Overview

Dataset statistics

Number of variables4
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory37.5 B

Variable types

Numeric4

Dataset

Description이 데이터는 2017년 1월 부터 2024년 3월까지의 안심귀가 스카우트 서비스 월별 현황입니다. 이 데이터에는 귀가지원, 순찰 현황이 포함되어 있습니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15055180/fileData.do

Alerts

연도 is highly overall correlated with 귀가지원High correlation
귀가지원 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
순찰 is highly overall correlated with 귀가지원High correlation
귀가지원 has 2 (2.3%) zerosZeros
순찰 has 2 (2.3%) zerosZeros

Reproduction

Analysis started2024-04-20 05:22:05.069745
Analysis finished2024-04-20 05:22:13.322884
Duration8.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.1379
Minimum2017
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-20T05:22:13.713860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32022
95-th percentile2023
Maximum2024
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1085232
Coefficient of variation (CV)0.0010437521
Kurtosis-1.1786975
Mean2020.1379
Median Absolute Deviation (MAD)2
Skewness0.042607818
Sum175752
Variance4.4458701
MonotonicityIncreasing
2024-04-20T05:22:14.277093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2017 12
13.8%
2018 12
13.8%
2019 12
13.8%
2020 12
13.8%
2021 12
13.8%
2022 12
13.8%
2023 12
13.8%
2024 3
 
3.4%
ValueCountFrequency (%)
2017 12
13.8%
2018 12
13.8%
2019 12
13.8%
2020 12
13.8%
2021 12
13.8%
2022 12
13.8%
2023 12
13.8%
2024 3
 
3.4%
ValueCountFrequency (%)
2024 3
 
3.4%
2023 12
13.8%
2022 12
13.8%
2021 12
13.8%
2020 12
13.8%
2019 12
13.8%
2018 12
13.8%
2017 12
13.8%

월
Real number (ℝ)

Distinct12
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3448276
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-20T05:22:14.740372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5135207
Coefficient of variation (CV)0.55376141
Kurtosis-1.2492461
Mean6.3448276
Median Absolute Deviation (MAD)3
Skewness0.053278732
Sum552
Variance12.344828
MonotonicityNot monotonic
2024-04-20T05:22:15.160990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 8
9.2%
2 8
9.2%
3 8
9.2%
4 7
8.0%
5 7
8.0%
6 7
8.0%
7 7
8.0%
8 7
8.0%
9 7
8.0%
10 7
8.0%
Other values (2) 14
16.1%
ValueCountFrequency (%)
1 8
9.2%
2 8
9.2%
3 8
9.2%
4 7
8.0%
5 7
8.0%
6 7
8.0%
7 7
8.0%
8 7
8.0%
9 7
8.0%
10 7
8.0%
ValueCountFrequency (%)
12 7
8.0%
11 7
8.0%
10 7
8.0%
9 7
8.0%
8 7
8.0%
7 7
8.0%
6 7
8.0%
5 7
8.0%
4 7
8.0%
3 8
9.2%

귀가지원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct85
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1225.6207
Minimum0
Maximum1925
Zeros2
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-20T05:22:15.631924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile328.5
Q1852
median1395
Q31587.5
95-th percentile1848.8
Maximum1925
Range1925
Interquartile range (IQR)735.5

Descriptive statistics

Standard deviation470.98243
Coefficient of variation (CV)0.38428074
Kurtosis-0.3399121
Mean1225.6207
Median Absolute Deviation (MAD)329
Skewness-0.6470411
Sum106629
Variance221824.45
MonotonicityNot monotonic
2024-04-20T05:22:16.120333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1839 2
 
2.3%
0 2
 
2.3%
1219 1
 
1.1%
1353 1
 
1.1%
938 1
 
1.1%
849 1
 
1.1%
655 1
 
1.1%
450 1
 
1.1%
865 1
 
1.1%
1360 1
 
1.1%
Other values (75) 75
86.2%
ValueCountFrequency (%)
0 2
2.3%
252 1
1.1%
265 1
1.1%
306 1
1.1%
381 1
1.1%
450 1
1.1%
508 1
1.1%
653 1
1.1%
655 1
1.1%
757 1
1.1%
ValueCountFrequency (%)
1925 1
1.1%
1903 1
1.1%
1870 1
1.1%
1859 1
1.1%
1853 1
1.1%
1839 2
2.3%
1803 1
1.1%
1785 1
1.1%
1731 1
1.1%
1724 1
1.1%

순찰
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct85
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean816.35632
Minimum0
Maximum1206
Zeros2
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-20T05:22:16.836145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile340.9
Q1689
median856
Q3992.5
95-th percentile1125.7
Maximum1206
Range1206
Interquartile range (IQR)303.5

Descriptive statistics

Standard deviation253.0176
Coefficient of variation (CV)0.30993525
Kurtosis1.5545171
Mean816.35632
Median Absolute Deviation (MAD)152
Skewness-1.1618383
Sum71023
Variance64017.906
MonotonicityNot monotonic
2024-04-20T05:22:17.467527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
890 2
 
2.3%
0 2
 
2.3%
583 1
 
1.1%
995 1
 
1.1%
658 1
 
1.1%
500 1
 
1.1%
399 1
 
1.1%
731 1
 
1.1%
973 1
 
1.1%
1010 1
 
1.1%
Other values (75) 75
86.2%
ValueCountFrequency (%)
0 2
2.3%
134 1
1.1%
272 1
1.1%
316 1
1.1%
399 1
1.1%
415 1
1.1%
435 1
1.1%
490 1
1.1%
500 1
1.1%
504 1
1.1%
ValueCountFrequency (%)
1206 1
1.1%
1194 1
1.1%
1186 1
1.1%
1134 1
1.1%
1129 1
1.1%
1118 1
1.1%
1104 1
1.1%
1102 1
1.1%
1101 1
1.1%
1086 1
1.1%

Interactions

2024-04-20T05:22:11.487406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:08.530066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:09.611869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:10.516784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:11.744943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:08.806147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:09.863994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:10.758459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:12.071383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:09.064905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:10.100235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:10.934558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:12.383993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:09.342399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:10.331203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:11.230940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T05:22:17.731720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월귀가지원순찰
연도1.0000.0000.7600.693
월0.0001.0000.0000.413
귀가지원0.7600.0001.0000.916
순찰0.6930.4130.9161.000
2024-04-20T05:22:17.986252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월귀가지원순찰
연도1.000-0.076-0.747-0.298
월-0.0761.0000.3240.437
귀가지원-0.7470.3241.0000.700
순찰-0.2980.4370.7001.000

Missing values

2024-04-20T05:22:12.749958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T05:22:13.213157image/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

연도월귀가지원순찰
0201711219583
1201721216585
2201731925963
3201741839852
4201751691817
5201761859904
6201771870929
7201781903938
8201791719921
92017101321688
연도월귀가지원순찰
7720236832775
7820237653566
7920238859890
8020239769690
81202310779789
82202311831793
83202312770931
8420241252272
8520242265134
8620243381490