Overview

Dataset statistics

Number of variables6
Number of observations165
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory50.8 B

Variable types

Numeric2
Text2
Categorical1
DateTime1

Dataset

Description인천광역시 서구 자전거 보관함에 대한 데이터로 시설명, 주소, 총보관대수, 공기주입기유무 등의 정보가 포함되어 있습니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15091258/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:02:30.440959
Analysis finished2023-12-12 16:02:31.634820
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct165
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83
Minimum1
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T01:02:31.713301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.2
Q142
median83
Q3124
95-th percentile156.8
Maximum165
Range164
Interquartile range (IQR)82

Descriptive statistics

Standard deviation47.775517
Coefficient of variation (CV)0.57560864
Kurtosis-1.2
Mean83
Median Absolute Deviation (MAD)41
Skewness0
Sum13695
Variance2282.5
MonotonicityStrictly increasing
2023-12-13T01:02:31.846352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
105 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
Other values (155) 155
93.9%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%

시설명
Text

UNIQUE 

Distinct165
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:02:32.020772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length11.460606
Min length3

Characters and Unicode

Total characters1891
Distinct characters199
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)100.0%

Sample

1st row2호선 주안국가산단역 1번출구
2nd row2호선 주안국가산단역 2번출구
3rd row2호선 가재울역 1번출구
4th row2호선 가재울역 2번출구
5th row2호선 가재울역 4번출구
ValueCountFrequency (%)
행정복지센터 14
 
4.5%
1번출구 9
 
2.9%
2번출구 8
 
2.6%
아시아드경기장 7
 
2.3%
출구 7
 
2.3%
석남역 7
 
2.3%
버스정류소 6
 
1.9%
4번출구 6
 
1.9%
앞 6
 
1.9%
초은고등학교 5
 
1.6%
Other values (179) 234
75.7%
2023-12-13T01:02:32.347660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
 
7.8%
정 70
 
3.7%
구 53
 
2.8%
청 44
 
2.3%
교 44
 
2.3%
역 43
 
2.3%
학 40
 
2.1%
소 37
 
2.0%
번 36
 
1.9%
출 36
 
1.9%
Other values (189) 1341
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1568
82.9%
Space Separator 147
 
7.8%
Decimal Number 72
 
3.8%
Open Punctuation 27
 
1.4%
Close Punctuation 27
 
1.4%
Dash Punctuation 25
 
1.3%
Uppercase Letter 24
 
1.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 70
 
4.5%
구 53
 
3.4%
청 44
 
2.8%
교 44
 
2.8%
역 43
 
2.7%
학 40
 
2.6%
소 37
 
2.4%
번 36
 
2.3%
출 36
 
2.3%
등 35
 
2.2%
Other values (172) 1130
72.1%
Decimal Number
ValueCountFrequency (%)
2 21
29.2%
1 20
27.8%
3 10
13.9%
4 9
12.5%
7 4
 
5.6%
5 3
 
4.2%
6 2
 
2.8%
0 1
 
1.4%
8 1
 
1.4%
9 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
S 12
50.0%
N 12
50.0%
Space Separator
ValueCountFrequency (%)
147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1568
82.9%
Common 299
 
15.8%
Latin 24
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 70
 
4.5%
구 53
 
3.4%
청 44
 
2.8%
교 44
 
2.8%
역 43
 
2.7%
학 40
 
2.6%
소 37
 
2.4%
번 36
 
2.3%
출 36
 
2.3%
등 35
 
2.2%
Other values (172) 1130
72.1%
Common
ValueCountFrequency (%)
147
49.2%
( 27
 
9.0%
) 27
 
9.0%
- 25
 
8.4%
2 21
 
7.0%
1 20
 
6.7%
3 10
 
3.3%
4 9
 
3.0%
7 4
 
1.3%
5 3
 
1.0%
Other values (5) 6
 
2.0%
Latin
ValueCountFrequency (%)
S 12
50.0%
N 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1568
82.9%
ASCII 323
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
45.5%
( 27
 
