Overview

Dataset statistics

Number of variables11
Number of observations30
Missing cells28
Missing cells (%)8.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory95.4 B

Variable types

Numeric3
Text4
Categorical3
DateTime1

Dataset

Description대전광역시 서구 공한지주차장 시설현황입니다.(순번, 주차장명, 행정동, 행정동코드, 법정동, 법정동코드, 지번주소, 도로명주소, 상세주소, 면적, 주차면수, 설치일, 소유자)
URLhttps://www.data.go.kr/data/15104077/fileData.do

Alerts

면적(m2) is highly overall correlated with 주차면수 and 1 other fieldsHigh correlation
주차면수 is highly overall correlated with 면적(m2) and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 법정동High correlation
법정동 is highly overall correlated with 행정동High correlation
소유자 is highly overall correlated with 면적(m2) and 1 other fieldsHigh correlation
소유자 is highly imbalanced (61.7%)Imbalance
도로명주소 has 28 (93.3%) missing valuesMissing
순번 has unique valuesUnique
주차장명 has unique valuesUnique
지번주소 has unique valuesUnique
상세주소 has unique valuesUnique
면적(m2) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:05:26.172712
Analysis finished2023-12-12 15:05:27.413810
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:05:27.468985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityNot monotonic
2023-12-13T00:05:27.589869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
23 1
 
3.3%
22 1
 
3.3%
24 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

주차장명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T00:05:27.807298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.033333
Min length12

Characters and Unicode

Total characters361
Distinct characters44
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row도마제2공한지무료주차장
2nd row변동제1공한지무료주차장
3rd row괴정제1공한지무료주차장
4th row둔산제1공한지무료주차장
5th row월평제3공한지무료주차장
ValueCountFrequency (%)
도마제2공한지무료주차장 1
 
3.3%
변동제1공한지무료주차장 1
 
3.3%
관저제8공한지무료주차장 1
 
3.3%
관저제7공한지무료주차장 1
 
3.3%
관저제6공한지무료주차장 1
 
3.3%
관저제5공한지무료주차장 1
 
3.3%
괴정제2공한지무료주차장 1
 
3.3%
용문제1공한지무료주차장 1
 
3.3%
관저제4공한지무료주차장 1
 
3.3%
관저제3공한지무료주차장 1
 
3.3%
Other values (20) 20
66.7%
2023-12-13T00:05:28.167837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 30
 
8.3%
제 30
 
8.3%
공 30
 
8.3%
한 30
 
8.3%
지 30
 
8.3%
료 30
 
8.3%
주 30
 
8.3%
차 30
 
8.3%
무 29
 
8.0%
관 9
 
2.5%
Other values (34) 83
23.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
91.7%
Decimal Number 30
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 30
9.1%
제 30
9.1%
공 30
9.1%
한 30
9.1%
지 30
9.1%
료 30
9.1%
주 30
9.1%
차 30
9.1%
무 29
8.8%
관 9
 
2.7%
Other values (25) 53
16.0%
Decimal Number
ValueCountFrequency (%)
1 9
30.0%
2 5
16.7%
3 5
16.7%
4 3
 
10.0%
5 3
 
10.0%
6 2
 
6.7%
8 1
 
3.3%
7 1
 
3.3%
9 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
91.7%
Common 30
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 30
9.1%
제 30
9.1%
공 30
9.1%
한 30
9.1%
지 30
9.1%
료 30
9.1%
주 30
9.1%
차 30
9.1%
무 29
8.8%
관 9
 
2.7%
Other values (25) 53
16.0%
Common
ValueCountFrequency (%)
1 9
30.0%
2 5
16.7%
3 5
16.7%
4 3
 
10.0%
5 3
 
10.0%
6 2
 
6.7%
8 1
 
3.3%
7 1
 
3.3%
9 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
91.7%
ASCII 30
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 30
9.1%
제 30
9.1%
공 30
9.1%
한 30
9.1%
지 30
9.1%
료 30
9.1%
주 30
9.1%
차 30
9.1%
무 29
8.8%
관 9
 
