Overview

Dataset statistics

Number of variables70
Number of observations10000
Missing cells407451
Missing cells (%)58.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 MiB
Average record size in memory625.0 B

Variable types

Numeric35
Text5
Categorical15
Unsupported15

Alerts

opnsvcnm has constant value ""Constant
sitetel has constant value ""Constant
updategbn is highly imbalanced (97.8%)Imbalance
updatedt is highly imbalanced (98.8%)Imbalance
trdstatenm is highly imbalanced (55.8%)Imbalance
etcstfcnt is highly imbalanced (99.4%)Imbalance
nutrcnt is highly imbalanced (99.1%)Imbalance
metrorgassrnm is highly imbalanced (57.6%)Imbalance
undernumlay is highly imbalanced (99.2%)Imbalance
pmtbednum is highly imbalanced (78.1%)Imbalance
opnsvcnm has 9999 (> 99.9%) missing valuesMissing
sitepostno has 3322 (33.2%) missing valuesMissing
sitewhladdr has 882 (8.8%) missing valuesMissing
rdnpostno has 2149 (21.5%) missing valuesMissing
rdnwhladdr has 884 (8.8%) missing valuesMissing
dcbymd has 5820 (58.2%) missing valuesMissing
clgstdt has 9930 (99.3%) missing valuesMissing
clgenddt has 9929 (99.3%) missing valuesMissing
ropnymd has 10000 (100.0%) missing valuesMissing
x has 868 (8.7%) missing valuesMissing
y has 868 (8.7%) missing valuesMissing
nursecnt has 9972 (99.7%) missing valuesMissing
nursaidcnt has 9972 (99.7%) missing valuesMissing
bdnglayercnt has 9971 (99.7%) missing valuesMissing
rescnt has 10000 (100.0%) missing valuesMissing
pomfacilar has 9980 (99.8%) missing valuesMissing
etcepcnt has 10000 (100.0%) missing valuesMissing
mmknurmar has 9977 (99.8%) missing valuesMissing
btrmar has 9984 (99.8%) missing valuesMissing
btpnum has 9984 (99.8%) missing valuesMissing
sicbnum has 5966 (59.7%) missing valuesMissing
astnepnum has 10000 (100.0%) missing valuesMissing
ofear has 9980 (99.8%) missing valuesMissing
warmar has 9982 (99.8%) missing valuesMissing
facilmngnum has 10000 (100.0%) missing valuesMissing
pharmtrdar has 7322 (73.2%) missing valuesMissing
bbrmar has 9971 (99.7%) missing valuesMissing
babyrglstnum has 9968 (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 5966 (59.7%) missing valuesMissing
pgrmar has 9971 (99.7%) missing valuesMissing
pwnmrglstnum has 9968 (99.7%) missing valuesMissing
hstrmnum has 5966 (59.7%) missing valuesMissing
qutnownernum has 10000 (100.0%) missing valuesMissing
joriwontoilar has 9979 (99.8%) missing valuesMissing
epcnt has 10000 (100.0%) missing valuesMissing
jisgnumlay has 9976 (99.8%) missing valuesMissing
asgnymd has 7320 (73.2%) missing valuesMissing
asgncancelymd has 9666 (96.7%) missing valuesMissing
medextritemscn has 10000 (100.0%) missing valuesMissing
medextritemscnnm has 10000 (100.0%) missing valuesMissing
totar has 5966 (59.7%) missing valuesMissing
totepnum has 10000 (100.0%) missing valuesMissing
frstasgnymd has 10000 (100.0%) missing valuesMissing
copnum has 9982 (99.8%) missing valuesMissing
storetrdar has 5011 (50.1%) missing valuesMissing
dcbymd is highly skewed (γ1 = -59.11267843)Skewed
metrpnum is highly skewed (γ1 = 28.22486866)Skewed
totar is highly skewed (γ1 = 59.15483372)Skewed
storetrdar is highly skewed (γ1 = 42.67986225)Skewed
skey has unique valuesUnique
mgtno has unique valuesUnique
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 3409 (34.1%) zerosZeros
pharmtrdar has 294 (2.9%) zerosZeros
hstrmnum has 3448 (34.5%) zerosZeros
totar has 598 (6.0%) zerosZeros
storetrdar has 3684 (36.8%) zerosZeros

Reproduction

Analysis started2024-04-16 21:50:20.512207
Analysis finished2024-04-16 21:50:22.479589
Duration1.97 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%
Mean8384.9123
Minimum562
Maximum16076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:22.532144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum562
5-th percentile1363.9
Q14501.75
median8430.5
Q312247.25
95-th percentile15317.05
Maximum16076
Range15514
Interquartile range (IQR)7745.5

Descriptive statistics

Standard deviation4474.9574
Coefficient of variation (CV)0.53369162
Kurtosis-1.1987455
Mean8384.9123
Median Absolute Deviation (MAD)3877
Skewness-0.015104456
Sum83849123
Variance20025244
MonotonicityNot monotonic
2024-04-17T06:50:22.637738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9909 1
 
< 0.1%
13556 1
 
< 0.1%
8347 1
 
< 0.1%
14838 1
 
< 0.1%
5076 1
 
< 0.1%
1964 1
 
< 0.1%
1394 1
 
< 0.1%
11235 1
 
< 0.1%
13047 1
 
< 0.1%
9604 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
562 1
< 0.1%
563 1
< 0.1%
564 1
< 0.1%
565 1
< 0.1%
567 1
< 0.1%
568 1
< 0.1%
569 1
< 0.1%
572 1
< 0.1%
573 1
< 0.1%
575 1
< 0.1%
ValueCountFrequency (%)
16076 1
< 0.1%
16075 1
< 0.1%
16074 1
< 0.1%
16073 1
< 0.1%
16071 1
< 0.1%
16070 1
< 0.1%
16069 1
< 0.1%
16067 1
< 0.1%
16063 1
< 0.1%
16062 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326471
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:22.736082image/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 deviation38863.186
Coefficient of variation (CV)0.011683007
Kurtosis-0.78561821
Mean3326471
Median Absolute Deviation (MAD)30000
Skewness0.0085327599
Sum3.326471 × 1010
Variance1.5103472 × 109
MonotonicityNot monotonic
2024-04-17T06:50:22.824839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 1284
12.8%
3350000 1171
11.7%
3330000 1082
10.8%
3340000 975
9.8%
3300000 760
7.6%
3310000 725
 
7.2%
3370000 594
 
5.9%
3320000 573
 
5.7%
3380000 561
 
5.6%
3390000 452
 
4.5%
Other values (6) 1823
18.2%
ValueCountFrequency (%)
3250000 319
 
3.2%
3260000 358
 
3.6%
3270000 332
 
3.3%
3280000 267
 
2.7%
3290000 1284
12.8%
3300000 760
7.6%
3310000 725
7.2%
3320000 573
5.7%
3330000 1082
10.8%
3340000 975
9.8%
ValueCountFrequency (%)
3400000 361
 
3.6%
3390000 452
 
4.5%
3380000 561
5.6%
3370000 594
5.9%
3360000 186
 
1.9%
3350000 1171
11.7%
3340000 975
9.8%
3330000 1082
10.8%
3320000 573
5.7%
3310000 725
7.2%

mgtno
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:23.002697image/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 rowPHMH320123310024087500062
2nd rowPHMA220163360024021200001
3rd rowPHMA119913260022041100011
4th rowPHMA120093320045041100017
5th rowPHMA120083290024041100046
ValueCountFrequency (%)
phmh320123310024087500062 1
 
< 0.1%
phmh320133360024087500005 1
 
< 0.1%
phmh320173330024087500032 1
 
< 0.1%
phma119913330024041100001 1
 
< 0.1%
phma119903380023041100005 1
 
< 0.1%
phmd119923350024084000013 1
 
< 0.1%
phma120143330024041100024 1
 
< 0.1%
phma120093280023041100003 1
 
< 0.1%
phma119863260022041100001 1
 
< 0.1%
phmd120143310024084000007 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T06:50:23.276771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81214
32.5%
1 31298
 
12.5%
2 26381
 
10.6%
3 24497
 
9.8%
4 16964
 
6.8%
H 11986
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7995
 
3.2%
5 7115
 
2.8%
Other values (6) 22550
 
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 81214
38.7%
1 31298
 
14.9%
2 26381
 
12.6%
3 24497
 
11.7%
4 16964
 
8.1%
8 7995
 
3.8%
5 7115
 
3.4%
9 6606
 
3.1%
7 5220
 
2.5%
6 2710
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
H 11986
30.0%
P 10000
25.0%
M 10000
25.0%
A 5302
13.3%
D 2680
 
6.7%
B 32
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 81214
38.7%
1 31298
 
14.9%
2 26381
 
12.6%
3 24497
 
11.7%
4 16964
 
8.1%
8 7995
 
3.8%
5 7115
 
3.4%
9 6606
 
3.1%
7 5220
 
2.5%
6 2710
 
1.3%
Latin
ValueCountFrequency (%)
H 11986
30.0%
P 10000
25.0%
M 10000
25.0%
A 5302
13.3%
D 2680
 
6.7%
B 32
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81214
32.5%
1 31298
 
12.5%
2 26381
 
10.6%
3 24497
 
9.8%
4 16964
 
6.8%
H 11986
 
4.8%
P 10000
 
4.0%
M 10000
 
4.0%
8 7995
 
3.2%
5 7115
 
2.8%
Other values (6) 22550
 
9.0%

opnsvcid
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
01_01_02_P
4952 
01_01_06_P
2680 
01_01_05_P
1986 
01_01_01_P
 
334
01_01_04_P
 
32

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_01_05_P
2nd row01_01_01_P
3rd row01_01_02_P
4th row01_01_02_P
5th row01_01_02_P

Common Values

ValueCountFrequency (%)
01_01_02_P 4952
49.5%
01_01_06_P 2680
26.8%
01_01_05_P 1986
19.9%
01_01_01_P 334
 
3.3%
01_01_04_P 32
 
0.3%
01_01_03_P 16
 
0.2%

Length

2024-04-17T06:50:23.388686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:23.467069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_01_02_p 4952
49.5%
01_01_06_p 2680
26.8%
01_01_05_p 1986
19.9%
01_01_01_p 334
 
3.3%
01_01_04_p 32
 
0.3%
01_01_03_p 16
 
0.2%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
9979 
U
 
21

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 9979
99.8%
U 21
 
0.2%

Length

2024-04-17T06:50:23.557649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:23.627585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9979
99.8%
u 21
 
0.2%

updatedt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-08-31 23:59:59.0
9974 
2018-09-06 11:42:31.0
 
13
2018-09-06 11:42:33.0
 
6
2018-09-06 11:42:32.0
 
4
2018-09-06 11:42:30.0
 
2

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique1 ?
Unique (%)< 0.1%

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 9974
99.7%
2018-09-06 11:42:31.0 13
 
0.1%
2018-09-06 11:42:33.0 6
 
0.1%
2018-09-06 11:42:32.0 4
 
< 0.1%
2018-09-06 11:42:30.0 2
 
< 0.1%
2018-10-18 02:35:26.0 1
 
< 0.1%

Length

2024-04-17T06:50:23.697715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:23.774461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 9974
49.9%
23:59:59.0 9974
49.9%
2018-09-06 25
 
0.1%
11:42:31.0 13
 
0.1%
11:42:33.0 6
 
< 0.1%
11:42:32.0 4
 
< 0.1%
11:42:30.0 2
 
< 0.1%
2018-10-18 1
 
< 0.1%
02:35:26.0 1
 
< 0.1%

opnsvcnm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T06:50:23.878024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row안전상비의약품 판매업소
ValueCountFrequency (%)
안전상비의약품 1
50.0%
판매업소 1
50.0%
2024-04-17T06:50:24.076355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
91.7%
Space Separator 1
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
91.7%
Common 1
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
91.7%
ASCII 1
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
ASCII
ValueCountFrequency (%)
1
100.0%

bplcnm
Text

Distinct7770
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T06:50:24.304101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length7.2929
Min length2

