2%
01_01_07_P 4
 
< 0.1%

Length

2024-04-17T06:50:43.353381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:43.436032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_01_02_p 4946
49.5%
01_01_06_p 2684
26.8%
01_01_05_p 1967
 
19.7%
01_01_01_p 353
 
3.5%
01_01_04_p 29
 
0.3%
01_01_03_p 17
 
0.2%
01_01_07_p 4
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9981 
U
 
19

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 9981
99.8%
U 19
 
0.2%

Length

2024-04-17T06:50:43.531240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:43.618975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9981
99.8%
u 19
 
0.2%

updatedt
Date

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2018-10-18 02:35:27
2024-04-17T06:50:43.681552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:50:43.765890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

opnsvcnm
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9994 
안전상비의약품 판매업소
 
5
약국
 
1

Length

Max length12
Median length4
Mean length4.0038
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9994
99.9%
안전상비의약품 판매업소 5
 
0.1%
약국 1
 
< 0.1%

Length

2024-04-17T06:50:43.884104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:43.999752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9994
99.9%
안전상비의약품 5
 
< 0.1%
판매업소 5
 
< 0.1%
약국 1
 
< 0.1%

bplcnm
Text

Distinct7714
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:44.230685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length7.2777
Min length3

Characters and Unicode

Total characters72777
Distinct characters692
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6642 ?
Unique (%)66.4%

Sample

1st row도담약국
2nd row현대약국
3rd row대학로약국
4th row씨유 화명롯데카이저점
5th row동아사약국
ValueCountFrequency (%)
gs25 290
 
2.4%
씨유 261
 
2.2%
세븐일레븐 186
 
1.6%
미니스톱 105
 
0.9%
cu 84
 
0.7%
약국 66
 
0.6%
주)코리아세븐 64
 
0.5%
의료법인 58
 
0.5%
한의원 48
 
0.4%
의원 47
 
0.4%
Other values (7881) 10676
89.8%
2024-04-17T06:50:44.569849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 5620
 
7.7%
의 5504
 
7.6%
과 2837
 
3.9%
국 2753
 
3.8%
약 2692
 
3.7%
1898
 
2.6%
점 1873
 
2.6%
한 1756
 
2.4%
치 1191
 
1.6%
부 1094
 
1.5%
Other values (682) 45559
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67159
92.3%
Space Separator 1898
 
2.6%
Uppercase Letter 1578
 
2.2%
Decimal Number 1465
 
2.0%
Close Punctuation 284
 
0.4%
Open Punctuation 271
 
0.4%
Lowercase Letter 77
 
0.1%
Other Punctuation 32
 
< 0.1%
Dash Punctuation 11
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 5620
 
8.4%
의 5504
 
8.2%
과 2837
 
4.2%
국 2753
 
4.1%
약 2692
 
4.0%
점 1873
 
2.8%
한 1756
 
2.6%
치 1191
 
1.8%
부 1094
 
1.6%
산 1055
 
1.6%
Other values (621) 40784
60.7%
Uppercase Letter
ValueCountFrequency (%)
S 594
37.6%
G 557
35.3%
C 147
 
9.3%
U 136
 
8.6%
K 30
 
1.9%
B 14
 
0.9%
L 11
 
0.7%
N 11
 
0.7%
M 10
 
0.6%
H 10
 
0.6%
Other values (14) 58
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
e 34
44.2%
h 8
 
10.4%
c 5
 
6.5%
i 5
 
6.5%
a 3
 
3.9%
l 3
 
3.9%
r 3
 
3.9%
t 3
 
3.9%
u 3
 
3.9%
n 2
 
2.6%
Other values (7) 8
 
10.4%
Decimal Number
ValueCountFrequency (%)
2 706
48.2%
5 622
42.5%
4 53
 
3.6%
1 35
 
2.4%
3 22
 
1.5%
0 8
 
0.5%
6 7
 
0.5%
7 6
 
0.4%
9 5
 
0.3%
8 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 10
31.2%
& 9
28.1%
· 7
21.9%
, 5
15.6%
@ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
1898
100.0%
Close Punctuation
ValueCountFrequency (%)
) 284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67151
92.3%
Common 3961
 
5.4%
Latin 1655
 
2.3%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 5620
 
8.4%
의 5504
 
8.2%
과 2837
 
4.2%
국 2753
 
4.1%
약 2692
 
4.0%
점 1873
 
2.8%
한 1756
 
2.6%
치 1191
 
1.8%
부 1094
 
1.6%
산 1055
 
1.6%
Other values (613) 40776
60.7%
Latin
ValueCountFrequency (%)
S 594
35.9%
G 557
33.7%
C 147
 
8.9%
U 136
 
8.2%
e 34
 
2.1%
K 30
 
1.8%
B 14
 
0.8%
L 11
 
0.7%
N 11
 
0.7%
M 10
 
0.6%
Other values (31) 111
 
6.7%
Common
ValueCountFrequency (%)
1898
47.9%
2 706
 
17.8%
5 622
 
15.7%
) 284
 
7.2%
( 271
 
6.8%
4 53
 
1.3%
1 35
 
0.9%
3 22
 
0.6%
- 11
 
0.3%
. 10
 
0.3%
Other values (9) 49
 
1.2%
Han
ValueCountFrequency (%)
美 2
20.0%
林 1
10.0%
菊 1
10.0%
東 1
10.0%
長 1
10.0%
韓 1
10.0%
人 1
10.0%
名 1
10.0%
安 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67148
92.3%
ASCII 5609
 
7.7%
CJK 10
 
< 0.1%
None 9
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 5620
 
8.4%
의 5504
 
8.2%
과 2837
 
4.2%
국 2753
 
4.1%
약 2692
 
4.0%
점 1873
 
2.8%
한 1756
 
2.6%
치 1191
 
1.8%
부 1094
 
1.6%
산 1055
 
1.6%
Other values (611) 40773
60.7%
ASCII
ValueCountFrequency (%)
1898
33.8%
2 706
 
12.6%
5 622
 
11.1%
S 594
 
10.6%
G 557
 
9.9%
) 284
 
5.1%
( 271
 
4.8%
C 147
 
2.6%
U 136
 
2.4%
4 53
 
0.9%
Other values (49) 341
 
6.1%
None
ValueCountFrequency (%)
· 7
77.8%
㈜ 2
 
22.2%
CJK
ValueCountFrequency (%)
美 2
20.0%
林 1
10.0%
菊 1
10.0%
東 1
10.0%
長 1
10.0%
韓 1
10.0%
人 1
10.0%
名 1
10.0%
安 1
10.0%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%

sitepostno
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3353
Missing (%)33.5%
Memory size156.2 KiB

sitewhladdr
Text

MISSING 

Distinct7564
Distinct (%)83.1%
Missing895
Missing (%)8.9%
Memory size156.2 KiB
2024-04-17T06:50:44.870138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length53
Mean length23.937946
Min length1

