Overview

Dataset statistics

Number of variables5
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory48.3 B

Variable types

Text1
Numeric4

Dataset

Description경기도 노인학대 현황
Author경기도사회서비스원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=X49V6YUNVPPF30IOHEJN31609680&infSeq=1

Alerts

총사례수 is highly overall correlated with 일반사례수 and 2 other fieldsHigh correlation
일반사례수 is highly overall correlated with 총사례수 and 1 other fieldsHigh correlation
가정학대사례수 is highly overall correlated with 총사례수 and 2 other fieldsHigh correlation
시설학대사례수 is highly overall correlated with 총사례수 and 1 other fieldsHigh correlation
시군명 has unique valuesUnique
시설학대사례수 has 5 (16.1%) zerosZeros

Reproduction

Analysis started2024-03-23 01:43:42.649779
Analysis finished2024-03-23 01:43:47.645638
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-23T01:43:47.947139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Characters and Unicode

Total characters96
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row광명시
5th row광주시
ValueCountFrequency (%)
가평군 1
 
3.2%
안양시 1
 
3.2%
하남시 1
 
3.2%
포천시 1
 
3.2%
평택시 1
 
3.2%
파주시 1
 
3.2%
이천시 1
 
3.2%
의정부시 1
 
3.2%
의왕시 1
 
3.2%
용인시 1
 
3.2%
Other values (21) 21
67.7%
2024-03-23T01:43:48.754674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

총사례수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.6129
Minimum13
Maximum330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-23T01:43:49.197757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile19.5
Q133.5
median76
Q3153.5
95-th percentile297.5
Maximum330
Range317
Interquartile range (IQR)120

Descriptive statistics

Standard deviation94.078576
Coefficient of variation (CV)0.85828012
Kurtosis-0.01151686
Mean109.6129
Median Absolute Deviation (MAD)54
Skewness1.0577542
Sum3398
Variance8850.7785
MonotonicityNot monotonic
2024-03-23T01:43:49.606616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
76 2
 
6.5%
22 2
 
6.5%
21 1
 
3.2%
157 1
 
3.2%
95 1
 
3.2%
37 1
 
3.2%
57 1
 
3.2%
82 1
 
3.2%
150 1
 
3.2%
298 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
13 1
3.2%
19 1
3.2%
20 1
3.2%
21 1
3.2%
22 2
6.5%
24 1
3.2%
30 1
3.2%
37 1
3.2%
53 1
3.2%
57 1
3.2%
ValueCountFrequency (%)
330 1
3.2%
298 1
3.2%
297 1
3.2%
266 1
3.2%
227 1
3.2%
213 1
3.2%
196 1
3.2%
157 1
3.2%
150 1
3.2%
147 1
3.2%

일반사례수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.548387
Minimum5
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-23T01:43:49.995476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.5
Q113
median49
Q370
95-th percentile164
Maximum188
Range183
Interquartile range (IQR)57

Descriptive statistics

Standard deviation49.926505
Coefficient of variation (CV)0.89879307
Kurtosis1.1553513
Mean55.548387
Median Absolute Deviation (MAD)35
Skewness1.2948463
Sum1722
Variance2492.6559
MonotonicityNot monotonic
2024-03-23T01:43:50.424887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
11 2
 
6.5%
13 2
 
6.5%
38 2
 
6.5%
6 1
 
3.2%
50 1
 
3.2%
67 1
 
3.2%
56 1
 
3.2%
63 1
 
3.2%
14 1
 
3.2%
175 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
5 1
3.2%
6 1
3.2%
9 1
3.2%
10 1
3.2%
11 2
6.5%
12 1
3.2%
13 2
6.5%
14 1
3.2%
18 1
3.2%
34 1
3.2%
ValueCountFrequency (%)
188 1
3.2%
175 1
3.2%
153 1
3.2%
129 1
3.2%
106 1
3.2%
85 1
3.2%
83 1
3.2%
73 1
3.2%
67 1
3.2%
65 1
3.2%

