Overview

Dataset statistics

Number of variables9
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory77.3 B

Variable types

Numeric3
Categorical1
Text3
DateTime2

Dataset

Description광주광역시 광산구 내 폐기물 재활용 업체 현황(업종, 업소명, 도로명주소, 폐기물종류 등)에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15055958/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
업종 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:50:07.159940
Analysis finished2023-12-12 13:50:08.891337
Duration1.73 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T22:50:08.974119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2023-12-12T22:50:09.139739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

업종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
종합재활용업
29 
중간재활용업
28 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종합재활용업 29
50.9%
중간재활용업 28
49.1%

Length

2023-12-12T22:50:09.303515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:09.413024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합재활용업 29
50.9%
중간재활용업 28
49.1%

사업장명
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T22:50:09.698403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.1929825
Min length3

Characters and Unicode

Total characters353
Distinct characters131
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)96.5%

Sample

1st row한국전선가공
2nd row한영기업
3rd row㈜반도기연
4th row신흥자원㈜
5th row솔라뱅크(유)
ValueCountFrequency (%)
㈜성신 2
 
3.2%
광주지점 2
 
3.2%
㈜크린환경산업 1
 
1.6%
서일화성 1
 
1.6%
㈜고속에너지 1
 
1.6%
㈜조선우드 1
 
1.6%
㈜정우화학 1
 
1.6%
㈜한국스치로폴 1
 
1.6%
유)초지 1
 
1.6%
정오자원 1
 
1.6%
Other values (50) 50
80.6%
2023-12-12T22:50:10.156840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 29
 
8.2%
업 13
 
3.7%
산 10
 
2.8%
대 9
 
2.5%
지 8
 
2.3%
) 8
 
2.3%
( 8
 
2.3%
원 8
 
2.3%
에 8
 
2.3%
광 7
 
2.0%
Other values (121) 245
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
85.0%
Other Symbol 29
 
8.2%
Close Punctuation 8
 
2.3%
Open Punctuation 8
 
2.3%
Space Separator 5
 
1.4%
Uppercase Letter 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 13
 
4.3%
산 10
 
3.3%
대 9
 
3.0%
지 8
 
2.7%
원 8
 
2.7%
에 8
 
2.7%
광 7
 
2.3%
주 7
 
2.3%
스 7
 
2.3%
자 7
 
2.3%
Other values (114) 216
72.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 329
93.2%
Common 22
 
6.2%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 29
 
8.8%
업 13
 
4.0%
산 10
 
3.0%
대 9
 
2.7%
지 8
 
2.4%
원 8
 
2.4%
에 8
 
2.4%
광 7
 
2.1%
주 7
 
2.1%
스 7
 
2.1%
Other values (115) 223
67.8%
Common
ValueCountFrequency (%)
) 8
36.4%
( 8
36.4%
5
22.7%
& 1
 
4.5%
Latin
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
85.0%
None 29
 
8.2%
ASCII 24
 
6.8%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 29
100.0%
Hangul
ValueCountFrequency (%)
업 13
 
4.3%
산 10
 
3.3%
대 9
 
3.0%
지 8
 
2.7%
원 8
 
2.7%
에 8
 
2.7%
광 7
 
2.3%
주 7
 
2.3%
스 7
 
2.3%
자 7
 
2.3%
Other values (114) 216
72.0%
ASCII
ValueCountFrequency (%)
) 8
33.3%
( 8
33.3%
5
20.8%
P 1
 
4.2%
& 1
 
4.2%
C 1
 
4.2%

주소
Text

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T22:50:10.417939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length24.649123
Min length21

Characters and Unicode

Total characters1405
Distinct characters85
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

Unique53 ?
Unique (%)93.0%

Sample

1st row광주광역시 광산구 풍영정길 93(신창동)
2nd row광주광역시 광산구 하남산단6번로 24(오선동)
3rd row광주광역시 광산구 용아로 627(오선동)
4th row광주광역시 광산구 북문대로420번길150(신창동)
5th row광주광역시 광산구 금동학동길 306-16(덕림동)
ValueCountFrequency (%)
광주광역시 57
25.9%
광산구 57
25.9%
평동산단외로 9
 
4.1%
평동매화길 3
 
1.4%
도천남길 3
 
1.4%
북문대로 3
 
1.4%
풍영정길 2
 
0.9%
하남산단3번로 2
 
0.9%
대산로 2
 
0.9%
용아로 2
 
0.9%
Other values (77) 80
36.4%
2023-12-12T22:50:10.874283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 171
 
12.2%
163
 
11.6%
산 80
 
5.7%
동 79
 
5.6%
역 57
 
4.1%
시 57
 
4.1%
구 57
 
4.1%
주 57
 
4.1%
) 56
 
4.0%
( 56
 
4.0%
Other values (75) 572
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
63.8%
Decimal Number 213
 