Characters and Unicode

Total characters217955
Distinct characters461
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6557 ?
Unique (%)72.0%

Sample

1st row부산광역시 기장군 정관읍 매학리 720번지 7호
2nd row부산광역시 금정구 남산동 225번지 34호
3rd row부산광역시 북구 화명동 2314번지 1호
4th row부산광역시 동구 범일2동 640번지 5호
5th row부산광역시해운대구중1동1394-385
ValueCountFrequency (%)
부산광역시 8860
 
19.3%
부산진구 1184
 
2.6%
금정구 1178
 
2.6%
1호 1046
 
2.3%
해운대구 963
 
2.1%
사하구 875
 
1.9%
동래구 679
 
1.5%
남구 650
 
1.4%
연제구 523
 
1.1%
북구 523
 
1.1%
Other values (5003) 29463
64.1%
2024-04-17T06:50:45.326125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36954
 
17.0%
부 11147
 
5.1%
1 10988
 
5.0%
산 10815
 
5.0%
동 10222
 
4.7%
광 9233
 
4.2%
구 9114
 
4.2%
시 9020
 
4.1%
역 8940
 
4.1%
지 7552
 
3.5%
Other values (451) 93970
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130340
59.8%
Decimal Number 47463
 
21.8%
Space Separator 36954
 
17.0%
Dash Punctuation 1699
 
0.8%
Other Punctuation 480
 
0.2%
Open Punctuation 343
 
0.2%
Close Punctuation 341
 
0.2%
Uppercase Letter 234
 
0.1%
Math Symbol 67
 
< 0.1%
Lowercase Letter 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 11147
 
8.6%
산 10815
 
8.3%
동 10222
 
7.8%
광 9233
 
7.1%
구 9114
 
7.0%
시 9020
 
6.9%
역 8940
 
6.9%
지 7552
 
5.8%
호 7401
 
5.7%
번 7238
 
5.6%
Other values (390) 39658
30.4%
Uppercase Letter
ValueCountFrequency (%)
A 36
15.4%
B 35
15.0%
S 22
 
9.4%
K 20
 
8.5%
G 15
 
6.4%
F 14
 
6.0%
L 13
 
5.6%
C 8
 
3.4%
I 8
 
3.4%
E 8
 
3.4%
Other values (15) 55
23.5%
Lowercase Letter
ValueCountFrequency (%)
e 7
21.2%
s 6
18.2%
i 3
9.1%
k 3
9.1%
a 3
9.1%
n 2
 
6.1%
u 2
 
6.1%
r 2
 
6.1%
q 2
 
6.1%
j 1
 
3.0%
Other values (2) 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 10988
23.2%
2 7266
15.3%
3 5553
11.7%
4 4541
9.6%
5 3921
 
8.3%
6 3298
 
6.9%
0 3293
 
6.9%
7 3256
 
6.9%
8 2801
 
5.9%
9 2546
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 441
91.9%
@ 21
 
4.4%
. 9
 
1.9%
/ 7
 
1.5%
· 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 341
99.4%
[ 2
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 338
99.1%
] 3
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 66
98.5%
∼ 1
 
1.5%
Space Separator
ValueCountFrequency (%)
36954
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1699
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130340
59.8%
Common 87347
40.1%
Latin 268
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 11147
 
8.6%
산 10815
 
8.3%
동 10222
 
7.8%
광 9233
 
7.1%
구 9114
 
7.0%
시 9020
 
6.9%
역 8940
 
6.9%
지 7552
 
5.8%
호 7401
 
5.7%
번 7238
 
5.6%
Other values (390) 39658
30.4%
Latin
ValueCountFrequency (%)
A 36
13.4%
B 35
 
13.1%
S 22
 
8.2%
K 20
 
7.5%
G 15
 
5.6%
F 14
 
5.2%
L 13
 
4.9%
C 8
 
3.0%
I 8
 
3.0%
E 8
 
3.0%
Other values (28) 89
33.2%
Common
ValueCountFrequency (%)
36954
42.3%
1 10988
 
12.6%
2 7266
 
8.3%
3 5553
 
6.4%
4 4541
 
5.2%
5 3921
 
4.5%
6 3298
 
3.8%
0 3293
 
3.8%
7 3256
 
3.7%
8 2801
 
3.2%
Other values (13) 5476
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130337
59.8%
ASCII 87611
40.2%
Compat Jamo 3
 
< 0.1%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36954
42.2%
1 10988
 
12.5%
2 7266
 
8.3%
3 5553
 
6.3%
4 4541
 
5.2%
5 3921
 
4.5%
6 3298
 
3.8%
0 3293
 
3.8%
7 3256
 
3.7%
8 2801
 
3.2%
Other values (48) 5740
 
6.6%
Hangul
ValueCountFrequency (%)
부 11147
 
8.6%
산 10815
 
8.3%
동 10222
 
7.8%
광 9233
 
7.1%
구 9114
 
7.0%
시 9020
 
6.9%
역 8940
 
6.9%
지 7552
 
5.8%
호 7401
 
5.7%
번 7238
 
5.6%
Other values (387) 39655
30.4%
None
ValueCountFrequency (%)
· 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
33.3%
ㅏ 1
33.3%
ㅓ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1887
Distinct (%)24.0%
Missing2142
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean139652.5
Minimum12800
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:45.439771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12800
5-th percentile46241.7
Q147241
median48060
Q349211
95-th percentile614101
Maximum619963
Range607163
Interquartile range (IQR)1970

Descriptive statistics

Standard deviation208143.54
Coefficient of variation (CV)1.490439
Kurtosis1.3280929
Mean139652.5
Median Absolute Deviation (MAD)936
Skewness1.8239061
Sum1.0973894 × 109
Variance4.3323734 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:45.544203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47286 65
 
0.7%
47257 61
 
0.6%
48060 60
 
0.6%
48095 54
 
0.5%
46576 49
 
0.5%
46015 43
 
0.4%
46526 41
 
0.4%
48111 39
 
0.4%
46726 39
 
0.4%
46243 37
 
0.4%
Other values (1877) 7370
73.7%
(Missing) 2142
 
21.4%
ValueCountFrequency (%)
12800 1
 
< 0.1%
13246 1
 
< 0.1%
36917 1
 
< 0.1%
46002 4
 
< 0.1%
46007 4
 
< 0.1%
46008 19
0.2%
46010 1
 
< 0.1%
46012 5
 
0.1%
46013 5
 
0.1%
46014 2
 
< 0.1%
ValueCountFrequency (%)
619963 17
0.2%
619962 3
 
< 0.1%
619961 2
 
< 0.1%
619952 3
 
< 0.1%
619951 3
 
< 0.1%
619950 1
 
< 0.1%
619912 4
 
< 0.1%
619906 4
 
< 0.1%
619905 15
0.1%
619904 2
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct7545
Distinct (%)82.6%
Missing867
Missing (%)8.7%
Memory size156.2 KiB
2024-04-17T06:50:45.840922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length56
Mean length28.376875
Min length19

