Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells2221
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory177.0 B

Variable types

Text5
DateTime1
Categorical4
Numeric6
Boolean4

Dataset

Description건강보험심사평가원에서 제공하는 「건강보험 행위 급여·비급여 목록표 및 급여 상대가치점수」 / 건강보험심사평가원 홈페이지 > 제도정책 > 보험인정기준 메뉴에서 확인 가능
URLhttps://www.data.go.kr/data/15067456/fileData.do

Alerts

장구분 is highly overall correlated with 1-2구분 and 1 other fieldsHigh correlation
중복인정여부 is highly overall correlated with 본인부담률80High correlation
본인부담률80 is highly overall correlated with 중복인정여부High correlation
1-2구분 is highly overall correlated with 장구분High correlation
의원단가 is highly overall correlated with 치과병의원단가 and 3 other fieldsHigh correlation
병원급이상단가 is highly overall correlated with 치과병의원단가 and 3 other fieldsHigh correlation
치과병의원단가 is highly overall correlated with 의원단가 and 4 other fieldsHigh correlation
보건기관단가 is highly overall correlated with 의원단가 and 3 other fieldsHigh correlation
한방병원단가 is highly overall correlated with 의원단가 and 4 other fieldsHigh correlation
상대가치점수 is highly overall correlated with 의원단가 and 5 other fieldsHigh correlation
수술여부 is highly overall correlated with 병원급이상단가 and 2 other fieldsHigh correlation
수술여부 is highly imbalanced (87.8%)Imbalance
조산원단가 is highly imbalanced (99.8%)Imbalance
본인부담률50 is highly imbalanced (92.9%)Imbalance
본인부담률80 is highly imbalanced (59.4%)Imbalance
본인부담률90 is highly imbalanced (90.1%)Imbalance
중복인정여부 is highly imbalanced (58.4%)Imbalance
영문명 has 665 (6.7%) missing valuesMissing
상대가치점수 has 400 (4.0%) missing valuesMissing
산정명칭 has 1156 (11.6%) missing valuesMissing
수가코드 has unique valuesUnique
의원단가 has 2221 (22.2%) zerosZeros
병원급이상단가 has 304 (3.0%) zerosZeros
치과병의원단가 has 2029 (20.3%) zerosZeros
보건기관단가 has 2212 (22.1%) zerosZeros
한방병원단가 has 2244 (22.4%) zerosZeros

Reproduction

Analysis started2023-12-12 09:10:25.360791
Analysis finished2023-12-12 09:10:34.226205
Duration8.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수가코드
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:10:34.548182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.7666
Min length5

Characters and Unicode

Total characters77666
Distinct characters33
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 rowHJ241600
2nd rowD5321382
3rd rowD473101B
4th rowAK500
5th rowAB105203
ValueCountFrequency (%)
hj241600 1
 
< 0.1%
l1232e49 1
 
< 0.1%
ha623537 1
 
< 0.1%
l1212a29 1
 
< 0.1%
ha603926 1
 
< 0.1%
d5336300 1
 
< 0.1%
71024 1
 
< 0.1%
d1520016 1
 
< 0.1%
d2253001 1
 
< 0.1%
eb482 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T18:10:35.079506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14473
18.6%
1 9063
11.7%
2 7125
9.2%
5 6525
8.4%
3 6430
8.3%
4 5103
 
6.6%
6 4995
 
6.4%
D 3902
 
5.0%
A 3487
 
4.5%
7 2973
 
3.8%
Other values (23) 13590
17.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61052
78.6%
Uppercase Letter 16614
 
21.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 3902
23.5%
A 3487
21.0%
H 2022
12.2%
B 1498
 
9.0%
L 1474
 
8.9%
C 1106
 
6.7%
E 833
 
5.0%
G 488
 
2.9%
M 441
 
2.7%
F 419
 
2.5%
Other values (13) 944
 
5.7%
Decimal Number
ValueCountFrequency (%)
0 14473
23.7%
1 9063
14.8%
2 7125
11.7%
5 6525
10.7%
3 6430
10.5%
4 5103
 
8.4%
6 4995
 
8.2%
7 2973
 
4.9%
8 2415
 
4.0%
9 1950
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 61052
78.6%
Latin 16614
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 3902
23.5%
A 3487
21.0%
H 2022
12.2%
B 1498
 
9.0%
L 1474
 
8.9%
C 1106
 
6.7%
E 833
 
5.0%
G 488
 
2.9%
M 441
 
2.7%
F 419
 
2.5%
Other values (13) 944
 
5.7%
Common
ValueCountFrequency (%)
0 14473
23.7%
1 9063
14.8%
2 7125
11.7%
5 6525
10.7%
3 6430
10.5%
4 5103
 
8.4%
6 4995
 
8.2%
7 2973
 
4.9%
8 2415
 
4.0%
9 1950
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14473
18.6%
1 9063
11.7%
2 7125
9.2%
5 6525
8.4%
3 6430
8.3%
4 5103
 
6.6%
6 4995
 
6.4%
D 3902
 
5.0%
A 3487
 
4.5%
7 2973
 
3.8%
Other values (23) 13590
17.5%
Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2010-01-31 00:00:00
Maximum2024-07-01 00:00:00
2023-12-12T18:10:35.263654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:35.391485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
Distinct2270
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:10:35.733231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.7433
Min length2

Characters and Unicode

Total characters67433
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1028 ?
Unique (%)10.3%

Sample

1st row다246가(8)(나)2)
2nd row누532가(1)
3rd row누473가
4th row요54(1)
5th row가2가(1)
ValueCountFrequency (%)
누532다(4 146
 