15.2%
Space Separator 163
 
11.6%
Close Punctuation 56
 
4.0%
Open Punctuation 56
 
4.0%
Dash Punctuation 21
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 171
19.1%
산 80
 
8.9%
동 79
 
8.8%
역 57
 
6.4%
시 57
 
6.4%
구 57
 
6.4%
주 57
 
6.4%
로 42
 
4.7%
길 22
 
2.5%
단 18
 
2.0%
Other values (61) 256
28.6%
Decimal Number
ValueCountFrequency (%)
1 43
20.2%
2 34
16.0%
3 28
13.1%
6 20
9.4%
4 20
9.4%
0 18
8.5%
9 15
 
7.0%
5 13
 
6.1%
7 12
 
5.6%
8 10
 
4.7%
Space Separator
ValueCountFrequency (%)
163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
63.8%
Common 509
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 171
19.1%
산 80
 
8.9%
동 79
 
8.8%
역 57
 
6.4%
시 57
 
6.4%
구 57
 
6.4%
주 57
 
6.4%
로 42
 
4.7%
길 22
 
2.5%
단 18
 
2.0%
Other values (61) 256
28.6%
Common
ValueCountFrequency (%)
163
32.0%
) 56
 
11.0%
( 56
 
11.0%
1 43
 
8.4%
2 34
 
6.7%
3 28
 
5.5%
- 21
 
4.1%
6 20
 
3.9%
4 20
 
3.9%
0 18
 
3.5%
Other values (4) 50
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
63.8%
ASCII 509
36.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 171
19.1%
산 80
 
8.9%
동 79
 
8.8%
역 57
 
6.4%
시 57
 
6.4%
구 57
 
6.4%
주 57
 
6.4%
로 42
 
4.7%
길 22
 
2.5%
단 18
 
2.0%
Other values (61) 256
28.6%
ASCII
ValueCountFrequency (%)
163
32.0%
) 56
 
11.0%
( 56
 
11.0%
1 43
 
8.4%
2 34
 
6.7%
3 28
 
5.5%
- 21
 
4.1%
6 20
 
3.9%
4 20
 
3.9%
0 18
 
3.5%
Other values (4) 50
 
9.8%

등록일자
Date

Distinct53
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2011-09-30 00:00:00
Maximum2023-03-08 00:00:00
2023-12-12T22:50:11.060657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:11.233446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐기물종류
Text

Distinct47
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T22:50:11.481892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length160
Median length31
Mean length21.210526
Min length4

Characters and Unicode

Total characters1209
Distinct characters110
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)71.9%

Sample

1st row폐합성수지(폐전선)
2nd row사업장일반폐기물(폐합성수지)
3rd row폐합성수지(폐전선)
4th row폐지,고철, 폐합성수지류
5th row폐섬유, 폐보온재, 폐고무, 폐합성수지류, 폐목재류
ValueCountFrequency (%)
폐합성수지류 9
 
5.4%
폐합성수지 9
 
5.4%
중 6
 
3.6%
및 5
 
3.0%
폐목재류 4
 
2.4%
사업장일반폐기물(폐합성수지 4
 
2.4%
사업장 4
 
2.4%
사업장일반폐기물 4
 
2.4%
폐합성고무 4
 
2.4%
고철 4
 
2.4%
Other values (81) 114
68.3%
2023-12-12T22:50:11.908481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 125
 
10.3%
111
 
9.2%
, 78
 
6.5%
성 49
 
4.1%
합 49
 
4.1%
지 44
 
3.6%
( 43
 
3.6%
) 42
 
3.5%
수 41
 
3.4%
물 40
 
3.3%
Other values (100) 587
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 864
71.5%
Space Separator 111
 
9.2%
Other Punctuation 80
 
6.6%
Uppercase Letter 52
 
4.3%
Open Punctuation 43
 
3.6%
Close Punctuation 42
 
3.5%
Decimal Number 15
 
1.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 125
 
14.5%
성 49
 
5.7%
합 49
 
5.7%
지 44
 
5.1%
수 41
 
4.7%
물 40
 
4.6%
기 35
 
4.1%
류 24
 
2.8%
업 23
 
2.7%
사 23
 
2.7%
Other values (83) 411
47.6%
Uppercase Letter
ValueCountFrequency (%)
P 26
50.0%
S 9
 
17.3%
E 7
 
13.5%
B 4
 
7.7%
A 4
 
7.7%
V 1
 
1.9%
C 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 78
97.5%
: 1
 
1.2%
· 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 5
33.3%
2 5
33.3%
3 5
33.3%
Space Separator
ValueCountFrequency (%)
111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 864
71.5%
Common 293
 
