Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory110.0 B

Variable types

Text2
Numeric6
Boolean1
DateTime2
Categorical1

Dataset

Description근로복지공단 직영병원 진료수가입니다. 수가, 단가, 감액가능품목 여부, 적용일자 등 관련 데이터입니다. 2019년 기준
Author근로복지공단
URLhttps://www.data.go.kr/data/15042045/fileData.do

Alerts

적용종료일자 is highly overall correlated with 산재단가금액 and 6 other fieldsHigh correlation
감액가능품목여부 is highly overall correlated with 적용종료일자High correlation
산재단가금액 is highly overall correlated with 일반단가금액 and 5 other fieldsHigh correlation
일반단가금액 is highly overall correlated with 산재단가금액 and 5 other fieldsHigh correlation
건강단가금액 is highly overall correlated with 산재단가금액 and 5 other fieldsHigh correlation
보호일반단가금액 is highly overall correlated with 산재단가금액 and 5 other fieldsHigh correlation
산재일반단가금액 is highly overall correlated with 산재단가금액 and 5 other fieldsHigh correlation
산재후유단가금액 is highly overall correlated with 산재단가금액 and 5 other fieldsHigh correlation
산재단가금액 has 854 (8.5%) zerosZeros
일반단가금액 has 819 (8.2%) zerosZeros
건강단가금액 has 939 (9.4%) zerosZeros
보호일반단가금액 has 949 (9.5%) zerosZeros
산재일반단가금액 has 854 (8.5%) zerosZeros
산재후유단가금액 has 854 (8.5%) zerosZeros

Reproduction

Analysis started2023-12-12 08:18:53.892738
Analysis finished2023-12-12 08:19:01.719849
Duration7.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수가코드
Text

Distinct9989
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:19:01.989505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.2851
Min length4

Characters and Unicode

Total characters62851
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9987 ?
Unique (%)99.9%

Sample

1st rowBJ5004JB
2nd row91615
3rd rowN2461
4th rowB1185
5th rowUA345
ValueCountFrequency (%)
9.12e+05 9
 
0.1%
9.19e+05 4
 
< 0.1%
yg7310044m 1
 
< 0.1%
xf694p 1
 
< 0.1%
r4004 1
 
< 0.1%
ygor0194 1
 
< 0.1%
j2001002 1
 
< 0.1%
bj5004jb 1
 
< 0.1%
mrm0022 1
 
< 0.1%
domsx 1
 
< 0.1%
Other values (9979) 9979
99.8%
2023-12-12T17:19:02.439599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9190
 
14.6%
1 6090
 
9.7%
2 4801
 
7.6%
4 3393
 
5.4%
D 3225
 
5.1%
3 3221
 
5.1%
5 2905
 
4.6%
O 2384
 
3.8%
6 2315
 
3.7%
C 2028
 
3.2%
Other values (30) 23299
37.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36648
58.3%
Uppercase Letter 26131
41.6%
Dash Punctuation 41
 
0.1%
Other Punctuation 17
 
< 0.1%
Math Symbol 14
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 3225
 
12.3%
O 2384
 
9.1%
C 2028
 
7.8%
B 1593
 
6.1%
A 1462
 
5.6%
R 1405
 
5.4%
S 1278
 
4.9%
E 1245
 
4.8%
N 1169
 
4.5%
G 1033
 
4.0%
Other values (16) 9309
35.6%
Decimal Number
ValueCountFrequency (%)
0 9190
25.1%
1 6090
16.6%
2 4801
13.1%
4 3393
 
9.3%
3 3221
 
8.8%
5 2905
 
7.9%
6 2315
 
6.3%
7 1858
 
5.1%
9 1534
 
4.2%
8 1341
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 16
94.1%
: 1
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Math Symbol
ValueCountFrequency (%)
+ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36720
58.4%
Latin 26131
41.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 3225
 
12.3%
O 2384
 
9.1%
C 2028
 
7.8%
B 1593
 
6.1%
A 1462
 
5.6%
R 1405
 
5.4%
S 1278
 
4.9%
E 1245
 
4.8%
N 1169
 
4.5%
G 1033
 
4.0%
Other values (16) 9309
35.6%
Common
ValueCountFrequency (%)
0 9190
25.0%
1 6090
16.6%
2 4801
13.1%
4 3393
 
