Overview

Dataset statistics

Number of variables12
Number of observations35
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory102.8 B

Variable types

Numeric3
Categorical3
Text3
DateTime3

Dataset

Description광주광역시 내 사용종료된 비위생매립지 현황입니다. 위치(소재지지번주소), 매립기간, 면적, 매립량, 토지이용실태 등의 내용을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15056450/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
비고(현지번) is highly overall correlated with 면적(천제곱미터) and 3 other fieldsHigh correlation
연번 is highly overall correlated with 구분High correlation
면적(천제곱미터) is highly overall correlated with 매립량(천톤) and 2 other fieldsHigh correlation
매립량(천톤) is highly overall correlated with 면적(천제곱미터) and 3 other fieldsHigh correlation
관리기관 is highly overall correlated with 면적(천제곱미터) and 3 other fieldsHigh correlation
구분 is highly imbalanced (57.8%)Imbalance
토지이용실태 has 1 (2.9%) missing valuesMissing
연번 has unique valuesUnique
매립장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-23 08:10:57.869512
Analysis finished2023-12-23 08:11:01.701714
Duration3.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-23T08:11:01.877132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2023-12-23T08:11:02.317804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
27 1
 
2.9%
28 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
사후관리종료대상
32 
사후관리대상
 
3

Length

Max length8
Median length8
Mean length7.8285714
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사후관리대상
2nd row사후관리대상
3rd row사후관리대상
4th row사후관리종료대상
5th row사후관리종료대상

Common Values

ValueCountFrequency (%)
사후관리종료대상 32
91.4%
사후관리대상 3
 
8.6%

Length

2023-12-23T08:11:03.117218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T08:11:03.432698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사후관리종료대상 32
91.4%
사후관리대상 3
 
8.6%

관리기관
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
광주광역시 광산구
23 
광주광역시 북구
9 
광주광역시 남구
 
2
광주광역시 서구
 
1

Length

Max length9
Median length9
Mean length8.6571429
Min length8

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row광주광역시 서구
2nd row광주광역시 북구
3rd row광주광역시 북구
4th row광주광역시 남구
5th row광주광역시 남구

Common Values

ValueCountFrequency (%)
광주광역시 광산구 23
65.7%
광주광역시 북구 9
 
25.7%
광주광역시 남구 2
 
5.7%
광주광역시 서구 1
 
2.9%

Length

2023-12-23T08:11:03.761486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T08:11:04.066358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 35
50.0%
광산구 23
32.9%
북구 9
 
12.9%
남구 2
 
2.9%
서구 1
 
1.4%

매립장명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-23T08:11:04.508232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8285714
Min length2

Characters and Unicode

Total characters99
Distinct characters32
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row풍암
2nd row일곡4
3rd row일곡5
4th row유안
5th row봉선
ValueCountFrequency (%)
산월 2
 
5.6%
연산2 1
 
2.8%
유곡1 1
 
2.8%
장덕2 1
 
2.8%
하남1 1
 
2.8%
하남2 1
 
2.8%
하남3 1
 
2.8%
하남4 1
 
2.8%
풍암 1
 
2.8%
오룡 1
 
2.8%
Other values (25) 25
69.4%
2023-12-23T08:11:05.149248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
곡 16
16.2%
유 9
 
9.1%
일 8
 
8.1%
산 7
 
7.1%
1 6
 
6.1%
2 6
 
6.1%
남 4
 
4.0%
하 4
 
4.0%
4 3
 
3.0%
3 3
 
3.0%
Other values (22) 33
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
72.7%
Decimal Number 26
 
26.3%
Space Separator 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
곡 16
22.2%
유 9
12.5%
일 8
11.1%
산 7
9.7%
남 4
 
5.6%
하 4
 
5.6%
선 2
 
2.8%
덕 2
 
2.8%
장 2
 
2.8%
동 2
 
2.8%
Other values (13) 16
22.2%
Decimal Number
ValueCountFrequency (%)
1 6
23.1%
2 6
23.1%
4 3
11.5%
3 3
11.5%
5 2
 
7.7%
6 2
 
7.7%
8 2
 
7.7%
7 2
 
7.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
72.7%
Common 27
 
27.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
곡 16
22.2%
유 9
12.5%
일 8
11.1%
산 7
9.7%
남 4
 
5.6%
하 4
 
5.6%
선 2
 
2.8%
덕 2
 
2.8%
장 2
 
2.8%
동 2
 
2.8%
Other values (13) 16
22.2%
Common
ValueCountFrequency (%)
1 6
22.2%
2 6
22.2%
4 3
11.1%
3 3
11.1%
5 2
 
