Overview

Dataset statistics

Number of variables7
Number of observations402
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.7 KiB
Average record size in memory60.3 B

Variable types

Numeric4
Categorical1
DateTime2

Dataset

Description일상생활 평가 도구로서 일상생활 동작을 10개의 세부항목으로 나누고 각 항목은 도움의 정도에 따라 5단계의 점수체계를 가지며 최대 점수는 100점이다.
Author보건복지부 국립재활원
URLhttps://www.data.go.kr/data/15005530/fileData.do

Alerts

대상 has constant value ""Constant
입원시점수 is highly overall correlated with 퇴원시점수High correlation
퇴원시점수 is highly overall correlated with 입원시점수High correlation
번호 has unique valuesUnique
입원시점수 has 18 (4.5%) zerosZeros
퇴원시점수 has 19 (4.7%) zerosZeros
비교점수 has 79 (19.7%) zerosZeros

Reproduction

Analysis started2023-12-12 12:03:44.825694
Analysis finished2023-12-12 12:03:47.042166
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct402
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.5
Minimum1
Maximum402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-12T21:03:47.122638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.05
Q1101.25
median201.5
Q3301.75
95-th percentile381.95
Maximum402
Range401
Interquartile range (IQR)200.5

Descriptive statistics

Standard deviation116.19165
Coefficient of variation (CV)0.57663351
Kurtosis-1.2
Mean201.5
Median Absolute Deviation (MAD)100.5
Skewness0
Sum81003
Variance13500.5
MonotonicityStrictly increasing
2023-12-12T21:03:47.302539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
266 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
269 1
 
0.2%
Other values (392) 392
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%
393 1
0.2%

대상
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
입원환자
402 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
입원환자 402
100.0%

Length

2023-12-12T21:03:47.488302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:47.594504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입원환자 402
100.0%

입원일
Date

Distinct207
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2016-07-12 00:00:00
Maximum2021-12-06 00:00:00
2023-12-12T21:03:47.693542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:47.854287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

퇴원일
Date

Distinct170
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2017-01-02 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T21:03:48.006506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:48.157589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

입원시점수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.271144
Minimum0
Maximum100
Zeros18
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-12T21:03:48.322578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q126.5
median52.5
Q374
95-th percentile92
Maximum100
Range100
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation28.156379
Coefficient of variation (CV)0.56009027
Kurtosis-1.1018703
Mean50.271144
Median Absolute Deviation (MAD)23.5
Skewness-0.18424831
Sum20209
Variance792.78166
MonotonicityNot monotonic
2023-12-12T21:03:48.473862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
4.5%
77 13
 
3.2%
72 11
 
2.7%
68 10
 
2.5%
80 9
 
2.2%
15 9
 
2.2%
84 8
 
2.0%
47 8
 
2.0%
92 7
 
1.7%
43 7
 
1.7%
Other values (84) 302
75.1%
ValueCountFrequency (%)
0 18
4.5%
2 1
 
0.2%
3 3
 
0.7%
4 3
 
0.7%
5 2
 
0.5%
6 3
 
0.7%
7 6
 
1.5%
8 3
 
0.7%
9 6
 
1.5%
10 5
 
1.2%
ValueCountFrequency (%)
100 4
1.0%
98 2
 
0.5%
97 1
 
0.2%
96 1
 
0.2%
95 5
1.2%
94 3
0.7%
92 7
1.7%
91 2
 
0.5%
90 1
 
0.2%
89 4
1.0%

퇴원시점수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct92
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.91791
Minimum0
Maximum100
Zeros19
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-12T21:03:48.616943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q135
median65
Q384
95-th percentile98
Maximum100
Range100
Interquartile range (IQR)49

Descriptive statistics

Standard deviation29.927606
Coefficient of variation (CV)0.50795429
Kurtosis-0.94008776
Mean58.91791
Median Absolute Deviation (MAD)21
Skewness-0.50593095
Sum23685
Variance895.66157
MonotonicityNot monotonic
2023-12-12T21:03:48.776220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
4.7%
80 16
 