9.2%
3 3221
 
8.8%
5 2905
 
7.9%
6 2315
 
6.3%
7 1858
 
5.1%
9 1534
 
4.2%
8 1341
 
3.7%
Other values (4) 72
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62851
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9190
 
14.6%
1 6090
 
9.7%
2 4801
 
7.6%
4 3393
 
5.4%
D 3225
 
5.1%
3 3221
 
5.1%
5 2905
 
4.6%
O 2384
 
3.8%
6 2315
 
3.7%
C 2028
 
3.2%
Other values (30) 23299
37.1%

한글수가명
Text

Distinct9870
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:19:02.787895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length62
Mean length17.9284
Min length2

Characters and Unicode

Total characters179284
Distinct characters858
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9747 ?
Unique (%)97.5%

Sample

1st rowGRASPING FORCEPS WITH NET
2nd row인지재활훈련프로그램(30분당)
3rd row척추고정술-전방고정-경추-경구강접근
4th rowIron Stain(철염색)
5th row부분틀니[1악당]-납의치시적(5단계)
ValueCountFrequency (%)
및 233
 
1.1%
179
 
0.8%
screw 141
 
0.7%
또는 139
 
0.6%
신경인지검사 136
 
0.6%
plate 121
 
0.6%
이상 92
 
0.4%
약물 89
 
0.4%
정 77
 
0.4%
locking 73
 
0.3%
Other values (11603) 20294
94.1%
2023-12-12T17:19:03.410969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11819
 
6.6%
( 4726
 
2.6%
) 4724
 
2.6%
- 3866
 
2.2%
술 2623
 
1.5%
0 2610
 
1.5%
정 2291
 
1.3%
m 2193
 
1.2%
e 2166
 
1.2%
A 2087
 
1.2%
Other values (848) 140179
78.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92877
51.8%
Uppercase Letter 23949
 
13.4%
Lowercase Letter 22552
 
12.6%
Space Separator 11819
 
6.6%
Decimal Number 9659
 
5.4%
Open Punctuation 5722
 
3.2%
Close Punctuation 5717
 
3.2%
Dash Punctuation 3866
 
2.2%
Other Punctuation 2855
 
1.6%
Math Symbol 68
 
< 0.1%
Other values (6) 200
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
술 2623
 
2.8%
정 2291
 
2.5%
절 1526
 
1.6%
부 1513
 
1.6%
제 1464
 
1.6%
관 1461
 
1.6%
경 1387
 
1.5%
사 1351
 
1.5%
이 1284
 
1.4%
료 1110
 
1.2%
Other values (738) 76867
82.8%
Lowercase Letter
ValueCountFrequency (%)
m 2193
 
9.7%
e 2166
 
9.6%
i 1871
 
8.3%
g 1696
 
7.5%
a 1578
 
7.0%
r 1498
 
6.6%
l 1490
 
6.6%
o 1430
 
6.3%
t 1365
 
6.1%
n 1351
 
6.0%
Other values (19) 5914
26.2%
Uppercase Letter
ValueCountFrequency (%)
A 2087
 
8.7%
E 2056
 
8.6%
I 1856
 
7.7%
C 1830
 
7.6%
T 1757
 
7.3%
S 1608
 
6.7%
R 1573
 
6.6%
L 1486
 
6.2%
M 1274
 
5.3%
O 1142
 
4.8%
Other values (16) 7280
30.4%
Other Punctuation
ValueCountFrequency (%)
. 698
24.4%
@ 584
20.5%
/ 555
19.4%
, 260
 
9.1%
: 208
 
7.3%
% 184
 
6.4%
† 134
 
4.7%
* 76
 
2.7%
· 56
 
2.0%
& 49
 
1.7%
Other values (5) 51
 
1.8%
Decimal Number
ValueCountFrequency (%)
0 2610
27.0%
1 1985
20.6%
5 1358
14.1%
2 1354
14.0%
3 835
 