Characters and Unicode

Total characters259166
Distinct characters531
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6494 ?
Unique (%)71.1%

Sample

1st row부산광역시 기장군 정관읍 정관6로 31, 105호
2nd row부산광역시 금정구 중앙대로 2001 (남산동)
3rd row부산광역시 북구 학사로 15 (화명동)
4th row부산광역시 북구 금곡대로 166, 907동 101호 (화명동, 화명롯데캐슬카이저)
5th row부산광역시 동구 진시장로 19-2 (범일동)
ValueCountFrequency (%)
부산광역시 9127
 
17.6%
부산진구 1181
 
2.3%
금정구 1082
 
2.1%
해운대구 1033
 
2.0%
사하구 796
 
1.5%
동래구 742
 
1.4%
북구 581
 
1.1%
1층 573
 
1.1%
중앙대로 554
 
1.1%
연제구 552
 
1.1%
Other values (5088) 35531
68.7%
2024-04-17T06:50:46.272272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42634
 
16.5%
동 11583
 
4.5%
부 11484
 
4.4%
산 11202
 
4.3%
광 9644
 
3.7%
시 9569
 
3.7%
구 9426
 
3.6%
역 9134
 
3.5%
로 9076
 
3.5%
( 8955
 
3.5%
Other values (521) 126459
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153988
59.4%
Space Separator 42634
 
16.5%
Decimal Number 37475
 
14.5%
Open Punctuation 8956
 
3.5%
Close Punctuation 8955
 
3.5%
Other Punctuation 5627
 
2.2%
Dash Punctuation 1037
 
0.4%
Uppercase Letter 302
 
0.1%
Math Symbol 133
 
0.1%
Lowercase Letter 59
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11583
 
7.5%
부 11484
 
7.5%
산 11202
 
7.3%
광 9644
 
6.3%
시 9569
 
6.2%
구 9426
 
6.1%
역 9134
 
5.9%
로 9076
 
5.9%
대 4871
 
3.2%
층 2614
 
1.7%
Other values (460) 65385
42.5%
Uppercase Letter
ValueCountFrequency (%)
B 55
18.2%
A 43
14.2%
S 29
9.6%
K 24
 
7.9%
C 20
 
6.6%
G 17
 
5.6%
E 16
 
5.3%
L 12
 
4.0%
I 11
 
3.6%
D 9
 
3.0%
Other values (14) 66
21.9%
Lowercase Letter
ValueCountFrequency (%)
e 16
27.1%
s 8
13.6%
a 6
 
10.2%
r 5
 
8.5%
q 4
 
6.8%
u 4
 
6.8%
i 4
 
6.8%
n 3
 
5.1%
k 2
 
3.4%
c 2
 
3.4%
Other values (4) 5
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 8477
22.6%
2 5845
15.6%
3 4147
11.1%
0 3532
9.4%
4 3397
9.1%
5 2923
 
7.8%
7 2483
 
6.6%
6 2472
 
6.6%
9 2143
 
5.7%
8 2056
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 5599
99.5%
. 17
 
0.3%
@ 6
 
0.1%
· 3
 
0.1%
/ 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 8955
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8954
> 99.9%
] 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 132
99.2%
∼ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
42634
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1037
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153988
59.4%
Common 104817
40.4%
Latin 361
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11583
 
7.5%
부 11484
 
7.5%
산 11202
 
7.3%
광 9644
 
6.3%
시 9569
 
6.2%
구 9426
 
6.1%
역 9134
 
5.9%
로 9076
 
5.9%
대 4871
 
3.2%
층 2614
 
1.7%
Other values (460) 65385
42.5%
Latin
ValueCountFrequency (%)
B 55
15.2%
A 43
 
11.9%
S 29
 
8.0%
K 24
 
6.6%
C 20
 
5.5%
G 17
 
4.7%
e 16
 
4.4%
E 16
 
4.4%
L 12
 
3.3%
I 11
 
3.0%
Other values (28) 118
32.7%
Common
ValueCountFrequency (%)
42634
40.7%
( 8955
 
8.5%
) 8954
 
8.5%
1 8477
 
8.1%
2 5845
 
5.6%
, 5599
 
5.3%
3 4147
 
4.0%
0 3532
 
3.4%
4 3397
 
3.2%
5 2923
 
2.8%
Other values (13) 10354
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153988
59.4%
ASCII 105174
40.6%
None 3
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42634
40.5%
( 8955
 
8.5%
) 8954
 
8.5%
1 8477
 
8.1%
2 5845
 
5.6%
, 5599
 
5.3%
3 4147
 
3.9%
0 3532
 
3.4%
4 3397
 
3.2%
5 2923
 
2.8%
Other values (49) 10711
 
10.2%
Hangul
ValueCountFrequency (%)
동 11583
 
7.5%
부 11484
 
7.5%
산 11202
 
7.3%
광 9644
 
6.3%
시 9569
 
6.2%
구 9426
 
6.1%
역 9134
 
5.9%
로 9076
 
5.9%
대 4871
 
3.2%
층 2614
 
1.7%
Other values (460) 65385
42.5%
None
ValueCountFrequency (%)
· 3
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

apvpermymd
Real number (ℝ)

Distinct5230
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20056953
Minimum19590110
Maximum20181017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:46.389506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19590110
5-th percentile19830517
Q120010118
median20090814
Q320140306
95-th percentile20171023
Maximum20181017
Range590907
Interquartile range (IQR)130188

Descriptive statistics

Standard deviation110504.47
Coefficient of variation (CV)0.0055095341
Kurtosis1.3781803
Mean20056953
Median Absolute Deviation (MAD)59915
Skewness-1.3090402
Sum2.0056953 × 1011
Variance1.2211237 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:46.499823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121112 113
 
1.1%
20121109 83
 
0.8%
20121115 82
 
0.8%
20121114 71
 
0.7%
20121116 65
 
0.7%
20121113 65
 
0.7%
20121108 46
 
0.5%
20121107 29
 
0.3%
20121106 22
 
0.2%
20121105 16
 
0.2%
Other values (5220) 9408
94.1%
ValueCountFrequency (%)
19590110 1
< 0.1%
19590207 1
< 0.1%
19600101 1
< 0.1%
19610418 1
< 0.1%
19611107 1
< 0.1%
19620310 1
< 0.1%
19620312 1
< 0.1%
19620313 1
< 0.1%
19620503 1
< 0.1%
19630101 1
< 0.1%
ValueCountFrequency (%)
20181017 1
 
< 0.1%
20181016 5
0.1%
20180904 1
 
< 0.1%
20180903 4
< 0.1%
20180901 1
 
< 0.1%
20180831 2
 
< 0.1%
20180830 5
0.1%
20180829 5
0.1%
20180828 2
 
< 0.1%
20180827 3
< 0.1%

dcbymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5807
Missing (%)58.1%
Memory size156.2 KiB

clgstdt
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)98.5%
Missing9935
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20128302
Minimum20000403
Maximum20180829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:46.634984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20082665
Q120100901
median20121020
Q320170307
95-th percentile20180585
Maximum20180829
Range180426
Interquartile range (IQR)69406

