Overview

Dataset statistics

Number of variables70
Number of observations10000
Missing cells397290
Missing cells (%)56.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 MiB
Average record size in memory626.0 B

Variable types

Numeric34
Text4
Categorical16
Unsupported16

Alerts

sitetel has constant value ""Constant
updategbn is highly imbalanced (98.0%)Imbalance
updatedt is highly imbalanced (98.7%)Imbalance
etcstfcnt is highly imbalanced (99.5%)Imbalance
btpnum is highly imbalanced (99.2%)Imbalance
nutrcnt is highly imbalanced (99.3%)Imbalance
metrorgassrnm is highly imbalanced (56.6%)Imbalance
undernumlay is highly imbalanced (99.5%)Imbalance
pmtbednum is highly imbalanced (75.9%)Imbalance
opnsvcnm has 10000 (100.0%) missing valuesMissing
sitepostno has 3319 (33.2%) missing valuesMissing
sitewhladdr has 879 (8.8%) missing valuesMissing
rdnpostno has 2131 (21.3%) missing valuesMissing
rdnwhladdr has 868 (8.7%) missing valuesMissing
dcbymd has 5816 (58.2%) missing valuesMissing
clgstdt has 9930 (99.3%) missing valuesMissing
clgenddt has 9930 (99.3%) missing valuesMissing
ropnymd has 10000 (100.0%) missing valuesMissing
x has 855 (8.6%) missing valuesMissing
y has 855 (8.6%) missing valuesMissing
nursecnt has 9974 (99.7%) missing valuesMissing
nursaidcnt has 9974 (99.7%) missing valuesMissing
bdnglayercnt has 9975 (99.8%) missing valuesMissing
rescnt has 10000 (100.0%) missing valuesMissing
pomfacilar has 9986 (99.9%) missing valuesMissing
etcepcnt has 10000 (100.0%) missing valuesMissing
mmknurmar has 9979 (99.8%) missing valuesMissing
btrmar has 9990 (99.9%) missing valuesMissing
sicbnum has 5901 (59.0%) missing valuesMissing
astnepnum has 10000 (100.0%) missing valuesMissing
ofear has 9983 (99.8%) missing valuesMissing
warmar has 9986 (99.9%) missing valuesMissing
facilmngnum has 10000 (100.0%) missing valuesMissing
pharmtrdar has 7389 (73.9%) missing valuesMissing
bbrmar has 9976 (99.8%) missing valuesMissing
babyrglstnum has 9972 (99.7%) 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 5901 (59.0%) missing valuesMissing
pgrmar has 9975 (99.8%) missing valuesMissing
pwnmrglstnum has 9972 (99.7%) missing valuesMissing
hstrmnum has 5901 (59.0%) missing valuesMissing
qutnownernum has 10000 (100.0%) missing valuesMissing
joriwontoilar has 9984 (99.8%) missing valuesMissing
epcnt has 10000 (100.0%) missing valuesMissing
jisgnumlay has 9978 (99.8%) missing valuesMissing
asgnymd has 7388 (73.9%) missing valuesMissing
asgncancelymd has 9625 (96.2%) missing valuesMissing
medextritemscn has 10000 (100.0%) missing valuesMissing
medextritemscnnm has 10000 (100.0%) missing valuesMissing
totar has 5901 (59.0%) missing valuesMissing
totepnum has 10000 (100.0%) missing valuesMissing
frstasgnymd has 10000 (100.0%) missing valuesMissing
copnum has 9985 (99.9%) missing valuesMissing
storetrdar has 5012 (50.1%) missing valuesMissing
dcbymd is highly skewed (γ1 = -58.70949181)Skewed
pharmtrdar is highly skewed (γ1 = 51.03387207)Skewed
metrpnum is highly skewed (γ1 = 30.45652372)Skewed
totar is highly skewed (γ1 = 60.36514026)Skewed
storetrdar is highly skewed (γ1 = 41.55410359)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 3446 (34.5%) zerosZeros
pharmtrdar has 282 (2.8%) zerosZeros
hstrmnum has 3487 (34.9%) zerosZeros
totar has 622 (6.2%) zerosZeros
storetrdar has 3702 (37.0%) zerosZeros

Reproduction

Analysis started2024-04-16 21:49:41.716533
Analysis finished2024-04-16 21:49:43.635441
Duration1.92 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%
Mean8287.7477
Minimum563
Maximum16076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:43.689601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum563
5-th percentile1318.95
Q14406.75
median8269.5
Q312159.25
95-th percentile15289.05
Maximum16076
Range15513
Interquartile range (IQR)7752.5

Descriptive statistics

Standard deviation4473.7254
Coefficient of variation (CV)0.5397999
Kurtosis-1.197766
Mean8287.7477
Median Absolute Deviation (MAD)3876.5
Skewness0.0077520582
Sum82877477
Variance20014219
MonotonicityNot monotonic
2024-04-17T06:49:43.799773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2305 1
 
< 0.1%
10424 1
 
< 0.1%
4639 1
 
< 0.1%
6710 1
 
< 0.1%
12091 1
 
< 0.1%
3720 1
 
< 0.1%
5923 1
 
< 0.1%
14101 1
 
< 0.1%
10421 1
 
< 0.1%
4856 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%
567 1
< 0.1%
569 1
< 0.1%
570 1
< 0.1%
571 1
< 0.1%
572 1
< 0.1%
573 1
< 0.1%
ValueCountFrequency (%)
16076 1
< 0.1%
16074 1
< 0.1%
16071 1
< 0.1%
16070 1
< 0.1%
16069 1
< 0.1%
16064 1
< 0.1%
16063 1
< 0.1%
16061 1
< 0.1%
16060 1
< 0.1%
16059 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326516
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:43.897841image/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 deviation38576.295
Coefficient of variation (CV)0.011596606
Kurtosis-0.77333536
Mean3326516
Median Absolute Deviation (MAD)30000
Skewness0.014328006
Sum3.326516 × 1010
Variance1.4881306 × 109
MonotonicityNot monotonic
2024-04-17T06:49:43.991271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 1291
12.9%
3350000 1171
11.7%
3330000 1105
11.1%
3340000 979
9.8%
3300000 783
7.8%
3310000 743
7.4%
3370000 592
 
5.9%
3320000 556
 
5.6%
3380000 545
 
5.5%
3390000 466
 
4.7%
Other values (6) 1769
17.7%
ValueCountFrequency (%)
3250000 304
 
3.0%
3260000 345
 
3.5%
3270000 332
 
3.3%
3280000 255
 
2.5%
3290000 1291
12.9%
3300000 783
7.8%
3310000 743
7.4%
3320000 556
5.6%
3330000 1105
11.1%
3340000 979
9.8%
ValueCountFrequency (%)
3400000 344
 
3.4%
3390000 466
 
4.7%
3380000 545
5.5%
3370000 592
5.9%
3360000 189
 
1.9%
3350000 1171
11.7%
3340000 979
9.8%
3330000 1105
11.1%
3320000 556
5.6%
3310000 743
7.4%

mgtno
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:49:44.166259image/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 rowPHMA120123290024041100011
2nd rowPHMA120123330024041100023
3rd rowPHMH320173390023087500030
4th rowPHMH320123400013087500009
5th rowPHMA119853300024041100005
ValueCountFrequency (%)
phma120123290024041100011 1
 
< 0.1%
phmd120093330024084000022 1
 
< 0.1%
phma119713250021041100001 1
 
< 0.1%
phmd120143310024084000003 1
 
< 0.1%
phma120153320045041100016 1
 
< 0.1%
phma119993350024041100006 1
 
< 0.1%
phmd120173250021084000003 1
 
< 0.1%
phma119843300024041100002 1
 
< 0.1%
phma120073340025041200024 1
 
< 0.1%
phmh320123330024087500056 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T06:49:44.457040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81230
32.5%
1 31289
 
12.5%
2 26503
 
10.6%
3 24502
 
9.8%
4 17008
 
6.8%
H 11950
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7914
 
3.2%
5 7069
 
2.8%
Other values (6) 22535
 
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 81230
38.7%
1 31289
 
14.9%
2 26503
 
12.6%
3 24502
 
11.7%
4 17008
 
8.1%
8 7914
 
3.8%
5 7069
 
3.4%
9 6643
 
3.2%
7 5182
 
2.5%
6 2660
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
H 11950
29.9%
P 10000
25.0%
M 10000
25.0%
A 5410
13.5%
D 2612
 
6.5%
B 28
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 81230
38.7%
1 31289
 
14.9%
2 26503
 
12.6%
3 24502
 
11.7%
4 17008
 
8.1%
8 7914
 
3.8%
5 7069
 
3.4%
9 6643
 
3.2%
7 5182
 
2.5%
6 2660
 
1.3%
Latin
ValueCountFrequency (%)
H 11950
29.9%
P 10000
25.0%
M 10000
25.0%
A 5410
13.5%
D 2612
 
6.5%
B 28
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81230
32.5%
1 31289
 
12.5%
2 26503
 
10.6%
3 24502
 
9.8%
4 17008
 
6.8%
H 11950
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7914
 
3.2%
5 7069
 
2.8%
Other values (6) 22535
 
9.0%

opnsvcid
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
01_01_02_P
5013 
01_01_06_P
2612 
01_01_05_P
1950 
01_01_01_P
 
375
01_01_04_P
 
28

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
01_01_02_P 5013
50.1%
01_01_06_P 2612
26.1%
01_01_05_P 1950
 
19.5%
01_01_01_P 375
 
3.8%
01_01_04_P 28
 
0.3%
01_01_03_P 22
 
0.2%

Length

2024-04-17T06:49:44.563044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:44.642442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_01_02_p 5013
50.1%
01_01_06_p 2612
26.1%
01_01_05_p 1950
 
19.5%
01_01_01_p 375
 
3.8%
01_01_04_p 28
 
0.3%
01_01_03_p 22
 
0.2%

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

2024-04-17T06:49:44.730592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:44.799091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9981
99.8%
u 19
 
0.2%

updatedt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-08-31 23:59:59.0
9975 
2018-09-06 11:42:31.0
 
11
2018-09-06 11:42:33.0
 
7
2018-09-06 11:42:32.0
 
4
2018-09-06 11:42:30.0
 
3

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 9975
99.8%
2018-09-06 11:42:31.0 11
 
0.1%
2018-09-06 11:42:33.0 7
 
0.1%
2018-09-06 11:42:32.0 4
 
< 0.1%
2018-09-06 11:42:30.0 3
 
< 0.1%

Length

2024-04-17T06:49:44.868853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:44.954634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 9975
49.9%
23:59:59.0 9975
49.9%
2018-09-06 25
 
0.1%
11:42:31.0 11
 
0.1%
11:42:33.0 7
 
< 0.1%
11:42:32.0 4
 
< 0.1%
11:42:30.0 3
 
< 0.1%

opnsvcnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

bplcnm
Text

Distinct7735
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:49:45.205045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length7.3009
Min length2

Characters and Unicode

Total characters73009
Distinct characters689
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

Unique6660 ?
Unique (%)66.6%

Sample

1st row박철보비뇨기과의원
2nd row최갑림치과의원
3rd row씨유 엄궁중앙점
4th rowGS기장창기점
5th row신기영내과의원
ValueCountFrequency (%)
gs25 286
 