Characters and Unicode

Total characters72929
Distinct characters687
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

Unique6718 ?
Unique (%)67.2%

Sample

1st row씨유 대연동천점
2nd row명지아동병원
3rd row동선한의원
4th row서울플란트치과의원
5th row효정의료소비자협동조합효림의원
ValueCountFrequency (%)
gs25 276
 
2.3%
씨유 240
 
2.0%
세븐일레븐 191
 
1.6%
미니스톱 113
 
1.0%
cu 86
 
0.7%
약국 65
 
0.5%
주)코리아세븐 59
 
0.5%
한의원 56
 
0.5%
의원 51
 
0.4%
치과의원 49
 
0.4%
Other values (7927) 10666
90.0%
2024-04-17T06:50:24.650160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5609
 
7.7%
5517
 
7.6%
2891
 
4.0%
2749
 
3.8%
2689
 
3.7%
1890
 
2.6%
1862
 
2.6%
1745
 
2.4%
1200
 
1.6%
1091
 
1.5%
Other values (677) 45686
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67316
92.3%
Space Separator 1862
 
2.6%
Uppercase Letter 1625
 
2.2%
Decimal Number 1487
 
2.0%
Close Punctuation 276
 
0.4%
Open Punctuation 260
 
0.4%
Lowercase Letter 61
 
0.1%
Other Punctuation 34
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5609
 
8.3%
5517
 
8.2%
2891
 
4.3%
2749
 
4.1%
2689
 
4.0%
1890
 
2.8%
1745
 
2.6%
1200
 
1.8%
1091
 
1.6%
1056
 
1.6%
Other values (617) 40879
60.7%
Uppercase Letter
ValueCountFrequency (%)
S 619
38.1%
G 578
35.6%
C 145
 
8.9%
U 137
 
8.4%
K 35
 
2.2%
B 19
 
1.2%
L 14
 
0.9%
H 10
 
0.6%
M 10
 
0.6%
N 8
 
0.5%
Other values (14) 50
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
e 31
50.8%
h 6
 
9.8%
i 5
 
8.2%
u 2
 
3.3%
c 2
 
3.3%
r 2
 
3.3%
m 2
 
3.3%
a 2
 
3.3%
l 2
 
3.3%
d 1
 
1.6%
Other values (6) 6
 
9.8%
Decimal Number
ValueCountFrequency (%)
2 711
47.8%
5 639
43.0%
4 46
 
3.1%
1 38
 
2.6%
3 27
 
1.8%
0 11
 
0.7%
6 8
 
0.5%
7 3
 
0.2%
8 2
 
0.1%
9 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 13
38.2%
& 9
26.5%
· 8
23.5%
, 3
 
8.8%
@ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1862
100.0%
Close Punctuation
ValueCountFrequency (%)
) 276
100.0%
Open Punctuation
ValueCountFrequency (%)
( 260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67310
92.3%
Common 3924
 
5.4%
Latin 1686
 
2.3%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5609
 
8.3%
5517
 
8.2%
2891
 
4.3%
2749
 
4.1%
2689
 
4.0%
1890
 
2.8%
1745
 
2.6%
1200
 
1.8%
1091
 
1.6%
1056
 
1.6%
Other values (611) 40873
60.7%
Latin
ValueCountFrequency (%)
S 619
36.7%
G 578
34.3%
C 145
 
8.6%
U 137
 
8.1%
K 35
 
2.1%
e 31
 
1.8%
B 19
 
1.1%
L 14
 
0.8%
H 10
 
0.6%
M 10
 
0.6%
Other values (30) 88
 
5.2%
Common
ValueCountFrequency (%)
1862
47.5%
2 711
 
18.1%
5 639
 
16.3%
) 276
 
7.0%
( 260
 
6.6%
4 46
 
1.2%
1 38
 
1.0%
3 27
 
0.7%
. 13
 
0.3%
0 11
 
0.3%
Other values (9) 41
 
1.0%
Han
ValueCountFrequency (%)
3
33.3%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67306
92.3%
ASCII 5602
 
7.7%
None 11
 
< 0.1%
CJK 9
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5609
 
8.3%
5517
 
8.2%
2891
 
4.3%
2749
 
4.1%
2689
 
4.0%
1890
 
2.8%
1745
 
2.6%
1200
 
1.8%
1091
 
1.6%
1056
 
1.6%
Other values (609) 40869
60.7%
ASCII
ValueCountFrequency (%)
1862
33.2%
2 711
 
12.7%
5 639
 
11.4%
S 619
 
11.0%
G 578
 
10.3%
) 276
 
4.9%
( 260
 
4.6%
C 145
 
2.6%
U 137
 
2.4%
4 46
 
0.8%
Other values (48) 329
 
5.9%
None
ValueCountFrequency (%)
· 8
72.7%
3
 
27.3%
CJK
ValueCountFrequency (%)
3
33.3%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%
1
 
11.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

sitepostno
Real number (ℝ)

MISSING 

Distinct935
Distinct (%)14.0%
Missing3322
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean608865.53
Minimum607
Maximum621070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:24.768648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum607
5-th percentile601823
Q1607824
median611072
Q3614031
95-th percentile617816
Maximum621070
Range620463
Interquartile range (IQR)6207

Descriptive statistics

Standard deviation32162.808
Coefficient of variation (CV)0.052824157
Kurtosis317.95206
Mean608865.53
Median Absolute Deviation (MAD)3240
Skewness-17.666658
Sum4.066004 × 109
Variance1.0344462 × 109
MonotonicityNot monotonic
2024-04-17T06:50:24.883946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609310 107
 
1.1%
609400 93
 
0.9%
609320 90
 
0.9%
614847 69
 
0.7%
609390 69
 
0.7%
616852 58
 
0.6%
614849 51
 
0.5%
601812 49
 
0.5%
619963 46
 
0.5%
612842 45
 
0.4%
Other values (925) 6001
60.0%
(Missing) 3322
33.2%
ValueCountFrequency (%)
607 9
0.1%
46067 1
 
< 0.1%
46217 1
 
< 0.1%
46235 1
 
< 0.1%
46243 1
 
< 0.1%
46249 1
 
< 0.1%
46957 1
 
< 0.1%
46988 1
 
< 0.1%
48024 1
 
< 0.1%
48059 1
 
< 0.1%
ValueCountFrequency (%)
621070 1
 
< 0.1%
619963 46
0.5%
619962 12
 
0.1%
619961 4
 
< 0.1%
619953 7
 
0.1%
619952 5
 
0.1%
619951 5
 
0.1%
619913 1
 
< 0.1%
619912 7
 
0.1%
619911 3
 
< 0.1%

sitewhladdr
Text

MISSING 

Distinct7555
Distinct (%)82.9%
Missing882
Missing (%)8.8%
Memory size156.2 KiB
2024-04-17T06:50:25.156874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length53
Mean length23.957556
Min length2

Characters and Unicode

Total characters218445
Distinct characters468
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6522 ?
Unique (%)71.5%

Sample

1st row부산광역시 남구 대연동 1505번지 1호
2nd row부산광역시 강서구 명지동 3412번지 4호 402,501,601호(국제메디칼빌딩)
3rd row부산광역시 서구 암남동 288-5
4th row부산광역시 북구 덕천2동 398번지 13호 8층
5th row부산광역시 부산진구 가야동 602번지 7호
ValueCountFrequency (%)
부산광역시 8891
 
19.3%
부산진구 1180
 
2.6%
금정구 1160
 
2.5%
1호 1076
 
2.3%
사하구 929
 
2.0%
해운대구 919
 
2.0%
동래구 662
 
1.4%
남구 657
 
1.4%
연제구 538
 
1.2%
수영구 510
 
1.1%
Other values (4970) 29551
64.1%
2024-04-17T06:50:25.573047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37073
 
17.0%
11180
 
5.1%
1 11001
 
5.0%
10864
 
5.0%
10191
 
4.7%
9265
 
4.2%
9122
 
4.2%
9046
 
4.1%
8974
 
4.1%
7570
 
3.5%
Other values (458) 94159
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130619
59.8%
Decimal Number 47461
 
21.7%
Space Separator 37073
 
17.0%
Dash Punctuation 1712
 
0.8%
Other Punctuation 511
 
0.2%
Open Punctuation 370
 
0.2%
Close Punctuation 368
 
0.2%
Uppercase Letter 237
 
0.1%
Math Symbol 59
 
< 0.1%
Lowercase Letter 32
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11180
 
8.6%
10864
 
8.3%
10191
 
7.8%
9265
 
7.1%
9122
 
7.0%
9046
 
6.9%
8974
 
6.9%
7570
 
5.8%
7430
 
5.7%
7252
 
5.6%
Other values (395) 39725
30.4%
Uppercase Letter
ValueCountFrequency (%)
A 41
17.3%
B 36
15.2%
S 21
 
8.9%
K 17
 
7.2%
F 15
 
6.3%
G 15
 
6.3%
L 12
 
5.1%
C 11
 
4.6%
E 8
 
3.4%
D 8
 
3.4%
Other values (15) 53
22.4%
Lowercase Letter
ValueCountFrequency (%)
s 7
21.9%
e 6
18.8%
i 4
12.5%
a 3
9.4%
u 2
 
6.2%
l 2
 
6.2%
k 2
 
6.2%
p 1
 
3.1%
c 1
 
3.1%
v 1
 
3.1%
Other values (3) 3
9.4%
Decimal Number
ValueCountFrequency (%)
1 11001
23.2%
2 7314
15.4%
3 5515
11.6%
4 4520
9.5%
5 3936
 
8.3%
0 3294
 
6.9%
6 3234
 
6.8%
7 3227
 
6.8%
8 2818
 
5.9%
9 2602
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 462
90.4%
@ 22
 
4.3%
. 14
 
2.7%
/ 8
 
1.6%
· 5
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 369
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 367
99.7%
] 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 57
96.6%
2
 
3.4%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
37073
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1712
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130619
59.8%
Common 87554
40.1%
Latin 272
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11180
 
8.6%
10864
 
8.3%
10191
 
7.8%
9265
 
7.1%
9122
 
7.0%
9046
 
6.9%
8974
 
6.9%
7570
 
5.8%
7430
 
5.7%
7252
 
5.6%
Other values (395) 39725
30.4%
Latin
ValueCountFrequency (%)
A 41
15.1%
B 36
13.2%
S 21
 
7.7%
K 17
 
6.2%
F 15
 
5.5%
G 15
 
5.5%
L 12
 
4.4%
C 11
 
4.0%
E 8
 
2.9%
D 8
 
2.9%
Other values (30) 88
32.4%
Common
ValueCountFrequency (%)
37073
42.3%
1 11001
 
12.6%
2 7314
 
8.4%
3 5515
 
6.3%
4 4520
 
5.2%
5 3936
 
4.5%
0 3294
 
3.8%
6 3234
 
3.7%
7 3227
 
3.7%
8 2818
 
3.2%
Other values (13) 5622
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130616
59.8%
ASCII 87816
40.2%
None 5
 
< 0.1%
Number Forms 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37073
42.2%
1 11001
 