Descriptive statistics

Standard deviation39690.145
Coefficient of variation (CV)0.0019718576
Kurtosis0.76549237
Mean20128302
Median Absolute Deviation (MAD)20911
Skewness-0.61213069
Sum1.3083396 × 109
Variance1.5753076 × 109
MonotonicityNot monotonic
2024-04-17T06:50:46.755987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110706 2
 
< 0.1%
20171002 1
 
< 0.1%
20161010 1
 
< 0.1%
20120827 1
 
< 0.1%
20140811 1
 
< 0.1%
20110511 1
 
< 0.1%
20090702 1
 
< 0.1%
20180703 1
 
< 0.1%
20170822 1
 
< 0.1%
20090615 1
 
< 0.1%
Other values (54) 54
 
0.5%
(Missing) 9935
99.4%
ValueCountFrequency (%)
20000403 1
< 0.1%
20020101 1
< 0.1%
20051001 1
< 0.1%
20080801 1
< 0.1%
20090120 1
< 0.1%
20090202 1
< 0.1%
20090615 1
< 0.1%
20090702 1
< 0.1%
20090824 1
< 0.1%
20091130 1
< 0.1%
ValueCountFrequency (%)
20180829 1
< 0.1%
20180723 1
< 0.1%
20180703 1
< 0.1%
20180626 1
< 0.1%
20180420 1
< 0.1%
20180328 1
< 0.1%
20180224 1
< 0.1%
20180219 1
< 0.1%
20180201 1
< 0.1%
20180101 1
< 0.1%

clgenddt
Real number (ℝ)

MISSING 

Distinct60
Distinct (%)92.3%
Missing9935
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20135634
Minimum20000403
Maximum20221227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:46.875322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20090411
Q120110331
median20131231
Q320170904
95-th percentile20190125
Maximum20221227
Range220824
Interquartile range (IQR)60573

Descriptive statistics

Standard deviation41768.691
Coefficient of variation (CV)0.0020743668
Kurtosis0.79870616
Mean20135634
Median Absolute Deviation (MAD)30504
Skewness-0.56418206
Sum1.3088162 × 109
Variance1.7446236 × 109
MonotonicityNot monotonic
2024-04-17T06:50:46.981963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131231 3
 
< 0.1%
20111205 2
 
< 0.1%
20170531 2
 
< 0.1%
20121231 2
 
< 0.1%
20100228 1
 
< 0.1%
20181031 1
 
< 0.1%
20080731 1
 
< 0.1%
20101031 1
 
< 0.1%
20190221 1
 
< 0.1%
20171002 1
 
< 0.1%
Other values (50) 50
 
0.5%
(Missing) 9935
99.4%
ValueCountFrequency (%)
20000403 1
< 0.1%
20020101 1
< 0.1%
20080731 1
< 0.1%
20090331 1
< 0.1%
20090730 1
< 0.1%
20090901 1
< 0.1%
20091031 1
< 0.1%
20091231 1
< 0.1%
20100228 1
< 0.1%
20100603 1
< 0.1%
ValueCountFrequency (%)
20221227 1
< 0.1%
20191231 1
< 0.1%
20190221 1
< 0.1%
20190131 1
< 0.1%
20190102 1
< 0.1%
20181231 1
< 0.1%
20181228 1
< 0.1%
20181130 1
< 0.1%
20181031 1
< 0.1%
20180930 1
< 0.1%

ropnymd
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:47.081809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row재개업일자
ValueCountFrequency (%)
재개업일자 1
100.0%
2024-04-17T06:50:47.263767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
재 1
20.0%
개 1
20.0%
업 1
20.0%
일 1
20.0%
자 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
재 1
20.0%
개 1
20.0%
업 1
20.0%
일 1
20.0%
자 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
재 1
20.0%
개 1
20.0%
업 1
20.0%
일 1
20.0%
자 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
재 1
20.0%
개 1
20.0%
업 1
20.0%
일 1
20.0%
자 1
20.0%

trdstatenm
Unsupported

REJECTED  UNSUPPORTED 

Missing5
Missing (%)< 0.1%
Memory size156.2 KiB

dtlstatenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
5659 
폐업
4293 
직권폐업
 
32
휴업
 
12
<NA>
 
4

Length

Max length4
Median length3
Mean length2.5731
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 5659
56.6%
폐업 4293
42.9%
직권폐업 32
 
0.3%
휴업 12
 
0.1%
<NA> 4
 
< 0.1%

Length

2024-04-17T06:50:47.371971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:47.484127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 5659
56.6%
폐업 4293
42.9%
직권폐업 32
 
0.3%
휴업 12
 
0.1%
na 4
 
< 0.1%

x
Real number (ℝ)

MISSING 

Distinct5326
Distinct (%)58.2%
Missing851
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean388208.2
Minimum187216.74
Maximum407581.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:47.603956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187216.74
5-th percentile379635.15
Q1384445.23
median388785.44
Q3391624.83
95-th percentile398143.16
Maximum407581.08
Range220364.35
Interquartile range (IQR)7179.5993

Descriptive statistics

Standard deviation6975.0563
Coefficient of variation (CV)0.017967308
Kurtosis219.7883
Mean388208.2
Median Absolute Deviation (MAD)3431.6875
Skewness-8.7515263
Sum3.5517169 × 109
Variance48651410
MonotonicityNot monotonic
2024-04-17T06:50:47.732051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387537.525975 28
 
0.3%
387475.894546 18
 
0.2%
394248.454507 16
 
0.2%
398226.822818 15
 
0.1%
398310.243451 15
 
0.1%
397548.804885 14
 
0.1%
398401.454439 14
 
0.1%
387532.458643 13
 
0.1%
394179.058785 13
 
0.1%
397594.434796 12
 
0.1%
Other values (5316) 8991
89.9%
(Missing) 851
 
8.5%
ValueCountFrequency (%)
187216.73647 1
< 0.1%
204412.090101 1
< 0.1%
212973.223657615 1
< 0.1%
229116.693892418 1
< 0.1%
249634.039189 1
< 0.1%
298905.597798326 1
< 0.1%
365157.276407 1
< 0.1%
366830.688326 1
< 0.1%
366851.651911 2
< 0.1%
366858.579155 1
< 0.1%
ValueCountFrequency (%)
407581.083119 2
< 0.1%
407515.749132 2
< 0.1%
407504.0 1
< 0.1%
407472.279312 1
< 0.1%
407448.0 1
< 0.1%
407369.530548 1
< 0.1%
407209.258171 2
< 0.1%
407126.309068 1
< 0.1%
407077.691757 1
< 0.1%
405468.503509 1
< 0.1%

y
Real number (ℝ)

