Overview

Dataset statistics

Number of variables6
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory54.3 B

Variable types

Categorical3
Text2
Numeric1

Dataset

Description강서구시설관리공단에서 운영하고 관리하는 공영주차장 현황입니다. 주차장명, 급지, 면수, 관리주체에 대한 정보를 담고 있습니다.
Author강서구시설관리공단
URLhttps://www.data.go.kr/data/15087708/fileData.do

Alerts

급지 is highly overall correlated with 구분(노상-노외) and 1 other fieldsHigh correlation
요금(5분당) is highly overall correlated with 구분(노상-노외) and 1 other fieldsHigh correlation
구분(노상-노외) is highly overall correlated with 급지 and 1 other fieldsHigh correlation
주차장명 has unique valuesUnique
주소 has unique valuesUnique
면수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:29:05.839780
Analysis finished2023-12-12 23:29:06.435075
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분(노상-노외)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
노외
17 
노상
8 
부설
3 
임시
3 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노외 17
54.8%
노상 8
25.8%
부설 3
 
9.7%
임시 3
 
9.7%

Length

2023-12-13T08:29:06.499148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:29:06.602781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노외 17
54.8%
노상 8
25.8%
부설 3
 
9.7%
임시 3
 
9.7%

주차장명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T08:29:06.799377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length4.9032258
Min length2

Characters and Unicode

Total characters152
Distinct characters58
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row달구지길
2nd row배다리동길
3rd row배다리서길
4th row신학대길
5th row방죽길
ValueCountFrequency (%)
달구지길 1
 
3.0%
화곡5-2 1
 
3.0%
마곡7구역 1
 
3.0%
공항2구역 1
 
3.0%
등서초 1
 
3.0%
화곡4-1 1
 
3.0%
복지센터 1
 
3.0%
곰달래 1
 
3.0%
제2주차장 1
 
3.0%
서울식물원 1
 
3.0%
Other values (23) 23
69.7%
2023-12-13T08:29:07.123351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
곡 16
 
10.5%
- 15
 
9.9%
화 14
 
9.2%
1 12
 
7.9%
길 8
 
5.3%
2 8
 
5.3%
구 5
 
3.3%
5 3
 
2.0%
공 3
 
2.0%
원 3
 
2.0%
Other values (48) 65
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103
67.8%
Decimal Number 32
 
21.1%
Dash Punctuation 15
 
9.9%
Space Separator 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
곡 16
 
15.5%
화 14
 
13.6%
길 8
 
7.8%
구 5
 
4.9%
공 3
 
2.9%
원 3
 
2.9%
서 3
 
2.9%
역 3
 
2.9%
등 2
 
1.9%
달 2
 
1.9%
Other values (38) 44
42.7%
Decimal Number
ValueCountFrequency (%)
1 12
37.5%
2 8
25.0%
5 3
 
9.4%
8 3
 
9.4%
3 2
 
6.2%
7 2
 
6.2%
4 1
 
3.1%
6 1
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 103
67.8%
Common 49
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
곡 16
 
15.5%
화 14
 
13.6%
길 8
 
7.8%
구 5
 
4.9%
공 3
 
2.9%
원 3
 
2.9%
서 3
 
2.9%
역 3
 
2.9%
등 2
 
1.9%
달 2
 
1.9%
Other values (38) 44
42.7%
Common
ValueCountFrequency (%)
- 15
30.6%
1 12
24.5%
2 8
16.3%
5 3
 
6.1%
8 3
 
6.1%
3 2
 
4.1%
7 2
 
4.1%
2
 
4.1%
4 1
 
2.0%
6 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 103
67.8%
ASCII 49
32.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
곡 16
 
15.5%
화 14
 
13.6%
길 8
 
7.8%
구 5
 
4.9%
공 3
 
2.9%
원 3
 
2.9%
서 3
 
2.9%
역 3
 
2.9%
등 2
 
1.9%
달 2
 
1.9%
Other values (38) 44
42.7%
ASCII
ValueCountFrequency (%)
- 15
30.6%
1 12
24.5%
2 8
16.3%
5 3
 