8.6%
4 589
 
6.1%
6 357
 
3.7%
8 231
 
2.4%
7 196
 
2.0%
9 143
 
1.5%
Math Symbol
ValueCountFrequency (%)
~ 40
58.8%
× 12
 
17.6%
∼ 6
 
8.8%
+ 6
 
8.8%
= 2
 
2.9%
> 1
 
1.5%
< 1
 
1.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 26
51.0%
Ⅰ 12
23.5%
Ⅲ 7
 
13.7%
Ⅳ 5
 
9.8%
Ⅴ 1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 4726
82.6%
[ 975
 
17.0%
〔 20
 
0.3%
［ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4724
82.6%
] 972
 
17.0%
〕 20
 
0.3%
］ 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
㎠ 35
83.3%
° 6
 
14.3%
㈜ 1
 
2.4%
Space Separator
ValueCountFrequency (%)
11819
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3866
100.0%
Control
ValueCountFrequency (%)
62
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 35
100.0%
Other Number
ValueCountFrequency (%)
² 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92878
51.8%
Latin 46543
26.0%
Common 39857
22.2%
Greek 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
술 2623
 
2.8%
정 2291
 
2.5%
절 1526
 
1.6%
부 1513
 
1.6%
제 1464
 
1.6%
관 1461
 
1.6%
경 1387
 
1.5%
사 1351
 
1.5%
이 1284
 
1.4%
료 1110
 
1.2%
Other values (739) 76868
82.8%
Latin
ValueCountFrequency (%)
m 2193
 
4.7%
e 2166
 
4.7%
A 2087
 
4.5%
E 2056
 
4.4%
i 1871
 
4.0%
I 1856
 
4.0%
C 1830
 
3.9%
T 1757
 
3.8%
g 1696
 
3.6%
S 1608
 
3.5%
Other values (47) 27423
58.9%
Common
ValueCountFrequency (%)
11819
29.7%
( 4726
 
11.9%
) 4724
 
11.9%
- 3866
 
9.7%
0 2610
 
6.5%
1 1985
 
5.0%
5 1358
 
3.4%
2 1354
 
3.4%
[ 975
 
2.4%
] 972
 
2.4%
Other values (40) 5468
13.7%
Greek
ValueCountFrequency (%)
β 4
66.7%
δ 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92877
51.8%
ASCII 86047
48.0%
Punctuation 134
 
0.1%
None 131
 
0.1%
Number Forms 51
 
< 0.1%
CJK Compat 35
 
< 0.1%
Math Operators 6
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11819
 
13.7%
( 4726
 
5.5%
) 4724
 
5.5%
- 3866
 
4.5%
0 2610
 
3.0%
m 2193
 
2.5%
e 2166
 
2.5%
A 2087
 
2.4%
E 2056
 
2.4%
1 1985
 
2.3%
Other values (78) 47815
55.6%
Hangul
ValueCountFrequency (%)
술 2623
 
2.8%
정 2291
 
2.5%
절 1526
 
1.6%
부 1513
 
1.6%
제 1464
 
1.6%
관 1461
 
1.6%
경 1387
 
1.5%
사 1351
 
1.5%
이 1284
 
1.4%
료 1110
 
1.2%
Other values (738) 76867
82.8%
Punctuation
ValueCountFrequency (%)
† 134
100.0%
None
ValueCountFrequency (%)
· 56
42.7%
〔 20
 
15.3%
〕 20
 
15.3%
× 12
 
9.2%
² 6
 
4.6%
° 6
 
4.6%
β 4
 
3.1%
δ 2
 
1.5%
０ 1
 
0.8%
［ 1
 
0.8%
Other values (3) 3
 
2.3%
CJK Compat
ValueCountFrequency (%)
㎠ 35
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 26
51.0%
Ⅰ 12
23.5%
Ⅲ 7
 
13.7%
Ⅳ 5
 
9.8%
Ⅴ 1
 
2.0%
Math Operators
ValueCountFrequency (%)
∼ 6
100.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 3
100.0%

산재단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5476
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206319.43
Minimum0
Maximum17886920
Zeros854
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:03.561248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12219.5
median21490
Q3181002.5
95-th percentile1040400
Maximum17886920
Range17886920
Interquartile range (IQR)178783

Descriptive statistics

Standard deviation503158.21
Coefficient of variation (CV)2.438734
Kurtosis301.27901
Mean206319.43
Median Absolute Deviation (MAD)21490
Skewness11.193601
Sum2.0631943 × 109
Variance2.5316819 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:03.742811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 854
 