4.0%
100 13
 
3.2%
86 11
 
2.7%
58 10
 
2.5%
92 10
 
2.5%
93 9
 
2.2%
83 9
 
2.2%
50 9
 
2.2%
77 8
 
2.0%
Other values (82) 288
71.6%
ValueCountFrequency (%)
0 19
4.7%
2 1
 
0.2%
4 2
 
0.5%
5 4
 
1.0%
6 2
 
0.5%
7 3
 
0.7%
8 6
 
1.5%
9 1
 
0.2%
10 5
 
1.2%
11 1
 
0.2%
ValueCountFrequency (%)
100 13
3.2%
99 3
 
0.7%
98 8
2.0%
97 6
1.5%
96 3
 
0.7%
95 3
 
0.7%
94 2
 
0.5%
93 9
2.2%
92 10
2.5%
91 2
 
0.5%

비교점수
Real number (ℝ)

ZEROS 

Distinct62
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6467662
Minimum-60
Maximum90
Zeros79
Zeros (%)19.7%
Negative31
Negative (%)7.7%
Memory size3.7 KiB
2023-12-12T21:03:49.256527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-60
5-th percentile-3
Q10
median6
Q313
95-th percentile30.95
Maximum90
Range150
Interquartile range (IQR)13

Descriptive statistics

Standard deviation12.997395
Coefficient of variation (CV)1.503151
Kurtosis9.1191981
Mean8.6467662
Median Absolute Deviation (MAD)6
Skewness1.5926818
Sum3476
Variance168.93227
MonotonicityNot monotonic
2023-12-12T21:03:49.445329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 79
19.7%
5 23
 
5.7%
3 23
 
5.7%
8 23
 
5.7%
4 20
 
5.0%
10 20
 
5.0%
6 15
 
3.7%
12 14
 
3.5%
14 14
 
3.5%
2 12
 
3.0%
Other values (52) 159
39.6%
ValueCountFrequency (%)
-60 1
 
0.2%
-34 1
 
0.2%
-22 1
 
0.2%
-16 1
 
0.2%
-12 1
 
0.2%
-9 1
 
0.2%
-8 3
0.7%
-7 1
 
0.2%
-6 2
0.5%
-5 2
0.5%
ValueCountFrequency (%)
90 1
0.2%
76 1
0.2%
66 1
0.2%
57 1
0.2%
54 1
0.2%
53 1
0.2%
52 1
0.2%
50 1
0.2%
49 1
0.2%
45 1
0.2%

Interactions

2023-12-12T21:03:46.384355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:44.993682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.454868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.899802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.506770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.121518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.572339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.032140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.628644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.233371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.685791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.138357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.721753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.342819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:45.790172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:46.262531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:03:49.566063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호입원시점수퇴원시점수비교점수
번호1.0000.1870.2010.051
입원시점수0.1871.0000.9140.345
퇴원시점수0.2010.9141.0000.210
비교점수0.0510.3450.2101.000
2023-12-12T21:03:49.736270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호입원시점수퇴원시점수비교점수
번호1.000-0.166-0.117-0.017
입원시점수-0.1661.0000.8950.005
퇴원시점수-0.1170.8951.0000.341
비교점수-0.0170.0050.3411.000

Missing values

2023-12-12T21:03:46.871833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:03:46.996890image/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

번호대상입원일퇴원일입원시점수퇴원시점수비교점수
01입원환자2016-09-262017-01-0284895
12입원환자2016-10-052017-01-03000
23입원환자2016-09-222017-01-04637512
34입원환자2016-10-102017-01-05000
45입원환자2016-10-072017-01-0666704
56입원환자2016-09-302017-01-0661654
67입원환자2016-10-142017-01-06356530
78입원환자2016-10-062017-01-0968724
89입원환자2016-09-222017-01-09536512
910입원환자2016-08-162017-01-1083863
번호대상입원일퇴원일입원시점수퇴원시점수비교점수
392393입원환자2021-07-062021-12-21244824
393394입원환자2021-09-242021-12-24385113
394395입원환자2021-06-282021-12-24368044
395396입원환자2021-06-282021-12-24728614
396397입원환자2021-09-302021-12-2885894
397398입원환자2021-09-062021-12-28000
398399입원환자2021-10-012021-12-29385012
399400입원환자2021-11-152021-12-303226-6
400401입원환자2021-10-062021-12-3174828
401402입원환자2021-07-072021-12-31435310