Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description부산광역시 연제구 관내 설치된 CCTV의 심볼정보(레이어명, 심볼명, 위도, 경도)에 대한 자료입니다.(2023. 9. 1.기준)
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15039757/fileData.do

Alerts

경도 is highly skewed (γ1 = -70.12338466)Skewed
위도 is highly skewed (γ1 = -70.60162023)Skewed
심볼 명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:57:21.799321
Analysis finished2023-12-11 22:57:22.677735
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

레이어 명칭
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
새주소
4949 
지번
4589 
건물
 
462

Length

Max length3
Median length2
Mean length2.4949
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row새주소
2nd row지번
3rd row새주소
4th row새주소
5th row지번

Common Values

ValueCountFrequency (%)
새주소 4949
49.5%
지번 4589
45.9%
건물 462
 
4.6%

Length

2023-12-12T07:57:22.736477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:57:22.821138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
새주소 4949
49.5%
지번 4589
45.9%
건물 462
 
4.6%

심볼 명칭
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T07:57:23.095971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length20.1372
Min length2

Characters and Unicode

Total characters201372
Distinct characters381
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row부산광역시 연제구 대리로19번길 11
2nd row부산광역시 연제구 연산동 22-105
3rd row부산광역시 연제구 중앙천로4번길 16-1
4th row부산광역시 연제구 월드컵대로99번길 33-1
5th row부산광역시 연제구 거제동 766-76
ValueCountFrequency (%)
연제구 9541
24.3%
부산광역시 9539
24.3%
연산동 3431
 
8.7%
거제동 1164
 
3.0%
과정로 114
 
0.3%
거제천로 100
 
0.3%
10 82
 
0.2%
9 80
 
0.2%
쌍미천로 77
 
0.2%
11 76
 
0.2%
Other values (6967) 15061
38.4%
2023-12-12T07:57:23.593447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29265
 
14.5%
연 13624
 
6.8%
산 13347
 
6.6%
제 11301
 
5.6%
1 10137
 
5.0%
시 9761
 
4.8%
부 9599
 
4.8%
광 9570
 
4.8%
역 9554
 
4.7%
구 9552
 
4.7%
Other values (371) 75662
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121179
60.2%
Decimal Number 44455
 
22.1%
Space Separator 29265
 
14.5%
Dash Punctuation 6418
 
3.2%
Uppercase Letter 44
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 13624
11.2%
산 13347
11.0%
제 11301
9.3%
시 9761
 
8.1%
부 9599
 
7.9%
광 9570
 
7.9%
역 9554
 
7.9%
구 9552
 
7.9%
로 4983
 
4.1%
동 4808
 
4.0%
Other values (337) 25080
20.7%
Uppercase Letter
ValueCountFrequency (%)
B 10
22.7%
A 6
13.6%
K 5
11.4%
S 4
 
9.1%
I 3
 
6.8%
M 2
 
4.5%
H 2
 
4.5%
G 2
 
4.5%
T 2
 
4.5%
C 1
 
2.3%
Other values (7) 7
15.9%
Decimal Number
ValueCountFrequency (%)
1 10137
22.8%
2 6294
14.2%
3 4833
10.9%
4 4162
9.4%
6 3632
 
8.2%
5 3592
 
8.1%
7 3307
 
7.4%
8 3119
 
7.0%
0 2768
 
6.2%
9 2611
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
29265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6418
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121179
60.2%
Common 80146
39.8%
Latin 47
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 13624
11.2%
산 13347
11.0%
제 11301
9.3%
시 9761
 
8.1%
부 9599
 
7.9%
광 9570
 
7.9%
역 9554
 
7.9%
구 9552
 
7.9%
로 4983
 
4.1%
동 4808
 
4.0%
Other values (337) 25080
20.7%
Latin
ValueCountFrequency (%)
B 10
21.3%
A 6
12.8%
K 5
10.6%
S 4
 
8.5%
e 3
 
6.4%
I 3
 
6.4%
M 2
 
4.3%
H 2
 
4.3%
G 2
 
4.3%
T 2
 
4.3%
Other values (8) 8
17.0%
Common
ValueCountFrequency (%)
29265
36.5%
1 10137
 
12.6%
- 6418
 
8.0%
2 6294
 
7.9%
3 4833
 
6.0%
4 4162
 
5.2%
6 3632
 
4.5%
5 3592
 
4.5%
7 3307
 
4.1%
8 3119
 
3.9%
Other values (6) 5387
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121179
60.2%
ASCII 80193
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29265
36.5%
1 10137
 
12.6%
- 6418
 
8.0%
2 6294
 
7.8%
3 4833
 
6.0%
4 4162
 
5.2%
6 3632
 
4.5%
5 3592
 
4.5%
7 3307
 
4.1%
8 3119
 
3.9%
Other values (24) 5434
 
6.8%
Hangul
ValueCountFrequency (%)
연 13624
11.2%
산 13347
11.0%
제 11301
9.3%
시 9761
 
8.1%
부 9599
 
7.9%
광 9570
 
7.9%
역 9554
 
7.9%
구 9552
 
7.9%
로 4983
 
4.1%
동 4808
 
4.0%
Other values (337) 25080
20.7%

경도
Real number (ℝ)

SKEWED 

Distinct7563
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08347
Minimum117.9926
Maximum129.11399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:57:23.752868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum117.9926
5-th percentile129.06677
Q1129.07731
median129.08631
Q3129.09389
95-th percentile129.10756
Maximum129.11399
Range11.121382
Interquartile range (IQR)0.01657525

