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,비입원자수,유지율(%)
Author서울시정신건강복지센터
URLhttps://data.seoul.go.kr/dataList/OA-20333/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
비입원자수 is highly overall correlated with 등록회원 and 1 other fieldsHigh correlation
유지율(%) is highly overall correlated with 비입원자수High correlation
지역이름 is highly overall correlated with 주민등록인구High correlation
주민등록인구 has 26 (9.1%) missing valuesMissing
등록회원 has 26 (9.1%) missing valuesMissing
비입원자수 has 26 (9.1%) missing valuesMissing
유지율(%) has 26 (9.1%) missing valuesMissing

Reproduction

Analysis started2024-04-06 13:17:04.323227
Analysis finished2024-04-06 13:17:07.839005
Duration3.52 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
2024-04-06T22:17:07.894557image/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
2024-04-06T22:17:08.001732image/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

2024-04-06T22:17:08.124753image/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
2024-04-06T22:17:08.262460image/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
2024-04-06T22:17:08.402067image/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
2024-04-06T22:17:08.539721image/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
2024-04-06T22:17:08.683425image/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%

비입원자수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct214
Distinct (%)82.3%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean736.13846
Minimum74
Maximum11989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-06T22:17:08.852249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile136.9
Q1242.5
median416
Q3509
95-th percentile778.55
Maximum11989
Range11915
Interquartile range (IQR)266.5

Descriptive statistics

Standard deviation1848.8381
Coefficient of variation (CV)2.5115359
Kurtosis25.860045
Mean736.13846
Median Absolute Deviation (MAD)132
Skewness5.1784439
Sum191396
Variance3418202.5
MonotonicityNot monotonic
2024-04-06T22:17:08.995471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
468 4
 
1.4%
264 3
 
1.0%
449 3
 
1.0%
431 3
 
1.0%
464 2
 
0.7%
216 2
 
0.7%
190 2
 
0.7%
430 2
 
0.7%
327 2
 
0.7%
509 2
 
0.7%
Other values (204) 235
82.2%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
74 1
0.3%
92 1
0.3%
98 2
0.7%
100 1
0.3%
115 2
0.7%
119 2
0.7%
126 1
0.3%
134 2
0.7%
135 1
0.3%
137 1
0.3%
ValueCountFrequency (%)
11989 1
0.3%
11332 1
0.3%
11271 1
0.3%
10823 1
0.3%
10789 1
0.3%
10595 1
0.3%
10454 1
0.3%
9114 1
0.3%
5533 1
0.3%
3790 1
0.3%

유지율(%)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct194
Distinct (%)74.6%
Missing26
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean88.164885
Minimum54.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-06T22:17:09.161712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54.4
5-th percentile64.645
Q186.2
median90.7
Q394.2925
95-th percentile97.2305
Maximum100
Range45.6
Interquartile range (IQR)8.0925

Descriptive statistics

Standard deviation9.3608862
Coefficient of variation (CV)0.10617477
Kurtosis3.1615802
Mean88.164885
Median Absolute Deviation (MAD)3.95
Skewness-1.8381115
Sum22922.87
Variance87.62619
MonotonicityNot monotonic
2024-04-06T22:17:09.384502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89.4 4
 
1.4%
90.7 4
 
1.4%
91.5 4
 
1.4%
94.1 3
 
1.0%
90.9 3
 
1.0%
92.9 3
 
1.0%
88.3 3
 
1.0%
91.3 3
 
1.0%
91.9 3
 
1.0%
87.2 3
 
1.0%
Other values (184) 227
79.4%
(Missing) 26
 
9.1%
ValueCountFrequency (%)
54.4 1
0.3%
54.9 1
0.3%
55.0 2
0.7%
58.9 1
0.3%
59.0 1
0.3%
60.5 1
0.3%
62.0 1
0.3%
62.3 1
0.3%
62.9 1
0.3%
63.1 1
0.3%
ValueCountFrequency (%)
100.0 1
0.3%
98.8 1
0.3%
98.66 1
0.3%
97.93 1
0.3%
97.88 1
0.3%
97.86 1
0.3%
97.75 1
0.3%
97.62 1
0.3%
97.55 1
0.3%
97.52 1
0.3%

Interactions

2024-04-06T22:17:07.077402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:04.608952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.155531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.822607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.519794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:07.176473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:04.714815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.276621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.945507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.643866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:07.258360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:04.836199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.401924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.077471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.773488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:07.345277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:04.936450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.539427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.263796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.874894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:07.431388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.033389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:05.690514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.413404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:17:06.984222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T22:17:09.485884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역이름주민등록인구등록회원비입원자수유지율(%)
연도1.0000.0000.0000.0000.0000.710
지역이름0.0001.0001.0000.6870.6240.056
주민등록인구0.0001.0001.0001.0001.0000.000
등록회원0.0000.6871.0001.0001.0000.365
비입원자수0.0000.6241.0001.0001.0000.242
유지율(%)0.7100.0560.0000.3650.2421.000
2024-04-06T22:17:09.591388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도주민등록인구등록회원비입원자수유지율(%)지역이름
연도1.000-0.078-0.395-0.406-0.2670.000
주민등록인구-0.0781.0000.5280.4940.0250.952
등록회원-0.3950.5281.0000.9890.4520.395
비입원자수-0.4060.4940.9891.0000.5550.325
유지율(%)-0.2670.0250.4520.5551.0000.000
지역이름0.0000.9520.3950.3250.0001.000

Missing values

2024-04-06T22:17:07.542305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T22:17:07.654462image/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.
2024-04-06T22:17:07.771443image/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

연도지역이름주민등록인구등록회원비입원자수유지율(%)
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>
연도지역이름주민등록인구등록회원비입원자수유지율(%)
2762011성동구30071150347995.22
2772011중구13319336432789.83
2782011은평구49363441734181.77
2792011종로구16838223320487.55
2802011동작구40140847142189.38
2812011노원구6039301246116193.17
2822011강북구34505459454691.91
2832011강서구56907281374591.63
2842011도봉구36557383377492.91
2852011서대문구31485253444984.08