2.4%
씨유 247
 
2.1%
세븐일레븐 193
 
1.6%
미니스톱 117
 
1.0%
cu 87
 
0.7%
한의원 56
 
0.5%
의원 56
 
0.5%
약국 56
 
0.5%
치과의원 52
 
0.4%
주)코리아세븐 50
 
0.4%
Other values (7909) 10661
89.9%
2024-04-17T06:49:45.778045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5716
 
7.8%
5596
 
7.7%
2885
 
4.0%
2683
 
3.7%
2627
 
3.6%
1869
 
2.6%
1865
 
2.6%
1775
 
2.4%
1215
 
1.7%
1100
 
1.5%
Other values (679) 45678
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67513
92.5%
Space Separator 1865
 
2.6%
Uppercase Letter 1571
 
2.2%
Decimal Number 1451
 
2.0%
Close Punctuation 261
 
0.4%
Open Punctuation 245
 
0.3%
Lowercase Letter 60
 
0.1%
Other Punctuation 34
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5716
 
8.5%
5596
 
8.3%
2885
 
4.3%
2683
 
4.0%
2627
 
3.9%
1869
 
2.8%
1775
 
2.6%
1215
 
1.8%
1100
 
1.6%
1068
 
1.6%
Other values (624) 40979
60.7%
Uppercase Letter
ValueCountFrequency (%)
S 595
37.9%
G 557
35.5%
C 151
 
9.6%
U 141
 
9.0%
K 30
 
1.9%
B 15
 
1.0%
N 12
 
0.8%
L 11
 
0.7%
H 8
 
0.5%
P 6
 
0.4%
Other values (15) 45
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
e 31
51.7%
h 5
 
8.3%
i 4
 
6.7%
c 4
 
6.7%
m 3
 
5.0%
t 3
 
5.0%
u 3
 
5.0%
r 2
 
3.3%
l 2
 
3.3%
a 2
 
3.3%
Decimal Number
ValueCountFrequency (%)
2 699
48.2%
5 616
42.5%
4 55
 
3.8%
1 34
 
2.3%
3 23
 
1.6%
0 8
 
0.6%
6 8
 
0.6%
7 6
 
0.4%
8 1
 
0.1%
9 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
& 9
26.5%
. 9
26.5%
· 9
26.5%
, 7
20.6%
Space Separator
ValueCountFrequency (%)
1865
100.0%
Close Punctuation
ValueCountFrequency (%)
) 261
100.0%
Open Punctuation
ValueCountFrequency (%)
( 245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67505
92.5%
Common 3863
 
5.3%
Latin 1631
 
2.2%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5716
 
8.5%
5596
 
8.3%
2885
 
4.3%
2683
 
4.0%
2627
 
3.9%
1869
 
2.8%
1775
 
2.6%
1215
 
1.8%
1100
 
1.6%
1068
 
1.6%
Other values (616) 40971
60.7%
Latin
ValueCountFrequency (%)
S 595
36.5%
G 557
34.2%
C 151
 
9.3%
U 141
 
8.6%
e 31
 
1.9%
K 30
 
1.8%
B 15
 
0.9%
N 12
 
0.7%
L 11
 
0.7%
H 8
 
0.5%
Other values (26) 80
 
4.9%
Common
ValueCountFrequency (%)
1865
48.3%
2 699
 
18.1%
5 616
 
15.9%
) 261
 
6.8%
( 245
 
6.3%
4 55
 
1.4%
1 34
 
0.9%
3 23
 
0.6%
& 9
 
0.2%
. 9
 
0.2%
Other values (8) 47
 
1.2%
Han
ValueCountFrequency (%)
2
20.0%
1
10.0%
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 67502
92.5%
ASCII 5485
 
7.5%
None 11
 
< 0.1%
CJK 10
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5716
 
8.5%
5596
 
8.3%
2885
 
4.3%
2683
 
4.0%
2627
 
3.9%
1869
 
2.8%
1775
 
2.6%
1215
 
1.8%
1100
 
1.6%
1068
 
1.6%
Other values (614) 40968
60.7%
ASCII
ValueCountFrequency (%)
1865
34.0%
2 699
 
12.7%
5 616
 
11.2%
S 595
 
10.8%
G 557
 
10.2%
) 261
 
4.8%
( 245
 
4.5%
C 151
 
2.8%
U 141
 
2.6%
4 55
 
1.0%
Other values (43) 300
 
5.5%
None
ValueCountFrequency (%)
· 9
81.8%
2
 
18.2%
CJK
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

sitepostno
Real number (ℝ)

MISSING 

Distinct936
Distinct (%)14.0%
Missing3319
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean608937.09
Minimum607
Maximum621070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:45.890723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum607
5-th percentile601829
Q1607824
median611073
Q3614030
95-th percentile617800
Maximum621070
Range620463
Interquartile range (IQR)6206

Descriptive statistics

Standard deviation31686.402
Coefficient of variation (CV)0.052035593
Kurtosis333.86353
Mean608937.09
Median Absolute Deviation (MAD)3239
Skewness-18.107013
Sum4.0683087 × 109
Variance1.0040281 × 109
MonotonicityNot monotonic
2024-04-17T06:49:45.992349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609310 122
 
1.2%
609320 90
 
0.9%
609400 82
 
0.8%
614847 70
 
0.7%
609390 68
 
0.7%
616852 55
 
0.5%
601812 49
 
0.5%
612842 49
 
0.5%
614849 47
 
0.5%
612021 43
 
0.4%
Other values (926) 6006
60.1%
(Missing) 3319
33.2%
ValueCountFrequency (%)
607 10
0.1%
46067 1
 
< 0.1%
46235 1
 
< 0.1%
46243 1
 
< 0.1%
46702 1
 
< 0.1%
46957 1
 
< 0.1%
47354 1
 
< 0.1%
48024 1
 
< 0.1%
48059 1
 
< 0.1%
48111 1
 
< 0.1%
ValueCountFrequency (%)
621070 1
 
< 0.1%
619963 38
0.4%
619962 11
 
0.1%
619961 5
 
0.1%
619953 6
 
0.1%
619952 4
 
< 0.1%
619951 5
 
0.1%
619913 1
 
< 0.1%
619912 7
 
0.1%
619906 7
 
0.1%

sitewhladdr
Text

MISSING 

Distinct7551
Distinct (%)82.8%
Missing879
Missing (%)8.8%
Memory size156.2 KiB
2024-04-17T06:49:46.301865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length56
Mean length23.918978
Min length2

Characters and Unicode

Total characters218165
Distinct characters461
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

Unique6514 ?
Unique (%)71.4%

Sample

1st row부산광역시 부산진구 부전2동 467번지 10호
2nd row부산광역시 해운대구 우동 1407번지 두산위브제니스 104동532호533호534호535호
3rd row부산광역시 기장군 기장읍 청강리 703번지 4호
4th row사직1동 47-26
5th row부산광역시 금정구 금사동 80번지 1호
ValueCountFrequency (%)
부산광역시 8889
 
19.3%
부산진구 1185
 
2.6%
금정구 1160
 
2.5%
1호 1076
 
2.3%
해운대구 946
 
2.1%
사하구 939
 
2.0%
동래구 680
 
1.5%
남구 675
 
1.5%
연제구 529
 
1.2%
수영구 505
 
1.1%
Other values (4976) 29388
63.9%
2024-04-17T06:49:46.755763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36971
 
16.9%
11165
 
5.1%
1 10966
 
5.0%
10855
 
5.0%
10246
 
4.7%
9245
 
4.2%
9129
 
4.2%
9036
 
4.1%
8960
 
4.1%
7532
 
3.5%
Other values (451) 94060
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130357
59.8%
Decimal Number 47480
 
21.8%
Space Separator 36971
 
16.9%
Dash Punctuation 1757
 
0.8%
Other Punctuation 530
 
0.2%
Open Punctuation 366
 
0.2%
Close Punctuation 366
 
0.2%
Uppercase Letter 236
 
0.1%
Math Symbol 71
 
< 0.1%
Lowercase Letter 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11165
 
8.6%
10855
 
8.3%
10246
 
7.9%
9245
 
7.1%
9129
 
7.0%
9036
 
6.9%
8960
 
6.9%
7532
 
5.8%
7386
 
5.7%
7227
 
5.5%
Other values (391) 39576
30.4%
Uppercase Letter
ValueCountFrequency (%)
A 42
17.8%
B 41
17.4%
F 20
8.5%
S 19
8.1%
K 16
 
6.8%
G 16
 
6.8%
L 11
 
4.7%
C 10
 
4.2%
D 7
 
3.0%
T 7
 
3.0%
Other values (14) 47
19.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
22.2%
s 5
18.5%
i 4
14.8%
a 3
11.1%
n 2
 
7.4%
k 2
 
7.4%
w 1
 
3.7%
j 1
 
3.7%
u 1
 
3.7%
q 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
1 10966
23.1%
2 7343
15.5%
3 5518
11.6%
4 4548
9.6%
5 3960
 
8.3%
0 3307
 
7.0%
6 3246
 
6.8%
7 3229
 
6.8%
8 2785
 
5.9%
9 2578
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 485
91.5%
@ 20
 
3.8%
. 14
 
2.6%
/ 6
 
1.1%
· 3
 
0.6%
" 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 365
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 365
99.7%
] 1
 
0.3%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
36971
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1757
100.0%
Math Symbol
ValueCountFrequency (%)
~ 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130357
59.8%
Common 87541
40.1%
Latin 267
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11165
 
8.6%
10855
 
8.3%
10246
 
7.9%
9245
 
7.1%
9129
 
7.0%
9036
 
6.9%
8960
 
6.9%
7532
 
5.8%
7386
 
5.7%
7227
 
5.5%
Other values (391) 39576
30.4%
Latin
ValueCountFrequency (%)
A 42
15.7%
B 41
15.4%
F 20
 
7.5%
S 19
 
7.1%
K 16
 
6.0%
G 16
 
6.0%
L 11
 
4.1%
C 10
 
3.7%
D 7
 
2.6%
T 7
 
2.6%
Other values (27) 78
29.2%
Common
ValueCountFrequency (%)
36971
42.2%
1 10966
 
12.5%
2 7343
 
8.4%
3 5518
 
6.3%
4 4548
 
5.2%
5 3960
 
4.5%
0 3307
 
3.8%
6 3246
 
3.7%
7 3229
 
3.7%
8 2785
 
3.2%
Other values (13) 5668
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130354
59.8%
ASCII 87801
40.2%
Number Forms 4
 
< 0.1%
None 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36971
42.1%
1 10966
 
12.5%
2 7343
 
8.4%
3 5518
 
6.3%
4 4548
 
5.2%
5 3960
 
4.5%
0 3307
 
3.8%
6 3246
 
3.7%
7 3229
 
3.7%
8 2785
 
3.2%
Other values (47) 5928
 
6.8%
Hangul
ValueCountFrequency (%)
11165
 
8.6%
10855
 
8.3%
10246
 
7.9%
9245
 
7.1%
9129
 
7.0%
9036
 
6.9%
8960
 
6.9%
7532
 
5.8%
7386
 
5.7%
7227
 
5.5%
Other values (388) 39573
30.4%
None
ValueCountFrequency (%)
· 3
100.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1884
Distinct (%)23.9%
Missing2131
Missing (%)21.3%
Infinite0
Infinite (%)0.0%
Mean139395.13
Minimum46002
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:46.867785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46230
Q147253
median48078
Q349228
95-th percentile614805
Maximum619963
Range573961
Interquartile range (IQR)1975

