Overview

Dataset statistics

Number of variables12
Number of observations511
Missing cells2025
Missing cells (%)33.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.5 KiB
Average record size in memory99.3 B

Variable types

Categorical5
Text4
Numeric3

Dataset

Description한국원자력의학원 원자력병원 비급여진료비 최저비용, 최고비용(행위, 치료재료, 제증명수수료, 약제)현황입니다.
Author한국원자력의학원
URLhttps://www.data.go.kr/data/15038588/fileData.do

Alerts

WORKGUBN has constant value ""Constant
비용 is highly overall correlated with 약제 포함High correlation
최저비용 is highly overall correlated with 최대비용 and 1 other fieldsHigh correlation
최대비용 is highly overall correlated with 최저비용 and 1 other fieldsHigh correlation
중분류 is highly overall correlated with 소분류 and 1 other fieldsHigh correlation
소분류 is highly overall correlated with 중분류 and 1 other fieldsHigh correlation
약제 포함 is highly overall correlated with 비용High correlation
특이사항 is highly overall correlated with 최저비용 and 3 other fieldsHigh correlation
약제 포함 is highly imbalanced (94.4%)Imbalance
특이사항 is highly imbalanced (50.2%)Imbalance
코드 has 93 (18.2%) missing valuesMissing
구분 has 462 (90.4%) missing valuesMissing
비용 has 59 (11.5%) missing valuesMissing
최저비용 has 452 (88.5%) missing valuesMissing
최대비용 has 452 (88.5%) missing valuesMissing
재료 포함 has 507 (99.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 17:32:31.371035
Analysis finished2023-12-12 17:32:33.717013
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

중분류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
자기공명영상진단료(MRI)
213 
검사료
106 
처치 및 수술료
61 
초음파 검사료
39 
치과의 보철료
36 
Other values (4)
56 

Length

Max length14
Median length13
Mean length9.1800391
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자기공명영상진단료(MRI) 213
41.7%
검사료 106
20.7%
처치 및 수술료 61
 
11.9%
초음파 검사료 39
 
7.6%
치과의 보철료 36
 
7.0%
이학요법료 32
 
6.3%
영상진단 및 방사선치료료 10
 
2.0%
상급병실료차액 9
 
1.8%
기본진료료 5
 
1.0%

Length

2023-12-13T02:32:33.788577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:32:33.938324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자기공명영상진단료(mri 213
29.3%
검사료 145
19.9%
및 71
 
9.8%
처치 61
 
8.4%
수술료 61
 
8.4%
초음파 39
 
5.4%
치과의 36
 
4.9%
보철료 36
 
4.9%
이학요법료 32
 
4.4%
영상진단 10
 
1.4%
Other values (3) 24
 
3.3%

소분류
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
기타
72 
복부
46 
<NA>
43 
초음파 검사료
40 
두경부
32 
Other values (44)
278 

Length

Max length13
Median length11
Mean length3.9217221
Min length1

Unique

Unique15 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
기타 72
14.1%
복부 46
 
9.0%
<NA> 43
 
8.4%
초음파 검사료 40
 
7.8%
두경부 32
 
6.3%
근골격계 31
 
6.1%
혈관 29
 
5.7%
척추 23
 
4.5%
특수검사 22
 
4.3%
수술료 21
 
4.1%
Other values (39) 152
29.7%

Length

2023-12-13T02:32:34.090612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 72
 
12.9%
복부 46
 
8.2%
na 43
 
7.7%
초음파 40
 
7.2%
검사료 40
 
7.2%
두경부 32
 
5.7%
근골격계 31
 
5.6%
혈관 29
 
5.2%
척추 23
 
4.1%
특수검사 22
 
3.9%
Other values (46) 180
32.3%

명칭
Text

Distinct490
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T02:32:34.350779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length32
Mean length15.320939
Min length2

Characters and Unicode

Total characters7829
Distinct characters337
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique475 ?
Unique (%)93.0%

Sample

1st row1인실 입원료
2nd rowVIP실 입원료
3rd row간호간병 1인실 입원료
4th row실료차호스피스1인실(1H)
5th row특실(SR) 입원료
ValueCountFrequency (%)
판독료 60
 
5.1%
사용 57
 
4.9%
mri 46
 
3.9%
외부필름:mr 31
 
2.7%
mr 23
 
2.0%
20
 
1.7%
조영제 18
 
1.5%
초음파 18
 
1.5%
제한적 12
 
1.0%
외부필름 10
 
0.9%
Other values (594) 873
74.7%
2023-12-13T02:32:34.803171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
697
 
