Overview

Dataset statistics

Number of variables7
Number of observations191
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory58.7 B

Variable types

Numeric1
Categorical3
Text2
Boolean1

Dataset

Description서울특별시_서울시 전동킥보드 주차구역 현황을 제공하여 개인형 이동장치 이용자의 이용 편의를 제공하고자 합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15119757/fileData.do

Alerts

순번 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
거치대 유무 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
거치대 크기 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
설치일자 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 11:20:42.415797
Analysis finished2024-04-17 11:20:42.999121
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96
Minimum1
Maximum191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-17T20:20:43.058502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.5
Q148.5
median96
Q3143.5
95-th percentile181.5
Maximum191
Range190
Interquartile range (IQR)95

Descriptive statistics

Standard deviation55.2811
Coefficient of variation (CV)0.57584479
Kurtosis-1.2
Mean96
Median Absolute Deviation (MAD)48
Skewness0
Sum18336
Variance3056
MonotonicityStrictly increasing
2024-04-17T20:20:43.181865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
2 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
Other values (181) 181
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%

시군구명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
서초구
49 
강서구
22 
종로구
17 
동대문구
15 
마포구
10 
Other values (19)
78 

Length

Max length4
Median length3
Mean length3.0628272
Min length2

Unique

Unique4 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 49
25.7%
강서구 22
11.5%
종로구 17
 
8.9%
동대문구 15
 
7.9%
마포구 10
 
5.2%
강남구 10
 
5.2%
강북구 9
 
4.7%
송파구 7
 
3.7%
관악구 6
 
3.1%
금천구 5
 
2.6%
Other values (14) 41
21.5%

Length

2024-04-17T20:20:43.322477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서초구 49
25.7%
강서구 22
11.5%
종로구 17
 
8.9%
동대문구 15
 
7.9%
마포구 10
 
5.2%
강남구 10
 
5.2%
강북구 9
 
4.7%
송파구 7
 
3.7%
관악구 6
 
3.1%
금천구 5
 
2.6%
Other values (14) 41
21.5%

주소
Text

Distinct178
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-17T20:20:43.607789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.0837696
Min length5

Characters and Unicode

Total characters1735
Distinct characters135
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

Unique168 ?
Unique (%)88.0%

Sample

1st row팔판동 115-63
2nd row연건동 218-1
3rd row연건동 178-3
4th row동승동 1-24
5th row와룡동 75-4
ValueCountFrequency (%)
서초동 29
 
7.4%
마곡동 8
 
2.0%
반포동 7
 
1.8%
양재동 6
 
1.5%
방배동 6
 
1.5%
등촌동 6
 
1.5%
남부순환로 5
 
1.3%
전농동 5
 
1.3%
미아동 5
 
1.3%
을지로 4
 
1.0%
Other values (259) 310
79.3%
2024-04-17T20:20:43.998103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
 
11.5%
동 174
 
10.0%
1 163
 
9.4%
- 141
 
8.1%
2 91
 
5.2%
4 89
 
5.1%
7 78
 
4.5%
3 72
 
4.1%
5 67
 
3.9%
6 60
 
3.5%
Other values (125) 600
34.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 771
44.4%
Other Letter 623
35.9%
Space Separator 200
 
11.5%
Dash Punctuation 141
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 174
27.9%
서 30
 
4.8%
초 29
 
4.7%
로 22
 
3.5%
곡 13
 
2.1%
가 13
 
2.1%
구 11
 
1.8%
마 11
 
1.8%
산 10
 
1.6%
양 10
 
1.6%
Other values (113) 300
48.2%
Decimal Number
ValueCountFrequency (%)
1 163
21.1%
2 91
11.8%
4 89
11.5%
7 78
10.1%
3 72
9.3%
5 67
8.7%
6 60
 
7.8%
8 55
 
7.1%
0 54
 
7.0%
9 42
 
5.4%
Space Separator
ValueCountFrequency (%)
200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1112
64.1%
Hangul 623
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 174
27.9%
서 30
 
4.8%
초 29
 
4.7%
로 22
 
3.5%
곡 13
 
2.1%
가 13
 
2.1%
구 11
 
1.8%
마 11
 
1.8%
산 10
 
1.6%
양 10
 
1.6%
Other values (113) 300
48.2%
Common
ValueCountFrequency (%)
200
18.0%
1 163
14.7%
- 141
12.7%
2 91
8.2%
4 89
8.0%
7 78
 