Descriptive statistics

Standard deviation207874.28
Coefficient of variation (CV)1.4912592
Kurtosis1.3458748
Mean139395.13
Median Absolute Deviation (MAD)945
Skewness1.828819
Sum1.0969003 × 109
Variance4.3211715 × 1010
MonotonicityNot monotonic
2024-04-17T06:49:46.982685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48060 63
 
0.6%
47286 59
 
0.6%
47257 58
 
0.6%
48095 46
 
0.5%
46576 43
 
0.4%
46526 41
 
0.4%
46015 41
 
0.4%
46726 38
 
0.4%
47285 37
 
0.4%
48111 36
 
0.4%
Other values (1874) 7407
74.1%
(Missing) 2131
 
21.3%
ValueCountFrequency (%)
46002 3
 
< 0.1%
46006 1
 
< 0.1%
46007 6
 
0.1%
46008 19
0.2%
46010 1
 
< 0.1%
46012 6
 
0.1%
46013 4
 
< 0.1%
46014 1
 
< 0.1%
46015 41
0.4%
46016 3
 
< 0.1%
ValueCountFrequency (%)
619963 18
0.2%
619962 4
 
< 0.1%
619961 1
 
< 0.1%
619953 2
 
< 0.1%
619952 3
 
< 0.1%
619951 2
 
< 0.1%
619950 1
 
< 0.1%
619913 2
 
< 0.1%
619912 4
 
< 0.1%
619906 3
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct7441
Distinct (%)81.5%
Missing868
Missing (%)8.7%
Memory size156.2 KiB
2024-04-17T06:49:47.282036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length57
Mean length28.282194
Min length13

Characters and Unicode

Total characters258273
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

Unique6316 ?
Unique (%)69.2%

Sample

1st row부산광역시 부산진구 가야대로 763-1 (부전동)
2nd row부산광역시 해운대구 마린시티2로 33, 104동 532~535호 (우동, 두산위브제니스)
3rd row부산광역시 사상구 엄궁북로 32-1, 1층 (엄궁동)
4th row부산광역시 기장군 기장읍 대청로72번길 9
5th row부산광역시 동래구 석사로 5 (사직동)
ValueCountFrequency (%)
부산광역시 9132
 
17.7%
부산진구 1169
 
2.3%
금정구 1068
 
2.1%
해운대구 1007
 
2.0%
사하구 857
 
1.7%
동래구 744
 
1.4%
남구 565
 
1.1%
연제구 559
 
1.1%
1층 556
 
1.1%
중앙대로 537
 
1.0%
Other values (4982) 35348
68.6%
2024-04-17T06:49:47.686839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42433
 
16.4%
11584
 
4.5%
11458
 
4.4%
11222
 
4.3%
9629
 
3.7%
9550
 
3.7%
9435
 
3.7%
9136
 
3.5%
9066
 
3.5%
( 8971
 
3.5%
Other values (525) 125789
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153629
59.5%
Space Separator 42433
 
16.4%
Decimal Number 37289
 
14.4%
Open Punctuation 8971
 
3.5%
Close Punctuation 8970
 
3.5%
Other Punctuation 5463
 
2.1%
Dash Punctuation 1040
 
0.4%
Uppercase Letter 286
 
0.1%
Math Symbol 135
 
0.1%
Lowercase Letter 53
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11584
 
7.5%
11458
 
7.5%
11222
 
7.3%
9629
 
6.3%
9550
 
6.2%
9435
 
6.1%
9136
 
5.9%
9066
 
5.9%
4876
 
3.2%
2549
 
1.7%
Other values (464) 65124
42.4%
Uppercase Letter
ValueCountFrequency (%)
B 56
19.6%
A 47
16.4%
S 29
10.1%
K 22
 
7.7%
C 19
 
6.6%
G 16
 
5.6%
E 13
 
4.5%
I 9
 
3.1%
L 9
 
3.1%
M 7
 
2.4%
Other values (14) 59
20.6%
Lowercase Letter
ValueCountFrequency (%)
e 13
24.5%
s 8
15.1%
a 6
11.3%
i 5
 
9.4%
u 4
 
7.5%
r 4
 
7.5%
q 4
 
7.5%
n 2
 
3.8%
o 1
 
1.9%
d 1
 
1.9%
Other values (5) 5
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 8498
22.8%
2 5729
15.4%
3 4151
11.1%
0 3460
9.3%
4 3381
 
9.1%
5 2980
 
8.0%
7 2435
 
6.5%
6 2420
 
6.5%
9 2165
 
5.8%
8 2070
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 5436
99.5%
. 14
 
0.3%
@ 8
 
0.1%
· 3
 
0.1%
/ 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 134
99.3%
1
 
0.7%
Space Separator
ValueCountFrequency (%)
42433
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8971
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8970
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1040
100.0%
Letter Number
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153629
59.5%
Common 104301
40.4%
Latin 343
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11584
 
7.5%
11458
 
7.5%
11222
 
7.3%
9629
 
6.3%
9550
 
6.2%
9435
 
6.1%
9136
 
5.9%
9066
 
5.9%
4876
 
3.2%
2549
 
1.7%
Other values (464) 65124
42.4%
Latin
ValueCountFrequency (%)
B 56
16.3%
A 47
13.7%
S 29
 
8.5%
K 22
 
6.4%
C 19
 
5.5%
G 16
 
4.7%
E 13
 
3.8%
e 13
 
3.8%
I 9
 
2.6%
L 9
 
2.6%
Other values (30) 110
32.1%
Common
ValueCountFrequency (%)
42433
40.7%
( 8971
 
8.6%
) 8970
 
8.6%
1 8498
 
8.1%
2 5729
 
5.5%
, 5436
 
5.2%
3 4151
 
4.0%
0 3460
 
3.3%
4 3381
 
3.2%
5 2980
 
2.9%
Other values (11) 10292
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153629
59.5%
ASCII 104636
40.5%
Number Forms 4
 
< 0.1%
None 3
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42433
40.6%
( 8971
 
8.6%
) 8970
 
8.6%
1 8498
 
8.1%
2 5729
 
5.5%
, 5436
 
5.2%
3 4151
 
4.0%
0 3460
 
3.3%
4 3381
 
3.2%
5 2980
 
2.8%
Other values (48) 10627
 
10.2%
Hangul
ValueCountFrequency (%)
11584
 
7.5%
11458
 
7.5%
11222
 
7.3%
9629
 
6.3%
9550
 
6.2%
9435
 
6.1%
9136
 
5.9%
9066
 
5.9%
4876
 
3.2%
2549
 
1.7%
Other values (464) 65124
42.4%
Number Forms
ValueCountFrequency (%)
4
100.0%
None
ValueCountFrequency (%)
· 3
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

Distinct5299
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20054337
Minimum19570101
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:47.801292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19570101
5-th percentile19829666
Q120001103
median20090429
Q320140107
95-th percentile20171010
Maximum20180903
Range610802
Interquartile range (IQR)139004

Descriptive statistics

Standard deviation111973.09
Coefficient of variation (CV)0.0055834853
Kurtosis1.2872561
Mean20054337
Median Absolute Deviation (MAD)60086
Skewness-1.2902527
Sum2.0054337 × 1011
Variance1.2537974 × 1010
MonotonicityNot monotonic
2024-04-17T06:49:47.909686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121112 120
 
1.2%
20121115 79
 
0.8%
20121114 79
 
0.8%
20121113 76
 
0.8%
20121109 69
 
0.7%
20121116 63
 
0.6%
20121108 43
 
0.4%
20121107 33
 
0.3%
20121106 29
 
0.3%
20121110 16
 
0.2%
Other values (5289) 9393
93.9%
ValueCountFrequency (%)
19570101 1
< 0.1%
19590110 1
< 0.1%
19600101 1
< 0.1%
19610316 1
< 0.1%
19610418 1
< 0.1%
19611107 1
< 0.1%
19611220 1
< 0.1%
19620130 1
< 0.1%
19620312 1
< 0.1%
19620503 1
< 0.1%
ValueCountFrequency (%)
20180903 6
0.1%
20180901 1
 
< 0.1%
20180831 2
 
< 0.1%
20180830 6
0.1%
20180829 2
 
< 0.1%
20180828 2
 
< 0.1%
20180827 2
 
< 0.1%
20180824 1
 
< 0.1%
20180823 1
 
< 0.1%
20180822 2
 
< 0.1%

dcbymd
Real number (ℝ)

MISSING  SKEWED 

Distinct2485
Distinct (%)59.4%
Missing5816
Missing (%)58.2%
Infinite0
Infinite (%)0.0%
Mean20097145
Minimum10101
Maximum20180904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:48.019926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile19911131
Q120090701
median20121202
Q320151027
95-th percentile20180314
Maximum20180904
Range20170803
Interquartile range (IQR)60326

Descriptive statistics

Standard deviation320873.67
Coefficient of variation (CV)0.015966132
Kurtosis3673.7896
Mean20097145
Median Absolute Deviation (MAD)30273.5
Skewness-58.709492
Sum8.4086454 × 1010
Variance1.0295991 × 1011
MonotonicityNot monotonic
2024-04-17T06:49:48.136555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130701 13
 
0.1%
20140901 12
 
0.1%
20091231 10
 
0.1%
20110502 10
 
0.1%
20130102 9
 
0.1%
20141201 9
 
0.1%
20130902 9
 
0.1%
20131101 8
 
0.1%
20171229 8
 
0.1%
20161201 8
 
0.1%
Other values (2475) 4088
40.9%
(Missing) 5816
58.2%
ValueCountFrequency (%)
10101 1
< 0.1%
19000101 1
< 0.1%
19760520 1
< 0.1%
19770128 1
< 0.1%
19770415 1
< 0.1%
19770512 1
< 0.1%
19770621 1
< 0.1%
19790214 1
< 0.1%
19790402 1
< 0.1%
19790409 1
< 0.1%
ValueCountFrequency (%)
20180904 1
 
< 0.1%
20180903 4
< 0.1%
20180901 3
< 0.1%
20180831 3
< 0.1%
20180830 4
< 0.1%
20180829 2
< 0.1%
20180827 3
< 0.1%
20180824 1
 
< 0.1%
20180823 1
 
< 0.1%
20180821 4
< 0.1%

clgstdt
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)100.0%
Missing9930
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20130812
Minimum20000403
Maximum20181001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:48.246931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20085169
Q120100728
median20126016
Q320170193
95-th percentile20180667
Maximum20181001
Range180598
Interquartile range (IQR)69465.25

Descriptive statistics

Standard deviation38269.87
Coefficient of variation (CV)0.0019010594
Kurtosis0.31490628
Mean20130812
Median Absolute Deviation (MAD)34844.5
Skewness-0.48817418
Sum1.4091569 × 109
Variance1.4645829 × 109
MonotonicityNot monotonic
2024-04-17T06:49:48.368337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110609 1
 