8.5%
47880 55
 
0.5%
11180 33
 
0.3%
18710 29
 
0.3%
4800 27
 
0.3%
15600 27
 
0.3%
18080 25
 
0.2%
8870 24
 
0.2%
9030 24
 
0.2%
16520 24
 
0.2%
Other values (5466) 8878
88.8%
ValueCountFrequency (%)
0 854
8.5%
1 5
 
0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
8540160 1
< 0.1%
6500000 1
< 0.1%
5500000 1
< 0.1%
5056610 1
< 0.1%
4576000 1
< 0.1%
4574520 1
< 0.1%
4420500 1
< 0.1%
4116000 1
< 0.1%

일반단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5588
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean267217.32
Minimum0
Maximum17886920
Zeros819
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:03.915101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12474
median27130
Q3225070
95-th percentile1367098
Maximum17886920
Range17886920
Interquartile range (IQR)222596

Descriptive statistics

Standard deviation630689.34
Coefficient of variation (CV)2.3602113
Kurtosis141.13879
Mean267217.32
Median Absolute Deviation (MAD)27130
Skewness7.776069
Sum2.6721732 × 109
Variance3.9776904 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:04.076005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 819
 
8.2%
69420 55
 
0.5%
16210 32
 
0.3%
27130 28
 
0.3%
22610 27
 
0.3%
6960 27
 
0.3%
26220 24
 
0.2%
12870 24
 
0.2%
13090 24
 
0.2%
23950 24
 
0.2%
Other values (5578) 8916
89.2%
ValueCountFrequency (%)
0 819
8.2%
2 1
 
< 0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
8 4
 
< 0.1%
9 2
 
< 0.1%
10 4
 
< 0.1%
11 7
 
0.1%
12 3
 
< 0.1%
13 3
 
< 0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
12489909 1
< 0.1%
8540160 1
< 0.1%
7332080 1
< 0.1%
6500000 1
< 0.1%
5619170 1
< 0.1%
5577490 1
< 0.1%
5500000 1
< 0.1%
5306950 1
< 0.1%

건강단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5423
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205487.53
Minimum0
Maximum17886920
Zeros939
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:04.246844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11880
median20410
Q3177445
95-th percentile1045000
Maximum17886920
Range17886920
Interquartile range (IQR)175565

Descriptive statistics

Standard deviation503983.17
Coefficient of variation (CV)2.4526217
Kurtosis299.41092
Mean205487.53
Median Absolute Deviation (MAD)20410
Skewness11.153673
Sum2.0548753 × 109
Variance2.5399903 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:04.410138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 939
 
9.4%
47880 55
 
0.5%
11180 33
 
0.3%
18710 28
 
0.3%
15600 27
 
0.3%
4800 27
 
0.3%
18080 26
 
0.3%
16520 24
 
0.2%
8870 24
 
0.2%
9030 24
 
0.2%
Other values (5413) 8793
87.9%
ValueCountFrequency (%)
0 939
9.4%
1 5
 
0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
8540160 1
< 0.1%
6500000 1
< 0.1%
5500000 1
< 0.1%
5056610 1
< 0.1%
4576000 1
< 0.1%
4574520 1
< 0.1%
4420500 1
< 0.1%
4116000 1
< 0.1%

보호일반단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5418
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205474.54
Minimum0
Maximum17886920
Zeros949
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:04.587589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11865.25
median20374.5
Q3177445
95-th percentile1045000
Maximum17886920
Range17886920
Interquartile range (IQR)175579.75

Descriptive statistics

Standard deviation503987.99
Coefficient of variation (CV)2.4528003
Kurtosis299.40049
Mean205474.54
Median Absolute Deviation (MAD)20374.5
Skewness11.15342
Sum2.0547454 × 109
Variance2.540039 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:04.773552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 949
 
9.5%
47880 55
 
0.5%
11180 33
 
0.3%
18710 28
 
0.3%
4800 27
 
0.3%
15600 27
 
0.3%
18080 26
 
0.3%
8870 24
 
0.2%
16520 24
 
0.2%
9030 24
 
0.2%
Other values (5408) 8783
87.8%
ValueCountFrequency (%)
0 949
9.5%
1 5
 
0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
8540160 1
< 0.1%
6500000 1
< 0.1%
5500000 1
< 0.1%
5056610 1
< 0.1%
4576000 1
< 0.1%
4574520 1
< 0.1%
4420500 1
< 0.1%
4116000 1
< 0.1%