1.5%
요51 134
 
1.3%
바2나(2 127
 
1.3%
누532다(4)주 127
 
1.3%
바2가(2 126
 
1.3%
누532다(2)주 122
 
1.2%
바2가(1 116
 
1.2%
누532다(2 113
 
1.1%
바2나(1 108
 
1.1%
나580다(3 98
 
1.0%
Other values (2262) 8794
87.8%
2023-12-12T18:10:36.285384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7849
11.6%
) 7318
10.9%
( 6248
 
9.3%
1 4823
 
7.2%
4465
 
6.6%
4334
 
6.4%
5 4157
 
6.2%
3833
 
5.7%
3 3581
 
5.3%
3416
 
5.1%
Other values (54) 17409
25.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31368
46.5%
Other Letter 22134
32.8%
Close Punctuation 7318
 
10.9%
Open Punctuation 6248
 
9.3%
Dash Punctuation 353
 
0.5%
Space Separator 11
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4465
20.2%
4334
19.6%
3833
17.3%
3416
15.4%
1616
 
7.3%
1557
 
7.0%
689
 
3.1%
494
 
2.2%
479
 
2.2%
433
 
2.0%
Other values (39) 818
 
3.7%
Decimal Number
ValueCountFrequency (%)
2 7849
25.0%
1 4823
15.4%
5 4157
13.3%
3 3581
11.4%
4 2886
 
9.2%
6 2833
 
9.0%
0 1815
 
5.8%
8 1446
 
4.6%
7 1202
 
3.8%
9 776
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 7318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 353
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45299
67.2%
Hangul 22134
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4465
20.2%
4334
19.6%
3833
17.3%
3416
15.4%
1616
 
7.3%
1557
 
7.0%
689
 
3.1%
494
 
2.2%
479
 
2.2%
433
 
2.0%
Other values (39) 818
 
3.7%
Common
ValueCountFrequency (%)
2 7849
17.3%
) 7318
16.2%
( 6248
13.8%
1 4823
10.6%
5 4157
9.2%
3 3581
7.9%
4 2886
 
6.4%
6 2833
 
6.3%
0 1815
 
4.0%
8 1446
 
3.2%
Other values (5) 2343
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45298
67.2%
Hangul 22134
32.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7849
17.3%
) 7318
16.2%
( 6248
13.8%
1 4823
10.6%
5 4157
9.2%
3 3581
7.9%
4 2886
 
6.4%
6 2833
 
6.3%
0 1815
 
4.0%
8 1446
 
3.2%
Other values (4) 2342
 
5.2%
Hangul
ValueCountFrequency (%)
4465
20.2%
4334
19.6%
3833
17.3%
3416
15.4%
1616
 
7.3%
1557
 
7.0%
689
 
3.1%
494
 
2.2%
479
 
2.2%
433
 
2.0%
Other values (39) 818
 
3.7%
None
ValueCountFrequency (%)
· 1
100.0%
Distinct4436
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:10:36.675567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length122
Median length83
Mean length29.3998
Min length2

Characters and Unicode

Total characters293998
Distinct characters631
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2311 ?
Unique (%)23.1%

Sample

1st row자기공명영상진단-기본검사-전신-조영제 주입 전·후 촬영 판독-판독료
2nd row약물 및 독물-[일반면역검사](정성)_δ-Aminolevulinic Acid
3rd row단백분획[분획분석]-일반_단백분획측정(혈청)
4th row격리실 입원료-1인용
5th row상급종합병원5등급간호관리료적용기본입원료
ValueCountFrequency (%)
1658
 
6.4%
약물 1232
 
4.8%
gene 506
 
2.0%
401
 
1.5%
유전성 388
 
1.5%
유전자검사-염기서열분석-염기서열반응 352
 
1.4%
입원환자군 318
 
1.2%
초과 266
 
1.0%
232
 
0.9%
의·치과 199
 
0.8%
Other values (5261) 20331
78.5%
2023-12-12T18:10:37.338533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15943
 
5.4%
- 15023
 
5.1%
5433
 
1.8%
[ 4899
 
1.7%
] 4896
 
1.7%
4660
 
1.6%
4399
 
1.5%
) 4006
 
1.4%
( 3998
 
1.4%
e 3990
 
1.4%
Other values (621) 226751
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192744
65.6%
Lowercase Letter 27480
 
9.3%
Space Separator 15946
 
5.4%
Dash Punctuation 15023
 
5.1%
Uppercase Letter 9121
 
3.1%
Decimal Number 8999
 
3.1%
Open Punctuation 8904
 
3.0%
Close Punctuation 8903
 
3.0%
Other Punctuation 3827
 
1.3%
Connector Punctuation 2851
 
1.0%
Other values (3) 200
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5433
 
2.8%
4660
 
2.4%
4399
 
2.3%
3942
 
2.0%
3749
 
1.9%
3622
 
1.9%
2818
 
1.5%
2805
 
1.5%
2794
 
1.4%
2787
 
1.4%
Other values (523) 155735
80.8%
Lowercase Letter
ValueCountFrequency (%)
e 3990
14.5%
i 2847
10.4%
n 2383
 
8.7%
a 2375
 
8.6%
o 2094
 
7.6%
r 1787
 
6.5%
l 1631
 
5.9%
t 1287
 
4.7%
p 1177
 
4.3%
s 1055
 
3.8%
Other values (20) 6854
24.9%
Uppercase Letter
ValueCountFrequency (%)
A 903
 
9.9%
G 818
 
9.0%
I 775
 
8.5%
C 727
 
8.0%
T 605
 
6.6%
M 593
 
6.5%
P 558
 
6.1%
B 427
 
4.7%
H 403
 
4.4%
V 388
 
4.3%
Other values (16) 2924
32.1%
Decimal Number
ValueCountFrequency (%)
1 3245
36.1%
2 1271
 
