Overview

Dataset statistics

Number of variables7
Number of observations116
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory63.1 B

Variable types

Categorical1
Text1
Numeric5

Dataset

Description부산교통공사_CCTV카메라설치현황_20221231
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3046976

Alerts

승강장 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 승강장High correlation
역무자동설비 has 3 (2.6%) zerosZeros
편의설비 has 2 (1.7%) zerosZeros
기타 has 89 (76.7%) zerosZeros

Reproduction

Analysis started2023-12-10 17:36:36.447010
Analysis finished2023-12-10 17:36:44.175147
Duration7.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2
43 
1
40 
3
18 
4
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 43
37.1%
1 40
34.5%
3 18
15.5%
4 15
 
12.9%

Length

2023-12-11T02:36:44.358869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:36:44.634326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 43
37.1%
1 40
34.5%
3 18
15.5%
4 15
 
12.9%

역사
Text

Distinct110
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T02:36:45.250387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.5517241
Min length2

Characters and Unicode

Total characters296
Distinct characters132
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)89.7%

Sample

1st row다대포해수욕장
2nd row다대포항
3rd row낫개
4th row신장림
5th row장림
ValueCountFrequency (%)
연산 2
 
1.7%
수영 2
 
1.7%
동래 2
 
1.7%
덕천 2
 
1.7%
서면 2
 
1.7%
미남 2
 
1.7%
호포 1
 
0.9%
화명 1
 
0.9%
율리 1
 
0.9%
동원 1
 
0.9%
Other values (100) 100
86.2%
2023-12-11T02:36:46.195655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 19
 
6.4%
대 18
 
6.1%
동 11
 
3.7%
부 9
 
3.0%
장 9
 
3.0%
남 8
 
2.7%
포 7
 
2.4%
사 6
 
2.0%
서 6
 
2.0%
구 5
 
1.7%
Other values (122) 198
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
99.7%
Uppercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 19
 
6.4%
대 18
 
6.1%
동 11
 
3.7%
부 9
 
3.1%
장 9
 
3.1%
남 8
 
2.7%
포 7
 
2.4%
사 6
 
2.0%
서 6
 
2.0%
구 5
 
1.7%
Other values (121) 197
66.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
99.7%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 19
 
6.4%
대 18
 
6.1%
동 11
 
3.7%
부 9
 
3.1%
장 9
 
3.1%
남 8
 
2.7%
포 7
 
2.4%
사 6
 
2.0%
서 6
 
2.0%
구 5
 
1.7%
Other values (121) 197
66.8%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 19
 
6.4%
대 18
 
6.1%
동 11
 
3.7%
부 9
 
3.1%
장 9
 
3.1%
남 8
 
2.7%
포 7
 
2.4%
사 6
 
2.0%
서 6
 
2.0%
구 5
 
1.7%
Other values (121) 197
66.8%
ASCII
ValueCountFrequency (%)
C 1
100.0%

승강장
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0517241
Minimum0
Maximum18
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:36:46.458269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q16
median8
Q310
95-th percentile18
Maximum18
Range18
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.7851996
Coefficient of variation (CV)0.41817443
Kurtosis0.44227958
Mean9.0517241
Median Absolute Deviation (MAD)2
Skewness0.74042811
Sum1050
Variance14.327736
MonotonicityNot monotonic
2023-12-11T02:36:46.715904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
10 31
26.7%
8 31
26.7%
6 17
14.7%
4 14
12.1%
14 9
 
7.8%
18 8
 
6.9%
15 2
 
1.7%
11 1
 
0.9%
16 1
 
0.9%
7 1
 
0.9%
ValueCountFrequency (%)
0 1
 
0.9%
4 14
12.1%
6 17
14.7%
7 1
 
0.9%
8 31
26.7%
10 31
26.7%
11 1
 
0.9%
14 9
 
7.8%
15 2
 
1.7%
16 1
 
0.9%
ValueCountFrequency (%)
18 8
 
6.9%
16 1
 
0.9%
15 2
 
1.7%
14 9
 
7.8%
11 1
 
0.9%
10 31
26.7%
8 31
26.7%
7 1
 
0.9%
6 17
14.7%
4 14
12.1%

대합실,기능실
Real number (ℝ)

Distinct18
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8017241
Minimum2
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:36:46.972654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q17
median9
Q312
95-th percentile18
Maximum24
Range22
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.9917738
Coefficient of variation (CV)0.40725221
Kurtosis2.5234191
Mean9.8017241
Median Absolute Deviation (MAD)2
Skewness1.3003825
Sum1137
Variance15.934258
MonotonicityNot monotonic
2023-12-11T02:36:47.218354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9 24
20.7%
6 15
12.9%
8 12
10.3%
10 11
9.5%
12 10
8.6%
13 7
 
6.0%
11 7
 
6.0%
5 6
 
5.2%
7 6
 
5.2%
14 3
 
2.6%
Other values (8) 15
12.9%
ValueCountFrequency (%)
2 1
 
0.9%
4 3
 
2.6%
5 6
 
5.2%
6 15
12.9%
7 6
 
5.2%
8 12
10.3%
9 24
20.7%
10 11
9.5%
11 7
 
6.0%
12 10
8.6%
ValueCountFrequency (%)
24 2
 
1.7%
23 1
 
0.9%
19 1
 
0.9%
18 3
 
2.6%
17 1
 
0.9%
16 3
 
2.6%
14 3
 
2.6%
13 7
6.0%
12 10
8.6%
11 7
6.0%

역무자동설비
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8362069
Minimum0
Maximum11
Zeros3
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:36:47.466693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q15
median6
Q37
95-th percentile9
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1946336
Coefficient of variation (CV)0.37603767
Kurtosis0.28522051
Mean5.8362069
Median Absolute Deviation (MAD)1
Skewness-0.28990004
Sum677
Variance4.8164168
MonotonicityNot monotonic
2023-12-11T02:36:47.738509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
7 25
21.6%
5 22
19.0%
6 22
19.0%
3 14
12.1%
8 11
9.5%
9 6
 