6.1%
8 3
 
6.1%
3 2
 
4.1%
7 2
 
4.1%
2
 
4.1%
4 1
 
2.0%
6 1
 
2.0%

급지
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
5
16 
2
7 
4
7 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
5 16
51.6%
2 7
22.6%
4 7
22.6%
3 1
 
3.2%

Length

2023-12-13T08:29:07.274046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:29:07.410536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 16
51.6%
2 7
22.6%
4 7
22.6%
3 1
 
3.2%

주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T08:29:07.675190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length17.322581
Min length9

Characters and Unicode

Total characters537
Distinct characters86
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row화곡1동 대림아파트 옆
2nd row화곡2,4,8동 복개도로(국회대로7길)
3rd row화곡1동 복개도로(강서로5나길)
4th row화곡6동 강서구청 후문
5th row화곡6동 뉴리젠트호텔 후면
ValueCountFrequency (%)
입체식 9
 
8.0%
초록마을로 4
 
3.6%
강서로 4
 
3.6%
3단 4
 
3.6%
2층 4
 
3.6%
마곡동 3
 
2.7%
평면식 3
 
2.7%
후면 3
 
2.7%
4단 3
 
2.7%
화곡로 2
 
1.8%
Other values (64) 73
65.2%
2023-12-13T08:29:08.156031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
15.1%
로 27
 
5.0%
1 25
 
4.7%
2 25
 
4.7%
길 20
 
3.7%
3 19
 
3.5%
) 18
 
3.4%
( 18
 
3.4%
층 15
 
2.8%
5 14
 
2.6%
Other values (76) 275
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
51.2%
Decimal Number 132
24.6%
Space Separator 81
 
15.1%
Close Punctuation 18
 
3.4%
Open Punctuation 18
 
3.4%
Dash Punctuation 7
 
1.3%
Math Symbol 4
 
0.7%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 27
 
9.8%
길 20
 
7.3%
층 15
 
5.5%
식 12
 
4.4%
동 12
 
4.4%
곡 12
 
4.4%
화 10
 
3.6%
체 9
 
3.3%
입 9
 
3.3%
단 9
 
3.3%
Other values (60) 140
50.9%
Decimal Number
ValueCountFrequency (%)
1 25
18.9%
2 25
18.9%
3 19
14.4%
5 14
10.6%
8 14
10.6%
4 13
9.8%
6 10
 
7.6%
7 5
 
3.8%
0 5
 
3.8%
9 2
 
1.5%
Space Separator
ValueCountFrequency (%)
81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
51.2%
Common 262
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 27
 
9.8%
길 20
 
7.3%
층 15
 
5.5%
식 12
 
4.4%
동 12
 
4.4%
곡 12
 
4.4%
화 10
 
3.6%
체 9
 
3.3%
입 9
 
3.3%
단 9
 
3.3%
Other values (60) 140
50.9%
Common
ValueCountFrequency (%)
81
30.9%
1 25
 
9.5%
2 25
 
9.5%
3 19
 
7.3%
) 18
 
6.9%
( 18
 
6.9%
5 14
 
5.3%
8 14
 
5.3%
4 13
 
5.0%
6 10
 
3.8%
Other values (6) 25
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
51.2%
ASCII 262
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
30.9%
1 25
 
9.5%
2 25
 
9.5%
3 19
 
7.3%
) 18
 
6.9%
( 18
 
6.9%
5 14
 
5.3%
8 14
 
5.3%
4 13
 
5.0%
6 10
 
3.8%
Other values (6) 25
 
9.5%
Hangul
ValueCountFrequency (%)
로 27
 
9.8%
길 20
 
7.3%
층 15
 
5.5%
식 12
 
4.4%
동 12
 
4.4%
곡 12
 
4.4%
화 10
 
3.6%
체 9
 
3.3%
입 9
 
3.3%
단 9
 
3.3%
Other values (60) 140
50.9%

면수
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.32258
Minimum9
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T08:29:08.337714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile20.5
Q149.5
median90
Q3201
95-th percentile357.5
Maximum500
Range491
Interquartile range (IQR)151.5

