Overview

Dataset statistics

Number of variables6
Number of observations5366
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory267.4 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-20944/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 07:17:06.533973
Analysis finished2024-03-13 07:17:07.305144
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
관악구
5366 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관악구 5366
100.0%

Length

2024-03-13T16:17:07.357818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:17:07.452760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관악구 5366
100.0%

안심 주소
Text

UNIQUE 

Distinct5366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2024-03-13T16:17:07.690045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length50
Mean length26.356131
Min length17

Characters and Unicode

Total characters141427
Distinct characters349
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5366 ?
Unique (%)100.0%

Sample

1st row AD037 1-1RZ 삼성동 산 83, 등산로길
2nd row JA016 2-4UC 미성동 1478-7
3rd rowA0001 1-1RZ 쑥고개어린이공원 (서림동 1564-68)
4th rowA0002 1-1RZ 쑥고개어린이공원 (서림동 1564-68)
5th rowA0003 1-1R 백설어린이공원 (낙성대동 1606-11)
ValueCountFrequency (%)
난곡동 355
 
1.5%
미성동 328
 
1.3%
신림동 289
 
1.2%
청룡동 270
 
1.1%
은천동 235
 
1.0%
1-1r 223
 
0.9%
서림동 219
 
0.9%
3-4s 219
 
0.9%
2-4s 215
 
0.9%
신사동 215
 
0.9%
Other values (4644) 21912
89.5%
2024-03-13T16:17:08.072988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19155
 
13.5%
1 11807
 
8.3%
- 10940
 
7.7%
0 10884
 
7.7%
2 6770
 
4.8%
3 6311
 
4.5%
4 6200
 
4.4%
5 6100
 
4.3%
동 5745
 
4.1%
6 4807
 
3.4%
Other values (339) 52708
37.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61362
43.4%
Other Letter 29188
20.6%
Space Separator 19155
 
13.5%
Uppercase Letter 17264
 
12.2%
Dash Punctuation 10940
 
7.7%
Open Punctuation 1467
 
1.0%
Close Punctuation 1465
 
1.0%
Other Punctuation 581
 
0.4%
Lowercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5745
 
19.7%
신 1192
 
4.1%
성 1145
 
3.9%
원 1110
 
3.8%
림 939
 
3.2%
공 817
 
2.8%
와 702
 
2.4%
난 661
 
2.3%
영 559
 
1.9%
곡 552
 
1.9%
Other values (287) 15766
54.0%
Uppercase Letter
ValueCountFrequency (%)
S 3358
19.5%
D 3004
17.4%
C 1393
8.1%
R 1357
7.9%
Z 1198
 
6.9%
A 1104
 
6.4%
L 898
 
5.2%
F 826
 
4.8%
P 793
 
4.6%
G 523
 
3.0%
Other values (16) 2810
16.3%
Decimal Number
ValueCountFrequency (%)
1 11807
19.2%
0 10884
17.7%
2 6770
11.0%
3 6311
10.3%
4 6200
10.1%
5 6100
9.9%
6 4807
7.8%
7 3112
 
5.1%
8 2743
 
4.5%
9 2628
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 519
89.3%
# 43
 
7.4%
/ 12
 
2.1%
. 3
 
0.5%
& 3
 
0.5%
? 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1423
97.0%
[ 43
 
2.9%
{ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1422
97.1%
] 43
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
e 2
50.0%
Space Separator
ValueCountFrequency (%)
19155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10940
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 94971
67.2%
Hangul 29188
 
20.6%
Latin 17268
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5745
 
19.7%
신 1192
 
4.1%
성 1145
 
3.9%
원 1110
 
3.8%
림 939
 
3.2%
공 817
 
2.8%
와 702
 
2.4%
난 661
 
2.3%
영 559
 
1.9%
곡 552
 
1.9%
Other values (287) 15766
54.0%
Latin
ValueCountFrequency (%)
S 3358
19.4%
D 3004
17.4%
C 1393
8.1%
R 1357
7.9%
Z 1198
 
