Overview

Dataset statistics

Number of variables6
Number of observations286
Missing cells104
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.9 KiB
Average record size in memory53.5 B

Variable types

Numeric5
Categorical1

Dataset

Description연도,지역이름,주민등록인구,등록회원,장기재원건수,경험율(%)
Author서울시정신건강복지센터
URLhttps://data.seoul.go.kr/dataList/OA-20334/S/1/datasetView.do

Alerts

주민등록인구 is highly overall correlated with 등록회원 and 1 other fieldsHigh correlation
등록회원 is highly overall correlated with 주민등록인구 and 1 other fieldsHigh correlation
장기재원건수 is highly overall correlated with 등록회원 and 1 other fieldsHigh correlation
경험율(%) is highly overall correlated with 장기재원건수High correlation
지역이름 is highly overall correlated with 주민등록인구High correlation
주민등록인구 has 26 (9.1%) missing valuesMissing
등록회원 has 26 (9.1%) missing valuesMissing
장기재원건수 has 26 (9.1%) missing valuesMissing
경험율(%) has 26 (9.1%) missing valuesMissing

Reproduction

Analysis started2024-05-04 04:24:14.179014
Analysis finished2024-05-04 04:24:23.558006
Duration9.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct11
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.9091
Minimum2011
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-04T04:24:23.904972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12014
median2017
Q32020
95-th percentile2022
Maximum2022
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.32119
Coefficient of variation (CV)0.0016466731
Kurtosis-1.0393846
Mean2016.9091
Median Absolute Deviation (MAD)3
Skewness-0.14549456
Sum576836
Variance11.030303
MonotonicityDecreasing
2024-05-04T04:24:24.476333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2022 26
9.1%
2021 26
9.1%
2020 26
9.1%
2019 26
9.1%
2018 26
9.1%
2017 26
9.1%
2016 26
9.1%
2015 26
9.1%
2014 26
9.1%
2013 26
9.1%
ValueCountFrequency (%)
2011 26
9.1%
2013 26
9.1%
2014 26
9.1%
2015 26
9.1%
2016 26
9.1%
2017 26
9.1%
2018 26
9.1%
2019 26
9.1%
2020 26
9.1%
2021 26
9.1%
ValueCountFrequency (%)
2022 26
9.1%
2021 26
9.1%
2020 26
9.1%
2019 26
9.1%
2018 26
9.1%
2017 26
9.1%
2016 26
9.1%
2015 26
9.1%
2014 26
9.1%
2013 26
9.1%

지역이름
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
서초구
 
11
마포구
 
11
동작구
 
11
서울시
 
11
강남구
 
11
Other values (21)
231 

Length

Max length11
Median length10
Mean length9.8076923
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 서초구
2nd row 마포구
3rd row 동작구
4th row서울시
5th row 강남구

Common Values

ValueCountFrequency (%)
서초구 11
 
3.8%
마포구 11
 
3.8%
동작구 11
 
3.8%
서울시 11
 
3.8%
강남구 11
 
3.8%
종로구 11
 
3.8%
도봉구 11
 
3.8%
금천구 11
 
3.8%
강북구 11
 
3.8%
성북구 11
 
3.8%
Other values (16) 176
61.5%

Length

2024-05-04T04:24:25.062506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서초구 11
 
3.8%
마포구 11
 
3.8%
광진구 11
 
3.8%
강서구 11
 
3.8%
관악구 11
 
3.8%
노원구 11
 
3.8%
서대문구 11
 
3.8%
구로구 11
 
3.8%
동대문구 11
 
3.8%
중랑구 11
 
3.8%
Other values (16) 176
61.5%

주민등록인구
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct260
Distinct (%)100.0%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean761368.72
Minimum122499
Maximum10249679
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-04T04:24:25.617077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum122499
5-th percentile152664.65
Q1323150.25
median400819
Q3492804.5
95-th percentile667982.75
Maximum10249679
Range10127180
Interquartile range (IQR)169654.25