7.0%
3 72
 
6.5%
5 67
 
6.0%
6 60
 
5.4%
8 55
 
4.9%
Other values (2) 96
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1112
64.1%
Hangul 623
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200
18.0%
1 163
14.7%
- 141
12.7%
2 91
8.2%
4 89
8.0%
7 78
 
7.0%
3 72
 
6.5%
5 67
 
6.0%
6 60
 
5.4%
8 55
 
4.9%
Other values (2) 96
8.6%
Hangul
ValueCountFrequency (%)
동 174
27.9%
서 30
 
4.8%
초 29
 
4.7%
로 22
 
3.5%
곡 13
 
2.1%
가 13
 
2.1%
구 11
 
1.8%
마 11
 
1.8%
산 10
 
1.6%
양 10
 
1.6%
Other values (113) 300
48.2%

상세위치
Text

Distinct189
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-17T20:20:44.223996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length13.486911
Min length6

Characters and Unicode

Total characters2576
Distinct characters294
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

Unique188 ?
Unique (%)98.4%

Sample

1st row청와대 춘추문 맞은편 인근
2nd rowKT광화문 혜화지사 앞
3rd row홍익대학교 대학로 맞은편
4th row대학로 마로니에공원 앞
5th row연악사 맞은편
ValueCountFrequency (%)
출구 90
 
13.5%
앞 71
 
10.7%
인근 21
 
3.2%
4번 20
 
3.0%
1번 15
 
2.3%
2번 14
 
2.1%
옆 10
 
1.5%
측면 10
 
1.5%
3번 9
 
1.4%
5번 9
 
1.4%
Other values (280) 397
59.6%
2024-04-17T20:20:44.564051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
478
 
18.6%
구 145
 
5.6%
출 121
 
4.7%
역 119
 
4.6%
번 118
 
4.6%
앞 86
 
3.3%
대 39
 
1.5%
1 36
 
1.4%
사 34
 
1.3%
근 32
 
1.2%
Other values (284) 1368
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1822
70.7%
Space Separator 478
 
18.6%
Decimal Number 179
 
6.9%
Open Punctuation 32
 
1.2%
Close Punctuation 32
 
1.2%
Other Punctuation 16
 
0.6%
Uppercase Letter 14
 
0.5%
Dash Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 145
 
8.0%
출 121
 
6.6%
역 119
 
6.5%
번 118
 
6.5%
앞 86
 
4.7%
대 39
 
2.1%
사 34
 
1.9%
근 32
 
1.8%
이 32
 
1.8%
스 25
 
1.4%
Other values (256) 1071
58.8%
Decimal Number
ValueCountFrequency (%)
1 36
20.1%
4 27
15.1%
2 26
14.5%
3 19
10.6%
5 19
10.6%
0 12
 
6.7%
6 11
 
6.1%
8 11
 
6.1%
7 11
 
6.1%
9 7
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
K 2
14.3%
L 2
14.3%
G 2
14.3%
B 2
14.3%
T 2
14.3%
A 1
7.1%
I 1
7.1%
M 1
7.1%
Y 1
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 8
50.0%
, 7
43.8%
? 1
 
6.2%
Space Separator
ValueCountFrequency (%)
478
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1822
70.7%
Common 739
28.7%
Latin 15
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 145
 
8.0%
출 121
 
6.6%
역 119
 
6.5%
번 118
 
6.5%
앞 86
 
4.7%
대 39
 
2.1%
사 34
 
1.9%
근 32
 
1.8%
이 32
 
1.8%
스 25
 
1.4%
Other values (256) 1071
58.8%
Common
ValueCountFrequency (%)
478
64.7%
1 36
 
4.9%
( 32
 
4.3%
) 32
 
4.3%
4 27
 
3.7%
2 26
 
3.5%
3 19
 
2.6%
5 19
 
2.6%
0 12
 
1.6%
6 11
 
1.5%
Other values (8) 47
 
6.4%
Latin
ValueCountFrequency (%)
K 2
13.3%
L 2
13.3%
G 2
13.3%
B 2
13.3%
T 2
13.3%
A 1
6.7%
m 1
6.7%
I 1
6.7%
M 1
6.7%
Y 1
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1822
70.7%
ASCII 754
29.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
478
63.4%
1 36
 