7.4%
6 2
 
7.4%
8 2
 
7.4%
7 2
 
7.4%
1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
72.7%
ASCII 27
 
27.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
곡 16
22.2%
유 9
12.5%
일 8
11.1%
산 7
9.7%
남 4
 
5.6%
하 4
 
5.6%
선 2
 
2.8%
덕 2
 
2.8%
장 2
 
2.8%
동 2
 
2.8%
Other values (13) 16
22.2%
ASCII
ValueCountFrequency (%)
1 6
22.2%
2 6
22.2%
4 3
11.1%
3 3
11.1%
5 2
 
7.4%
6 2
 
7.4%
8 2
 
7.4%
7 2
 
7.4%
1
 
3.7%

소재지지번주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-23T08:11:05.584743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length17.971429
Min length14

Characters and Unicode

Total characters629
Distinct characters49
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

Unique35 ?
Unique (%)100.0%

Sample

1st row광주광역시 서구 풍암동 34
2nd row광주광역시 북구 일곡동 26
3rd row광주광역시 북구 일곡동 24
4th row광주광역시 남구 봉선동 130
5th row광주광역시 남구 봉선동 116
ValueCountFrequency (%)
광주광역시 27
18.4%
광산구 13
 
8.8%
북구 11
 
7.5%
전라남도 8
 
5.4%
나주시 8
 
5.4%
일곡동 8
 
5.4%
노안면 8
 
5.4%
유곡리 8
 
5.4%
하남동 4
 
2.7%
동산동 2
 
1.4%
Other values (46) 50
34.0%
2023-12-23T08:11:06.183623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
18.0%
광 67
 
10.7%
시 35
 
5.6%
주 35
 
5.6%
동 30
 
4.8%
역 27
 
4.3%
구 27
 
4.3%
1 22
 
3.5%
산 21
 
3.3%
곡 16
 
2.5%
Other values (39) 236
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 391
62.2%
Space Separator 113
 
18.0%
Decimal Number 111
 
17.6%
Dash Punctuation 13
 
2.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 67
17.1%
시 35
 
9.0%
주 35
 
9.0%
동 30
 
7.7%
역 27
 
6.9%
구 27
 
6.9%
산 21
 
5.4%
곡 16
 
4.1%
남 14
 
3.6%
북 11
 
2.8%
Other values (26) 108
27.6%
Decimal Number
ValueCountFrequency (%)
1 22
19.8%
3 16
14.4%
4 15
13.5%
6 11
9.9%
0 11
9.9%
2 10
9.0%
9 8
 
7.2%
8 7
 
6.3%
5 7
 
6.3%
7 4
 
3.6%
Space Separator
ValueCountFrequency (%)
113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 391
62.2%
Common 238
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 67
17.1%
시 35
 
9.0%
주 35
 
9.0%
동 30
 
7.7%
역 27
 
6.9%
구 27
 
6.9%
산 21
 
5.4%
곡 16
 
4.1%
남 14
 
3.6%
북 11
 
2.8%
Other values (26) 108
27.6%
Common
ValueCountFrequency (%)
113
47.5%
1 22
 
9.2%
3 16
 
6.7%
4 15
 
6.3%
- 13
 
5.5%
6 11
 
4.6%
0 11
 
4.6%
2 10
 
4.2%
9 8
 
3.4%
8 7
 
2.9%
Other values (3) 12
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 391
62.2%
ASCII 238
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
47.5%
1 22
 
9.2%
3 16
 
6.7%
4 15
 
6.3%
- 13
 
5.5%
6 11
 
4.6%
0 11
 
4.6%
2 10
 
4.2%
9 8
 
3.4%
8 7
 
2.9%
Other values (3) 12
 
5.0%
Hangul
ValueCountFrequency (%)
광 67
17.1%
시 35
 
9.0%
주 35
 
9.0%
동 30
 
7.7%
역 27
 
6.9%
구 27
 
6.9%
산 21
 
5.4%
곡 16
 
4.1%
남 14
 
3.6%
북 11
 
2.8%
Other values (26) 108
27.6%

매립기간(시작)
Date

Distinct27
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum1986-10-01 00:00:00
Maximum1994-01-01 00:00:00
2023-12-23T08:11:06.434676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:11:06.809873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

매립기간(종료)
Date

Distinct24
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum1986-12-01 00:00:00
Maximum1994-12-01 00:00:00
2023-12-23T08:11:07.144704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:11:07.554459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