12.5%
2 7314
 
8.3%
3 5515
 
6.3%
4 4520
 
5.1%
5 3936
 
4.5%
0 3294
 
3.8%
6 3234
 
3.7%
7 3227
 
3.7%
8 2818
 
3.2%
Other values (49) 5884
 
6.7%
Hangul
ValueCountFrequency (%)
11180
 
8.6%
10864
 
8.3%
10191
 
7.8%
9265
 
7.1%
9122
 
7.0%
9046
 
6.9%
8974
 
6.9%
7570
 
5.8%
7430
 
5.7%
7252
 
5.6%
Other values (392) 39722
30.4%
None
ValueCountFrequency (%)
· 5
100.0%
Math Operators
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1882
Distinct (%)24.0%
Missing2149
Missing (%)21.5%
Infinite0
Infinite (%)0.0%
Mean140276.94
Minimum46002
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:25.686679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46231
Q147251
median48078
Q349234.5
95-th percentile614812
Maximum619963
Range573961
Interquartile range (IQR)1983.5

Descriptive statistics

Standard deviation208689.94
Coefficient of variation (CV)1.4876995
Kurtosis1.2910233
Mean140276.94
Median Absolute Deviation (MAD)945
Skewness1.8137248
Sum1.1013143 × 109
Variance4.355149 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:25.785481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47257 64
 
0.6%
48060 62
 
0.6%
47286 60
 
0.6%
48095 56
 
0.6%
46526 47
 
0.5%
46015 46
 
0.5%
46576 42
 
0.4%
47287 36
 
0.4%
47520 35
 
0.4%
46243 34
 
0.3%
Other values (1872) 7369
73.7%
(Missing) 2149
 
21.5%
ValueCountFrequency (%)
46002 4
 
< 0.1%
46007 5
 
0.1%
46008 17
 
0.2%
46010 1
 
< 0.1%
46012 5
 
0.1%
46013 5
 
0.1%
46014 2
 
< 0.1%
46015 46
0.5%
46016 2
 
< 0.1%
46017 9
 
0.1%
ValueCountFrequency (%)
619963 21
0.2%
619962 4
 
< 0.1%
619961 3
 
< 0.1%
619953 2
 
< 0.1%
619952 4
 
< 0.1%
619951 2
 
< 0.1%
619950 1
 
< 0.1%
619913 2
 
< 0.1%
619912 6
 
0.1%
619911 2
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct7440
Distinct (%)81.6%
Missing884
Missing (%)8.8%
Memory size156.2 KiB
2024-04-17T06:50:26.078689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length58
Mean length28.280935
Min length13

Characters and Unicode

Total characters257809
Distinct characters534
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6322 ?
Unique (%)69.4%

Sample

1st row부산광역시 남구 못골번영로 47, 102호 (대연동)
2nd row부산광역시 강서구 명지국제8로 240, 402,501,601호 (명지동, 국제메디칼빌딩)
3rd row부산광역시 서구 충무대로 37-1 (암남동)
4th row부산광역시 북구 만덕대로 21 (덕천동)
5th row부산광역시 부산진구 가야공원로 44 (가야동)
ValueCountFrequency (%)
부산광역시 9115
 
17.7%
부산진구 1160
 
2.3%
금정구 1057
 
2.1%
해운대구 977
 
1.9%
사하구 844
 
1.6%
동래구 733
 
1.4%
연제구 567
 
1.1%
2층 552
 
1.1%
북구 550
 
1.1%
중앙대로 549
 
1.1%
Other values (5016) 35445
68.8%
2024-04-17T06:50:26.701573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42452
 
16.5%
11514
 
4.5%
11435
 
4.4%
11180
 
4.3%
9647
 
3.7%
9509
 
3.7%
9394
 
3.6%
9120
 
3.5%
9071
 
3.5%
) 8922
 
3.5%
Other values (524) 125565
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153352
59.5%
Space Separator 42452
 
16.5%
Decimal Number 37103
 
14.4%
Close Punctuation 8922
 
3.5%
Open Punctuation 8921
 
3.5%
Other Punctuation 5516
 
2.1%
Dash Punctuation 1034
 
0.4%
Uppercase Letter 343
 
0.1%
Math Symbol 124
 
< 0.1%
Lowercase Letter 37
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11514
 
7.5%
11435
 
7.5%
11180
 
7.3%
9647
 
6.3%
9509
 
6.2%
9394
 
6.1%
9120
 
5.9%
9071
 
5.9%
4897
 
3.2%
2593
 
1.7%
Other values (465) 64992
42.4%
Uppercase Letter
ValueCountFrequency (%)
B 60
17.5%
A 44
12.8%
S 36
10.5%
C 27
 
7.9%
K 24
 
7.0%
E 19
 
5.5%
G 17
 
5.0%
I 13
 
3.8%
L 12
 
3.5%
D 11
 
3.2%
Other values (14) 80
23.3%
Lowercase Letter
ValueCountFrequency (%)
e 13
35.1%
s 5
 
13.5%
i 4
 
10.8%
a 3
 
8.1%
r 2
 
5.4%
o 2
 
5.4%
c 1
 
2.7%
v 1
 
2.7%
l 1
 
2.7%
k 1
 
2.7%
Other values (4) 4
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 8424
22.7%
2 5723
15.4%
3 4086
11.0%
4 3449
9.3%
0 3420
9.2%
5 2876
 
7.8%
7 2507
 
6.8%
6 2454
 
6.6%
9 2115
 
5.7%
8 2049
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 5483
99.4%
. 17
 
0.3%
· 7
 
0.1%
@ 6
 
0.1%
/ 3
 
0.1%
Space Separator
ValueCountFrequency (%)
42452
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8922
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8921
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1034
100.0%
Math Symbol
ValueCountFrequency (%)
~ 124
100.0%
Letter Number
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153352
59.5%
Common 104072
40.4%
Latin 385
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11514
 
7.5%
11435
 
7.5%
11180
 
7.3%
9647
 
6.3%
9509
 
6.2%
9394
 
6.1%
9120
 
5.9%
9071
 
5.9%
4897
 
3.2%
2593
 
1.7%
Other values (465) 64992
42.4%
Latin
ValueCountFrequency (%)
B 60
15.6%
A 44
 
11.4%
S 36
 
9.4%
C 27
 
7.0%
K 24
 
6.2%
E 19
 
4.9%
G 17
 
4.4%
I 13
 
3.4%
e 13
 
3.4%
L 12
 
3.1%
Other values (29) 120
31.2%
Common
ValueCountFrequency (%)
42452
40.8%
) 8922
 
8.6%
( 8921
 
8.6%
1 8424
 
8.1%
2 5723
 
5.5%
, 5483
 
5.3%
3 4086
 
3.9%
4 3449
 
3.3%
0 3420
 
3.3%
5 2876
 
2.8%
Other values (10) 10316
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153352
59.5%
ASCII 104445
40.5%
None 7
 
< 0.1%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42452
40.6%
) 8922
 
8.5%
( 8921
 
8.5%
1 8424
 
8.1%
2 5723
 
5.5%
, 5483
 
5.2%
3 4086
 
3.9%
4 3449
 
3.3%
0 3420
 
3.3%
5 2876
 
2.8%
Other values (47) 10689
 
10.2%
Hangul
ValueCountFrequency (%)
11514
 
7.5%
11435
 
7.5%
11180
 
7.3%
9647
 
6.3%
9509
 
6.2%
9394
 
6.1%
9120
 
5.9%
9071
 
5.9%
4897
 
3.2%
2593
 
1.7%
Other values (465) 64992
42.4%
None
ValueCountFrequency (%)
· 7
100.0%
Number Forms
ValueCountFrequency (%)
5
100.0%

apvpermymd
Real number (ℝ)

Distinct5317
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20055436
Minimum19590207
Maximum20181016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:26.817448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19590207
5-th percentile19829671
Q120001116
median20090728
Q320140121
95-th percentile20171010
Maximum20181016
Range590809
Interquartile range (IQR)139005

Descriptive statistics

Standard deviation111679.05
Coefficient of variation (CV)0.0055685176
Kurtosis1.2769767
Mean20055436
Median Absolute Deviation (MAD)59992.5
Skewness-1.2951174
Sum2.0055436 × 1011
Variance1.2472211 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:26.929441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121112 125
 
1.2%
20121109 92
 
0.9%
20121114 82
 
0.8%
20121116 71
 
0.7%
20121115 70
 
0.7%
20121113 67
 
0.7%
20121108 40
 
0.4%
20121107 35
 
0.4%
20121110 18
 
0.2%
20121106 18
 
0.2%
Other values (5307) 9382
93.8%
ValueCountFrequency (%)
19590207 1
< 0.1%
19600101 1
< 0.1%
19610316 1
< 0.1%
19610418 1
< 0.1%
19620130 1
< 0.1%
19620310 1
< 0.1%
19620313 1
< 0.1%
19620503 1
< 0.1%
19620928 1
< 0.1%
19630101 1
< 0.1%
ValueCountFrequency (%)
20181016 1
 
< 0.1%
20180904 1
 
< 0.1%
20180903 3
< 0.1%
20180831 1
 
< 0.1%
20180830 5
0.1%
20180829 4
< 0.1%
20180828 2
 
< 0.1%
20180827 3
< 0.1%
20180822 5
0.1%
20180821 5
0.1%

dcbymd
Real number (ℝ)

MISSING  SKEWED 

Distinct2513
Distinct (%)60.1%
Missing5820
Missing (%)58.2%
Infinite0
Infinite (%)0.0%
Mean20097716
Minimum10101
Maximum20180904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:27.041929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile19920302
Q120090701
median20121119
Q320151006
95-th percentile20180308
Maximum20180904
Range20170803
Interquartile range (IQR)60304.75

Descriptive statistics

Standard deviation320234.17
Coefficient of variation (CV)0.015933859
Kurtosis3707.1877
Mean20097716
Median Absolute Deviation (MAD)30190.5
Skewness-59.112678
Sum8.4008451 × 1010
Variance1.0254992 × 1011
MonotonicityNot monotonic
2024-04-17T06:50:27.156721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140901 11
 
0.1%
20090302 10
 
0.1%
20100302 10
 
0.1%
20110502 9
 
0.1%
20161201 9
 
0.1%
20171229 9
 
0.1%
20130701 9
 
0.1%
20141231 9
 
0.1%
20091231 8
 
0.1%
20150501 8
 
0.1%
Other values (2503) 4088
40.9%
(Missing) 5820
58.2%
ValueCountFrequency (%)
10101 1
< 0.1%
19760520 1
< 0.1%
19770128 1
< 0.1%
19770415 1
< 0.1%
19770512 1
< 0.1%
19780331 1
< 0.1%
19781124 1
< 0.1%
19790214 1
< 0.1%
19790402 1
< 0.1%
19790731 1
< 0.1%
ValueCountFrequency (%)
20180904 1
 
< 0.1%
20180903 3
< 0.1%
20180901 2
< 0.1%
20180831 3
< 0.1%
20180830 2
< 0.1%
20180829 2
< 0.1%
20180827 3
< 0.1%
20180824 1
 
< 0.1%
20180823 1
 
< 0.1%
20180822 1
 
< 0.1%

clgstdt
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)98.6%
Missing9930
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20131216
Minimum20051001
Maximum20181001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:27.273942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20051001
5-th percentile20090157
Q120100930
median20120913
Q320170257
95-th percentile20180667
Maximum20181001
Range130000
Interquartile range (IQR)69326.5

Descriptive statistics

Standard deviation34754.754
Coefficient of variation (CV)0.001726411
Kurtosis-1.1836391
Mean20131216
Median Absolute Deviation (MAD)25251.5
Skewness0.14758995
Sum1.4091851 × 109
Variance1.2078929 × 109
MonotonicityNot monotonic
2024-04-17T06:50:27.387096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110706 2
 
