Overview

Dataset statistics

Number of variables10
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory91.0 B

Variable types

Categorical3
Numeric7

Dataset

Description대구보훈병원에서 개방하는 진료정보 데이터로, 대구보훈병원 만성질환 환자 연령별 현황에 대한 내용이 포함된 공공데이터 입니다.
URLhttps://www.data.go.kr/data/15102221/fileData.do

Alerts

상병명칭 is highly overall correlated with 상병코드High correlation
상병코드 is highly overall correlated with 상병명칭High correlation
합계 is highly overall correlated with 59세이하 and 5 other fieldsHigh correlation
59세이하 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
60세-64세 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
65세-69세 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
70세-79세 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
80세-89세 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
90세이상 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
59세이하 has 7 (21.2%) zerosZeros
60세-64세 has 11 (33.3%) zerosZeros
65세-69세 has 7 (21.2%) zerosZeros
80세-89세 has 4 (12.1%) zerosZeros
90세이상 has 6 (18.2%) zerosZeros

Reproduction

Analysis started2023-12-12 01:14:09.364791
Analysis finished2023-12-12 01:14:15.946501
Duration6.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
입원(실인원)
11 
입원(연인원)
11 
외래
11 

Length

Max length7
Median length7
Mean length5.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입원(실인원)
2nd row입원(실인원)
3rd row입원(실인원)
4th row입원(실인원)
5th row입원(실인원)

Common Values

ValueCountFrequency (%)
입원(실인원) 11
33.3%
입원(연인원) 11
33.3%
외래 11
33.3%

Length

2023-12-12T10:14:16.021142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:14:16.145457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입원(실인원 11
33.3%
입원(연인원 11
33.3%
외래 11
33.3%

상병코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
I10~I13, I15
3 
E10~E14
3 
F00~F99, G40~G41
3 
A15, A16, A19
3 
I05~I09, I20~I27, I30~I52
3 
Other values (6)
18 

Length

Max length25
Median length17
Mean length12.636364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI10~I13, I15
2nd rowE10~E14
3rd rowF00~F99, G40~G41
4th rowA15, A16, A19
5th rowI05~I09, I20~I27, I30~I52

Common Values

ValueCountFrequency (%)
I10~I13, I15 3
9.1%
E10~E14 3
9.1%
F00~F99, G40~G41 3
9.1%
A15, A16, A19 3
9.1%
I05~I09, I20~I27, I30~I52 3
9.1%
I60~I69 3
9.1%
G00~G37, G43~G83 3
9.1%
C00~C97, D00~D09 3
9.1%
E00~E07 3
9.1%
B18, B19, K70~K77 3
9.1%

Length

2023-12-12T10:14:16.285843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
i10~i13 3
 
4.8%
i60~i69 3
 
4.8%
k70~k77 3
 
4.8%
b19 3
 
4.8%
b18 3
 
4.8%
e00~e07 3
 
4.8%
d00~d09 3
 
4.8%
c00~c97 3
 
4.8%
g43~g83 3
 
4.8%
g00~g37 3
 
4.8%
Other values (11) 33
52.4%

상병명칭
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
고혈압
3 
당뇨병
3 
정신 및 행동장애
3 
호흡기결핵
3 
심장질환
3 
Other values (6)
18 

Length

Max length9
Median length7
Mean length5.2727273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고혈압
2nd row당뇨병
3rd row정신 및 행동장애
4th row호흡기결핵
5th row심장질환

Common Values

ValueCountFrequency (%)
고혈압 3
9.1%
당뇨병 3
9.1%
정신 및 행동장애 3
9.1%
호흡기결핵 3
9.1%
심장질환 3
9.1%
대뇌혈관질환 3
9.1%
신경계질환 3
9.1%
악성신생물 3
9.1%
갑상선의 장애 3
9.1%
간의 질환 3
9.1%

Length

2023-12-12T10:14:16.470224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고혈압 3
 
6.7%
당뇨병 3
 
6.7%
정신 3
 
6.7%
및 3
 
6.7%
행동장애 3
 
6.7%
호흡기결핵 3
 
6.7%
심장질환 3
 
6.7%
대뇌혈관질환 3
 
6.7%
신경계질환 3
 
6.7%
악성신생물 3
 
6.7%
Other values (5) 15
33.3%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5546.3636
Minimum1
Maximum25068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:16.636429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q161
median1136
Q39472
95-th percentile21051
Maximum25068
Range25067
Interquartile range (IQR)9411

