Overview

Dataset statistics

Number of variables4
Number of observations264
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory33.5 B

Variable types

Categorical3
Numeric1

Dataset

Description연간 본태성(원발성) 고혈압 환자수 현황 입니다.1. 진료일기준(한의분류 제외, 약국 제외), 연령(연말기준)2. 건강보험 급여실적(의료급여 제외)이며, 비급여는 제외- 2023년 6월 지급분까지 반영3. 아래 질병통계 자료는 요양기관에서 환자진료중 진단명이 확정되지 않은 상태에서의 호소, 증세 등에 따라일차진단명을 부여하고 청구한 내역중 주진단명 및 제1부상병 기준으로 발췌한 것이므로 최종확정된 질병과는 다를수 있음주상병코드: I10
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15125131/fileData.do

Reproduction

Analysis started2023-12-12 04:18:05.109518
Analysis finished2023-12-12 04:18:05.517183
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2017년
44 
2018년
44 
2019년
44 
2020년
44 
2021년
44 

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 (%)
2017년 44
16.7%
2018년 44
16.7%
2019년 44
16.7%
2020년 44
16.7%
2021년 44
16.7%
2022년 44
16.7%

Length

2023-12-12T13:18:05.883875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:18:06.017972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017년 44
16.7%
2018년 44
16.7%
2019년 44
16.7%
2020년 44
16.7%
2021년 44
16.7%
2022년 44
16.7%

성별
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
남자
132 
여자
132 

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 (%)
남자 132
50.0%
여자 132
50.0%

Length

2023-12-12T13:18:06.142090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:18:06.224260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남자 132
50.0%
여자 132
50.0%

연령
Categorical

Distinct22
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0세
 
12
1-4세
 
12
5-9세
 
12
10-14세
 
12
15-19세
 
12
Other values (17)
204 

Length

Max length6
Median length6
Mean length5.6363636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0세
2nd row1-4세
3rd row5-9세
4th row10-14세
5th row15-19세

Common Values

ValueCountFrequency (%)
0세 12
 
4.5%
1-4세 12
 
4.5%
5-9세 12
 
4.5%
10-14세 12
 
4.5%
15-19세 12
 
4.5%
20-24세 12
 
4.5%
25-29세 12
 
4.5%
30-34세 12
 
4.5%
35-39세 12
 
4.5%
40-44세 12
 
4.5%
Other values (12) 144
54.5%

Length

2023-12-12T13:18:06.349837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0세 12
 
4.5%
1-4세 12
 
4.5%
95-99세 12
 
4.5%
90-94세 12
 
4.5%
85-89세 12
 
4.5%
80-84세 12
 
4.5%
75-79세 12
 
4.5%
70-74세 12
 
4.5%
65-69세 12
 
4.5%
60-64세 12
 
4.5%
Other values (12) 144
54.5%

진료인원(명)
Real number (ℝ)

Distinct263
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186236.14
Minimum60
Maximum763327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T13:18:06.520556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile192.05
Q13257
median58004
Q3367830
95-th percentile618022.65
Maximum763327
Range763267
Interquartile range (IQR)364573

Descriptive statistics

Standard deviation222897.97
Coefficient of variation (CV)1.1968567
Kurtosis-0.75894513
Mean186236.14
Median Absolute Deviation (MAD)57748.5
Skewness0.85788483
Sum49166340
Variance4.9683504 × 1010
MonotonicityNot monotonic
2023-12-12T13:18:06.686618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2
 
0.8%
112 1
 
0.4%
13330 1
 
0.4%
599409 1
 
0.4%
573778 1
 
0.4%
534144 1
 
0.4%
497309 1
 
0.4%
398244 1
 
0.4%
222665 1
 
0.4%
82279 1
 
0.4%
Other values (253) 253
95.8%
ValueCountFrequency (%)
60 1
0.4%
68 1
0.4%
69 1
0.4%
77 1
0.4%
84 1
0.4%
86 1
0.4%
90 2
0.8%
92 1
0.4%
103 1
0.4%
106 1
0.4%
ValueCountFrequency (%)
763327 1
0.4%
740245 1
0.4%
693914 1
0.4%
661803 1
0.4%
647245 1
0.4%
646333 1
0.4%
646123 1
0.4%
637791 1
0.4%
627473 1
0.4%
626984 1
0.4%

Interactions

2023-12-12T13:18:05.265769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:18:06.806156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년도성별연령진료인원(명)
진료년도1.0000.0000.0000.000
성별0.0001.0000.0000.178
연령0.0000.0001.0000.839
진료인원(명)0.0000.1780.8391.000
2023-12-12T13:18:06.914644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령진료년도
성별1.0000.0000.000
연령0.0001.0000.000
진료년도0.0000.0001.000
2023-12-12T13:18:07.023044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료인원(명)진료년도성별연령
진료인원(명)1.0000.0000.1340.494
진료년도0.0001.0000.0000.000
성별0.1340.0001.0000.000
연령0.4940.0000.0001.000

Missing values

2023-12-12T13:18:05.392374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:18:05.484058image/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)
02017년남자0세112
12017년남자1-4세251
22017년남자5-9세486
32017년남자10-14세1007
42017년남자15-19세4948
52017년남자20-24세11793
62017년남자25-29세17624
72017년남자30-34세38616
82017년남자35-39세97767
92017년남자40-44세192524
진료년도성별연령진료인원(명)
2542022년여자55-59세457342
2552022년여자60-64세646123
2562022년여자65-69세646333
2572022년여자70-74세570416
2582022년여자75-79세491233
2592022년여자80-84세457124
2602022년여자85-89세261275
2612022년여자90-94세99668
2622022년여자95-99세22631
2632022년여자100세이상3590