Overview

Dataset statistics

Number of variables6
Number of observations5771
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory304.5 KiB
Average record size in memory54.0 B

Variable types

Numeric5
Categorical1

Dataset

Description순번,년도,차수,일차(1일차,2일차),분반번호,교육신청idx(tb_edu_join테이블)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15707/S/1/datasetView.do

Alerts

년도 is highly overall correlated with 차수 and 1 other fieldsHigh correlation
차수 is highly overall correlated with 년도 and 1 other fieldsHigh correlation
교육신청idx(tb_edu_join테이블) is highly overall correlated with 년도 and 1 other fieldsHigh correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-05-11 06:08:43.744790
Analysis finished2024-05-11 06:08:49.158937
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct5771
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4579.7881
Minimum21
Maximum9996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.9 KiB
2024-05-11T15:08:49.285540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile484.5
Q12489.5
median4506
Q36631.5
95-th percentile8740.5
Maximum9996
Range9975
Interquartile range (IQR)4142

Descriptive statistics

Standard deviation2528.6176
Coefficient of variation (CV)0.55212546
Kurtosis-0.92790599
Mean4579.7881
Median Absolute Deviation (MAD)2090
Skewness0.05748183
Sum26429957
Variance6393906.9
MonotonicityStrictly decreasing
2024-05-11T15:08:49.496852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9996 1
 
< 0.1%
3279 1
 
< 0.1%
3281 1
 
< 0.1%
3282 1
 
< 0.1%
3283 1
 
< 0.1%
3284 1
 
< 0.1%
3285 1
 
< 0.1%
3286 1
 
< 0.1%
3287 1
 
< 0.1%
3288 1
 
< 0.1%
Other values (5761) 5761
99.8%
ValueCountFrequency (%)
21 1
< 0.1%
42 1
< 0.1%
43 1
< 0.1%
44 1
< 0.1%
45 1
< 0.1%
46 1
< 0.1%
47 1
< 0.1%
48 1
< 0.1%
49 1
< 0.1%
50 1
< 0.1%
ValueCountFrequency (%)
9996 1
< 0.1%
9987 1
< 0.1%
9971 1
< 0.1%
9959 1
< 0.1%
9945 1
< 0.1%
9943 1
< 0.1%
9933 1
< 0.1%
9920 1
< 0.1%
9900 1
< 0.1%
9897 1
< 0.1%

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.6862
Minimum2017
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.9 KiB
2024-05-11T15:08:49.663665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32019
95-th percentile2021
Maximum2024
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2780434
Coefficient of variation (CV)0.00063310654
Kurtosis-0.54169604
Mean2018.6862
Median Absolute Deviation (MAD)1
Skewness0.55444282
Sum11649838
Variance1.633395
MonotonicityNot monotonic
2024-05-11T15:08:50.163234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 1838
31.8%
2019 1670
28.9%
2017 1047
18.1%
2021 893
15.5%
2020 320
 
5.5%
2024 3
 
0.1%
ValueCountFrequency (%)
2017 1047
18.1%
2018 1838
31.8%
2019 1670
28.9%
2020 320
 
5.5%
2021 893
15.5%
2024 3
 
0.1%
ValueCountFrequency (%)
2024 3
 
0.1%
2021 893
15.5%
2020 320
 
5.5%
2019 1670
28.9%
2018 1838
31.8%
2017 1047
18.1%

차수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3671807
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.9 KiB
2024-05-11T15:08:50.383086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q310
95-th percentile13
Maximum13
Range12
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.1810612
Coefficient of variation (CV)0.77900511
Kurtosis-1.1600698
Mean5.3671807
Median Absolute Deviation (MAD)2
Skewness0.62422121
Sum30974
Variance17.481273
MonotonicityNot monotonic
2024-05-11T15:08:50.567358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 1165
20.2%
3 946
16.4%
2 780
13.5%
11 675
11.7%
4 587
10.2%
13 510
8.8%
10 416
 
7.2%
6 309
 
5.4%
7 276
 
4.8%
9 54
 
0.9%
Other values (2) 53
 
0.9%
ValueCountFrequency (%)
1 1165
20.2%
2 780
13.5%
3 946
16.4%
4 587
10.2%
6 309
 
5.4%
7 276
 
4.8%
8 15
 
0.3%
9 54
 
0.9%
10 416
 
7.2%
11 675
11.7%
ValueCountFrequency (%)
13 510
8.8%
12 38
 
0.7%
11 675
11.7%
10 416
7.2%
9 54
 
0.9%
8 15
 
0.3%
7 276
 
4.8%
6 309
 
5.4%
4 587
10.2%
3 946
16.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.2 KiB
1
2978 
2
2793 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 2978
51.6%
2 2793
48.4%

