Overview

Dataset statistics

Number of variables15
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory131.5 B

Variable types

Numeric5
Categorical6
Text3
DateTime1

Dataset

Description인천광역시 미집행도시계획시설현황(구분,군구명,시설 구분,시설의 세분,시설명,위치,결정 면적 (㎡),미집행 면적 (제곱미터),총 사업비 (백만원),향후 사업비 (백만원),단계 구분,최초 결정일,실효 시기,관리 방안,비고)자료를 제공합니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15030360

Alerts

관리 방안 has constant value ""Constant
실효 시기 is highly overall correlated with 군구명 and 3 other fieldsHigh correlation
비고 is highly overall correlated with 구분 and 8 other fieldsHigh correlation
시설 구분 is highly overall correlated with 구분 and 3 other fieldsHigh correlation
단계 구분 is highly overall correlated with 결정 면적 (제곱미터) and 5 other fieldsHigh correlation
군구명 is highly overall correlated with 미집행 면적 (제곱미터) and 3 other fieldsHigh correlation
구분 is highly overall correlated with 시설 구분 and 1 other fieldsHigh correlation
결정 면적 (제곱미터) is highly overall correlated with 미집행 면적 (제곱미터) and 4 other fieldsHigh correlation
미집행 면적 (제곱미터) is highly overall correlated with 결정 면적 (제곱미터) and 5 other fieldsHigh correlation
총 사업비 (백만원) is highly overall correlated with 결정 면적 (제곱미터) and 3 other fieldsHigh correlation
향후 사업비 (백만원) is highly overall correlated with 결정 면적 (제곱미터) and 3 other fieldsHigh correlation
구분 has unique valuesUnique
시설명 has unique valuesUnique
결정 면적 (제곱미터) has unique valuesUnique
미집행 면적 (제곱미터) has unique valuesUnique
총 사업비 (백만원) has unique valuesUnique
향후 사업비 (백만원) has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:27:23.651595
Analysis finished2024-01-28 17:27:26.574162
Duration2.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:27:26.631425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-01-29T02:27:26.737900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

군구명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
부평구
14 
서구
4 
연수구
2 
남동구
2 
계양구
 
1

Length

Max length3
Median length3
Mean length2.7916667
Min length2

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row서구
2nd row부평구
3rd row부평구
4th row부평구
5th row부평구

Common Values

ValueCountFrequency (%)
부평구 14
58.3%
서구 4
 
16.7%
연수구 2
 
8.3%
남동구 2
 
8.3%
계양구 1
 
4.2%
중구 1
 
4.2%

Length

2024-01-29T02:27:26.836626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:26.925282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 14
58.3%
서구 4
 
16.7%
연수구 2
 
8.3%
남동구 2
 
8.3%
계양구 1
 
4.2%
중구 1
 
4.2%

시설 구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
공간시설
11 
공공문화 체육시설
7 
교통시설
5 
자동차 정류장
 
1

Length

Max length9
Median length4
Mean length5.5833333
Min length4

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
공간시설 11
45.8%
공공문화 체육시설 7
29.2%
교통시설 5
20.8%
자동차 정류장 1
 
4.2%

Length

2024-01-29T02:27:27.026253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:27.107567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공간시설 11
34.4%
공공문화 7
21.9%
체육시설 7
21.9%
교통시설 5
15.6%
자동차 1
 
3.1%
정류장 1
 
3.1%

시설의 세분
Text

Distinct12
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:27:27.232601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length3.9583333
Min length2

Characters and Unicode

Total characters95
Distinct characters40
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

Unique7 ?
Unique (%)29.2%

Sample

1st row도로
2nd row도로
3rd row도로
4th row도로
5th row도로
ValueCountFrequency (%)
도로 5
20.0%
완충녹지 5
20.0%
근린공원 3
12.0%
경관녹지 2
 
8.0%
공공청사 2
 
8.0%
여객자동차터미널 1
 
4.0%
일반광장 1
 
4.0%
문화시설 1
 
4.0%
체육시설 1
 
4.0%
도서관 1
 
4.0%
Other values (3) 3
12.0%
2024-01-29T02:27:27.475359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 8
 