Descriptive statistics

Standard deviation7417.355
Coefficient of variation (CV)1.3373366
Kurtosis0.8056577
Mean5546.3636
Median Absolute Deviation (MAD)1135
Skewness1.3429029
Sum183030
Variance55017155
MonotonicityNot monotonic
2023-12-12T10:14:16.776527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 2
 
6.1%
23358 1
 
3.0%
992 1
 
3.0%
5824 1
 
3.0%
19513 1
 
3.0%
25068 1
 
3.0%
15437 1
 
3.0%
43 1
 
3.0%
36 1
 
3.0%
3690 1
 
3.0%
Other values (22) 22
66.7%
ValueCountFrequency (%)
1 2
6.1%
3 1
3.0%
7 1
3.0%
27 1
3.0%
36 1
3.0%
43 1
3.0%
54 1
3.0%
61 1
3.0%
85 1
3.0%
109 1
3.0%
ValueCountFrequency (%)
25068 1
3.0%
23358 1
3.0%
19513 1
3.0%
16923 1
3.0%
15437 1
3.0%
13569 1
3.0%
10797 1
3.0%
9759 1
3.0%
9472 1
3.0%
9269 1
3.0%

59세이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.66667
Minimum0
Maximum1395
Zeros7
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:16.927594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median16
Q3505
95-th percentile1160.6
Maximum1395
Range1395
Interquartile range (IQR)504

Descriptive statistics

Standard deviation434.50249
Coefficient of variation (CV)1.494848
Kurtosis0.4319567
Mean290.66667
Median Absolute Deviation (MAD)16
Skewness1.3295369
Sum9592
Variance188792.42
MonotonicityNot monotonic
2023-12-12T10:14:17.088129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
21.2%
2 4
 
12.1%
1 3
 
9.1%
1395 1
 
3.0%
977 1
 
3.0%
639 1
 
3.0%
505 1
 
3.0%
178 1
 
3.0%
1280 1
 
3.0%
308 1
 
3.0%
Other values (12) 12
36.4%
ValueCountFrequency (%)
0 7
21.2%
1 3
9.1%
2 4
12.1%
4 1
 
3.0%
10 1
 
3.0%
16 1
 
3.0%
21 1
 
3.0%
30 1
 
3.0%
80 1
 
3.0%
163 1
 
3.0%
ValueCountFrequency (%)
1395 1
3.0%
1280 1
3.0%
1081 1
3.0%
977 1
3.0%
953 1
3.0%
841 1
3.0%
746 1
3.0%
639 1
3.0%
505 1
3.0%
354 1
3.0%

60세-64세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197.84848
Minimum0
Maximum1277
Zeros11
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:17.265843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q3332
95-th percentile872
Maximum1277
Range1277
Interquartile range (IQR)332

Descriptive statistics

Standard deviation333.62059
Coefficient of variation (CV)1.6862428
Kurtosis3.614275
Mean197.84848
Median Absolute Deviation (MAD)7
Skewness1.9831257
Sum6529
Variance111302.7
MonotonicityNot monotonic
2023-12-12T10:14:17.422732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 11
33.3%
1 2
 
6.1%
7 2
 
6.1%
1277 1
 
3.0%
598 1
 
3.0%
292 1
 
3.0%
349 1
 
3.0%
97 1
 
3.0%
596 1
 
3.0%
367 1
 
3.0%
Other values (11) 11
33.3%
ValueCountFrequency (%)
0 11
33.3%
1 2
 
6.1%
2 1
 
3.0%
3 1
 
3.0%
7 2
 
6.1%
11 1
 
3.0%
19 1
 
3.0%
30 1
 
3.0%
43 1
 
3.0%
97 1
 
3.0%
ValueCountFrequency (%)
1277 1
3.0%
1133 1
3.0%
698 1
3.0%
598 1
3.0%
596 1
3.0%
495 1
3.0%
367 1
3.0%
349 1
3.0%
332 1
3.0%
292 1
3.0%

65세-69세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.87879
Minimum0
Maximum2203
Zeros7
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:17.579948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median35
Q3437
95-th percentile1606
Maximum2203
Range2203
Interquartile range (IQR)436

Descriptive statistics

Standard deviation571.76463
Coefficient of variation (CV)1.6578713
Kurtosis3.9287775
Mean344.87879
Median Absolute Deviation (MAD)35
Skewness2.0611433
Sum11381
Variance326914.8
MonotonicityNot monotonic
2023-12-12T10:14:17.738329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
1969 1
 
3.0%
579 1
 
3.0%
382 1
 
3.0%
720 1
 
3.0%
437 1
 
3.0%
829 1
 
3.0%
Other values (14) 14
42.4%
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
4 2
 
