Overview

Dataset statistics

Number of variables6
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory55.9 B

Variable types

Categorical2
Numeric4

Dataset

Description정신질환 상병별 진료실인원 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=JEDF8ZTDNLDRJ8WEDZB626134756&infSeq=1

Alerts

전체실인원수(명) is highly overall correlated with 입내원일수(입원,내원)(일) and 1 other fieldsHigh correlation
입내원일수(입원,내원)(일) is highly overall correlated with 전체실인원수(명) and 3 other fieldsHigh correlation
총진료비(천원) is highly overall correlated with 입내원일수(입원,내원)(일) and 2 other fieldsHigh correlation
공단부담금(천원) is highly overall correlated with 입내원일수(입원,내원)(일) and 2 other fieldsHigh correlation
상병명내역 is highly overall correlated with 전체실인원수(명) and 3 other fieldsHigh correlation
입내원일수(입원,내원)(일) has unique valuesUnique
총진료비(천원) has unique valuesUnique
공단부담금(천원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:59:40.465275
Analysis finished2023-12-10 21:59:42.481203
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct5
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
2016
9 
2015
9 
2014
9 
2013
9 
2012
9 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 9
20.0%
2015 9
20.0%
2014 9
20.0%
2013 9
20.0%
2012 9
20.0%

Length

2023-12-11T06:59:42.540148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:59:42.646544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 9
20.0%
2015 9
20.0%
2014 9
20.0%
2013 9
20.0%
2012 9
20.0%

상병명내역
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
1. 치매
5 
2. 알콜사용에 의한 정신행동장애
5 
3. 기타 정신활성물질 사용에 의한 정신 및 행동장애
5 
4. 정신분열증 분열형 및 망상성 장애
5 
5. 기분(정동성) 장애
5 
Other values (4)
20 

Length

Max length29
Median length15
Mean length15.555556
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1. 치매
2nd row2. 알콜사용에 의한 정신행동장애
3rd row3. 기타 정신활성물질 사용에 의한 정신 및 행동장애
4th row4. 정신분열증 분열형 및 망상성 장애
5th row5. 기분(정동성) 장애

Common Values

ValueCountFrequency (%)
1. 치매 5
11.1%
2. 알콜사용에 의한 정신행동장애 5
11.1%
3. 기타 정신활성물질 사용에 의한 정신 및 행동장애 5
11.1%
4. 정신분열증 분열형 및 망상성 장애 5
11.1%
5. 기분(정동성) 장애 5
11.1%
6. 신경증적 스트레스와 관련된 신체형 장애 5
11.1%
7. 정신발육지체 5
11.1%
8. 기타 정신 및 행동장애 5
11.1%
9. 뇌전증 5
11.1%

Length

2023-12-11T06:59:42.767474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:59:42.888747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애 15
 
7.9%
및 15
 
7.9%
정신 10
 
5.3%
의한 10
 
5.3%
기타 10
 
5.3%
행동장애 10
 
5.3%
기분(정동성 5
 
2.6%
6 5
 
2.6%
신경증적 5
 
2.6%
스트레스와 5
 
2.6%
Other values (20) 100
52.6%

전체실인원수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8855.3778
Minimum146
Maximum18104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T06:59:43.050355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum146
5-th percentile167
Q13512
median9603
Q313983
95-th percentile15415.8
Maximum18104
Range17958
Interquartile range (IQR)10471

Descriptive statistics

Standard deviation5604.2886
Coefficient of variation (CV)0.63286839
Kurtosis-1.3560028
Mean8855.3778
Median Absolute Deviation (MAD)4889
Skewness-0.29255752
Sum398492
Variance31408051
MonotonicityNot monotonic
2023-12-11T06:59:43.197758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
179 2
 