8.4%
공 7
 
7.4%
녹 7
 
7.4%
도 6
 
6.3%
완 5
 
5.3%
충 5
 
5.3%
로 5
 
5.3%
설 4
 
4.2%
시 4
 
4.2%
원 3
 
3.2%
Other values (30) 41
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
98.9%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 8
 
8.5%
공 7
 
7.4%
녹 7
 
7.4%
도 6
 
6.4%
완 5
 
5.3%
충 5
 
5.3%
로 5
 
5.3%
설 4
 
4.3%
시 4
 
4.3%
원 3
 
3.2%
Other values (29) 40
42.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
98.9%
Common 1
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 8
 
8.5%
공 7
 
7.4%
녹 7
 
7.4%
도 6
 
6.4%
완 5
 
5.3%
충 5
 
5.3%
로 5
 
5.3%
설 4
 
4.3%
시 4
 
4.3%
원 3
 
3.2%
Other values (29) 40
42.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
98.9%
ASCII 1
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 8
 
8.5%
공 7
 
7.4%
녹 7
 
7.4%
도 6
 
6.4%
완 5
 
5.3%
충 5
 
5.3%
로 5
 
5.3%
설 4
 
4.3%
시 4
 
4.3%
원 3
 
3.2%
Other values (29) 40
42.6%
ASCII
ValueCountFrequency (%)
1
100.0%

시설명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:27:27.635390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.4166667
Min length3

Characters and Unicode

Total characters154
Distinct characters67
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row대로3-114
2nd row중로1-377
3rd row중로3-411
4th row중로3-412
5th row중로3-413
ValueCountFrequency (%)
대로3-114 1
 
3.4%
검단2’녹지 1
 
3.4%
청소년 1
 
3.4%
복지시설 1
 
3.4%
사회 1
 
3.4%
도서관 1
 
3.4%
체육시설 1
 
3.4%
문화시설 1
 
3.4%
경찰서 1
 
3.4%
소방서 1
 
3.4%
Other values (19) 19
65.5%
2024-01-29T02:27:27.882186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 11
 
7.1%
1 11
 
7.1%
녹 7
 
4.5%
3 7
 
4.5%
로 5
 
3.2%
시 5
 
3.2%
5
 
3.2%
- 5
 
3.2%
설 4
 
2.6%
중 4
 
2.6%
Other values (57) 90
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
72.1%
Decimal Number 26
 
16.9%
Space Separator 5
 
3.2%
Dash Punctuation 5
 
3.2%
Final Punctuation 3
 
1.9%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 11
 
9.9%
녹 7
 
6.3%
로 5
 
4.5%
시 5
 
4.5%
설 4
 
3.6%
중 4
 
3.6%
원 4
 
3.6%
공 4
 
3.6%
서 3
 
2.7%
단 3
 
2.7%
Other values (47) 61
55.0%
Decimal Number
ValueCountFrequency (%)
1 11
42.3%
3 7
26.9%
4 4
 
15.4%
2 2
 
7.7%
7 2
 
7.7%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
72.1%
Common 43
 
27.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 11
 
9.9%
녹 7
 
6.3%
로 5
 
4.5%
시 5
 
4.5%
설 4
 
3.6%
중 4
 
3.6%
원 4
 
3.6%
공 4
 
3.6%
서 3
 
2.7%
단 3
 
2.7%
Other values (47) 61
55.0%
Common
ValueCountFrequency (%)
1 11
25.6%
3 7
16.3%
5
11.6%
- 5
11.6%
4 4
 
9.3%
’ 3
 
7.0%
( 2
 
4.7%
) 2
 
4.7%
2 2
 
4.7%
7 2
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
72.1%
ASCII 40
 
26.0%
Punctuation 3
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 11
 
9.9%
녹 7
 
6.3%
로 5
 
4.5%
시 5
 
4.5%
설 4
 
3.6%
중 4
 
3.6%
원 4
 
3.6%
공 4
 
3.6%
서 3
 
2.7%
단 3
 
2.7%
Other values (47) 61
55.0%
ASCII
ValueCountFrequency (%)
1 11
27.5%
3 7
17.5%
5
12.5%
- 5
12.5%
4 4
 