면적(천제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.897143
Minimum-53.7
Maximum82.6
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)2.9%
Memory size447.0 B
2023-12-23T08:11:07.900547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-53.7
5-th percentile1.21
Q13.35
median6
Q315.5
95-th percentile52.2
Maximum82.6
Range136.3
Interquartile range (IQR)12.15

Descriptive statistics

Standard deviation22.428153
Coefficient of variation (CV)1.7390017
Kurtosis5.1464205
Mean12.897143
Median Absolute Deviation (MAD)4.7
Skewness0.92773795
Sum451.4
Variance503.02205
MonotonicityNot monotonic
2023-12-23T08:11:08.480034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4.0 3
 
8.6%
3.0 3
 
8.6%
14.0 2
 
5.7%
5.0 2
 
5.7%
29.0 2
 
5.7%
76.0 1
 
2.9%
2.5 1
 
2.9%
6.0 1
 
2.9%
15.0 1
 
2.9%
42.0 1
 
2.9%
Other values (18) 18
51.4%
ValueCountFrequency (%)
-53.7 1
 
2.9%
1.0 1
 
2.9%
1.3 1
 
2.9%
2.0 1
 
2.9%
2.5 1
 
2.9%
2.6 1
 
2.9%
3.0 3
8.6%
3.7 1
 
2.9%
4.0 3
8.6%
4.5 1
 
2.9%
ValueCountFrequency (%)
82.6 1
2.9%
76.0 1
2.9%
42.0 1
2.9%
41.3 1
2.9%
29.0 2
5.7%
18.0 1
2.9%
17.6 1
2.9%
16.0 1
2.9%
15.0 1
2.9%
14.0 2
5.7%

매립량(천톤)
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.377143
Minimum-197
Maximum580
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)2.9%
Memory size447.0 B
2023-12-23T08:11:08.910296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-197
5-th percentile7.4
Q120
median34
Q383
95-th percentile160.16
Maximum580
Range777
Interquartile range (IQR)63

Descriptive statistics

Standard deviation109.32532
Coefficient of variation (CV)1.7249961
Kurtosis15.439556
Mean63.377143
Median Absolute Deviation (MAD)23
Skewness2.9179169
Sum2218.2
Variance11952.027
MonotonicityNot monotonic
2023-12-23T08:11:09.396530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20.0 2
 
5.7%
11.0 2
 
5.7%
580.0 1
 
2.9%
168.0 1
 
2.9%
65.0 1
 
2.9%
40.0 1
 
2.9%
32.0 1
 
2.9%
17.0 1
 
2.9%
33.0 1
 
2.9%
73.0 1
 
2.9%
Other values (23) 23
65.7%
ValueCountFrequency (%)
-197.0 1
2.9%
6.0 1
2.9%
8.0 1
2.9%
11.0 2
5.7%
13.0 1
2.9%
17.0 1
2.9%
18.0 1
2.9%
20.0 2
5.7%
26.0 1
2.9%
28.9 1
2.9%
ValueCountFrequency (%)
580.0 1
2.9%
168.0 1
2.9%
156.8 1
2.9%
151.0 1
2.9%
150.0 1
2.9%
107.0 1
2.9%
95.0 1
2.9%
90.0 1
2.9%
86.0 1
2.9%
80.0 1
2.9%

토지이용실태
Text

MISSING 

Distinct17
Distinct (%)50.0%
Missing1
Missing (%)2.9%
Memory size412.0 B
2023-12-23T08:11:09.829674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length9
Mean length5.3823529
Min length2

Characters and Unicode

Total characters183
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)29.4%

Sample

1st row생활체육공원
2nd row농경지
3rd row유안근린공원조성(’06.봉선동133-1)
4th row주차장
5th row기타(군부대)
ValueCountFrequency (%)
초지 12
34.3%
농경지 3
 
8.6%
외곽도로(진곡산단 2
 
5.7%
상가건물(수완지구 2
 
5.7%
공장부지 2
 
5.7%
공원조성(첨단 2
 
5.7%
나대지 2
 
5.7%
버스정류장 1
 
2.9%
기타(화훼단지 1
 
2.9%
기타(주유소 1
 
2.9%
Other values (7) 7
20.0%
2023-12-23T08:11:10.689792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 23
 
12.6%
초 13
 
7.1%
( 12
 
6.6%
) 12
 
6.6%
공 7
 
3.8%
단 6
 
3.3%
원 5
 
2.7%
장 4
 
2.2%
성 3
 
1.6%
구 3
 
1.6%
Other values (56) 95
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148
80.9%
Open Punctuation 12
 
