Overview

Dataset statistics

Number of variables70
Number of observations10000
Missing cells417423
Missing cells (%)59.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 MiB
Average record size in memory626.0 B

Variable types

Numeric36
Text4
Categorical12
DateTime2
Unsupported16

Alerts

sitetel has constant value ""Constant
updategbn is highly imbalanced (98.1%)Imbalance
nutrcnt is highly imbalanced (99.0%)Imbalance
metrorgassrnm is highly imbalanced (58.1%)Imbalance
undernumlay is highly imbalanced (99.3%)Imbalance
pmtbednum is highly imbalanced (77.6%)Imbalance
opnsvcnm has 10000 (100.0%) missing valuesMissing
sitepostno has 3323 (33.2%) missing valuesMissing
sitewhladdr has 881 (8.8%) missing valuesMissing
rdnpostno has 2159 (21.6%) missing valuesMissing
rdnwhladdr has 869 (8.7%) missing valuesMissing
dcbymd has 5803 (58.0%) missing valuesMissing
clgstdt has 9938 (99.4%) missing valuesMissing
clgenddt has 9937 (99.4%) missing valuesMissing
ropnymd has 10000 (100.0%) missing valuesMissing
x has 851 (8.5%) missing valuesMissing
y has 851 (8.5%) missing valuesMissing
nursecnt has 9969 (99.7%) missing valuesMissing
nursaidcnt has 9969 (99.7%) missing valuesMissing
bdnglayercnt has 9968 (99.7%) missing valuesMissing
rescnt has 10000 (100.0%) missing valuesMissing
pomfacilar has 9981 (99.8%) missing valuesMissing
etcstfcnt has 9985 (99.9%) missing valuesMissing
etcepcnt has 10000 (100.0%) missing valuesMissing
mmknurmar has 9973 (99.7%) missing valuesMissing
btrmar has 9986 (99.9%) missing valuesMissing
btpnum has 9982 (99.8%) missing valuesMissing
sicbnum has 5958 (59.6%) missing valuesMissing
astnepnum has 10000 (100.0%) missing valuesMissing
ofear has 9980 (99.8%) missing valuesMissing
warmar has 9982 (99.8%) missing valuesMissing
facilmngnum has 10000 (100.0%) missing valuesMissing
pharmtrdar has 7364 (73.6%) missing valuesMissing
bbrmar has 9967 (99.7%) missing valuesMissing
babyrglstnum has 9964 (99.6%) missing valuesMissing
mitmdcdepnm has 10000 (100.0%) missing valuesMissing
mitmdcasgntype has 10000 (100.0%) missing valuesMissing
batrar has 10000 (100.0%) missing valuesMissing
metrbosassrnm has 10000 (100.0%) missing valuesMissing
metrpnum has 5958 (59.6%) missing valuesMissing
pgrmar has 9969 (99.7%) missing valuesMissing
pwnmrglstnum has 9964 (99.6%) missing valuesMissing
hstrmnum has 5958 (59.6%) missing valuesMissing
qutnownernum has 10000 (100.0%) missing valuesMissing
joriwontoilar has 9979 (99.8%) missing valuesMissing
epcnt has 10000 (100.0%) missing valuesMissing
jisgnumlay has 9974 (99.7%) missing valuesMissing
asgnymd has 7362 (73.6%) missing valuesMissing
asgncancelymd has 9655 (96.5%) missing valuesMissing
medextritemscn has 10000 (100.0%) missing valuesMissing
medextritemscnnm has 10000 (100.0%) missing valuesMissing
totar has 5958 (59.6%) missing valuesMissing
totepnum has 10000 (100.0%) missing valuesMissing
frstasgnymd has 10000 (100.0%) missing valuesMissing
copnum has 9981 (99.8%) missing valuesMissing
storetrdar has 5025 (50.2%) missing valuesMissing
pharmtrdar is highly skewed (γ1 = 51.26749767)Skewed
metrpnum is highly skewed (γ1 = 25.16930193)Skewed
totar is highly skewed (γ1 = 60.34608235)Skewed
skey has unique valuesUnique
mgtno has unique valuesUnique
opnsvcnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
ropnymd 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
etcepcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
astnepnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
facilmngnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
mitmdcdepnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
mitmdcasgntype is an unsupported type, check if it needs cleaning or further analysisUnsupported
batrar is an unsupported type, check if it needs cleaning or further analysisUnsupported
metrbosassrnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
qutnownernum is an unsupported type, check if it needs cleaning or further analysisUnsupported
epcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
medextritemscn is an unsupported type, check if it needs cleaning or further analysisUnsupported
medextritemscnnm is an unsupported type, check if it needs cleaning or further analysisUnsupported
totepnum is an unsupported type, check if it needs cleaning or further analysisUnsupported
frstasgnymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
sicbnum has 3401 (34.0%) zerosZeros
pharmtrdar has 296 (3.0%) zerosZeros
hstrmnum has 3445 (34.4%) zerosZeros
totar has 599 (6.0%) zerosZeros
storetrdar has 3681 (36.8%) zerosZeros

Reproduction

Analysis started2024-04-16 21:50:01.201130
Analysis finished2024-04-16 21:50:02.885527
Duration1.68 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%
Mean8319.1742
Minimum563
Maximum16076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:02.941629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum563
5-th percentile1364.95
Q14451.25
median8323.5
Q312189.25
95-th percentile15266.05
Maximum16076
Range15513
Interquartile range (IQR)7738

Descriptive statistics

Standard deviation4472.7468
Coefficient of variation (CV)0.53764312
Kurtosis-1.2052205
Mean8319.1742
Median Absolute Deviation (MAD)3868
Skewness-0.0025895545
Sum83191742
Variance20005464
MonotonicityNot monotonic
2024-04-17T06:50:03.046282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2400 1
 
< 0.1%
9753 1
 
< 0.1%
10401 1
 
< 0.1%
807 1
 
< 0.1%
8991 1
 
< 0.1%
4562 1
 
< 0.1%
10036 1
 
< 0.1%
1698 1
 
< 0.1%
1708 1
 
< 0.1%
3970 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
563 1
< 0.1%
565 1
< 0.1%
567 1
< 0.1%
568 1
< 0.1%
570 1
< 0.1%
571 1
< 0.1%
573 1
< 0.1%
575 1
< 0.1%
577 1
< 0.1%
578 1
< 0.1%
ValueCountFrequency (%)
16076 1
< 0.1%
16075 1
< 0.1%
16073 1
< 0.1%
16072 1
< 0.1%
16071 1
< 0.1%
16070 1
< 0.1%
16067 1
< 0.1%
16066 1
< 0.1%
16064 1
< 0.1%
16061 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326288
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:03.143156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation38399.85
Coefficient of variation (CV)0.011544355
Kurtosis-0.77175734
Mean3326288
Median Absolute Deviation (MAD)30000
Skewness0.023991991
Sum3.326288 × 1010
Variance1.4745485 × 109
MonotonicityNot monotonic
2024-04-17T06:50:03.230508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 1331
13.3%
3350000 1183
11.8%
3330000 1107
11.1%
3340000 979
9.8%
3300000 763
7.6%
3310000 719
7.2%
3320000 584
 
5.8%
3370000 574
 
5.7%
3380000 545
 
5.5%
3390000 456
 
4.6%
Other values (6) 1759
17.6%
ValueCountFrequency (%)
3250000 286
 
2.9%
3260000 352
 
3.5%
3270000 334
 
3.3%
3280000 265
 
2.6%
3290000 1331
13.3%
3300000 763
7.6%
3310000 719
7.2%
3320000 584
5.8%
3330000 1107
11.1%
3340000 979
9.8%
ValueCountFrequency (%)
3400000 334
 
3.3%
3390000 456
 
4.6%
3380000 545
5.5%
3370000 574
5.7%
3360000 188
 
1.9%
3350000 1183
11.8%
3340000 979
9.8%
3330000 1107
11.1%
3320000 584
5.8%
3310000 719
7.2%

mgtno
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:03.588133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters250000
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 rowPHMA120063290024041100047
2nd rowPHMH320153340025087500012
3rd rowPHMD120113400013084000016
4th rowPHMH320153340025087500007
5th rowPHMH320163390023087500008
ValueCountFrequency (%)
phma120063290024041100047 1
 
< 0.1%
phma120023270022041100004 1
 
< 0.1%
phma120153370022041100010 1
 
< 0.1%
phma120013310024041100004 1
 
< 0.1%
phmh320183330024087500002 1
 
< 0.1%
phma220073330024021200003 1
 
< 0.1%
phmh320173250021087500006 1
 
< 0.1%
phma120133320045041100002 1
 
< 0.1%
phmh320123310024087500055 1
 
< 0.1%
phmh320153300024087500003 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T06:50:03.844570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81178
32.5%
1 31217
 
12.5%
2 26445
 
10.6%
3 24504
 
9.8%
4 17064
 
6.8%
H 11971
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7958
 
3.2%
5 7096
 
2.8%
Other values (6) 22567
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210000
84.0%
Uppercase Letter 40000
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81178
38.7%
1 31217
 
14.9%
2 26445
 
12.6%
3 24504
 
11.7%
4 17064
 
8.1%
8 7958
 
3.8%
5 7096
 
3.4%
9 6696
 
3.2%
7 5192
 
2.5%
6 2650
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
H 11971
29.9%
P 10000
25.0%
M 10000
25.0%
A 5355
13.4%
D 2638
 
6.6%
B 36
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 210000
84.0%
Latin 40000
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81178
38.7%
1 31217
 
14.9%
2 26445
 
12.6%
3 24504
 
11.7%
4 17064
 
8.1%
8 7958
 
3.8%
5 7096
 
3.4%
9 6696
 
3.2%
7 5192
 
2.5%
6 2650
 
1.3%
Latin
ValueCountFrequency (%)
H 11971
29.9%
P 10000
25.0%
M 10000
25.0%
A 5355
13.4%
D 2638
 
6.6%
B 36
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81178
32.5%
1 31217
 
12.5%
2 26445
 
10.6%
3 24504
 
9.8%
4 17064
 
6.8%
H 11971
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7958
 
3.2%
5 7096
 
2.8%
Other values (6) 22567
 
9.0%

opnsvcid
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
01_01_02_P
4994 
01_01_06_P
2638 
01_01_05_P
1971 
01_01_01_P
 
345
01_01_04_P
 
36

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_01_02_P
2nd row01_01_05_P
3rd row01_01_06_P
4th row01_01_05_P
5th row01_01_05_P

Common Values

ValueCountFrequency (%)
01_01_02_P 4994
49.9%
01_01_06_P 2638
26.4%
01_01_05_P 1971
 
19.7%
01_01_01_P 345
 
3.5%
01_01_04_P 36
 
0.4%
01_01_03_P 16
 
0.2%

Length

2024-04-17T06:50:03.950203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:04.028002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_01_02_p 4994
49.9%
01_01_06_p 2638
26.4%
01_01_05_p 1971
 
19.7%
01_01_01_p 345
 
3.5%
01_01_04_p 36
 
0.4%
01_01_03_p 16
 
0.2%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9982 
U
 
18

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 9982
99.8%
U 18
 
0.2%

Length

2024-04-17T06:50:04.117412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:04.187054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9982
99.8%
u 18
 
0.2%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2018-09-06 11:42:33
2024-04-17T06:50:04.245055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:50:04.320231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

opnsvcnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

bplcnm
Text

Distinct7716
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:04.538857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length7.2805
Min length2

