Overview

Dataset statistics

Number of variables7
Number of observations69
Missing cells21
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory60.9 B

Variable types

Numeric3
Categorical1
Text2
DateTime1

Dataset

Description인천광역시 중구 공영주차장 장애인전용주차구획 현황입니다. 주차장명 주차장위치 면적 요금체계 등의 항목으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15103400/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
연번 is highly overall correlated with 관리주체High correlation
면수 is highly overall correlated with 장애인주차구획 면수High correlation
장애인주차구획 면수 is highly overall correlated with 면수High correlation
관리주체 is highly overall correlated with 연번High correlation
장애인주차구획 면수 has 21 (30.4%) missing valuesMissing
연번 has unique valuesUnique
장애인주차구획 면수 has 7 (10.1%) zerosZeros

Reproduction

Analysis started2023-12-12 16:56:23.749317
Analysis finished2023-12-12 16:56:25.435938
Duration1.69 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-13T01:56:25.514569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q118
median35
Q352
95-th percentile65.6
Maximum69
Range68
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.062403
Coefficient of variation (CV)0.5732115
Kurtosis-1.2
Mean35
Median Absolute Deviation (MAD)17
Skewness0
Sum2415
Variance402.5
MonotonicityStrictly increasing
2023-12-13T01:56:25.691741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
45 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
44 1
 
1.4%
53 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%
60 1
1.4%

관리주체
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size684.0 B
중구
57 
경제청(영종)
7 
시
 
5

Length

Max length7
Median length2
Mean length2.4347826
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 57
82.6%
경제청(영종) 7
 
10.1%
시 5
 
7.2%

Length

2023-12-13T01:56:25.865660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:56:25.984129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 57
82.6%
경제청(영종 7
 
10.1%
시 5
 
7.2%

주차장명
Text

Distinct66
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-13T01:56:26.199376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.4492754
Min length3

Characters and Unicode

Total characters652
Distinct characters120
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)91.3%

Sample

1st row도원역
2nd row구인천여고
3rd row월미도
4th row동인천
5th row신포동
ValueCountFrequency (%)
자유공원공영주차장 2
 
2.9%
공항공사공영주차장1 2
 
2.9%
신흥시장공영주차장 2
 
2.9%
은골1공영주차장 1
 
1.4%
기독병원공영주차장2 1
 
1.4%
운서1공영주차장 1
 
1.4%
율목공원공영주차장4 1
 
1.4%
도원역 1
 
1.4%
해광사위공영주차장 1
 
1.4%
섭리어린이집인근공영주차장 1
 
1.4%
Other values (56) 56
81.2%
2023-12-13T01:56:26.591145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 74
 
11.3%
장 69
 
10.6%
차 65
 
10.0%
주 64
 
9.8%
영 61
 
9.4%
원 17
 
2.6%
동 15
 
2.3%
인 11
 
1.7%
2 10
 
1.5%
앞 9
 
1.4%
Other values (110) 257
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 624
95.7%
Decimal Number 25
 
3.8%
Dash Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 74
 
11.9%
장 69
 
11.1%
차 65
 
10.4%
주 64
 
10.3%
영 61
 
9.8%
원 17
 
2.7%
동 15
 
2.4%
인 11
 
1.8%
앞 9
 
1.4%
신 8
 
1.3%
Other values (101) 231
37.0%
Decimal Number
ValueCountFrequency (%)
2 10
40.0%
1 9
36.0%
3 2
 
8.0%
8 2
 
8.0%
7 1
 
4.0%
4 1
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 624
95.7%
Common 28
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 74
 
11.9%
장 69
 
11.1%
차 65
 
10.4%
주 64
 
10.3%
영 61
 
9.8%
원 17
 
2.7%
동 15
 
2.4%
인 11
 
1.8%
앞 9
 
1.4%
신 8
 
1.3%
Other values (101) 231
37.0%
Common
ValueCountFrequency (%)
2 10
35.7%
1 9
32.1%
3 2
 
7.1%
8 2
 
7.1%
7 1
 
3.6%
- 1
 
3.6%
( 1
 
3.6%
) 1
 
3.6%
4 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 624
95.7%
ASCII 28
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 74
 