6.9%
A 1104
 
6.4%
L 898
 
5.2%
F 826
 
4.8%
P 793
 
4.6%
G 523
 
3.0%
Other values (18) 2814
16.3%
Common
ValueCountFrequency (%)
19155
20.2%
1 11807
12.4%
- 10940
11.5%
0 10884
11.5%
2 6770
 
7.1%
3 6311
 
6.6%
4 6200
 
6.5%
5 6100
 
6.4%
6 4807
 
5.1%
7 3112
 
3.3%
Other values (14) 8885
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112239
79.4%
Hangul 29188
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19155
17.1%
1 11807
10.5%
- 10940
9.7%
0 10884
9.7%
2 6770
 
6.0%
3 6311
 
5.6%
4 6200
 
5.5%
5 6100
 
5.4%
6 4807
 
4.3%
S 3358
 
3.0%
Other values (42) 25907
23.1%
Hangul
ValueCountFrequency (%)
동 5745
 
19.7%
신 1192
 
4.1%
성 1145
 
3.9%
원 1110
 
3.8%
림 939
 
3.2%
공 817
 
2.8%
와 702
 
2.4%
난 661
 
2.3%
영 559
 
1.9%
곡 552
 
1.9%
Other values (287) 15766
54.0%

위도
Real number (ℝ)

Distinct357
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.478549
Minimum37.4424
Maximum37.4937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2024-03-13T16:17:08.192180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.4424
5-th percentile37.4653
Q137.4729
median37.47895
Q337.4847
95-th percentile37.4899
Maximum37.4937
Range0.0513
Interquartile range (IQR)0.0118

Descriptive statistics

Standard deviation0.0077250254
Coefficient of variation (CV)0.00020611858
Kurtosis-0.54039635
Mean37.478549
Median Absolute Deviation (MAD)0.00585
Skewness-0.29740334
Sum201109.9
Variance5.9676017 × 10-5
MonotonicityNot monotonic
2024-03-13T16:17:08.622900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4701 56
 
1.0%
37.4761 55
 
1.0%
37.4845 49
 
0.9%
37.4722 44
 
0.8%
37.481 43
 
0.8%
37.4886 42
 
0.8%
37.4798 40
 
0.7%
37.4875 39
 
0.7%
37.4723 39
 
0.7%
37.4873 38
 
0.7%
Other values (347) 4921
91.7%
ValueCountFrequency (%)
37.4424 1
< 0.1%
37.4503 1
< 0.1%
37.4524 1
< 0.1%
37.4547 1
< 0.1%
37.4556 1
< 0.1%
37.4564 1
< 0.1%
37.4565 1
< 0.1%
37.4567 1
< 0.1%
37.4568 1
< 0.1%
37.457 1
< 0.1%
ValueCountFrequency (%)
37.4937 1
 
< 0.1%
37.4935 3
0.1%
37.4934 2
 
< 0.1%
37.4931 2
 
< 0.1%
37.493 5
0.1%
37.4929 3
0.1%
37.4928 1
 
< 0.1%
37.4927 7
0.1%
37.4926 4
0.1%
37.4925 3
0.1%

경도
Real number (ℝ)

Distinct754
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93642
Minimum126.9002
Maximum126.9824
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2024-03-13T16:17:08.741862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9002
5-th percentile126.9121
Q1126.9228
median126.9338
Q3126.9486
95-th percentile126.9688
Maximum126.9824
Range0.0822
Interquartile range (IQR)0.0258

Descriptive statistics

Standard deviation0.017672164
Coefficient of variation (CV)0.0001392206
Kurtosis-0.46668115
Mean126.93642
Median Absolute Deviation (MAD)0.0121
Skewness0.47329973
Sum681140.82
Variance0.0003123054
MonotonicityNot monotonic
2024-03-13T16:17:08.872815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9294 34
 
