Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory44.2 B

Variable types

Categorical2
Text2
Numeric1

Dataset

Description종로구 (공/민영) 주차장내 장애인주차공간 현황입니다. 공영,민영주차장 모두 60개의 주차장이 기입되어 있습니다.
Author서울특별시 종로구
URLhttps://www.data.go.kr/data/15101209/fileData.do

Alerts

구분 is highly overall correlated with 구획면 and 1 other fieldsHigh correlation
장애인 is highly overall correlated with 구획면 and 1 other fieldsHigh correlation
구획면 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구영주차장명 has unique valuesUnique
주소 has unique valuesUnique
구획면 has 45 (75.0%) zerosZeros

Reproduction

Analysis started2023-12-12 22:53:34.093161
Analysis finished2023-12-12 22:53:34.639417
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
민영
45 
공영
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민영 45
75.0%
공영 15
 
25.0%

Length

2023-12-13T07:53:34.695561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:34.780719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민영 45
75.0%
공영 15
 
25.0%

구영주차장명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T07:53:34.979217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.95
Min length2

Characters and Unicode

Total characters237
Distinct characters99
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row효자 공영
2nd row누상 공영
3rd row세종마을신교공영
4th row삼청공영
5th row교남 공영
ValueCountFrequency (%)
공영 7
 
9.9%
gs타임즈 3
 
4.2%
창일 2
 
2.8%
지상낙원주차장 1
 
1.4%
연지 1
 
1.4%
익선 1
 
1.4%
고강 1
 
1.4%
익선동 1
 
1.4%
신원남 1
 
1.4%
황소 1
 
1.4%
Other values (52) 52
73.2%
2023-12-13T07:53:35.374344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 14
 
5.9%
공 13
 
5.5%
12
 
5.1%
원 8
 
3.4%
동 7
 
3.0%
장 6
 
2.5%
차 6
 
2.5%
주 6
 
2.5%
즈 5
 
2.1%
임 5
 
2.1%
Other values (89) 155
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
87.3%
Uppercase Letter 16
 
6.8%
Space Separator 12
 
5.1%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 14
 
6.8%
공 13
 
6.3%
원 8
 
3.9%
동 7
 
3.4%
장 6
 
2.9%
차 6
 
2.9%
주 6
 
2.9%
즈 5
 
2.4%
임 5
 
2.4%
타 5
 
2.4%
Other values (79) 132
63.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
31.2%
G 5
31.2%
J 2
 
12.5%
M 1
 
6.2%
Y 1
 
6.2%
C 1
 
6.2%
A 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
87.3%
Latin 16
 
6.8%
Common 14
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 14
 
6.8%
공 13
 
6.3%
원 8
 
3.9%
동 7
 
3.4%
장 6
 
2.9%
차 6
 
2.9%
주 6
 
2.9%
즈 5
 
2.4%
임 5
 
2.4%
타 5
 
2.4%
Other values (79) 132
63.8%
Latin
ValueCountFrequency (%)
S 5
31.2%
G 5
31.2%
J 2
 
12.5%
M 1
 
6.2%
Y 1
 
6.2%
C 1
 
6.2%
A 1
 
6.2%
Common
ValueCountFrequency (%)
12
85.7%
4 1
 
7.1%
1 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
87.3%
ASCII 30
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 14
 
6.8%
공 13
 
6.3%
원 8
 
3.9%
동 7
 
3.4%
장 6
 
2.9%
차 6
 
2.9%
주 6
 
2.9%
즈 5
 
2.4%
임 5
 
2.4%
타 5
 
2.4%
Other values (79) 132
63.8%
ASCII
ValueCountFrequency (%)
12
40.0%
S 5
16.7%
G 5
16.7%
J 2
 
6.7%
4 1
 
3.3%
M 1
 
3.3%
1 1
 
3.3%
Y 1
 
3.3%
C 1
 
3.3%
A 1
 
3.3%

주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T07:53:35.646498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length17.35
Min length9

Characters and Unicode

Total characters1041
Distinct characters89
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

Unique60 ?
Unique (%)100.0%

Sample

1st row자하문로 82(효자동68-1)
2nd row옥인동6길 39(누상동166-50)
3rd row종로구 자하문로 89(신교동66)
4th row삼청로 143-1(삼청동 1-4번지)
5th row사직로2길 13 옆(행촌동1-53)
ValueCountFrequency (%)
종로구 47
25.0%
서울특별시 45
23.9%
인사동 3
 
1.6%
자하문로 2
 
1.1%
익선동 1
 
0.5%
174-2 1
 
0.5%
171-2 1
 
0.5%
원남동 1
 
0.5%
114-2 1
 
0.5%
운니동 1
 
0.5%
Other values (85) 85
45.2%
2023-12-13T07:53:36.048706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
 
12.3%
1 67
 
6.4%
로 59
 
5.7%
동 58
 
5.6%
종 48
 
4.6%
구 47
 
4.5%
서 46
 
4.4%
특 45
 
4.3%
시 45
 
4.3%
별 45
 
4.3%
Other values (79) 453
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 604
58.0%
Decimal Number 246
23.6%
Space Separator 128
 
12.3%
Dash Punctuation 37
 
3.6%
Close Punctuation 12
 
1.2%
Open Punctuation 12
 
1.2%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 59
 
9.8%
동 58
 
9.6%
종 48
 
7.9%
구 47
 
7.8%
서 46
 
7.6%
특 45
 
7.5%
시 45
 
7.5%
별 45
 
7.5%
울 45
 
7.5%
길 14
 
2.3%
Other values (63) 152
25.2%
Decimal Number
ValueCountFrequency (%)
1 67
27.2%
2 34
13.8%
3 28
11.4%
6 26
 
