Overview

Dataset statistics

Number of variables8
Number of observations249
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory69.5 B

Variable types

Categorical3
Numeric5

Dataset

Description1. 진료년도: 2017~2022년(진료일기준)- 2023년 6월 지급분까지 반영2. 연령: 0~99세(5세 단위), 100세 이상(연도말 기준)3. 건강보험 급여실적(의료급여 제외)이며, 한의분류 및 약국 제외, 비급여 제외- 주상병코드:T67(열 및 빛의 영향), T68(저체온증), T33(표재성 동상), T34(조직괴사를 동반한 동상), T35(여러 신체부위를 침범한 동상 및 상세불명의 동상), T69.0(침수병 및 침족병), T69.1(동창)- 해당 질병통계 자료는 요양기관에서 환자진료 중 진단명이 확정되지 않은 상태에서의 호소, 증세 등에 따라 일차진단명을 부여하고 청구한 내역 중주진단명 기준으로 발췌한 것이므로 최종 확정된 질병과는 다를 수 있음※ 민원인의 공공데이터 제공 신청에 따라 2024-02-14 발췌 및 구성
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15126731/fileData.do

Alerts

진료인원(명) is highly overall correlated with 입내원일수(일) and 2 other fieldsHigh correlation
입내원일수(일) is highly overall correlated with 진료인원(명) and 3 other fieldsHigh correlation
진료건수(건) is highly overall correlated with 진료인원(명) and 3 other fieldsHigh correlation
진료비(천원) is highly overall correlated with 진료인원(명) and 3 other fieldsHigh correlation
공단부담금(천원) is highly overall correlated with 입내원일수(일) and 2 other fieldsHigh correlation
진료비(천원) has unique valuesUnique
공단부담금(천원) has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:13:54.774233
Analysis finished2024-03-14 11:14:02.251939
Duration7.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2018년
42 
2020년
42 
2022년
42 
2017년
41 
2019년
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017년
2nd row2017년
3rd row2017년
4th row2017년
5th row2017년

Common Values

ValueCountFrequency (%)
2018년 42
16.9%
2020년 42
16.9%
2022년 42
16.9%
2017년 41
16.5%
2019년 41
16.5%
2021년 41
16.5%

Length

2024-03-14T20:14:02.456602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:14:02.780687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018년 42
16.9%
2020년 42
16.9%
2022년 42
16.9%
2017년 41
16.5%
2019년 41
16.5%
2021년 41
16.5%

성별
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
여자
126 
남자
123 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여자 126
50.6%
남자 123
49.4%

Length

2024-03-14T20:14:03.152139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:14:03.444860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여자 126
50.6%
남자 123
49.4%

연령
Categorical

Distinct21
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0-4세
 
12
5-9세
 
12
10-14세
 
12
15-19세
 
12
20-24세
 
12
Other values (16)
189 

Length

Max length7
Median length6
Mean length5.8433735
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0-4세
2nd row5-9세
3rd row10-14세
4th row15-19세
5th row20-24세

Common Values

ValueCountFrequency (%)
0-4세 12
 
4.8%
5-9세 12
 
4.8%
10-14세 12
 
4.8%
15-19세 12
 
4.8%
20-24세 12
 
4.8%
25-29세 12
 
4.8%
30-34세 12
 
4.8%
35-39세 12
 
4.8%
40-44세 12
 
4.8%
45-49세 12
 
4.8%
Other values (11) 129
51.8%

Length

2024-03-14T20:14:03.783069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0-4세 12
 
4.7%
5-9세 12
 
4.7%
95-99세 12
 
4.7%
90-94세 12
 
4.7%
85-89세 12
 
4.7%
80-84세 12
 
4.7%
75-79세 12
 
4.7%
70-74세 12
 
4.7%
65-69세 12
 
4.7%
60-64세 12
 
4.7%
Other values (12) 138
53.5%

진료인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct231
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean922.38153
Minimum1
Maximum2736
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-14T20:14:04.147413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.4
Q1472
median905
Q31306
95-th percentile1920
Maximum2736
Range2735
Interquartile range (IQR)834

Descriptive statistics

Standard deviation595.02456
Coefficient of variation (CV)0.64509592
Kurtosis-0.30426779
Mean922.38153
Median Absolute Deviation (MAD)413
Skewness0.3351331
Sum229673
Variance354054.23
MonotonicityNot monotonic
2024-03-14T20:14:04.554891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
776 3
 
1.2%
2 2
 
0.8%
953 2
 
0.8%
1193 2
 
0.8%
1567 2
 
0.8%
1692 2
 
0.8%
34 2
 
0.8%
7 2
 
0.8%
373 2
 
0.8%
1205 2
 
0.8%
Other values (221) 228
91.6%
ValueCountFrequency (%)
1 1
0.4%
2 2
0.8%
3 1
0.4%
4 1
0.4%
5 2
0.8%
6 1
0.4%
7 2
0.8%
8 1
0.4%
11 1
0.4%
12 1
0.4%
ValueCountFrequency (%)
2736 1
0.4%
2537 1
0.4%
2438 1
0.4%
2361 1
0.4%
2294 1
0.4%
2229 1
0.4%
2191 1
0.4%
2181 1
0.4%
2143 1
0.4%
2056 1
0.4%