< 0.1%
20170307 1
 
< 0.1%
20180703 1
 
< 0.1%
20090225 1
 
< 0.1%
20120726 1
 
< 0.1%
20090615 1
 
< 0.1%
20160715 1
 
< 0.1%
20140115 1
 
< 0.1%
20170416 1
 
< 0.1%
20110304 1
 
< 0.1%
Other values (60) 60
 
0.6%
(Missing) 9930
99.3%
ValueCountFrequency (%)
20000403 1
< 0.1%
20051001 1
< 0.1%
20080904 1
< 0.1%
20081118 1
< 0.1%
20090120 1
< 0.1%
20090201 1
< 0.1%
20090202 1
< 0.1%
20090225 1
< 0.1%
20090604 1
< 0.1%
20090615 1
< 0.1%
ValueCountFrequency (%)
20181001 1
< 0.1%
20180901 1
< 0.1%
20180703 1
< 0.1%
20180701 1
< 0.1%
20180626 1
< 0.1%
20180603 1
< 0.1%
20180420 1
< 0.1%
20180417 1
< 0.1%
20180224 1
< 0.1%
20180201 1
< 0.1%

clgenddt
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)92.9%
Missing9930
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean21280121
Minimum20000403
Maximum99991231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:48.513410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000403
5-th percentile20090720
Q120110180
median20140514
Q320170978
95-th percentile20190885
Maximum99991231
Range79990828
Interquartile range (IQR)60797.25

Descriptive statistics

Standard deviation9544202.7
Coefficient of variation (CV)0.44850322
Kurtosis69.997517
Mean21280121
Median Absolute Deviation (MAD)30439
Skewness8.3663808
Sum1.4896085 × 109
Variance9.1091806 × 1013
MonotonicityNot monotonic
2024-04-17T06:49:48.629112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131231 3
 
< 0.1%
20170131 2
 
< 0.1%
20170331 2
 
< 0.1%
20121231 2
 
< 0.1%
20171002 1
 
< 0.1%
20110803 1
 
< 0.1%
20180716 1
 
< 0.1%
20100914 1
 
< 0.1%
20130924 1
 
< 0.1%
20110504 1
 
< 0.1%
Other values (55) 55
 
0.5%
(Missing) 9930
99.3%
ValueCountFrequency (%)
20000403 1
< 0.1%
20090331 1
< 0.1%
20090518 1
< 0.1%
20090712 1
< 0.1%
20090730 1
< 0.1%
20090901 1
< 0.1%
20091031 1
< 0.1%
20091231 1
< 0.1%
20100201 1
< 0.1%
20100224 1
< 0.1%
ValueCountFrequency (%)
99991231 1
< 0.1%
20221227 1
< 0.1%
20191231 1
< 0.1%
20190930 1
< 0.1%
20190831 1
< 0.1%
20190630 1
< 0.1%
20190602 1
< 0.1%
20190131 1
< 0.1%
20190102 1
< 0.1%
20181231 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
5666 
3
4291 
24
 
30
2
 
13

Length

Max length2
Median length2
Mean length1.5696
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 5666
56.7%
3 4291
42.9%
24 30
 
0.3%
2 13
 
0.1%

Length

2024-04-17T06:49:48.733684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:48.807986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 5666
56.7%
3 4291
42.9%
24 30
 
0.3%
2 13
 
0.1%

dtlstatenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
5666 
폐업
4291 
직권폐업
 
30
휴업
 
13

Length

Max length4
Median length3
Mean length2.5726
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 5666
56.7%
폐업 4291
42.9%
직권폐업 30
 
0.3%
휴업 13
 
0.1%

Length

2024-04-17T06:49:48.894291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:48.975839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 5666
56.7%
폐업 4291
42.9%
직권폐업 30
 
0.3%
휴업 13
 
0.1%

x
Real number (ℝ)

MISSING 

Distinct5305
Distinct (%)58.0%
Missing855
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean388253.71
Minimum365157.28
Maximum407581.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:49.063555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365157.28
5-th percentile379621.65
Q1384371.75
median388785.44
Q3391572.76
95-th percentile398134.03
Maximum407581.08
Range42423.807
Interquartile range (IQR)7201.0091

Descriptive statistics

Standard deviation5605.4378
Coefficient of variation (CV)0.014437564
Kurtosis0.46781296
Mean388253.71
Median Absolute Deviation (MAD)3432.7843
Skewness-0.068491694
Sum3.5505801 × 109
Variance31420933
MonotonicityNot monotonic
2024-04-17T06:49:49.159619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387537.525975 21
 
0.2%
398226.822818 19
 
0.2%
387475.894546 19
 
0.2%
394179.058785 18
 
0.2%
398207.440468 14
 
0.1%
397548.804885 14
 
0.1%
398310.243451 13
 
0.1%
389193.047711 13
 
0.1%
392456.731808 11
 
0.1%
391109.287295 11
 
0.1%
Other values (5295) 8992
89.9%
(Missing) 855
 
8.6%
ValueCountFrequency (%)
365157.276407 1
< 0.1%
366830.688326 1
< 0.1%
366851.651911 1
< 0.1%
366871.978797 1
< 0.1%
366877.108901 1
< 0.1%
367041.14892 1
< 0.1%
367134.0 1
< 0.1%
367149.616883 2
< 0.1%
367185.0 1
< 0.1%
367228.343027 1
< 0.1%
ValueCountFrequency (%)
407581.083119 3
< 0.1%
407515.749132 1
 
< 0.1%
407504.0 1
 
< 0.1%
407448.0 1
 
< 0.1%
407369.530548 1
 
< 0.1%
407340.290634 1
 
< 0.1%
407209.258171 1
 
< 0.1%
407077.691757 1
 
< 0.1%
405468.503509 1
 
< 0.1%
404343.092468 2
< 0.1%

y
Real number (ℝ)

MISSING 

Distinct5304
Distinct (%)58.0%
Missing855
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean187734.4
Minimum170014.45
Maximum211893.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:49.266004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170014.45
5-th percentile178609.77
Q1183467.78
median187531.4
Q3191794.21
95-th percentile197704.36
Maximum211893.97
Range41879.512
Interquartile range (IQR)8326.4249

Descriptive statistics

Standard deviation6084.9706
Coefficient of variation (CV)0.032412657
Kurtosis0.074822285
Mean187734.4
Median Absolute Deviation (MAD)4172.9963
Skewness0.33502648
Sum1.7168311 × 109
Variance37026867
MonotonicityNot monotonic
2024-04-17T06:49:49.369045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186476.330395 21
 
0.2%
187989.753665 19
 
0.2%
186570.418307 19
 
0.2%
187825.814573 18
 
0.2%
188174.016538 14
 
0.1%
187626.880998 14
 
0.1%
188031.67198 13
 
0.1%
191850.435201 13
 
0.1%
183776.525264 11
 
0.1%
191389.277107 11
 
0.1%
Other values (5294) 8992
89.9%
(Missing) 855
 
8.6%
ValueCountFrequency (%)
170014.453769 1
 
< 0.1%
170016.321524 1
 
< 0.1%
171205.308829 1
 
< 0.1%
174205.541619 1
 
< 0.1%
174237.045871 2
< 0.1%
174251.931196 1
 
< 0.1%
174292.594164 2
< 0.1%
174396.378069 4
< 0.1%
174413.752458 1
 
< 0.1%
174415.392886 1
 
< 0.1%
ValueCountFrequency (%)
211893.965608 2
< 0.1%
211392.6938 1
 
< 0.1%
208906.876551 1
 
< 0.1%
207362.005561 1
 
< 0.1%
206821.489013 1
 
< 0.1%
206576.725149 1
 
< 0.1%
206494.685696 1
 
< 0.1%
206426.679067 4
< 0.1%
206423.253753 2
< 0.1%
206411.480935 1
 
< 0.1%

lastmodts
Real number (ℝ)

Distinct8015
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0149674 × 1013
Minimum2.0081008 × 1013
Maximum2.0180904 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:49.476311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081008 × 1013
5-th percentile2.0090202 × 1013
Q12.0130705 × 1013
median2.0160722 × 1013
Q32.0170905 × 1013
95-th percentile2.0180711 × 1013
Maximum2.0180904 × 1013
Range9.989602 × 1010
Interquartile range (IQR)4.0200016 × 1010

Descriptive statistics

Standard deviation2.9168561 × 1010
Coefficient of variation (CV)0.0014475946
Kurtosis-0.49446676
Mean2.0149674 × 1013
Median Absolute Deviation (MAD)1.9599074 × 1010
Skewness-0.82926094
Sum2.0149674 × 1017
Variance8.5080493 × 1020
MonotonicityNot monotonic
2024-04-17T06:49:49.592057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905183844 207
 
2.1%
20170905183851 195
 
1.9%
20170905183850 193
 
1.9%
20170905183853 176
 
1.8%
20170905183849 148
 
1.5%
20170905183843 113
 
1.1%
20170905183852 108
 
1.1%
20170905183848 101
 
1.0%
20170905183858 77
 
0.8%
20170905183859 75
 
0.8%
Other values (8005) 8607
86.1%
ValueCountFrequency (%)
20081008160928 1
< 0.1%
20081020092224 1
< 0.1%
20081022163931 1
< 0.1%
20081111113351 1
< 0.1%
20081118094507 1
< 0.1%
20081125173655 1
< 0.1%
20081125181445 1
< 0.1%
20081126095545 1
< 0.1%
20081126101537 1
< 0.1%
20081126142837 1
< 0.1%
ValueCountFrequency (%)
20180904181338 1
< 0.1%
20180904180453 1
< 0.1%
20180904174554 1
< 0.1%
20180904174453 1
< 0.1%
20180904174336 1
< 0.1%
20180904165343 1
< 0.1%
20180904154925 1
< 0.1%
20180904140506 1
< 0.1%
20180904132218 1
< 0.1%
20180904105301 1
< 0.1%

uptaenm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4612 
의원
2610 
한의원
1226 
치과의원
1130 
요양병원(일반요양병원)
 
173
Other values (9)
 
249

Length

Max length12
Median length4
Mean length3.473
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4612
46.1%
의원 2610
26.1%
한의원 1226
 
12.3%
치과의원 1130
 
11.3%
요양병원(일반요양병원) 173
 
1.7%
병원 134
 
1.3%
조산원 22
 
0.2%
종합병원 21
 
0.2%
치과병원 19
 
0.2%
요양병원(정신병원) 15
 
0.1%
Other values (4) 38
 
0.4%

Length

2024-04-17T06:49:49.697227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4612
46.1%
의원 2610
26.1%
한의원 1226
 
12.3%
치과의원 1130
 
11.3%
요양병원(일반요양병원 173
 
1.7%
병원 134
 
1.3%
조산원 22
 
0.2%
종합병원 21
 
0.2%
치과병원 19
 
0.2%
요양병원(정신병원 15
 
0.1%
Other values (4) 38
 
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

2024-04-17T06:49:49.793667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:49.859433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 10000
100.0%

nursecnt
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)23.1%
Missing9974
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean3.4615385
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:49.922879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12.25
median3
Q34
95-th percentile5.75
Maximum6
Range5
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation1.3335897
Coefficient of variation (CV)0.38525925
Kurtosis-0.65673082
Mean3.4615385
Median Absolute Deviation (MAD)1
Skewness0.2536277
Sum90
Variance1.7784615
MonotonicityNot monotonic
2024-04-17T06:49:50.005315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 7
 