10.0%
( 2
 
5.0%
) 2
 
5.0%
2 2
 
5.0%
7 2
 
5.0%
Punctuation
ValueCountFrequency (%)
’ 3
100.0%

위치
Text

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:27:28.036859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length15.25
Min length13

Characters and Unicode

Total characters366
Distinct characters41
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

Unique20 ?
Unique (%)83.3%

Sample

1st row서구 오류동 1537 일원
2nd row부평구 산곡동 292-1 일원
3rd row부평구 산곡동 산20-8 일원
4th row부평구 산곡동 산20-7 일원
5th row부평구 산곡동 292-1 일원
ValueCountFrequency (%)
일원 20
21.7%
부평구 14
15.2%
산곡동 12
13.0%
서구 4
 
4.3%
292-1 3
 
3.3%
왕길동 3
 
3.3%
산20-8 3
 
3.3%
연수구 2
 
2.2%
동춘동 2
 
2.2%
남동구 2
 
2.2%
Other values (27) 27
29.3%
2024-01-29T02:27:28.299997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
18.6%
동 28
 
7.7%
구 24
 
6.6%
- 22
 
6.0%
산 20
 
5.5%
2 20
 
5.5%
일 20
 
5.5%
원 20
 
5.5%
1 16
 
4.4%
부 15
 
4.1%
Other values (31) 113
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
51.1%
Decimal Number 89
24.3%
Space Separator 68
 
18.6%
Dash Punctuation 22
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
15.0%
구 24
12.8%
산 20
10.7%
일 20
10.7%
원 20
10.7%
부 15
8.0%
평 15
8.0%
곡 12
6.4%
서 4
 
2.1%
수 3
 
1.6%
Other values (19) 26
13.9%
Decimal Number
ValueCountFrequency (%)
2 20
22.5%
1 16
18.0%
9 13
14.6%
7 8
 
9.0%
6 7
 
7.9%
0 6
 
6.7%
3 6
 
6.7%
5 5
 
5.6%
4 4
 
4.5%
8 4
 
4.5%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
51.1%
Common 179
48.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
15.0%
구 24
12.8%
산 20
10.7%
일 20
10.7%
원 20
10.7%
부 15
8.0%
평 15
8.0%
곡 12
6.4%
서 4
 
2.1%
수 3
 
1.6%
Other values (19) 26
13.9%
Common
ValueCountFrequency (%)
68
38.0%
- 22
 
12.3%
2 20
 
11.2%
1 16
 
8.9%
9 13
 
7.3%
7 8
 
4.5%
6 7
 
3.9%
0 6
 
3.4%
3 6
 
3.4%
5 5
 
2.8%
Other values (2) 8
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
51.1%
ASCII 179
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
38.0%
- 22
 
12.3%
2 20
 
11.2%
1 16
 
8.9%
9 13
 
7.3%
7 8
 
4.5%
6 7
 
3.9%
0 6
 
3.4%
3 6
 
3.4%
5 5
 
2.8%
Other values (2) 8
 
4.5%
Hangul
ValueCountFrequency (%)
동 28
15.0%
구 24
12.8%
산 20
10.7%
일 20
10.7%
원 20
10.7%
부 15
8.0%
평 15
8.0%
곡 12
6.4%
서 4
 
2.1%
수 3
 
1.6%
Other values (19) 26
13.9%

결정 면적 (제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29418.304
Minimum642
Maximum431503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:27:28.397366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum642
5-th percentile980.15
Q14383.325
median8138
Q317990
95-th percentile57396.1
Maximum431503
Range430861
Interquartile range (IQR)13606.675

Descriptive statistics

Standard deviation86594.069
Coefficient of variation (CV)2.9435439
Kurtosis22.820071
Mean29418.304
Median Absolute Deviation (MAD)6324
Skewness4.7345764
Sum706039.3
Variance7.4985328 × 109
MonotonicityNot monotonic
2024-01-29T02:27:28.481421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
63256.0 1
 