6.1%
6 1
 
3.0%
7 1
 
3.0%
9 2
 
6.1%
11 1
 
3.0%
35 1
 
3.0%
53 1
 
3.0%
60 1
 
3.0%
ValueCountFrequency (%)
2203 1
3.0%
1969 1
3.0%
1364 1
3.0%
934 1
3.0%
906 1
3.0%
829 1
3.0%
720 1
3.0%
579 1
3.0%
437 1
3.0%
382 1
3.0%

70세-79세
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3599.2727
Minimum1
Maximum16739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:17.898641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q131
median720
Q36466
95-th percentile14015.8
Maximum16739
Range16738
Interquartile range (IQR)6435

Descriptive statistics

Standard deviation4936.1604
Coefficient of variation (CV)1.3714327
Kurtosis1.2728096
Mean3599.2727
Median Absolute Deviation (MAD)719
Skewness1.4599826
Sum118776
Variance24365679
MonotonicityNot monotonic
2023-12-12T10:14:18.077760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 3
 
9.1%
18 1
 
3.0%
3580 1
 
3.0%
5962 1
 
3.0%
1876 1
 
3.0%
3448 1
 
3.0%
6599 1
 
3.0%
12393 1
 
3.0%
8938 1
 
3.0%
16450 1
 
3.0%
Other values (21) 21
63.6%
ValueCountFrequency (%)
1 3
9.1%
3 1
 
3.0%
15 1
 
3.0%
18 1
 
3.0%
19 1
 
3.0%
24 1
 
3.0%
31 1
 
3.0%
47 1
 
3.0%
53 1
 
3.0%
75 1
 
3.0%
ValueCountFrequency (%)
16739 1
3.0%
16450 1
3.0%
12393 1
3.0%
12035 1
3.0%
8938 1
3.0%
7559 1
3.0%
7347 1
3.0%
6599 1
3.0%
6466 1
3.0%
5962 1
3.0%

80세-89세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean790.36364
Minimum0
Maximum3650
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:18.245958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median189
Q31474
95-th percentile2921.4
Maximum3650
Range3650
Interquartile range (IQR)1461

Descriptive statistics

Standard deviation1075.5997
Coefficient of variation (CV)1.3608922
Kurtosis0.49800962
Mean790.36364
Median Absolute Deviation (MAD)189
Skewness1.2807962
Sum26082
Variance1156914.8
MonotonicityNot monotonic
2023-12-12T10:14:18.424767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 4
 
12.1%
4 2
 
6.1%
20 2
 
6.1%
8 1
 
3.0%
55 1
 
3.0%
1064 1
 
3.0%
189 1
 
3.0%
416 1
 
3.0%
1474 1
 
3.0%
1475 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
0 4
12.1%
2 1
 
3.0%
4 2
6.1%
8 1
 
3.0%
13 1
 
3.0%
20 2
6.1%
22 1
 
3.0%
29 1
 
3.0%
55 1
 
3.0%
85 1
 
3.0%
ValueCountFrequency (%)
3650 1
3.0%
3138 1
3.0%
2777 1
3.0%
2377 1
3.0%
2255 1
3.0%
2167 1
3.0%
1848 1
3.0%
1475 1
3.0%
1474 1
3.0%
1064 1
3.0%

90세이상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean323.33333
Minimum0
Maximum1846
Zeros6
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T10:14:18.601055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median60
Q3484
95-th percentile1334.8
Maximum1846
Range1846
Interquartile range (IQR)480

Descriptive statistics

Standard deviation489.69293
Coefficient of variation (CV)1.5145142
Kurtosis2.5929321
Mean323.33333
Median Absolute Deviation (MAD)60
Skewness1.7677246
Sum10670
Variance239799.17
MonotonicityNot monotonic
2023-12-12T10:14:18.777702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 6
18.2%
4 4
 
12.1%
6 2
 
6.1%
918 1
 
3.0%
579 1
 
3.0%
19 1
 
3.0%
137 1
 
3.0%
484 1
 
3.0%
350 1
 
3.0%
795 1
 
3.0%
Other values (14) 14
42.4%
ValueCountFrequency (%)
0 6
18.2%
2 1
 
3.0%
4 4
12.1%
6 2
 
6.1%
11 1
 
3.0%
19 1
 
3.0%
58 1
 
3.0%
60 1
 
3.0%
64 1
 
3.0%
116 1
 
3.0%
ValueCountFrequency (%)
1846 1
3.0%
1591 1
3.0%
1164 1
3.0%
962 1
3.0%
918 1
3.0%
795 1
3.0%
677 1
3.0%
579 1
3.0%
484 1
3.0%
350 1
3.0%