8.9%
( 275
 
3.5%
) 275
 
3.5%
e 251
 
3.2%
R 240
 
3.1%
M 228
 
2.9%
i 222
 
2.8%
n 214
 
2.7%
o 187
 
2.4%
I 180
 
2.3%
Other values (327) 5060
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2653
33.9%
Lowercase Letter 2180
27.8%
Uppercase Letter 1455
18.6%
Space Separator 697
 
8.9%
Open Punctuation 275
 
3.5%
Close Punctuation 275
 
3.5%
Decimal Number 122
 
1.6%
Other Punctuation 111
 
1.4%
Dash Punctuation 59
 
0.8%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 114
 
4.3%
사 111
 
4.2%
제 91
 
3.4%
용 76
 
2.9%
영 75
 
2.8%
조 73
 
2.8%
부 71
 
2.7%
판 67
 
2.5%
독 66
 
2.5%
외 61
 
2.3%
Other values (255) 1848
69.7%
Lowercase Letter
ValueCountFrequency (%)
e 251
11.5%
i 222
10.2%
n 214
9.8%
o 187
 
8.6%
a 174
 
8.0%
r 174
 
8.0%
t 158
 
7.2%
l 108
 
5.0%
s 89
 
4.1%
p 83
 
3.8%
Other values (16) 520
23.9%
Uppercase Letter
ValueCountFrequency (%)
R 240
16.5%
M 228
15.7%
I 180
12.4%
A 127
8.7%
C 85
 
5.8%
S 78
 
5.4%
P 77
 
5.3%
T 64
 
4.4%
E 58
 
4.0%
B 51
 
3.5%
Other values (15) 267
18.4%
Decimal Number
ValueCountFrequency (%)
1 35
28.7%
0 21
17.2%
3 18
14.8%
5 15
12.3%
2 11
 
9.0%
4 8
 
6.6%
8 6
 
4.9%
9 5
 
4.1%
6 2
 
1.6%
7 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
: 51
45.9%
, 30
27.0%
& 12
 
10.8%
/ 11
 
9.9%
% 4
 
3.6%
. 3
 
2.7%
Space Separator
ValueCountFrequency (%)
697
100.0%
Open Punctuation
ValueCountFrequency (%)
( 275
100.0%
Close Punctuation
ValueCountFrequency (%)
) 275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3634
46.4%
Hangul 2653
33.9%
Common 1541
19.7%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 114
 
4.3%
사 111
 
4.2%
제 91
 
3.4%
용 76
 
2.9%
영 75
 
2.8%
조 73
 
2.8%
부 71
 
2.7%
판 67
 
2.5%
독 66
 
2.5%
외 61
 
2.3%
Other values (255) 1848
69.7%
Latin
ValueCountFrequency (%)
e 251
 
6.9%
R 240
 
6.6%
M 228
 
6.3%
i 222
 
6.1%
n 214
 
5.9%
o 187
 
5.1%
I 180
 
5.0%
a 174
 
4.8%
r 174
 
4.8%
t 158
 
4.3%
Other values (40) 1606
44.2%
Common
ValueCountFrequency (%)
697
45.2%
( 275
 
17.8%
) 275
 
17.8%
- 59
 
3.8%
: 51
 
3.3%
1 35
 
2.3%
, 30
 
1.9%
0 21
 
1.4%
3 18
 
1.2%
5 15
 
1.0%
Other values (11) 65
 
4.2%
Greek
ValueCountFrequency (%)
α 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5175
66.1%
Hangul 2653
33.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
697
 
13.5%
( 275
 
5.3%
) 275
 
5.3%
e 251
 
4.9%
R 240
 
4.6%
M 228
 
4.4%
i 222
 
4.3%
n 214
 
4.1%
o 187
 
3.6%
I 180
 
3.5%
Other values (61) 2406
46.5%
Hangul
ValueCountFrequency (%)
료 114
 
4.3%
사 111
 
4.2%
제 91
 
3.4%
용 76
 
2.9%
영 75
 
2.8%
조 73
 
2.8%
부 71
 
2.7%
판 67
 
2.5%
독 66
 
2.5%
외 61
 
2.3%
Other values (255) 1848
69.7%
None
ValueCountFrequency (%)
α 1
100.0%

코드
Text

MISSING 

Distinct341
Distinct (%)81.6%
Missing93
Missing (%)18.2%
Memory size4.1 KiB
2023-12-13T02:32:35.161839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.3133971
Min length3