24.2%
Latin 52
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 125
 
14.5%
성 49
 
5.7%
합 49
 
5.7%
지 44
 
5.1%
수 41
 
4.7%
물 40
 
4.6%
기 35
 
4.1%
류 24
 
2.8%
업 23
 
2.7%
사 23
 
2.7%
Other values (83) 411
47.6%
Common
ValueCountFrequency (%)
111
37.9%
, 78
26.6%
( 43
 
14.7%
) 42
 
14.3%
1 5
 
1.7%
2 5
 
1.7%
3 5
 
1.7%
- 2
 
0.7%
: 1
 
0.3%
· 1
 
0.3%
Latin
ValueCountFrequency (%)
P 26
50.0%
S 9
 
17.3%
E 7
 
13.5%
B 4
 
7.7%
A 4
 
7.7%
V 1
 
1.9%
C 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 864
71.5%
ASCII 344
 
28.5%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 125
 
14.5%
성 49
 
5.7%
합 49
 
5.7%
지 44
 
5.1%
수 41
 
4.7%
물 40
 
4.6%
기 35
 
4.1%
류 24
 
2.8%
업 23
 
2.7%
사 23
 
2.7%
Other values (83) 411
47.6%
ASCII
ValueCountFrequency (%)
111
32.3%
, 78
22.7%
( 43
 
12.5%
) 42
 
12.2%
P 26
 
7.6%
S 9
 
2.6%
E 7
 
2.0%
1 5
 
1.5%
2 5
 
1.5%
3 5
 
1.5%
Other values (6) 13
 
3.8%
None
ValueCountFrequency (%)
· 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.167897
Minimum35.092711
Maximum35.215091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T22:50:12.110621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.092711
5-th percentile35.123669
Q135.140213
median35.181615
Q335.192002
95-th percentile35.212442
Maximum35.215091
Range0.12238076
Interquartile range (IQR)0.051789685

Descriptive statistics

Standard deviation0.031932916
Coefficient of variation (CV)0.00090801324
Kurtosis-1.2120882
Mean35.167897
Median Absolute Deviation (MAD)0.031288885
Skewness-0.18113114
Sum2004.5701
Variance0.0010197111
MonotonicityNot monotonic
2023-12-12T22:50:12.285653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1901422020702 2
 
3.5%
35.1402255762531 2
 
3.5%
35.1824598447947 1
 
1.8%
35.1877160979713 1
 
1.8%
35.1980575117811 1
 
1.8%
35.1858774152026 1
 
1.8%
35.2148829498159 1
 
1.8%
35.1454891047767 1
 
1.8%
35.1883033082104 1
 
1.8%
35.1404613050672 1
 
1.8%
Other values (45) 45
78.9%
ValueCountFrequency (%)
35.0927105101599 1
1.8%
35.1145707887594 1
1.8%
35.1188435048123 1
1.8%
35.1248750029013 1
1.8%
35.1299903013563 1
1.8%
35.1352105525641 1
1.8%
35.1355824741283 1
1.8%
35.1358006005581 1
1.8%
35.1360426065592 1
1.8%
35.1368690196074 1
1.8%
ValueCountFrequency (%)
35.2150912726076 1
1.8%
35.214963023266 1
1.8%
35.2148829498159 1
1.8%
35.2118321427554 1
1.8%
35.2105874540423 1
1.8%
35.2087495639874 1
1.8%
35.2078043575363 1
1.8%
35.2066115351248 1
1.8%
35.2040946572623 1
1.8%
35.2018683887903 1
1.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.77028
Minimum126.66261
Maximum126.85601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T22:50:12.432799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66261
5-th percentile126.66789
Q1126.75465
median126.77737
Q3126.8179
95-th percentile126.85517
Maximum126.85601
Range0.19339892
Interquartile range (IQR)0.063243027

Descriptive statistics

Standard deviation0.060786859
Coefficient of variation (CV)0.00047950402
Kurtosis-0.84698589
Mean126.77028
Median Absolute Deviation (MAD)0.037004655
Skewness-0.50511303
Sum7225.9059
Variance0.0036950423
MonotonicityNot monotonic
2023-12-12T22:50:12.591013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.673288197951 2
 