2.7%
Other values (25) 53
16.0%
ASCII
ValueCountFrequency (%)
1 9
30.0%
2 5
16.7%
3 5
16.7%
4 3
 
10.0%
5 3
 
10.0%
6 2
 
6.7%
8 1
 
3.3%
7 1
 
3.3%
9 1
 
3.3%

행정동
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
변동
5 
관저1동
5 
관저2동
4 
도마2동
3 
가수원동
3 
Other values (8)
10 

Length

Max length4
Median length4
Mean length3.4333333
Min length2

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row도마2동
2nd row변동
3rd row괴정동
4th row둔산1동
5th row월평1동

Common Values

ValueCountFrequency (%)
변동 5
16.7%
관저1동 5
16.7%
관저2동 4
13.3%
도마2동 3
10.0%
가수원동 3
10.0%
괴정동 2
 
6.7%
기성동 2
 
6.7%
둔산1동 1
 
3.3%
월평1동 1
 
3.3%
탄방동 1
 
3.3%
Other values (3) 3
10.0%

Length

2023-12-13T00:05:28.362505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
변동 5
16.7%
관저1동 5
16.7%
관저2동 4
13.3%
도마2동 3
10.0%
가수원동 3
10.0%
괴정동 2
 
6.7%
기성동 2
 
6.7%
둔산1동 1
 
3.3%
월평1동 1
 
3.3%
탄방동 1
 
3.3%
Other values (3) 3
10.0%

법정동
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
관저동
9 
변동
5 
도마동
3 
괴정동
2 
둔산동
2 
Other values (8)
9 

Length

Max length4
Median length3
Mean length2.8666667
Min length2

Unique

Unique7 ?
Unique (%)23.3%

Sample

1st row도마동
2nd row변동
3rd row괴정동
4th row둔산동
5th row월평동

Common Values

ValueCountFrequency (%)
관저동 9
30.0%
변동 5
16.7%
도마동 3
 
10.0%
괴정동 2
 
6.7%
둔산동 2
 
6.7%
도안동 2
 
6.7%
월평동 1
 
3.3%
탄방동 1
 
3.3%
우명동 1
 
3.3%
가수원동 1
 
3.3%
Other values (3) 3
 
10.0%

Length

2023-12-13T00:05:28.519231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관저동 9
30.0%
변동 5
16.7%
도마동 3
 
10.0%
괴정동 2
 
6.7%
둔산동 2
 
6.7%
도안동 2
 
6.7%
월평동 1
 
3.3%
탄방동 1
 
3.3%
우명동 1
 
3.3%
가수원동 1
 
3.3%
Other values (3) 3
 
10.0%

지번주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T00:05:28.735988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length15.033333
Min length13

Characters and Unicode

Total characters451
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row대전 서구 도마2동 549-13
2nd row대전 서구 변동 32-46
3rd row대전 서구 괴정동 46-9
4th row대전 서구 둔산1동 1409
5th row대전 서구 월평1동 1439
ValueCountFrequency (%)
대전 30
24.6%
서구 30
24.6%
관저동 9
 
7.4%
변동 5
 
4.1%
괴정동 2
 
1.6%
도안동 2
 
1.6%
도마동 2
 
1.6%
1113 1
 
0.8%
934 1
 
0.8%
용촌동 1
 
0.8%
Other values (39) 39
32.0%
2023-12-13T00:05:29.181633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
20.4%
1 37
 
8.2%
대 30
 
6.7%
전 30
 
6.7%
서 30
 
6.7%
구 30
 
6.7%
동 30
 
6.7%
- 17
 
3.8%
3 15
 
3.3%
5 14
 
3.1%
Other values (32) 126
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
45.7%
Decimal Number 133
29.5%
Space Separator 92
20.4%
Dash Punctuation 17
 