입내원일수(일)
Real number (ℝ)

HIGH CORRELATION 

Distinct242
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1579.7831
Minimum1
Maximum4813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-14T20:14:04.964052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile34.6
Q1800
median1634
Q32235
95-th percentile3284.2
Maximum4813
Range4812
Interquartile range (IQR)1435

Descriptive statistics

Standard deviation1003.1311
Coefficient of variation (CV)0.63498028
Kurtosis0.13354625
Mean1579.7831
Median Absolute Deviation (MAD)701
Skewness0.45292512
Sum393366
Variance1006272.1
MonotonicityNot monotonic
2024-03-14T20:14:05.403668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
359 2
 
0.8%
5 2
 
0.8%
1687 2
 
0.8%
276 2
 
0.8%
131 2
 
0.8%
3 2
 
0.8%
1231 2
 
0.8%
914 1
 
0.4%
436 1
 
0.4%
731 1
 
0.4%
Other values (232) 232
93.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 2
0.8%
5 2
0.8%
7 1
0.4%
12 1
0.4%
13 1
0.4%
16 1
0.4%
20 1
0.4%
28 1
0.4%
ValueCountFrequency (%)
4813 1
0.4%
4797 1
0.4%
4693 1
0.4%
3978 1
0.4%
3953 1
0.4%
3868 1
0.4%
3630 1
0.4%
3592 1
0.4%
3571 1
0.4%
3555 1
0.4%

진료건수(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct234
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1395.4618
Minimum1
Maximum4245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-14T20:14:05.813220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q1686
median1490
Q31994
95-th percentile2868.8
Maximum4245
Range4244
Interquartile range (IQR)1308

Descriptive statistics

Standard deviation884.08018
Coefficient of variation (CV)0.63353949
Kurtosis-0.31291401
Mean1395.4618
Median Absolute Deviation (MAD)637
Skewness0.25861973
Sum347470
Variance781597.77
MonotonicityNot monotonic
2024-03-14T20:14:06.226930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2127 3
 
1.2%
2 2
 
0.8%
1527 2
 
0.8%
40 2
 
0.8%
1656 2
 
0.8%
1562 2
 
0.8%
749 2
 
0.8%
381 2
 
0.8%
2072 2
 
0.8%
997 2
 
0.8%
Other values (224) 228
91.6%
ValueCountFrequency (%)
1 1
0.4%
2 2
0.8%
3 1
0.4%
5 2
0.8%
6 1
0.4%
7 1
0.4%
8 1
0.4%
11 1
0.4%
15 1
0.4%
17 1
0.4%
ValueCountFrequency (%)
4245 1
0.4%
3888 1
0.4%
3733 1
0.4%
3521 1
0.4%
3362 1
0.4%
3038 1
0.4%
3027 1
0.4%
3026 1
0.4%
2974 1
0.4%
2970 1
0.4%

진료비(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106094.17
Minimum80.89
Maximum474820.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-14T20:14:06.624338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80.89
5-th percentile5472.97
Q138881.23
median74153.52
Q3156034.56
95-th percentile303120.17
Maximum474820.95
Range474740.06
Interquartile range (IQR)117153.33

Descriptive statistics

Standard deviation94395.102
Coefficient of variation (CV)0.88972943
Kurtosis1.3841161
Mean106094.17
Median Absolute Deviation (MAD)47835.96
Skewness1.3157488
Sum26417447
Variance8.9104353 × 109
MonotonicityNot monotonic
2024-03-14T20:14:07.036813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59150.5 1
 
0.4%
200442.32 1
 
0.4%
136791.81 1
 
0.4%
136911.37 1
 
0.4%
175632.84 1
 
0.4%
140834.64 1
 
0.4%
99368.03 1
 
0.4%
21328.36 1
 
0.4%
8764.49 1
 
0.4%
258.35 1
 
0.4%
Other values (239) 239
96.0%
ValueCountFrequency (%)
80.89 1
0.4%
258.35 1
0.4%
622.1 1
0.4%
648.63 1
0.4%
665.85 1
0.4%
859.42 1
0.4%
1308.65 1
0.4%
1933.29 1
0.4%
2004.22 1
0.4%
3099.66 1
0.4%
ValueCountFrequency (%)
474820.95 1
0.4%
388980.13 1
0.4%
388399.5 1
0.4%
383208.38 1
0.4%
379517.59 1
0.4%
379512.86 1
0.4%
360840.57 1
0.4%
352819.82 1
0.4%
351103.26 1
0.4%
318243.86 1
0.4%

공단부담금(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77632.364
Minimum46.99
Maximum348161.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-14T20:14:07.433905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46.99
5-th percentile3937.88
Q127640.61
median52399.67
Q3115994.02
95-th percentile222335.69
Maximum348161.92
Range348114.93
Interquartile range (IQR)88353.41