14.1%
5 1104
 
12.3%
3 892
 
9.9%
0 872
 
9.7%
4 765
 
8.5%
8 291
 
3.2%
6 252
 
2.8%
7 195
 
2.2%
9 112
 
1.2%
Letter Number
ValueCountFrequency (%)
34
34.7%
19
19.4%
15
15.3%
13
 
13.3%
5
 
5.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
2
 
2.0%
1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 2254
58.9%
· 1305
34.1%
/ 135
 
3.5%
: 104
 
2.7%
. 12
 
0.3%
% 8
 
0.2%
\ 4
 
0.1%
" 4
 
0.1%
' 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 4899
55.0%
( 3998
44.9%
{ 7
 
0.1%
Close Punctuation
ValueCountFrequency (%)
] 4896
55.0%
) 4006
45.0%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15943
> 99.9%
  3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 94
96.9%
3
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 15023
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2851
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192744
65.6%
Common 64555
 
22.0%
Latin 36672
 
12.5%
Greek 27
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5433
 
2.8%
4660
 
2.4%
4399
 
2.3%
3942
 
2.0%
3749
 
1.9%
3622
 
1.9%
2818
 
1.5%
2805
 
1.5%
2794
 
1.4%
2787
 
1.4%
Other values (523) 155735
80.8%
Latin
ValueCountFrequency (%)
e 3990
 
10.9%
i 2847
 
7.8%
n 2383
 
6.5%
a 2375
 
6.5%
o 2094
 
5.7%
r 1787
 
4.9%
l 1631
 
4.4%
t 1287
 
3.5%
p 1177
 
3.2%
s 1055
 
2.9%
Other values (52) 16046
43.8%
Common
ValueCountFrequency (%)
15943
24.7%
- 15023
23.3%
[ 4899
 
7.6%
] 4896
 
7.6%
) 4006
 
6.2%
( 3998
 
6.2%
1 3245
 
5.0%
_ 2851
 
4.4%
, 2254
 
3.5%
· 1305
 
2.0%
Other values (22) 6135
 
9.5%
Greek
ValueCountFrequency (%)
δ 22
81.5%
γ 2
 
7.4%
α 2
 
7.4%
β 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192735
65.6%
ASCII 99812
33.9%
None 1336
 
0.5%
Number Forms 98
 
< 0.1%
Compat Jamo 9
 
< 0.1%
CJK Compat 5
 
< 0.1%
Math Operators 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15943
16.0%
- 15023
 
15.1%
[ 4899
 
4.9%
] 4896
 
4.9%
) 4006
 
4.0%
( 3998
 
4.0%
e 3990
 
4.0%
1 3245
 
3.3%
_ 2851
 
2.9%
i 2847
 
2.9%
Other values (69) 38114
38.2%
Hangul
ValueCountFrequency (%)
5433
 
2.8%
4660
 
2.4%
4399
 
2.3%
3942
 
2.0%
3749
 
1.9%
3622
 
1.9%
2818
 
1.5%
2805
 
1.5%
2794
 
1.4%
2787
 
1.4%
Other values (522) 155726
80.8%
None
ValueCountFrequency (%)
· 1305
97.7%
δ 22
 
1.6%
  3
 
0.2%
γ 2
 
0.1%
α 2
 
0.1%
β 1
 
0.1%
1
 
0.1%
Number Forms
ValueCountFrequency (%)
34
34.7%
19
19.4%
15
15.3%
13
 
13.3%
5
 
5.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
2
 
2.0%
1
 
1.0%
Compat Jamo
ValueCountFrequency (%)
9
100.0%
CJK Compat
ValueCountFrequency (%)
5
100.0%
Math Operators
ValueCountFrequency (%)
3
100.0%

영문명
Text

MISSING 

Distinct2181
Distinct (%)23.4%
Missing665
Missing (%)6.7%
Memory size156.2 KiB
2023-12-12T18:10:37.680400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length144
Median length97
Mean length39.024531
Min length1

Characters and Unicode

Total characters364294
Distinct characters104
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique853 ?
Unique (%)9.1%

Sample

1st rowMagnetic Resonance Imaging-Whole Body
2nd rowDrug, Toxic Agent Test-δ-Aminolevulinic Acid
3rd rowProtein Electrophoresis-General-Protein Electrophoresis(Serum)
4th rowIsolation Room Patient Care
5th rowInpatient Care
ValueCountFrequency (%)
anesthesia 1506
 
3.7%
for 1492
 
3.7%
drug 1259
 
3.1%
toxic 1229
 
3.1%
agent 1228
 
3.1%
of 1071
 
2.7%
care 755
 
1.9%
general 649
 
1.6%
circuit 646
 
1.6%
inpatient 554
 
1.4%
Other values (2888) 29833
74.2%
2023-12-12T18:10:38.156116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 34460
 
9.5%
32582
 
8.9%
n 25903
 
7.1%
i 25208
 
6.9%
a 24830
 
6.8%
t 23058
 
6.3%
r 20266
 
5.6%
o 19322
 
5.3%
s 14110
 
3.9%
l 11740
 
3.2%
Other values (94) 132815
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 268365
73.7%
Uppercase Letter 47230
 