MISSING 

Distinct5324
Distinct (%)58.2%
Missing851
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean187916.64
Minimum159865.53
Maximum445110.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:47.827959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum159865.53
5-th percentile178567.7
Q1183946.54
median187626.88
Q3191850.44
95-th percentile197602.47
Maximum445110.29
Range285244.75
Interquartile range (IQR)7903.899

Descriptive statistics

Standard deviation7746.3395
Coefficient of variation (CV)0.041222211
Kurtosis376.75926
Mean187916.64
Median Absolute Deviation (MAD)4135.1455
Skewness12.226644
Sum1.7192494 × 109
Variance60005776
MonotonicityNot monotonic
2024-04-17T06:50:47.927519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186476.330395 28
 
0.3%
186570.418307 18
 
0.2%
187726.224988 16
 
0.2%
187989.753665 15
 
0.1%
188031.67198 15
 
0.1%
187626.880998 14
 
0.1%
188080.4441 14
 
0.1%
187825.814573 13
 
0.1%
186392.673729 13
 
0.1%
196480.347212 12
 
0.1%
Other values (5314) 8991
89.9%
(Missing) 851
 
8.5%
ValueCountFrequency (%)
159865.533264 1
 
< 0.1%
170014.453769 1
 
< 0.1%
170016.321524 1
 
< 0.1%
171205.308829 1
 
< 0.1%
174205.541619 1
 
< 0.1%
174237.045871 1
 
< 0.1%
174251.931196 1
 
< 0.1%
174292.594164 1
 
< 0.1%
174396.378069 4
< 0.1%
174413.752458 3
< 0.1%
ValueCountFrequency (%)
445110.286986 1
 
< 0.1%
437595.180855679 1
 
< 0.1%
428070.370521473 1
 
< 0.1%
359925.060602723 1
 
< 0.1%
211893.965608 1
 
< 0.1%
208906.876551 1
 
< 0.1%
206821.489013 1
 
< 0.1%
206494.685696 1
 
< 0.1%
206426.679067 3
< 0.1%
206423.253753 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct8053
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0149481 × 1013
Minimum2.0081008 × 1013
Maximum2.0181016 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:48.042317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081008 × 1013
5-th percentile2.0090202 × 1013
Q12.0130703 × 1013
median2.0160711 × 1013
Q32.0170905 × 1013
95-th percentile2.018071 × 1013
Maximum2.0181016 × 1013
Range1.0000802 × 1011
Interquartile range (IQR)4.0202564 × 1010

Descriptive statistics

Standard deviation2.9174078 × 1010
Coefficient of variation (CV)0.0014478824
Kurtosis-0.51202711
Mean2.0149481 × 1013
Median Absolute Deviation (MAD)1.9604943 × 1010
Skewness-0.82060509
Sum2.0149481 × 1017
Variance8.5112685 × 1020
MonotonicityNot monotonic
2024-04-17T06:50:48.152827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905183851 199
 
2.0%
20170905183844 196
 
2.0%
20170905183850 185
 
1.8%
20170905183853 178
 
1.8%
20170905183849 153
 
1.5%
20170905183843 109
 
1.1%
20170905183852 105
 
1.1%
20170905183848 103
 
1.0%
20170905183859 82
 
0.8%
20170905183858 70
 
0.7%
Other values (8043) 8620
86.2%
ValueCountFrequency (%)
20081008160928 1
< 0.1%
20081117091658 1
< 0.1%
20081117094150 1
< 0.1%
20081118094507 1
< 0.1%
20081125181445 1
< 0.1%
20081126095545 1
< 0.1%
20081126103530 1
< 0.1%
20081126142837 1
< 0.1%
20081126154442 1
< 0.1%
20081126154559 1
< 0.1%
ValueCountFrequency (%)
20181016185445 1
< 0.1%
20181016175532 1
< 0.1%
20181016174307 1
< 0.1%
20181016173009 1
< 0.1%
20181016171940 1
< 0.1%
20181016145549 1
< 0.1%
20180904181338 1
< 0.1%
20180904180453 1
< 0.1%
20180904174554 1
< 0.1%
20180904174453 1
< 0.1%

uptaenm
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4700 
의원
2598 
한의원
1197 
치과의원
1107 
요양병원(일반요양병원)
 
165
Other values (10)
 
233

Length

Max length12
Median length4
Mean length3.4718
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4700
47.0%
의원 2598
26.0%
한의원 1197
 
12.0%
치과의원 1107
 
11.1%
요양병원(일반요양병원) 165
 
1.7%
병원 127
 
1.3%
조산원 20
 
0.2%
치과병원 18
 
0.2%
종합병원 18
 
0.2%
한방병원 13
 
0.1%
Other values (5) 37
 
0.4%

Length

2024-04-17T06:50:48.255793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4700
47.0%
의원 2598
26.0%
한의원 1197
 
12.0%
치과의원 1107
 
11.1%
요양병원(일반요양병원 165
 
1.7%
병원 127
 
1.3%
조산원 20
 
0.2%
치과병원 18
 
0.2%
종합병원 18
 
0.2%
한방병원 13
 
0.1%
Other values (5) 37
 
0.4%

sitetel
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
051-123-1234
10000 

Length

Max length12
Median length12
Mean length12
Min length12

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 10000
100.0%

Length

2024-04-17T06:50:48.350546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:48.417087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 10000
100.0%

nursecnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9973
Missing (%)99.7%
Memory size156.2 KiB

nursaidcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9973
Missing (%)99.7%
Memory size156.2 KiB

bdnglayercnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9975
Missing (%)99.8%
Memory size156.2 KiB

emercargen
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5971
Missing (%)59.7%
Memory size156.2 KiB

emercarspec
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5971
Missing (%)59.7%
Memory size156.2 KiB

rescnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB

pomfacilar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9989
Missing (%)99.9%
Memory size156.2 KiB

etcstfcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9993
Missing (%)99.9%
Memory size156.2 KiB

etcepcnt
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:48.496680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타종업원수
ValueCountFrequency (%)
기타종업원수 1
100.0%
2024-04-17T06:50:48.683590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

mmknurmar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9980
Missing (%)99.8%
Memory size156.2 KiB

btrmar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9992
Missing (%)99.9%
Memory size156.2 KiB

btpnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9988
Missing (%)99.9%
Memory size156.2 KiB

sicbnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5968
Missing (%)59.7%
Memory size156.2 KiB

astnepnum
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:48.785136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row보조종업원수
ValueCountFrequency (%)
보조종업원수 1
100.0%
2024-04-17T06:50:49.244080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 1
16.7%
조 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 1
16.7%
조 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 1
16.7%
조 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 1
16.7%
조 1
16.7%
종 1
16.7%
업 1
16.7%
원 1
16.7%
수 1
16.7%

ofear
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9986
Missing (%)99.9%
Memory size156.2 KiB

warmar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9989
Missing (%)99.9%
Memory size156.2 KiB