Descriptive statistics

Standard deviation1835702.5
Coefficient of variation (CV)2.4110559
Kurtosis21.302268
Mean761368.72
Median Absolute Deviation (MAD)85971
Skewness4.7952611
Sum1.9795587 × 108
Variance3.3698038 × 1012
MonotonicityNot monotonic
2024-05-04T04:24:26.208752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459275 1
 
0.3%
351242 1
 
0.3%
312141 1
 
0.3%
236284 1
 
0.3%
10022181 1
 
0.3%
509663 1
 
0.3%
446764 1
 
0.3%
458658 1
 
0.3%
233342 1
 
0.3%
125733 1
 
0.3%
Other values (250) 250
87.4%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
122499 1
0.3%
125240 1
0.3%
125249 1
0.3%
125709 1
0.3%
125725 1
0.3%
125733 1
0.3%
126171 1
0.3%
128065 1
0.3%
130465 1
0.3%
133193 1
0.3%
ValueCountFrequency (%)
10249679 1
0.3%
10143645 1
0.3%
10103233 1
0.3%
10022181 1
0.3%
9930616 1
0.3%
9857426 1
0.3%
9765623 1
0.3%
9729107 1
0.3%
9668465 1
0.3%
9509458 1
0.3%

등록회원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct203
Distinct (%)78.1%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean818.00769
Minimum108
Maximum12427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-04T04:24:26.869988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile194
Q1271
median454.5
Q3549.25
95-th percentile839.2
Maximum12427
Range12319
Interquartile range (IQR)278.25

Descriptive statistics

Standard deviation2026.6227
Coefficient of variation (CV)2.4775105
Kurtosis24.765204
Mean818.00769
Median Absolute Deviation (MAD)132.5
Skewness5.081221
Sum212682
Variance4107199.4
MonotonicityNot monotonic
2024-05-04T04:24:27.386667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
494 4
 
1.4%
246 3
 
1.0%
271 3
 
1.0%
508 3
 
1.0%
530 3
 
1.0%
519 3
 
1.0%
198 3
 
1.0%
257 3
 
1.0%
233 3
 
1.0%
238 3
 
1.0%
Other values (193) 229
80.1%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
108 1
0.3%
136 1
0.3%
150 1
0.3%
152 1
0.3%
156 1
0.3%
159 1
0.3%
162 1
0.3%
184 1
0.3%
189 1
0.3%
192 1
0.3%
ValueCountFrequency (%)
12427 1
0.3%
12369 1
0.3%
12008 1
0.3%
11936 1
0.3%
11871 1
0.3%
11870 1
0.3%
11529 1
0.3%
9950 1
0.3%
6772 1
0.3%
5609 1
0.3%

장기재원건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)19.2%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean27.915385
Minimum0
Maximum502
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-04T04:24:27.891878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q19
median13
Q321
95-th percentile38.05
Maximum502
Range502
Interquartile range (IQR)12

Descriptive statistics

Standard deviation72.230918
Coefficient of variation (CV)2.587495
Kurtosis28.871387
Mean27.915385
Median Absolute Deviation (MAD)6
Skewness5.3910072
Sum7258
Variance5217.3056
MonotonicityNot monotonic
2024-05-04T04:24:28.334206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 17
 
5.9%
10 15
 
5.2%
13 15
 
5.2%
11 15
 
5.2%
2 13
 
4.5%
12 12
 
4.2%
15 11
 
3.8%
14 11
 
3.8%
18 10
 
3.5%
8 10
 
3.5%
Other values (40) 131
45.8%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
0 2
 
0.7%
1 3
 
1.0%
2 13
4.5%
3 7
2.4%
4 6
 
2.1%
5 8
2.8%
6 8
2.8%
7 7
2.4%
8 10
3.5%
9 17
5.9%
ValueCountFrequency (%)
502 1
0.3%
480 2
0.7%
450 1
0.3%
401 1
0.3%
392 1
0.3%
364 1
0.3%
277 1
0.3%
164 1
0.3%
119 1
0.3%
45 1
0.3%