가정학대사례수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.741935
Minimum4
Maximum198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-23T01:43:50.816112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6
Q114.5
median29
Q364.5
95-th percentile149
Maximum198
Range194
Interquartile range (IQR)50

Descriptive statistics

Standard deviation47.965938
Coefficient of variation (CV)1.0261864
Kurtosis2.8333535
Mean46.741935
Median Absolute Deviation (MAD)18
Skewness1.7528838
Sum1449
Variance2300.7312
MonotonicityNot monotonic
2024-03-23T01:43:51.254472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
25 2
 
6.5%
39 2
 
6.5%
17 2
 
6.5%
12 1
 
3.2%
54 1
 
3.2%
34 1
 
3.2%
24 1
 
3.2%
79 1
 
3.2%
7 1
 
3.2%
97 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
4 1
3.2%
5 1
3.2%
7 1
3.2%
8 1
3.2%
10 1
3.2%
11 1
3.2%
12 1
3.2%
14 1
3.2%
15 1
3.2%
17 2
6.5%
ValueCountFrequency (%)
198 1
3.2%
163 1
3.2%
135 1
3.2%
97 1
3.2%
88 1
3.2%
83 1
3.2%
79 1
3.2%
74 1
3.2%
55 1
3.2%
54 1
3.2%

시설학대사례수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3225806
Minimum0
Maximum41
Zeros5
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-23T01:43:51.749905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38.5
95-th percentile32
Maximum41
Range41
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation10.621949
Coefficient of variation (CV)1.4505746
Kurtosis4.2969307
Mean7.3225806
Median Absolute Deviation (MAD)3
Skewness2.1904257
Sum227
Variance112.82581
MonotonicityNot monotonic
2024-03-23T01:43:52.172595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 5
16.1%
1 5
16.1%
3 4
12.9%
2 3
9.7%
9 2
 
6.5%
4 2
 
6.5%
23 1
 
3.2%
10 1
 
3.2%
8 1
 
3.2%
26 1
 
3.2%
Other values (6) 6
19.4%
ValueCountFrequency (%)
0 5
16.1%
1 5
16.1%
2 3
9.7%
3 4
12.9%
4 2
 
6.5%
5 1
 
3.2%
6 1
 
3.2%
7 1
 
3.2%
8 1
 
3.2%
9 2
 
6.5%
ValueCountFrequency (%)
41 1
3.2%
38 1
3.2%
26 1
3.2%
23 1
3.2%
14 1
3.2%
10 1
3.2%
9 2
6.5%
8 1
3.2%
7 1
3.2%
6 1
3.2%

Interactions

2024-03-23T01:43:46.111834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:42.926532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:44.005307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:45.044367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:46.351217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:43.183017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:44.274087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:45.286614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:46.721627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:43.435274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:44.524040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:45.605462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:46.978968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:43.712159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:44.793240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:43:45.877634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T01:43:52.415155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명총사례수일반사례수가정학대사례수시설학대사례수
시군명1.0001.0001.0001.0001.000
총사례수1.0001.0000.8700.8650.828
일반사례수1.0000.8701.0000.7650.713
가정학대사례수1.0000.8650.7651.0000.772
시설학대사례수1.0000.8280.7130.7721.000
2024-03-23T01:43:52.691561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총사례수일반사례수가정학대사례수시설학대사례수
총사례수1.0000.9400.9400.511
일반사례수0.9401.0000.8150.314
가정학대사례수0.9400.8151.0000.586
시설학대사례수0.5110.3140.5861.000

Missing values

2024-03-23T01:43:47.289787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T01:43:47.533287image/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

시군명총사례수일반사례수가정학대사례수시설학대사례수
0가평군216123
1고양시33015316314
2과천시191180
3광명시7949291
4광주시7339313
5구리시7618553
6군포시7651250
7김포시7834395
8남양주시2975819841
9동두천시2412111
시군명총사례수일반사례수가정학대사례수시설학대사례수
21오산시5338141
22용인시196858823
23의왕시20956
24의정부시2981759726
25이천시221471
26파주시15063798
27평택시8256242
28포천시57133410
29하남시3711179
30화성시9567253