8.4%
) 27
 
8.4%
- 25
 
7.7%
2 21
 
6.5%
1 20
 
6.2%
S 12
 
3.7%
N 12
 
3.7%
3 10
 
3.1%
4 9
 
2.8%
Other values (7) 13
 
4.0%
Hangul
ValueCountFrequency (%)
정 70
 
4.5%
구 53
 
3.4%
청 44
 
2.8%
교 44
 
2.8%
역 43
 
2.7%
학 40
 
2.6%
소 37
 
2.4%
번 36
 
2.3%
출 36
 
2.3%
등 35
 
2.2%
Other values (172) 1130
72.1%

주소
Text

Distinct118
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:02:32.583495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length16.563636
Min length12

Characters and Unicode

Total characters2733
Distinct characters101
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

Unique102 ?
Unique (%)61.8%

Sample

1st row인천광역시 서구 가좌동 606-40
2nd row인천광역시 서구 주안동 1381-6
3rd row인천광역시 서구 가좌동 305-5
4th row인천광역시 서구 열우물로 252
5th row인천광역시 서구 열우물로 249
ValueCountFrequency (%)
인천광역시 165
25.9%
서구 165
25.9%
청중로 12
 
1.9%
경제로 12
 
1.9%
서곶로 11
 
1.7%
봉수대로 10
 
1.6%
826 7
 
1.1%
원당대로 6
 
0.9%
완정로 6
 
0.9%
검단로 5
 
0.8%
Other values (166) 238
37.4%
2023-12-13T01:02:32.944910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
17.3%
서 181
 
6.6%
인 165
 
6.0%
천 165
 
6.0%
광 165
 
6.0%
역 165
 
6.0%
시 165
 
6.0%
구 165
 
6.0%
로 144
 
5.3%
1 83
 
3.0%
Other values (91) 862
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1760
64.4%
Decimal Number 478
 
17.5%
Space Separator 473
 
17.3%
Dash Punctuation 22
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 181
10.3%
인 165
9.4%
천 165
9.4%
광 165
9.4%
역 165
9.4%
시 165
9.4%
구 165
9.4%
로 144
 
8.2%
길 36
 
2.0%
번 31
 
1.8%
Other values (79) 378
21.5%
Decimal Number
ValueCountFrequency (%)
1 83
17.4%
2 78
16.3%
6 49
10.3%
0 45
9.4%
4 43
9.0%
5 38
7.9%
3 37
7.7%
9 36
7.5%
8 35
7.3%
7 34
7.1%
Space Separator
ValueCountFrequency (%)
473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1760
64.4%
Common 973
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 181
10.3%
인 165
9.4%
천 165
9.4%
광 165
9.4%
역 165
9.4%
시 165
9.4%
구 165
9.4%
로 144
 
8.2%
길 36
 
2.0%
번 31
 
1.8%
Other values (79) 378
21.5%
Common
ValueCountFrequency (%)
473
48.6%
1 83
 
8.5%
2 78
 
8.0%
6 49
 
5.0%
0 45
 
4.6%
4 43
 
4.4%
5 38
 
3.9%
3 37
 
3.8%
9 36
 
3.7%
8 35
 
3.6%
Other values (2) 56
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1760
64.4%
ASCII 973
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
48.6%
1 83
 
8.5%
2 78
 
8.0%
6 49
 
5.0%
0 45
 
4.6%
4 43
 
4.4%
5 38
 
3.9%
3 37
 
3.8%
9 36
 
3.7%
8 35
 
3.6%
Other values (2) 56
 
5.8%
Hangul
ValueCountFrequency (%)
서 181
10.3%
인 165
9.4%
천 165
9.4%
광 165
9.4%
역 165
9.4%
시 165
9.4%
구 165
9.4%
로 144
 
8.2%
길 36
 
2.0%
번 31
 
1.8%
Other values (79) 378
21.5%

총보관대수
Real number (ℝ)

Distinct33
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.224242
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T01:02:33.056874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q110
median10
Q320
95-th percentile50
Maximum180
Range178
Interquartile range (IQR)10