Characters and Unicode

Total characters72805
Distinct characters690
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6631 ?
Unique (%)66.3%

Sample

1st row오행선침한의원
2nd row씨유감천대로점
3rd row하나약국
4th row씨유장림장평점
5th rowGS25사상덕포역점
ValueCountFrequency (%)
gs25 283
 
2.4%
씨유 235
 
2.0%
세븐일레븐 170
 
1.4%
미니스톱 113
 
1.0%
cu 87
 
0.7%
약국 67
 
0.6%
주)코리아세븐 59
 
0.5%
의원 53
 
0.4%
의료법인 53
 
0.4%
치과의원 50
 
0.4%
Other values (7882) 10675
90.1%
2024-04-17T06:50:04.892058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5676
 
7.8%
5534
 
7.6%
2897
 
4.0%
2699
 
3.7%
2652
 
3.6%
1875
 
2.6%
1853
 
2.5%
1749
 
2.4%
1240
 
1.7%
1064
 
1.5%
Other values (680) 45566
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67156
92.2%
Space Separator 1853
 
2.5%
Uppercase Letter 1627
 
2.2%
Decimal Number 1523
 
2.1%
Close Punctuation 270
 
0.4%
Open Punctuation 253
 
0.3%
Lowercase Letter 82
 
0.1%
Other Punctuation 32
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5676
 
8.5%
5534
 
8.2%
2897
 
4.3%
2699
 
4.0%
2652
 
3.9%
1875
 
2.8%
1749
 
2.6%
1240
 
1.8%
1064
 
1.6%
1060
 
1.6%
Other values (623) 40710
60.6%
Uppercase Letter
ValueCountFrequency (%)
S 619
38.0%
G 587
36.1%
C 149
 
9.2%
U 146
 
9.0%
K 23
 
1.4%
B 18
 
1.1%
H 11
 
0.7%
L 10
 
0.6%
M 9
 
0.6%
N 8
 
0.5%
Other values (13) 47
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
e 33
40.2%
h 8
 
9.8%
i 7
 
8.5%
c 6
 
7.3%
u 5
 
6.1%
r 4
 
4.9%
a 4
 
4.9%
t 4
 
4.9%
l 3
 
3.7%
n 2
 
2.4%
Other values (5) 6
 
7.3%
Decimal Number
ValueCountFrequency (%)
2 736
48.3%
5 652
42.8%
4 56
 
3.7%
1 32
 
2.1%
3 21
 
1.4%
0 8
 
0.5%
6 6
 
0.4%
7 6
 
0.4%
9 4
 
0.3%
8 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
& 11
34.4%
. 10
31.2%
, 6
18.8%
· 5
15.6%
Space Separator
ValueCountFrequency (%)
1853
100.0%
Close Punctuation
ValueCountFrequency (%)
) 270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67148
92.2%
Common 3938
 
5.4%
Latin 1709
 
2.3%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5676
 
8.5%
5534
 
8.2%
2897
 
4.3%
2699
 
4.0%
2652
 
3.9%
1875
 
2.8%
1749
 
2.6%
1240
 
1.8%
1064
 
1.6%
1060
 
1.6%
Other values (616) 40702
60.6%
Latin
ValueCountFrequency (%)
S 619
36.2%
G 587
34.3%
C 149
 
8.7%
U 146
 
8.5%
e 33
 
1.9%
K 23
 
1.3%
B 18
 
1.1%
H 11
 
0.6%
L 10
 
0.6%
M 9
 
0.5%
Other values (28) 104
 
6.1%
Common
ValueCountFrequency (%)
1853
47.1%
2 736
 
18.7%
5 652
 
16.6%
) 270
 
6.9%
( 253
 
6.4%
4 56
 
1.4%
1 32
 
0.8%
3 21
 
0.5%
& 11
 
0.3%
. 10
 
0.3%
Other values (8) 44
 
1.1%
Han
ValueCountFrequency (%)
3
30.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67146
92.2%
ASCII 5642
 
7.7%
CJK 10
 
< 0.1%
None 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5676
 
8.5%
5534
 
8.2%
2897
 
4.3%
2699
 
4.0%
2652
 
3.9%
1875
 
2.8%
1749
 
2.6%
1240
 
1.8%
1064
 
1.6%
1060
 
1.6%
Other values (615) 40700
60.6%
ASCII
ValueCountFrequency (%)
1853
32.8%
2 736
 
13.0%
5 652
 
11.6%
S 619
 
11.0%
G 587
 
10.4%
) 270
 
4.8%
( 253
 
4.5%
C 149
 
2.6%
U 146
 
2.6%
4 56
 
1.0%
Other values (45) 321
 
5.7%
None
ValueCountFrequency (%)
· 5
71.4%
2
 
28.6%
CJK
ValueCountFrequency (%)
3
30.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%

sitepostno
Real number (ℝ)

MISSING 

Distinct931
Distinct (%)13.9%
Missing3323
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean609115.29
Minimum607
Maximum626756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:05.018444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum607
5-th percentile601829
Q1607824
median611073
Q3614030
95-th percentile617756.4
Maximum626756
Range626149
Interquartile range (IQR)6206

Descriptive statistics

Standard deviation30036.286
Coefficient of variation (CV)0.049311332
Kurtosis371.56765
Mean609115.29
Median Absolute Deviation (MAD)3239
Skewness-19.072537
Sum4.0670628 × 109
Variance9.021785 × 108
MonotonicityNot monotonic
2024-04-17T06:50:05.155120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609310 131
 
1.3%
609320 101
 
1.0%
609400 96
 
1.0%
614847 79
 
0.8%
609390 70
 
0.7%
616852 55
 
0.5%
614849 50
 
0.5%
601812 50
 
0.5%
612842 46
 
0.5%
616820 46
 
0.5%
Other values (921) 5953
59.5%
(Missing) 3323
33.2%
ValueCountFrequency (%)
607 9
0.1%
46067 1
 
< 0.1%
46217 1
 
< 0.1%
46235 1
 
< 0.1%
46702 1
 
< 0.1%
46957 1
 
< 0.1%
47256 1
 
< 0.1%
47354 1
 
< 0.1%
48111 1
 
< 0.1%
600011 2
 
< 0.1%
ValueCountFrequency (%)
626756 1
 
< 0.1%
621021 1
 
< 0.1%
619963 42
0.4%
619962 6
 
0.1%
619961 5
 
0.1%
619953 6
 
0.1%
619952 3
 
< 0.1%
619951 2
 
< 0.1%
619913 1
 
< 0.1%
619912 8
 
0.1%

sitewhladdr
Text

MISSING 

Distinct7549
Distinct (%)82.8%
Missing881
Missing (%)8.8%
Memory size156.2 KiB
2024-04-17T06:50:05.470832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length57
Mean length23.918522
Min length2

Characters and Unicode

Total characters218113
Distinct characters459
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6513 ?
Unique (%)71.4%

Sample

1st row부산광역시 부산진구 가야1동 19-1
2nd row부산광역시 사하구 감천동 42번지 1호
3rd row부산광역시 기장군 기장읍 교리 356번지 3호
4th row부산광역시 사하구 장림동 321번지 20호
5th row부산광역시 부산진구 가야동 271번지 53호
ValueCountFrequency (%)
부산광역시 8884
 
19.3%
부산진구 1215
 
2.6%
금정구 1174
 
2.5%
1호 1054
 
2.3%
해운대구 935
 
2.0%
사하구 933
 
2.0%
동래구 665
 
1.4%
남구 653
 
1.4%
북구 518
 
1.1%
연제구 513
 
1.1%
Other values (4933) 29507
64.1%
2024-04-17T06:50:05.925199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37045
 
17.0%
11232
 
5.1%
1 10909
 
5.0%
10886
 
5.0%
10228
 
4.7%
9251
 
4.2%
9150
 
4.2%
9043
 
4.1%
8965
 
4.1%
7566
 
3.5%
Other values (449) 93838
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130476
59.8%
Decimal Number 47358
 
21.7%
Space Separator 37045
 
17.0%
Dash Punctuation 1682
 
0.8%
Other Punctuation 513
 
0.2%
Open Punctuation 346
 
0.2%
Close Punctuation 343
 
0.2%
Uppercase Letter 233
 
0.1%
Math Symbol 76
 
< 0.1%
Lowercase Letter 40
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11232
 
8.6%
10886
 
8.3%
10228
 
7.8%
9251
 
7.1%
9150
 
7.0%
9043
 
6.9%
8965
 
6.9%
7566
 
5.8%
7441
 
5.7%
7255
 
5.6%
Other values (386) 39459
30.2%
Uppercase Letter
ValueCountFrequency (%)
B 37
15.9%
A 36
15.5%
S 22
9.4%
F 20
8.6%
G 17
 
7.3%
K 17
 
7.3%
L 13
 
5.6%
C 11
 
4.7%
E 6
 
2.6%
H 6
 
2.6%
Other values (15) 48
20.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
20.0%
s 7
17.5%
i 6
15.0%
a 4
10.0%
u 3
 
7.5%
q 2
 
5.0%
r 2
 
5.0%
l 2
 
5.0%
c 1
 
2.5%
j 1
 
2.5%
Other values (4) 4
10.0%
Decimal Number
ValueCountFrequency (%)
1 10909
23.0%
2 7290
15.4%
3 5542
11.7%
4 4591
9.7%
5 3963
 
8.4%
0 3305
 
7.0%
6 3279
 
6.9%
7 3182
 
6.7%
8 2788
 
5.9%
9 2509
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 470
91.6%
@ 18
 
3.5%
. 13
 
2.5%
· 7
 
1.4%
/ 5
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 345
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 342
99.7%
] 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 75
98.7%
1
 
1.3%
Space Separator
ValueCountFrequency (%)
37045
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1682
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130476
59.8%
Common 87363
40.1%
Latin 274
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11232
 
8.6%
10886
 
8.3%
10228
 
7.8%
9251
 
7.1%
9150
 
7.0%
9043
 
6.9%
8965
 
6.9%
7566
 
5.8%
7441
 
5.7%
7255
 
5.6%
Other values (386) 39459
30.2%
Latin
ValueCountFrequency (%)
B 37
13.5%
A 36
13.1%
S 22
 
8.0%
F 20
 
7.3%
G 17
 
6.2%
K 17
 
6.2%
L 13
 
4.7%
C 11
 
4.0%
e 8
 
2.9%
s 7
 
2.6%
Other values (30) 86
31.4%
Common
ValueCountFrequency (%)
37045
42.4%
1 10909
 
12.5%
2 7290
 
8.3%
3 5542
 
6.3%
4 4591
 
5.3%
5 3963
 
4.5%
0 3305
 
3.8%
6 3279
 
3.8%
7 3182
 
3.6%
8 2788
 
3.2%
Other values (13) 5469
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130476
59.8%
ASCII 87628
40.2%
None 7
 
< 0.1%
Math Operators 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37045
42.3%
1 10909
 