< 0.1%
20140501 1
 
< 0.1%
20180703 1
 
< 0.1%
20160715 1
 
< 0.1%
20110811 1
 
< 0.1%
20090615 1
 
< 0.1%
20101019 1
 
< 0.1%
20131014 1
 
< 0.1%
20090824 1
 
< 0.1%
20100109 1
 
< 0.1%
Other values (59) 59
 
0.6%
(Missing) 9930
99.3%
ValueCountFrequency (%)
20051001 1
< 0.1%
20080801 1
< 0.1%
20081118 1
< 0.1%
20090120 1
< 0.1%
20090202 1
< 0.1%
20090225 1
< 0.1%
20090615 1
< 0.1%
20090824 1
< 0.1%
20090901 1
< 0.1%
20091130 1
< 0.1%
ValueCountFrequency (%)
20181001 1
< 0.1%
20180829 1
< 0.1%
20180703 1
< 0.1%
20180701 1
< 0.1%
20180626 1
< 0.1%
20180616 1
< 0.1%
20180603 1
< 0.1%
20180528 1
< 0.1%
20180420 1
< 0.1%
20180417 1
< 0.1%

clgenddt
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)91.5%
Missing9929
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean22387105
Minimum20080731
Maximum99991231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:27.502761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080731
5-th percentile20090816
Q120110470
median20131130
Q320175617
95-th percentile20190780
Maximum99991231
Range79910500
Interquartile range (IQR)65146.5

Descriptive statistics

Standard deviation13306278
Coefficient of variation (CV)0.59437244
Kurtosis32.882294
Mean22387105
Median Absolute Deviation (MAD)30609
Skewness5.8271947
Sum1.5894845 × 109
Variance1.7705704 × 1014
MonotonicityNot monotonic
2024-04-17T06:50:27.622681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131231 3
 
< 0.1%
20170131 2
 
< 0.1%
20121231 2
 
< 0.1%
20111205 2
 
< 0.1%
20170531 2
 
< 0.1%
20180630 1
 
< 0.1%
20090730 1
 
< 0.1%
20160731 1
 
< 0.1%
20111110 1
 
< 0.1%
20110331 1
 
< 0.1%
Other values (55) 55
 
0.5%
(Missing) 9929
99.3%
ValueCountFrequency (%)
20080731 1
< 0.1%
20090331 1
< 0.1%
20090518 1
< 0.1%
20090730 1
< 0.1%
20090901 1
< 0.1%
20091231 1
< 0.1%
20100224 1
< 0.1%
20100228 1
< 0.1%
20100331 1
< 0.1%
20100513 1
< 0.1%
ValueCountFrequency (%)
99991231 1
< 0.1%
99991111 1
< 0.1%
20221227 1
< 0.1%
20190930 1
< 0.1%
20190630 1
< 0.1%
20190602 1
< 0.1%
20190131 1
< 0.1%
20190102 1
< 0.1%
20181231 1
< 0.1%
20181228 1
< 0.1%

ropnymd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

trdstatenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
13
5675 
3
4281 
24
 
28
2
 
15
<NA>
 
1

Length

Max length4
Median length2
Mean length1.5706
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 5675
56.8%
3 4281
42.8%
24 28
 
0.3%
2 15
 
0.1%
<NA> 1
 
< 0.1%

Length

2024-04-17T06:50:27.736866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:27.817097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 5675
56.8%
3 4281
42.8%
24 28
 
0.3%
2 15
 
0.1%
na 1
 
< 0.1%

dtlstatenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
5676 
폐업
4281 
직권폐업
 
28
휴업
 
15

Length

Max length4
Median length3
Mean length2.5732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 5676
56.8%
폐업 4281
42.8%
직권폐업 28
 
0.3%
휴업 15
 
0.1%

Length

2024-04-17T06:50:27.910288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:27.992300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 5676
56.8%
폐업 4281
42.8%
직권폐업 28
 
0.3%
휴업 15
 
0.1%

x
Real number (ℝ)

MISSING 

Distinct5274
Distinct (%)57.8%
Missing868
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean388250.5
Minimum204412.09
Maximum407581.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:28.082275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204412.09
5-th percentile379669.83
Q1384354.16
median388749.87
Q3391581.27
95-th percentile398143.16
Maximum407581.08
Range203168.99
Interquartile range (IQR)7227.1033

Descriptive statistics

Standard deviation5922.0046
Coefficient of variation (CV)0.015253051
Kurtosis101.55752
Mean388250.5
Median Absolute Deviation (MAD)3435.4597
Skewness-3.2839188
Sum3.5455035 × 109
Variance35070138
MonotonicityNot monotonic
2024-04-17T06:50:28.194403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387537.525975 22
 
0.2%
387475.894546 18
 
0.2%
397548.804885 14
 
0.1%
394179.058785 14
 
0.1%
387532.458643 13
 
0.1%
398226.822818 13
 
0.1%
398401.454439 12
 
0.1%
389193.047711 12
 
0.1%
401736.191361 11
 
0.1%
394199.877518 11
 
0.1%
Other values (5264) 8992
89.9%
(Missing) 868
 
8.7%
ValueCountFrequency (%)
204412.090101 1
< 0.1%
365512.102998 1
< 0.1%
366851.651911 1
< 0.1%
366858.579155 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%
367196.193814 1
< 0.1%
ValueCountFrequency (%)
407581.083119 2
< 0.1%
407515.749132 3
< 0.1%
407448.0 2
< 0.1%
407369.530548 1
 
< 0.1%
407340.290634 1
 
< 0.1%
407209.258171 1
 
< 0.1%
407126.309068 1
 
< 0.1%
405468.503509 4
< 0.1%
405416.668261 2
< 0.1%
404343.092468 1
 
< 0.1%

y
Real number (ℝ)

MISSING 

Distinct5273
Distinct (%)57.7%
Missing868
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean187790.29
Minimum171993.68
Maximum445110.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:28.304957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171993.68
5-th percentile178557.26
Q1183587.6
median187559.87
Q3191804.88
95-th percentile197704.36
Maximum445110.29
Range273116.61
Interquartile range (IQR)8217.2818

Descriptive statistics

Standard deviation6671.8541
Coefficient of variation (CV)0.035528217
Kurtosis241.61623
Mean187790.29
Median Absolute Deviation (MAD)4177.5444
Skewness6.5258162
Sum1.7149009 × 109
Variance44513637
MonotonicityNot monotonic
2024-04-17T06:50:28.410923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186476.330395 22
 
0.2%
186570.418307 18
 
0.2%
187825.814573 14
 
0.1%
187626.880998 14
 
0.1%
187989.753665 13
 
0.1%
186392.673729 13
 
0.1%
191850.435201 12
 
0.1%
188080.4441 12
 
0.1%
196350.002951 11
 
0.1%
187795.493731 11
 
0.1%
Other values (5263) 8992
89.9%
(Missing) 868
 
8.7%
ValueCountFrequency (%)
171993.680351 1
 
< 0.1%
174063.354003 1
 
< 0.1%
174205.541619 1
 
< 0.1%
174237.045871 1
 
< 0.1%
174251.931196 1
 
< 0.1%
174292.594164 1
 
< 0.1%
174396.378069 4
< 0.1%
174404.947794 1
 
< 0.1%
174413.752458 2
< 0.1%
174415.392886 1
 
< 0.1%
ValueCountFrequency (%)
445110.286986 1
 
< 0.1%
211893.965608 1
 
< 0.1%
211392.6938 2
< 0.1%
208906.876551 1
 
< 0.1%
206494.685696 1
 
< 0.1%
206426.679067 3
< 0.1%
206423.253753 3
< 0.1%
206378.281379 2
< 0.1%
206377.970967 3
< 0.1%
206336.380838 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct8037
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0149528 × 1013
Minimum2.0081022 × 1013
Maximum2.0181016 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:28.523718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081022 × 1013
5-th percentile2.0090202 × 1013
Q12.0130711 × 1013
median2.0160715 × 1013
Q32.0170905 × 1013
95-th percentile2.018071 × 1013
Maximum2.0181016 × 1013
Range9.9994009 × 1010
Interquartile range (IQR)4.0194313 × 1010

Descriptive statistics

Standard deviation2.9134199 × 1010
Coefficient of variation (CV)0.0014458999
Kurtosis-0.50843282
Mean2.0149528 × 1013
Median Absolute Deviation (MAD)1.9605961 × 1010
Skewness-0.82057813
Sum2.0149528 × 1017
Variance8.4880154 × 1020
MonotonicityNot monotonic
2024-04-17T06:50:28.633914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905183851 203
 
2.0%
20170905183844 196
 
2.0%
20170905183850 191
 
1.9%
20170905183853 174
 
1.7%
20170905183849 156
 
1.6%
20170905183843 122
 
1.2%
20170905183852 122
 
1.2%
20170905183848 89
 
0.9%
20170905183859 79
 
0.8%
20170905183858 68
 
0.7%
Other values (8027) 8600
86.0%
ValueCountFrequency (%)
20081022163931 1
< 0.1%
20081117091658 1
< 0.1%
20081118094507 1
< 0.1%
20081126101537 1
< 0.1%
20081126103530 1
< 0.1%
20081126142837 1
< 0.1%
20081126154902 1
< 0.1%
20081126154951 1
< 0.1%
20081126155156 1
< 0.1%
20081126155236 1
< 0.1%
ValueCountFrequency (%)
20181016173009 1
< 0.1%
20180904174523 1
< 0.1%
20180904174453 1
< 0.1%
20180904174336 1
< 0.1%
20180904165343 1
< 0.1%
20180904154925 1
< 0.1%
20180904152059 1
< 0.1%
20180904143316 1
< 0.1%
20180904140506 1
< 0.1%
20180904132218 1
< 0.1%

uptaenm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4714 
의원
2610 
한의원
1197 
치과의원
1108 
요양병원(일반요양병원)
 
144
Other values (9)
 
227

Length

Max length12
Median length4
Mean length3.4519
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4714
47.1%
의원 2610
26.1%
한의원 1197
 
12.0%
치과의원 1108
 
11.1%
요양병원(일반요양병원) 144
 
1.4%
병원 130
 
1.3%
치과병원 20
 
0.2%
종합병원 16
 
0.2%
조산원 15
 
0.1%
한방병원 13
 
0.1%
Other values (4) 33
 
0.3%

Length

2024-04-17T06:50:28.739511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4714
47.1%
의원 2610
26.1%
한의원 1197
 
12.0%
치과의원 1108
 
11.1%
요양병원(일반요양병원 144
 
1.4%
병원 130
 
1.3%
치과병원 20
 
0.2%
종합병원 16
 
0.2%
조산원 15
 
0.1%
한방병원 13
 
0.1%
Other values (4) 33
 
0.3%

sitetel
Categorical

CONSTANT 

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

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 10000
100.0%

Length

2024-04-17T06:50:28.825751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:28.893821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 10000
100.0%

nursecnt
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)25.0%
Missing9972
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean3.5714286
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:28.951679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3.5
Q34
95-th percentile5.65
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4253933
Coefficient of variation (CV)0.39911012
Kurtosis2.321232
Mean3.5714286
Median Absolute Deviation (MAD)0.5
Skewness1.0017478
Sum100
Variance2.031746
MonotonicityNot monotonic
2024-04-17T06:50:29.029519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4 9
 
0.1%
3 8
 
0.1%
2 5
 
0.1%
5 3
 
< 0.1%
1 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 9972
99.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 5
0.1%
3 8
0.1%
4 9
0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 1
 
< 0.1%
5 3
 
< 0.1%
4 9
0.1%
3 8
0.1%
2 5
0.1%
1 1
 
< 0.1%

nursaidcnt
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)57.1%
Missing9972
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean7.6785714
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:29.122748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median7
Q311
95-th percentile16.65
Maximum22
Range21
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.2567669
Coefficient of variation (CV)0.6846022
Kurtosis0.5619029
Mean7.6785714
Median Absolute Deviation (MAD)4
Skewness0.91362614
Sum215
Variance27.633598
MonotonicityNot monotonic
2024-04-17T06:50:29.227768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 4
 