facilmngnum
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:49.345316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row시설관리자수
ValueCountFrequency (%)
시설관리자수 1
100.0%
2024-04-17T06:50:49.566658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1
16.7%
설 1
16.7%
관 1
16.7%
리 1
16.7%
자 1
16.7%
수 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1
16.7%
설 1
16.7%
관 1
16.7%
리 1
16.7%
자 1
16.7%
수 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1
16.7%
설 1
16.7%
관 1
16.7%
리 1
16.7%
자 1
16.7%
수 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1
16.7%
설 1
16.7%
관 1
16.7%
리 1
16.7%
자 1
16.7%
수 1
16.7%

pharmtrdar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7317
Missing (%)73.2%
Memory size156.2 KiB

nutrcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9989
Missing (%)99.9%
Memory size156.2 KiB

bbrmar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9973
Missing (%)99.7%
Memory size156.2 KiB

babyrglstnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9970
Missing (%)99.7%
Memory size156.2 KiB

mitmdcdepnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:49.680557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row완화의료담당부서명
ValueCountFrequency (%)
완화의료담당부서명 1
100.0%
2024-04-17T06:50:49.876254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
완 1
11.1%
화 1
11.1%
의 1
11.1%
료 1
11.1%
담 1
11.1%
당 1
11.1%
부 1
11.1%
서 1
11.1%
명 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
완 1
11.1%
화 1
11.1%
의 1
11.1%
료 1
11.1%
담 1
11.1%
당 1
11.1%
부 1
11.1%
서 1
11.1%
명 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
완 1
11.1%
화 1
11.1%
의 1
11.1%
료 1
11.1%
담 1
11.1%
당 1
11.1%
부 1
11.1%
서 1
11.1%
명 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
완 1
11.1%
화 1
11.1%
의 1
11.1%
료 1
11.1%
담 1
11.1%
당 1
11.1%
부 1
11.1%
서 1
11.1%
명 1
11.1%

mitmdcasgntype
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:49.987681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row완화의료지정형태
ValueCountFrequency (%)
완화의료지정형태 1
100.0%
2024-04-17T06:50:50.186568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
완 1
12.5%
화 1
12.5%
의 1
12.5%
료 1
12.5%
지 1
12.5%
정 1
12.5%
형 1
12.5%
태 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
완 1
12.5%
화 1
12.5%
의 1
12.5%
료 1
12.5%
지 1
12.5%
정 1
12.5%
형 1
12.5%
태 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
완 1
12.5%
화 1
12.5%
의 1
12.5%
료 1
12.5%
지 1
12.5%
정 1
12.5%
형 1
12.5%
태 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
완 1
12.5%
화 1
12.5%
의 1
12.5%
료 1
12.5%
지 1
12.5%
정 1
12.5%
형 1
12.5%
태 1
12.5%

batrar
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:50.282199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row욕실면적
ValueCountFrequency (%)
욕실면적 1
100.0%
2024-04-17T06:50:50.472491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
욕 1
25.0%
실 1
25.0%
면 1
25.0%
적 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
욕 1
25.0%
실 1
25.0%
면 1
25.0%
적 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
욕 1
25.0%
실 1
25.0%
면 1
25.0%
적 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
욕 1
25.0%
실 1
25.0%
면 1
25.0%
적 1
25.0%

metrorgassrnm
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5972 
의원
1949 
한의원
886 
치과의원
806 
요양병원(일반요양병원)
 
165
Other values (12)
 
222

Length

Max length12
Median length4
Mean length3.6341
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5972
59.7%
의원 1949
 
19.5%
한의원 886
 
8.9%
치과의원 806
 
8.1%
요양병원(일반요양병원) 165
 
1.7%
병원 127
 
1.3%
종합병원 18
 
0.2%
치과병원 18
 
0.2%
부속의원 14
 
0.1%
한방병원 13
 
0.1%
Other values (7) 32
 
0.3%

Length

2024-04-17T06:50:50.577547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5972
59.7%
의원 1949
 
19.5%
한의원 886
 
8.9%
치과의원 806
 
8.1%
요양병원(일반요양병원 165
 
1.7%
병원 127
 
1.3%
종합병원 18
 
0.2%
치과병원 18
 
0.2%
부속의원 14
 
0.1%
한방병원 13
 
0.1%
Other values (7) 32
 
0.3%

metrbosassrnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:50.684718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row의료유사업종별명
ValueCountFrequency (%)
의료유사업종별명 1
100.0%
2024-04-17T06:50:50.884739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 1
12.5%
료 1
12.5%
유 1
12.5%
사 1
12.5%
업 1
12.5%
종 1
12.5%
별 1
12.5%
명 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1
12.5%
료 1
12.5%
유 1
12.5%
사 1
12.5%
업 1
12.5%
종 1
12.5%
별 1
12.5%
명 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1
12.5%
료 1
12.5%
유 1
12.5%
사 1
12.5%
업 1
12.5%
종 1
12.5%
별 1
12.5%
명 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 1
12.5%
료 1
12.5%
유 1
12.5%
사 1
12.5%
업 1
12.5%
종 1
12.5%
별 1
12.5%
명 1
12.5%

metrpnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5972
Missing (%)59.7%
Memory size156.2 KiB

pgrmar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9974
Missing (%)99.7%
Memory size156.2 KiB

pwnmrglstnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9970
Missing (%)99.7%
Memory size156.2 KiB

hstrmnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5968
Missing (%)59.7%
Memory size156.2 KiB

qutnownernum
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:50.999799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자격증소유자수
ValueCountFrequency (%)
자격증소유자수 1
100.0%
2024-04-17T06:50:51.209596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 2
28.6%
격 1
14.3%
증 1
14.3%
소 1
14.3%
유 1
14.3%
수 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 2
28.6%
격 1
14.3%
증 1
14.3%
소 1
14.3%
유 1
14.3%
수 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 2
28.6%
격 1
14.3%
증 1
14.3%
소 1
14.3%
유 1
14.3%
수 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 2
28.6%
격 1
14.3%
증 1
14.3%
소 1
14.3%
유 1
14.3%
수 1
14.3%

joriwontoilar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9986
Missing (%)99.9%
Memory size156.2 KiB

epcnt
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:51.307839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row종업원수
ValueCountFrequency (%)
종업원수 1
100.0%
2024-04-17T06:50:51.484030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
종 1
25.0%
업 1
25.0%
원 1
25.0%
수 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 1
25.0%
업 1
25.0%
원 1
25.0%
수 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 1
25.0%
업 1
25.0%
원 1
25.0%
수 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
종 1
25.0%
업 1
25.0%
원 1
25.0%
수 1
25.0%

jisgnumlay
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9980
Missing (%)99.8%
Memory size156.2 KiB

asgnymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7315
Missing (%)73.2%
Memory size156.2 KiB

asgncancelymd
Text

MISSING 

Distinct191
Distinct (%)54.0%
Missing9646
Missing (%)96.5%
Memory size156.2 KiB
2024-04-17T06:50:51.697013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9943503
Min length6

