Overview

Dataset statistics

Number of variables6
Number of observations3471
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory173.0 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-20930/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
CCTV 수량 has constant value ""Constant
수정 일시 has constant value ""Constant
안심 주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 07:13:20.467572
Analysis finished2024-03-13 07:13:21.248964
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
중랑구
3471 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중랑구 3471
100.0%

Length

2024-03-13T16:13:21.305172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:13:21.387169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중랑구 3471
100.0%

안심 주소
Text

UNIQUE 

Distinct3471
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
2024-03-13T16:13:21.604209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length60
Mean length30.645635
Min length7

Characters and Unicode

Total characters106371
Distinct characters525
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3471 ?
Unique (%)100.0%

Sample

1st row중화2동 325-103 (공원 입구)_C-JH02-0035
2nd row중화2동 325-103(고정1)_C-JH02-0035-A
3rd row중화2동 325-103(고정2)_C-JH02-0035-B
4th row중화2동 325-103(고정3)_C-JH02-0035-C
5th row중화2동 325-59 (고정)_C-JH02-0055-A
ValueCountFrequency (%)
면목본동 359
 
3.9%
망우본동 292
 
3.1%
면목3.8동 263
 
2.8%
중화2동 234
 
2.5%
묵1동 234
 
2.5%
면목2동 232
 
2.5%
면목7동 223
 
2.4%
망우3동 206
 
2.2%
상봉1동 201
 
2.2%
면목4동 185
 
2.0%
Other values (5163) 6850
73.8%
2024-03-13T16:13:21.966654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 11921
 
11.2%
0 11490
 
10.8%
1 7282
 
6.8%
5828
 
5.5%
2 5650
 
5.3%
3 4323
 
4.1%
M 3708
 
3.5%
동 3617
 
3.4%
C 3525
 
3.3%
) 3463
 
3.3%
Other values (515) 45564
42.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41339
38.9%
Other Letter 24503
23.0%
Uppercase Letter 11927
 
11.2%
Dash Punctuation 11921
 
11.2%
Space Separator 5828
 
5.5%
Close Punctuation 3463
 
3.3%
Open Punctuation 3461
 
3.3%
Connector Punctuation 3429
 
3.2%
Other Punctuation 349
 
0.3%
Math Symbol 138
 
0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3617
 
14.8%
정 2200
 
9.0%
고 2145
 
8.8%
목 1683
 
6.9%
면 1547
 
6.3%
본 667
 
2.7%
우 586
 
2.4%
망 547
 
2.2%
중 516
 
2.1%
화 492
 
2.0%
Other values (467) 10503
42.9%
Uppercase Letter
ValueCountFrequency (%)
M 3708
31.1%
C 3525
29.6%
B 1059
 
8.9%
A 923
 
7.7%
S 607
 
5.1%
U 502
 
4.2%
J 400
 
3.4%
K 393
 
3.3%
H 373
 
3.1%
N 267
 
2.2%
Other values (10) 170
 
1.4%
Decimal Number
ValueCountFrequency (%)
0 11490
27.8%
1 7282
17.6%
2 5650
13.7%
3 4323
 
10.5%
4 2945
 
7.1%
5 2495
 
6.0%
8 1918
 
4.6%
7 1860
 
4.5%
6 1755
 
4.2%
9 1621
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 278
79.7%
# 44
 
12.6%
@ 15
 
4.3%
? 9
 
2.6%
, 3
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
c 5
41.7%
h 4
33.3%
e 1
 
8.3%
j 1
 
8.3%
m 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
< 69
50.0%
> 69
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 11921
100.0%
Space Separator
ValueCountFrequency (%)
5828
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3463
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3461
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3429
100.0%
Other Symbol
ValueCountFrequency (%)
㉵ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69928
65.7%
Hangul 24504
 