Descriptive statistics

Standard deviation70228.272
Coefficient of variation (CV)0.90462621
Kurtosis1.3663062
Mean77632.364
Median Absolute Deviation (MAD)34043.46
Skewness1.3253591
Sum19330459
Variance4.9320101 × 109
MonotonicityNot monotonic
2024-03-14T20:14:07.870987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47354.55 1
 
0.4%
145763.98 1
 
0.4%
99759.7 1
 
0.4%
103473.94 1
 
0.4%
137585.93 1
 
0.4%
105018.88 1
 
0.4%
75899.68 1
 
0.4%
15820.6 1
 
0.4%
6576.78 1
 
0.4%
159.95 1
 
0.4%
Other values (239) 239
96.0%
ValueCountFrequency (%)
46.99 1
0.4%
159.95 1
0.4%
345.69 1
0.4%
479.72 1
0.4%
503.63 1
0.4%
654.17 1
0.4%
771.19 1
0.4%
1391.62 1
0.4%
1493.58 1
0.4%
2364.37 1
0.4%
ValueCountFrequency (%)
348161.92 1
0.4%
291204.96 1
0.4%
289036.39 1
0.4%
285834.82 1
0.4%
283685.88 1
0.4%
280794.96 1
0.4%
266927.14 1
0.4%
258369.62 1
0.4%
254917.5 1
0.4%
242833.82 1
0.4%

Interactions

2024-03-14T20:14:00.309047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:55.247275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:56.473432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:57.705434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:59.105088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:00.562212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:55.496758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:56.719900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:57.943545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:59.343176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:00.814983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:55.739630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:56.960178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:58.182895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:59.584658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:01.063653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:55.975395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:57.196785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:58.412369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:59.816039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:01.312505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:56.214207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:57.436548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:13:58.644480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:00.052826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:14:08.147097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년도성별연령진료인원(명)입내원일수(일)진료건수(건)진료비(천원)공단부담금(천원)
진료년도1.0000.0000.0000.3750.4130.3710.2760.291
성별0.0001.0000.0000.1350.0000.2350.4160.375
연령0.0000.0001.0000.7740.7500.7770.6630.657
진료인원(명)0.3750.1350.7741.0000.9140.9640.6050.613
입내원일수(일)0.4130.0000.7500.9141.0000.9680.7710.734
진료건수(건)0.3710.2350.7770.9640.9681.0000.6960.687
진료비(천원)0.2760.4160.6630.6050.7710.6961.0000.995
공단부담금(천원)0.2910.3750.6570.6130.7340.6870.9951.000
2024-03-14T20:14:08.431662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년도성별연령
진료년도1.0000.0000.000
성별0.0001.0000.000
연령0.0000.0001.000
2024-03-14T20:14:08.690165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료인원(명)입내원일수(일)진료건수(건)진료비(천원)공단부담금(천원)진료년도성별연령
진료인원(명)1.0000.9230.9630.5230.4980.2060.1010.409
입내원일수(일)0.9231.0000.9840.7400.7220.2300.0000.383
진료건수(건)0.9630.9841.0000.6450.6240.2030.1770.412
진료비(천원)0.5230.7400.6451.0000.9980.1470.3140.306
공단부담금(천원)0.4980.7220.6240.9981.0000.1550.2830.302
진료년도0.2060.2300.2030.1470.1551.0000.0000.000
성별0.1010.0000.1770.3140.2830.0001.0000.000
연령0.4090.3830.4120.3060.3020.0000.0001.000

Missing values

2024-03-14T20:14:01.672106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:14:02.090683image/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

진료년도성별연령진료인원(명)입내원일수(일)진료건수(건)진료비(천원)공단부담금(천원)
02017년남자0-4세66891477959150.547354.55
12017년남자5-9세50268765520741.3414107.75
22017년남자10-14세7251073105132954.3322853.72
32017년남자15-19세10691492146144213.9630437.17
42017년남자20-24세12671961168694738.2467405.58
52017년남자25-29세12101672158095617.0668711.15
62017년남자30-34세9871290121657996.9440046.07
72017년남자35-39세118317711619106920.7376299.94
82017년남자40-44세10891606152769537.3846959.21
92017년남자45-49세141422791953158435.45114855.96
진료년도성별연령진료인원(명)입내원일수(일)진료건수(건)진료비(천원)공단부담금(천원)
2392022년여자55-59세14952209217079441.7755452.29
2402022년여자60-64세169226922613112917.4980837.35
2412022년여자65-69세144624912370133585.69101124.68
2422022년여자70-74세110220081835153407.67115994.02
2432022년여자75-79세91623352058193020.77145571.98
2442022년여자80-84세77119451659218447.45165169.81
2452022년여자85-89세39392369285887.8965016.96
2462022년여자90-94세13034824067053.6349792.85
2472022년여자95-99세2646408243.455996.65
2482022년여자100세 이상51211859.42654.17