Interactions

2023-12-12T10:14:14.822244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:09.829823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.479494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.214189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.947802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.868666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.984467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.924399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:09.912224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.592062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.320140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.055447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.269927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.103256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:15.026108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.005680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.697949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.448274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.167146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.387639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.232800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:15.152434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.107754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.801082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.561204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.280987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.507631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.348809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:15.260754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.188526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.894741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.660424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.369809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.608025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.468582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:15.381472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.280676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.001997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.759597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.476568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.723576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.578350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:15.481639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:10.383277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.102887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:11.850039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:12.700892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:13.851954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:14:14.709419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:14:18.894698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상병코드상병명칭합계59세이하60세-64세65세-69세70세-79세80세-89세90세이상
구분1.0000.0000.0000.7710.7150.5630.6110.5790.7860.707
상병코드0.0001.0001.0000.0000.0000.0000.2340.0000.3610.000
상병명칭0.0001.0001.0000.0000.0000.0000.2340.0000.3610.000
합계0.7710.0000.0001.0000.9300.8920.8630.9660.9540.945
59세이하0.7150.0000.0000.9301.0000.8630.8950.8300.9550.907
60세-64세0.5630.0000.0000.8920.8631.0000.9740.9280.9190.900
65세-69세0.6110.2340.2340.8630.8950.9741.0000.9370.9150.858
70세-79세0.5790.0000.0000.9660.8300.9280.9371.0000.8590.823
80세-89세0.7860.3610.3610.9540.9550.9190.9150.8591.0000.975
90세이상0.7070.0000.0000.9450.9070.9000.8580.8230.9751.000
2023-12-12T10:14:19.063994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상병명칭상병코드
구분1.0000.0000.000
상병명칭0.0001.0001.000
상병코드0.0001.0001.000
2023-12-12T10:14:19.210263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계59세이하60세-64세65세-69세70세-79세80세-89세90세이상구분상병코드상병명칭
합계1.0000.8820.9020.9270.9930.9570.8550.4180.0000.000
59세이하0.8821.0000.8990.8910.8820.8460.6650.3680.0000.000
60세-64세0.9020.8991.0000.9300.9120.8820.7190.3850.0000.000
65세-69세0.9270.8910.9301.0000.9390.9210.8310.4320.0000.000
70세-79세0.9930.8820.9120.9391.0000.9550.8370.4000.0000.000
80세-89세0.9570.8460.8820.9210.9551.0000.8030.4330.1220.122
90세이상0.8550.6650.7190.8310.8370.8031.0000.3610.0000.000
구분0.4180.3680.3850.4320.4000.4330.3611.0000.0000.000
상병코드0.0000.0000.0000.0000.0000.1220.0000.0001.0001.000
상병명칭0.0000.0000.0000.0000.0000.1220.0000.0001.0001.000

Missing values

2023-12-12T10:14:15.682378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:14:15.873789image/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

구분상병코드상병명칭합계59세이하60세-64세65세-69세70세-79세80세-89세90세이상
0입원(실인원)I10~I13, I15고혈압362041884
1입원(실인원)E10~E14당뇨병2081076159224
2입원(실인원)F00~F99, G40~G41정신 및 행동장애3000120
3입원(실인원)A15, A16, A19호흡기결핵7000304
4입원(실인원)I05~I09, I20~I27, I30~I52심장질환98530305368313158
5입원(실인원)I60~I69대뇌혈관질환5422431132
6입원(실인원)G00~G37, G43~G83신경계질환612115340
7입원(실인원)C00~C97, D00~D09악성신생물20613111512911
8입원(실인원)E00~E07갑상선의 장애1000100
9입원(실인원)B18, B19, K70~K77간의 질환271011546
구분상병코드상병명칭합계59세이하60세-64세65세-69세70세-79세80세-89세90세이상
23외래E10~E14당뇨병25068139512772203167392777677
24외래F00~F99, G40~G41정신 및 행동장애15437953495934755936501846
25외래A15, A16, A19호흡기결핵4300019204
26외래I05~I09, I20~I27, I30~I52심장질환233587466981364164503138962
27외래I60~I69대뇌혈관질환1356930836790689382255795
28외래G00~G37, G43~G83신경계질환169231280596829123931475350
29외래C00~C97, D00~D09악성신생물92691789743765991474484
30외래E00~E07갑상선의 장애55755053497203448416137
31외래B18, B19, K70~K77간의 질환3397639292382187618919
32외래N18만성신부전증975997759857959621064579