3.8%
Other Punctuation 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 30
14.6%
전 30
14.6%
서 30
14.6%
구 30
14.6%
동 30
14.6%
관 9
 
4.4%
저 9
 
4.4%
도 5
 
2.4%
변 5
 
2.4%
마 3
 
1.5%
Other values (18) 25
12.1%
Decimal Number
ValueCountFrequency (%)
1 37
27.8%
3 15
11.3%
5 14
 
10.5%
9 13
 
9.8%
2 13
 
9.8%
4 12
 
9.0%
6 9
 
6.8%
8 8
 
6.0%
7 7
 
5.3%
0 5
 
3.8%
Space Separator
ValueCountFrequency (%)
92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 245
54.3%
Hangul 206
45.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 30
14.6%
전 30
14.6%
서 30
14.6%
구 30
14.6%
동 30
14.6%
관 9
 
4.4%
저 9
 
4.4%
도 5
 
2.4%
변 5
 
2.4%
마 3
 
1.5%
Other values (18) 25
12.1%
Common
ValueCountFrequency (%)
92
37.6%
1 37
15.1%
- 17
 
6.9%
3 15
 
6.1%
5 14
 
5.7%
9 13
 
5.3%
2 13
 
5.3%
4 12
 
4.9%
6 9
 
3.7%
8 8
 
3.3%
Other values (4) 15
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 245
54.3%
Hangul 206
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
37.6%
1 37
15.1%
- 17
 
6.9%
3 15
 
6.1%
5 14
 
5.7%
9 13
 
5.3%
2 13
 
5.3%
4 12
 
4.9%
6 9
 
3.7%
8 8
 
3.3%
Other values (4) 15
 
6.1%
Hangul
ValueCountFrequency (%)
대 30
14.6%
전 30
14.6%
서 30
14.6%
구 30
14.6%
동 30
14.6%
관 9
 
4.4%
저 9
 
4.4%
도 5
 
2.4%
변 5
 
2.4%
마 3
 
1.5%
Other values (18) 25
12.1%

도로명주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing28
Missing (%)93.3%
Memory size372.0 B
2023-12-13T00:05:29.381639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18.5
Mean length18.5
Min length18

Characters and Unicode

Total characters37
Distinct characters19
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

Unique2 ?
Unique (%)100.0%

Sample

1st row대전 서구 우명길 68 (우명동)
2nd row대전 서구 정방길 200 (용촌동)
ValueCountFrequency (%)
대전 2
20.0%
서구 2
20.0%
우명길 1
10.0%
68 1
10.0%
우명동 1
10.0%
정방길 1
10.0%
200 1
10.0%
용촌동 1
10.0%
2023-12-13T00:05:29.722750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
21.6%
대 2
 
5.4%
서 2
 
5.4%
구 2
 
5.4%
우 2
 
5.4%
명 2
 
5.4%
길 2
 
5.4%
전 2
 
5.4%
( 2
 
5.4%
동 2
 
5.4%
Other values (9) 11
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20
54.1%
Space Separator 8
 
21.6%
Decimal Number 5
 
13.5%
Open Punctuation 2
 
5.4%
Close Punctuation 2
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 2
10.0%
서 2
10.0%
구 2
10.0%
우 2
10.0%
명 2
10.0%
길 2
10.0%
전 2
10.0%
동 2
10.0%
용 1
5.0%
방 1
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
0 2
40.0%
2 1
20.0%
8 1
20.0%
6 1
20.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20
54.1%
Common 17
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 2
10.0%
서 2
10.0%
구 2
10.0%
우 2
10.0%
명 2
10.0%
길 2
10.0%
전 2
10.0%
동 2
10.0%
용 1
5.0%
방 1
5.0%
Other values (2) 2
10.0%
Common
ValueCountFrequency (%)
8
47.1%
( 2
 
11.8%
) 2
 
11.8%
0 2
 
11.8%
2 1
 
5.9%
8 1
 
5.9%
6 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20
54.1%
ASCII 17
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
47.1%
( 2
 