4.2%
14747.0 1
 
4.2%
14950.0 1
 
4.2%
5250.0 1
 
4.2%
8050.0 1
 
4.2%
18050.0 1
 
4.2%
17970.0 1
 
4.2%
18540.0 1
 
4.2%
24190.0 1
 
4.2%
6890.0 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
642.0 1
4.2%
944.0 1
4.2%
1185.0 1
4.2%
2099.0 1
4.2%
3384.0 1
4.2%
4210.3 1
4.2%
4441.0 1
4.2%
5250.0 1
4.2%
6539.0 1
4.2%
6890.0 1
4.2%
ValueCountFrequency (%)
431503.0 1
4.2%
63256.0 1
4.2%
24190.0 1
4.2%
18700.0 1
4.2%
18540.0 1
4.2%
18050.0 1
4.2%
17970.0 1
4.2%
14950.0 1
4.2%
14747.0 1
4.2%
13733.0 1
4.2%

미집행 면적 (제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26180.388
Minimum165
Maximum388144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:27:28.584962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165
5-th percentile687.3
Q14383.325
median8138
Q317990
95-th percentile29064.75
Maximum388144
Range387979
Interquartile range (IQR)13606.675

Descriptive statistics

Standard deviation77499.106
Coefficient of variation (CV)2.960197
Kurtosis23.439258
Mean26180.388
Median Absolute Deviation (MAD)6324
Skewness4.817204
Sum628329.3
Variance6.0061114 × 109
MonotonicityNot monotonic
2024-01-29T02:27:28.685877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
29925.0 1
 
4.2%
14747.0 1
 
4.2%
14950.0 1
 
4.2%
5250.0 1
 
4.2%
8050.0 1
 
4.2%
18050.0 1
 
4.2%
17970.0 1
 
4.2%
18540.0 1
 
4.2%
24190.0 1
 
4.2%
6890.0 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
165.0 1
4.2%
642.0 1
4.2%
944.0 1
4.2%
2099.0 1
4.2%
3384.0 1
4.2%
4210.3 1
4.2%
4441.0 1
4.2%
5250.0 1
4.2%
6539.0 1
4.2%
6890.0 1
4.2%
ValueCountFrequency (%)
388144.0 1
4.2%
29925.0 1
4.2%
24190.0 1
4.2%
18700.0 1
4.2%
18540.0 1
4.2%
18050.0 1
4.2%
17970.0 1
4.2%
14950.0 1
4.2%
14747.0 1
4.2%
13733.0 1
4.2%

총 사업비 (백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14390.917
Minimum24
Maximum110000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:27:28.800123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile199.7
Q11011
median7792
Q314727
95-th percentile44919
Maximum110000
Range109976
Interquartile range (IQR)13716

Descriptive statistics

Standard deviation23736.971
Coefficient of variation (CV)1.6494412
Kurtosis11.753614
Mean14390.917
Median Absolute Deviation (MAD)6802
Skewness3.1871504
Sum345382
Variance5.6344378 × 108
MonotonicityNot monotonic
2024-01-29T02:27:28.911256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
22952 1
 
4.2%
14248 1
 
4.2%
1032 1
 
4.2%
735 1
 
4.2%
555 1
 
4.2%
5131 1
 
4.2%
1240 1
 
4.2%
41587 1
 
4.2%
45507 1
 
4.2%
11979 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
24 1
4.2%
137 1
4.2%
555 1
4.2%
660 1
4.2%
735 1
4.2%
948 1
4.2%
1032 1
4.2%
1050 1
4.2%
1240 1
4.2%
2958 1
4.2%
ValueCountFrequency (%)
110000 1
4.2%
45507 1
4.2%
41587 1
4.2%
22952 1
4.2%
17400 1
4.2%
16164 1
4.2%
14248 1
4.2%
13500 1
4.2%
11979 1
4.2%
11391 1
4.2%

향후 사업비 (백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14390.917
Minimum24
Maximum110000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:27:29.008952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile199.7
Q11011
median7792
Q314727
95-th percentile44919
Maximum110000
Range109976
Interquartile range (IQR)13716