12.4%
2 7290
 
8.3%
3 5542
 
6.3%
4 4591
 
5.2%
5 3963
 
4.5%
0 3305
 
3.8%
6 3279
 
3.7%
7 3182
 
3.6%
8 2788
 
3.2%
Other values (50) 5734
 
6.5%
Hangul
ValueCountFrequency (%)
11232
 
8.6%
10886
 
8.3%
10228
 
7.8%
9251
 
7.1%
9150
 
7.0%
9043
 
6.9%
8965
 
6.9%
7566
 
5.8%
7441
 
5.7%
7255
 
5.6%
Other values (386) 39459
30.2%
None
ValueCountFrequency (%)
· 7
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1852
Distinct (%)23.6%
Missing2159
Missing (%)21.6%
Infinite0
Infinite (%)0.0%
Mean138541.09
Minimum46002
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:06.035961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46233
Q147251
median48075
Q349228
95-th percentile614817
Maximum619963
Range573961
Interquartile range (IQR)1977

Descriptive statistics

Standard deviation207138.45
Coefficient of variation (CV)1.4951408
Kurtosis1.4042564
Mean138541.09
Median Absolute Deviation (MAD)942
Skewness1.8447051
Sum1.0863007 × 109
Variance4.2906337 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:06.133296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47257 61
 
0.6%
48060 56
 
0.6%
46576 55
 
0.5%
47286 55
 
0.5%
48095 48
 
0.5%
46015 43
 
0.4%
46526 41
 
0.4%
47287 40
 
0.4%
48111 37
 
0.4%
46548 36
 
0.4%
Other values (1842) 7369
73.7%
(Missing) 2159
 
21.6%
ValueCountFrequency (%)
46002 3
 
< 0.1%
46007 3
 
< 0.1%
46008 13
 
0.1%
46010 1
 
< 0.1%
46012 4
 
< 0.1%
46013 5
 
0.1%
46014 2
 
< 0.1%
46015 43
0.4%
46016 1
 
< 0.1%
46017 12
 
0.1%
ValueCountFrequency (%)
619963 21
0.2%
619962 2
 
< 0.1%
619961 1
 
< 0.1%
619953 3
 
< 0.1%
619952 3
 
< 0.1%
619951 2
 
< 0.1%
619913 2
 
< 0.1%
619912 6
 
0.1%
619911 1
 
< 0.1%
619906 4
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct7424
Distinct (%)81.3%
Missing869
Missing (%)8.7%
Memory size156.2 KiB
2024-04-17T06:50:06.414678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length58
Mean length28.268864
Min length13

Characters and Unicode

Total characters258123
Distinct characters535
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6302 ?
Unique (%)69.0%

Sample

1st row부산광역시 부산진구 가야대로 651 (가야동)
2nd row부산광역시 사하구 감천로 141, 1층 (감천동)
3rd row부산광역시 기장군 기장읍 차성로 436
4th row부산광역시 사하구 장림로 197, 101호 (장림동)
5th row부산광역시 사상구 사상로 313 (덕포동)
ValueCountFrequency (%)
부산광역시 9131
 
17.7%
부산진구 1201
 
2.3%
금정구 1077
 
2.1%
해운대구 1005
 
1.9%
사하구 852
 
1.7%
동래구 727
 
1.4%
북구 564
 
1.1%
2층 555
 
1.1%
남구 553
 
1.1%
1층 546
 
1.1%
Other values (4980) 35356
68.6%
2024-04-17T06:50:06.812861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42460
 
16.4%
11535
 
4.5%
11522
 
4.5%
11242
 
4.4%
9636
 
3.7%
9578
 
3.7%
9458
 
3.7%
9138
 
3.5%
9079
 
3.5%
( 8962
 
3.5%
Other values (525) 125513
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153543
59.5%
Space Separator 42460
 
16.4%
Decimal Number 37241
 
14.4%
Open Punctuation 8962
 
3.5%
Close Punctuation 8962
 
3.5%
Other Punctuation 5440
 
2.1%
Dash Punctuation 1028
 
0.4%
Uppercase Letter 297
 
0.1%
Math Symbol 127
 
< 0.1%
Lowercase Letter 61
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11535
 
7.5%
11522
 
7.5%
11242
 
7.3%
9636
 
6.3%
9578
 
6.2%
9458
 
6.2%
9138
 
6.0%
9079
 
5.9%
4924
 
3.2%
2558
 
1.7%
Other values (464) 64873
42.3%
Uppercase Letter
ValueCountFrequency (%)
B 60
20.2%
A 40
13.5%
S 30
10.1%
C 23
 
7.7%
K 21
 
7.1%
G 17
 
5.7%
E 13
 
4.4%
L 12
 
4.0%
I 10
 
3.4%
F 8
 
2.7%
Other values (14) 63
21.2%
Lowercase Letter
ValueCountFrequency (%)
e 16
26.2%
s 8
13.1%
i 7
11.5%
a 6
 
9.8%
r 4
 
6.6%
v 3
 
4.9%
q 3
 
4.9%
u 3
 
4.9%
c 2
 
3.3%
o 2
 
3.3%
Other values (6) 7
11.5%
Decimal Number
ValueCountFrequency (%)
1 8469
22.7%
2 5798
15.6%
3 4043
10.9%
0 3491
9.4%
4 3410
9.2%
5 2866
 
7.7%
7 2489
 
6.7%
6 2455
 
6.6%
9 2145
 
5.8%
8 2075
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 5411
99.5%
. 16
 
0.3%
@ 8
 
0.1%
· 5
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 126
99.2%
1
 
0.8%
Space Separator
ValueCountFrequency (%)
42460
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8962
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8962
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1028
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153543
59.5%
Common 104220
40.4%
Latin 360
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11535
 
7.5%
11522
 
7.5%
11242
 
7.3%
9636
 
6.3%
9578
 
6.2%
9458
 
6.2%
9138
 
6.0%
9079
 
5.9%
4924
 
3.2%
2558
 
1.7%
Other values (464) 64873
42.3%
Latin
ValueCountFrequency (%)
B 60
16.7%
A 40
 
11.1%
S 30
 
8.3%
C 23
 
6.4%
K 21
 
5.8%
G 17
 
4.7%
e 16
 
4.4%
E 13
 
3.6%
L 12
 
3.3%
I 10
 
2.8%
Other values (31) 118
32.8%
Common
ValueCountFrequency (%)
42460
40.7%
( 8962
 
8.6%
) 8962
 
8.6%
1 8469
 
8.1%
2 5798
 
5.6%
, 5411
 
5.2%
3 4043
 
3.9%
0 3491
 
3.3%
4 3410
 
3.3%
5 2866
 
2.7%
Other values (10) 10348
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153543
59.5%
ASCII 104572
40.5%
None 5
 
< 0.1%
Number Forms 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42460
40.6%
( 8962
 
8.6%
) 8962
 
8.6%
1 8469
 
8.1%
2 5798
 
5.5%
, 5411
 
5.2%
3 4043
 
3.9%
0 3491
 
3.3%
4 3410
 
3.3%
5 2866
 
2.7%
Other values (48) 10700
 
10.2%
Hangul
ValueCountFrequency (%)
11535
 
7.5%
11522
 
7.5%
11242
 
7.3%
9636
 
6.3%
9578
 
6.2%
9458
 
6.2%
9138
 
6.0%
9079
 
5.9%
4924
 
3.2%
2558
 
1.7%
Other values (464) 64873
42.3%
None
ValueCountFrequency (%)
· 5
100.0%
Number Forms
ValueCountFrequency (%)
2
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

Distinct5265
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20055073
Minimum19570101
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:06.931881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19570101
5-th percentile19821117
Q120001026
median20090702
Q320131223
95-th percentile20171011
Maximum20180903
Range610802
Interquartile range (IQR)130197

Descriptive statistics

Standard deviation111589.1
Coefficient of variation (CV)0.0055641334
Kurtosis1.3013189
Mean20055073
Median Absolute Deviation (MAD)59923
Skewness-1.2950941
Sum2.0055073 × 1011
Variance1.2452127 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:07.049381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121112 126
 
1.3%
20121109 84
 
0.8%
20121113 78
 
0.8%
20121115 76
 
0.8%
20121114 76
 
0.8%
20121116 74
 
0.7%
20121108 47
 
0.5%
20121107 30
 
0.3%
20121106 26
 
0.3%
20121105 17
 
0.2%
Other values (5255) 9366
93.7%
ValueCountFrequency (%)
19570101 1
< 0.1%
19590110 1
< 0.1%
19590207 1
< 0.1%
19600101 1
< 0.1%
19610418 1
< 0.1%
19611107 1
< 0.1%
19611220 1
< 0.1%
19620130 1
< 0.1%
19620312 1
< 0.1%
19620313 1
< 0.1%
ValueCountFrequency (%)
20180903 6
0.1%
20180901 1
 
< 0.1%
20180831 1
 
< 0.1%
20180830 6
0.1%
20180829 5
0.1%
20180828 2
 
< 0.1%
20180827 3
< 0.1%
20180824 1
 
< 0.1%
20180823 1
 
< 0.1%
20180822 3
< 0.1%

dcbymd
Real number (ℝ)

MISSING 

Distinct2527
Distinct (%)60.2%
Missing5803
Missing (%)58.0%
Infinite0
Infinite (%)0.0%
Mean20101326
Minimum19760520
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:07.160133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19760520
5-th percentile19920119
Q120090427
median20121122
Q320151021
95-th percentile20180213
Maximum20180903
Range420383
Interquartile range (IQR)60594

Descriptive statistics

Standard deviation78420.106
Coefficient of variation (CV)0.0039012404
Kurtosis2.6445679
Mean20101326
Median Absolute Deviation (MAD)30391
Skewness-1.7195505
Sum8.4365265 × 1010
Variance6.149713 × 109
MonotonicityNot monotonic
2024-04-17T06:50:07.265964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090302 12
 
0.1%
20130902 9
 
0.1%
20130701 9
 
0.1%
20131231 9
 
0.1%
20151102 8
 
0.1%
20180430 8
 
0.1%
20090102 8
 
0.1%
20130102 8
 
0.1%
20101129 8
 
0.1%
20141201 8
 
0.1%
Other values (2517) 4110
41.1%
(Missing) 5803
58.0%
ValueCountFrequency (%)
19760520 1
< 0.1%
19760609 1
< 0.1%
19770415 1
< 0.1%
19770512 1
< 0.1%
19781124 1
< 0.1%
19781216 1
< 0.1%
19790214 1
< 0.1%
19790411 1
< 0.1%
19790915 1
< 0.1%
19800229 1
< 0.1%
ValueCountFrequency (%)
20180903 4
< 0.1%
20180901 1
 
< 0.1%
20180831 3
< 0.1%
20180830 3
< 0.1%
20180827 1
 
< 0.1%
20180824 2
< 0.1%
20180822 1
 
< 0.1%
20180821 3
< 0.1%
20180814 2
< 0.1%
20180813 1
 
< 0.1%

clgstdt
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)98.4%
Missing9938
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20129656
Minimum20000403
Maximum20181001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:07.367872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20081568
Q120100738
median20121124
Q320170193
95-th percentile20180522
Maximum20181001
Range180598
Interquartile range (IQR)69455.5

Descriptive statistics

Standard deviation37750.146
Coefficient of variation (CV)0.0018753498
Kurtosis0.72477983
Mean20129656
Median Absolute Deviation (MAD)25462.5
Skewness-0.52602773
Sum1.2480387 × 109
Variance1.4250735 × 109
MonotonicityNot monotonic
2024-04-17T06:50:07.487118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110706 2
 