Characters and Unicode

Total characters2830
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

Unique137 ?
Unique (%)38.7%

Sample

1st row20170905
2nd row20170905
3rd row20180727
4th row20170905
5th row20131230
ValueCountFrequency (%)
20170905 32
 
9.0%
20180808 13
 
3.7%
20180813 10
 
2.8%
20180810 9
 
2.5%
20180823 8
 
2.3%
20180614 8
 
2.3%
20180831 6
 
1.7%
20180713 6
 
1.7%
20180829 5
 
1.4%
20180809 5
 
1.4%
Other values (181) 252
71.2%
2024-04-17T06:50:52.025569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 842
29.8%
1 565
20.0%
2 528
18.7%
8 331
 
11.7%
7 123
 
4.3%
3 103
 
3.6%
5 100
 
3.5%
9 83
 
2.9%
4 75
 
2.7%
6 74
 
2.6%
Other values (6) 6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2824
99.8%
Other Letter 6
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 842
29.8%
1 565
20.0%
2 528
18.7%
8 331
 
11.7%
7 123
 
4.4%
3 103
 
3.6%
5 100
 
3.5%
9 83
 
2.9%
4 75
 
2.7%
6 74
 
2.6%
Other Letter
ValueCountFrequency (%)
지 1
16.7%
정 1
16.7%
취 1
16.7%
소 1
16.7%
일 1
16.7%
자 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2824
99.8%
Hangul 6
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 842
29.8%
1 565
20.0%
2 528
18.7%
8 331
 
11.7%
7 123
 
4.4%
3 103
 
3.6%
5 100
 
3.5%
9 83
 
2.9%
4 75
 
2.7%
6 74
 
2.6%
Hangul
ValueCountFrequency (%)
지 1
16.7%
정 1
16.7%
취 1
16.7%
소 1
16.7%
일 1
16.7%
자 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2824
99.8%
Hangul 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 842
29.8%
1 565
20.0%
2 528
18.7%
8 331
 
11.7%
7 123
 
4.4%
3 103
 
3.6%
5 100
 
3.5%
9 83
 
2.9%
4 75
 
2.7%
6 74
 
2.6%
Hangul
ValueCountFrequency (%)
지 1
16.7%
정 1
16.7%
취 1
16.7%
소 1
16.7%
일 1
16.7%
자 1
16.7%

undernumlay
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9993
Missing (%)99.9%
Memory size156.2 KiB

medextritemscn
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:52.148587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row진료과목내용
ValueCountFrequency (%)
진료과목내용 1
100.0%
2024-04-17T06:50:52.334916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 1
16.7%
료 1
16.7%
과 1
16.7%
목 1
16.7%
내 1
16.7%
용 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 1
16.7%
료 1
16.7%
과 1
16.7%
목 1
16.7%
내 1
16.7%
용 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 1
16.7%
료 1
16.7%
과 1
16.7%
목 1
16.7%
내 1
16.7%
용 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 1
16.7%
료 1
16.7%
과 1
16.7%
목 1
16.7%
내 1
16.7%
용 1
16.7%

medextritemscnnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:52.442171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row진료과목내용명
ValueCountFrequency (%)
진료과목내용명 1
100.0%
2024-04-17T06:50:52.653777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 1
14.3%
료 1
14.3%
과 1
14.3%
목 1
14.3%
내 1
14.3%
용 1
14.3%
명 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 1
14.3%
료 1
14.3%
과 1
14.3%
목 1
14.3%
내 1
14.3%
용 1
14.3%
명 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 1
14.3%
료 1
14.3%
과 1
14.3%
목 1
14.3%
내 1
14.3%
용 1
14.3%
명 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 1
14.3%
료 1
14.3%
과 1
14.3%
목 1
14.3%
내 1
14.3%
용 1
14.3%
명 1
14.3%

totar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5968
Missing (%)59.7%
Memory size156.2 KiB

totepnum
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:52.737120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row총인원
ValueCountFrequency (%)
총인원 1
100.0%
2024-04-17T06:50:52.922717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
총 1
33.3%
인 1
33.3%
원 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
총 1
33.3%
인 1
33.3%
원 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
총 1
33.3%
인 1
33.3%
원 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
총 1
33.3%
인 1
33.3%
원 1
33.3%

frstasgnymd
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:53.029869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row최초지정일자
ValueCountFrequency (%)
최초지정일자 1
100.0%
2024-04-17T06:50:53.218847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
최 1
16.7%
초 1
16.7%
지 1
16.7%
정 1
16.7%
일 1
16.7%
자 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
최 1
16.7%
초 1
16.7%
지 1
16.7%
정 1
16.7%
일 1
16.7%
자 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
최 1
16.7%
초 1
16.7%
지 1
16.7%
정 1
16.7%
일 1
16.7%
자 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
최 1
16.7%
초 1
16.7%
지 1
16.7%
정 1
16.7%
일 1
16.7%
자 1
16.7%

copnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9987
Missing (%)99.9%
Memory size156.2 KiB

storetrdar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5074
Missing (%)50.7%
Memory size156.2 KiB

pmtbednum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9629
Missing (%)96.3%
Memory size156.2 KiB