13.0%
Space Separator 32585
 
8.9%
Dash Punctuation 6302
 
1.7%
Decimal Number 3478
 
1.0%
Other Punctuation 2487
 
0.7%
Close Punctuation 1345
 
0.4%
Open Punctuation 1344
 
0.4%
Connector Punctuation 1087
 
0.3%
Letter Number 52
 
< 0.1%
Other values (2) 19
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 34460
12.8%
n 25903
9.7%
i 25208
9.4%
a 24830
9.3%
t 23058
 
8.6%
r 20266
 
7.6%
o 19322
 
7.2%
s 14110
 
5.3%
l 11740
 
4.4%
c 11532
 
4.3%
Other values (19) 57936
21.6%
Uppercase Letter
ValueCountFrequency (%)
A 6434
13.6%
T 5014
10.6%
C 4937
10.5%
M 3280
 
6.9%
G 3271
 
6.9%
S 3089
 
6.5%
I 2739
 
5.8%
P 2468
 
5.2%
B 2423
 
5.1%
D 2050
 
4.3%
Other values (16) 11525
24.4%
Other Letter
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%
Decimal Number
ValueCountFrequency (%)
1 1513
43.5%
5 639
18.4%
2 435
 
12.5%
3 279
 
8.0%
0 138
 
4.0%
6 116
 
3.3%
7 107
 
3.1%
4 98
 
2.8%
9 79
 
2.3%
8 74
 
2.1%
Letter Number
ValueCountFrequency (%)
22
42.3%
9
17.3%
5
 
9.6%
4
 
7.7%
3
 
5.8%
3
 
5.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 2174
87.4%
/ 167
 
6.7%
· 71
 
2.9%
. 27
 
1.1%
: 26
 
1.0%
& 15
 
0.6%
' 6
 
0.2%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
32582
> 99.9%
  3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 743
55.2%
] 602
44.8%
Open Punctuation
ValueCountFrequency (%)
( 740
55.1%
[ 604
44.9%
Dash Punctuation
ValueCountFrequency (%)
- 6302
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1087
100.0%
Math Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 315589
86.6%
Common 48629
 
13.3%
Greek 58
 
< 0.1%
Hangul 18
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 34460
 
10.9%
n 25903
 
8.2%
i 25208
 
8.0%
a 24830
 
7.9%
t 23058
 
7.3%
r 20266
 
6.4%
o 19322
 
6.1%
s 14110
 
4.5%
l 11740
 
3.7%
c 11532
 
3.7%
Other values (51) 105160
33.3%
Common
ValueCountFrequency (%)
32582
67.0%
- 6302
 
13.0%
, 2174
 
4.5%
1 1513
 
3.1%
_ 1087
 
2.2%
) 743
 
1.5%
( 740
 
1.5%
5 639
 
1.3%
[ 604
 
1.2%
] 602
 
1.2%
Other values (17) 1643
 
3.4%
Hangul
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%
Greek
ValueCountFrequency (%)
α 23
39.7%
δ 22
37.9%
β 13
22.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 364090
99.9%
None 133
 
< 0.1%
Number Forms 52
 
< 0.1%
Hangul 18
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 34460
 
9.5%
32582
 
8.9%
n 25903
 
7.1%
i 25208
 
6.9%
a 24830
 
6.8%
t 23058
 
6.3%
r 20266
 
5.6%
o 19322
 
5.3%
s 14110
 
3.9%
l 11740
 
3.2%
Other values (65) 132611
36.4%
None
ValueCountFrequency (%)
· 71
53.4%
α 23
 
17.3%
δ 22
 
16.5%
β 13
 
9.8%
  3
 
2.3%
1
 
0.8%
Number Forms
ValueCountFrequency (%)
22
42.3%
9
17.3%
5
 
9.6%
4
 
7.7%
3
 
5.8%
3
 
5.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
Hangul
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%
Math Operators
ValueCountFrequency (%)
1
100.0%

1-2구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8649 
1
1351 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 8649
86.5%
1 1351
 
13.5%

Length

2023-12-12T18:10:38.303097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:38.421159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8649
86.5%
1 1351
 
13.5%

수술여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9833 
9
 
167

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9833
98.3%
9 167
 
1.7%

Length

2023-12-12T18:10:38.536207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:38.635614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9833
98.3%
9 167
 
1.7%

의원단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3494
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121521.24
Minimum0
Maximum11468990
Zeros2221
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:38.749238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13715
median29660
Q3114152.5
95-th percentile479755
Maximum11468990
Range11468990
Interquartile range (IQR)110437.5

Descriptive statistics

Standard deviation345462.87
Coefficient of variation (CV)2.8428188
Kurtosis310.56203
Mean121521.24
Median Absolute Deviation (MAD)29660
Skewness13.499263
Sum1.2152124 × 109
Variance1.1934459 × 1011
MonotonicityNot monotonic
2023-12-12T18:10:38.889209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2221
 
22.2%
53610 59
 
0.6%
94480 39
 
0.4%
29240 36
 
0.4%
50360 34
 
0.3%
17530 33
 
0.3%
296870 32
 
0.3%
434710 32
 
0.3%
28110 31
 
0.3%
48780 27
 
0.3%
Other values (3484) 7456
74.6%
ValueCountFrequency (%)
0 2221
22.2%
130 1
 
< 0.1%
250 1
 
< 0.1%
270 1
 
< 0.1%
300 2
 
< 0.1%
330 2
 
< 0.1%
420 1
 
< 0.1%
460 1
 
< 0.1%
470 2
 
< 0.1%
500 1
 
< 0.1%
ValueCountFrequency (%)
11468990 2
< 0.1%
7196940 1
< 0.1%
6428340 1
< 0.1%
5757550 1
< 0.1%
5500000 1
< 0.1%
4576000 1
< 0.1%
4484690 1
< 0.1%
4318170 1
< 0.1%
4311930 1
< 0.1%
4308970 1
< 0.1%