< 0.1%
20100504 1
 
< 0.1%
20080801 1
 
< 0.1%
20161010 1
 
< 0.1%
20000403 1
 
< 0.1%
20170309 1
 
< 0.1%
20170224 1
 
< 0.1%
20140906 1
 
< 0.1%
20170307 1
 
< 0.1%
20120726 1
 
< 0.1%
Other values (51) 51
 
0.5%
(Missing) 9938
99.4%
ValueCountFrequency (%)
20000403 1
< 0.1%
20051001 1
< 0.1%
20080801 1
< 0.1%
20081118 1
< 0.1%
20090120 1
< 0.1%
20090201 1
< 0.1%
20090225 1
< 0.1%
20090604 1
< 0.1%
20090901 1
< 0.1%
20090924 1
< 0.1%
ValueCountFrequency (%)
20181001 1
< 0.1%
20180901 1
< 0.1%
20180603 1
< 0.1%
20180528 1
< 0.1%
20180417 1
< 0.1%
20180328 1
< 0.1%
20180224 1
< 0.1%
20180201 1
< 0.1%
20180101 1
< 0.1%
20171017 1
< 0.1%

clgenddt
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)93.7%
Missing9937
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean21405464
Minimum20000403
Maximum99991231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:07.598887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20090537
Q120110463
median20140226
Q320170868
95-th percentile20190920
Maximum99991231
Range79990828
Interquartile range (IQR)60404.5

Descriptive statistics

Standard deviation10060645
Coefficient of variation (CV)0.4700036
Kurtosis62.997957
Mean21405464
Median Absolute Deviation (MAD)30605
Skewness7.9370639
Sum1.3485442 × 109
Variance1.0121658 × 1014
MonotonicityNot monotonic
2024-04-17T06:50:07.714023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170331 2
 
< 0.1%
20170531 2
 
< 0.1%
20111205 2
 
< 0.1%
20121231 2
 
< 0.1%
20121212 1
 
< 0.1%
20080731 1
 
< 0.1%
20000403 1
 
< 0.1%
20170430 1
 
< 0.1%
20150301 1
 
< 0.1%
20191231 1
 
< 0.1%
Other values (49) 49
 
0.5%
(Missing) 9937
99.4%
ValueCountFrequency (%)
20000403 1
< 0.1%
20080731 1
< 0.1%
20090331 1
< 0.1%
20090518 1
< 0.1%
20090712 1
< 0.1%
20091031 1
< 0.1%
20100201 1
< 0.1%
20100224 1
< 0.1%
20100228 1
< 0.1%
20100331 1
< 0.1%
ValueCountFrequency (%)
99991231 1
< 0.1%
20221227 1
< 0.1%
20191231 1
< 0.1%
20190930 1
< 0.1%
20190831 1
< 0.1%
20190602 1
< 0.1%
20190221 1
< 0.1%
20190131 1
< 0.1%
20181231 1
< 0.1%
20181228 1
< 0.1%

ropnymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

trdstatenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
13
5670 
3
4294 
24
 
26
2
 
10

Length

Max length2
Median length2
Mean length1.5696
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row13
5th row3

Common Values

ValueCountFrequency (%)
13 5670
56.7%
3 4294
42.9%
24 26
 
0.3%
2 10
 
0.1%

Length

2024-04-17T06:50:07.828223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:07.902934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 5670
56.7%
3 4294
42.9%
24 26
 
0.3%
2 10
 
0.1%

dtlstatenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
5670 
폐업
4294 
직권폐업
 
26
휴업
 
10

Length

Max length4
Median length3
Mean length2.5722
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 5670
56.7%
폐업 4294
42.9%
직권폐업 26
 
0.3%
휴업 10
 
0.1%

Length

2024-04-17T06:50:07.989429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:08.083424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 5670
56.7%
폐업 4294
42.9%
직권폐업 26
 
0.3%
휴업 10
 
0.1%

x
Real number (ℝ)

MISSING 

Distinct5286
Distinct (%)57.8%
Missing851
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean388239.01
Minimum365157.28
Maximum407581.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:08.169507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365157.28
5-th percentile379634.81
Q1384335.22
median388743.35
Q3391572.76
95-th percentile398147.33
Maximum407581.08
Range42423.807
Interquartile range (IQR)7237.538

Descriptive statistics

Standard deviation5612.2146
Coefficient of variation (CV)0.014455566
Kurtosis0.48147045
Mean388239.01
Median Absolute Deviation (MAD)3436.26
Skewness-0.039361418
Sum3.5519987 × 109
Variance31496953
MonotonicityNot monotonic
2024-04-17T06:50:08.270706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387537.525975 22
 
0.2%
387475.894546 16
 
0.2%
398310.243451 16
 
0.2%
398226.822818 16
 
0.2%
389565.428128 14
 
0.1%
394179.058785 14
 
0.1%
398401.454439 13
 
0.1%
395542.647016 12
 
0.1%
394248.454507 12
 
0.1%
390419.767349 12
 
0.1%
Other values (5276) 9002
90.0%
(Missing) 851
 
8.5%
ValueCountFrequency (%)
365157.276407 1
< 0.1%
365770.285901 1
< 0.1%
366851.651911 1
< 0.1%
366858.579155 1
< 0.1%
366871.978797 1
< 0.1%
366877.108901 1
< 0.1%
367000.987237 1
< 0.1%
367041.14892 1
< 0.1%
367134.0 1
< 0.1%
367149.616883 2
< 0.1%
ValueCountFrequency (%)
407581.083119 2
< 0.1%
407515.749132 1
 
< 0.1%
407504.0 1
 
< 0.1%
407472.279312 1
 
< 0.1%
407448.0 2
< 0.1%
407209.258171 2
< 0.1%
407126.309068 1
 
< 0.1%
407077.691757 1
 
< 0.1%
405468.503509 3
< 0.1%
405436.871967 1
 
< 0.1%

y
Real number (ℝ)

MISSING 

Distinct5285
Distinct (%)57.8%
Missing851
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean187744.5
Minimum170014.45
Maximum211893.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:08.373971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170014.45
5-th percentile178463.45
Q1183707.09
median187554.34
Q3191801.04
95-th percentile197664.2
Maximum211893.97
Range41879.512
Interquartile range (IQR)8093.9462

Descriptive statistics

Standard deviation6060.9019
Coefficient of variation (CV)0.032282714
Kurtosis0.011961658
Mean187744.5
Median Absolute Deviation (MAD)4155.0688
Skewness0.29566888
Sum1.7176744 × 109
Variance36734532
MonotonicityNot monotonic
2024-04-17T06:50:08.474016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186476.330395 22
 
0.2%
186570.418307 16
 
0.2%
188031.67198 16
 
0.2%
187989.753665 16
 
0.2%
189797.541402 14
 
0.1%
187825.814573 14
 
0.1%
188080.4441 13
 
0.1%
186642.306762 12
 
0.1%
187726.224988 12
 
0.1%
194138.616285 12
 
0.1%
Other values (5275) 9002
90.0%
(Missing) 851
 
8.5%
ValueCountFrequency (%)
170014.453769 1
 
< 0.1%
171205.308829 1
 
< 0.1%
171801.632147 1
 
< 0.1%
174063.354003 1
 
< 0.1%
174237.045871 2
 
< 0.1%
174292.594164 1
 
< 0.1%
174396.378069 5
0.1%
174404.947794 1
 
< 0.1%
174413.752458 4
< 0.1%
174415.392886 2
 
< 0.1%
ValueCountFrequency (%)
211893.965608 1
< 0.1%
211392.6938 1
< 0.1%
208906.876551 1
< 0.1%
206494.685696 1
< 0.1%
206426.679067 2
< 0.1%
206423.253753 1
< 0.1%
206411.480935 1
< 0.1%
206378.281379 1
< 0.1%
206377.970967 1
< 0.1%
206335.181672 1
< 0.1%

lastmodts
Real number (ℝ)

Distinct8048
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0149508 × 1013
Minimum2.0081008 × 1013
Maximum2.0180904 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:08.823517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081008 × 1013
5-th percentile2.0090202 × 1013
Q12.0130705 × 1013
median2.0160724 × 1013
Q32.0170905 × 1013
95-th percentile2.0180705 × 1013
Maximum2.0180904 × 1013
Range9.989602 × 1010
Interquartile range (IQR)4.0200016 × 1010

Descriptive statistics

Standard deviation2.926625 × 1010
Coefficient of variation (CV)0.0014524548
Kurtosis-0.51293336
Mean2.0149508 × 1013
Median Absolute Deviation (MAD)1.9597565 × 1010
Skewness-0.82425242
Sum2.0149508 × 1017
Variance8.5651341 × 1020
MonotonicityNot monotonic
2024-04-17T06:50:08.937124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905183851 208
 
2.1%
20170905183844 190
 
1.9%
20170905183850 181
 
1.8%
20170905183853 177
 
1.8%
20170905183849 159
 
1.6%
20170905183852 109
 
1.1%
20170905183843 103
 
1.0%
20170905183848 101
 
1.0%
20170905183859 85
 
0.9%
20170905183858 65
 
0.7%
Other values (8038) 8622
86.2%
ValueCountFrequency (%)
20081008160928 1
< 0.1%
20081022163931 1
< 0.1%
20081117091658 1
< 0.1%
20081125173655 1
< 0.1%
20081125181445 1
< 0.1%
20081126095545 1
< 0.1%
20081126101537 1
< 0.1%
20081126103530 1
< 0.1%
20081126154559 1
< 0.1%
20081126154902 1
< 0.1%
ValueCountFrequency (%)
20180904181338 1
< 0.1%
20180904174554 1
< 0.1%
20180904174523 1
< 0.1%
20180904174336 1
< 0.1%
20180904172545 1
< 0.1%
20180904165343 1
< 0.1%
20180904154925 1
< 0.1%
20180904143316 1
< 0.1%
20180904140506 1
< 0.1%
20180904132218 1
< 0.1%

uptaenm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4661 
의원
2587 
한의원
1198 
치과의원
1172 
요양병원(일반요양병원)
 
159
Other values (9)
 
223

Length

Max length12
Median length4
Mean length3.4685
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4661
46.6%
의원 2587
25.9%
한의원 1198
 
12.0%
치과의원 1172
 
11.7%
요양병원(일반요양병원) 159
 
1.6%
병원 123
 
1.2%
종합병원 23
 
0.2%
치과병원 19
 
0.2%
조산원 17
 
0.2%
한방병원 12
 
0.1%
Other values (4) 29
 
0.3%

Length

2024-04-17T06:50:09.041696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4661
46.6%
의원 2587
25.9%
한의원 1198
 
12.0%
치과의원 1172
 
11.7%
요양병원(일반요양병원 159
 
1.6%
병원 123
 
1.2%
종합병원 23
 
0.2%
치과병원 19
 
0.2%
조산원 17
 
0.2%
한방병원 12
 
0.1%
Other values (4) 29
 
0.3%

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

2024-04-17T06:50:09.134218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:09.200632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 10000
100.0%

nursecnt
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)19.4%
Missing9969
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean3.7096774
Minimum2
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:09.263367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12.5
median3
Q35
95-th percentile6
Maximum8
Range6
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.531743
Coefficient of variation (CV)0.41290463
Kurtosis0.41542984
Mean3.7096774
Median Absolute Deviation (MAD)1
Skewness0.82355924
Sum115
Variance2.3462366
MonotonicityNot monotonic
2024-04-17T06:50:09.339847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 8
 