산재일반단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5476
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206319.43
Minimum0
Maximum17886920
Zeros854
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:04.956234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12219.5
median21490
Q3181002.5
95-th percentile1040400
Maximum17886920
Range17886920
Interquartile range (IQR)178783

Descriptive statistics

Standard deviation503158.21
Coefficient of variation (CV)2.438734
Kurtosis301.27901
Mean206319.43
Median Absolute Deviation (MAD)21490
Skewness11.193601
Sum2.0631943 × 109
Variance2.5316819 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:05.132237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 854
 
8.5%
47880 55
 
0.5%
11180 33
 
0.3%
18710 29
 
0.3%
4800 27
 
0.3%
15600 27
 
0.3%
18080 25
 
0.2%
8870 24
 
0.2%
9030 24
 
0.2%
16520 24
 
0.2%
Other values (5466) 8878
88.8%
ValueCountFrequency (%)
0 854
8.5%
1 5
 
0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
8540160 1
< 0.1%
6500000 1
< 0.1%
5500000 1
< 0.1%
5056610 1
< 0.1%
4576000 1
< 0.1%
4574520 1
< 0.1%
4420500 1
< 0.1%
4116000 1
< 0.1%

산재후유단가금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5476
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206319.43
Minimum0
Maximum17886920
Zeros854
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:19:05.335721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12219.5
median21490
Q3181002.5
95-th percentile1040400
Maximum17886920
Range17886920
Interquartile range (IQR)178783

Descriptive statistics

Standard deviation503158.21
Coefficient of variation (CV)2.438734
Kurtosis301.27901
Mean206319.43
Median Absolute Deviation (MAD)21490
Skewness11.193601
Sum2.0631943 × 109
Variance2.5316819 × 1011
MonotonicityNot monotonic
2023-12-12T17:19:05.495820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 854
 
8.5%
47880 55
 
0.5%
11180 33
 
0.3%
18710 29
 
0.3%
4800 27
 
0.3%
15600 27
 
0.3%
18080 25
 
0.2%
8870 24
 
0.2%
9030 24
 
0.2%
16520 24
 
0.2%
Other values (5466) 8878
88.8%
ValueCountFrequency (%)
0 854
8.5%
1 5
 
0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
17886920 1
< 0.1%
17160160 1
< 0.1%
8540160 1
< 0.1%
6500000 1
< 0.1%
5500000 1
< 0.1%
5056610 1
< 0.1%
4576000 1
< 0.1%
4574520 1
< 0.1%
4420500 1
< 0.1%
4116000 1
< 0.1%

감액가능품목여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
5235 
False
4765 
ValueCountFrequency (%)
True 5235
52.3%
False 4765
47.6%
2023-12-12T17:19:05.635041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

해당수가입력일자
Date

Distinct1160
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1991-01-01 00:00:00
Maximum2019-12-31 00:00:00
2023-12-12T17:19:06.116361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:06.286271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

적용시작일자
Date

Distinct340
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2014-06-01 00:00:00
Maximum2019-12-15 00:00:00
2023-12-12T17:19:06.439677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:06.600961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

적용종료일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019-12-31
5793 
<NA>
4207 

Length

Max length10
Median length10
Mean length7.4758
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row2019-12-31
3rd row2019-12-31
4th row2019-12-31
5th row2019-12-31

Common Values

ValueCountFrequency (%)
2019-12-31 5793
57.9%
<NA> 4207
42.1%

Length

2023-12-12T17:19:06.802985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:06.938107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-12-31 5793
57.9%
na 4207
42.1%

