Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory761.7 KiB
Average record size in memory78.0 B

Variable types

Categorical2
Text1
Numeric5

Dataset

Description의원급 의료기관의 표시과목별 상병별 진료비 통계 / 진료일자 기준(심사분은 각 진료년+4개월) (예) 진료년월: 2022.1월~12월, 심사년월: 2022.1월~2023.4월 / 보험자: 건강보험 / 한방상병 제외
URLhttps://www.data.go.kr/data/15055564/fileData.do

Alerts

진료년도 has constant value ""Constant
환자수 is highly overall correlated with 명세서청구건수 and 3 other fieldsHigh correlation
명세서청구건수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
입내원일수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
요양급여비용총액 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
보험자부담금 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
환자수 is highly skewed (γ1 = 33.64604856)Skewed
명세서청구건수 is highly skewed (γ1 = 28.82891797)Skewed
입내원일수 is highly skewed (γ1 = 28.75921458)Skewed
요양급여비용총액 is highly skewed (γ1 = 29.25376539)Skewed
보험자부담금 is highly skewed (γ1 = 31.71654597)Skewed

Reproduction

Analysis started2023-12-12 09:11:16.078791
Analysis finished2023-12-12 09:11:21.092543
Duration5.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-12T18:11:21.176790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:11:21.319790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

표시과목
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반의
696 
내과
 
672
소아청소년과
 
633
가정의학과
 
620
정형외과
 
587
Other values (22)
6792 

Length

Max length12
Median length7
Mean length4.6646
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재활의학과
2nd row정신건강의학과
3rd row신경외과
4th row정형외과
5th row이비인후과

Common Values

ValueCountFrequency (%)
일반의 696
 
7.0%
내과 672
 
6.7%
소아청소년과 633
 
6.3%
가정의학과 620
 
6.2%
정형외과 587
 
5.9%
산부인과 583
 
5.8%
외과 572
 
5.7%
이비인후과 568
 
5.7%
진단방사선과,영상의학과 530
 
5.3%
신경외과 518
 
5.2%
Other values (17) 4021
40.2%

Length

2023-12-12T18:11:21.462560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반의 696
 
7.0%
내과 672
 
6.7%
소아청소년과 633
 
6.3%
가정의학과 620
 
6.2%
정형외과 587
 
5.9%
산부인과 583
 
5.8%
외과 572
 
5.7%
이비인후과 568
 
5.7%
진단방사선과,영상의학과 530
 
5.3%
신경외과 518
 
5.2%
Other values (17) 4021
40.2%

주상병코드
Text

Distinct1621
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:11:22.030553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30000
Distinct characters32
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

Unique93 ?
Unique (%)0.9%

Sample

1st rowG24
2nd rowD46
3rd rowG13
4th rowF52
5th rowI78
ValueCountFrequency (%)
h10 16
 
0.2%
h65 15
 
0.1%
h11 15
 
0.1%
d17 15
 
0.1%
r68 15
 
0.1%
m10 15
 
0.1%
n64 14
 
0.1%
e03 14
 
0.1%
s63 14
 
0.1%
r31 14
 
0.1%
Other values (1611) 9853
98.5%
2023-12-12T18:11:22.736318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2584
 
8.6%
1 2216
 
7.4%
2 2163
 
7.2%
3 2075
 
6.9%
4 1990
 
6.6%
5 1963
 
6.5%
6 1893
 
6.3%
8 1789
 
6.0%
7 1666
 
5.6%
9 1661
 
5.5%
Other values (22) 10000
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20000
66.7%
Uppercase Letter 10000
33.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 710
 
7.1%
R 627
 
6.3%
M 620
 
6.2%
K 596
 
6.0%
C 592
 
5.9%
N 580
 
5.8%
L 555
 
5.5%
I 535
 
5.3%
D 534
 
5.3%
T 500
 
5.0%
Other values (12) 4151
41.5%
Decimal Number
ValueCountFrequency (%)
0 2584
12.9%
1 2216
11.1%
2 2163
10.8%
3 2075
10.4%
4 1990
10.0%
5 1963
9.8%
6 1893
9.5%
8 1789
8.9%
7 1666
8.3%
9 1661
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 20000
66.7%
Latin 10000
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 710
 