Characters and Unicode

Total characters2221
Distinct characters29
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

Unique316 ?
Unique (%)75.6%

Sample

1st rowAB901
2nd rowAB901
3rd rowAB901
4th rowAB901
5th rowAZ001
ValueCountFrequency (%)
mz006 22
 
5.3%
qz964 14
 
3.3%
ab901 8
 
1.9%
eb471 6
 
1.4%
cz581 5
 
1.2%
fz689 4
 
1.0%
cz977 3
 
0.7%
nz009 3
 
0.7%
fz690 3
 
0.7%
oz304 3
 
0.7%
Other values (331) 347
83.0%
2023-12-13T02:32:35.718712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 287
12.9%
1 260
11.7%
H 221
 
10.0%
2 199
 
9.0%
4 140
 
6.3%
6 129
 
5.8%
3 123
 
5.5%
Z 111
 
5.0%
J 92
 
4.1%
9 82
 
3.7%
Other values (19) 577
26.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1402
63.1%
Uppercase Letter 819
36.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 221
27.0%
Z 111
13.6%
J 92
11.2%
E 80
 
9.8%
I 64
 
7.8%
B 52
 
6.3%
C 47
 
5.7%
F 43
 
5.3%
M 28
 
3.4%
D 21
 
2.6%
Other values (9) 60
 
7.3%
Decimal Number
ValueCountFrequency (%)
0 287
20.5%
1 260
18.5%
2 199
14.2%
4 140
10.0%
6 129
9.2%
3 123
8.8%
9 82
 
5.8%
8 73
 
5.2%
5 58
 
4.1%
7 51
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1402
63.1%
Latin 819
36.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 221
27.0%
Z 111
13.6%
J 92
11.2%
E 80
 
9.8%
I 64
 
7.8%
B 52
 
6.3%
C 47
 
5.7%
F 43
 
5.3%
M 28
 
3.4%
D 21
 
2.6%
Other values (9) 60
 
7.3%
Common
ValueCountFrequency (%)
0 287
20.5%
1 260
18.5%
2 199
14.2%
4 140
10.0%
6 129
9.2%
3 123
8.8%
9 82
 
5.8%
8 73
 
5.2%
5 58
 
4.1%
7 51
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 287
12.9%
1 260
11.7%
H 221
 
10.0%
2 199
 
9.0%
4 140
 
6.3%
6 129
 
5.8%
3 123
 
5.5%
Z 111
 
5.0%
J 92
 
4.1%
9 82
 
3.7%
Other values (19) 577
26.0%

구분
Text

MISSING 

Distinct37
Distinct (%)75.5%
Missing462
Missing (%)90.4%
Memory size4.1 KiB
2023-12-13T02:32:35.999684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.5102041
Min length1

Characters and Unicode

Total characters221
Distinct characters80
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)57.1%

Sample

1st row당뇨병교육
2nd row당뇨병교육
3rd row당뇨병교육
4th row자율신경계이상검사
5th row자율신경계이상검사
ValueCountFrequency (%)
당뇨병교육 3
 
5.3%
자율신경계이상검사 3
 
5.3%
신경 3
 
5.3%
상지,동맥 2
 
3.5%
양측 2
 
3.5%
하지,정맥 2
 
3.5%
하지,동맥 2
 
3.5%
범위별 2
 
3.5%
피부 2
 
3.5%
근골 2
 
3.5%
Other values (33) 34
59.6%
2023-12-13T02:32:36.405963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 18
 
8.1%
지 12
 
5.4%
상 11
 
5.0%
신 10
 
4.5%
8
 
3.6%
맥 8
 
3.6%
부 7
 
3.2%
경 6
 
2.7%
하 6
 
2.7%
측 5
 
2.3%
Other values (70) 130
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 190
86.0%
Other Punctuation 20
 
9.0%
Space Separator 8
 
3.6%
Dash Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 12
 
6.3%
상 11
 
5.8%
신 10
 
5.3%
맥 8
 
4.2%
부 7
 
3.7%
경 6
 
3.2%
하 6
 
3.2%
측 5
 
2.6%
정 5
 
2.6%
사 4
 
2.1%
Other values (63) 116
61.1%
Other Punctuation
ValueCountFrequency (%)
, 18
90.0%
· 1
 