경험율(%)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct111
Distinct (%)42.7%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean3.378
Minimum0
Maximum10.3
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-04T04:24:28.907639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9
Q12.1
median3.1
Q34.385
95-th percentile6.4525
Maximum10.3
Range10.3
Interquartile range (IQR)2.285

Descriptive statistics

Standard deviation1.7722139
Coefficient of variation (CV)0.52463406
Kurtosis1.1523301
Mean3.378
Median Absolute Deviation (MAD)1.1
Skewness0.86864584
Sum878.28
Variance3.1407419
MonotonicityNot monotonic
2024-05-04T04:24:29.399216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.9 9
 
3.1%
2.6 9
 
3.1%
2.3 8
 
2.8%
3.0 8
 
2.8%
3.5 7
 
2.4%
1.8 7
 
2.4%
3.4 6
 
2.1%
4.0 6
 
2.1%
1.9 6
 
2.1%
2.5 6
 
2.1%
Other values (101) 188
65.7%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
0.0 2
 
0.7%
0.4 1
 
0.3%
0.5 2
 
0.7%
0.6 1
 
0.3%
0.7 3
1.0%
0.8 3
1.0%
0.9 3
1.0%
0.99 1
 
0.3%
1.0 1
 
0.3%
1.1 5
1.7%
ValueCountFrequency (%)
10.3 1
0.3%
9.7 1
0.3%
9.0 1
0.3%
8.52 1
0.3%
7.9 1
0.3%
7.8 2
0.7%
7.5 1
0.3%
7.2 1
0.3%
7.17 1
0.3%
6.8 1
0.3%

Interactions

2024-05-04T04:24:21.031310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:14.561017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:15.943167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:17.558413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:19.118075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:21.347392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:14.836610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:16.217677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:17.894484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:19.720693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:21.617550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:15.096833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:16.533639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:18.210216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:20.056211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:21.905246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:15.377868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:16.903457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:18.505255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:20.381145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:22.261036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:15.630968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:17.240252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:18.802319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:24:20.691495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:24:29.734772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역이름주민등록인구등록회원장기재원건수경험율(%)
연도1.0000.0000.0000.0000.0000.434
지역이름0.0001.0001.0000.6870.5640.552
주민등록인구0.0001.0001.0001.0001.0000.000
등록회원0.0000.6871.0001.0001.0000.000
장기재원건수0.0000.5641.0001.0001.0000.000
경험율(%)0.4340.5520.0000.0000.0001.000
2024-05-04T04:24:30.064484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도주민등록인구등록회원장기재원건수경험율(%)지역이름
연도1.000-0.078-0.395-0.2030.0470.000
주민등록인구-0.0781.0000.5280.3970.0440.952
등록회원-0.3950.5281.0000.6820.0800.395
장기재원건수-0.2030.3970.6821.0000.7300.268
경험율(%)0.0470.0440.0800.7301.0000.226
지역이름0.0000.9520.3950.2680.2261.000

Missing values

2024-05-04T04:24:22.762142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:24:23.111698image/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.
2024-05-04T04:24:23.396212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연도지역이름주민등록인구등록회원장기재원건수경험율(%)
02022서초구<NA><NA><NA><NA>
12022마포구<NA><NA><NA><NA>
22022동작구<NA><NA><NA><NA>
32022서울시<NA><NA><NA><NA>
42022강남구<NA><NA><NA><NA>
52022종로구<NA><NA><NA><NA>
62022도봉구<NA><NA><NA><NA>
72022금천구<NA><NA><NA><NA>
82022강북구<NA><NA><NA><NA>
92022성북구<NA><NA><NA><NA>
연도지역이름주민등록인구등록회원장기재원건수경험율(%)
2762011성동구30071150361.2
2772011중구133193364184.9
2782011은평구493634417133.1
2792011종로구16838223341.7
2802011동작구40140847191.9
2812011노원구6039301246282.2
2822011강북구345054594152.5
2832011강서구569072813151.8
2842011도봉구365573833111.3
2852011서대문구31485253491.7