0.1%
2 8
 
0.1%
4 6
 
0.1%
5 5
 
0.1%
6 3
 
< 0.1%
8 1
 
< 0.1%
(Missing) 9969
99.7%
ValueCountFrequency (%)
2 8
0.1%
3 8
0.1%
4 6
0.1%
5 5
0.1%
6 3
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 3
 
< 0.1%
5 5
0.1%
4 6
0.1%
3 8
0.1%
2 8
0.1%

nursaidcnt
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)54.8%
Missing9969
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean8.2258065
Minimum2
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:09.423288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14.5
median7
Q310.5
95-th percentile16.5
Maximum22
Range20
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.0113849
Coefficient of variation (CV)0.60922718
Kurtosis0.4692324
Mean8.2258065
Median Absolute Deviation (MAD)3
Skewness0.8103611
Sum255
Variance25.113978
MonotonicityNot monotonic
2024-04-17T06:50:09.514212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 5
 
0.1%
9 4
 
< 0.1%
7 4
 
< 0.1%
4 2
 
< 0.1%
10 2
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
22 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 9969
99.7%
ValueCountFrequency (%)
2 5
0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 4
< 0.1%
8 1
 
< 0.1%
9 4
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
22 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 2
< 0.1%
9 4
< 0.1%

bdnglayercnt
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)40.6%
Missing9968
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean6.96875
Minimum0
Maximum23
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:09.606769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.75
median7
Q39.5
95-th percentile14
Maximum23
Range23
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation5.1711631
Coefficient of variation (CV)0.7420503
Kurtosis1.4722041
Mean6.96875
Median Absolute Deviation (MAD)4
Skewness0.79245234
Sum223
Variance26.740927
MonotonicityNot monotonic
2024-04-17T06:50:09.685869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8 5
 
0.1%
0 5
 
0.1%
2 3
 
< 0.1%
12 3
 
< 0.1%
7 3
 
< 0.1%
11 2
 
< 0.1%
9 2
 
< 0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
14 2
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 9968
99.7%
ValueCountFrequency (%)
0 5
0.1%
2 3
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 3
< 0.1%
8 5
0.1%
9 2
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
14 2
 
< 0.1%
12 3
< 0.1%
11 2
 
< 0.1%
9 2
 
< 0.1%
8 5
0.1%
7 3
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 1
 
< 0.1%

emercargen
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5958 
0
4042 

Length

Max length4
Median length4
Mean length2.7874
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5958
59.6%
0 4042
40.4%

Length

2024-04-17T06:50:09.801642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:09.899815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5958
59.6%
0 4042
40.4%

emercarspec
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5958 
0
4042 

Length

Max length4
Median length4
Mean length2.7874
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5958
59.6%
0 4042
40.4%

Length

2024-04-17T06:50:09.977677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:10.078859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5958
59.6%
0 4042
40.4%

rescnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

pomfacilar
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)89.5%
Missing9981
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean49.036842
Minimum0
Maximum162
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:10.165576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118.46
median34.53
Q359.035
95-th percentile161.37
Maximum162
Range162
Interquartile range (IQR)40.575

Descriptive statistics

Standard deviation48.608792
Coefficient of variation (CV)0.99127085
Kurtosis1.3966614
Mean49.036842
Median Absolute Deviation (MAD)22.47
Skewness1.4139733
Sum931.7
Variance2362.8147
MonotonicityNot monotonic
2024-04-17T06:50:10.266114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 3
 
< 0.1%
34.53 1
 
< 0.1%
109.6 1
 
< 0.1%
15.4 1
 
< 0.1%
161.3 1
 
< 0.1%
60.48 1
 
< 0.1%
24.05 1
 
< 0.1%
162.0 1
 
< 0.1%
28.32 1
 
< 0.1%
20.42 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 9981
99.8%
ValueCountFrequency (%)
0.0 3
< 0.1%
15.4 1
 
< 0.1%
16.5 1
 
< 0.1%
20.42 1
 
< 0.1%
23.76 1
 
< 0.1%
24.05 1
 
< 0.1%
28.32 1
 
< 0.1%
34.53 1
 
< 0.1%
38.34 1
 
< 0.1%
42.56 1
 
< 0.1%
ValueCountFrequency (%)
162.0 1
< 0.1%
161.3 1
< 0.1%
109.6 1
< 0.1%
79.85 1
< 0.1%
60.48 1
< 0.1%
57.59 1
< 0.1%
57.0 1
< 0.1%
42.56 1
< 0.1%
38.34 1
< 0.1%
34.53 1
< 0.1%

etcstfcnt
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)40.0%
Missing9985
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean2.6
Minimum0
Maximum6
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:10.346337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q11
median1
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1646511
Coefficient of variation (CV)0.83255811
Kurtosis-1.4742827
Mean2.6
Median Absolute Deviation (MAD)1
Skewness0.59869521
Sum39
Variance4.6857143
MonotonicityNot monotonic
2024-04-17T06:50:10.425000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
0.1%
5 3
 
< 0.1%
6 2
 
< 0.1%
0 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
(Missing) 9985
99.9%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 7
0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 3
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1 7
0.1%
0 1
 
< 0.1%

etcepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

mmknurmar
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)96.3%
Missing9973
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean43.311852
Minimum6.8
Maximum494.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:10.512923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile8.816
Q112.5
median22.96
Q337.05
95-th percentile64.381
Maximum494.67
Range487.87
Interquartile range (IQR)24.55

Descriptive statistics

Standard deviation91.693453
Coefficient of variation (CV)2.1170522
Kurtosis25.082484
Mean43.311852
Median Absolute Deviation (MAD)11.96
Skewness4.9327032
Sum1169.42
Variance8407.6893
MonotonicityNot monotonic
2024-04-17T06:50:10.608473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
9.3 2
 
< 0.1%
32.0 1
 
< 0.1%
14.9 1
 
< 0.1%
8.97 1
 
< 0.1%
13.0 1
 
< 0.1%
53.28 1
 
< 0.1%
6.8 1
 
< 0.1%
68.8 1
 
< 0.1%
494.67 1
 
< 0.1%
35.3 1
 
< 0.1%
Other values (16) 16
 
0.2%
(Missing) 9973
99.7%
ValueCountFrequency (%)
6.8 1
< 0.1%
8.75 1
< 0.1%
8.97 1
< 0.1%
9.3 2
< 0.1%
11.0 1
< 0.1%
12.0 1
< 0.1%
13.0 1
< 0.1%
14.12 1
< 0.1%
14.9 1
< 0.1%
15.3 1
< 0.1%
ValueCountFrequency (%)
494.67 1
< 0.1%
68.8 1
< 0.1%
54.07 1
< 0.1%
53.28 1
< 0.1%
46.8 1
< 0.1%
41.29 1
< 0.1%
38.8 1
< 0.1%
35.3 1
< 0.1%
33.66 1
< 0.1%
33.4 1
< 0.1%

btrmar
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)92.9%
Missing9986
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean25.272857
Minimum0
Maximum160.44
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:10.691970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.4575
median7.565
Q318.42
95-th percentile108.024
Maximum160.44
Range160.44
Interquartile range (IQR)14.9625

Descriptive statistics

Standard deviation44.530506
Coefficient of variation (CV)1.7619894
Kurtosis6.8867059
Mean25.272857
Median Absolute Deviation (MAD)4.4
Skewness2.5879968
Sum353.82
Variance1982.9659
MonotonicityNot monotonic
2024-04-17T06:50:10.777033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
4.14 1
 
< 0.1%
3.23 1
 
< 0.1%
6.0 1
 
< 0.1%
8.03 1
 
< 0.1%
9.18 1
 
< 0.1%
7.1 1
 
< 0.1%
42.4 1
 
< 0.1%
160.44 1
 
< 0.1%
79.8 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 9986
99.9%
ValueCountFrequency (%)
0.0 2
< 0.1%
3.1 1
< 0.1%
3.23 1
< 0.1%
4.14 1
< 0.1%
6.0 1
< 0.1%
7.1 1
< 0.1%
8.03 1
< 0.1%
8.9 1
< 0.1%
9.18 1
< 0.1%
21.5 1
< 0.1%
ValueCountFrequency (%)
160.44 1
< 0.1%
79.8 1
< 0.1%
42.4 1
< 0.1%
21.5 1
< 0.1%
9.18 1
< 0.1%
8.9 1
< 0.1%
8.03 1
< 0.1%
7.1 1
< 0.1%
6.0 1
< 0.1%
4.14 1
< 0.1%

btpnum
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)33.3%
Missing9982
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2.0555556
Minimum0
Maximum6
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:10.876652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.85
Q11
median2
Q32.75
95-th percentile4.3
Maximum6
Range6
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation1.4741786
Coefficient of variation (CV)0.71716798
Kurtosis1.690724
Mean2.0555556
Median Absolute Deviation (MAD)1
Skewness1.2567212
Sum37
Variance2.1732026
MonotonicityNot monotonic
2024-04-17T06:50:10.984829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
0.1%
2 5
 
0.1%
4 2
 
< 0.1%
3 2
 
< 0.1%
0 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 9982
99.8%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 7
0.1%
2 5
0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 2
 
< 0.1%
3 2
 
< 0.1%
2 5
0.1%
1 7
0.1%
0 1
 
< 0.1%

sicbnum
Real number (ℝ)

MISSING  ZEROS 

Distinct199
Distinct (%)4.9%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean13.874072
Minimum0
Maximum999
Zeros3401
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:11.087821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile98
Maximum999
Range999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation56.337976
Coefficient of variation (CV)4.0606662
Kurtosis67.870691
Mean13.874072
Median Absolute Deviation (MAD)0
Skewness6.7937908
Sum56079
Variance3173.9676
MonotonicityNot monotonic
2024-04-17T06:50:11.202464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3401
34.0%
29 63
 
0.6%
1 38
 
0.4%
2 36
 
0.4%
3 26
 
0.3%
4 23
 
0.2%
199 14
 
0.1%
7 10
 
0.1%
5 9
 
0.1%
28 9
 
0.1%
Other values (189) 413
 
4.1%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0 3401
34.0%
1 38
 
0.4%
2 36
 
0.4%
3 26
 
0.3%
4 23
 
0.2%
5 9
 
0.1%
6 8
 
0.1%
7 10
 
0.1%
8 8
 
0.1%
9 6
 
0.1%
ValueCountFrequency (%)
999 1
< 0.1%
896 1
< 0.1%
797 1
< 0.1%
580 1
< 0.1%
555 1
< 0.1%
539 1
< 0.1%
457 1
< 0.1%
439 1
< 0.1%
428 1
< 0.1%
420 1
< 0.1%

astnepnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

ofear
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing9980
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean13.9385
Minimum0
Maximum42
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:11.301753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.8
Q17.9775
median11.355
Q314.505
95-th percentile32.12
Maximum42
Range42
Interquartile range (IQR)6.5275

Descriptive statistics

Standard deviation10.213824
Coefficient of variation (CV)0.73277785
Kurtosis1.9780919
Mean13.9385
Median Absolute Deviation (MAD)3.4
Skewness1.4708154
Sum278.77
Variance104.3222
MonotonicityNot monotonic
2024-04-17T06:50:11.385374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 1
 