7.1%
R 627
 
6.3%
M 620
 
6.2%
K 596
 
6.0%
C 592
 
5.9%
N 580
 
5.8%
L 555
 
5.5%
I 535
 
5.3%
D 534
 
5.3%
T 500
 
5.0%
Other values (12) 4151
41.5%
Common
ValueCountFrequency (%)
0 2584
12.9%
1 2216
11.1%
2 2163
10.8%
3 2075
10.4%
4 1990
10.0%
5 1963
9.8%
6 1893
9.5%
8 1789
8.9%
7 1666
8.3%
9 1661
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2584
 
8.6%
1 2216
 
7.4%
2 2163
 
7.2%
3 2075
 
6.9%
4 1990
 
6.6%
5 1963
 
6.5%
6 1893
 
6.3%
8 1789
 
6.0%
7 1666
 
5.6%
9 1661
 
5.5%
Other values (22) 10000
33.3%

환자수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2295
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11975.336
Minimum1
Maximum8902566
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:11:22.903735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median24
Q3305.25
95-th percentile15787.7
Maximum8902566
Range8902565
Interquartile range (IQR)302.25

Descriptive statistics

Standard deviation151506.02
Coefficient of variation (CV)12.651505
Kurtosis1543.962
Mean11975.336
Median Absolute Deviation (MAD)23
Skewness33.646049
Sum1.1975336 × 108
Variance2.2954075 × 1010
MonotonicityNot monotonic
2023-12-12T18:11:23.098422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1413
 
14.1%
2 693
 
6.9%
3 450
 
4.5%
4 367
 
3.7%
5 277
 
2.8%
6 218
 
2.2%
7 176
 
1.8%
8 156
 
1.6%
9 148
 
1.5%
10 136
 
1.4%
Other values (2285) 5966
59.7%
ValueCountFrequency (%)
1 1413
14.1%
2 693
6.9%
3 450
 
4.5%
4 367
 
3.7%
5 277
 
2.8%
6 218
 
2.2%
7 176
 
1.8%
8 156
 
1.6%
9 148
 
1.5%
10 136
 
1.4%
ValueCountFrequency (%)
8902566 1
< 0.1%
5780056 1
< 0.1%
3695455 1
< 0.1%
3447522 1
< 0.1%
3417555 1
< 0.1%
3096800 1
< 0.1%
2755930 1
< 0.1%
2569570 1
< 0.1%
2466664 1
< 0.1%
2428789 1
< 0.1%

명세서청구건수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2795
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27435.626
Minimum1
Maximum15869981
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:11:23.268374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median51
Q3618
95-th percentile34407.75
Maximum15869981
Range15869980
Interquartile range (IQR)612

Descriptive statistics

Standard deviation336616.56
Coefficient of variation (CV)12.269323
Kurtosis1039.7039
Mean27435.626
Median Absolute Deviation (MAD)50
Skewness28.828918
Sum2.7435626 × 108
Variance1.1331071 × 1011
MonotonicityNot monotonic
2023-12-12T18:11:23.431250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1026
 
10.3%
2 536
 
5.4%
3 374
 
3.7%
4 286
 
2.9%
5 203
 
2.0%
6 186
 
1.9%
8 161
 
1.6%
7 160
 
1.6%
9 130
 
1.3%
11 119
 
1.2%
Other values (2785) 6819
68.2%
ValueCountFrequency (%)
1 1026
10.3%
2 536
5.4%
3 374
 