4.4%
8152 1
 
2.2%
13679 1
 
2.2%
7747 1
 
2.2%
14104 1
 
2.2%
1771 1
 
2.2%
10129 1
 
2.2%
16769 1
 
2.2%
13259 1
 
2.2%
3754 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
146 1
2.2%
149 1
2.2%
164 1
2.2%
179 2
4.4%
1169 1
2.2%
1615 1
2.2%
1669 1
2.2%
1771 1
2.2%
1986 1
2.2%
3313 1
2.2%
ValueCountFrequency (%)
18104 1
2.2%
16769 1
2.2%
15505 1
2.2%
15059 1
2.2%
14964 1
2.2%
14630 1
2.2%
14578 1
2.2%
14492 1
2.2%
14104 1
2.2%
14088 1
2.2%

입내원일수(입원,내원)(일)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160218.44
Minimum663
Maximum522190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T06:59:43.347317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum663
5-th percentile937.2
Q161590
median97477
Q3161522
95-th percentile512929.6
Maximum522190
Range521527
Interquartile range (IQR)99932

Descriptive statistics

Standard deviation162098.8
Coefficient of variation (CV)1.0117362
Kurtosis0.35416967
Mean160218.44
Median Absolute Deviation (MAD)40124
Skewness1.30888
Sum7209830
Variance2.6276022 × 1010
MonotonicityNot monotonic
2023-12-11T06:59:43.493113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
331822 1
 
2.2%
128039 1
 
2.2%
126603 1
 
2.2%
65187 1
 
2.2%
347248 1
 
2.2%
107724 1
 
2.2%
1123 1
 
2.2%
520453 1
 
2.2%
161522 1
 
2.2%
57746 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
663 1
2.2%
793 1
2.2%
932 1
2.2%
958 1
2.2%
1123 1
2.2%
37525 1
2.2%
51867 1
2.2%
57310 1
2.2%
57353 1
2.2%
57746 1
2.2%
ValueCountFrequency (%)
522190 1
2.2%
520453 1
2.2%
513588 1
2.2%
510296 1
2.2%
498599 1
2.2%
438332 1
2.2%
391499 1
2.2%
347248 1
2.2%
341941 1
2.2%
331822 1
2.2%

총진료비(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12006025
Minimum125234
Maximum37609874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T06:59:43.622059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125234
5-th percentile135350
Q13624858
median7966911
Q311586283
95-th percentile35568321
Maximum37609874
Range37484640
Interquartile range (IQR)7961425

Descriptive statistics

Standard deviation11928753
Coefficient of variation (CV)0.99356388
Kurtosis-0.053822151
Mean12006025
Median Absolute Deviation (MAD)4342053
Skewness1.1765177
Sum5.4027113 × 108
Variance1.4229515 × 1014
MonotonicityNot monotonic
2023-12-11T06:59:43.756015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
28179404 1
 
2.2%
7846442 1
 
2.2%
8120466 1
 
2.2%
11024574 1
 
2.2%
27352617 1
 
2.2%
6846952 1
 
2.2%
135120 1
 
2.2%
35408847 1
 
2.2%
9853379 1
 
2.2%
2843587 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
125234 1
2.2%
135066 1
2.2%
135120 1
2.2%
136270 1
2.2%
157102 1
2.2%
2059175 1
2.2%
2843587 1
2.2%
2923874 1
2.2%
2984729 1
2.2%
3023286 1
2.2%
ValueCountFrequency (%)
37609874 1
2.2%
37281172 1
2.2%
35608189 1
2.2%
35408847 1
2.2%
35381766 1
2.2%
34061904 1
2.2%
31413134 1
2.2%
28179404 1
2.2%
27352617 1
2.2%
26318787 1
2.2%

공단부담금(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9221108.5
Minimum96969
Maximum31373381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T06:59:43.891306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum96969
5-th percentile101550.6
Q12675292
median5787340
Q38725907
95-th percentile29618577
Maximum31373381
Range31276412
Interquartile range (IQR)6050615

Descriptive statistics

Standard deviation9616355.8
Coefficient of variation (CV)1.0428633
Kurtosis0.34085905
Mean9221108.5
Median Absolute Deviation (MAD)3112048
Skewness1.3007661
Sum4.1494988 × 108
Variance9.2474298 × 1013
MonotonicityNot monotonic
2023-12-11T06:59:44.037344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
20723762 1
 
