Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1643
Duplicate rows (%)16.4%
Total size in memory429.7 KiB
Average record size in memory44.0 B

Variable types

Numeric4

Dataset

Description서울시 강서구 CCTV 관제시스템 데이터 개방 자료
Author서울특별시 강서구
URLhttps://www.data.go.kr/data/15072605/fileData.do

Alerts

Dataset has 1643 (16.4%) duplicate rowsDuplicates
접속년 is highly overall correlated with 접속건수High correlation
접속건수 is highly overall correlated with 접속년High correlation
접속건수 is highly skewed (γ1 = 57.88651581)Skewed

Reproduction

Analysis started2023-12-12 14:15:36.141625
Analysis finished2023-12-12 14:15:38.377202
Duration2.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접속년
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.727
Minimum2013
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:15:38.429035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12017
median2018
Q32019
95-th percentile2020
Maximum2020
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7670833
Coefficient of variation (CV)0.00087577916
Kurtosis0.45758224
Mean2017.727
Median Absolute Deviation (MAD)1
Skewness-0.76554629
Sum20177270
Variance3.1225833
MonotonicityNot monotonic
2023-12-12T23:15:38.573543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2019 2138
21.4%
2017 1902
19.0%
2016 1864
18.6%
2018 1805
18.1%
2020 1741
17.4%
2013 534
 
5.3%
2015 14
 
0.1%
2014 2
 
< 0.1%
ValueCountFrequency (%)
2013 534
 
5.3%
2014 2
 
< 0.1%
2015 14
 
0.1%
2016 1864
18.6%
2017 1902
19.0%
2018 1805
18.1%
2019 2138
21.4%
2020 1741
17.4%
ValueCountFrequency (%)
2020 1741
17.4%
2019 2138
21.4%
2018 1805
18.1%
2017 1902
19.0%
2016 1864
18.6%
2015 14
 
0.1%
2014 2
 
< 0.1%
2013 534
 
5.3%

접속월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5186
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:15:38.704376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2815135
Coefficient of variation (CV)0.50340771
Kurtosis-1.0870352
Mean6.5186
Median Absolute Deviation (MAD)3
Skewness-0.021801876
Sum65186
Variance10.768331
MonotonicityNot monotonic
2023-12-12T23:15:38.817221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 958
9.6%
8 956
9.6%
9 926
9.3%
6 925
9.2%
4 912
9.1%
5 893
8.9%
10 809
8.1%
3 761
7.6%
1 735
7.3%
11 713
7.1%
Other values (2) 1412
14.1%
ValueCountFrequency (%)
1 735
7.3%
2 706
7.1%
3 761
7.6%
4 912
9.1%
5 893
8.9%
6 925
9.2%
7 958
9.6%
8 956
9.6%
9 926
9.3%
10 809
8.1%
ValueCountFrequency (%)
12 706
7.1%
11 713
7.1%
10 809
8.1%
9 926
9.3%
8 956
9.6%
7 958
9.6%
6 925
9.2%
5 893
8.9%
4 912
9.1%
3 761
7.6%

접속일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.6982
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:15:38.956512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.807342
Coefficient of variation (CV)0.56104152
Kurtosis-1.2023891
Mean15.6982
Median Absolute Deviation (MAD)8
Skewness0.021673859
Sum156982
Variance77.569274
MonotonicityNot monotonic
2023-12-12T23:15:39.084960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7 355
 
3.5%
8 344
 
3.4%
6 342
 
3.4%
26 342
 
3.4%
11 339
 
3.4%
24 336
 
3.4%
10 335
 
3.4%
18 334
 
3.3%
12 333
 
3.3%
9 332
 
3.3%
Other values (21) 6608
66.1%
ValueCountFrequency (%)
1 320
3.2%
2 324
3.2%
3 323
3.2%
4 327
3.3%
5 327
3.3%
6 342
3.4%
7 355
3.5%
8 344
3.4%
9 332
3.3%
10 335
3.4%
ValueCountFrequency (%)
31 194
1.9%
30 302
3.0%
29 307
3.1%
28 328
3.3%
27 330
3.3%
26 342
3.4%
25 326
3.3%
24 336
3.4%
23 311
3.1%
22 319
3.2%

접속건수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1265
Minimum1
Maximum7350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:15:39.576146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile30
Maximum7350
Range7349
Interquartile range (IQR)1

Descriptive statistics

Standard deviation102.53053
Coefficient of variation (CV)16.73558
Kurtosis3647.833
Mean6.1265
Median Absolute Deviation (MAD)0
Skewness57.886516
Sum61265
Variance10512.51
MonotonicityNot monotonic
2023-12-12T23:15:39.735832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 6608
66.1%
1 2770
27.7%
30 274
 
2.7%
50 240
 
2.4%
20 23
 
0.2%
3 15
 
0.1%
6 4
 
< 0.1%
4 4
 
< 0.1%
14 2
 
< 0.1%
10 2
 
< 0.1%
Other values (48) 58
 
0.6%
ValueCountFrequency (%)
1 2770
27.7%
2 6608
66.1%
3 15
 
0.1%
4 4
 
< 0.1%
6 4
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 2
 
< 0.1%
11 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
7350 1
< 0.1%
5550 1
< 0.1%
3390 1
< 0.1%
2626 1
< 0.1%
652 1
< 0.1%
486 1
< 0.1%
364 1
< 0.1%
282 1
< 0.1%
264 1
< 0.1%
230 1
< 0.1%

Interactions

2023-12-12T23:15:37.687438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.518217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.882555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.287916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.820436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.609733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.971332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.390129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.941228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.701451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.057052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.481642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:38.081974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:36.793502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.172644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:37.578391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:15:39.828036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접속년접속월접속일접속건수
접속년1.0000.2410.0000.000
접속월0.2411.0000.0000.000
접속일0.0000.0001.0000.011
접속건수0.0000.0000.0111.000
2023-12-12T23:15:39.918629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접속년접속월접속일접속건수
접속년1.000-0.161-0.015-0.800
접속월-0.1611.000-0.015-0.085
접속일-0.015-0.0151.0000.009
접속건수-0.800-0.0850.0091.000

Missing values

2023-12-12T23:15:38.247300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:15:38.339460image/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

접속년접속월접속일접속건수
3439201611272
42842018142
992820193222
1268620207201
8524201812292
698520171142
286420169242
822520199241
557820178122
225120163734
접속년접속월접속일접속건수
705620184272
101162020281
1209720207151
973220199271
404120182252
63682017822
1956201610222
99042019322
2693201611222
42852018142

Duplicate rows

Most frequently occurring

접속년접속월접속일접속건수# duplicates
862016629212
88201671212
94201677212
1292016811212
4201648211
802016623211
1302016812211
1602202093111
1603202094111
142016418210