6.6%
Close Punctuation 12
 
6.6%
Decimal Number 6
 
3.3%
Space Separator 2
 
1.1%
Dash Punctuation 1
 
0.5%
Other Punctuation 1
 
0.5%
Final Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 23
 
15.5%
초 13
 
8.8%
공 7
 
4.7%
단 6
 
4.1%
원 5
 
3.4%
장 4
 
2.7%
성 3
 
2.0%
구 3
 
2.0%
조 3
 
2.0%
경 3
 
2.0%
Other values (46) 78
52.7%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
3 2
33.3%
6 1
16.7%
0 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148
80.9%
Common 35
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 23
 
15.5%
초 13
 
8.8%
공 7
 
4.7%
단 6
 
4.1%
원 5
 
3.4%
장 4
 
2.7%
성 3
 
2.0%
구 3
 
2.0%
조 3
 
2.0%
경 3
 
2.0%
Other values (46) 78
52.7%
Common
ValueCountFrequency (%)
( 12
34.3%
) 12
34.3%
2
 
5.7%
1 2
 
5.7%
3 2
 
5.7%
- 1
 
2.9%
. 1
 
2.9%
6 1
 
2.9%
0 1
 
2.9%
’ 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148
80.9%
ASCII 34
 
18.6%
Punctuation 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 23
 
15.5%
초 13
 
8.8%
공 7
 
4.7%
단 6
 
4.1%
원 5
 
3.4%
장 4
 
2.7%
성 3
 
2.0%
구 3
 
2.0%
조 3
 
2.0%
경 3
 
2.0%
Other values (46) 78
52.7%
ASCII
ValueCountFrequency (%)
( 12
35.3%
) 12
35.3%
2
 
5.9%
1 2
 
5.9%
3 2
 
5.9%
- 1
 
2.9%
. 1
 
2.9%
6 1
 
2.9%
0 1
 
2.9%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

비고(현지번)
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
17 
<NA>
3 
쌍암동 695-3
2 
산59-1
2 
봉선동 134
 
1
Other values (10)
10 

Length

Max length9
Median length8
Mean length4.4571429
Min length2

Unique

Unique11 ?
Unique (%)31.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row봉선동 134
5th row

Common Values

ValueCountFrequency (%)
17
48.6%
<NA> 3
 
8.6%
쌍암동 695-3 2
 
5.7%
산59-1 2
 
5.7%
봉선동 134 1
 
2.9%
일곡동 1-1 1
 
2.9%
일곡동 40-1 1
 
2.9%
일곡동 산 22 1
 
2.9%
일곡동 51-9 1
 
2.9%
일곡동 5-1 1
 
2.9%
Other values (5) 5
 
14.3%

Length

2023-12-23T08:11:11.168342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일곡동 6
18.8%
na 3
 
9.4%
695-3 2
 
6.2%
산59-1 2
 
6.2%
장덕동 2
 
6.2%
동산동 2
 
6.2%
쌍암동 2
 
6.2%
5-1 1
 
3.1%
1650 1
 
3.1%
61-1 1
 
3.1%
Other values (10) 10
31.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2023-12-06 00:00:00
Maximum2023-12-06 00:00:00
2023-12-23T08:11:11.516733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:11:11.922153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-23T08:10:59.997726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:58.817903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:59.393478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:11:00.210795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:59.064395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:59.554461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:11:00.479171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:59.223874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:10:59.782822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T08:11:12.175550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분관리기관매립장명소재지지번주소매립기간(시작)매립기간(종료)면적(천제곱미터)매립량(천톤)토지이용실태비고(현지번)
연번1.0000.9410.6641.0001.0000.1680.0000.4540.5710.8150.771
구분0.9411.0000.8221.0001.0000.2720.0000.3420.7841.000NaN
관리기관0.6640.8221.0001.0001.0000.9060.0000.7160.9050.9880.803
매립장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
매립기간(시작)0.1680.2720.9061.0001.0001.0000.9020.9420.9230.8250.000
매립기간(종료)0.0000.0000.0001.0001.0000.9021.0000.7890.0000.5020.903
면적(천제곱미터)0.4540.3420.7161.0001.0000.9420.7891.0000.7670.8880.903
매립량(천톤)0.5710.7840.9051.0001.0000.9230.0000.7671.0000.9230.741
토지이용실태0.8151.0000.9881.0001.0000.8250.5020.8880.9231.0000.891
비고(현지번)0.771NaN0.8031.0001.0000.0000.9030.9030.7410.8911.000
2023-12-23T08:11:12.458332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분관리기관비고(현지번)
구분1.0000.5961.000
관리기관0.5961.0000.506
비고(현지번)1.0000.5061.000
2023-12-23T08:11:12.617950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(천제곱미터)매립량(천톤)구분관리기관비고(현지번)
연번1.000-0.407-0.2410.6900.4100.386
면적(천제곱미터)-0.4071.0000.7640.2220.5280.604
매립량(천톤)-0.2410.7641.0000.5320.7000.584
구분0.6900.2220.5321.0000.5961.000
관리기관0.4100.5280.7000.5961.0000.506
비고(현지번)0.3860.6040.5841.0000.5061.000