병원급이상단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4478
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152618.78
Minimum0
Maximum9924850
Zeros304
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:39.040740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2400
Q115170
median46775
Q3146160
95-th percentile567310
Maximum9924850
Range9924850
Interquartile range (IQR)130990

Descriptive statistics

Standard deviation402107.14
Coefficient of variation (CV)2.634716
Kurtosis134.877
Mean152618.78
Median Absolute Deviation (MAD)38240
Skewness9.5284385
Sum1.5261878 × 109
Variance1.6169015 × 1011
MonotonicityNot monotonic
2023-12-12T18:10:39.173145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 304
 
3.0%
46390 59
 
0.6%
24330 52
 
0.5%
81760 39
 
0.4%
25300 36
 
0.4%
43580 35
 
0.4%
15170 33
 
0.3%
376180 32
 
0.3%
256900 32
 
0.3%
60840 28
 
0.3%
Other values (4468) 9350
93.5%
ValueCountFrequency (%)
0 304
3.0%
110 1
 
< 0.1%
220 2
 
< 0.1%
230 1
 
< 0.1%
260 3
 
< 0.1%
290 2
 
< 0.1%
370 1
 
< 0.1%
400 2
 
< 0.1%
430 1
 
< 0.1%
450 1
 
< 0.1%
ValueCountFrequency (%)
9924850 2
< 0.1%
6227970 2
< 0.1%
5562850 1
 
< 0.1%
5500000 1
 
< 0.1%
5480620 2
< 0.1%
5183790 2
< 0.1%
4982380 4
< 0.1%
4729770 1
 
< 0.1%
4576000 1
 
< 0.1%
4474110 2
< 0.1%

치과병의원단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3628
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123725.26
Minimum0
Maximum11581070
Zeros2029
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:39.309630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15517.5
median32760
Q3116150
95-th percentile484435.5
Maximum11581070
Range11581070
Interquartile range (IQR)110632.5

Descriptive statistics

Standard deviation348403
Coefficient of variation (CV)2.8159407
Kurtosis311.60808
Mean123725.26
Median Absolute Deviation (MAD)32760
Skewness13.520792
Sum1.2372526 × 109
Variance1.2138465 × 1011
MonotonicityNot monotonic
2023-12-12T18:10:39.433559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2029
 
20.3%
54130 59
 
0.6%
28390 51
 
0.5%
95400 39
 
0.4%
29530 36
 
0.4%
50850 34
 
0.3%
17700 33
 
0.3%
438950 32
 
0.3%
299770 32
 
0.3%
49250 27
 
0.3%
Other values (3618) 7628
76.3%
ValueCountFrequency (%)
0 2029
20.3%
130 1
 
< 0.1%
260 1
 
< 0.1%
270 1
 
< 0.1%
300 2
 
< 0.1%
330 2
 
< 0.1%
430 1
 
< 0.1%
470 2
 
< 0.1%
480 1
 
< 0.1%
500 1
 
< 0.1%
ValueCountFrequency (%)
11581070 2
< 0.1%
7267270 1
< 0.1%
6491160 1
< 0.1%
5813820 1
< 0.1%
5500000 1
< 0.1%
4576000 1
< 0.1%
4528510 1
< 0.1%
4360360 1
< 0.1%
4354060 1
< 0.1%
4351070 1
< 0.1%

보건기관단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3504
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120096.18
Minimum0
Maximum11332010
Zeros2212
Zeros (%)22.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:39.876940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13745
median29310
Q3112667.5
95-th percentile474025
Maximum11332010
Range11332010
Interquartile range (IQR)108922.5

Descriptive statistics

Standard deviation341602.37
Coefficient of variation (CV)2.8444066
Kurtosis310.05533
Mean120096.18
Median Absolute Deviation (MAD)29310
Skewness13.494267
Sum1.2009618 × 109
Variance1.1669218 × 1011
MonotonicityNot monotonic
2023-12-12T18:10:40.009235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2212
 
22.1%
52970 59
 
0.6%
27780 51
 
0.5%
93350 39
 
0.4%
28890 36
 
0.4%
49750 34
 
0.3%
17320 33
 
0.3%
429510 32
 
0.3%
293320 32
 
0.3%
48200 27
 
0.3%
Other values (3494) 7445
74.5%
ValueCountFrequency (%)
0 2212
22.1%
130 1
 
< 0.1%
250 1
 
< 0.1%
260 1
 
< 0.1%
300 2
 
< 0.1%
330 2
 
< 0.1%
420 1
 
< 0.1%
460 2
 
< 0.1%
470 1
 
< 0.1%
490 1
 
< 0.1%
ValueCountFrequency (%)
11332010 2
< 0.1%
7110990 1
< 0.1%
6351560 1
< 0.1%
5688790 1
< 0.1%
5500000 1
< 0.1%
4576000 1
< 0.1%
4431120 1
< 0.1%
4266590 1
< 0.1%
4260430 1
< 0.1%
4257500 1
< 0.1%

조산원단가
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9997 
603540
 
1
4950
 
1
14320
 
1

Length

Max length6
Median length1
Mean length1.0012
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 9997
> 99.9%
603540 1
 
< 0.1%
4950 1
 
< 0.1%
14320 1
 
< 0.1%

Length

2023-12-12T18:10:40.133494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:40.234071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9997
> 99.9%
603540 1
 