< 0.1%
3 3
 
< 0.1%
11 3
 
< 0.1%
7 3
 
< 0.1%
4 2
 
< 0.1%
10 2
 
< 0.1%
6 2
 
< 0.1%
1 1
 
< 0.1%
9 1
 
< 0.1%
14 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 9972
99.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 4
< 0.1%
3 3
< 0.1%
4 2
< 0.1%
5 1
 
< 0.1%
6 2
< 0.1%
7 3
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 2
< 0.1%
ValueCountFrequency (%)
22 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
11 3
< 0.1%
10 2
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 3
< 0.1%

bdnglayercnt
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)51.7%
Missing9971
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean7.4827586
Minimum0
Maximum23
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:29.328984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q311
95-th percentile18.8
Maximum23
Range23
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.8774429
Coefficient of variation (CV)0.78546472
Kurtosis1.2348311
Mean7.4827586
Median Absolute Deviation (MAD)4
Skewness0.91291286
Sum217
Variance34.544335
MonotonicityNot monotonic
2024-04-17T06:50:29.425101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 5
 
0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
11 3
 
< 0.1%
9 2
 
< 0.1%
6 2
 
< 0.1%
12 2
 
< 0.1%
2 2
 
< 0.1%
10 1
 
< 0.1%
3 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 9971
99.7%
ValueCountFrequency (%)
0 5
0.1%
2 2
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 3
< 0.1%
8 3
< 0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
14 1
 
< 0.1%
12 2
< 0.1%
11 3
< 0.1%
10 1
 
< 0.1%
9 2
< 0.1%
8 3
< 0.1%
7 3
< 0.1%
6 2
< 0.1%

emercargen
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5966 
0
4034 

Length

Max length4
Median length4
Mean length2.7898
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5966
59.7%
0 4034
40.3%

Length

2024-04-17T06:50:29.520395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:29.593723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5966
59.7%
0 4034
40.3%

emercarspec
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5966 
0
4034 

Length

Max length4
Median length4
Mean length2.7898
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5966
59.7%
0 4034
40.3%

Length

2024-04-17T06:50:29.673835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:29.750025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5966
59.7%
0 4034
40.3%

rescnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

pomfacilar
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)95.0%
Missing9980
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean53.1025
Minimum0
Maximum162
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:29.816898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.9775
median44
Q360.8725
95-th percentile161.335
Maximum162
Range162
Interquartile range (IQR)36.895

Descriptive statistics

Standard deviation45.574527
Coefficient of variation (CV)0.85823694
Kurtosis1.6530103
Mean53.1025
Median Absolute Deviation (MAD)19.475
Skewness1.4046501
Sum1062.05
Variance2077.0375
MonotonicityNot monotonic
2024-04-17T06:50:29.906794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
57.0 1
 
< 0.1%
25.0 1
 
< 0.1%
23.76 1
 
< 0.1%
57.59 1
 
< 0.1%
15.4 1
 
< 0.1%
62.05 1
 
< 0.1%
60.48 1
 
< 0.1%
38.0 1
 
< 0.1%
50.0 1
 
< 0.1%
Other values (9) 9
 
0.1%
(Missing) 9980
99.8%
ValueCountFrequency (%)
0.0 2
< 0.1%
15.4 1
< 0.1%
20.42 1
< 0.1%
23.76 1
< 0.1%
24.05 1
< 0.1%
25.0 1
< 0.1%
28.32 1
< 0.1%
34.53 1
< 0.1%
38.0 1
< 0.1%
50.0 1
< 0.1%
ValueCountFrequency (%)
162.0 1
< 0.1%
161.3 1
< 0.1%
109.6 1
< 0.1%
79.85 1
< 0.1%
62.05 1
< 0.1%
60.48 1
< 0.1%
57.59 1
< 0.1%
57.0 1
< 0.1%
52.7 1
< 0.1%
50.0 1
< 0.1%

etcstfcnt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9988 
1
 
6
5
 
3
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9964
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9988
99.9%
1 6
 
0.1%
5 3
 
< 0.1%
2 1
 
< 0.1%
6 1
 
< 0.1%
0 1
 
< 0.1%

Length

2024-04-17T06:50:30.005150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:30.088174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9988
99.9%
1 6
 
0.1%
5 3
 
< 0.1%
2 1
 
< 0.1%
6 1
 
< 0.1%
0 1
 
< 0.1%

etcepcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

mmknurmar
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)95.7%
Missing9977
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean44.11913
Minimum6.8
Maximum494.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:30.167760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile7.175
Q19.93
median16.12
Q338.295
95-th percentile67.248
Maximum494.67
Range487.87
Interquartile range (IQR)28.365

Descriptive statistics

Standard deviation99.727152
Coefficient of variation (CV)2.2604061
Kurtosis21.441004
Mean44.11913
Median Absolute Deviation (MAD)7.37
Skewness4.5666763
Sum1014.74
Variance9945.5048
MonotonicityNot monotonic
2024-04-17T06:50:30.261628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9.3 2
 
< 0.1%
32.0 1
 
< 0.1%
13.0 1
 
< 0.1%
10.7 1
 
< 0.1%
46.8 1
 
< 0.1%
33.4 1
 
< 0.1%
6.8 1
 
< 0.1%
10.56 1
 
< 0.1%
21.6 1
 
< 0.1%
42.0 1
 
< 0.1%
Other values (12) 12
 
0.1%
(Missing) 9977
99.8%
ValueCountFrequency (%)
6.8 1
< 0.1%
7.0 1
< 0.1%
8.75 1
< 0.1%
8.97 1
< 0.1%
9.3 2
< 0.1%
10.56 1
< 0.1%
10.7 1
< 0.1%
11.0 1
< 0.1%
13.0 1
< 0.1%
15.3 1
< 0.1%
ValueCountFrequency (%)
494.67 1
< 0.1%
68.8 1
< 0.1%
53.28 1
< 0.1%
46.8 1
< 0.1%
42.0 1
< 0.1%
41.29 1
< 0.1%
35.3 1
< 0.1%
33.4 1
< 0.1%
32.0 1
< 0.1%
21.6 1
< 0.1%

btrmar
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)93.8%
Missing9984
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean24.026875
Minimum0
Maximum160.44
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:30.351778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.9125
median7.75
Q321.44
95-th percentile99.96
Maximum160.44
Range160.44
Interquartile range (IQR)17.5275

Descriptive statistics

Standard deviation41.66099
Coefficient of variation (CV)1.7339329
Kurtosis8.1212242
Mean24.026875
Median Absolute Deviation (MAD)4.585
Skewness2.7809032
Sum384.43
Variance1735.6381
MonotonicityNot monotonic
2024-04-17T06:50:30.448772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
42.4 1
 
< 0.1%
21.5 1
 
< 0.1%
3.23 1
 
< 0.1%
7.1 1
 
< 0.1%
79.8 1
 
< 0.1%
4.14 1
 
< 0.1%
8.4 1
 
< 0.1%
11.0 1
 
< 0.1%
160.44 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 9984
99.8%
ValueCountFrequency (%)
0.0 2
< 0.1%
3.1 1
< 0.1%
3.23 1
< 0.1%
4.14 1
< 0.1%
6.0 1
< 0.1%
7.0 1
< 0.1%
7.1 1
< 0.1%
8.4 1
< 0.1%
8.9 1
< 0.1%
11.0 1
< 0.1%
ValueCountFrequency (%)
160.44 1
< 0.1%
79.8 1
< 0.1%
42.4 1
< 0.1%
21.5 1
< 0.1%
21.42 1
< 0.1%
11.0 1
< 0.1%
8.9 1
< 0.1%
8.4 1
< 0.1%
7.1 1
< 0.1%
7.0 1
< 0.1%

btpnum
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)37.5%
Missing9984
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2.0625
Minimum0
Maximum6
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:30.530641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75
Q11
median2
Q32.25
95-th percentile4.5
Maximum6
Range6
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation1.5261608
Coefficient of variation (CV)0.73995673
Kurtosis1.7103387
Mean2.0625
Median Absolute Deviation (MAD)1
Skewness1.2955747
Sum33
Variance2.3291667
MonotonicityNot monotonic
2024-04-17T06:50:30.853777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
 
0.1%
2 5
 
0.1%
4 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%
0 1
 
< 0.1%
(Missing) 9984
99.8%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 6
0.1%
2 5
0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%
2 5
0.1%
1 6
0.1%
0 1
 
< 0.1%

sicbnum
Real number (ℝ)

MISSING  ZEROS 

Distinct195
Distinct (%)4.8%
Missing5966
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean12.646009
Minimum0
Maximum999
Zeros3409
Zeros (%)34.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:30.965714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile79.35
Maximum999
Range999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation53.467622
Coefficient of variation (CV)4.2280235
Kurtosis82.086131
Mean12.646009
Median Absolute Deviation (MAD)0
Skewness7.4307429
Sum51014
Variance2858.7866
MonotonicityNot monotonic
2024-04-17T06:50:31.070966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3409
34.1%
29 54
 
0.5%
1 40
 
0.4%
2 35
 
0.4%
4 32
 
0.3%
3 22
 
0.2%
199 13
 
0.1%
30 10
 
0.1%
10 10
 
0.1%
20 9
 
0.1%
Other values (185) 400
 
4.0%
(Missing) 5966
59.7%
ValueCountFrequency (%)
0 3409
34.1%
1 40
 
0.4%
2 35
 
0.4%
3 22
 
0.2%
4 32
 
0.3%
5 8
 
0.1%
6 8
 
0.1%
7 8
 
0.1%
8 9
 
0.1%
9 7
 
0.1%
ValueCountFrequency (%)
999 1
< 0.1%
896 1
< 0.1%
797 1
< 0.1%
590 1
< 0.1%
580 1
< 0.1%
539 1
< 0.1%
524 1
< 0.1%
428 1
< 0.1%
420 1
< 0.1%
400 2
< 0.1%

astnepnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

ofear
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)95.0%
Missing9980
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean13.3065
Minimum0
Maximum42
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:31.163331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.8
Q17.9
median10.055
Q313.235
95-th percentile32.12
Maximum42
Range42
Interquartile range (IQR)5.335

Descriptive statistics

Standard deviation10.431725
Coefficient of variation (CV)0.78395709
Kurtosis2.0134659
Mean13.3065
Median Absolute Deviation (MAD)2.7
Skewness1.5347609
Sum266.13
Variance108.82089
MonotonicityNot monotonic
2024-04-17T06:50:31.242930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8.0 2
 
< 0.1%
13.94 1
 
< 0.1%
28.2 1
 
< 0.1%
4.3 1
 
< 0.1%
8.4 1
 
< 0.1%
6.6 1
 
< 0.1%
10.0 1
 
< 0.1%
31.6 1
 
< 0.1%
25.2 1
 
< 0.1%
13.0 1
 
< 0.1%
Other values (9) 9
 
0.1%
(Missing) 9980
99.8%
ValueCountFrequency (%)
0.0 1
< 0.1%
4.0 1
< 0.1%
4.3 1
< 0.1%
6.6 1
< 0.1%
7.6 1
< 0.1%
8.0 2
< 0.1%
8.4 1
< 0.1%
9.3 1
< 0.1%
10.0 1
< 0.1%
10.11 1
< 0.1%
ValueCountFrequency (%)
42.0 1
< 0.1%
31.6 1
< 0.1%
28.2 1
< 0.1%
25.2 1
< 0.1%
13.94 1
< 0.1%
13.0 1
< 0.1%
12.4 1
< 0.1%
12.06 1
< 0.1%
11.42 1
< 0.1%
10.11 1
< 0.1%

warmar
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)94.4%
Missing9982
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean16.905
Minimum0
Maximum48.7
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:31.322450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.0825
median12.5
Q327.725
95-th percentile43.005
Maximum48.7
Range48.7
Interquartile range (IQR)22.6425