11.8%
) 2
 
11.8%
0 2
 
11.8%
2 1
 
5.9%
8 1
 
5.9%
6 1
 
5.9%
Hangul
ValueCountFrequency (%)
대 2
10.0%
서 2
10.0%
구 2
10.0%
우 2
10.0%
명 2
10.0%
길 2
10.0%
전 2
10.0%
동 2
10.0%
용 1
5.0%
방 1
5.0%
Other values (2) 2
10.0%

상세주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T00:05:29.975310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.0666667
Min length7

Characters and Unicode

Total characters272
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row도마2동 549-13
2nd row변동 32-46
3rd row괴정 46-9
4th row둔산1동 1409
5th row월평1동 1439
ValueCountFrequency (%)
관저동 9
 
14.5%
변동 5
 
8.1%
도마동 2
 
3.2%
도안동 2
 
3.2%
1965-1 1
 
1.6%
용촌동 1
 
1.6%
412-1 1
 
1.6%
4-35 1
 
1.6%
1550-2 1
 
1.6%
1343 1
 
1.6%
Other values (38) 38
61.3%
2023-12-13T00:05:30.391798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 37
13.6%
32
 
11.8%
동 29
 
10.7%
- 17
 
6.2%
3 15
 
5.5%
2 14
 
5.1%
5 14
 
5.1%
9 13
 
4.8%
4 12
 
4.4%
관 9
 
3.3%
Other values (29) 80
29.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134
49.3%
Other Letter 86
31.6%
Space Separator 32
 
11.8%
Dash Punctuation 17
 
6.2%
Other Punctuation 2
 
0.7%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
33.7%
관 9
 
10.5%
저 9
 
10.5%
도 5
 
5.8%
변 5
 
5.8%
마 3
 
3.5%
용 2
 
2.3%
둔 2
 
2.3%
안 2
 
2.3%
산 2
 
2.3%
Other values (15) 18
20.9%
Decimal Number
ValueCountFrequency (%)
1 37
27.6%
3 15
11.2%
2 14
 
10.4%
5 14
 
10.4%
9 13
 
9.7%
4 12
 
9.0%
6 9
 
6.7%
8 8
 
6.0%
7 7
 
5.2%
0 5
 
3.7%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 186
68.4%
Hangul 86
31.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
33.7%
관 9
 
10.5%
저 9
 
10.5%
도 5
 
5.8%
변 5
 
5.8%
마 3
 
3.5%
용 2
 
2.3%
둔 2
 
2.3%
안 2
 
2.3%
산 2
 
2.3%
Other values (15) 18
20.9%
Common
ValueCountFrequency (%)
1 37
19.9%
32
17.2%
- 17
9.1%
3 15
8.1%
2 14
 
7.5%
5 14
 
7.5%
9 13
 
7.0%
4 12
 
6.5%
6 9
 
4.8%
8 8
 
4.3%
Other values (4) 15
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
68.4%
Hangul 86
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37
19.9%
32
17.2%
- 17
9.1%
3 15
8.1%
2 14
 
7.5%
5 14
 
7.5%
9 13
 
7.0%
4 12
 
6.5%
6 9
 
4.8%
8 8
 
4.3%
Other values (4) 15
8.1%
Hangul
ValueCountFrequency (%)
동 29
33.7%
관 9
 
10.5%
저 9
 
10.5%
도 5
 
5.8%
변 5
 
5.8%
마 3
 
3.5%
용 2
 
2.3%
둔 2
 
2.3%
안 2
 
2.3%
산 2
 
2.3%
Other values (15) 18
20.9%

면적(m2)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean756.42
Minimum99.2
Maximum4329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:05:30.570960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum99.2
5-th percentile144.585
Q1207.7
median297.85
Q3662.625
95-th percentile3024.41
Maximum4329
Range4229.8
Interquartile range (IQR)454.925