< 0.1%
28.2 1
 
< 0.1%
13.94 1
 
< 0.1%
6.6 1
 
< 0.1%
12.4 1
 
< 0.1%
12.06 1
 
< 0.1%
7.6 1
 
< 0.1%
31.6 1
 
< 0.1%
11.42 1
 
< 0.1%
10.11 1
 
< 0.1%
Other values (10) 10
 
0.1%
(Missing) 9980
99.8%
ValueCountFrequency (%)
0.0 1
< 0.1%
4.0 1
< 0.1%
6.6 1
< 0.1%
7.6 1
< 0.1%
7.91 1
< 0.1%
8.0 1
< 0.1%
8.4 1
< 0.1%
9.2 1
< 0.1%
10.11 1
< 0.1%
11.29 1
< 0.1%
ValueCountFrequency (%)
42.0 1
< 0.1%
31.6 1
< 0.1%
28.2 1
< 0.1%
25.2 1
< 0.1%
16.2 1
< 0.1%
13.94 1
< 0.1%
12.64 1
< 0.1%
12.4 1
< 0.1%
12.06 1
< 0.1%
11.42 1
< 0.1%

warmar
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)94.4%
Missing9982
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean15.907222
Minimum0
Maximum48.7
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:11.466873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.025
median9.06
Q327.725
95-th percentile43.005
Maximum48.7
Range48.7
Interquartile range (IQR)22.7

Descriptive statistics

Standard deviation15.514358
Coefficient of variation (CV)0.97530275
Kurtosis-0.50518631
Mean15.907222
Median Absolute Deviation (MAD)7.32
Skewness0.88856981
Sum286.33
Variance240.69529
MonotonicityNot monotonic
2024-04-17T06:50:11.552341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
42.0 1
 
< 0.1%
37.0 1
 
< 0.1%
5.52 1
 
< 0.1%
11.62 1
 
< 0.1%
7.2 1
 
< 0.1%
4.86 1
 
< 0.1%
16.2 1
 
< 0.1%
5.75 1
 
< 0.1%
10.12 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 9982
99.8%
ValueCountFrequency (%)
0.0 2
< 0.1%
1.56 1
< 0.1%
2.5 1
< 0.1%
4.86 1
< 0.1%
5.52 1
< 0.1%
5.75 1
< 0.1%
7.2 1
< 0.1%
8.0 1
< 0.1%
10.12 1
< 0.1%
11.62 1
< 0.1%
ValueCountFrequency (%)
48.7 1
< 0.1%
42.0 1
< 0.1%
37.0 1
< 0.1%
30.2 1
< 0.1%
27.9 1
< 0.1%
27.2 1
< 0.1%
16.2 1
< 0.1%
11.62 1
< 0.1%
10.12 1
< 0.1%
8.0 1
< 0.1%

facilmngnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

pharmtrdar
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1103
Distinct (%)41.8%
Missing7364
Missing (%)73.6%
Infinite0
Infinite (%)0.0%
Mean77.173809
Minimum0
Maximum74949
Zeros296
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:11.647191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.41
median42
Q366
95-th percentile131.435
Maximum74949
Range74949
Interquartile range (IQR)46.59

Descriptive statistics

Standard deviation1459.5559
Coefficient of variation (CV)18.912581
Kurtosis2630.895
Mean77.173809
Median Absolute Deviation (MAD)24
Skewness51.267498
Sum203430.16
Variance2130303.5
MonotonicityNot monotonic
2024-04-17T06:50:11.755333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 296
 
3.0%
1.0 289
 
2.9%
33.0 28
 
0.3%
66.0 28
 
0.3%
49.5 26
 
0.3%
82.5 19
 
0.2%
46.2 16
 
0.2%
99.0 16
 
0.2%
30.0 14
 
0.1%
59.4 14
 
0.1%
Other values (1093) 1890
 
18.9%
(Missing) 7364
73.6%
ValueCountFrequency (%)
0.0 296
3.0%
1.0 289
2.9%
9.0 1
 
< 0.1%
11.11 2
 
< 0.1%
12.0 1
 
< 0.1%
12.5 1
 
< 0.1%
12.9 1
 
< 0.1%
12.96 4
 
< 0.1%
13.2 2
 
< 0.1%
13.51 1
 
< 0.1%
ValueCountFrequency (%)
74949.0 1
 
< 0.1%
516.04 1
 
< 0.1%
454.92 1
 
< 0.1%
450.0 2
< 0.1%
364.85 1
 
< 0.1%
282.0 1
 
< 0.1%
251.0 3
< 0.1%
250.0 2
< 0.1%
247.07 1
 
< 0.1%
240.0 1
 
< 0.1%

nutrcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9984 
0
 
8
1
 
7
2
 
1

Length

Max length4
Median length4
Mean length3.9952
Min length1

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> 9984
99.8%
0 8
 
0.1%
1 7
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T06:50:11.869791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:11.947844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9984
99.8%
0 8
 
0.1%
1 7
 
0.1%
2 1
 
< 0.1%

bbrmar
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)97.0%
Missing9967
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean54.273636
Minimum1.7
Maximum114.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:12.028052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile17.68
Q124.13
median53.43
Q381
95-th percentile102.192
Maximum114.3
Range112.6
Interquartile range (IQR)56.87

Descriptive statistics

Standard deviation30.903763
Coefficient of variation (CV)0.56940653
Kurtosis-1.0604794
Mean54.273636
Median Absolute Deviation (MAD)27.57
Skewness0.29729598
Sum1791.03
Variance955.04258
MonotonicityNot monotonic
2024-04-17T06:50:12.119758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
81.0 2
 
< 0.1%
19.82 1
 
< 0.1%
23.73 1
 
< 0.1%
32.38 1
 
< 0.1%
87.01 1
 
< 0.1%
18.0 1
 
< 0.1%
96.2 1
 
< 0.1%
93.0 1
 
< 0.1%
40.3 1
 
< 0.1%
17.2 1
 
< 0.1%
Other values (22) 22
 
0.2%
(Missing) 9967
99.7%
ValueCountFrequency (%)
1.7 1
< 0.1%
17.2 1
< 0.1%
18.0 1
< 0.1%
19.82 1
< 0.1%
20.5 1
< 0.1%
22.2 1
< 0.1%
22.4 1
< 0.1%
23.73 1
< 0.1%
24.13 1
< 0.1%
29.89 1
< 0.1%
ValueCountFrequency (%)
114.3 1
< 0.1%
103.08 1
< 0.1%
101.6 1
< 0.1%
99.87 1
< 0.1%
96.2 1
< 0.1%
93.0 1
< 0.1%
87.01 1
< 0.1%
81.0 2
< 0.1%
71.4 1
< 0.1%
67.92 1
< 0.1%

babyrglstnum
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)63.9%
Missing9964
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean22.25
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:12.209081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.75
Q111.75
median19.5
Q328.25
95-th percentile46.25
Maximum50
Range45
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation13.380957
Coefficient of variation (CV)0.60139131
Kurtosis-0.52302846
Mean22.25
Median Absolute Deviation (MAD)8.5
Skewness0.81148006
Sum801
Variance179.05
MonotonicityNot monotonic
2024-04-17T06:50:12.299704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20 4
 
< 0.1%
17 4
 
< 0.1%
9 3
 
< 0.1%
8 2
 
< 0.1%
50 2
 
< 0.1%
43 2
 
< 0.1%
12 2
 
< 0.1%
24 2
 
< 0.1%
26 1
 
< 0.1%
5 1
 
< 0.1%
Other values (13) 13
 
0.1%
(Missing) 9964
99.6%
ValueCountFrequency (%)
5 1
 
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 3
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
12 2
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
17 4
< 0.1%
ValueCountFrequency (%)
50 2
< 0.1%
45 1
< 0.1%
44 1
< 0.1%
43 2
< 0.1%
40 1
< 0.1%
38 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
26 1
< 0.1%
24 2
< 0.1%

mitmdcdepnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

mitmdcasgntype
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

batrar
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

metrorgassrnm
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5958 
의원
1929 
한의원
870 
치과의원
867 
요양병원(일반요양병원)
 
159
Other values (14)
 
217

Length

Max length12
Median length4
Mean length3.6335
Min length2

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5958
59.6%
의원 1929
 
19.3%
한의원 870
 
8.7%
치과의원 867
 
8.7%
요양병원(일반요양병원) 159
 
1.6%
병원 123
 
1.2%
종합병원 23
 
0.2%
치과병원 19
 
0.2%
한방병원 12
 
0.1%
부속의원 11
 
0.1%
Other values (9) 29
 
0.3%

Length

2024-04-17T06:50:12.396111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5958
59.6%
의원 1929
 
19.3%
한의원 870
 
8.7%
치과의원 867
 
8.7%
요양병원(일반요양병원 159
 
1.6%
병원 123
 
1.2%
종합병원 23
 
0.2%
치과병원 19
 
0.2%
한방병원 12
 
0.1%
부속의원 11
 
0.1%
Other values (9) 29
 
0.3%

metrbosassrnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

metrpnum
Real number (ℝ)

MISSING  SKEWED 

Distinct85
Distinct (%)2.1%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean4.9421079
Minimum0
Maximum1436
Zeros67
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:12.491061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile12
Maximum1436
Range1436
Interquartile range (IQR)0

Descriptive statistics

Standard deviation40.506966
Coefficient of variation (CV)8.1962933
Kurtosis764.97405
Mean4.9421079
Median Absolute Deviation (MAD)0
Skewness25.169302
Sum19976
Variance1640.8143
MonotonicityNot monotonic
2024-04-17T06:50:12.615232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3007
30.1%
2 415
 
4.2%
3 126
 
1.3%
0 67
 
0.7%
4 59
 
0.6%
5 47
 
0.5%
6 27
 
0.3%
7 23
 
0.2%
8 20
 
0.2%
10 16
 
0.2%
Other values (75) 235
 
2.4%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0 67
 
0.7%
1 3007
30.1%
2 415
 
4.2%
3 126
 
1.3%
4 59
 
0.6%
5 47
 
0.5%
6 27
 
0.3%
7 23
 
0.2%
8 20
 
0.2%
9 13
 
0.1%
ValueCountFrequency (%)
1436 1
< 0.1%
1282 1
< 0.1%
1077 1
< 0.1%
419 1
< 0.1%
378 1
< 0.1%
367 1
< 0.1%
366 1
< 0.1%
353 1
< 0.1%
352 1
< 0.1%
341 1
< 0.1%

pgrmar
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)100.0%
Missing9969
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean428.76516
Minimum6.3
Maximum1975.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:12.745458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.3
5-th percentile7.75
Q1148.26
median385.97
Q3578.685
95-th percentile916.3
Maximum1975.92
Range1969.62
Interquartile range (IQR)430.425

Descriptive statistics

Standard deviation400.55687
Coefficient of variation (CV)0.93421039
Kurtosis6.3281465
Mean428.76516
Median Absolute Deviation (MAD)231.45
Skewness2.003482
Sum13291.72
Variance160445.81
MonotonicityNot monotonic
2024-04-17T06:50:12.844002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
11.6 1
 