Missing values

2023-12-23T08:11:00.913946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T08:11:01.493186image/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

연번구분관리기관매립장명소재지지번주소매립기간(시작)매립기간(종료)면적(천제곱미터)매립량(천톤)토지이용실태비고(현지번)데이터기준일자
01사후관리대상광주광역시 서구풍암광주광역시 서구 풍암동 341991-06-011994-12-0176.0580.0생활체육공원<NA>2023-12-06
12사후관리대상광주광역시 북구일곡4광주광역시 북구 일곡동 261992-01-011992-07-0118.0107.0농경지<NA>2023-12-06
23사후관리대상광주광역시 북구일곡5광주광역시 북구 일곡동 241992-07-011992-12-0114.086.0<NA><NA>2023-12-06
34사후관리종료대상광주광역시 남구유안광주광역시 남구 봉선동 1301989-10-011991-06-01-53.7-197.0유안근린공원조성(’06.봉선동133-1)봉선동 1342023-12-06
45사후관리종료대상광주광역시 남구봉선광주광역시 남구 봉선동 1161988-07-011988-10-0110.846.0주차장2023-12-06
56사후관리종료대상광주광역시 북구일곡1광주광역시 북구 일곡동 481988-10-011993-10-0182.620.0기타(군부대)일곡동 1-12023-12-06
67사후관리종료대상광주광역시 북구용강광주광역시 북구 용강동 234-11989-05-011989-07-0113.261.3농경지2023-12-06
78사후관리종료대상광주광역시 북구일곡2광주광역시 북구 일곡동 401989-01-011989-04-0117.653.7기타(화훼단지)일곡동 40-12023-12-06
89사후관리종료대상광주광역시 북구일곡7광주광역시 북구 일곡동 91993-09-011993-01-017.228.9농경지일곡동 산 222023-12-06
910사후관리종료대상광주광역시 북구일곡3광주광역시 북구 일곡동 48-11991-07-011991-11-0114.090.0기타(주유소)일곡동 51-92023-12-06
연번구분관리기관매립장명소재지지번주소매립기간(시작)매립기간(종료)면적(천제곱미터)매립량(천톤)토지이용실태비고(현지번)데이터기준일자
2526사후관리종료대상광주광역시 광산구산월광주광역시 북구 산월동 819-21989-08-011990-03-0142.0168.0공원조성(첨단)쌍암동 695-32023-12-06
2627사후관리종료대상광주광역시 광산구오룡 산월광주광역시 북구 오룡동 401, 산월동 819-41990-11-011991-06-0129.0150.0공원조성(첨단)쌍암동 695-32023-12-06
2728사후관리종료대상광주광역시 광산구유곡1전라남도 나주시 노안면 유곡리 산551990-02-011990-12-0115.073.0초지2023-12-06
2829사후관리종료대상광주광역시 광산구유곡2전라남도 나주시 노안면 유곡리 591991-01-011991-12-013.011.0초지산59-12023-12-06
2930사후관리종료대상광주광역시 광산구유곡3전라남도 나주시 노안면 유곡리 6331992-05-011992-07-014.020.0초지2023-12-06
3031사후관리종료대상광주광역시 광산구유곡4전라남도 나주시 노안면 유곡리 57-11992-08-011992-12-014.034.0초지산59-12023-12-06
3132사후관리종료대상광주광역시 광산구유곡5전라남도 나주시 노안면 유곡리 6391993-03-011993-06-014.011.0초지2023-12-06
3233사후관리종료대상광주광역시 광산구유곡6전라남도 나주시 노안면 유곡리 6301993-06-011993-08-013.013.0초지2023-12-06
3334사후관리종료대상광주광역시 광산구유곡7전라남도 나주시 노안면 유곡리 6351993-08-011993-12-015.030.0초지2023-12-06
3435사후관리종료대상광주광역시 광산구유곡8전라남도 나주시 노안면 유곡리 636-11994-01-011994-12-016.080.0초지2023-12-06