4.8%
( 32
 
4.2%
) 32
 
4.2%
4 27
 
3.6%
2 26
 
3.4%
3 19
 
2.5%
5 19
 
2.5%
0 12
 
1.6%
6 11
 
1.5%
Other values (18) 62
 
8.2%
Hangul
ValueCountFrequency (%)
구 145
 
8.0%
출 121
 
6.6%
역 119
 
6.5%
번 118
 
6.5%
앞 86
 
4.7%
대 39
 
2.1%
사 34
 
1.9%
근 32
 
1.8%
이 32
 
1.8%
스 25
 
1.4%
Other values (256) 1071
58.8%

거치대 유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size323.0 B
False
131 
True
60 
ValueCountFrequency (%)
False 131
68.6%
True 60
31.4%
2024-04-17T20:20:44.664421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

거치대 크기
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
109 
6
47 
8
15 
5
13 
4
 
6

Length

Max length4
Median length4
Mean length2.7120419
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row6
2nd row6
3rd row6
4th row8
5th row8

Common Values

ValueCountFrequency (%)
<NA> 109
57.1%
6 47
24.6%
8 15
 
7.9%
5 13
 
6.8%
4 6
 
3.1%
3 1
 
0.5%

Length

2024-04-17T20:20:44.755943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:20:44.850606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 109
57.1%
6 47
24.6%
8 15
 
7.9%
5 13
 
6.8%
4 6
 
3.1%
3 1
 
0.5%

설치일자
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2022-11
85 
2022-12
66 
2022-07
17 
2022-08
10 
2022.12
 
4
Other values (3)
9 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row2022-09
2nd row2022-12
3rd row2022-12
4th row2022-12
5th row2022-12

Common Values

ValueCountFrequency (%)
2022-11 85
44.5%
2022-12 66
34.6%
2022-07 17
 
8.9%
2022-08 10
 
5.2%
2022.12 4
 
2.1%
2022-10 4
 
2.1%
2023-03 4
 
2.1%
2022-09 1
 
0.5%

Length

2024-04-17T20:20:44.946329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:20:45.045774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11 85
44.5%
2022-12 66
34.6%
2022-07 17
 
8.9%
2022-08 10
 
5.2%
2022.12 4
 
2.1%
2022-10 4
 
2.1%
2023-03 4
 
2.1%
2022-09 1
 
0.5%

Interactions

2024-04-17T20:20:42.770799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:20:45.120798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군구명거치대 유무거치대 크기설치일자
순번1.0000.9570.9140.6660.672
시군구명0.9571.0000.9940.8190.989
거치대 유무0.9140.9941.0000.5190.882
거치대 크기0.6660.8190.5191.0000.394
설치일자0.6720.9890.8820.3941.000
2024-04-17T20:20:45.453888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명거치대 크기거치대 유무설치일자
시군구명1.0000.5680.8810.804
거치대 크기0.5681.0000.6170.247
거치대 유무0.8810.6171.0000.695
설치일자0.8040.2470.6951.000
2024-04-17T20:20:45.532679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군구명거치대 유무거치대 크기설치일자
순번1.0000.7560.7600.4940.407
시군구명0.7561.0000.8810.5680.804
거치대 유무0.7600.8811.0000.6170.695
거치대 크기0.4940.5680.6171.0000.247
설치일자0.4070.8040.6950.2471.000

Missing values

2024-04-17T20:20:42.871284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:20:42.961166image/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

순번시군구명주소상세위치거치대 유무거치대 크기설치일자
01종로구팔판동 115-63청와대 춘추문 맞은편 인근Y62022-09
12종로구연건동 218-1KT광화문 혜화지사 앞Y62022-12
23종로구연건동 178-3홍익대학교 대학로 맞은편Y62022-12
34종로구동승동 1-24대학로 마로니에공원 앞Y82022-12
45종로구와룡동 75-4연악사 맞은편Y82022-12
56종로구명륜4가 96-4흥사단 동숭미술관 맞은편Y62022-12
67종로구소격동 165-5국립현대미술관 앞Y62022-12
78종로구신문로1가 5-4새문안교회 앞Y82022-12
89종로구신문로 2가 58(구) 경찰박물관 앞Y82022-12
910종로구무악동 41-7무악현대아파트 앞Y62022-12
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