< 0.1%
4950 1
 
< 0.1%
14320 1
 
< 0.1%

한방병원단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3565
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123765.91
Minimum0
Maximum11879940
Zeros2244
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:40.343046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13747.5
median30290
Q3115110
95-th percentile489446
Maximum11879940
Range11879940
Interquartile range (IQR)111362.5

Descriptive statistics

Standard deviation354642.45
Coefficient of variation (CV)2.8654291
Kurtosis320.667
Mean123765.91
Median Absolute Deviation (MAD)30290
Skewness13.742357
Sum1.2376591 × 109
Variance1.2577126 × 1011
MonotonicityNot monotonic
2023-12-12T18:10:40.500167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2244
 
22.4%
55530 59
 
0.6%
29120 51
 
0.5%
97860 39
 
0.4%
30290 36
 
0.4%
52160 34
 
0.3%
18160 33
 
0.3%
450280 32
 
0.3%
307510 32
 
0.3%
50530 27
 
0.3%
Other values (3555) 7413
74.1%
ValueCountFrequency (%)
0 2244
22.4%
130 1
 
< 0.1%
260 1
 
< 0.1%
280 1
 
< 0.1%
310 3
 
< 0.1%
340 2
 
< 0.1%
440 1
 
< 0.1%
480 2
 
< 0.1%
520 1
 
< 0.1%
540 1
 
< 0.1%
ValueCountFrequency (%)
11879940 2
< 0.1%
7454810 1
< 0.1%
6658670 1
< 0.1%
5963850 1
< 0.1%
5500000 1
< 0.1%
4645380 1
< 0.1%
4576000 1
< 0.1%
4472890 1
< 0.1%
4466420 1
< 0.1%
4463360 1
< 0.1%

상대가치점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct5016
Distinct (%)52.2%
Missing400
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean1974.361
Minimum1.38
Maximum124527.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:10:40.668873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.38
5-th percentile57.2495
Q1215.1025
median636.18
Q31975.03
95-th percentile7126.33
Maximum124527.63
Range124526.25
Interquartile range (IQR)1759.9275

Descriptive statistics

Standard deviation5036.2028
Coefficient of variation (CV)2.5508014
Kurtosis136.11653
Mean1974.361
Median Absolute Deviation (MAD)505.955
Skewness9.5135398
Sum18953866
Variance25363339
MonotonicityNot monotonic
2023-12-12T18:10:40.874374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
582.05 59
 
0.6%
1025.79 39
 
0.4%
317.5 36
 
0.4%
546.75 34
 
0.3%
4719.94 32
 
0.3%
190.36 32
 
0.3%
3223.33 32
 
0.3%
305.26 31
 
0.3%
763.41 28
 
0.3%
529.62 27
 
0.3%
Other values (5006) 9250
92.5%
(Missing) 400
 
4.0%
ValueCountFrequency (%)
1.38 1
< 0.1%
2.72 1
< 0.1%
2.75 1
< 0.1%
2.91 1
< 0.1%
3.25 2
< 0.1%
3.3 1
< 0.1%
3.58 2
< 0.1%
4.58 1
< 0.1%
5.01 1
< 0.1%
5.08 1
< 0.1%
ValueCountFrequency (%)
124527.63 2
< 0.1%
78142.7 2
< 0.1%
69797.39 1
 
< 0.1%
68765.58 2
< 0.1%
65041.24 2
< 0.1%
62514.16 4
< 0.1%
59344.67 1
 
< 0.1%
56136.85 2
< 0.1%
55749.63 2
< 0.1%
54074.16 1
 
< 0.1%

본인부담률50
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9915 
True
 
85
ValueCountFrequency (%)
False 9915
99.2%
True 85
 
0.9%
2023-12-12T18:10:40.996105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

본인부담률80
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9190 
True
 
810
ValueCountFrequency (%)
False 9190
91.9%
True 810
 
8.1%
2023-12-12T18:10:41.099066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

본인부담률90
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9871 
True
 
129
ValueCountFrequency (%)
False 9871
98.7%
True 129
 
1.3%
2023-12-12T18:10:41.199062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

중복인정여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9161 
True
 
839
ValueCountFrequency (%)
False 9161
91.6%
True 839
 
8.4%
2023-12-12T18:10:41.305279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

산정명칭
Text

MISSING 

Distinct815
Distinct (%)9.2%
Missing1156
Missing (%)11.6%
Memory size156.2 KiB
2023-12-12T18:10:41.623586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length49
Mean length18.406829
Min length2

Characters and Unicode

Total characters162790
Distinct characters206
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)3.0%

Sample

1st row만6세미만
2nd row진단검사 질가산(3%)
3rd row진단검사 질가산(3%) 진단검사의학과전문의 등 판독
4th row18-24시퇴원 강내치료실
5th row만1세미만
ValueCountFrequency (%)
진단검사 2593
 
9.4%
2143
 
7.8%
판독 1971
 
7.1%
진단검사의학과전문의 1694
 
6.1%
질가산(4 1355
 
4.9%
만6세미만 1031
 
3.7%
질가산(2 648
 
2.3%
질가산(1 645
 
2.3%
질가산(3 642
 
2.3%
핵의학검사 562
 
2.0%
Other values (166) 14358
51.9%
2023-12-12T18:10:42.194698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21118
 
13.0%
5729
 
3.5%
5540
 
3.4%
5262
 
3.2%
5186
 
3.2%
4425
 
2.7%
( 4361
 
2.7%
) 4361
 
2.7%
4321
 
2.7%
3566
 
2.2%
Other values (196) 98921
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114786
70.5%
Space Separator 21118
 