Descriptive statistics

Standard deviation15.114208
Coefficient of variation (CV)0.8940673
Kurtosis-0.48982859
Mean16.905
Median Absolute Deviation (MAD)10.47
Skewness0.77484196
Sum304.29
Variance228.43927
MonotonicityNot monotonic
2024-04-17T06:50:31.405234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 2
 
< 0.1%
9.2 1
 
< 0.1%
11.0 1
 
< 0.1%
2.5 1
 
< 0.1%
15.3 1
 
< 0.1%
27.2 1
 
< 0.1%
14.0 1
 
< 0.1%
37.0 1
 
< 0.1%
17.0 1
 
< 0.1%
27.9 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 9982
99.8%
ValueCountFrequency (%)
0.0 2
< 0.1%
1.56 1
< 0.1%
2.5 1
< 0.1%
4.86 1
< 0.1%
5.75 1
< 0.1%
9.2 1
< 0.1%
10.12 1
< 0.1%
11.0 1
< 0.1%
14.0 1
< 0.1%
15.3 1
< 0.1%
ValueCountFrequency (%)
48.7 1
< 0.1%
42.0 1
< 0.1%
37.0 1
< 0.1%
30.2 1
< 0.1%
27.9 1
< 0.1%
27.2 1
< 0.1%
17.0 1
< 0.1%
15.3 1
< 0.1%
14.0 1
< 0.1%
11.0 1
< 0.1%

facilmngnum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

pharmtrdar
Real number (ℝ)

MISSING  ZEROS 

Distinct1111
Distinct (%)41.5%
Missing7322
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean49.12618
Minimum0
Maximum516.04
Zeros294
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:31.502292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120.2025
median42.64
Q367.075
95-th percentile129.632
Maximum516.04
Range516.04
Interquartile range (IQR)46.8725

Descriptive statistics

Standard deviation45.515984
Coefficient of variation (CV)0.92651177
Kurtosis16.571555
Mean49.12618
Median Absolute Deviation (MAD)23.375
Skewness2.5691009
Sum131559.91
Variance2071.7048
MonotonicityNot monotonic
2024-04-17T06:50:31.616547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 294
 
2.9%
1.0 282
 
2.8%
66.0 30
 
0.3%
49.5 28
 
0.3%
33.0 24
 
0.2%
82.5 20
 
0.2%
99.0 18
 
0.2%
56.1 16
 
0.2%
30.0 15
 
0.1%
39.6 15
 
0.1%
Other values (1101) 1936
 
19.4%
(Missing) 7322
73.2%
ValueCountFrequency (%)
0.0 294
2.9%
1.0 282
2.8%
8.86 1
 
< 0.1%
10.28 1
 
< 0.1%
11.11 1
 
< 0.1%
12.0 1
 
< 0.1%
12.5 1
 
< 0.1%
12.9 2
 
< 0.1%
12.96 2
 
< 0.1%
13.2 1
 
< 0.1%
ValueCountFrequency (%)
516.04 2
< 0.1%
454.92 1
< 0.1%
450.0 2
< 0.1%
364.85 1
< 0.1%
251.0 2
< 0.1%
250.47 1
< 0.1%
247.07 1
< 0.1%
240.0 1
< 0.1%
235.98 1
< 0.1%
224.0 1
< 0.1%

nutrcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9988 
0
 
8
1
 
4

Length

Max length4
Median length4
Mean length3.9964
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> 9988
99.9%
0 8
 
0.1%
1 4
 
< 0.1%

Length

2024-04-17T06:50:31.717397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:31.799635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9988
99.9%
0 8
 
0.1%
1 4
 
< 0.1%

bbrmar
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing9971
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean48.432759
Minimum1.7
Maximum114.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:31.877904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile15.4
Q123.73
median39.78
Q367.37
95-th percentile100.908
Maximum114.3
Range112.6
Interquartile range (IQR)43.64

Descriptive statistics

Standard deviation30.882581
Coefficient of variation (CV)0.63763828
Kurtosis-0.61755417
Mean48.432759
Median Absolute Deviation (MAD)17.58
Skewness0.70143491
Sum1404.55
Variance953.73379
MonotonicityNot monotonic
2024-04-17T06:50:31.969381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
24.0 1
 
< 0.1%
37.1 1
 
< 0.1%
14.2 1
 
< 0.1%
41.04 1
 
< 0.1%
1.7 1
 
< 0.1%
114.3 1
 
< 0.1%
71.4 1
 
< 0.1%
17.2 1
 
< 0.1%
39.78 1
 
< 0.1%
87.01 1
 
< 0.1%
Other values (19) 19
 
0.2%
(Missing) 9971
99.7%
ValueCountFrequency (%)
1.7 1
< 0.1%
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%
22.4 1
< 0.1%
23.73 1
< 0.1%
24.0 1
< 0.1%
24.13 1
< 0.1%
ValueCountFrequency (%)
114.3 1
< 0.1%
101.6 1
< 0.1%
99.87 1
< 0.1%
96.2 1
< 0.1%
93.0 1
< 0.1%
87.01 1
< 0.1%
71.4 1
< 0.1%
67.37 1
< 0.1%
60.84 1
< 0.1%
54.0 1
< 0.1%

babyrglstnum
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)78.1%
Missing9968
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20.875
Minimum3
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:32.058429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q110.75
median19.5
Q327.25
95-th percentile44.45
Maximum50
Range47
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation12.528033
Coefficient of variation (CV)0.6001453
Kurtosis-0.080558701
Mean20.875
Median Absolute Deviation (MAD)8.5
Skewness0.8387479
Sum668
Variance156.95161
MonotonicityNot monotonic
2024-04-17T06:50:32.145481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
9 3
 
< 0.1%
17 2
 
< 0.1%
7 2
 
< 0.1%
12 2
 
< 0.1%
20 2
 
< 0.1%
28 2
 
< 0.1%
24 1
 
< 0.1%
19 1
 
< 0.1%
23 1
 
< 0.1%
15 1
 
< 0.1%
Other values (15) 15
 
0.1%
(Missing) 9968
99.7%
ValueCountFrequency (%)
3 1
 
< 0.1%
7 2
< 0.1%
8 1
 
< 0.1%
9 3
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
12 2
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
17 2
< 0.1%
ValueCountFrequency (%)
50 1
< 0.1%
45 1
< 0.1%
44 1
< 0.1%
43 1
< 0.1%
40 1
< 0.1%
29 1
< 0.1%
28 2
< 0.1%
27 1
< 0.1%
26 1
< 0.1%
24 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>
5966 
의원
1962 
한의원
883 
치과의원
827 
요양병원(일반요양병원)
 
144
Other values (13)
 
218

Length

Max length12
Median length4
Mean length3.6136
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5966
59.7%
의원 1962
 
19.6%
한의원 883
 
8.8%
치과의원 827
 
8.3%
요양병원(일반요양병원) 144
 
1.4%
병원 130
 
1.3%
치과병원 20
 
0.2%
종합병원 16
 
0.2%
한방병원 13
 
0.1%
부속의원 11
 
0.1%
Other values (8) 28
 
0.3%

Length

2024-04-17T06:50:32.238247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5966
59.7%
의원 1962
 
19.6%
한의원 883
 
8.8%
치과의원 827
 
8.3%
요양병원(일반요양병원 144
 
1.4%
병원 130
 
1.3%
치과병원 20
 
0.2%
종합병원 16
 
0.2%
한방병원 13
 
0.1%
요양병원(정신병원 11
 
0.1%
Other values (8) 28
 
0.3%

metrbosassrnm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

metrpnum
Real number (ℝ)

MISSING  SKEWED 

Distinct76
Distinct (%)1.9%
Missing5966
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean4.3430838
Minimum0
Maximum1436
Zeros73
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:32.333771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile11
Maximum1436
Range1436
Interquartile range (IQR)0

Descriptive statistics

Standard deviation38.661896
Coefficient of variation (CV)8.9019456
Kurtosis918.6882
Mean4.3430838
Median Absolute Deviation (MAD)0
Skewness28.224869
Sum17520
Variance1494.7422
MonotonicityNot monotonic
2024-04-17T06:50:32.443885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3030
30.3%
2 424
 
4.2%
3 112
 
1.1%
0 73
 
0.7%
4 49
 
0.5%
5 41
 
0.4%
7 27
 
0.3%
6 27
 
0.3%
11 22
 
0.2%
8 20
 
0.2%
Other values (66) 209
 
2.1%
(Missing) 5966
59.7%
ValueCountFrequency (%)
0 73
 
0.7%
1 3030
30.3%
2 424
 
4.2%
3 112
 
1.1%
4 49
 
0.5%
5 41
 
0.4%
6 27
 
0.3%
7 27
 
0.3%
8 20
 
0.2%
9 9
 
0.1%
ValueCountFrequency (%)
1436 1
< 0.1%
1282 1
< 0.1%
1077 1
< 0.1%
419 1
< 0.1%
367 1
< 0.1%
352 1
< 0.1%
331 1
< 0.1%
310 1
< 0.1%
278 1
< 0.1%
268 1
< 0.1%

pgrmar
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing9971
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean385.52862
Minimum6.3
Maximum1975.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:32.545742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.3
5-th percentile7.2
Q1132.61
median328.7
Q3504.56
95-th percentile902.854
Maximum1975.92
Range1969.62
Interquartile range (IQR)371.95

Descriptive statistics

Standard deviation409.41768
Coefficient of variation (CV)1.0619644
Kurtosis7.2652723
Mean385.52862
Median Absolute Deviation (MAD)196.09
Skewness2.2361703
Sum11180.33
Variance167622.84
MonotonicityNot monotonic
2024-04-17T06:50:32.646852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
146.0 1
 
< 0.1%
309.1 1
 
< 0.1%
61.2 1
 
< 0.1%
406.64 1
 
< 0.1%
6.3 1
 
< 0.1%
848.02 1
 
< 0.1%
328.7 1
 
< 0.1%
7.5 1
 
< 0.1%
414.76 1
 
< 0.1%
1975.92 1
 
< 0.1%
Other values (19) 19
 
0.2%
(Missing) 9971
99.7%
ValueCountFrequency (%)
6.3 1
< 0.1%
7.0 1
< 0.1%
7.5 1
< 0.1%
8.0 1
< 0.1%
11.2 1
< 0.1%
11.6 1
< 0.1%
61.2 1
< 0.1%
132.61 1
< 0.1%
146.0 1
< 0.1%
154.52 1
< 0.1%
ValueCountFrequency (%)
1975.92 1
< 0.1%
938.49 1
< 0.1%
849.4 1
< 0.1%
848.02 1
< 0.1%
669.9 1
< 0.1%
545.11 1
< 0.1%
533.9 1
< 0.1%
504.56 1
< 0.1%
482.0 1
< 0.1%
462.31 1
< 0.1%

pwnmrglstnum
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)78.1%
Missing9968
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean21.03125
Minimum7
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:32.742297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7
Q111
median19.5
Q327.25
95-th percentile44.45
Maximum47
Range40
Interquartile range (IQR)16.25

Descriptive statistics

Standard deviation12.044231
Coefficient of variation (CV)0.57268262
Kurtosis-0.20001408
Mean21.03125
Median Absolute Deviation (MAD)8.5
Skewness0.84827956
Sum673
Variance145.06351
MonotonicityNot monotonic
2024-04-17T06:50:32.834569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
7 3
 