0.1%
2 6
 
0.1%
4 6
 
0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
1 1
 
< 0.1%
(Missing) 9974
99.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 6
0.1%
3 7
0.1%
4 6
0.1%
5 4
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 4
< 0.1%
4 6
0.1%
3 7
0.1%
2 6
0.1%
1 1
 
< 0.1%

nursaidcnt
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)46.2%
Missing9974
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean6.3461538
Minimum2
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:50.335024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13
median6
Q39
95-th percentile13.25
Maximum15
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.730333
Coefficient of variation (CV)0.58781006
Kurtosis-0.17955934
Mean6.3461538
Median Absolute Deviation (MAD)3
Skewness0.67172261
Sum165
Variance13.915385
MonotonicityNot monotonic
2024-04-17T06:49:50.420052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 5
 
0.1%
6 4
 
< 0.1%
3 3
 
< 0.1%
9 3
 
< 0.1%
4 2
 
< 0.1%
7 2
 
< 0.1%
10 2
 
< 0.1%
14 1
 
< 0.1%
5 1
 
< 0.1%
15 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 9974
99.7%
ValueCountFrequency (%)
2 5
0.1%
3 3
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 4
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 3
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 2
< 0.1%
9 3
< 0.1%
8 1
 
< 0.1%
7 2
< 0.1%
6 4
< 0.1%
5 1
 
< 0.1%
4 2
< 0.1%

bdnglayercnt
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)56.0%
Missing9975
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean8.08
Minimum0
Maximum23
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:50.504084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q311
95-th percentile20.4
Maximum23
Range23
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.0409712
Coefficient of variation (CV)0.74764495
Kurtosis0.88726682
Mean8.08
Median Absolute Deviation (MAD)4
Skewness0.8212968
Sum202
Variance36.493333
MonotonicityNot monotonic
2024-04-17T06:49:50.585856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 3
 
< 0.1%
8 3
 
< 0.1%
2 3
 
< 0.1%
12 3
 
< 0.1%
9 2
 
< 0.1%
7 2
 
< 0.1%
11 2
 
< 0.1%
6 1
 
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 9975
99.8%
ValueCountFrequency (%)
0 3
< 0.1%
2 3
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%
8 3
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
11 2
< 0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
14 1
 
< 0.1%
12 3
< 0.1%
11 2
< 0.1%
10 1
 
< 0.1%
9 2
< 0.1%
8 3
< 0.1%
7 2
< 0.1%
6 1
 
< 0.1%

emercargen
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5901 
0
4099 

Length

Max length4
Median length4
Mean length2.7703
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5901
59.0%
0 4099
41.0%

Length

2024-04-17T06:49:50.681059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:50.762301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5901
59.0%
0 4099
41.0%

emercarspec
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5901 
0
4099 

Length

Max length4
Median length4
Mean length2.7703
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5901
59.0%
0 4099
41.0%

Length

2024-04-17T06:49:50.847855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:50.923873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5901
59.0%
0 4099
41.0%

rescnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

pomfacilar
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)92.9%
Missing9986
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean45.729286
Minimum0
Maximum162
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:50.987564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118.315
median38.17
Q355.25
95-th percentile127.94
Maximum162
Range162
Interquartile range (IQR)36.935

Descriptive statistics

Standard deviation43.855772
Coefficient of variation (CV)0.95903032
Kurtosis3.1141649
Mean45.729286
Median Absolute Deviation (MAD)20.25
Skewness1.6743786
Sum640.21
Variance1923.3287
MonotonicityNot monotonic
2024-04-17T06:49:51.073694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
25.0 1
 
< 0.1%
42.56 1
 
< 0.1%
109.6 1
 
< 0.1%
162.0 1
 
< 0.1%
16.5 1
 
< 0.1%
62.05 1
 
< 0.1%
38.0 1
 
< 0.1%
38.34 1
 
< 0.1%
23.76 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 9986
99.9%
ValueCountFrequency (%)
0.0 2
< 0.1%
15.4 1
< 0.1%
16.5 1
< 0.1%
23.76 1
< 0.1%
25.0 1
< 0.1%
38.0 1
< 0.1%
38.34 1
< 0.1%
42.56 1
< 0.1%
50.0 1
< 0.1%
57.0 1
< 0.1%
ValueCountFrequency (%)
162.0 1
< 0.1%
109.6 1
< 0.1%
62.05 1
< 0.1%
57.0 1
< 0.1%
50.0 1
< 0.1%
42.56 1
< 0.1%
38.34 1
< 0.1%
38.0 1
< 0.1%
25.0 1
< 0.1%
23.76 1
< 0.1%

etcstfcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9992 
1
 
6
0
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.9976
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9992
99.9%
1 6
 
0.1%
0 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T06:49:51.172497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:51.251141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9992
99.9%
1 6
 
0.1%
0 1
 
< 0.1%
5 1
 
< 0.1%

etcepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

mmknurmar
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)100.0%
Missing9979
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean48.878095
Minimum6.8
Maximum494.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:51.331854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile7
Q111
median22.96
Q342
95-th percentile68.8
Maximum494.67
Range487.87
Interquartile range (IQR)31

Descriptive statistics

Standard deviation103.7373
Coefficient of variation (CV)2.1223678
Kurtosis19.538181
Mean48.878095
Median Absolute Deviation (MAD)12.4
Skewness4.3573228
Sum1026.44
Variance10761.427
MonotonicityNot monotonic
2024-04-17T06:49:51.427659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
33.66 1
 
< 0.1%
7.0 1
 
< 0.1%
14.12 1
 
< 0.1%
11.0 1
 
< 0.1%
68.8 1
 
< 0.1%
6.8 1
 
< 0.1%
46.8 1
 
< 0.1%
16.12 1
 
< 0.1%
54.07 1
 
< 0.1%
494.67 1
 
< 0.1%
Other values (11) 11
 
0.1%
(Missing) 9979
99.8%
ValueCountFrequency (%)
6.8 1
< 0.1%
7.0 1
< 0.1%
8.97 1
< 0.1%
10.56 1
< 0.1%
10.7 1
< 0.1%
11.0 1
< 0.1%
13.0 1
< 0.1%
14.12 1
< 0.1%
14.9 1
< 0.1%
16.12 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%
42.0 1
< 0.1%
38.8 1
< 0.1%
33.66 1
< 0.1%
32.0 1
< 0.1%
26.23 1
< 0.1%

btrmar
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)90.0%
Missing9990
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean9.013
Minimum0
Maximum21.5
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:51.510679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.075
median8.465
Q310.545
95-th percentile21.464
Maximum21.5
Range21.5
Interquartile range (IQR)6.47

Descriptive statistics

Standard deviation7.574064
Coefficient of variation (CV)0.84034883
Kurtosis-0.19681567
Mean9.013
Median Absolute Deviation (MAD)3.95
Skewness0.6983063
Sum90.13
Variance57.366446
MonotonicityNot monotonic
2024-04-17T06:49:51.589556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
7.0 1
 
< 0.1%
8.03 1
 
< 0.1%
21.42 1
 
< 0.1%
8.9 1
 
< 0.1%
11.0 1
 
< 0.1%
9.18 1
 
< 0.1%
3.1 1
 
< 0.1%
21.5 1
 
< 0.1%
(Missing) 9990
99.9%
ValueCountFrequency (%)
0.0 2
< 0.1%
3.1 1
< 0.1%
7.0 1
< 0.1%
8.03 1
< 0.1%
8.9 1
< 0.1%
9.18 1
< 0.1%
11.0 1
< 0.1%
21.42 1
< 0.1%
21.5 1
< 0.1%
ValueCountFrequency (%)
21.5 1
< 0.1%
21.42 1
< 0.1%
11.0 1
< 0.1%
9.18 1
< 0.1%
8.9 1
< 0.1%
8.03 1
< 0.1%
7.0 1
< 0.1%
3.1 1
< 0.1%
0.0 2
< 0.1%

btpnum
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9986 
1
 
8
2
 
4
0
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9958
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9986
99.9%
1 8
 
0.1%
2 4
 
< 0.1%
0 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-04-17T06:49:51.681925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:51.762652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9986
99.9%
1 8
 
0.1%
2 4
 
< 0.1%
0 1
 
< 0.1%
6 1
 
< 0.1%

sicbnum
Real number (ℝ)

MISSING  ZEROS 

Distinct206
Distinct (%)5.0%
Missing5901
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean14.003903
Minimum0
Maximum1306
Zeros3446
Zeros (%)34.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:51.852150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile97
Maximum1306
Range1306
Interquartile range (IQR)0

Descriptive statistics

Standard deviation57.445206
Coefficient of variation (CV)4.1020853
Kurtosis103.48447
Mean14.003903
Median Absolute Deviation (MAD)0
Skewness7.8814006
Sum57402
Variance3299.9517
MonotonicityNot monotonic
2024-04-17T06:49:51.969114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3446
34.5%
29 65
 
0.7%
1 34
 
0.3%
2 33
 
0.3%
4 32
 
0.3%
3 23
 
0.2%
6 14
 
0.1%
28 11
 
0.1%
30 11
 
0.1%
199 11
 
0.1%
Other values (196) 419
 
4.2%
(Missing) 5901
59.0%
ValueCountFrequency (%)
0 3446
34.5%
1 34
 
0.3%
2 33
 
0.3%
3 23
 
0.2%
4 32
 
0.3%
5 6
 
0.1%
6 14
 
0.1%
7 6
 
0.1%
8 6
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
1306 1
< 0.1%
896 1
< 0.1%
797 1
< 0.1%
590 1
< 0.1%
580 1
< 0.1%
524 1
< 0.1%
457 1
< 0.1%
439 1
< 0.1%
425 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 

Distinct16
Distinct (%)94.1%
Missing9983
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean11.702353
Minimum0
Maximum28.2
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:52.060926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.44
Q18
median11.29
Q313
95-th percentile25.8
Maximum28.2
Range28.2
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.8541635
Coefficient of variation (CV)0.58570815
Kurtosis1.7389583
Mean11.702353
Median Absolute Deviation (MAD)3.29
Skewness1.0420536
Sum198.94
Variance46.979557
MonotonicityNot monotonic
2024-04-17T06:49:52.141173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
8.0 2
 
< 0.1%
11.29 1
 
< 0.1%
13.94 1
 
< 0.1%
25.2 1
 
< 0.1%
9.2 1
 
< 0.1%
10.0 1
 
< 0.1%
28.2 1
 
< 0.1%
7.91 1
 
< 0.1%
16.2 1
 
< 0.1%
12.06 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 9983
99.8%
ValueCountFrequency (%)
0.0 1
< 0.1%
4.3 1
< 0.1%
6.6 1
< 0.1%
7.91 1
< 0.1%
8.0 2
< 0.1%
9.2 1
< 0.1%
10.0 1
< 0.1%
11.29 1
< 0.1%
12.06 1
< 0.1%
12.4 1
< 0.1%
ValueCountFrequency (%)
28.2 1
< 0.1%
25.2 1
< 0.1%
16.2 1
< 0.1%
13.94 1
< 0.1%
13.0 1
< 0.1%
12.64 1
< 0.1%
12.4 1
< 0.1%
12.06 1
< 0.1%
11.29 1
< 0.1%
10.0 1
< 0.1%

warmar
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing9986
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean16.061429
Minimum0
Maximum48.7
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:52.221684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.625
Q18.53
median12.81
Q316.8
95-th percentile41.095
Maximum48.7
Range48.7
Interquartile range (IQR)8.27