< 0.1%
654.9 1
 
< 0.1%
154.52 1
 
< 0.1%
462.31 1
 
< 0.1%
309.1 1
 
< 0.1%
849.4 1
 
< 0.1%
7.5 1
 
< 0.1%
459.31 1
 
< 0.1%
224.5 1
 
< 0.1%
669.9 1
 
< 0.1%
Other values (21) 21
 
0.2%
(Missing) 9969
99.7%
ValueCountFrequency (%)
6.3 1
< 0.1%
7.5 1
< 0.1%
8.0 1
< 0.1%
11.6 1
< 0.1%
43.0 1
< 0.1%
116.13 1
< 0.1%
132.61 1
< 0.1%
142.0 1
< 0.1%
154.52 1
< 0.1%
161.88 1
< 0.1%
ValueCountFrequency (%)
1975.92 1
< 0.1%
938.49 1
< 0.1%
894.11 1
< 0.1%
849.4 1
< 0.1%
848.02 1
< 0.1%
669.9 1
< 0.1%
654.9 1
< 0.1%
612.26 1
< 0.1%
545.11 1
< 0.1%
504.56 1
< 0.1%

pwnmrglstnum
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)66.7%
Missing9964
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean22.277778
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:12.940119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.75
Q111.75
median19.5
Q328.25
95-th percentile45.5
Maximum50
Range45
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation13.118386
Coefficient of variation (CV)0.58885525
Kurtosis-0.57719838
Mean22.277778
Median Absolute Deviation (MAD)8.5
Skewness0.79026719
Sum802
Variance172.09206
MonotonicityNot monotonic
2024-04-17T06:50:13.026364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20 4
 
< 0.1%
17 4
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
43 2
 
< 0.1%
14 2
 
< 0.1%
24 2
 
< 0.1%
11 2
 
< 0.1%
21 1
 
< 0.1%
7 1
 
< 0.1%
Other values (14) 14
 
0.1%
(Missing) 9964
99.6%
ValueCountFrequency (%)
5 1
 
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
11 2
< 0.1%
12 1
 
< 0.1%
14 2
< 0.1%
15 1
 
< 0.1%
17 4
< 0.1%
ValueCountFrequency (%)
50 1
< 0.1%
47 1
< 0.1%
45 1
< 0.1%
44 1
< 0.1%
43 2
< 0.1%
40 1
< 0.1%
38 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
26 1
< 0.1%

hstrmnum
Real number (ℝ)

MISSING  ZEROS 

Distinct89
Distinct (%)2.2%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean3.2219198
Minimum0
Maximum264
Zeros3445
Zeros (%)34.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:13.381199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile22
Maximum264
Range264
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.23819
Coefficient of variation (CV)4.1087894
Kurtosis100.81826
Mean3.2219198
Median Absolute Deviation (MAD)0
Skewness8.0965495
Sum13023
Variance175.24968
MonotonicityNot monotonic
2024-04-17T06:50:13.506228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3445
34.4%
1 58
 
0.6%
2 34
 
0.3%
3 27
 
0.3%
8 26
 
0.3%
7 26
 
0.3%
6 26
 
0.3%
4 23
 
0.2%
9 23
 
0.2%
5 21
 
0.2%
Other values (79) 333
 
3.3%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0 3445
34.4%
1 58
 
0.6%
2 34
 
0.3%
3 27
 
0.3%
4 23
 
0.2%
5 21
 
0.2%
6 26
 
0.3%
7 26
 
0.3%
8 26
 
0.3%
9 23
 
0.2%
ValueCountFrequency (%)
264 1
< 0.1%
250 1
< 0.1%
185 1
< 0.1%
146 1
< 0.1%
138 1
< 0.1%
133 1
< 0.1%
124 1
< 0.1%
122 2
< 0.1%
115 1
< 0.1%
114 1
< 0.1%

qutnownernum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

joriwontoilar
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)100.0%
Missing9979
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean42.904762
Minimum6.5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:13.630770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile6.6
Q115.1
median24.7
Q368
95-th percentile112.74
Maximum120
Range113.5
Interquartile range (IQR)52.9

Descriptive statistics

Standard deviation37.788052
Coefficient of variation (CV)0.88074261
Kurtosis-0.54199954
Mean42.904762
Median Absolute Deviation (MAD)13.1
Skewness0.95899117
Sum901
Variance1427.9369
MonotonicityNot monotonic
2024-04-17T06:50:13.743378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
24.7 1
 
< 0.1%
57.0 1
 
< 0.1%
33.4 1
 
< 0.1%
6.5 1
 
< 0.1%
15.1 1
 
< 0.1%
37.8 1
 
< 0.1%
79.8 1
 
< 0.1%
100.44 1
 
< 0.1%
15.18 1
 
< 0.1%
6.6 1
 
< 0.1%
Other values (11) 11
 
0.1%
(Missing) 9979
99.8%
ValueCountFrequency (%)
6.5 1
< 0.1%
6.6 1
< 0.1%
10.08 1
< 0.1%
11.68 1
< 0.1%
12.66 1
< 0.1%
15.1 1
< 0.1%
15.18 1
< 0.1%
16.08 1
< 0.1%
19.44 1
< 0.1%
24.3 1
< 0.1%
ValueCountFrequency (%)
120.0 1
< 0.1%
112.74 1
< 0.1%
100.44 1
< 0.1%
96.9 1
< 0.1%
79.8 1
< 0.1%
68.0 1
< 0.1%
57.0 1
< 0.1%
37.8 1
< 0.1%
33.4 1
< 0.1%
32.6 1
< 0.1%

epcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

jisgnumlay
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)46.2%
Missing9974
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean9.2307692
Minimum2
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:13.843284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.25
median5.5
Q38.75
95-th percentile20.25
Maximum78
Range76
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation14.722249
Coefficient of variation (CV)1.5949103
Kurtosis20.880272
Mean9.2307692
Median Absolute Deviation (MAD)2.5
Skewness4.4130956
Sum240
Variance216.74462
MonotonicityNot monotonic
2024-04-17T06:50:13.940014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 4
 
< 0.1%
2 4
 
< 0.1%
5 4
 
< 0.1%
3 3
 
< 0.1%
9 2
 
< 0.1%
4 2
 
< 0.1%
12 2
 
< 0.1%
78 1
 
< 0.1%
6 1
 
< 0.1%
23 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 9974
99.7%
ValueCountFrequency (%)
2 4
< 0.1%
3 3
< 0.1%
4 2
< 0.1%
5 4
< 0.1%
6 1
 
< 0.1%
7 4
< 0.1%
8 1
 
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
12 2
< 0.1%
ValueCountFrequency (%)
78 1
 
< 0.1%
23 1
 
< 0.1%
12 2
< 0.1%
10 1
 
< 0.1%
9 2
< 0.1%
8 1
 
< 0.1%
7 4
< 0.1%
6 1
 
< 0.1%
5 4
< 0.1%
4 2
< 0.1%

asgnymd
Real number (ℝ)

MISSING 

Distinct2016
Distinct (%)76.4%
Missing7362
Missing (%)73.6%
Infinite0
Infinite (%)0.0%
Mean20044549
Minimum19610418
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:14.081675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19610418
5-th percentile19780492
Q120001016
median20080702
Q320130102
95-th percentile20170601
Maximum20180903
Range570485
Interquartile range (IQR)129085.75

Descriptive statistics

Standard deviation116544.68
Coefficient of variation (CV)0.0058142829
Kurtosis1.2824167
Mean20044549
Median Absolute Deviation (MAD)59504
Skewness-1.3555506
Sum5.2877521 × 1010
Variance1.3582662 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:14.201321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19691231 8
 
0.1%
19660301 7
 
0.1%
20180702 6
 
0.1%
20070702 6
 
0.1%
20130701 6
 
0.1%
20180102 6
 
0.1%
20080102 6
 
0.1%
20140501 6
 
0.1%
20080701 6
 
0.1%
20060102 5
 
0.1%
Other values (2006) 2576
 
25.8%
(Missing) 7362
73.6%
ValueCountFrequency (%)
19610418 1
 
< 0.1%
19620924 1
 
< 0.1%
19620928 1
 
< 0.1%
19630703 1
 
< 0.1%
19660228 1
 
< 0.1%
19660301 7
0.1%
19660415 1
 
< 0.1%
19660521 1
 
< 0.1%
19660920 3
< 0.1%
19670214 1
 
< 0.1%
ValueCountFrequency (%)
20180903 5
0.1%
20180901 1
 
< 0.1%
20180829 1
 
< 0.1%
20180827 1
 
< 0.1%
20180821 3
< 0.1%
20180813 1
 
< 0.1%
20180809 1
 
< 0.1%
20180801 3
< 0.1%
20180730 2
 
< 0.1%
20180723 1
 
< 0.1%

asgncancelymd
Real number (ℝ)

MISSING 

Distinct185
Distinct (%)53.6%
Missing9655
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean20167203
Minimum20081220
Maximum20180904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:14.318357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081220
5-th percentile20110986
Q120170705
median20180501
Q320180726
95-th percentile20180829
Maximum20180904
Range99684
Interquartile range (IQR)10021

Descriptive statistics

Standard deviation23342.962
Coefficient of variation (CV)0.0011574715
Kurtosis2.0655095
Mean20167203
Median Absolute Deviation (MAD)320
Skewness-1.7606932
Sum6.957685 × 109
Variance5.4489386 × 108
MonotonicityNot monotonic
2024-04-17T06:50:14.428765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905 27
 
0.3%
20180808 12
 
0.1%
20180823 9
 
0.1%
20180831 9
 
0.1%
20180724 8
 
0.1%
20180614 6
 
0.1%
20180810 6
 
0.1%
20180813 5
 
0.1%
20180612 5
 
0.1%
20180713 5
 
0.1%
Other values (175) 253
 
2.5%
(Missing) 9655
96.5%
ValueCountFrequency (%)
20081220 1
< 0.1%
20081231 1
< 0.1%
20090219 1
< 0.1%
20091230 1
< 0.1%
20091231 1
< 0.1%
20100226 1
< 0.1%
20100326 1
< 0.1%
20100331 1
< 0.1%
20100416 1
< 0.1%
20100511 1
< 0.1%
ValueCountFrequency (%)
20180904 2
 
< 0.1%
20180903 1
 
< 0.1%
20180831 9
0.1%
20180830 3
 
< 0.1%
20180829 4
< 0.1%
20180828 1
 
< 0.1%
20180827 4
< 0.1%
20180824 2
 
< 0.1%
20180823 9
0.1%
20180822 2
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9989 
0
 
5
2
 
4
1
 
2

Length

Max length4
Median length4
Mean length3.9967
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> 9989
99.9%
0 5
 
0.1%
2 4
 
< 0.1%
1 2
 
< 0.1%

Length

2024-04-17T06:50:14.529480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:14.607629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9989
99.9%
0 5
 
< 0.1%
2 4
 
< 0.1%
1 2
 
< 0.1%

medextritemscn
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

medextritemscnnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

totar
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2712
Distinct (%)67.1%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean984.80965
Minimum0
Maximum1384945
Zeros599
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:14.706797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q186.7925
median158.555
Q3280.9225
95-th percentile2140.182
Maximum1384945
Range1384945
Interquartile range (IQR)194.13

Descriptive statistics

Standard deviation22176.519
Coefficient of variation (CV)22.518584
Kurtosis3757.0984
Mean984.80965
Median Absolute Deviation (MAD)88.84
Skewness60.346082
Sum3980600.6
Variance4.9179798 × 108
MonotonicityNot monotonic
2024-04-17T06:50:14.835025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 599
 
6.0%
1.0 90
 
0.9%
120.0 36
 
0.4%
100.0 10
 
0.1%
177.0 9
 
0.1%
165.0 9
 
0.1%
140.0 7
 
0.1%
109.0 6
 
0.1%
183.06 6
 
0.1%
198.0 6
 
0.1%
Other values (2702) 3264
32.6%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0.0 599
6.0%
1.0 90
 