Descriptive statistics

Standard deviation121.19059
Coefficient of variation (CV)0.92284655
Kurtosis1.8227658
Mean131.32258
Median Absolute Deviation (MAD)48
Skewness1.4834771
Sum4071
Variance14687.159
MonotonicityNot monotonic
2023-12-13T08:29:08.480887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
29 1
 
3.2%
315 1
 
3.2%
200 1
 
3.2%
400 1
 
3.2%
75 1
 
3.2%
32 1
 
3.2%
138 1
 
3.2%
248 1
 
3.2%
202 1
 
3.2%
90 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
9 1
3.2%
16 1
3.2%
25 1
3.2%
27 1
3.2%
29 1
3.2%
32 1
3.2%
48 1
3.2%
49 1
3.2%
50 1
3.2%
53 1
3.2%
ValueCountFrequency (%)
500 1
3.2%
400 1
3.2%
315 1
3.2%
298 1
3.2%
254 1
3.2%
248 1
3.2%
231 1
3.2%
202 1
3.2%
200 1
3.2%
138 1
3.2%

요금(5분당)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
50원
15 
100원
8 
250원
5 
200원
2 
150원
 
1

Length

Max length4
Median length4
Mean length3.516129
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row250원
2nd row200원
3rd row200원
4th row250원
5th row250원

Common Values

ValueCountFrequency (%)
50원 15
48.4%
100원 8
25.8%
250원 5
 
16.1%
200원 2
 
6.5%
150원 1
 
3.2%

Length

2023-12-13T08:29:08.644778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:29:08.768475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50원 15
48.4%
100원 8
25.8%
250원 5
 
16.1%
200원 2
 
6.5%
150원 1
 
3.2%

Interactions

2023-12-13T08:29:06.151037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:29:08.867263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(노상-노외)주차장명급지주소면수요금(5분당)
구분(노상-노외)1.0001.0000.9191.0000.3500.660
주차장명1.0001.0001.0001.0001.0001.000
급지0.9191.0001.0001.0000.4560.943
주소1.0001.0001.0001.0001.0001.000
면수0.3501.0000.4561.0001.0000.643
요금(5분당)0.6601.0000.9431.0000.6431.000
2023-12-13T08:29:08.979861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급지요금(5분당)구분(노상-노외)
급지1.0000.9470.622
요금(5분당)0.9471.0000.578
구분(노상-노외)0.6220.5781.000
2023-12-13T08:29:09.074262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면수구분(노상-노외)급지요금(5분당)
면수1.0000.1850.2630.396
구분(노상-노외)0.1851.0000.6220.578
급지0.2630.6221.0000.947
요금(5분당)0.3960.5780.9471.000

Missing values

2023-12-13T08:29:06.286443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:29:06.395266image/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

구분(노상-노외)주차장명급지주소면수요금(5분당)
0노상달구지길2화곡1동 대림아파트 옆29250원
1노상배다리동길2화곡2,4,8동 복개도로(국회대로7길)315200원
2노상배다리서길2화곡1동 복개도로(강서로5나길)254200원
3노상신학대길2화곡6동 강서구청 후문48250원
4노상방죽길2화곡6동 뉴리젠트호텔 후면50250원
5노상구암길2등촌3동 그랜드종합상가 후면49250원
6노상꿈나무길2등촌3동 미주진로아파트 후면62250원
7노상황금내공원길4가양3동 1485(황금내공원길)71100원
8노외가로공원4가로공원로 지하189 (지하1층~지하2층)500100원
9노외볏골5까치산로 4길 22 (지하1층~지하2층)231100원
구분(노상-노외)주차장명급지주소면수요금(5분당)
21노외화곡8-15초록마을로 22길 57-11 (2층 3단 입체식)5350원
22노외화곡8-25초록마을로 126 (2층 3단 입체식)11050원
23노외등촌2-15등촌로 55길 33-16 (1층 2단 입체식)9050원
24노외서울식물원 제2주차장4마곡동 811-5202100원
25부설곰달래 복지센터4강서로 5길 50248100원
26부설화곡4-15곰달래 57가길2013850원
27부설등서초5강서구 화곡로 58길 863250원
28임시공항2구역3방화대로 8길 375150원
29임시마곡7구역4마곡동 308-4400100원
30임시마곡8구역4마곡동 802-3200100원