13.0%
Decimal Number 10659
 
6.5%
Other Punctuation 5626
 
3.5%
Open Punctuation 4363
 
2.7%
Close Punctuation 4363
 
2.7%
Math Symbol 854
 
0.5%
Dash Punctuation 527
 
0.3%
Lowercase Letter 353
 
0.2%
Uppercase Letter 141
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5729
 
5.0%
5540
 
4.8%
5262
 
4.6%
5186
 
4.5%
4425
 
3.9%
4321
 
3.8%
3566
 
3.1%
3485
 
3.0%
3307
 
2.9%
3290
 
2.9%
Other values (153) 70675
61.6%
Lowercase Letter
ValueCountFrequency (%)
g 141
39.9%
n 36
 
10.2%
i 33
 
9.3%
e 30
 
8.5%
s 22
 
6.2%
u 21
 
5.9%
o 16
 
4.5%
f 15
 
4.2%
a 7
 
2.0%
t 7
 
2.0%
Other values (5) 25
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 2784
26.1%
6 2088
19.6%
4 1545
14.5%
3 1120
10.5%
2 1015
 
9.5%
0 948
 
8.9%
5 403
 
3.8%
8 264
 
2.5%
7 255
 
2.4%
9 237
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
A 51
36.2%
S 36
25.5%
P 18
 
12.8%
N 15
 
10.6%
R 15
 
10.6%
D 6
 
4.3%
Other Punctuation
ValueCountFrequency (%)
% 3290
58.5%
, 1041
 
18.5%
· 862
 
15.3%
. 433
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 4361
> 99.9%
2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4361
> 99.9%
2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 800
93.7%
+ 54
 
6.3%
Space Separator
ValueCountFrequency (%)
21118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 527
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114786
70.5%
Common 47510
29.2%
Latin 494
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5729
 
5.0%
5540
 
4.8%
5262
 
4.6%
5186
 
4.5%
4425
 
3.9%
4321
 
3.8%
3566
 
3.1%
3485
 
3.0%
3307
 
2.9%
3290
 
2.9%
Other values (153) 70675
61.6%
Common
ValueCountFrequency (%)
21118
44.4%
( 4361
 
9.2%
) 4361
 
9.2%
% 3290
 
6.9%
1 2784
 
5.9%
6 2088
 
4.4%
4 1545
 
3.3%
3 1120
 
2.4%
, 1041
 
2.2%
2 1015
 
2.1%
Other values (12) 4787
 
10.1%
Latin
ValueCountFrequency (%)
g 141
28.5%
A 51
 
10.3%
n 36
 
7.3%
S 36
 
7.3%
i 33
 
6.7%
e 30
 
6.1%
s 22
 
4.5%
u 21
 
4.3%
P 18
 
3.6%
o 16
 
3.2%
Other values (11) 90
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114708
70.5%
ASCII 47138
29.0%
None 866
 
0.5%
Compat Jamo 78
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21118
44.8%
( 4361
 
9.3%
) 4361
 
9.3%
% 3290
 
7.0%
1 2784
 
5.9%
6 2088
 
4.4%
4 1545
 
3.3%
3 1120
 
2.4%
, 1041
 
2.2%
2 1015
 
2.2%
Other values (30) 4415
 
9.4%
Hangul
ValueCountFrequency (%)
5729
 
5.0%
5540
 
4.8%
5262
 
4.6%
5186
 
4.5%
4425
 
3.9%
4321
 
3.8%
3566
 
3.1%
3485
 
3.0%
3307
 
2.9%
3290
 
2.9%
Other values (152) 70597
61.5%
None
ValueCountFrequency (%)
· 862
99.5%
2
 
0.2%
2
 
0.2%
Compat Jamo
ValueCountFrequency (%)
78
100.0%

장구분
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
4387 
3
1818 
6
934 
1
713 
06월 19일
528 
Other values (12)
1620 

Length

Max length7
Median length1
Mean length1.8648
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row요양병원
5th row1

Common Values

ValueCountFrequency (%)
2 4387
43.9%
3 1818
18.2%
6 934
 
9.3%
1 713
 
7.1%
06월 19일 528
 
5.3%
요양병원 477
 
4.8%
03월 19일 423
 
4.2%
9 280
 
2.8%
09월 19일 160
 
1.6%
공상 74
 
0.7%
Other values (7) 206
 
2.1%

Length

2023-12-12T18:10:42.385362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 4387
39.3%
3 1818
16.3%
19일 1167
 