11.9%
장 69
 
11.1%
차 65
 
10.4%
주 64
 
10.3%
영 61
 
9.8%
원 17
 
2.7%
동 15
 
2.4%
인 11
 
1.8%
앞 9
 
1.4%
신 8
 
1.3%
Other values (101) 231
37.0%
ASCII
ValueCountFrequency (%)
2 10
35.7%
1 9
32.1%
3 2
 
7.1%
8 2
 
7.1%
7 1
 
3.6%
- 1
 
3.6%
( 1
 
3.6%
) 1
 
3.6%
4 1
 
3.6%

주차장 위치
Text

Distinct68
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-13T01:56:26.946913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length21
Mean length18.550725
Min length15

Characters and Unicode

Total characters1280
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)97.1%

Sample

1st row인천광역시 중구 도원동 5-17
2nd row인천광역시 중구 전동 2-5
3rd row인천광역시 중구 북성동1가 98-39
4th row인천광역시 중구 용동 9-5
5th row인천광역시 중구 해안동4가 1-1
ValueCountFrequency (%)
인천광역시 69
24.6%
중구 69
24.6%
운서동 9
 
3.2%
율목동 8
 
2.9%
북성동1가 8
 
2.9%
내동 4
 
1.4%
도원동 3
 
1.1%
신흥동2가 3
 
1.1%
전동 3
 
1.1%
항동7가 3
 
1.1%
Other values (92) 101
36.1%
2023-12-13T01:56:27.401477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
233
18.2%
1 74
 
5.8%
천 69
 
5.4%
구 69
 
5.4%
중 69
 
5.4%
인 69
 
5.4%
시 69
 
5.4%
역 69
 
5.4%
광 69
 
5.4%
동 67
 
5.2%
Other values (48) 423
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 703
54.9%
Decimal Number 278
 
21.7%
Space Separator 233
 
18.2%
Dash Punctuation 59
 
4.6%
Other Punctuation 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 69
9.8%
구 69
9.8%
중 69
9.8%
인 69
9.8%
시 69
9.8%
역 69
9.8%
광 69
9.8%
동 67
9.5%
가 24
 
3.4%
북 10
 
1.4%
Other values (35) 119
16.9%
Decimal Number
ValueCountFrequency (%)
1 74
26.6%
2 50
18.0%
3 30
10.8%
7 24
 
8.6%
5 24
 
8.6%
8 20
 
7.2%
0 16
 
5.8%
6 14
 
5.0%
4 14
 
5.0%
9 12
 
4.3%
Space Separator
ValueCountFrequency (%)
233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 703
54.9%
Common 577
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 69
9.8%
구 69
9.8%
중 69
9.8%
인 69
9.8%
시 69
9.8%
역 69
9.8%
광 69
9.8%
동 67
9.5%
가 24
 
3.4%
북 10
 
1.4%
Other values (35) 119
16.9%
Common
ValueCountFrequency (%)
233
40.4%
1 74
 
12.8%
- 59
 
10.2%
2 50
 
8.7%
3 30
 
5.2%
7 24
 
4.2%
5 24
 
4.2%
8 20
 
3.5%
0 16
 
2.8%
6 14
 
2.4%
Other values (3) 33
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 703
54.9%
ASCII 577
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
233
40.4%
1 74
 
12.8%
- 59
 
10.2%
2 50
 
8.7%
3 30
 
5.2%
7 24
 
4.2%
5 24
 
4.2%
8 20
 
3.5%
0 16
 
2.8%
6 14
 
2.4%
Other values (3) 33
 
5.7%
Hangul
ValueCountFrequency (%)
천 69
9.8%
구 69
9.8%
중 69
9.8%
인 69
9.8%
시 69
9.8%
역 69
9.8%
광 69
9.8%
동 67
9.5%
가 24
 
3.4%
북 10
 
1.4%
Other values (35) 119
16.9%

면수
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.594203
Minimum2
Maximum282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-13T01:56:27.567651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.4
Q112
median25
Q375
95-th percentile175.2
Maximum282
Range280
Interquartile range (IQR)63