Descriptive statistics

Standard deviation13.439942
Coefficient of variation (CV)0.83678369
Kurtosis1.6573403
Mean16.061429
Median Absolute Deviation (MAD)4.5
Skewness1.3618603
Sum224.86
Variance180.63203
MonotonicityNot monotonic
2024-04-17T06:49:52.317060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
11.0 1
 
< 0.1%
5.52 1
 
< 0.1%
27.9 1
 
< 0.1%
0.0 1
 
< 0.1%
15.3 1
 
< 0.1%
8.0 1
 
< 0.1%
14.0 1
 
< 0.1%
16.2 1
 
< 0.1%
11.62 1
 
< 0.1%
10.12 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 9986
99.9%
ValueCountFrequency (%)
0.0 1
< 0.1%
2.5 1
< 0.1%
5.52 1
< 0.1%
8.0 1
< 0.1%
10.12 1
< 0.1%
11.0 1
< 0.1%
11.62 1
< 0.1%
14.0 1
< 0.1%
15.3 1
< 0.1%
16.2 1
< 0.1%
ValueCountFrequency (%)
48.7 1
< 0.1%
37.0 1
< 0.1%
27.9 1
< 0.1%
17.0 1
< 0.1%
16.2 1
< 0.1%
15.3 1
< 0.1%
14.0 1
< 0.1%
11.62 1
< 0.1%
11.0 1
< 0.1%
10.12 1
< 0.1%

facilmngnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

pharmtrdar
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1143
Distinct (%)43.8%
Missing7389
Missing (%)73.9%
Infinite0
Infinite (%)0.0%
Mean76.993026
Minimum0
Maximum74949
Zeros282
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:52.440126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.15
median42
Q366.435
95-th percentile127.635
Maximum74949
Range74949
Interquartile range (IQR)45.285

Descriptive statistics

Standard deviation1466.4391
Coefficient of variation (CV)19.046389
Kurtosis2606.6309
Mean76.993026
Median Absolute Deviation (MAD)23.75
Skewness51.033872
Sum201028.79
Variance2150443.6
MonotonicityNot monotonic
2024-04-17T06:49:52.557677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 282
 
2.8%
1.0 265
 
2.6%
33.0 32
 
0.3%
49.5 24
 
0.2%
66.0 24
 
0.2%
82.5 19
 
0.2%
99.0 17
 
0.2%
36.0 16
 
0.2%
24.0 15
 
0.1%
52.8 15
 
0.1%
Other values (1133) 1902
 
19.0%
(Missing) 7389
73.9%
ValueCountFrequency (%)
0.0 282
2.8%
1.0 265
2.6%
8.86 1
 
< 0.1%
9.0 1
 
< 0.1%
10.28 1
 
< 0.1%
11.11 1
 
< 0.1%
12.5 1
 
< 0.1%
12.9 2
 
< 0.1%
12.96 2
 
< 0.1%
13.2 1
 
< 0.1%
ValueCountFrequency (%)
74949.0 1
< 0.1%
454.92 1
< 0.1%
450.0 1
< 0.1%
294.0 1
< 0.1%
251.0 1
< 0.1%
250.47 1
< 0.1%
250.0 1
< 0.1%
247.07 1
< 0.1%
240.5 1
< 0.1%
240.0 1
< 0.1%

nutrcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9991 
0
 
6
1
 
3

Length

Max length4
Median length4
Mean length3.9973
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> 9991
99.9%
0 6
 
0.1%
1 3
 
< 0.1%

Length

2024-04-17T06:49:52.665998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:52.742287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9991
99.9%
0 6
 
0.1%
1 3
 
< 0.1%

bbrmar
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)100.0%
Missing9976
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean49.048333
Minimum14.2
Maximum114.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:52.816328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.2
5-th percentile17.593
Q123.9325
median42.02
Q363.4175
95-th percentile102.858
Maximum114.3
Range100.1
Interquartile range (IQR)39.485

Descriptive statistics

Standard deviation29.455791
Coefficient of variation (CV)0.60054621
Kurtosis-0.13446256
Mean49.048333
Median Absolute Deviation (MAD)19.055
Skewness0.89571154
Sum1177.16
Variance867.64361
MonotonicityNot monotonic
2024-04-17T06:49:52.904775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20.5 1
 
< 0.1%
41.04 1
 
< 0.1%
24.0 1
 
< 0.1%
43.0 1
 
< 0.1%
93.0 1
 
< 0.1%
25.0 1
 
< 0.1%
17.2 1
 
< 0.1%
114.3 1
 
< 0.1%
23.73 1
 
< 0.1%
67.92 1
 
< 0.1%
Other values (14) 14
 
0.1%
(Missing) 9976
99.8%
ValueCountFrequency (%)
14.2 1
< 0.1%
17.2 1
< 0.1%
19.82 1
< 0.1%
20.5 1
< 0.1%
22.2 1
< 0.1%
23.73 1
< 0.1%
24.0 1
< 0.1%
25.0 1
< 0.1%
29.89 1
< 0.1%
37.1 1
< 0.1%
ValueCountFrequency (%)
114.3 1
< 0.1%
103.08 1
< 0.1%
101.6 1
< 0.1%
93.0 1
< 0.1%
67.92 1
< 0.1%
67.37 1
< 0.1%
62.1 1
< 0.1%
54.0 1
< 0.1%
53.43 1
< 0.1%
53.14 1
< 0.1%

babyrglstnum
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)78.6%
Missing9972
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20.357143
Minimum3
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:53.018755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5.7
Q110.5
median18
Q325
95-th percentile43.65
Maximum50
Range47
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation12.7924
Coefficient of variation (CV)0.62839861
Kurtosis-0.12293703
Mean20.357143
Median Absolute Deviation (MAD)8
Skewness0.85583871
Sum570
Variance163.6455
MonotonicityNot monotonic
2024-04-17T06:49:53.118384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9 3
 
< 0.1%
24 2
 
< 0.1%
20 2
 
< 0.1%
17 2
 
< 0.1%
12 2
 
< 0.1%
28 1
 
< 0.1%
23 1
 
< 0.1%
13 1
 
< 0.1%
8 1
 
< 0.1%
14 1
 
< 0.1%
Other values (12) 12
 
0.1%
(Missing) 9972
99.7%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 3
< 0.1%
11 1
 
< 0.1%
12 2
< 0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
17 2
< 0.1%
ValueCountFrequency (%)
50 1
< 0.1%
44 1
< 0.1%
43 1
< 0.1%
40 1
< 0.1%
38 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
24 2
< 0.1%
23 1
< 0.1%
22 1
< 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 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5901 
의원
1955 
한의원
900 
치과의원
827 
요양병원(일반요양병원)
 
173
Other values (13)
 
244

Length

Max length12
Median length4
Mean length3.6374
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5901
59.0%
의원 1955
 
19.6%
한의원 900
 
9.0%
치과의원 827
 
8.3%
요양병원(일반요양병원) 173
 
1.7%
병원 134
 
1.3%
종합병원 21
 
0.2%
치과병원 19
 
0.2%
부속의원 16
 
0.2%
요양병원(정신병원) 15
 
0.1%
Other values (8) 39
 
0.4%

Length

2024-04-17T06:49:53.213748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5901
59.0%
의원 1955
 
19.6%
한의원 900
 
9.0%
치과의원 827
 
8.3%
요양병원(일반요양병원 173
 
1.7%
병원 134
 
1.3%
종합병원 21
 
0.2%
치과병원 19
 
0.2%
부속의원 16
 
0.2%
요양병원(정신병원 15
 
0.1%
Other values (8) 39
 
0.4%

metrbosassrnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

metrpnum
Real number (ℝ)

MISSING  SKEWED 

Distinct80
Distinct (%)2.0%
Missing5901
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean4.3625274
Minimum0
Maximum1436
Zeros73
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:53.314458image/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 deviation35.063963
Coefficient of variation (CV)8.0375341
Kurtosis1125.178
Mean4.3625274
Median Absolute Deviation (MAD)0
Skewness30.456524
Sum17882
Variance1229.4815
MonotonicityNot monotonic
2024-04-17T06:49:53.424242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3043
30.4%
2 421
 
4.2%
3 126
 
1.3%
0 73
 
0.7%
4 62
 
0.6%
5 41
 
0.4%
7 30
 
0.3%
6 26
 
0.3%
10 21
 
0.2%
8 17
 
0.2%
Other values (70) 239
 
2.4%
(Missing) 5901
59.0%
ValueCountFrequency (%)
0 73
 
0.7%
1 3043
30.4%
2 421
 
4.2%
3 126
 
1.3%
4 62
 
0.6%
5 41
 
0.4%
6 26
 
0.3%
7 30
 
0.3%
8 17
 
0.2%
9 14
 
0.1%
ValueCountFrequency (%)
1436 1
< 0.1%
1282 1
< 0.1%
406 1
< 0.1%
366 1
< 0.1%
353 1
< 0.1%
341 1
< 0.1%
331 1
< 0.1%
310 1
< 0.1%
278 1
< 0.1%
268 1
< 0.1%

pgrmar
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)100.0%
Missing9975
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean369.0048
Minimum7.5
Maximum894.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:53.520395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.5
5-th percentile11.76
Q1146
median385.97
Q3482
95-th percentile849.124
Maximum894.11
Range886.61
Interquartile range (IQR)336

Descriptive statistics

Standard deviation262.80237
Coefficient of variation (CV)0.71219227
Kurtosis-0.45948402
Mean369.0048
Median Absolute Deviation (MAD)226.29
Skewness0.46975829
Sum9225.12
Variance69065.084
MonotonicityNot monotonic
2024-04-17T06:49:53.610413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
894.11 1
 
< 0.1%
406.64 1
 
< 0.1%
146.0 1
 
< 0.1%
116.13 1
 
< 0.1%
482.0 1
 
< 0.1%
459.31 1
 
< 0.1%
14.0 1
 
< 0.1%
7.5 1
 
< 0.1%
848.02 1
 
< 0.1%
132.61 1
 
< 0.1%
Other values (15) 15
 
0.1%
(Missing) 9975
99.8%
ValueCountFrequency (%)
7.5 1
< 0.1%
11.2 1
< 0.1%
14.0 1
< 0.1%
61.2 1
< 0.1%
116.13 1
< 0.1%
132.61 1
< 0.1%
146.0 1
< 0.1%
154.52 1
< 0.1%
224.5 1
< 0.1%
295.92 1
< 0.1%
ValueCountFrequency (%)
894.11 1
< 0.1%
849.4 1
< 0.1%
848.02 1
< 0.1%
654.9 1
< 0.1%
612.26 1
< 0.1%
504.56 1
< 0.1%
482.0 1
< 0.1%
462.31 1
< 0.1%
459.31 1
< 0.1%
429.2 1
< 0.1%

pwnmrglstnum
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)75.0%
Missing9972
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20.642857
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:53.694978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q111
median18
Q325
95-th percentile43.65
Maximum50
Range45
Interquartile range (IQR)14