5.2%
2 4
 
3.4%
4 4
 
3.4%
10 3
 
2.6%
0 3
 
2.6%
ValueCountFrequency (%)
0 3
 
2.6%
2 4
 
3.4%
3 14
12.1%
4 4
 
3.4%
5 22
19.0%
6 22
19.0%
7 25
21.6%
8 11
9.5%
9 6
 
5.2%
10 3
 
2.6%
ValueCountFrequency (%)
11 2
 
1.7%
10 3
 
2.6%
9 6
 
5.2%
8 11
9.5%
7 25
21.6%
6 22
19.0%
5 22
19.0%
4 4
 
3.4%
3 14
12.1%
2 4
 
3.4%

편의설비
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.689655
Minimum0
Maximum46
Zeros2
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:36:48.055316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q112
median17
Q323
95-th percentile39.25
Maximum46
Range46
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.7020068
Coefficient of variation (CV)0.51911106
Kurtosis0.70232056
Mean18.689655
Median Absolute Deviation (MAD)5
Skewness0.88148584
Sum2168
Variance94.128936
MonotonicityNot monotonic
2023-12-11T02:36:48.625300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
12 11
 
9.5%
17 9
 
7.8%
16 8
 
6.9%
18 7
 
6.0%
15 6
 
5.2%
21 5
 
4.3%
14 5
 
4.3%
22 5
 
4.3%
13 5
 
4.3%
10 4
 
3.4%
Other values (28) 51
44.0%
ValueCountFrequency (%)
0 2
 
1.7%
3 2
 
1.7%
5 1
 
0.9%
6 4
 
3.4%
7 1
 
0.9%
8 3
 
2.6%
9 1
 
0.9%
10 4
 
3.4%
11 2
 
1.7%
12 11
9.5%
ValueCountFrequency (%)
46 1
0.9%
45 1
0.9%
44 1
0.9%
43 1
0.9%
41 1
0.9%
40 1
0.9%
39 2
1.7%
37 2
1.7%
33 1
0.9%
32 1
0.9%

기타
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.465517
Minimum0
Maximum328
Zeros89
Zeros (%)76.7%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:36:48.986715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.25
Maximum328
Range328
Interquartile range (IQR)0

Descriptive statistics

Standard deviation54.701789
Coefficient of variation (CV)4.7709831
Kurtosis24.511434
Mean11.465517
Median Absolute Deviation (MAD)0
Skewness5.0565097
Sum1330
Variance2992.2858
MonotonicityNot monotonic
2023-12-11T02:36:49.268198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 89
76.7%
2 10
 
8.6%
3 4
 
3.4%
4 3
 
2.6%
1 3
 
2.6%
281 1
 
0.9%
300 1
 
0.9%
328 1
 
0.9%
5 1
 
0.9%
90 1
 
0.9%
Other values (2) 2
 
1.7%
ValueCountFrequency (%)
0 89
76.7%
1 3
 
2.6%
2 10
 
8.6%
3 4
 
3.4%
4 3
 
2.6%
5 1
 
0.9%
6 1
 
0.9%
90 1
 
0.9%
273 1
 
0.9%
281 1
 
0.9%
ValueCountFrequency (%)
328 1
 
0.9%
300 1
 
0.9%
281 1
 
0.9%
273 1
 
0.9%
90 1
 
0.9%
6 1
 
0.9%
5 1
 
0.9%
4 3
 
2.6%
3 4
 
3.4%
2 10
8.6%

Interactions

2023-12-11T02:36:42.088541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:37.044232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:38.198679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:39.408247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:40.867225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:42.327331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:37.282197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:38.537085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:39.717866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:41.125641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:42.516422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:37.505119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:38.769571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:39.957387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:41.382972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:42.741898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:37.756575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:38.990273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:40.233852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:41.623780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:43.455174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:37.955809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:39.184550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:40.630361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:36:41.876766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:36:49.489995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선승강장대합실,기능실역무자동설비편의설비기타
호선1.0000.9630.2260.6500.0000.105
승강장0.9631.0000.4430.5700.3310.711
대합실,기능실0.2260.4431.0000.4770.5620.310
역무자동설비0.6500.5700.4771.0000.4820.548
편의설비0.0000.3310.5620.4821.0000.432
기타0.1050.7110.3100.5480.4321.000
2023-12-11T02:36:49.735482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승강장대합실,기능실역무자동설비편의설비기타호선
승강장1.0000.0810.400-0.067-0.1880.927
대합실,기능실0.0811.0000.2620.4550.0370.111
역무자동설비0.4000.2621.0000.036-0.1540.438
편의설비-0.0670.4550.0361.000-0.0600.000
기타-0.1880.037-0.154-0.0601.0000.039
호선0.9270.1110.4380.0000.0391.000

Missing values

2023-12-11T02:36:43.769827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:36:44.053636image/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

호선역사승강장대합실,기능실역무자동설비편의설비기타
01다대포해수욕장10245393
11다대포항14126432
21낫개18186372
31신장림1495320
41장림1096312
51동매10126450
61신평1013712281
71하단10165210
81당리1065170
91사하1065120
호선역사승강장대합실,기능실역무자동설비편의설비기타
1064명장493300
1074서동493300
1084금사4103242
1094반여농산물시장4106156
1104석대49270
1114영산대4113170
1124동부산대학483170
1134고촌483150
1144안평483152
1154안평기지6520273