< 0.1%
17 2
 
< 0.1%
11 2
 
< 0.1%
20 2
 
< 0.1%
9 2
 
< 0.1%
28 2
 
< 0.1%
24 1
 
< 0.1%
19 1
 
< 0.1%
23 1
 
< 0.1%
15 1
 
< 0.1%
Other values (15) 15
 
0.1%
(Missing) 9968
99.7%
ValueCountFrequency (%)
7 3
< 0.1%
8 1
 
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
11 2
< 0.1%
12 1
 
< 0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
17 2
< 0.1%
ValueCountFrequency (%)
47 1
< 0.1%
45 1
< 0.1%
44 1
< 0.1%
43 1
< 0.1%
40 1
< 0.1%
29 1
< 0.1%
28 2
< 0.1%
27 1
< 0.1%
26 1
< 0.1%
24 1
< 0.1%

hstrmnum
Real number (ℝ)

MISSING  ZEROS 

Distinct83
Distinct (%)2.1%
Missing5966
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean2.8822509
Minimum0
Maximum264
Zeros3448
Zeros (%)34.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:32.967860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20
Maximum264
Range264
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.19977
Coefficient of variation (CV)4.2327231
Kurtosis127.17323
Mean2.8822509
Median Absolute Deviation (MAD)0
Skewness8.9133844
Sum11627
Variance148.83438
MonotonicityNot monotonic
2024-04-17T06:50:33.105910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3448
34.5%
1 62
 
0.6%
2 43
 
0.4%
6 32
 
0.3%
3 29
 
0.3%
4 27
 
0.3%
9 22
 
0.2%
5 22
 
0.2%
7 21
 
0.2%
8 16
 
0.2%
Other values (73) 312
 
3.1%
(Missing) 5966
59.7%
ValueCountFrequency (%)
0 3448
34.5%
1 62
 
0.6%
2 43
 
0.4%
3 29
 
0.3%
4 27
 
0.3%
5 22
 
0.2%
6 32
 
0.3%
7 21
 
0.2%
8 16
 
0.2%
9 22
 
0.2%
ValueCountFrequency (%)
264 1
< 0.1%
250 1
< 0.1%
185 1
< 0.1%
133 1
< 0.1%
122 1
< 0.1%
114 1
< 0.1%
104 1
< 0.1%
101 1
< 0.1%
100 2
< 0.1%
99 1
< 0.1%

qutnownernum
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

joriwontoilar
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)100.0%
Missing9979
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean38.319048
Minimum6.5
Maximum100.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:33.200684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile6.6
Q112.66
median24.7
Q365
95-th percentile96.9
Maximum100.44
Range93.94
Interquartile range (IQR)52.34

Descriptive statistics

Standard deviation31.327917
Coefficient of variation (CV)0.81755469
Kurtosis-0.78210914
Mean38.319048
Median Absolute Deviation (MAD)13.1
Skewness0.80271831
Sum804.7
Variance981.43838
MonotonicityNot monotonic
2024-04-17T06:50:33.297652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
33.4 1
 
< 0.1%
57.0 1
 
< 0.1%
12.3 1
 
< 0.1%
68.0 1
 
< 0.1%
11.68 1
 
< 0.1%
6.5 1
 
< 0.1%
19.28 1
 
< 0.1%
100.44 1
 
< 0.1%
65.0 1
 
< 0.1%
96.9 1
 
< 0.1%
Other values (11) 11
 
0.1%
(Missing) 9979
99.8%
ValueCountFrequency (%)
6.5 1
< 0.1%
6.6 1
< 0.1%
10.08 1
< 0.1%
11.68 1
< 0.1%
12.3 1
< 0.1%
12.66 1
< 0.1%
15.1 1
< 0.1%
15.18 1
< 0.1%
16.08 1
< 0.1%
19.28 1
< 0.1%
ValueCountFrequency (%)
100.44 1
< 0.1%
96.9 1
< 0.1%
79.8 1
< 0.1%
79.2 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%

epcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

jisgnumlay
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)50.0%
Missing9976
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean44.083333
Minimum2
Maximum891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:33.399631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median7
Q39
95-th percentile22.55
Maximum891
Range889
Interquartile range (IQR)5

Descriptive statistics

Standard deviation180.46677
Coefficient of variation (CV)4.0937641
Kurtosis23.955094
Mean44.083333
Median Absolute Deviation (MAD)3
Skewness4.8924273
Sum1058
Variance32568.254
MonotonicityNot monotonic
2024-04-17T06:50:33.474941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 4
 
< 0.1%
9 3
 
< 0.1%
5 3
 
< 0.1%
4 3
 
< 0.1%
2 3
 
< 0.1%
3 2
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 9976
99.8%
ValueCountFrequency (%)
2 3
< 0.1%
3 2
< 0.1%
4 3
< 0.1%
5 3
< 0.1%
7 4
< 0.1%
8 1
 
< 0.1%
9 3
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
891 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
9 3
< 0.1%
8 1
 
< 0.1%
7 4
< 0.1%
5 3
< 0.1%
4 3
< 0.1%

asgnymd
Real number (ℝ)

MISSING 

Distinct2056
Distinct (%)76.7%
Missing7320
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean20044905
Minimum19610316
Maximum20180903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:33.567405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19610316
5-th percentile19780314
Q120001201
median20080804
Q320130102
95-th percentile20170626
Maximum20180903
Range570587
Interquartile range (IQR)128901

Descriptive statistics

Standard deviation116774.05
Coefficient of variation (CV)0.0058256225
Kurtosis1.3554824
Mean20044905
Median Absolute Deviation (MAD)59297.5
Skewness-1.3817708
Sum5.3720346 × 1010
Variance1.3636179 × 1010
MonotonicityNot monotonic
2024-04-17T06:50:33.679550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130701 9
 
0.1%
20110502 8
 
0.1%
20140901 7
 
0.1%
20130102 7
 
0.1%
20090302 7
 
0.1%
19660301 6
 
0.1%
20100302 6
 
0.1%
20130902 6
 
0.1%
19691231 6
 
0.1%
20070702 5
 
0.1%
Other values (2046) 2613
 
26.1%
(Missing) 7320
73.2%
ValueCountFrequency (%)
19610316 1
 
< 0.1%
19610418 1
 
< 0.1%
19620310 1
 
< 0.1%
19620928 1
 
< 0.1%
19630207 1
 
< 0.1%
19660228 1
 
< 0.1%
19660301 6
0.1%
19660415 1
 
< 0.1%
19660521 1
 
< 0.1%
19660920 2
 
< 0.1%
ValueCountFrequency (%)
20180903 3
< 0.1%
20180829 1
 
< 0.1%
20180827 2
< 0.1%
20180821 4
< 0.1%
20180814 1
 
< 0.1%
20180813 3
< 0.1%
20180803 1
 
< 0.1%
20180801 2
< 0.1%
20180731 1
 
< 0.1%
20180723 1
 
< 0.1%

asgncancelymd
Real number (ℝ)

MISSING 

Distinct178
Distinct (%)53.3%
Missing9666
Missing (%)96.7%
Infinite0
Infinite (%)0.0%
Mean20166281
Minimum20081231
Maximum20180904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:33.796334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081231
5-th percentile20110692
Q120170244
median20180424
Q320180727
95-th percentile20180828
Maximum20180904
Range99673
Interquartile range (IQR)10483

Descriptive statistics

Standard deviation24081.244
Coefficient of variation (CV)0.0011941341
Kurtosis1.7319475
Mean20166281
Median Absolute Deviation (MAD)397
Skewness-1.6856132
Sum6.7355377 × 109
Variance5.7990629 × 108
MonotonicityNot monotonic
2024-04-17T06:50:33.924095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170905 32
 
0.3%
20180724 11
 
0.1%
20180808 10
 
0.1%
20180813 9
 
0.1%
20180831 8
 
0.1%
20180810 7
 
0.1%
20180823 7
 
0.1%
20180614 6
 
0.1%
20130221 5
 
0.1%
20180829 5
 
0.1%
Other values (168) 234
 
2.3%
(Missing) 9666
96.7%
ValueCountFrequency (%)
20081231 1
< 0.1%
20090305 1
< 0.1%
20090401 1
< 0.1%
20091126 2
< 0.1%
20091231 1
< 0.1%
20100128 1
< 0.1%
20100226 1
< 0.1%
20100322 1
< 0.1%
20100416 1
< 0.1%
20100503 1
< 0.1%
ValueCountFrequency (%)
20180904 2
 
< 0.1%
20180831 8
0.1%
20180830 2
 
< 0.1%
20180829 5
0.1%
20180828 2
 
< 0.1%
20180827 3
 
< 0.1%
20180824 2
 
< 0.1%
20180823 7
0.1%
20180822 2
 
< 0.1%
20180821 4
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9988 
0
 
5
2
 
4
1
 
3

Length

Max length4
Median length4
Mean length3.9964
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> 9988
99.9%
0 5
 
0.1%
2 4
 
< 0.1%
1 3
 
< 0.1%

Length

2024-04-17T06:50:34.048402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:34.124259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9988
99.9%
0 5
 
< 0.1%
2 4
 
< 0.1%
1 3
 
< 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 

Distinct2691
Distinct (%)66.7%
Missing5966
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean976.45189
Minimum0
Maximum1384945
Zeros598
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:34.208043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q189
median157.605
Q3270.5575
95-th percentile1994.21
Maximum1384945
Range1384945
Interquartile range (IQR)181.5575

Descriptive statistics

Standard deviation22356.476
Coefficient of variation (CV)22.895625
Kurtosis3645.9689
Mean976.45189
Median Absolute Deviation (MAD)85.86
Skewness59.154834
Sum3939006.9
Variance4.9981201 × 108
MonotonicityNot monotonic
2024-04-17T06:50:34.312788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 598
 
6.0%
1.0 84
 
0.8%
120.0 50
 
0.5%
100.0 14
 
0.1%
132.0 9
 
0.1%
177.0 9
 
0.1%
140.0 8
 
0.1%
150.0 8
 
0.1%
165.0 7
 
0.1%
354.07 7
 
0.1%
Other values (2681) 3240
32.4%
(Missing) 5966
59.7%
ValueCountFrequency (%)
0.0 598
6.0%
1.0 84
 
0.8%
10.0 2
 
< 0.1%
11.5 1
 
< 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%
28.74 1
 
< 0.1%
ValueCountFrequency (%)
1384945.0 1
< 0.1%
186261.0 1
< 0.1%
168117.0 1
< 0.1%
113599.96 1
< 0.1%
90383.51 1
< 0.1%
56670.14 1
< 0.1%
51976.15 1
< 0.1%
41279.6 1
< 0.1%
31376.0 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 (%)33.3%
Missing9982
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2.7777778
Minimum0
Maximum15
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:34.402366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.85
Q11
median2
Q33
95-th percentile5.65
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2639845
Coefficient of variation (CV)1.1750344
Kurtosis12.960498
Mean2.7777778
Median Absolute Deviation (MAD)1
Skewness3.3740612
Sum50
Variance10.653595
MonotonicityNot monotonic
2024-04-17T06:50:34.481851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
 
0.1%
3 5
 
0.1%
2 3
 
< 0.1%
4 2
 
< 0.1%
0 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 9982
99.8%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 6
0.1%
2 3
< 0.1%
3 5
0.1%
4 2
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
4 2
 
< 0.1%
3 5
0.1%
2 3
< 0.1%
1 6
0.1%
0 1
 
< 0.1%

storetrdar
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct367
Distinct (%)7.4%
Missing5011
Missing (%)50.1%
Infinite0
Infinite (%)0.0%
Mean19.347587
Minimum0
Maximum4038
Zeros3684
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T06:50:34.836839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q330
95-th percentile99
Maximum4038
Range4038
Interquartile range (IQR)30