Descriptive statistics

Standard deviation12.505449
Coefficient of variation (CV)0.60580028
Kurtosis-0.051063409
Mean20.642857
Median Absolute Deviation (MAD)7
Skewness0.92016616
Sum578
Variance156.38624
MonotonicityNot monotonic
2024-04-17T06:49:53.781581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20 2
 
< 0.1%
14 2
 
< 0.1%
17 2
 
< 0.1%
7 2
 
< 0.1%
11 2
 
< 0.1%
9 2
 
< 0.1%
24 2
 
< 0.1%
23 1
 
< 0.1%
13 1
 
< 0.1%
8 1
 
< 0.1%
Other values (11) 11
 
0.1%
(Missing) 9972
99.7%
ValueCountFrequency (%)
5 1
< 0.1%
7 2
< 0.1%
8 1
< 0.1%
9 2
< 0.1%
11 2
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 2
< 0.1%
17 2
< 0.1%
19 1
< 0.1%
ValueCountFrequency (%)
50 1
< 0.1%
44 1
< 0.1%
43 1
< 0.1%
40 1
< 0.1%
38 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
24 2
< 0.1%
23 1
< 0.1%
22 1
< 0.1%

hstrmnum
Real number (ℝ)

MISSING  ZEROS 

Distinct91
Distinct (%)2.2%
Missing5901
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean3.2895828
Minimum0
Maximum345
Zeros3487
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:53.877120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile23
Maximum345
Range345
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.670861
Coefficient of variation (CV)4.155804
Kurtosis150.0796
Mean3.2895828
Median Absolute Deviation (MAD)0
Skewness9.3760123
Sum13484
Variance186.89245
MonotonicityNot monotonic
2024-04-17T06:49:53.987049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3487
34.9%
1 49
 
0.5%
2 41
 
0.4%
3 32
 
0.3%
6 29
 
0.3%
4 28
 
0.3%
9 24
 
0.2%
7 24
 
0.2%
5 20
 
0.2%
8 19
 
0.2%
Other values (81) 346
 
3.5%
(Missing) 5901
59.0%
ValueCountFrequency (%)
0 3487
34.9%
1 49
 
0.5%
2 41
 
0.4%
3 32
 
0.3%
4 28
 
0.3%
5 20
 
0.2%
6 29
 
0.3%
7 24
 
0.2%
8 19
 
0.2%
9 24
 
0.2%
ValueCountFrequency (%)
345 1
< 0.1%
250 1
< 0.1%
185 1
< 0.1%
149 1
< 0.1%
146 1
< 0.1%
133 1
< 0.1%
124 1
< 0.1%
122 2
< 0.1%
115 1
< 0.1%
104 1
< 0.1%

qutnownernum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

joriwontoilar
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)100.0%
Missing9984
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean40.2475
Minimum6.5
Maximum112.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:54.083946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile6.575
Q118.235
median33
Q359
95-th percentile100.86
Maximum112.74
Range106.24
Interquartile range (IQR)40.765

Descriptive statistics

Standard deviation31.687568
Coefficient of variation (CV)0.78731767
Kurtosis0.54102212
Mean40.2475
Median Absolute Deviation (MAD)19.3
Skewness1.1174851
Sum643.96
Variance1004.102
MonotonicityNot monotonic
2024-04-17T06:49:54.176977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
37.8 1
 
< 0.1%
37.0 1
 
< 0.1%
15.1 1
 
< 0.1%
6.5 1
 
< 0.1%
68.0 1
 
< 0.1%
6.6 1
 
< 0.1%
112.74 1
 
< 0.1%
12.3 1
 
< 0.1%
32.6 1
 
< 0.1%
65.0 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 9984
99.8%
ValueCountFrequency (%)
6.5 1
< 0.1%
6.6 1
< 0.1%
12.3 1
< 0.1%
15.1 1
< 0.1%
19.28 1
< 0.1%
19.44 1
< 0.1%
24.3 1
< 0.1%
32.6 1
< 0.1%
33.4 1
< 0.1%
37.0 1
< 0.1%
ValueCountFrequency (%)
112.74 1
< 0.1%
96.9 1
< 0.1%
68.0 1
< 0.1%
65.0 1
< 0.1%
57.0 1
< 0.1%
37.8 1
< 0.1%
37.0 1
< 0.1%
33.4 1
< 0.1%
32.6 1
< 0.1%
24.3 1
< 0.1%

epcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

jisgnumlay
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)63.6%
Missing9978
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean50.681818
Minimum2
Maximum891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:54.258779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.25
median7
Q39.75
95-th percentile75.25
Maximum891
Range889
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation188.36853
Coefficient of variation (CV)3.7166885
Kurtosis21.634786
Mean50.681818
Median Absolute Deviation (MAD)3.5
Skewness4.637061
Sum1115
Variance35482.703
MonotonicityNot monotonic
2024-04-17T06:49:54.336335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 4
 
< 0.1%
7 3
 
< 0.1%
9 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
12 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 9978
99.8%
ValueCountFrequency (%)
2 4
< 0.1%
3 2
< 0.1%
4 1
 
< 0.1%
5 2
< 0.1%
6 1
 
< 0.1%
7 3
< 0.1%
8 1
 
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
891 1
 
< 0.1%
78 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
9 2
< 0.1%
8 1
 
< 0.1%
7 3
< 0.1%
6 1
 
< 0.1%

asgnymd
Real number (ℝ)

MISSING 

Distinct2008
Distinct (%)76.9%
Missing7388
Missing (%)73.9%
Infinite0
Infinite (%)0.0%
Mean20045166
Minimum19610316
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:54.430406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19610316
5-th percentile19780318
Q120001210
median20080766
Q320130105
95-th percentile20170603
Maximum20180903
Range570587
Interquartile range (IQR)128894.5

Descriptive statistics

Standard deviation116718.22
Coefficient of variation (CV)0.0058227616
Kurtosis1.4377006
Mean20045166
Median Absolute Deviation (MAD)59456
Skewness-1.3956315
Sum5.2357974 × 1010
Variance1.3623144 × 1010
MonotonicityNot monotonic
2024-04-17T06:49:54.795001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110502 8
 
0.1%
20090302 8
 
0.1%
20070702 7
 
0.1%
19660301 7
 
0.1%
20180702 6
 
0.1%
20080901 6
 
0.1%
20150302 6
 
0.1%
20080102 6
 
0.1%
20130701 6
 
0.1%
20160302 6
 
0.1%
Other values (1998) 2546
 
25.5%
(Missing) 7388
73.9%
ValueCountFrequency (%)
19610316 1
 
< 0.1%
19610418 1
 
< 0.1%
19620928 1
 
< 0.1%
19630207 1
 
< 0.1%
19630703 1
 
< 0.1%
19630822 1
 
< 0.1%
19660301 7
0.1%
19660415 1
 
< 0.1%
19660521 1
 
< 0.1%
19660920 3
< 0.1%
ValueCountFrequency (%)
20180903 5
0.1%
20180901 1
 
< 0.1%
20180827 1
 
< 0.1%
20180821 3
< 0.1%
20180813 1
 
< 0.1%
20180809 1
 
< 0.1%
20180731 1
 
< 0.1%
20180730 3
< 0.1%
20180723 2
 
< 0.1%
20180710 1
 
< 0.1%

asgncancelymd
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)53.9%
Missing9625
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean20165611
Minimum20081220
Maximum20180904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:54.907910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081220
5-th percentile20110621
Q120151212
median20180423
Q320180724
95-th percentile20180827
Maximum20180904
Range99684
Interquartile range (IQR)29512

Descriptive statistics

Standard deviation24742.181
Coefficient of variation (CV)0.0012269492
Kurtosis1.5057363
Mean20165611
Median Absolute Deviation (MAD)397
Skewness-1.6201184
Sum7.5621043 × 109
Variance6.1217553 × 108
MonotonicityNot monotonic
2024-04-17T06:49:55.022611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905 28
 
0.3%
20180808 13
 
0.1%
20180724 10
 
0.1%
20180810 10
 
0.1%
20180831 9
 
0.1%
20180614 7
 
0.1%
20180821 7
 
0.1%
20180626 6
 
0.1%
20180813 6
 
0.1%
20180823 5
 
0.1%
Other values (192) 274
 
2.7%
(Missing) 9625
96.2%
ValueCountFrequency (%)
20081220 1
< 0.1%
20081231 1
< 0.1%
20090219 1
< 0.1%
20090305 1
< 0.1%
20090514 1
< 0.1%
20091126 2
< 0.1%
20091231 1
< 0.1%
20100128 1
< 0.1%
20100322 1
< 0.1%
20100323 1
< 0.1%
ValueCountFrequency (%)
20180904 2
 
< 0.1%
20180903 1
 
< 0.1%
20180831 9
0.1%
20180830 3
 
< 0.1%
20180829 3
 
< 0.1%
20180828 1
 
< 0.1%
20180827 2
 
< 0.1%
20180824 4
< 0.1%
20180823 5
0.1%
20180822 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9992 
0
 
4
2
 
3
1
 
1

Length

Max length4
Median length4
Mean length3.9976
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> 9992
99.9%
0 4
 
< 0.1%
2 3
 
< 0.1%
1 1
 
< 0.1%

Length

2024-04-17T06:49:55.137442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:55.217990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9992
99.9%
0 4
 
< 0.1%
2 3
 
< 0.1%
1 1
 
< 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 

Distinct2746
Distinct (%)67.0%
Missing5901
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean982.16526
Minimum0
Maximum1384945
Zeros622
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:55.304591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q185.835
median155.45
Q3276.865
95-th percentile2180.986
Maximum1384945
Range1384945
Interquartile range (IQR)191.03

Descriptive statistics

Standard deviation22075.792
Coefficient of variation (CV)22.476657
Kurtosis3773.1629
Mean982.16526
Median Absolute Deviation (MAD)87.49
Skewness60.36514
Sum4025895.4
Variance4.8734058 × 108
MonotonicityNot monotonic
2024-04-17T06:49:55.417849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 622
 
6.2%
1.0 88
 
0.9%
120.0 44
 
0.4%
100.0 13
 
0.1%
99.0 10
 
0.1%
132.0 7
 
0.1%
150.0 7
 
0.1%
165.0 7
 
0.1%
177.0 7
 
0.1%
183.06 6
 
0.1%
Other values (2736) 3288
32.9%
(Missing) 5901
59.0%
ValueCountFrequency (%)
0.0 622
6.2%
1.0 88
 
0.9%
10.0 2
 
< 0.1%
15.4 1
 
< 0.1%
20.0 1
 
< 0.1%
23.5 1
 
< 0.1%
26.4 1
 
< 0.1%
27.0 1
 
< 0.1%
28.5 1
 
< 0.1%
29.04 1
 
< 0.1%
ValueCountFrequency (%)
1384945.0 1
< 0.1%
168117.0 1
< 0.1%
135500.53 1
< 0.1%
113599.96 1
< 0.1%
59501.6 1
< 0.1%
56670.14 1
< 0.1%
51976.15 1
< 0.1%
44373.31 1
< 0.1%
41017.69 1
< 0.1%
29074.67 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 