10.5%
6 934
 
8.4%
1 713
 
6.4%
06월 528
 
4.7%
요양병원 477
 
4.3%
03월 423
 
3.8%
9 280
 
2.5%
09월 160
 
1.4%
Other values (8) 280
 
2.5%

Interactions

2023-12-12T18:10:32.467037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:28.700110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.292208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.884798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.569897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.617321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.613592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:28.788821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.387812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.978146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.672786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.733704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.783027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:28.885056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.475414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.105474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.045093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.890141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.958476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:28.983623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.581366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.218790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.163588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.025422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:33.141685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.079790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.685670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.331257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.284442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.177880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:33.291879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.182114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:29.791529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:30.459902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:31.401316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:32.316502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:10:42.517582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용일자1-2구분수술여부의원단가병원급이상단가치과병의원단가보건기관단가조산원단가한방병원단가상대가치점수본인부담률50본인부담률80본인부담률90중복인정여부장구분
적용일자1.0000.2720.0000.5790.2410.5790.4790.8560.5800.0000.1260.0000.0000.0000.645
1-2구분0.2721.0000.0770.0200.0340.0200.0420.0610.0180.0480.0000.1820.0670.1690.987
수술여부0.0000.0771.0000.5520.8050.5520.5570.0000.5230.8310.0000.0370.0090.0580.666
의원단가0.5790.0200.5521.0000.9601.0000.9990.0001.0000.8860.1380.0000.0690.0150.266
병원급이상단가0.2410.0340.8050.9601.0000.9600.9610.0000.9611.0000.0960.0180.0400.0410.411
치과병의원단가0.5790.0200.5521.0000.9601.0000.9990.0001.0000.8860.1380.0000.0690.0150.266
보건기관단가0.4790.0420.5570.9990.9610.9991.0000.0000.9990.8860.1380.0000.0690.0150.284
조산원단가0.8560.0610.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.310
한방병원단가0.5800.0180.5231.0000.9611.0000.9990.0001.0000.8820.1470.0000.0750.0120.253
상대가치점수0.0000.0480.8310.8861.0000.8860.8860.0000.8821.0000.0940.0200.0380.0430.485
본인부담률500.1260.0000.0000.1380.0960.1380.1380.0000.1470.0941.0000.0240.5870.1800.089
본인부담률800.0000.1820.0370.0000.0180.0000.0000.0000.0000.0200.0241.0000.0000.9880.474
본인부담률900.0000.0670.0090.0690.0400.0690.0690.0000.0750.0380.5870.0001.0000.3570.137
중복인정여부0.0000.1690.0580.0150.0410.0150.0150.0000.0120.0430.1800.9880.3571.0000.456
장구분0.6450.9870.6660.2660.4110.2660.2840.3100.2530.4850.0890.4740.1370.4561.000
2023-12-12T18:10:42.714284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본인부담률90본인부담률50수술여부장구분조산원단가중복인정여부본인부담률801-2구분
본인부담률901.0000.4000.0060.1230.0000.2320.0000.043
본인부담률500.4001.0000.0000.0800.0000.1150.0150.000
수술여부0.0060.0001.0000.6070.0000.0370.0240.049
장구분0.1230.0800.6071.0000.1770.4110.4260.995
조산원단가0.0000.0000.0000.1771.0000.0000.0000.040
중복인정여부0.2320.1150.0370.4110.0001.0000.9020.108
본인부담률800.0000.0150.0240.4260.0000.9021.0000.116
1-2구분0.0430.0000.0490.9950.0400.1080.1161.000
2023-12-12T18:10:42.890861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의원단가병원급이상단가치과병의원단가보건기관단가한방병원단가상대가치점수1-2구분수술여부조산원단가본인부담률50본인부담률80본인부담률90중복인정여부장구분
의원단가1.0000.4900.9720.9980.9160.5510.0150.4160.0000.1030.0000.0520.0110.114
병원급이상단가0.4901.0000.5050.4900.5740.9490.0260.6260.0000.0720.0130.0300.0310.186
치과병의원단가0.9720.5051.0000.9740.9400.5670.0150.4160.0000.1030.0000.0520.0110.114
보건기관단가0.9980.4900.9741.0000.9170.5500.0320.4210.0000.1030.0000.0520.0110.123
한방병원단가0.9160.5740.9400.9171.0000.5370.0130.3940.0000.1100.0000.0570.0090.109
상대가치점수0.5510.9490.5670.5500.5371.0000.0360.6510.0000.0710.0150.0290.0320.190
1-2구분0.0150.0260.0150.0320.0130.0361.0000.0490.0400.0000.1160.0430.1080.995
수술여부0.4160.6260.4160.4210.3940.6510.0491.0000.0000.0000.0240.0060.0370.607
조산원단가0.0000.0000.0000.0000.0000.0000.0400.0001.0000.0000.0000.0000.0000.177
본인부담률500.1030.0720.1030.1030.1100.0710.0000.0000.0001.0000.0150.4000.1150.080
본인부담률800.0000.0130.0000.0000.0000.0150.1160.0240.0000.0151.0000.0000.9020.426
본인부담률900.0520.0300.0520.0520.0570.0290.0430.0060.0000.4000.0001.0000.2320.123
중복인정여부0.0110.0310.0110.0110.0090.0320.1080.0370.0000.1150.9020.2321.0000.411
장구분0.1140.1860.1140.1230.1090.1900.9950.6070.1770.0800.4260.1230.4111.000

Missing values

2023-12-12T18:10:33.493564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:10:33.869616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T18:10:34.112702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

수가코드적용일자분류번호한글명영문명1-2구분수술여부의원단가병원급이상단가치과병의원단가보건기관단가조산원단가한방병원단가상대가치점수본인부담률50본인부담률80본인부담률90중복인정여부산정명칭장구분
39772HJ2416002023-01-01다246가(8)(나)2)자기공명영상진단-기본검사-전신-조영제 주입 전·후 촬영 판독-판독료Magnetic Resonance Imaging-Whole Body2021060018225021266020809002181502286.68NYNY만6세미만3
14994D53213822023-01-01누532가(1)약물 및 독물-[일반면역검사](정성)_δ-Aminolevulinic AcidDrug, Toxic Agent Test-δ-Aminolevulinic Acid2059605160602058900617064.71NNNN진단검사 질가산(3%)2
13953D473101B2023-01-01누473가단백분획[분획분석]-일반_단백분획측정(혈청)Protein Electrophoresis-General-Protein Electrophoresis(Serum)2011810102201192011670012230128.19NNNN진단검사 질가산(3%) 진단검사의학과전문의 등 판독2
6270AK5002023-01-01요54(1)격리실 입원료-1인용Isolation Room Patient Care10012546000001574.16NNNN<NA>요양병원
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