last_load_dttm
Date

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-02-01 05:19:03
Maximum2021-02-01 05:19:07
2024-04-17T06:50:53.300604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:50:53.388016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
15412159753400000PHMD12018340001308400000501_01_06_PI2018-08-31 23:59:59.0<NA>도담약국NaN부산광역시 기장군 정관읍 매학리 720번지 7호46017부산광역시 기장군 정관읍 정관6로 31, 105호2018042020180801.0<NA><NA><NA>3폐업397942.700664204428.57619720180731140109<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>134.67NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20180420.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:07
14447150093350000PHMD12000335002408400003101_01_06_PI2018-08-31 23:59:59.0<NA>현대약국609814.0부산광역시 금정구 남산동 225번지 34호<NA>부산광역시 금정구 중앙대로 2001 (남산동)2000040620030801.0<NA><NA><NA>3폐업390348.072207198284.80808320090121163530<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>1.0NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20000406.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:07
13240138043320000PHMD12013332004508400000201_01_06_PI2018-08-31 23:59:59.0<NA>대학로약국616853.0부산광역시 북구 화명동 2314번지 1호616853부산광역시 북구 학사로 15 (화명동)2013010220150102.0<NA><NA><NA>3폐업382785.826553193814.01668420150102095559<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>42.0NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20130102.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:06
9552101123320000PHMH32017332004508750001301_01_05_PI2018-08-31 23:59:59.0<NA>씨유 화명롯데카이저점NaN<NA>46539부산광역시 북구 금곡대로 166, 907동 101호 (화명동, 화명롯데캐슬카이저)20170829NaN<NA><NA><NA>13영업중383398.915235194063.87502620170829165514<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaN68.0NaN2021-02-01 05:19:05
11843124033270000PHMD12009327002208400000301_01_06_PI2018-08-31 23:59:59.0<NA>동아사약국601803.0부산광역시 동구 범일2동 640번지 5호601803부산광역시 동구 진시장로 19-2 (범일동)2009030220120227.0<NA><NA><NA>3폐업387656.446672184274.70716420120227153011<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>29.4NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20090302.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:06
494555053330000PHMA11984333002404110000101_01_02_PI2018-08-31 23:59:59.0<NA>해운대이비인후과의원612847부산광역시해운대구중1동1394-38548095부산광역시 해운대구 구남로29번길 38 (중동)19840117NaN<NA><NA><NA>13영업중397022.2533187278.73776320170905183857의원051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:04
401745773320000PHMA12012332004504110000101_01_02_PI2018-08-31 23:59:59.0<NA>이가의원·한의원616819부산광역시 북구 덕천1동 390번지 8호616819부산광역시 북구 만덕대로 126 (덕천동)2012012020131101<NA><NA><NA>03폐업383797.477305192590.45422320131101130847의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>139.94<NA><NA>NaN0NaN2021-02-01 05:19:04
759181603380000PHMA12003338002304110001301_01_02_PI2018-08-31 23:59:59.0<NA>광안미치과의원613100부산광역시 수영구 광안2동 143-648297부산광역시 수영구 수영로 582 (광안동)20030901NaN<NA><NA><NA>13영업중392570.780444186625.59715520170905183858치과의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>치과의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>187.2<NA><NA>NaN0NaN2021-02-01 05:19:04
324638073310000PHMA12009331002404110000501_01_02_PI2018-08-31 23:59:59.0<NA>정침한의원608807부산광역시 남구 대연5동 1742번지 1호 (2층)48445부산광역시 남구 진남로 9 (대연동, (2층))20090507NaN<NA><NA><NA>13영업중390634.792239184166.65643620170905183844한의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>한의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>136.48<NA><NA>NaN0NaN2021-02-01 05:19:04
10416109743350000PHMH32017335002408750002001_01_05_PI2018-08-31 23:59:59.0<NA>씨유 금정금샘로점46235.0부산광역시 금정구 구서동 1012번지 5호46235부산광역시 금정구 금샘로 423 (구서동, 이화빌딩)2017062820180625.0<NA><NA><NA>3폐업389667.309632198005.40389120180625131733<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:06
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
11265118213390000PHMH32015339002308750001901_01_05_PI2018-08-31 23:59:59.0<NA>씨유 주례대로점NaN부산광역시 사상구 주례동 692번지 32호47001부산광역시 사상구 가야대로 227 (주례동)20150828NaN<NA><NA><NA>13영업중382030.366314185604.78973120150828135429<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaN59.4NaN2021-02-01 05:19:06
11725122843260000PHMD12009326002208400001301_01_06_PI2018-08-31 23:59:59.0<NA>일한약국602061.0부산광역시 서구 아미동1가 21번지 2호49245부산광역시 서구 구덕로 167 (아미동1가)2009110220161104.0<NA><NA><NA>3폐업384147.995426179999.08969920161107091116<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>151.41NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20091102.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:06
622267913350000PHMA11991335002404110002301_01_02_PI2018-08-31 23:59:59.0<NA>이치과의원609320부산광역시 금정구 부곡동 295번지 15호<NA>부산광역시 금정구 부곡로 122 (부곡동)1991050719921125<NA><NA><NA>03폐업390481.25353194253.63620320090203115311치과의원051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:04
575863193340000PHMA11992334002504110000901_01_02_PI2018-08-31 23:59:59.0<NA>해동의원604851부산광역시 사하구 하단2동 500번지 10호<NA>부산광역시 사하구 낙동대로535번길 53 (하단동)1992100219930302<NA><NA><NA>03폐업378844.545112181190.61838820130524111329의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>106<NA><NA>NaN0NaN2021-02-01 05:19:04
599565573350000PHMA12003335002404110000901_01_02_PI2018-08-31 23:59:59.0<NA>남산하나정형외과의원609811부산광역시 금정구 남산동 91-12(2~3층)46219부산광역시 금정구 중앙대로 2049, 2,3층 (남산동)20030428NaN<NA><NA><NA>13영업중390408.262659198753.60927520170905183843의원051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:04
539159513340000PHMA11998334002504120000701_01_02_PI2018-08-31 23:59:59.0<NA>세브란스치과의원604814부산광역시 사하구 괴정동 949번지 2호49381부산광역시 사하구 사하로 195, 2층 (괴정동)19980728NaN<NA><NA><NA>13영업중381752.170489179901.32375720170905183850치과의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>치과의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>86.79<NA><NA>NaN0NaN2021-02-01 05:19:04
549360553340000PHMA12008334002504110000201_01_02_PI2018-08-31 23:59:59.0<NA>하단강산치과의원NaN부산광역시 사하구 하단동 526번지 4호 정우엠타워49311부산광역시 사하구 낙동남로 1409, 4층 (하단동)20081104NaN<NA><NA><NA>13영업중379233.382756180687.19585620180322142658치과의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>치과의원<NA>2NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>344.12<NA><NA>NaN0NaN2021-02-01 05:19:04
12004105623330000PHMH32016333002408750002501_01_05_PI2018-08-31 23:59:59.0<NA>CU 센텀클래스원점NaN부산광역시 해운대구 재송동 1210번지48059부산광역시 해운대구 센텀동로 99, 103호 (재송동, 벽산이센텀클래스원)20160831NaN<NA><NA><NA>13영업중393662.875985188708.32979120160831113004<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>NaN<NA><NA>NaN66.0NaN2021-02-01 05:19:06
295535143300000PHMA12017330002404110000101_01_02_PI2018-08-31 23:59:59.0<NA>예인의원NaN부산광역시 동래구 안락동 591번지 2호47796부산광역시 동래구 충렬대로 417, 3층 301호 (안락동)20170207NaN<NA><NA><NA>13영업중391632.35512190965.15725820170905183852의원051-123-1234NaNNaNNaN00NaNNaNNaN<NA>NaNNaNNaN0<NA>NaNNaN<NA>NaNNaNNaNNaN<NA><NA><NA>의원<NA>1NaNNaN0<NA>NaN<NA>NaNNaN<NA>NaN<NA><NA>241.37<NA><NA>NaN0NaN2021-02-01 05:19:04
15112156743380000PHMD12010338002308400000601_01_06_PI2018-08-31 23:59:59.0<NA>한마음약국613806.0부산광역시 수영구 광안4동 776번지 14호613806부산광역시 수영구 수영로 529 (광안동)2010061020120227.0<NA><NA><NA>3폐업392425.306382186123.93576820120227095348<NA>051-123-1234NaNNaNNaNNaNNaNNaNNaNNaN<NA>NaNNaNNaNNaN<NA>NaNNaN<NA>66.0NaNNaNNaN<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA>NaN<NA>NaN20100610.0<NA>NaN<NA><NA>NaN<NA><NA>NaNNaNNaN2021-02-01 05:19:07