5.0%
. 1
 
5.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 190
86.0%
Common 31
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 12
 
6.3%
상 11
 
5.8%
신 10
 
5.3%
맥 8
 
4.2%
부 7
 
3.7%
경 6
 
3.2%
하 6
 
3.2%
측 5
 
2.6%
정 5
 
2.6%
사 4
 
2.1%
Other values (63) 116
61.1%
Common
ValueCountFrequency (%)
, 18
58.1%
8
25.8%
- 1
 
3.2%
( 1
 
3.2%
) 1
 
3.2%
· 1
 
3.2%
. 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 190
86.0%
ASCII 30
 
13.6%
None 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 18
60.0%
8
26.7%
- 1
 
3.3%
( 1
 
3.3%
) 1
 
3.3%
. 1
 
3.3%
Hangul
ValueCountFrequency (%)
지 12
 
6.3%
상 11
 
5.8%
신 10
 
5.3%
맥 8
 
4.2%
부 7
 
3.7%
경 6
 
3.2%
하 6
 
3.2%
측 5
 
2.6%
정 5
 
2.6%
사 4
 
2.1%
Other values (63) 116
61.1%
None
ValueCountFrequency (%)
· 1
100.0%

비용
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct247
Distinct (%)54.6%
Missing59
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean564706.31
Minimum7210
Maximum15000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T02:32:36.628702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7210
5-th percentile25572
Q1102470
median225260
Q3427187.5
95-th percentile1109614
Maximum15000000
Range14992790
Interquartile range (IQR)324717.5

Descriptive statistics

Standard deviation1624035.6
Coefficient of variation (CV)2.8758942
Kurtosis44.87231
Mean564706.31
Median Absolute Deviation (MAD)145260
Skewness6.4718781
Sum2.5524725 × 108
Variance2.6374916 × 1012
MonotonicityNot monotonic
2023-12-13T02:32:36.823593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
288370 28
 
5.5%
169520 16
 
3.1%
425990 16
 
3.1%
159140 11
 
2.2%
102470 10
 
2.0%
225260 10
 
2.0%
706860 9
 
1.8%
532040 9
 
1.8%
566070 8
 
1.6%
566020 8
 
1.6%
Other values (237) 327
64.0%
(Missing) 59
 
11.5%
ValueCountFrequency (%)
7210 1
0.2%
10300 1
0.2%
10500 1
0.2%
11550 1
0.2%
12650 1
0.2%
13000 1
0.2%
13390 1
0.2%
15000 2
0.4%
17050 1
0.2%
17430 1
0.2%
ValueCountFrequency (%)
15000000 1
0.2%
14000000 1
0.2%
13000000 1
0.2%
12000000 1
0.2%
11000000 1
0.2%
10000000 1
0.2%
9000000 1
0.2%
8000000 1
0.2%
7000000 1
0.2%
6000000 1
0.2%

최저비용
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct47
Distinct (%)79.7%
Missing452
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean427331.86
Minimum10300
Maximum4043630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T02:32:37.001291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10300
5-th percentile20823
Q199240
median324640
Q3497500
95-th percentile1091800
Maximum4043630
Range4033330
Interquartile range (IQR)398260

Descriptive statistics

Standard deviation605745.49
Coefficient of variation (CV)1.417506
Kurtosis22.811756
Mean427331.86
Median Absolute Deviation (MAD)190360
Skewness4.3026373
Sum25212580
Variance3.669276 × 1011
MonotonicityNot monotonic
2023-12-13T02:32:37.156574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
432850 4
 
0.8%
10300 2
 
0.4%
42440 2
 
0.4%
515000 2
 
0.4%
103000 2
 
0.4%
600000 2
 
0.4%
309000 2
 
0.4%
201570 2
 
0.4%
150650 2
 
0.4%
378740 2
 
0.4%
Other values (37) 37
 
7.2%
(Missing) 452
88.5%
ValueCountFrequency (%)
10300 2
0.4%
13470 1
0.2%
21640 1
0.2%
26520 1
0.2%
30900 1
0.2%
31830 1
0.2%
41200 1
0.2%
42440 2
0.4%
51500 1
0.2%
61800 1
0.2%
ValueCountFrequency (%)
4043630 1
0.2%
2164240 1
0.2%
1648000 1
0.2%
1030000 1
0.2%
721000 1
0.2%
680040 1
0.2%
650000 1
0.2%
630170 1
0.2%
600000 2
0.4%
518780 1
0.2%