2.2%
5683541 1
 
2.2%
5896348 1
 
2.2%
8382700 1
 
2.2%
20004659 1
 
2.2%
5174615 1
 
2.2%
100462 1
 
2.2%
29579348 1
 
2.2%
7021472 1
 
2.2%
1950456 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
96969 1
2.2%
100376 1
2.2%
100462 1
2.2%
105905 1
2.2%
118268 1
2.2%
1417390 1
2.2%
1950456 1
2.2%
2023144 1
2.2%
2046273 1
2.2%
2085729 1
2.2%
ValueCountFrequency (%)
31373381 1
2.2%
31086321 1
2.2%
29628384 1
2.2%
29579348 1
2.2%
28423999 1
2.2%
25998762 1
2.2%
23000646 1
2.2%
20723762 1
2.2%
20004659 1
2.2%
19237248 1
2.2%

Interactions

2023-12-11T06:59:41.871929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:40.677995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:40.998226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.300743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.953973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:40.757897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.075591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.393590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:42.026850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:40.834732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.144015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.476333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:42.119989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:40.916789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.223543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:59:41.789138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:59:44.144481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도상병명내역전체실인원수(명)입내원일수(입원,내원)(일)총진료비(천원)공단부담금(천원)
기준년도1.0000.0000.0000.0000.0000.000
상병명내역0.0001.0000.9620.8770.8640.853
전체실인원수(명)0.0000.9621.0000.7800.7150.704
입내원일수(입원,내원)(일)0.0000.8770.7801.0000.9630.986
총진료비(천원)0.0000.8640.7150.9631.0000.981
공단부담금(천원)0.0000.8530.7040.9860.9811.000
2023-12-11T06:59:44.283531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상병명내역기준년도
상병명내역1.0000.000
기준년도0.0001.000
2023-12-11T06:59:44.369813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체실인원수(명)입내원일수(입원,내원)(일)총진료비(천원)공단부담금(천원)기준년도상병명내역
전체실인원수(명)1.0000.6050.4860.4740.0000.679
입내원일수(입원,내원)(일)0.6051.0000.8790.8790.0000.678
총진료비(천원)0.4860.8791.0000.9990.0000.651
공단부담금(천원)0.4740.8790.9991.0000.0000.632
기준년도0.0000.0000.0000.0001.0000.000
상병명내역0.6790.6780.6510.6320.0001.000

Missing values

2023-12-11T06:59:42.229706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:59:42.347377image/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

기준년도상병명내역전체실인원수(명)입내원일수(입원,내원)(일)총진료비(천원)공단부담금(천원)
020161. 치매139833318222817940420723762
120162. 알콜사용에 의한 정신행동장애11695186736248582723434
220163. 기타 정신활성물질 사용에 의한 정신 및 행동장애14666312523496969
320164. 정신분열증 분열형 및 망상성 장애97774985993728117231086321
420165. 기분(정동성) 장애1336212140582308595978223
520166. 신경증적 스트레스와 관련된 신체형 장애96033752520591751417390
620167. 정신발육지체38757188247592623541166
720168. 기타 정신 및 행동장애1320711274579669115787340
820169. 뇌전증8387680301297149010022117
920151. 치매146304383323560818925998762
기준년도상병명내역전체실인원수(명)입내원일수(입원,내원)(일)총진료비(천원)공단부담금(천원)
3520139. 뇌전증815268601114022168664239
3620121. 치매140883419412631878719237248
3720122. 알콜사용에 의한 정신행동장애198611593272724665508799
3820123. 기타 정신활성물질 사용에 의한 정신 및 행동장애149793136270105905
3920124. 정신분열증 분열형 및 망상성 장애104385135883406190428423999
4020125. 기분(정동성) 장애1810416851999990647096259
4120126. 신경증적 스트레스와 관련된 신체형 장애149646159029847292046273
4220127. 정신발육지체37955866233272992450696
4320128. 기타 정신 및 행동장애1449212655374886835410635
4420129. 뇌전증853969518115862838725907