10.6%
4 21
 
8.5%
0 16
 
6.5%
5 14
 
5.7%
8 14
 
5.7%
7 14
 
5.7%
9 12
 
4.9%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 604
58.0%
Common 437
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 59
 
9.8%
동 58
 
9.6%
종 48
 
7.9%
구 47
 
7.8%
서 46
 
7.6%
특 45
 
7.5%
시 45
 
7.5%
별 45
 
7.5%
울 45
 
7.5%
길 14
 
2.3%
Other values (63) 152
25.2%
Common
ValueCountFrequency (%)
128
29.3%
1 67
15.3%
- 37
 
8.5%
2 34
 
7.8%
3 28
 
6.4%
6 26
 
5.9%
4 21
 
4.8%
0 16
 
3.7%
5 14
 
3.2%
8 14
 
3.2%
Other values (6) 52
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 604
58.0%
ASCII 437
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
29.3%
1 67
15.3%
- 37
 
8.5%
2 34
 
7.8%
3 28
 
6.4%
6 26
 
5.9%
4 21
 
4.8%
0 16
 
3.7%
5 14
 
3.2%
8 14
 
3.2%
Other values (6) 52
11.9%
Hangul
ValueCountFrequency (%)
로 59
 
9.8%
동 58
 
9.6%
종 48
 
7.9%
구 47
 
7.8%
서 46
 
7.6%
특 45
 
7.5%
시 45
 
7.5%
별 45
 
7.5%
울 45
 
7.5%
길 14
 
2.3%
Other values (63) 152
25.2%

구획면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.083333
Minimum0
Maximum158
Zeros45
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T07:53:36.186254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.75
95-th percentile78.4
Maximum158
Range158
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation30.473824
Coefficient of variation (CV)2.1638218
Kurtosis8.6324529
Mean14.083333
Median Absolute Deviation (MAD)0
Skewness2.7521171
Sum845
Variance928.65395
MonotonicityNot monotonic
2023-12-13T07:53:36.291553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 45
75.0%
23 2
 
3.3%
33 1
 
1.7%
158 1
 
1.7%
27 1
 
1.7%
30 1
 
1.7%
100 1
 
1.7%
50 1
 
1.7%
78 1
 
1.7%
86 1
 
1.7%
Other values (5) 5
 
8.3%
ValueCountFrequency (%)
0 45
75.0%
23 2
 
3.3%
27 1
 
1.7%
29 1
 
1.7%
30 1
 
1.7%
33 1
 
1.7%
43 1
 
1.7%
46 1
 
1.7%
50 1
 
1.7%
53 1
 
1.7%
ValueCountFrequency (%)
158 1
1.7%
100 1
1.7%
86 1
1.7%
78 1
1.7%
66 1
1.7%
53 1
1.7%
50 1
1.7%
46 1
1.7%
43 1
1.7%
33 1
1.7%

장애인
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
45 
1
5 
2
5 
4
 
3
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row4
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 45
75.0%
1 5
 
8.3%
2 5
 
8.3%
4 3
 
5.0%
3 2
 
3.3%

Length

2023-12-13T07:53:36.418298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:36.539450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 45
75.0%
1 5
 
8.3%
2 5
 
8.3%
4 3
 
5.0%
3 2
 
3.3%

Interactions

2023-12-13T07:53:34.376095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:53:36.638114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분구영주차장명주소구획면장애인
구분1.0001.0001.0001.0001.000
구영주차장명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
구획면1.0001.0001.0001.0000.895
장애인1.0001.0001.0000.8951.000
2023-12-13T07:53:36.741208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분장애인
구분1.0000.974
장애인0.9741.000
2023-12-13T07:53:36.844121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구획면구분장애인
구획면1.0000.9470.796
구분0.9471.0000.974
장애인0.7960.9741.000

Missing values

2023-12-13T07:53:34.495525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:53:34.600495image/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

구분구영주차장명주소구획면장애인
0공영효자 공영자하문로 82(효자동68-1)231
1공영누상 공영옥인동6길 39(누상동166-50)331
2공영세종마을신교공영종로구 자하문로 89(신교동66)1584
3공영삼청공영삼청로 143-1(삼청동 1-4번지)271
4공영교남 공영사직로2길 13 옆(행촌동1-53)301
5공영동숭 공영동숭1길 11-1(동숭동 31-35)232
6공영이화 공영율곡로19길 17-3(이화동 13-2)1004
7공영명륜1가공영성균관로15길 10(명륜1가동 5-14)502
8공영명륜와룡공영명륜길 26(명륜3가 1-21)784
9공영창일 공영지봉로5길 20(창신동 82)863
구분구영주차장명주소구획면장애인
50민영황금서울특별시 종로구 대학로9길 1000
51민영강원서울특별시 종로구 창신동28700
52민영삼성서울특별시 종로구 창신동326-600
53민영화원서울특별시 종로구 창신동39900
54민영창일서울특별시 종로구 창신동401-4600
55민영창신서울특별시 종로구 창신동458-1000
56민영GS타임즈 동묘주차장서울특별시 종로구 창신동 401-8외 4필지00
57민영천일서울특별시 종로구 숭인동202-3700
58민영대성서울특별시 종로구 숭인동226-1700
59민영계명서울특별시 종로구 숭인동106300