Length

2024-05-11T15:08:50.767486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:08:50.937329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2978
51.6%
2 2793
48.4%

분반번호
Real number (ℝ)

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9199446
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.9 KiB
2024-05-11T15:08:51.080112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile14
Maximum20
Range19
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.0944866
Coefficient of variation (CV)0.69164273
Kurtosis0.70964612
Mean5.9199446
Median Absolute Deviation (MAD)3
Skewness1.0273737
Sum34164
Variance16.764821
MonotonicityNot monotonic
2024-05-11T15:08:51.281718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3 656
11.4%
1 655
11.3%
4 640
11.1%
2 626
10.8%
6 542
9.4%
5 540
9.4%
7 464
8.0%
8 422
7.3%
11 240
 
4.2%
12 207
 
3.6%
Other values (10) 779
13.5%
ValueCountFrequency (%)
1 655
11.3%
2 626
10.8%
3 656
11.4%
4 640
11.1%
5 540
9.4%
6 542
9.4%
7 464
8.0%
8 422
7.3%
9 177
 
3.1%
10 156
 
2.7%
ValueCountFrequency (%)
20 27
 
0.5%
19 27
 
0.5%
18 41
 
0.7%
17 38
 
0.7%
16 50
 
0.9%
15 69
 
1.2%
14 82
 
1.4%
13 112
1.9%
12 207
3.6%
11 240
4.2%

교육신청idx(tb_edu_join테이블)
Real number (ℝ)

HIGH CORRELATION 

Distinct3266
Distinct (%)56.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3070.1814
Minimum2
Maximum6229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.9 KiB
2024-05-11T15:08:51.540293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile329
Q11876
median3064
Q34335
95-th percentile5474
Maximum6229
Range6227
Interquartile range (IQR)2459

Descriptive statistics

Standard deviation1556.7977
Coefficient of variation (CV)0.50707027
Kurtosis-0.95328421
Mean3070.1814
Median Absolute Deviation (MAD)1218
Skewness-0.093126159
Sum17718017
Variance2423619.2
MonotonicityNot monotonic
2024-05-11T15:08:51.718776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1819 2
 
< 0.1%
3326 2
 
< 0.1%
3393 2
 
< 0.1%
3392 2
 
< 0.1%
3366 2
 
< 0.1%
3278 2
 
< 0.1%
3276 2
 
< 0.1%
3337 2
 
< 0.1%
3318 2
 
< 0.1%
3313 2
 
< 0.1%
Other values (3256) 5751
99.7%
ValueCountFrequency (%)
2 2
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
6229 1
< 0.1%
6175 1
< 0.1%
6107 1
< 0.1%
5638 2
< 0.1%
5637 2
< 0.1%
5636 2
< 0.1%
5634 2
< 0.1%
5633 2
< 0.1%
5632 1
< 0.1%
5631 2
< 0.1%

Interactions

2024-05-11T15:08:48.120476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:44.711211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.623609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.427082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.145375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:48.271650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:44.886867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.803387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.541676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.311020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:48.411769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.075851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.977012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.681715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.568178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:48.560661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.232113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.125457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.844784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.761604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:48.707815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:45.407519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:46.282450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.003258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:08:47.959561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:08:51.850868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번년도차수일차(1일차,2일차)분반번호교육신청idx(tb_edu_join테이블)
순번1.0000.9520.7530.1390.5960.932
년도0.9521.0000.7400.0000.5250.864
차수0.7530.7401.0000.0000.4680.766
일차(1일차,2일차)0.1390.0000.0001.0000.0000.049
분반번호0.5960.5250.4680.0001.0000.615
교육신청idx(tb_edu_join테이블)0.9320.8640.7660.0490.6151.000
2024-05-11T15:08:52.021986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번년도차수분반번호교육신청idx(tb_edu_join테이블)일차(1일차,2일차)
순번1.0000.3950.2130.0790.4010.107
년도0.3951.0000.5720.0100.9660.000
차수0.2130.5721.0000.1410.6870.000
분반번호0.0790.0100.1411.0000.0690.000
교육신청idx(tb_edu_join테이블)0.4010.9660.6870.0691.0000.038
일차(1일차,2일차)0.1070.0000.0000.0000.0381.000

Missing values

2024-05-11T15:08:48.903872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:08:49.088422image/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

순번년도차수일차(1일차,2일차)분반번호교육신청idx(tb_edu_join테이블)
0999620181241819
1998720181241821
2997120181241783
3995920181241686
4994520181241818
5994320181241820
6993320181241589
7992020181241796
8990020181241744
9989720181241579
순번년도차수일차(1일차,2일차)분반번호교육신청idx(tb_edu_join테이블)
57615020171111872
57624920171111254
57634820171111341
57644720171111314
57654620171111323
57664520171111329
57674420171111268
57684320171111331
57694220171111166
57702120181241592