23.0%
Latin 11939
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3617
 
14.8%
정 2200
 
9.0%
고 2145
 
8.8%
목 1683
 
6.9%
면 1547
 
6.3%
본 667
 
2.7%
우 586
 
2.4%
망 547
 
2.2%
중 516
 
2.1%
화 492
 
2.0%
Other values (468) 10504
42.9%
Latin
ValueCountFrequency (%)
M 3708
31.1%
C 3525
29.5%
B 1059
 
8.9%
A 923
 
7.7%
S 607
 
5.1%
U 502
 
4.2%
J 400
 
3.4%
K 393
 
3.3%
H 373
 
3.1%
N 267
 
2.2%
Other values (15) 182
 
1.5%
Common
ValueCountFrequency (%)
- 11921
17.0%
0 11490
16.4%
1 7282
10.4%
5828
8.3%
2 5650
8.1%
3 4323
 
6.2%
) 3463
 
5.0%
( 3461
 
4.9%
_ 3429
 
4.9%
4 2945
 
4.2%
Other values (12) 10136
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81867
77.0%
Hangul 24503
 
23.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 11921
14.6%
0 11490
14.0%
1 7282
 
8.9%
5828
 
7.1%
2 5650
 
6.9%
3 4323
 
5.3%
M 3708
 
4.5%
C 3525
 
4.3%
) 3463
 
4.2%
( 3461
 
4.2%
Other values (37) 21216
25.9%
Hangul
ValueCountFrequency (%)
동 3617
 
14.8%
정 2200
 
9.0%
고 2145
 
8.8%
목 1683
 
6.9%
면 1547
 
6.3%
본 667
 
2.7%
우 586
 
2.4%
망 547
 
2.2%
중 516
 
2.1%
화 492
 
2.0%
Other values (467) 10503
42.9%
None
ValueCountFrequency (%)
㉵ 1
100.0%

위도
Real number (ℝ)

Distinct423
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.594523
Minimum37.5709
Maximum37.6204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.6 KiB
2024-03-13T16:13:22.082127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5709
5-th percentile37.5763
Q137.5864
median37.5938
Q337.6022
95-th percentile37.6152
Maximum37.6204
Range0.0495
Interquartile range (IQR)0.0158

Descriptive statistics

Standard deviation0.01136446
Coefficient of variation (CV)0.00030229032
Kurtosis-0.63549609
Mean37.594523
Median Absolute Deviation (MAD)0.0079
Skewness0.16049575
Sum130490.59
Variance0.00012915096
MonotonicityNot monotonic
2024-03-13T16:13:22.202642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5889 40
 
1.2%
37.5877 26
 
0.7%
37.587 23
 
0.7%
37.6005 22
 
0.6%
37.5903 21
 
0.6%
37.5941 21
 
0.6%
37.5958 20
 
0.6%
37.602 20
 
0.6%
37.5915 20
 
0.6%
37.5985 20
 
0.6%
Other values (413) 3238
93.3%
ValueCountFrequency (%)
37.5709 4
 
0.1%
37.5711 3
 
0.1%
37.5712 3
 
0.1%
37.5715 5
0.1%
37.5717 6
0.2%
37.5718 11
0.3%
37.5719 3
 
0.1%
37.572 3
 
0.1%
37.5725 4
 
0.1%
37.5726 7
0.2%
ValueCountFrequency (%)
37.6204 3
 
0.1%
37.6198 3
 
0.1%
37.6193 3
 
0.1%
37.6191 3
 
0.1%
37.6186 4
 
0.1%
37.6185 3
 
0.1%
37.6183 7
0.2%
37.6182 12
0.3%
37.6181 2
 
0.1%
37.618 3
 
0.1%

경도
Real number (ℝ)

Distinct351
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.08764
Minimum127.0709
Maximum127.1146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.6 KiB
2024-03-13T16:13:22.321524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0709
5-th percentile127.0745
Q1127.0807
median127.0866
Q3127.094
95-th percentile127.10345
Maximum127.1146
Range0.0437
Interquartile range (IQR)0.0133