Descriptive statistics

Standard deviation23736.971
Coefficient of variation (CV)1.6494412
Kurtosis11.753614
Mean14390.917
Median Absolute Deviation (MAD)6802
Skewness3.1871504
Sum345382
Variance5.6344378 × 108
MonotonicityNot monotonic
2024-01-29T02:27:29.092902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
22952 1
 
4.2%
14248 1
 
4.2%
1032 1
 
4.2%
735 1
 
4.2%
555 1
 
4.2%
5131 1
 
4.2%
1240 1
 
4.2%
41587 1
 
4.2%
45507 1
 
4.2%
11979 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
24 1
4.2%
137 1
4.2%
555 1
4.2%
660 1
4.2%
735 1
4.2%
948 1
4.2%
1032 1
4.2%
1050 1
4.2%
1240 1
4.2%
2958 1
4.2%
ValueCountFrequency (%)
110000 1
4.2%
45507 1
4.2%
41587 1
4.2%
22952 1
4.2%
17400 1
4.2%
16164 1
4.2%
14248 1
4.2%
13500 1
4.2%
11979 1
4.2%
11391 1
4.2%

단계 구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2-2단계
12 
2-1단계
6 
2-1단계 2-2단계
2 
1단계 2-1단계 2-2단계
2 
1단계 2-1단계
 
1

Length

Max length15
Median length5
Mean length6.4583333
Min length4

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row2-1단계 2-2단계
2nd row2-2단계
3rd row2-2단계
4th row2-2단계
5th row2-2단계

Common Values

ValueCountFrequency (%)
2-2단계 12
50.0%
2-1단계 6
25.0%
2-1단계 2-2단계 2
 
8.3%
1단계 2-1단계 2-2단계 2
 
8.3%
1단계 2-1단계 1
 
4.2%
비재정적 1
 
4.2%

Length

2024-01-29T02:27:29.186579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:29.274588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2-2단계 16
51.6%
2-1단계 11
35.5%
1단계 3
 
9.7%
비재정적 1
 
3.2%

최초 결정일
Date

Distinct9
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2006-06-05 00:00:00
Maximum2010-10-04 00:00:00
2024-01-29T02:27:29.353070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:29.429988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

실효 시기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2029
14 
2027
5 
2026
4 
2030
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row2027
2nd row2029
3rd row2029
4th row2029
5th row2029

Common Values

ValueCountFrequency (%)
2029 14
58.3%
2027 5
 
20.8%
2026 4
 
16.7%
2030 1
 
4.2%

Length

2024-01-29T02:27:29.525709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:29.602904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2029 14
58.3%
2027 5
 
20.8%
2026 4
 
16.7%
2030 1
 
4.2%

관리 방안
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
존치
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
존치 24
100.0%

Length

2024-01-29T02:27:29.684440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:29.752433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
존치 24
100.0%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
12 
(부평미군부대)
12 

Length

Max length8
Median length6
Mean length6
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row(부평미군부대)
3rd row(부평미군부대)
4th row(부평미군부대)
5th row(부평미군부대)

Common Values

ValueCountFrequency (%)
<NA> 12
50.0%
(부평미군부대) 12
50.0%

Length

2024-01-29T02:27:29.831206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:27:29.912396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
50.0%
부평미군부대 12
50.0%