Distinct6
Distinct (%)40.0%
Missing9985
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1.8666667
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:55.522146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q11
median1
Q32.5
95-th percentile4.3
Maximum5
Range5
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.3557637
Coefficient of variation (CV)0.72630199
Kurtosis0.67023999
Mean1.8666667
Median Absolute Deviation (MAD)1
Skewness1.0691992
Sum28
Variance1.8380952
MonotonicityNot monotonic
2024-04-17T06:49:55.610115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
0.1%
2 3
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 9985
99.9%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 7
0.1%
2 3
< 0.1%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 1
 
< 0.1%
3 2
 
< 0.1%
2 3
< 0.1%
1 7
0.1%
0 1
 
< 0.1%

storetrdar
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct351
Distinct (%)7.0%
Missing5012
Missing (%)50.1%
Infinite0
Infinite (%)0.0%
Mean19.581077
Minimum0
Maximum4038
Zeros3702
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:49:55.719747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q327.4625
95-th percentile99
Maximum4038
Range4038
Interquartile range (IQR)27.4625

Descriptive statistics

Standard deviation68.213854
Coefficient of variation (CV)3.4836621
Kurtosis2417.6077
Mean19.581077
Median Absolute Deviation (MAD)0
Skewness41.554104
Sum97670.41
Variance4653.1298
MonotonicityNot monotonic
2024-04-17T06:49:55.831419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3702
37.0%
66.0 118
 
1.2%
49.5 106
 
1.1%
99.0 49
 
0.5%
82.5 44
 
0.4%
33.0 29
 
0.3%
59.4 26
 
0.3%
60.0 23
 
0.2%
100.0 23
 
0.2%
39.6 21
 
0.2%
Other values (341) 847
 
8.5%
(Missing) 5012
50.1%
ValueCountFrequency (%)
0.0 3702
37.0%
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 (%)
4038.0 1
< 0.1%
624.0 1
< 0.1%
605.15 1
< 0.1%
277.27 1
< 0.1%
230.0 2
< 0.1%
214.8 1
< 0.1%
208.31 1
< 0.1%
203.73 1
< 0.1%
203.0 1
< 0.1%
200.0 1
< 0.1%

pmtbednum
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9603 
0
 
397

Length

Max length4
Median length4
Mean length3.8809
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> 9603
96.0%
0 397
 
4.0%

Length

2024-04-17T06:49:55.951481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:56.033592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9603
96.0%
0 397
 
4.0%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-05-01 05:19:04
4215 
2021-05-01 05:19:06
3530 
2021-05-01 05:19:03
2073 
2021-05-01 05:19:05
 
182

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01 05:19:03
2nd row2021-05-01 05:19:04
3rd row2021-05-01 05:19:06
4th row2021-05-01 05:19:06
5th row2021-05-01 05:19:03

Common Values

ValueCountFrequency (%)
2021-05-01 05:19:04 4215
42.1%
2021-05-01 05:19:06 3530
35.3%
2021-05-01 05:19:03 2073
20.7%
2021-05-01 05:19:05 182
 
1.8%

Length

2024-04-17T06:49:56.128145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:49:56.206911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 10000
50.0%
05:19:04 4215
21.1%
05:19:06 3530
 
17.6%
05:19:03 2073
 
10.4%
05:19:05 182
 
0.9%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
173323053290000PHMA12012329002404110001101_01_02_PI2018-08-31 23:59:59.0<NA>박철보비뇨기과의원614876부산광역시 부산진구 부전2동 467번지 10호47257부산광역시 부산진구 가야대로 763-1 (부전동)20120305<NA><NA><NA><NA>13영업중387262.1208186548.04177920170905183852의원051-123-1234<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>221.36<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
468352523330000PHMA12012333002404110002301_01_02_PI2018-08-31 23:59:59.0<NA>최갑림치과의원612824부산광역시 해운대구 우동 1407번지 두산위브제니스 104동532호533호534호535호612824부산광역시 해운대구 마린시티2로 33, 104동 532~535호 (우동, 두산위브제니스)2012052420120909<NA><NA><NA>3폐업395542.647016186642.30676220150724091937치과의원051-123-1234<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>2021-05-01 05:19:04
11134116963390000PHMH32017339002308750003001_01_05_PI2018-08-31 23:59:59.0<NA>씨유 엄궁중앙점<NA><NA>47040부산광역시 사상구 엄궁북로 32-1, 1층 (엄궁동)20171128<NA><NA><NA><NA>13영업중379925.570362183102.97197920171128092916<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>70.0<NA>2021-05-01 05:19:06
11275118403400000PHMH32012340001308750000901_01_05_PI2018-08-31 23:59:59.0<NA>GS기장창기점619906부산광역시 기장군 기장읍 청강리 703번지 4호619906부산광역시 기장군 기장읍 대청로72번길 92012110720131128<NA><NA><NA>3폐업401825.863647195482.6644120140407155519<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>2021-05-01 05:19:06
256931383300000PHMA11985330002404110000501_01_02_PI2018-08-31 23:59:59.0<NA>신기영내과의원<NA>사직1동 47-2647859부산광역시 동래구 석사로 5 (사직동)1985102520170801<NA><NA><NA>3폐업387676.478191191013.27472120170731163316의원051-123-1234<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>0.0<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
625768343350000PHMA11977335002404110000301_01_02_PI2018-08-31 23:59:59.0<NA>삼화금사공장의무실609410부산광역시 금정구 금사동 80번지 1호<NA>부산광역시 금정구 공단서로8번길 53-4 (금사동)1977101819930519<NA><NA><NA>3폐업392519.200194193204.21962120090202173913의원051-123-1234<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>2021-05-01 05:19:04
10866114343380000PHMH32013338002308750002001_01_05_PI2018-08-31 23:59:59.0<NA>CU 민락태양점613827부산광역시 수영구 민락동 113번지 23호613827부산광역시 수영구 광안해변로294번길 3 (민락동)2013032820130723<NA><NA><NA>3폐업393722.454539186501.71200720140113141029<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>58.5<NA>2021-05-01 05:19:06
12496130543290000PHMD12014329002408400000801_01_06_PI2018-08-31 23:59:59.0<NA>삼한메디칼약국614850부산광역시 부산진구 부전동 522번지 4호47288부산광역시 부산진구 서면로 25, 105호 (부전동, 서면삼한골든뷰)20140409<NA><NA><NA><NA>13영업중387468.428999186001.50983820150706115230<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>47.15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20140409<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-05-01 05:19:06
142113163250000PHMA11985325002104110000101_01_02_PI2018-08-31 23:59:59.0<NA>대청치과의원<NA>부산광역시 중구 대청동 2가 17-348933부산광역시 중구 대청로 95-1 (대청동2가)19850206<NA><NA><NA><NA>13영업중385134.556205180413.93832620170905183855치과의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>치과의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
276833373300000PHMA12016330002404110000901_01_02_PI2018-08-31 23:59:59.0<NA>류마이지내과의원<NA>부산광역시 동래구 온천동 1440번지 1호 3층47824부산광역시 동래구 충렬대로 160, 3층 (온천동)20160321<NA><NA><NA><NA>13영업중389182.859746191745.67723120170905183852의원051-123-1234<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>321.45<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
12489130473290000PHMD12013329002408400002701_01_06_PI2018-08-31 23:59:59.0<NA>양정메디칼약국614853부산광역시 부산진구 양정동 369번지 6호47213부산광역시 부산진구 중앙대로 921 (양정동)20131216<NA><NA><NA><NA>13영업중388630.904763188194.96346620140730101533<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>64.96<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20131216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-05-01 05:19:06
704576163370000PHMA12003337002204110001201_01_02_PI2018-08-31 23:59:59.0<NA>7내과의원611822부산광역시 연제구 연산동 726번지 19호 디지탈빌딩 7층47520부산광역시 연제구 중앙대로 1112, 7층 (연산동)20030407<NA><NA><NA><NA>13영업중389618.14644189806.3832820170905183853의원051-123-1234<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>217.86<NA><NA><NA>0.0<NA>2021-05-01 05:19:04
532658953340000PHMA12016334002504110000801_01_02_PI2018-08-31 23:59:59.0<NA>행복한예일치과의원<NA>부산광역시 사하구 다대동 86번지 7호49515부산광역시 사하구 다송로 17, 2층 (다대동)20160715<NA><NA><NA><NA>13영업중380755.557417176196.25283520170905183851치과의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>치과의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>227.48<NA><NA><NA>0.0<NA>2021-05-01 05:19:04
272532943300000PHMA12000330002404110001001_01_02_PI2018-08-31 23:59:59.0<NA>부산치과의원607121부산광역시 동래구 사직1동 55-20607814부산광역시 동래구 사직북로28번길 113 (사직동)2000080820090827<NA><NA><NA>3폐업388013.123861191444.39994520120410134719치과의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>치과의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
911896913300000PHMH32013330002408750000301_01_05_PI2018-08-31 23:59:59.0<NA>CU 동래칠산점607030부산광역시 동래구 칠산동 211번지 1호47811부산광역시 동래구 명륜로112번길 115 (칠산동)20130925<NA><NA><NA><NA>13영업중390257.56287191564.67703120141118170823<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>2021-05-01 05:19:04
11374119413400000PHMH32015340001308750001001_01_05_PI2018-08-31 23:59:59.0<NA>GS25편의점(정관주민점)<NA><NA>46015부산광역시 기장군 정관면 정관로 4952015050120160330<NA><NA><NA>3폐업397381.527865205412.20591720160330181024<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>39.0<NA>2021-05-01 05:19:06
133812333250000PHMA12011325002104110000701_01_02_PI2018-08-31 23:59:59.0<NA>부산헬스케어의원600737부산광역시 중구 중앙동4가 88번지 7호 교보생명빌딩48939부산광역시 중구 충장대로 7 (중앙동4가)20110829<NA><NA><NA><NA>13영업중385751.519621180714.49609920170905183855의원051-123-1234<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>3<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>734.0<NA><NA><NA>0.0<NA>2021-05-01 05:19:03
825488273400000PHMA12016340001304110000501_01_02_PI2018-08-31 23:59:59.0<NA>부산아이정신건강의학과의원<NA>부산광역시 기장군 정관읍 매학리 713번지 2호46015부산광역시 기장군 정관읍 정관로 563, 5층 501호20160331<NA><NA><NA><NA>13영업중397844.635462204981.64080220170905183843의원051-123-1234<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>2021-05-01 05:19:04
585864293340000PHMA11990334002504110001301_01_02_PI2018-08-31 23:59:59.0<NA>박만희치과의원604020부산광역시 사하구 하단동 825번지 11호<NA><NA>1990102420021005<NA><NA><NA>3폐업<NA><NA>20130528101442치과의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>치과의원<NA>1<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>72.81<NA><NA><NA>0.0<NA>2021-05-01 05:19:04
124011343250000PHMA12003325002104110000101_01_02_PI2018-08-31 23:59:59.0<NA>김성균한의원<NA>부산광역시 중구 보수1동 83-248962부산광역시 중구 흑교로 50 (보수동1가)20030102<NA><NA><NA><NA>13영업중384647.326494180521.29762220171127150615한의원051-123-1234<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>94.5<NA><NA><NA>0.0<NA>2021-05-01 05:19:03