Descriptive statistics

Standard deviation0.0091396345
Coefficient of variation (CV)7.1915997 × 10-5
Kurtosis-0.50915184
Mean127.08764
Median Absolute Deviation (MAD)0.0066
Skewness0.43454541
Sum441121.21
Variance8.353292 × 10-5
MonotonicityNot monotonic
2024-03-13T16:13:22.487155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0809 33
 
1.0%
127.0833 31
 
0.9%
127.082 28
 
0.8%
127.088 27
 
0.8%
127.0887 26
 
0.7%
127.0878 25
 
0.7%
127.0772 24
 
0.7%
127.0783 24
 
0.7%
127.0755 23
 
0.7%
127.0839 23
 
0.7%
Other values (341) 3207
92.4%
ValueCountFrequency (%)
127.0709 6
0.2%
127.071 6
0.2%
127.0714 3
 
0.1%
127.0715 2
 
0.1%
127.0718 6
0.2%
127.0721 6
0.2%
127.0722 1
 
< 0.1%
127.0726 1
 
< 0.1%
127.0727 2
 
0.1%
127.0728 11
0.3%
ValueCountFrequency (%)
127.1146 3
0.1%
127.1134 4
0.1%
127.1127 3
0.1%
127.1122 2
 
0.1%
127.112 4
0.1%
127.1116 3
0.1%
127.1115 2
 
0.1%
127.1113 3
0.1%
127.1112 3
0.1%
127.1111 5
0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
1
3471 

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 (%)
1 3471
100.0%

Length

2024-03-13T16:13:22.625640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:13:22.711342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3471
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
2022-12-01
3471 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 3471
100.0%

Length

2024-03-13T16:13:22.794309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:13:22.869781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 3471
100.0%

Interactions

2024-03-13T16:13:20.904749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:13:20.758510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:13:20.995233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:13:20.833996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T16:13:22.915866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.554
경도0.5541.000
2024-03-13T16:13:22.978885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.034
경도-0.0341.000

Missing values

2024-03-13T16:13:21.098508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T16:13:21.204762image/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

자치구안심 주소위도경도CCTV 수량수정 일시
0중랑구중화2동 325-103 (공원 입구)_C-JH02-003537.5958127.070912022-12-01
1중랑구중화2동 325-103(고정1)_C-JH02-0035-A37.5958127.070912022-12-01
2중랑구중화2동 325-103(고정2)_C-JH02-0035-B37.5958127.070912022-12-01
3중랑구중화2동 325-103(고정3)_C-JH02-0035-C37.5958127.070912022-12-01
4중랑구중화2동 325-59 (고정)_C-JH02-0055-A37.5963127.070912022-12-01
5중랑구중화2동 325-59 (삼거리 공원 전신주옆 화단안)_C-JH02-005537.5963127.070912022-12-01
6중랑구중화2동 325-64 (공원 화단)_C-JH02-003137.5968127.07112022-12-01
7중랑구중화2동 325-64(고정1)_C-JH02-0031-A37.5968127.07112022-12-01
8중랑구중화2동 325-64(고정2)_C-JH02-0031-B37.5968127.07112022-12-01
9중랑구중화2동 326-100(보조)_C-JH02-0032-237.5975127.072212022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
3461중랑구침사지-면목고 뒷편배밭37.5841127.097312022-12-01
3462중랑구침사지-묵동천37.6183127.080612022-12-01
3463중랑구침사지-사가정역4번출구37.5805127.088912022-12-01
3464중랑구침사지-신내3지구저류조37.6157127.107212022-12-01
3465중랑구펌프장 - 면목 펌프장#1 (4ch)37.5782127.0812022-12-01
3466중랑구펌프장 - 면목 펌프장#2 (4ch)37.5782127.0812022-12-01
3467중랑구펌프장 - 면목 펌프장#3 (2ch)37.5782127.0812022-12-01
3468중랑구펌프장 - 면목4 빗물펌프장(4ch)37.574127.079512022-12-01
3469중랑구하천 예경보(면목천)37.5772127.079312022-12-01
3470중랑구하천 예경보(묵동천)37.6179127.093212022-12-01