Descriptive statistics

Standard deviation1030.9121
Coefficient of variation (CV)1.3628832
Kurtosis4.9360056
Mean756.42
Median Absolute Deviation (MAD)135.1
Skewness2.3243607
Sum22692.6
Variance1062779.7
MonotonicityNot monotonic
2023-12-13T00:05:30.732338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
188.0 1
 
3.3%
180.0 1
 
3.3%
335.2 1
 
3.3%
298.7 1
 
3.3%
466.0 1
 
3.3%
297.0 1
 
3.3%
3080.3 1
 
3.3%
235.0 1
 
3.3%
472.9 1
 
3.3%
285.1 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
99.2 1
3.3%
129.6 1
3.3%
162.9 1
3.3%
174.0 1
3.3%
180.0 1
3.3%
188.0 1
3.3%
193.4 1
3.3%
198.6 1
3.3%
235.0 1
3.3%
245.5 1
3.3%
ValueCountFrequency (%)
4329.0 1
3.3%
3080.3 1
3.3%
2956.1 1
3.3%
1911.2 1
3.3%
1867.5 1
3.3%
844.2 1
3.3%
712.0 1
3.3%
675.4 1
3.3%
624.3 1
3.3%
515.0 1
3.3%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum3
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:05:30.845595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.45
Q18.25
median10
Q325.75
95-th percentile89.5
Maximum121
Range118
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation29.819861
Coefficient of variation (CV)1.2171372
Kurtosis3.5378389
Mean24.5
Median Absolute Deviation (MAD)5
Skewness2.0405527
Sum735
Variance889.22414
MonotonicityNot monotonic
2023-12-13T00:05:30.983540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
9 4
13.3%
10 4
13.3%
8 2
 
6.7%
20 2
 
6.7%
6 2
 
6.7%
5 2
 
6.7%
11 2
 
6.7%
30 1
 
3.3%
27 1
 
3.3%
121 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
3 1
 
3.3%
4 1
 
3.3%
5 2
6.7%
6 2
6.7%
8 2
6.7%
9 4
13.3%
10 4
13.3%
11 2
6.7%
16 1
 
3.3%
20 2
6.7%
ValueCountFrequency (%)
121 1
3.3%
94 1
3.3%
84 1
3.3%
64 1
3.3%
60 1
3.3%
34 1
3.3%
30 1
3.3%
27 1
3.3%
22 1
3.3%
20 2
6.7%

설치일
Date

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1991-09-05 00:00:00
Maximum2023-05-04 00:00:00
2023-12-13T00:05:31.105983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.224328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

소유자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
개인
26 
LH
 
2
목원대학교
 
1
국
 
1

Length

Max length5
Median length2
Mean length2.0666667
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
개인 26
86.7%
LH 2
 
6.7%
목원대학교 1
 
3.3%
국 1
 
3.3%

Length

2023-12-13T00:05:31.364200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:05:31.482294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 26
86.7%
lh 2
 
6.7%
목원대학교 1
 
3.3%
국 1
 
3.3%

Interactions

2023-12-13T00:05:26.944125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.552203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.746969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.025308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.617495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.813439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.099260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.677032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.874460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:05:31.563310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번주차장명행정동법정동지번주소도로명주소상세주소면적(m2)주차면수설치일소유자
순번1.0001.0000.6560.4711.0000.0001.0000.4000.3590.9830.609
주차장명1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
행정동0.6561.0001.0000.9941.000NaN1.0000.0000.5750.9570.000
법정동0.4711.0000.9941.0001.0000.0001.0000.0000.0000.9680.000
지번주소1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
도로명주소0.0000.000NaN0.0000.0001.0000.000NaNNaN0.000NaN
상세주소1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
면적(m2)0.4001.0000.0000.0001.000NaN1.0001.0000.9950.6750.951
주차면수0.3591.0000.5750.0001.000NaN1.0000.9951.0000.3630.995
설치일0.9831.0000.9570.9681.0000.0001.0000.6750.3631.0001.000
소유자0.6091.0000.0000.0001.000NaN1.0000.9510.9951.0001.000
2023-12-13T00:05:31.714256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동소유자행정동
법정동1.0000.0000.846
소유자0.0001.0000.000
행정동0.8460.0001.000
2023-12-13T00:05:31.807989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적(m2)주차면수행정동법정동소유자
순번1.0000.2220.1350.2860.1430.348
면적(m2)0.2221.0000.9350.0000.0000.820
주차면수0.1350.9351.0000.2350.0000.834
행정동0.2860.0000.2351.0000.8460.000
법정동0.1430.0000.0000.8461.0000.000
소유자0.3480.8200.8340.0000.0001.000