Interactions

2024-01-29T02:27:25.990824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.250411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.686994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.278730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.656232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:26.061978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.324611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.757715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.345492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.716366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:26.140265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.405301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.825610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.407615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.776802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:26.214880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.502262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.901688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.497353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.853108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:26.277977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:24.613999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.209242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.579909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:27:25.922352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:27:29.979984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분군구명시설 구분시설의 세분시설명위치결정 면적 (제곱미터)미집행 면적 (제곱미터)총 사업비 (백만원)향후 사업비 (백만원)단계 구분최초 결정일실효 시기
구분1.0000.5110.9330.8391.0000.8790.0000.0000.5960.5960.7350.6110.581
군구명0.5111.0000.5310.0001.0001.0000.7250.7700.3210.3210.9220.9620.917
시설 구분0.9330.5311.0001.0001.0000.9050.0000.0000.3690.3690.7250.8230.930
시설의 세분0.8390.0001.0001.0001.0000.9540.0000.0000.0000.0000.6840.0000.949
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치0.8791.0000.9050.9541.0001.0001.0001.0001.0001.0001.0001.0001.000
결정 면적 (제곱미터)0.0000.7250.0000.0001.0001.0001.0001.0001.0001.0000.8711.0000.000
미집행 면적 (제곱미터)0.0000.7700.0000.0001.0001.0001.0001.0001.0001.0000.7701.0000.000
총 사업비 (백만원)0.5960.3210.3690.0001.0001.0001.0001.0001.0001.0000.6850.8030.000
향후 사업비 (백만원)0.5960.3210.3690.0001.0001.0001.0001.0001.0001.0000.6850.8030.000
단계 구분0.7350.9220.7250.6841.0001.0000.8710.7700.6850.6851.0001.0000.825
최초 결정일0.6110.9620.8230.0001.0001.0001.0001.0000.8030.8031.0001.0001.000
실효 시기0.5810.9170.9300.9491.0001.0000.0000.0000.0000.0000.8251.0001.000
2024-01-29T02:27:30.123516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실효 시기비고시설 구분단계 구분군구명
실효 시기1.0001.0000.6460.6410.762
비고1.0001.0001.0001.0001.000
시설 구분0.6461.0001.0000.5230.338
단계 구분0.6411.0000.5231.0000.593
군구명0.7621.0000.3380.5931.000
2024-01-29T02:27:30.451132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분결정 면적 (제곱미터)미집행 면적 (제곱미터)총 사업비 (백만원)향후 사업비 (백만원)군구명시설 구분단계 구분실효 시기비고
구분1.0000.2260.237-0.099-0.0990.2250.7010.4260.2991.000
결정 면적 (제곱미터)0.2261.0000.9970.6760.6760.3760.0000.5340.0001.000
미집행 면적 (제곱미터)0.2370.9971.0000.6790.6790.5220.0000.5220.0001.000
총 사업비 (백만원)-0.0990.6760.6791.0001.0000.0570.2110.2900.0001.000
향후 사업비 (백만원)-0.0990.6760.6791.0001.0000.0570.2110.2900.0001.000
군구명0.2250.3760.5220.0570.0571.0000.3380.5930.7621.000
시설 구분0.7010.0000.0000.2110.2110.3381.0000.5230.6461.000
단계 구분0.4260.5340.5220.2900.2900.5930.5231.0000.6411.000
실효 시기0.2990.0000.0000.0000.0000.7620.6460.6411.0001.000
비고1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-01-29T02:27:26.369030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:27:26.515821image/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

구분군구명시설 구분시설의 세분시설명위치결정 면적 (제곱미터)미집행 면적 (제곱미터)총 사업비 (백만원)향후 사업비 (백만원)단계 구분최초 결정일실효 시기관리 방안비고
01서구교통시설도로대로3-114서구 오류동 1537 일원63256.029925.022952229522-1단계 2-2단계2007-07-302027존치<NA>
12부평구교통시설도로중로1-377부평구 산곡동 292-1 일원4441.04441.0295829582-2단계2009-02-232029존치(부평미군부대)
23부평구교통시설도로중로3-411부평구 산곡동 산20-8 일원6539.06539.09489482-2단계2009-02-232029존치(부평미군부대)
34부평구교통시설도로중로3-412부평구 산곡동 산20-7 일원1185.0165.024242-2단계2009-02-232029존치(부평미군부대)
45부평구교통시설도로중로3-413부평구 산곡동 292-1 일원944.0944.01371372-2단계2009-02-232029존치(부평미군부대)
56연수구자동차 정류장여객자동차터미널동춘시내 버스터미널연수구 동춘동 913-17603.07603.013500135002-1단계 2-2단계2010-10-042030존치<NA>
67부평구공간시설근린공원산울림공원부평구 십정동 64-3 일원13733.013733.017400174001단계 2-1단계2006-07-182026존치<NA>
78연수구공간시설근린공원동춘공원연수구 동춘동 산59-1 일원431503.0388144.01100001100001단계 2-1단계 2-2단계2009-05-042029존치<NA>
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