Descriptive statistics

Standard deviation0.15730067
Coefficient of variation (CV)0.0012185965
Kurtosis4943.2161
Mean129.08347
Median Absolute Deviation (MAD)0.0082305
Skewness-70.123385
Sum1290834.7
Variance0.0247435
MonotonicityNot monotonic
2023-12-12T07:57:23.886928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.077154 6
 
0.1%
129.0866 5
 
0.1%
129.08765 5
 
0.1%
129.106968 5
 
0.1%
129.087782 5
 
0.1%
129.095906 5
 
0.1%
129.071481 5
 
0.1%
129.086857 5
 
0.1%
129.0871 5
 
0.1%
129.089219 5
 
0.1%
Other values (7553) 9949
99.5%
ValueCountFrequency (%)
117.992603 2
< 0.1%
129.050077 1
< 0.1%
129.05256 2
< 0.1%
129.053139 1
< 0.1%
129.053432 1
< 0.1%
129.053912 1
< 0.1%
129.054129 1
< 0.1%
129.054633 1
< 0.1%
129.054869 1
< 0.1%
129.059182 2
< 0.1%
ValueCountFrequency (%)
129.113985 1
< 0.1%
129.113934 1
< 0.1%
129.1139 1
< 0.1%
129.113843 1
< 0.1%
129.113794 2
< 0.1%
129.113742 1
< 0.1%
129.113575 2
< 0.1%
129.113428 1
< 0.1%
129.113039 1
< 0.1%
129.112906 1
< 0.1%

위도
Real number (ℝ)

SKEWED 

Distinct7072
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.179352
Minimum19.694477
Maximum35.199215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:57:24.027943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19.694477
5-th percentile35.171346
Q135.177252
median35.183026
Q335.187364
95-th percentile35.192476
Maximum35.199215
Range15.504738
Interquartile range (IQR)0.010112

Descriptive statistics

Standard deviation0.21912378
Coefficient of variation (CV)0.0062287611
Kurtosis4988.2205
Mean35.179352
Median Absolute Deviation (MAD)0.004963
Skewness-70.60162
Sum351793.52
Variance0.048015231
MonotonicityNot monotonic
2023-12-12T07:57:24.147760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17575 6
 
0.1%
35.179605 6
 
0.1%
35.189181 6
 
0.1%
35.186054 6
 
0.1%
35.184069 5
 
0.1%
35.181242 5
 
0.1%
35.187137 5
 
0.1%
35.181812 5
 
0.1%
35.174047 5
 
0.1%
35.188725 5
 
0.1%
Other values (7062) 9946
99.5%
ValueCountFrequency (%)
19.694477 2
< 0.1%
35.162364 1
< 0.1%
35.163393 1
< 0.1%
35.16355 1
< 0.1%
35.163676 1
< 0.1%
35.163924 1
< 0.1%
35.164041 1
< 0.1%
35.164101 1
< 0.1%
35.164132 1
< 0.1%
35.164166 1
< 0.1%
ValueCountFrequency (%)
35.199215 1
 
< 0.1%
35.199127 1
 
< 0.1%
35.199013 3
< 0.1%
35.198946 1
 
< 0.1%
35.19894 1
 
< 0.1%
35.198873 1
 
< 0.1%
35.198867 1
 
< 0.1%
35.198853 1
 
< 0.1%
35.19877 1
 
< 0.1%
35.19876 1
 
< 0.1%

Interactions

2023-12-12T07:57:22.387075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:57:22.222476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:57:22.467492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:57:22.301040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:57:24.236904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
레이어 명칭경도위도
레이어 명칭1.0000.0010.001
경도0.0011.0000.924
위도0.0010.9241.000
2023-12-12T07:57:24.317611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도레이어 명칭
경도1.000-0.1490.002
위도-0.1491.0000.002
레이어 명칭0.0020.0021.000

Missing values

2023-12-12T07:57:22.572385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:57:22.643665image/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

레이어 명칭심볼 명칭경도위도
7856새주소부산광역시 연제구 대리로19번길 11129.08547935.181822
28119지번부산광역시 연제구 연산동 22-105129.10372735.180817
16928새주소부산광역시 연제구 중앙천로4번길 16-1129.08508435.175424
15516새주소부산광역시 연제구 월드컵대로99번길 33-1129.08123735.183791
21660지번부산광역시 연제구 거제동 766-76129.06477335.180036
11173새주소부산광역시 연제구 쌍미천로59번길 25-2129.0877835.177887
8803새주소부산광역시 연제구 배산북로 11129.093135.175376
11102새주소부산광역시 연제구 쌍미천로52번길 23-5129.09060635.177199
14223새주소부산광역시 연제구 월드컵대로 27129.08539335.177027
2762새주소부산광역시 연제구 거제천로 268-1129.08627735.191613
레이어 명칭심볼 명칭경도위도
20355지번부산광역시 연제구 거제동 41-63129.07359935.183812
29952지번부산광역시 연제구 연산동 398-12129.10165335.188493
34679지번부산광역시 연제구 연산동 952-15129.09034935.185257
22130지번부산광역시 연제구 거제동 840-3129.07168135.1841
27922지번부산광역시 연제구 연산동 2140-3129.09184835.176444
12251새주소부산광역시 연제구 여고로52번길 25129.07002935.194695
19926지번부산광역시 연제구 거제동 312-116129.07676535.19141
6375새주소부산광역시 연제구 과정로344번길 9129.09095135.190944
32944지번부산광역시 연제구 연산동 664-71129.08805135.17796
15036새주소부산광역시 연제구 월드컵대로32번길 45-2129.0881535.17779