Overview

Dataset statistics

Number of variables5
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory45.0 B

Variable types

Numeric3
Categorical2

Dataset

Description영치년도,영치월,영치기관,영치기관코드,영치건수
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-20256/S/1/datasetView.do

Alerts

영치기관 has constant value ""Constant
영치기관코드 has constant value ""Constant

Reproduction

Analysis started2024-04-14 01:24:00.080487
Analysis finished2024-04-14 01:24:04.235843
Duration4.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

영치년도
Real number (ℝ)

Distinct11
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5902
Minimum2014
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-14T10:24:04.418943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2019
Q32021
95-th percentile2023
Maximum2024
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9451013
Coefficient of variation (CV)0.0014589892
Kurtosis-1.1982534
Mean2018.5902
Median Absolute Deviation (MAD)3
Skewness0.016043883
Sum246268
Variance8.6736215
MonotonicityDecreasing
2024-04-14T10:24:04.784975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2023 12
9.8%
2022 12
9.8%
2021 12
9.8%
2020 12
9.8%
2019 12
9.8%
2018 12
9.8%
2017 12
9.8%
2016 12
9.8%
2015 12
9.8%
2014 12
9.8%
ValueCountFrequency (%)
2014 12
9.8%
2015 12
9.8%
2016 12
9.8%
2017 12
9.8%
2018 12
9.8%
2019 12
9.8%
2020 12
9.8%
2021 12
9.8%
2022 12
9.8%
2023 12
9.8%
ValueCountFrequency (%)
2024 2
 
1.6%
2023 12
9.8%
2022 12
9.8%
2021 12
9.8%
2020 12
9.8%
2019 12
9.8%
2018 12
9.8%
2017 12
9.8%
2016 12
9.8%
2015 12
9.8%

영치월
Real number (ℝ)

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4180328
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-14T10:24:05.128180image/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 deviation3.4969648
Coefficient of variation (CV)0.54486553
Kurtosis-1.23558
Mean6.4180328
Median Absolute Deviation (MAD)3
Skewness0.020910043
Sum783
Variance12.228763
MonotonicityNot monotonic
2024-04-14T10:24:05.478626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 11
9.0%
1 11
9.0%
12 10
8.2%
11 10
8.2%
10 10
8.2%
9 10
8.2%
8 10
8.2%
7 10
8.2%
6 10
8.2%
5 10
8.2%
Other values (2) 20
16.4%
ValueCountFrequency (%)
1 11
9.0%
2 11
9.0%
3 10
8.2%
4 10
8.2%
5 10
8.2%
6 10
8.2%
7 10
8.2%
8 10
8.2%
9 10
8.2%
10 10
8.2%
ValueCountFrequency (%)
12 10
8.2%
11 10
8.2%
10 10
8.2%
9 10
8.2%
8 10
8.2%
7 10
8.2%
6 10
8.2%
5 10
8.2%
4 10
8.2%
3 10
8.2%

영치기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
용산구
122 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구 122
100.0%

Length

2024-04-14T10:24:05.854377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T10:24:06.161786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구 122
100.0%

영치기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
11170
122 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11170
2nd row11170
3rd row11170
4th row11170
5th row11170

Common Values

ValueCountFrequency (%)
11170 122
100.0%

Length

2024-04-14T10:24:06.475266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T10:24:06.770422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11170 122
100.0%

영치건수
Real number (ℝ)

Distinct62
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.713115
Minimum6
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-14T10:24:07.083081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile16.1
Q131
median44
Q359.75
95-th percentile81.85
Maximum137
Range131
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation22.489108
Coefficient of variation (CV)0.48143029
Kurtosis1.6560533
Mean46.713115
Median Absolute Deviation (MAD)14
Skewness0.93854937
Sum5699
Variance505.75999
MonotonicityNot monotonic
2024-04-14T10:24:07.341877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 6
 
4.9%
31 4
 
3.3%
49 4
 
3.3%
52 4
 
3.3%
34 4
 
3.3%
33 4
 
3.3%
30 3
 
2.5%
67 3
 
2.5%
41 3
 
2.5%
47 3
 
2.5%
Other values (52) 84
68.9%
ValueCountFrequency (%)
6 1
0.8%
8 2
1.6%
12 1
0.8%
14 2
1.6%
16 1
0.8%
18 1
0.8%
19 2
1.6%
20 1
0.8%
21 2
1.6%
22 2
1.6%
ValueCountFrequency (%)
137 1
0.8%
107 2
1.6%
101 1
0.8%
94 2
1.6%
82 1
0.8%
79 1
0.8%
77 2
1.6%
75 1
0.8%
74 2
1.6%
73 1
0.8%

Interactions

2024-04-14T10:24:02.961084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:01.488205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:02.234750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:03.209431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:01.736439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:02.475255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:03.452886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:01.977447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T10:24:02.712984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T10:24:07.503807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영치년도영치월영치건수
영치년도1.0000.0000.390
영치월0.0001.0000.276
영치건수0.3900.2761.000
2024-04-14T10:24:07.783309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영치년도영치월영치건수
영치년도1.000-0.041-0.211
영치월-0.0411.000-0.205
영치건수-0.211-0.2051.000

Missing values

2024-04-14T10:24:03.785781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T10:24:04.100726image/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

영치년도영치월영치기관영치기관코드영치건수
020242용산구1117020
120241용산구1117019
2202312용산구111708
3202311용산구1117016
4202310용산구1117021
520239용산구1117019
620238용산구1117026
720237용산구1117034
820236용산구1117039
920235용산구1117073
영치년도영치월영치기관영치기관코드영치건수
112201410용산구1117033
11320149용산구1117032
11420148용산구1117049
11520147용산구1117053
11620146용산구111706
11720145용산구1117030
11820144용산구1117029
11920143용산구1117028
12020142용산구1117029
12120141용산구1117028