3.7%
4 286
 
2.9%
5 203
 
2.0%
6 186
 
1.9%
7 160
 
1.6%
8 161
 
1.6%
9 130
 
1.3%
10 108
 
1.1%
ValueCountFrequency (%)
15869981 1
< 0.1%
13179001 1
< 0.1%
11758835 1
< 0.1%
9842291 1
< 0.1%
7668021 1
< 0.1%
7273668 1
< 0.1%
6407487 1
< 0.1%
5707339 1
< 0.1%
5475307 1
< 0.1%
5433771 1
< 0.1%

입내원일수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2800
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27621.719
Minimum0
Maximum15863801
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:11:23.631625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median52
Q3639
95-th percentile35740.5
Maximum15863801
Range15863801
Interquartile range (IQR)633

Descriptive statistics

Standard deviation337029.8
Coefficient of variation (CV)12.201623
Kurtosis1035.5062
Mean27621.719
Median Absolute Deviation (MAD)51
Skewness28.759215
Sum2.7621719 × 108
Variance1.1358908 × 1011
MonotonicityNot monotonic
2023-12-12T18:11:23.829986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1027
 
10.3%
2 531
 
5.3%
3 366
 
3.7%
4 275
 
2.8%
5 200
 
2.0%
6 189
 
1.9%
8 157
 
1.6%
7 153
 
1.5%
9 134
 
1.3%
11 114
 
1.1%
Other values (2790) 6854
68.5%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 1027
10.3%
2 531
5.3%
3 366
 
3.7%
4 275
 
2.8%
5 200
 
2.0%
6 189
 
1.9%
7 153
 
1.5%
8 157
 
1.6%
9 134
 
1.3%
ValueCountFrequency (%)
15863801 1
< 0.1%
13203888 1
< 0.1%
11758910 1
< 0.1%
9818285 1
< 0.1%
7668666 1
< 0.1%
7303391 1
< 0.1%
6413794 1
< 0.1%
5707068 1
< 0.1%
5498653 1
< 0.1%
5434444 1
< 0.1%

요양급여비용총액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8910
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.082091 × 109
Minimum0
Maximum6.3216734 × 1011
Zeros34
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:11:24.018012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16970
Q1170475
median1868095
Q323990140
95-th percentile1.6156621 × 109
Maximum6.3216734 × 1011
Range6.3216734 × 1011
Interquartile range (IQR)23819665

Descriptive statistics

Standard deviation1.2382255 × 1010
Coefficient of variation (CV)11.442896
Kurtosis1163.4374
Mean1.082091 × 109
Median Absolute Deviation (MAD)1844075
Skewness29.253765
Sum1.082091 × 1013
Variance1.5332023 × 1020
MonotonicityNot monotonic
2023-12-12T18:11:24.175436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16970 271
 
2.7%
12130 151
 
1.5%
21180 61
 
0.6%
33940 58
 
0.6%
29100 43
 
0.4%
0 34
 
0.3%
14780 24
 
0.2%
24260 21
 
0.2%
46070 18
 
0.2%
19350 17
 
0.2%
Other values (8900) 9302
93.0%
ValueCountFrequency (%)
0 34
0.3%
3290 3
 
< 0.1%
4430 1
 
< 0.1%
6070 6
 
0.1%
8480 1
 
< 0.1%
8840 4
 
< 0.1%
10020 7
 
0.1%
10590 5
 
0.1%
11490 1
 
< 0.1%
12120 1
 
< 0.1%
ValueCountFrequency (%)
632167337160 1
< 0.1%
532489856780 1
< 0.1%
341373411140 1
< 0.1%
276914768320 1
< 0.1%
240638016130 1
< 0.1%
234180930430 1
< 0.1%
202308075290 1
< 0.1%
199780761290 1
< 0.1%
189899420420 1
< 0.1%
187990391140 1
< 0.1%

보험자부담금
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9002
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2032569 × 108
Minimum0
Maximum5.4442104 × 1011
Zeros34
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:11:24.342773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13330
Q1131822.5
median1466275
Q318703090
95-th percentile1.2068414 × 109
Maximum5.4442104 × 1011
Range5.4442104 × 1011
Interquartile range (IQR)18571268