최대비용
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)78.0%
Missing452
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean816902.37
Minimum32470
Maximum6739370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T02:32:37.344119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32470
5-th percentile60997
Q1277275
median703380
Q3886910
95-th percentile2085488
Maximum6739370
Range6706900
Interquartile range (IQR)609635

Descriptive statistics

Standard deviation989865.66
Coefficient of variation (CV)1.2117307
Kurtosis22.311585
Mean816902.37
Median Absolute Deviation (MAD)326620
Skewness4.121342
Sum48197240
Variance9.7983403 × 1011
MonotonicityNot monotonic
2023-12-13T02:32:37.490995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
703380 7
 
1.4%
824000 3
 
0.6%
159140 2
 
0.4%
1030000 2
 
0.4%
1315520 2
 
0.4%
103000 2
 
0.4%
854020 2
 
0.4%
257500 1
 
0.2%
82400 1
 
0.2%
2000000 1
 
0.2%
Other values (36) 36
 
7.0%
(Missing) 452
88.5%
ValueCountFrequency (%)
32470 1
0.2%
51500 1
0.2%
53050 1
0.2%
61880 1
0.2%
64910 1
0.2%
82400 1
0.2%
103000 2
0.4%
135800 1
0.2%
154500 1
0.2%
159140 2
0.4%
ValueCountFrequency (%)
6739370 1
0.2%
3246350 1
0.2%
2314880 1
0.2%
2060000 1
0.2%
2000000 1
0.2%
1545000 1
0.2%
1315520 2
0.4%
1304910 1
0.2%
1241250 1
0.2%
1030000 2
0.4%

재료 포함
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing507
Missing (%)99.2%
Memory size4.1 KiB
2023-12-13T02:32:37.591365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowX
4th rowX
ValueCountFrequency (%)
o 2
50.0%
x 2
50.0%
2023-12-13T02:32:37.803067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 2
50.0%
X 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 2
50.0%
X 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 2
50.0%
X 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 2
50.0%
X 2
50.0%

약제 포함
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
506 
Y
 
3
X
 
2

Length

Max length4
Median length4
Mean length3.9706458
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> 506
99.0%
Y 3
 
0.6%
X 2
 
0.4%

Length

2023-12-13T02:32:37.945650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:32:38.044898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 506
99.0%
y 3
 
0.6%
x 2
 
0.4%

특이사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct22
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
급여 인정기준 외 실시한 경우 비급여
253 
<NA>
147 
위탁
35 
검진목적
 
20
행위, 치료재료 포함수가
 
14
Other values (17)
42 

Length

Max length20
Median length18
Mean length12.414873
Min length2

Unique

Unique5 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
급여 인정기준 외 실시한 경우 비급여 253
49.5%
<NA> 147
28.8%
위탁 35
 
6.8%
검진목적 20
 
3.9%
행위, 치료재료 포함수가 14
 
2.7%
국외위탁 8
 
1.6%
내시경수기료는 별도 4
 
0.8%
크기,개수 금액상이 3
 
0.6%
언어치료시간별 금액상이 3
 
0.6%
시간,그룹여부에 따라 단가상 3
 
0.6%
Other values (12) 21
 
4.1%

Length

2023-12-13T02:32:38.177394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
비급여 257
14.0%
실시한 255
13.8%
경우 255
13.8%
급여 253
13.7%
외 253
13.7%
인정기준 253
13.7%
na 147
8.0%
위탁 35
 
1.9%
검진목적 20
 
1.1%
행위 14
 
0.8%
Other values (29) 100
 
5.4%

WORKGUBN
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
S
511 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
S 511
100.0%

Length

2023-12-13T02:32:38.302147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:32:38.380382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 511
100.0%