0.9%
10.0 3
 
< 0.1%
20.0 1
 
< 0.1%
22.23 1
 
< 0.1%
27.0 1
 
< 0.1%
28.74 1
 
< 0.1%
29.04 1
 
< 0.1%
29.7 1
 
< 0.1%
32.0 2
 
< 0.1%
ValueCountFrequency (%)
1384945.0 1
< 0.1%
168117.0 1
< 0.1%
113599.96 1
< 0.1%
90383.51 1
< 0.1%
56670.14 1
< 0.1%
51976.15 1
< 0.1%
44373.31 1
< 0.1%
41279.6 1
< 0.1%
41017.69 1
< 0.1%
38985.48 1
< 0.1%

totepnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

frstasgnymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

copnum
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)36.8%
Missing9981
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2.8421053
Minimum0
Maximum15
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:14.923326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9
Q11
median2
Q33
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2190951
Coefficient of variation (CV)1.1326446
Kurtosis12.335414
Mean2.8421053
Median Absolute Deviation (MAD)1
Skewness3.252598
Sum54
Variance10.362573
MonotonicityNot monotonic
2024-04-17T06:50:15.001963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
 
0.1%
3 4
 
< 0.1%
2 4
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
0 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 9981
99.8%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 6
0.1%
2 4
< 0.1%
3 4
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 4
< 0.1%
2 4
< 0.1%
1 6
0.1%
0 1
 
< 0.1%

storetrdar
Real number (ℝ)

MISSING  ZEROS 

Distinct364
Distinct (%)7.3%
Missing5025
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean18.840183
Minimum0
Maximum605.15
Zeros3681
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:15.110912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329.725
95-th percentile99
Maximum605.15
Range605.15
Interquartile range (IQR)29.725

Descriptive statistics

Standard deviation36.86906
Coefficient of variation (CV)1.9569375
Kurtosis16.331132
Mean18.840183
Median Absolute Deviation (MAD)0
Skewness2.679719
Sum93729.91
Variance1359.3276
MonotonicityNot monotonic
2024-04-17T06:50:15.220583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3681
36.8%
49.5 122
 
1.2%
66.0 102
 
1.0%
99.0 52
 
0.5%
82.5 41
 
0.4%
33.0 36
 
0.4%
59.4 29
 
0.3%
132.0 26
 
0.3%
100.0 23
 
0.2%
60.0 20
 
0.2%
Other values (354) 843
 
8.4%
(Missing) 5025
50.2%
ValueCountFrequency (%)
0.0 3681
36.8%
3.0 1
 
< 0.1%
3.3 2
 
< 0.1%
3.5 2
 
< 0.1%
5.4 1
 
< 0.1%
6.6 2
 
< 0.1%
13.2 1
 
< 0.1%
15.0 1
 
< 0.1%
16.12 1
 
< 0.1%
16.5 2
 
< 0.1%
ValueCountFrequency (%)
605.15 1
< 0.1%
277.27 1
< 0.1%
264.0 1
< 0.1%
230.0 2
< 0.1%
208.31 1
< 0.1%
203.0 1
< 0.1%
200.0 1
< 0.1%
198.0 1
< 0.1%
197.07 1
< 0.1%
187.83 1
< 0.1%

pmtbednum
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9639 
0
 
361

Length

Max length4
Median length4
Mean length3.8917
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> 9639
96.4%
0 361
 
3.6%

Length

2024-04-17T06:50:15.338053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:15.412725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9639
96.4%
0 361
 
3.6%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-04-01 05:19:03
Maximum2021-04-01 05:19:07
2024-04-17T06:50:15.476409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:50:15.555507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
182924003290000PHMA12006329002404110004701_01_02_PI2018-08-31 23:59:59.0<NA>오행선침한의원<NA>부산광역시 부산진구 가야1동 19-1614800부산광역시 부산진구 가야대로 651 (가야동)2006121220140616<NA><NA><NA>3폐업386154.468752186330.52331320140616102620한의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>한의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>142.74<NA><NA><NA>0.0<NA>2021-04-01 05:19:04
10300108673340000PHMH32015334002508750001201_01_05_PI2018-08-31 23:59:59.0<NA>씨유감천대로점<NA>부산광역시 사하구 감천동 42번지 1호49376부산광역시 사하구 감천로 141, 1층 (감천동)2015090320180111<NA><NA><NA>3폐업383013.750986178531.52696920180111120015<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>82.5<NA>2021-04-01 05:19:06
15502160753400000PHMD12011340001308400001601_01_06_PI2018-08-31 23:59:59.0<NA>하나약국619901부산광역시 기장군 기장읍 교리 356번지 3호619901부산광역시 기장군 기장읍 차성로 4362011111720111223<NA><NA><NA>3폐업401845.50206197580.65998420140326110110<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>41.2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20111117<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:07
10296108633340000PHMH32015334002508750000701_01_05_PI2018-08-31 23:59:59.0<NA>씨유장림장평점604843부산광역시 사하구 장림동 321번지 20호49474부산광역시 사하구 장림로 197, 101호 (장림동)20150512<NA><NA><NA><NA>13영업중379734.357353178035.1085820150515131926<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>99.0<NA>2021-04-01 05:19:06
11115116773390000PHMH32016339002308750000801_01_05_PI2018-08-31 23:59:59.0<NA>GS25사상덕포역점<NA><NA>46948부산광역시 사상구 사상로 313 (덕포동)2016062220160706<NA><NA><NA>3폐업380679.383092188054.59261420160706143752<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>100.0<NA>2021-04-01 05:19:06
10130106983340000PHMH32018334002508750001501_01_05_PI2018-08-31 23:59:59.0<NA>지에스25새하단본동점<NA><NA>49409부산광역시 사하구 낙동대로457번길 27, 1층 (하단동)20180322<NA><NA><NA><NA>13영업중<NA><NA>20180322170707<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>33.0<NA>2021-04-01 05:19:06
12135126943290000PHMD11985329002408400000201_01_06_PI2018-08-31 23:59:59.0<NA>온누리 주민약국614803부산광역시 부산진구 가야동 271번지 53호47330부산광역시 부산진구 가야대로 594 (가야동)19850322<NA><NA><NA><NA>13영업중385604.347452186137.26919920140825134443<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>29.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19850322<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:06
61416163270000PHMA12006327002204110000201_01_02_PI2018-08-31 23:59:59.0<NA>편한세상마취통증의학과의원601808부산광역시 동구 범일동 833번지 22호48738부산광역시 동구 범일로 110-1, 3층 (범일동)20060817<NA><NA><NA><NA>13영업중387716.543681184550.24657420170905183845의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>의원<NA>2<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>293.04<NA><NA><NA>0.0<NA>2021-04-01 05:19:03
12000125583280000PHMD11968328002308400000301_01_06_PI2018-08-31 23:59:59.0<NA>제일 약국<NA>부산광역시 영도구 영선동2가 21606042부산광역시 영도구 남항로 48-1 (영선동2가)1968072620110502<NA><NA><NA>3폐업386179.748473178794.59117120131227171949<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19680726<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:06
204226103290000PHMA12009329002404110004501_01_02_PI2018-08-31 23:59:59.0<NA>우일한의원614852부산광역시 부산진구 양정2동 81번지 4호 (지하1층,지상1층 일부)<NA>부산광역시 부산진구 연수로8번길 13 (양정동,(지하1층,지상1층 일부))2009101920091028<NA><NA><NA>3폐업388843.97026188241.37866520091028113404한의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>한의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>130.76<NA><NA><NA>0.0<NA>2021-04-01 05:19:04
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
12084126403290000PHMD12004329002408400001001_01_06_PI2018-08-31 23:59:59.0<NA>대명약국<NA>부산광역시 부산진구 전포동 324-15 2층<NA><NA>2004122920090219<NA><NA><NA>3폐업<NA><NA>20090220111507<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>68.64<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20041229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:06
928798583300000PHMH32018330002408750000801_01_05_PI2018-08-31 23:59:59.0<NA>씨유 온천유림점<NA>부산광역시 동래구 온천동 460번지 6호 온천동 유림노르웨이숲47711부산광역시 동래구 중앙대로 1453, 1층 104호 (온천동, 온천동 유림노르웨이숲)20180326<NA><NA><NA><NA>13영업중389559.148357193094.52003220180327162056<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:05
460051693330000PHMA12014333002404110002701_01_02_PI2018-08-31 23:59:59.0<NA>부산뽀빠이정형외과의원612889부산광역시 해운대구 우동 1516번지 센텀타워메디컬 403호48060부산광역시 해운대구 센텀2로 20, 403호 (우동, 센텀타워메디컬)20140904<NA><NA><NA><NA>13영업중394248.454507187726.22498820180329221344의원051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:04
198725573290000PHMA11998329002404110000601_01_02_PI2018-08-31 23:59:59.0<NA>권혁한의원614871부산광역시 부산진구 초읍동 268번지 4호<NA>부산광역시 부산진구 새싹로 212 (초읍동)1998040120121107<NA><NA><NA>3폐업386665.338854188449.42004920121107160502한의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>한의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>188.76<NA><NA><NA>0.0<NA>2021-04-01 05:19:04
10299108663340000PHMH32015334002508750001001_01_05_PI2018-08-31 23:59:59.0<NA>GS25케이프포인트점604827부산광역시 사하구 다대동 1548번지49501부산광역시 사하구 다대낙조2길 85, 101호 (다대동)20150723<NA><NA><NA><NA>13영업중378962.18977174732.42240720150724110022<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>66.0<NA>2021-04-01 05:19:06
9543101123320000PHMH32017332004508750001301_01_05_PI2018-08-31 23:59:59.0<NA>씨유 화명롯데카이저점<NA><NA>46539부산광역시 북구 금곡대로 166, 907동 101호 (화명동, 화명롯데캐슬카이저)20170829<NA><NA><NA><NA>13영업중383398.915235194063.87502620170829165514<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>68.0<NA>2021-04-01 05:19:05
574963193340000PHMA11992334002504110000901_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>3폐업378844.545112181190.61838820130524111329의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>106.0<NA><NA><NA>0.0<NA>2021-04-01 05:19:04
10067106323340000PHMH32016334002508750002101_01_05_PI2018-08-31 23:59:59.0<NA>씨유장림삼거리점<NA>부산광역시 사하구 장림동49476부산광역시 사하구 장림시장5길 2 (장림동)2016100520180821<NA><NA><NA>3폐업379230.265721177853.37802720180821152253<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>39.6<NA>2021-04-01 05:19:06
670072763350000PHMA11991335002404110000401_01_02_PI2018-08-31 23:59:59.0<NA>박기봉치과의원609814부산광역시 금정구 남산동 129-1346227부산광역시 금정구 중앙대로1985번길 1 (남산동)19910516<NA><NA><NA><NA>13영업중390323.112067198111.00448220171026221338치과의원051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:19:04
261531843300000PHMA12015330002404110001201_01_02_PI2018-08-31 23:59:59.0<NA>꽃보다예쁜의원607824부산광역시 동래구 수안동 284번지 2,3층47813부산광역시 동래구 충렬대로 245, 2,3층 (수안동)20150514<NA><NA><NA><NA>13영업중389985.874632191444.446920170905183852의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>253.42<NA><NA><NA>0.0<NA>2021-04-01 05:19:04