Descriptive statistics

Standard deviation21.09339
Coefficient of variation (CV)1.1574358
Kurtosis24.054173
Mean18.224242
Median Absolute Deviation (MAD)3
Skewness4.1874235
Sum3007
Variance444.93112
MonotonicityNot monotonic
2023-12-13T01:02:33.158411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
10 70
42.4%
20 22
 
13.3%
5 13
 
7.9%
7 12
 
7.3%
40 6
 
3.6%
8 5
 
3.0%
30 3
 
1.8%
60 3
 
1.8%
25 3
 
1.8%
50 3
 
1.8%
Other values (23) 25
 
15.2%
ValueCountFrequency (%)
2 1
 
0.6%
4 1
 
0.6%
5 13
 
7.9%
6 1
 
0.6%
7 12
 
7.3%
8 5
 
3.0%
9 2
 
1.2%
10 70
42.4%
12 1
 
0.6%
13 1
 
0.6%
ValueCountFrequency (%)
180 1
 
0.6%
110 1
 
0.6%
104 1
 
0.6%
80 1
 
0.6%
70 1
 
0.6%
60 3
1.8%
50 3
1.8%
49 1
 
0.6%
48 1
 
0.6%
40 6
3.6%

공기주입기유무
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
무
146 
유
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유
2nd row무
3rd row무
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 146
88.5%
유 19
 
11.5%

Length

2023-12-13T01:02:33.261194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:02:33.343566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 146
88.5%
유 19
 
11.5%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2022-08-01 00:00:00
Maximum2022-08-01 00:00:00
2023-12-13T01:02:33.413585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:02:33.489975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:02:30.947615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:02:30.700344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:02:31.033614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:02:30.824844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:02:33.544600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번총보관대수공기주입기유무
연번1.0000.3210.415
총보관대수0.3211.0000.342
공기주입기유무0.4150.3421.000
2023-12-13T01:02:33.616273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번총보관대수공기주입기유무
연번1.0000.1520.311
총보관대수0.1521.0000.251
공기주입기유무0.3110.2511.000

Missing values

2023-12-13T01:02:31.491217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:02:31.592701image/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

연번시설명주소총보관대수공기주입기유무데이터기준일
012호선 주안국가산단역 1번출구인천광역시 서구 가좌동 606-4010유2022-08-01
122호선 주안국가산단역 2번출구인천광역시 서구 주안동 1381-610무2022-08-01
232호선 가재울역 1번출구인천광역시 서구 가좌동 305-510무2022-08-01
342호선 가재울역 2번출구인천광역시 서구 열우물로 25210무2022-08-01
452호선 가재울역 4번출구인천광역시 서구 열우물로 24920무2022-08-01
56가좌119 안전센터인천광역시 서구 백범로678번길 175무2022-08-01
67가좌4동 행정복지센터인천광역시 서구 장고개로280번길 147유2022-08-01
78가좌3동 행정복지센터인천광역시 서구 원적로57번길 45무2022-08-01
89가좌2동 행정복지센터인천광역시 서구 장고개로309번길 410유2022-08-01
910서부여성회관인천광역시 서구 서달로 1210무2022-08-01
연번시설명주소총보관대수공기주입기유무데이터기준일
155156청라 파크자이 더 테라스 앞인천광역시 서구 청라동 105-22무2022-08-01
156157청라고등학교인천광역시 서구 담지로86번길 16-1425무2022-08-01
157158용머리공원인천광역시 서구 청라동 137-348무2022-08-01
158159인천녹청자박물관인천광역시 서구 도요지로 5410무2022-08-01
159160청라국제입구 사거리인천광역시 서구 가정동 604-220무2022-08-01
160161백범로인천광역시 서구 백범로934번길 45무2022-08-01
161162청라호수공원 내인천광역시 서구 청라대로 20420유2022-08-01
162163경서1공원인천광역시 서구 오류동 1579-114무2022-08-01
163164가원초인천광역시 서구 청중로478번길 650무2022-08-01
164165서구국민체육센터인천광역시 서구 승학로 52540무2022-08-01