Interactions

2023-12-13T02:32:32.653241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.064205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.359231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.738491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.184364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.459332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:33.135431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.275314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:32:32.555587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:32:38.440673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중분류소분류구분비용최저비용최대비용재료 포함약제 포함특이사항
중분류1.0000.9931.0000.4460.0000.000NaN0.6110.991
소분류0.9931.0001.0000.0000.0000.0000.0000.6110.964
구분1.0001.0001.000NaN1.0001.000NaNNaN1.000
비용0.4460.000NaN1.000NaNNaNNaNNaN0.741
최저비용0.0000.0001.000NaN1.0000.9810.0000.0001.000
최대비용0.0000.0001.000NaN0.9811.0000.0000.0001.000
재료\n포함NaN0.000NaNNaN0.0000.0001.000NaNNaN
약제\n포함0.6110.611NaNNaN0.0000.000NaN1.000NaN
특이사항0.9910.9641.0000.7411.0001.000NaNNaN1.000
2023-12-13T02:32:38.555988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
약제 포함특이사항중분류소분류
약제\n포함1.000NaN0.3470.347
특이사항NaN1.0000.8380.739
중분류0.3470.8381.0000.894
소분류0.3470.7390.8941.000
2023-12-13T02:32:38.656470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용최저비용최대비용중분류소분류약제 포함특이사항
비용1.000NaNNaN0.2200.0001.0000.383
최저비용NaN1.0000.8130.0000.0000.0000.707
최대비용NaN0.8131.0000.0000.0000.0000.707
중분류0.2200.0000.0001.0000.8940.3470.838
소분류0.0000.0000.0000.8941.0000.3470.739
약제\n포함1.0000.0000.0000.3470.3471.000NaN
특이사항0.3830.7070.7070.8380.739NaN1.000

Missing values

2023-12-13T02:32:33.280359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:32:33.447295image/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.
2023-12-13T02:32:33.606075image/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

중분류소분류명칭코드구분비용최저비용최대비용재료 포함약제 포함특이사항WORKGUBN
0상급병실료차액상급병실료차액1인실 입원료AB901<NA>440100<NA><NA><NA><NA><NA>S
1상급병실료차액상급병실료차액VIP실 입원료AB901<NA>613700<NA><NA><NA><NA><NA>S
2상급병실료차액상급병실료차액간호간병 1인실 입원료AB901<NA>457700<NA><NA><NA><NA><NA>S
3상급병실료차액상급병실료차액실료차호스피스1인실(1H)<NA><NA>198500<NA><NA><NA><NA><NA>S
4상급병실료차액상급병실료차액특실(SR) 입원료AB901<NA>485000<NA><NA><NA><NA><NA>S
5기본진료료교육상담료당뇨교육(기본)AZ001당뇨병교육33000<NA><NA><NA><NA><NA>S
6기본진료료교육상담료당뇨교육(기본+인슐린주사법 포함)AZ001당뇨병교육42000<NA><NA><NA><NA><NA>S
7기본진료료교육상담료당뇨교육(인슐린 주사법 단독)AZ001당뇨병교육10500<NA><NA><NA><NA><NA>S
8검사료기타신경인지기능검사(SNSB)<NA><NA>309000<NA><NA><NA><NA>검진목적S
9검사료내시경(상부)수면내시경환자관리료EA002<NA>91980<NA><NA><NA><NA>내시경수기료는 별도S
중분류소분류명칭코드구분비용최저비용최대비용재료 포함약제 포함특이사항WORKGUBN
501이학요법료<NA>주의집중력검사FZ690<NA>120000<NA><NA><NA><NA><NA>S
502초음파 검사료초음파 검사료초음파-등EB471등159140<NA><NA><NA><NA>급여 인정기준 외 실시한 경우 비급여S
503초음파 검사료초음파 검사료초음파-둔부EB471둔부159140<NA><NA><NA><NA>급여 인정기준 외 실시한 경우 비급여S
504검사료내시경소화기 내시경초음파EZ992<NA><NA>324640919800<NA><NA>생검시행여 따라 금액 상이S
505이학요법료<NA>미술심리치료 40분NZ009<NA>80000<NA><NA><NA><NA>시간,그룹여부에 따라 단가상S
506이학요법료<NA>미술심리치료 50분NZ009<NA>90000<NA><NA><NA><NA>시간,그룹여부에 따라 단가상S
507이학요법료<NA>그룹미술심리치료NZ009<NA>70000<NA><NA><NA><NA>시간,그룹여부에 따라 단가상S
508기본진료료상담료비만상담(초진)NPIS0003<NA>30000<NA><NA><NA><NA><NA>S
509기본진료료상담료비만상담(재진)NPIS0003<NA>15000<NA><NA><NA><NA><NA>S
510처치 및 수술료<NA>열감응성겔 외과적 수술부위 통증조절PB0801<NA>100000<NA><NA><NA><NA><NA>S