Missing values

2023-12-13T00:05:27.209143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:05:27.358915image/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

순번주차장명행정동법정동지번주소도로명주소상세주소면적(m2)주차면수설치일소유자
01도마제2공한지무료주차장도마2동도마동대전 서구 도마2동 549-13<NA>도마2동 549-13188.082003-11-26개인
12변동제1공한지무료주차장변동변동대전 서구 변동 32-46<NA>변동 32-46198.691999-06-15개인
23괴정제1공한지무료주차장괴정동괴정동대전 서구 괴정동 46-9<NA>괴정 46-9433.1111991-09-05개인
34둔산제1공한지무료주차장둔산1동둔산동대전 서구 둔산1동 1409<NA>둔산1동 1409844.2342002-05-06개인
45월평제3공한지무료주차장월평1동월평동대전 서구 월평1동 1439<NA>월평1동 1439193.492001-05-21개인
58도안제2공한지무료주차장가수원동도안동대전 서구 도안동 1088<NA>도안동 1088265.4102016-04-29개인
69도마제3공한지무료주차장도마2동도마동대전 서구 도마동 479-1<NA>도마동 479-1268.042016-04-29개인
710탄방제1공한지무료주차장탄방동탄방동대전 서구 탄방동 1053<NA>탄방동 1053712.0302016-06-29개인
811도마제5공한지무료주차장도마2동도마동대전 서구 도마동 552-4<NA>도마동 552-4174.092017-07-11개인
912변동제4공한지무료주차장변동변동대전 서구 변동 3-13<NA>변동 3-13624.3272017-07-11개인
순번주차장명행정동법정동지번주소도로명주소상세주소면적(m2)주차면수설치일소유자
2025둔산제2공한지유료주차장둔산2동둔산동대전 서구 둔산동 1113, 1114<NA>둔산2동 1113, 11141867.5642023-05-03개인
2121관저제3공한지무료주차장관저2동관저동대전 서구 관저동 1965-1<NA>관저동 1965-1245.582021-04-27개인
2224관저제4공한지무료주차장관저1동관저동대전 서구 관저동 1883<NA>관저동 1883285.1102022-04-04개인
2322용문제1공한지무료주차장용문동용문동대전 서구 용문동 272-16<NA>용문동 272-16472.9202021-12-31개인
2423괴정제2공한지무료주차장괴정동괴정동대전 서구 괴정동 9-1<NA>괴정동 9-1235.052022-04-04개인
2526관저제5공한지무료주차장관저2동관저동대전 서구 관저동 1992-2~5<NA>관저동 1992-2~53080.3942023-05-03개인
2627관저제6공한지무료주차장관저1동관저동대전 서구 관저동 1792<NA>관저동 1792297.0102023-05-04개인
2728관저제7공한지무료주차장관저1동관저동대전 서구 관저동 1886<NA>관저동 1886466.0162023-05-04개인
2829관저제8공한지무료주차장관저1동관저동대전 서구 관저동 1653<NA>관저동 1653298.792023-05-04개인
2930관저제9공한지무료주차장관저1동관저동대전 서구 관저동 1711<NA>관저동 1711335.2112023-05-04개인