Descriptive statistics

Standard deviation62.326068
Coefficient of variation (CV)1.1850368
Kurtosis3.9486274
Mean52.594203
Median Absolute Deviation (MAD)18
Skewness1.9456862
Sum3629
Variance3884.5388
MonotonicityNot monotonic
2023-12-13T01:56:27.736527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
10 4
 
5.8%
14 4
 
5.8%
6 3
 
4.3%
4 3
 
4.3%
19 3
 
4.3%
25 3
 
4.3%
29 2
 
2.9%
2 2
 
2.9%
100 2
 
2.9%
15 2
 
2.9%
Other values (38) 41
59.4%
ValueCountFrequency (%)
2 2
2.9%
3 2
2.9%
4 3
4.3%
6 3
4.3%
7 1
 
1.4%
8 1
 
1.4%
10 4
5.8%
11 1
 
1.4%
12 1
 
1.4%
13 2
2.9%
ValueCountFrequency (%)
282 1
1.4%
273 1
1.4%
220 1
1.4%
186 1
1.4%
159 1
1.4%
137 1
1.4%
136 1
1.4%
127 1
1.4%
110 1
1.4%
109 1
1.4%

장애인주차구획 면수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct10
Distinct (%)20.8%
Missing21
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean2.4166667
Minimum0
Maximum9
Zeros7
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-13T01:56:27.880796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33.25
95-th percentile7.65
Maximum9
Range9
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation2.3323199
Coefficient of variation (CV)0.96509791
Kurtosis1.0871966
Mean2.4166667
Median Absolute Deviation (MAD)1
Skewness1.3386008
Sum116
Variance5.4397163
MonotonicityNot monotonic
2023-12-13T01:56:27.997145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 16
23.2%
2 9
13.0%
0 7
 
10.1%
4 5
 
7.2%
3 4
 
5.8%
7 2
 
2.9%
8 2
 
2.9%
5 1
 
1.4%
9 1
 
1.4%
6 1
 
1.4%
(Missing) 21
30.4%
ValueCountFrequency (%)
0 7
10.1%
1 16
23.2%
2 9
13.0%
3 4
 
5.8%
4 5
 
7.2%
5 1
 
1.4%
6 1
 
1.4%
7 2
 
2.9%
8 2
 
2.9%
9 1
 
1.4%
ValueCountFrequency (%)
9 1
 
1.4%
8 2
 
2.9%
7 2
 
2.9%
6 1
 
1.4%
5 1
 
1.4%
4 5
 
7.2%
3 4
 
5.8%
2 9
13.0%
1 16
23.2%
0 7
10.1%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2023-08-09 00:00:00
Maximum2023-08-09 00:00:00
2023-12-13T01:56:28.102099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:28.225613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:56:24.898907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.331952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.607626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.996521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.438643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.719494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:25.091618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.525409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:24.813873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:56:28.305721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리주체주차장명주차장 위치면수장애인주차구획 면수
연번1.0000.9300.9380.9390.3970.725
관리주체0.9301.0001.0001.0000.6820.509
주차장명0.9381.0001.0000.9970.9510.985
주차장 위치0.9391.0000.9971.0001.0000.980
면수0.3970.6820.9511.0001.0000.888
장애인주차구획 면수0.7250.5090.9850.9800.8881.000
2023-12-13T01:56:28.459424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면수장애인주차구획 면수관리주체
연번1.000-0.221-0.1380.857
면수-0.2211.0000.7730.372
장애인주차구획 면수-0.1380.7731.0000.321
관리주체0.8570.3720.3211.000

Missing values

2023-12-13T01:56:25.235661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:56:25.385459image/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

연번관리주체주차장명주차장 위치면수장애인주차구획 면수데이터 기준일자
01시도원역인천광역시 중구 도원동 5-176022023-08-09
12시구인천여고인천광역시 중구 전동 2-510032023-08-09
23시월미도인천광역시 중구 북성동1가 98-3912752023-08-09
34시동인천인천광역시 중구 용동 9-57522023-08-09
45시신포동인천광역시 중구 해안동4가 1-17132023-08-09
56중구한중문화관공영주차장인천광역시 중구 항동1가 1-1610942023-08-09
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