Interactions

2023-12-12T17:19:00.554801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:55.879621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.805776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.739727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.574269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.725268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:00.721192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.006857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.933828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.890830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.781837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.864809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:00.864115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.132326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.082642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.021501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.935029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.971187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:01.005560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.325476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.248450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.169852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.053410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:00.122073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:01.148371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.510891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.413990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.288023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.179845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:00.287508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:01.290552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:56.666465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:57.571424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:58.433568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:59.314749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:00.402139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:19:07.025697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산재단가금액일반단가금액건강단가금액보호일반단가금액산재일반단가금액산재후유단가금액감액가능품목여부
산재단가금액1.0000.8761.0001.0001.0001.0000.069
일반단가금액0.8761.0000.8760.8760.8760.8760.100
건강단가금액1.0000.8761.0001.0001.0001.0000.069
보호일반단가금액1.0000.8761.0001.0001.0001.0000.069
산재일반단가금액1.0000.8761.0001.0001.0001.0000.069
산재후유단가금액1.0000.8761.0001.0001.0001.0000.069
감액가능품목여부0.0690.1000.0690.0690.0690.0691.000
2023-12-12T17:19:07.148488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용종료일자감액가능품목여부
적용종료일자1.0001.000
감액가능품목여부1.0001.000
2023-12-12T17:19:07.261621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산재단가금액일반단가금액건강단가금액보호일반단가금액산재일반단가금액산재후유단가금액감액가능품목여부적용종료일자
산재단가금액1.0000.9800.9840.9851.0001.0000.0501.000
일반단가금액0.9801.0000.9960.9950.9800.9800.1071.000
건강단가금액0.9840.9961.0000.9990.9840.9840.0501.000
보호일반단가금액0.9850.9950.9991.0000.9850.9850.0501.000
산재일반단가금액1.0000.9800.9840.9851.0001.0000.0501.000
산재후유단가금액1.0000.9800.9840.9851.0001.0000.0501.000
감액가능품목여부0.0500.1070.0500.0500.0500.0501.0001.000
적용종료일자1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T17:19:01.457066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:19:01.639617image/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.

Sample

수가코드한글수가명산재단가금액일반단가금액건강단가금액보호일반단가금액산재일반단가금액산재후유단가금액감액가능품목여부해당수가입력일자적용시작일자적용종료일자
3824BJ5004JBGRASPING FORCEPS WITH NET143000143000143000143000143000143000N2016-07-292016-07-29<NA>
715591615인지재활훈련프로그램(30분당)260002600026000260002600026000Y2019-12-312019-01-012019-12-31
8052N2461척추고정술-전방고정-경추-경구강접근129386018761001293860129386012938601293860Y2007-12-312019-01-012019-12-31
4394B1185Iron Stain(철염색)8280120108280828082808280Y2001-01-012019-01-012019-12-31
9650UA345부분틀니[1악당]-납의치시적(5단계)117650117650113140113140117650117650Y2013-12-312019-01-012019-12-31
6296XF619P흉부 동맥조영 - 늑간동맥(외부병원필름판독료)623509041062350623506235062350Y2013-12-312019-01-012019-12-31
1877RABED20라베드정20mg000000N2013-07-032014-06-01<NA>
8979R4456인공임신중절수술[임신8주초과-12주미만]104070150900104070104070104070104070Y2001-01-012019-01-012019-12-31
1664DOTAMBOC탬보코정 50mg211244211211211211N2018-04-052018-11-01<NA>
2627DITRSB트리손키트주 2g161281792816128161281612816128N2014-07-292018-08-01<NA>
수가코드한글수가명산재단가금액일반단가금액건강단가금액보호일반단가금액산재일반단가금액산재후유단가금액감액가능품목여부해당수가입력일자적용시작일자적용종료일자
4915C4504010Primidone(정량)정밀169502457016950169501695016950Y2013-12-312019-01-012019-12-31
4378B1040RBC Count8701270870870870870Y2001-12-312019-01-012019-12-31
2358DIHALP히아루플러스주(프리필드)743681807436743674367436N2014-04-152015-11-01<NA>
3725YGOR0205LIBRA-kit-T2837908379083790837908379083790N2016-11-222019-04-01<NA>
3880YG7310044M압박용 스타킹 M (허벅지 밴드형, open toe 타입)255712557125571255712557125571N2019-04-032019-11-01<NA>
1124DOLVXC100레복사신정100mg000000N2018-01-262018-02-01<NA>
9091544통원 집중재활관리료(방문당)113100001131011310N2019-10-042019-10-01<NA>
391DOAFRAD안플레이드정100mg(씨제이)129586129129129129N2016-02-252018-08-01<NA>
7906N0737(복잡)관절고정술-족관절에 삼중관절고정술을 실시한 경우478490693810478490478490478490478490Y2015-12-282019-01-012019-12-31
878DOFST120파스틱정120mg(일동제약)000000N2016-02-252018-02-01<NA>