Descriptive statistics

Standard deviation9.6256205 × 109
Coefficient of variation (CV)11.733901
Kurtosis1398.1393
Mean8.2032569 × 108
Median Absolute Deviation (MAD)1447825
Skewness31.716546
Sum8.2032569 × 1012
Variance9.265257 × 1019
MonotonicityNot monotonic
2023-12-12T18:11:24.485234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11970 206
 
2.1%
8530 93
 
0.9%
15370 60
 
0.6%
14880 53
 
0.5%
10630 50
 
0.5%
0 34
 
0.3%
23940 29
 
0.3%
20500 26
 
0.3%
17060 19
 
0.2%
10380 18
 
0.2%
Other values (8992) 9412
94.1%
ValueCountFrequency (%)
0 34
0.3%
2390 3
 
< 0.1%
3130 1
 
< 0.1%
4270 5
 
0.1%
4570 1
 
< 0.1%
5980 1
 
< 0.1%
6240 2
 
< 0.1%
7020 6
 
0.1%
7340 2
 
< 0.1%
7490 4
 
< 0.1%
ValueCountFrequency (%)
544421038520 1
< 0.1%
381753564810 1
< 0.1%
259972416830 1
< 0.1%
199361566380 1
< 0.1%
192407764370 1
< 0.1%
178287255430 1
< 0.1%
169396512246 1
< 0.1%
147870477570 1
< 0.1%
136570317460 1
< 0.1%
135073773520 1
< 0.1%

Interactions

2023-12-12T18:11:20.078260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.223962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.870779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.567732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.339350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:20.210869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.330768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.001956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.687557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.463028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:20.380265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.475780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.146383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.859724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.612413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:20.543012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.605682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.300597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.009839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.771038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:20.693005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:17.727789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:18.429725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.157772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:19.926246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:11:24.868367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표시과목환자수명세서청구건수입내원일수요양급여비용총액보험자부담금
표시과목1.0000.0740.0500.0500.0510.045
환자수0.0741.0000.9180.9180.8670.961
명세서청구건수0.0500.9181.0001.0000.9180.922
입내원일수0.0500.9181.0001.0000.9180.922
요양급여비용총액0.0510.8670.9180.9181.0000.960
보험자부담금0.0450.9610.9220.9220.9601.000
2023-12-12T18:11:24.974714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자수명세서청구건수입내원일수요양급여비용총액보험자부담금표시과목
환자수1.0000.9760.9740.9470.9440.031
명세서청구건수0.9761.0000.9990.9660.9650.017
입내원일수0.9740.9991.0000.9690.9690.017
요양급여비용총액0.9470.9660.9691.0001.0000.020
보험자부담금0.9440.9650.9691.0001.0000.018
표시과목0.0310.0170.0170.0200.0181.000

Missing values

2023-12-12T18:11:20.841438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:11:21.007737image/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

진료년도표시과목주상병코드환자수명세서청구건수입내원일수요양급여비용총액보험자부담금
197092022재활의학과G241704314313298888024362840
43102022정신건강의학과D4611616520320494720
78502022신경외과G1312121393910352910
65622022정형외과F5213019019020010801498680
151552022이비인후과I78690128312832262712017418220
185892022진단방사선과,영상의학과M5426604398794004822315258301595369250
198382022재활의학과I82588159000120700
179912022진단방사선과,영상의학과C666878783807902034457920
12732022일반의R294987847822283984016532040
17822022내과C1973034103410218168530202198850
진료년도표시과목주상병코드환자수명세서청구건수입내원일수요양급여비용총액보험자부담금
2352022일반의D02673834011215498011172090
123452022소아청소년과A594762621124470837870
177792022비뇨의학과T172223394027340
194502022재활의학과A6961212184170134070
53152022외과G629229629652047304281330
81392022신경외과K9273888833913902443690
183542022진단방사선과,영상의학과I708911300129813137425094870450
144072022안과Q67233179030125430
169002022비뇨의학과C1331010328590312690
29522022내과S644251511353160957660