Descriptive statistics

Standard deviation67.541526
Coefficient of variation (CV)3.4909535
Kurtosis2514.4407
Mean19.347587
Median Absolute Deviation (MAD)0
Skewness42.679862
Sum96525.11
Variance4561.8577
MonotonicityNot monotonic
2024-04-17T06:50:34.977619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3684
36.8%
49.5 115
 
1.1%
66.0 111
 
1.1%
99.0 48
 
0.5%
82.5 44
 
0.4%
33.0 39
 
0.4%
59.4 28
 
0.3%
60.0 25
 
0.2%
132.0 21
 
0.2%
100.0 21
 
0.2%
Other values (357) 853
 
8.5%
(Missing) 5011
50.1%
ValueCountFrequency (%)
0.0 3684
36.8%
3.0 1
 
< 0.1%
3.3 5
 
0.1%
3.5 4
 
< 0.1%
13.2 1
 
< 0.1%
15.0 1
 
< 0.1%
16.12 1
 
< 0.1%
16.5 2
 
< 0.1%
17.8 1
 
< 0.1%
18.5 1
 
< 0.1%
ValueCountFrequency (%)
4038.0 1
< 0.1%
624.0 1
< 0.1%
329.9 1
< 0.1%
277.27 1
< 0.1%
264.0 1
< 0.1%
230.0 1
< 0.1%
208.31 1
< 0.1%
198.0 2
< 0.1%
197.07 1
< 0.1%
191.85 1
< 0.1%

pmtbednum
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9650 
0
 
350

Length

Max length4
Median length4
Mean length3.895
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9650
96.5%
0 350
 
3.5%

Length

2024-04-17T06:50:35.087594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:35.160880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9650
96.5%
0 350
 
3.5%

last_load_dttm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-03-01 05:19:04
4110 
2021-03-01 05:19:06
2426 
2021-03-01 05:19:03
1820 
2021-03-01 05:19:07
1183 
2021-03-01 05:19:05
461 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-03-01 05:19:04 4110
41.1%
2021-03-01 05:19:06 2426
24.3%
2021-03-01 05:19:03 1820
18.2%
2021-03-01 05:19:07 1183
 
11.8%
2021-03-01 05:19:05 461
 
4.6%

Length

2024-04-17T06:50:35.231728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:50:35.306555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 10000
50.0%
05:19:04 4110
20.5%
05:19:06 2426
 
12.1%
05:19:03 1820
 
9.1%
05:19:07 1183
 
5.9%
05:19:05 461
 
2.3%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
933899093310000PHMH32012331002408750006201_01_05_PI2018-08-31 23:59:59.0<NA>씨유 대연동천점608818부산광역시 남구 대연동 1505번지 1호48429부산광역시 남구 못골번영로 47, 102호 (대연동)20121113<NA><NA><NA><NA>13영업중390372.295101184560.56668220130812102013<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>108.8<NA>2021-03-01 05:19:05
10999813360000PHMA22016336002402120000101_01_01_PI2018-08-31 23:59:59.0<NA>명지아동병원<NA>부산광역시 강서구 명지동 3412번지 4호 402,501,601호(국제메디칼빌딩)46726부산광역시 강서구 명지국제8로 240, 402,501,601호 (명지동, 국제메디칼빌딩)20160627<NA><NA><NA><NA>13영업중374905.0179334.020180801155246병원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>74<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>병원<NA>10<NA><NA>42<NA><NA><NA><NA><NA>20180801<NA><NA><NA>1655.81<NA><NA><NA><NA>02021-03-01 05:19:03
145813533260000PHMA11991326002204110001101_01_02_PI2018-08-31 23:59:59.0<NA>동선한의원<NA>부산광역시 서구 암남동 288-549268부산광역시 서구 충무대로 37-1 (암남동)19911220<NA><NA><NA><NA>13영업중383944.518723177715.63014420171229165253한의원051-123-1234<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>0.0<NA><NA><NA>0.0<NA>2021-03-01 05:19:03
374543193320000PHMA12009332004504110001701_01_02_PI2018-08-31 23:59:59.0<NA>서울플란트치과의원616816부산광역시 북구 덕천2동 398번지 13호 8층46548부산광역시 북구 만덕대로 21 (덕천동)20091209<NA><NA><NA><NA>13영업중382786.713466192334.3836620170905183849치과의원051-123-1234<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>270.83<NA><NA><NA>0.0<NA>2021-03-01 05:19:04
220127723290000PHMA12008329002404110004601_01_02_PI2018-08-31 23:59:59.0<NA>효정의료소비자협동조합효림의원614010부산광역시 부산진구 가야동 602번지 7호<NA>부산광역시 부산진구 가야공원로 44 (가야동)2008100920090317<NA><NA><NA>3폐업384975.757099185572.5799520120917142138의원051-123-1234<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>179.4<NA><NA><NA>0.0<NA>2021-03-01 05:19:03
7856683290000PHMA22006329002402120000101_01_01_PI2018-08-31 23:59:59.0<NA>굿모닝요양병원614102부산광역시 부산진구 당감동 975번지47261부산광역시 부산진구 가야대로 713, 지상10~14층 (당감동)2006042620180321<NA><NA><NA>3폐업386750.216975186502.56430120180321082436요양병원(일반요양병원)051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>142<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>요양병원(일반요양병원)<NA>10<NA><NA>18<NA><NA><NA><NA><NA>20180321<NA><NA><NA>1861.85<NA><NA><NA><NA>02021-03-01 05:19:03
13025135993310000PHMD12010331002408400000401_01_06_PI2018-08-31 23:59:59.0<NA>오복당건재약국608811부산광역시 남구 대연1동 1729번지 3호608811부산광역시 남구 수영로 248 (대연동)2010020120150318<NA><NA><NA>3폐업390830.415758184073.20135120150318105022<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>127.4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20100201<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:06
209926673290000PHMA11980329002404110000201_01_02_PI2018-08-31 23:59:59.0<NA>김진철비뇨기과의원614030부산광역시 부산진구 부전동 485번지 17호<NA>부산광역시 부산진구 가야대로 775-1 (부전동)1980032420141028<NA><NA><NA>3폐업387381.144583186550.86327720141028142841의원051-123-1234<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>2021-03-01 05:19:03
14237148103350000PHMD11999335002408400000101_01_06_PI2018-08-31 23:59:59.0<NA>참약국609819부산광역시 금정구 부곡3동 223번지 71호 1층46276부산광역시 금정구 중앙대로1719번길 16, 1층 (부곡동)19990330<NA><NA><NA><NA>13영업중390371.667581195497.55611820140603163008<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>137.82<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990330<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:07
999385643390000PHMA12016339002304110000301_01_02_PI2018-08-31 23:59:59.0<NA>단디치과의원<NA><NA>47052부산광역시 사상구 학감대로 117, 3층 (학장동, (주)세원)20161124<NA><NA><NA><NA>13영업중381235.503179184628.67846820170905183850치과의원051-123-1234<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>196.0<NA><NA><NA>0.0<NA>2021-03-01 05:19:05
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelnursecntnursaidcntbdnglayercntemercargenemercarspecrescntpomfacilaretcstfcntetcepcntmmknurmarbtrmarbtpnumsicbnumastnepnumofearwarmarfacilmngnumpharmtrdarnutrcntbbrmarbabyrglstnummitmdcdepnmmitmdcasgntypebatrarmetrorgassrnmmetrbosassrnmmetrpnumpgrmarpwnmrglstnumhstrmnumqutnownernumjoriwontoilarepcntjisgnumlayasgnymdasgncancelymdundernumlaymedextritemscnmedextritemscnnmtotartotepnumfrstasgnymdcopnumstoretrdarpmtbednumlast_load_dttm
938899583310000PHMH32014331002408750001401_01_05_PI2018-08-31 23:59:59.0<NA>씨유 대연용소점608809부산광역시 남구 대연동 362번지 7호48498부산광역시 남구 수영로266번길 69 (대연동)20140922<NA><NA><NA><NA>13영업중391295.940867183967.31684320140922173437<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>43.0<NA>2021-03-01 05:19:05
279533643300000PHMA12011330002404110001501_01_02_PI2018-08-31 23:59:59.0<NA>신세계마취통증의학과 의원607842부산광역시 동래구 온천3동 1412번지 7호<NA>부산광역시 동래구 아시아드대로 226 (온천동)2011060320140501<NA><NA><NA>3폐업388261.622134191671.45170120140501094531의원051-123-1234<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>237.12<NA><NA><NA>0.0<NA>2021-03-01 05:19:03
14129147013350000PHMD11999335002408400001201_01_06_PI2018-08-31 23:59:59.0<NA>영생당약국609320부산광역시 금정구 부곡동 873번지 31호<NA>부산광역시 금정구 오시게로 40 (부곡동)1999052520000821<NA><NA><NA>3폐업390044.896904193602.64959120090120165354<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990525<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:07
717077433370000PHMA12005337002204110001801_01_02_PI2018-08-31 23:59:59.0<NA>쿨한의원611815부산광역시 연제구 연산동 1023번지 5호 외 1필지 2층47583부산광역시 연제구 고분로 118, 2층 (연산동)20050915<NA><NA><NA><NA>13영업중390852.893723189697.2652120180307134717한의원051-123-1234<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>100.45<NA><NA><NA>0.0<NA>2021-03-01 05:19:04
13227138013320000PHMD11999332004508400000301_01_06_PI2018-08-31 23:59:59.0<NA>구포시장약국616801부산광역시 북구 구포1동 598번지 4호46581부산광역시 북구 낙동대로 1774 (구포동)19990911<NA><NA><NA><NA>13영업중382430.883939192149.85525320120109094307<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>68.4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:06
605866323350000PHMA11995335002404110001401_01_02_PI2018-08-31 23:59:59.0<NA>김동일치과의원609310부산광역시 금정구 구서동 413번지 1호<NA>부산광역시 금정구 구서로 29 (구서동)1995050619960402<NA><NA><NA>3폐업390043.529094196466.89726320090203140920치과의원051-123-1234<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>2021-03-01 05:19:04
764782263380000PHMA12017338002304110001501_01_02_PI2018-08-31 23:59:59.0<NA>마인드풀정신건강의학과의원<NA><NA>48228부산광역시 수영구 수영로 699, 8층 801호 (수영동, 수영동디온플레이스)20170711<NA><NA><NA><NA>13영업중392768.421243187779.78491420170905183859의원051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>의원<NA>2<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA>360.21<NA><NA><NA>0.0<NA>2021-03-01 05:19:04
486554323330000PHMA11997333002404110000901_01_02_PI2018-08-31 23:59:59.0<NA>지창하비뇨기과의원612837좌동48078부산광역시 해운대구 좌동순환로 174, 302호 (좌동, 거성프라자)19970310<NA><NA><NA><NA>13영업중398143.158398188967.80964120170905183858의원051-123-1234<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>2021-03-01 05:19:04
13475140443330000PHMD12009333002408400001501_01_06_PI2018-08-31 23:59:59.0<NA>소나무약국612051부산광역시 해운대구 재송1동 1094번지 29호<NA>부산광역시 해운대구 해운대로 133 (재송동)2009073120090803<NA><NA><NA>3폐업393227.875223189714.40427320090803112637<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>56.7<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20090731<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:06
12045126033280000PHMD12009328002308400000401_01_06_PI2018-08-31 23:59:59.0<NA>뉴맘모스약국606012부산광역시 영도구 대교동2가 91번지 1호606012부산광역시 영도구 태종로 93 (대교동2가)2009040720141231<NA><NA><NA>3폐업386146.48718179191.084920141231143025<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>132.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20090407<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:19:06