0.6%
126.9233 31
 
0.6%
126.9234 30
 
0.6%
126.9236 27
 
0.5%
126.9292 27
 
0.5%
126.9293 27
 
0.5%
126.9237 27
 
0.5%
126.9343 26
 
0.5%
126.9235 26
 
0.5%
126.9224 26
 
0.5%
Other values (744) 5085
94.8%
ValueCountFrequency (%)
126.9002 2
< 0.1%
126.9003 1
 
< 0.1%
126.9006 1
 
< 0.1%
126.9013 2
< 0.1%
126.9014 2
< 0.1%
126.9015 3
0.1%
126.9016 1
 
< 0.1%
126.9019 1
 
< 0.1%
126.902 2
< 0.1%
126.9021 3
0.1%
ValueCountFrequency (%)
126.9824 1
 
< 0.1%
126.9822 1
 
< 0.1%
126.9821 1
 
< 0.1%
126.9819 1
 
< 0.1%
126.9818 4
0.1%
126.9816 2
< 0.1%
126.9815 2
< 0.1%
126.9814 4
0.1%
126.9813 2
< 0.1%
126.9812 1
 
< 0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
1
5366 

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 5366
100.0%

Length

2024-03-13T16:17:08.977616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:17:09.049691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5366
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2022-12-01
5366 

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 5366
100.0%

Length

2024-03-13T16:17:09.126823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:17:09.201500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 5366
100.0%

Interactions

2024-03-13T16:17:06.982000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:17:06.828044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:17:07.062493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:17:06.907143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T16:17:09.245349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.568
경도0.5681.000
2024-03-13T16:17:09.315367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.019
경도0.0191.000

Missing values

2024-03-13T16:17:07.166658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T16:17:07.266519image/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
0관악구AD037 1-1RZ 삼성동 산 83, 등산로길37.4612126.929412022-12-01
1관악구JA016 2-4UC 미성동 1478-737.4781126.914312022-12-01
2관악구A0001 1-1RZ 쑥고개어린이공원 (서림동 1564-68)37.4759126.940712022-12-01
3관악구A0002 1-1RZ 쑥고개어린이공원 (서림동 1564-68)37.476126.94112022-12-01
4관악구A0003 1-1R 백설어린이공원 (낙성대동 1606-11)37.4759126.953612022-12-01
5관악구A0004 1-1R 백설어린이공원 (낙성대동 1606-11)37.4761126.953812022-12-01
6관악구A0005 1-1R 신화어린이공원 (서림동 408-10)37.4769126.935712022-12-01
7관악구A0006 1-1R 봉림어린이공원 (서원동 1510-2)37.4827126.935612022-12-01
8관악구A0007 1-1R 약수어린이공원 (낙성대동 1510-19)37.474126.962212022-12-01
9관악구A0008 1-1RZ 해태어린이공원 (서림동 103-141)37.4725126.940512022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
5356관악구[철거] DG024 1-2S 난곡동 646-19137.4689126.92412022-12-01
5357관악구[철거] DG024 2-2S 난곡동 646-19137.4689126.92412022-12-01
5358관악구[철거] DG025 1-2S 난곡동 646-16937.4688126.924212022-12-01
5359관악구[철거] DG025 2-2S 난곡동 646-16937.4688126.924212022-12-01
5360관악구[철거] P1028 1-4R 중앙동 41-271와 41-28437.4853126.953712022-12-01
5361관악구[철거] P1028 2-4S 중앙동 41-271와 41-28437.4853126.953712022-12-01
5362관악구[철거] P1028 3-4S 중앙동 41-271와 41-28437.4852126.953612022-12-01
5363관악구[철거] P1028 4-4S 중앙동 41-271와 41-28437.4853126.953812022-12-01
5364관악구[철거]CB012 1-5RZ 낙성대동 1624-2037.4765126.957812022-12-01
5365관악구[철거]CB012 3-5SCZ 낙성대동 1624-2037.4765126.957612022-12-01