3.5%
126.756542947326 2
 
3.5%
126.844724005599 1
 
1.8%
126.798249908239 1
 
1.8%
126.805867214304 1
 
1.8%
126.798297271506 1
 
1.8%
126.814379478855 1
 
1.8%
126.662614398775 1
 
1.8%
126.798399315299 1
 
1.8%
126.758989569905 1
 
1.8%
Other values (45) 45
78.9%
ValueCountFrequency (%)
126.662614398775 1
1.8%
126.663426282558 1
1.8%
126.665658330708 1
1.8%
126.668449212387 1
1.8%
126.671250684728 1
1.8%
126.671929783043 1
1.8%
126.673288197951 2
3.5%
126.674090494782 1
1.8%
126.676450092219 1
1.8%
126.683158029873 1
1.8%
ValueCountFrequency (%)
126.856013322334 1
1.8%
126.855640618084 1
1.8%
126.855527209892 1
1.8%
126.855084419104 1
1.8%
126.854619578474 1
1.8%
126.853729072512 1
1.8%
126.844724005599 1
1.8%
126.844302615009 1
1.8%
126.826658946693 1
1.8%
126.821168941549 1
1.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2023-05-04 00:00:00
Maximum2023-05-04 00:00:00
2023-12-12T22:50:12.737195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:12.839996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:50:08.249209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:07.697098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:07.957863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:08.340768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:07.771985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:08.040078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:08.447883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:07.863231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:08.126444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:50:12.918490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종사업장명주소등록일자폐기물종류위도경도
연번1.0001.0000.9410.8860.9420.7900.3320.225
업종1.0001.0000.0000.0000.8760.6510.0000.000
사업장명0.9410.0001.0001.0000.9900.9841.0001.000
주소0.8860.0001.0001.0000.9730.9421.0001.000
등록일자0.9420.8760.9900.9731.0000.9720.6980.536
폐기물종류0.7900.6510.9840.9420.9721.0000.0000.000
위도0.3320.0001.0001.0000.6980.0001.0000.779
경도0.2250.0001.0001.0000.5360.0000.7791.000
2023-12-12T22:50:13.035363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도업종
연번1.000-0.258-0.1570.892
위도-0.2581.0000.6010.000
경도-0.1570.6011.0000.000
업종0.8920.0000.0001.000

Missing values

2023-12-12T22:50:08.631944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:50:08.821064image/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

연번업종사업장명주소등록일자폐기물종류위도경도데이터기준일자
01중간재활용업한국전선가공광주광역시 광산구 풍영정길 93(신창동)2011-10-21폐합성수지(폐전선)35.18246126.8447242023-05-04
12중간재활용업한영기업광주광역시 광산구 하남산단6번로 24(오선동)2011-10-23사업장일반폐기물(폐합성수지)35.201868126.7979642023-05-04
23중간재활용업㈜반도기연광주광역시 광산구 용아로 627(오선동)2012-01-11폐합성수지(폐전선)35.19947126.8039742023-05-04
34중간재활용업신흥자원㈜광주광역시 광산구 북문대로420번길150(신창동)2012-02-13폐지,고철, 폐합성수지류35.192002126.8555272023-05-04
45중간재활용업솔라뱅크(유)광주광역시 광산구 금동학동길 306-16(덕림동)2012-05-31폐섬유, 폐보온재, 폐고무, 폐합성수지류, 폐목재류35.190142126.6732882023-05-04
56중간재활용업해남의류자원광주광역시 광산구 쌍내길 15(대산동)2012-11-29폐플라스틱(PP,PE,PS,ABS), 폐폴리염화비닐수지류(PVC), 페의류35.135801126.6634262023-05-04
67중간재활용업광주전남재향군인회광주광역시 광산구 도천남길 41-46(도천동)2013-04-30폐전선, 고철, 비철35.206612126.8186682023-05-04
78중간재활용업(유)국제비철금속광주광역시 광산구 도천남길 65(도천동)2013-06-07폐전선, 고철, 비철, 폐합성수지류35.20875126.8192272023-05-04
89중간재활용업대우비철광주광역시 광산구 사암로 776(도천동)2013-06-25사업장일반폐기물(폐전선, 고철, 비철)35.211832126.8184772023-05-04
910중간재활용업명창비철광주광역시 광산구 하남산단3번로14-66(장덕동)2013-07-15사업장생활계,사업장배출시설계 폐기물(폐전선)35.188335126.8037062023-05-04
연번업종사업장명주소등록일자폐기물종류위도경도데이터기준일자
4748종합재활용업㈜디케이보드광주광역시 광산구 손재로 436-54(오선동)2012-05-25사업장일반폐기물(폐스티로폼)35.204095126.8007512023-05-04
4849종합재활용업현대환경(주)광주광역시 광산구 북문대로 342-35(신창동)2014-02-24사업장일반폐기물, 생활계폐기물(폐합성수지, 철캔, 알루미늄캔,폐스티로폼)35.191266126.8556412023-05-04
4950종합재활용업㈜메탈코리아광주광역시 광산구 평동산단1번로 10(용동)2014-08-13폐알루미늄(자동차 휠, 스크랩)35.135582126.7573892023-05-04
5051종합재활용업㈜성신 광주지점광주광역시 광산구 평동매화길 3-5(지죽동)2016-12-30사업장일반폐기물 중 폐합성수지류, 폐목재류35.140226126.7565432023-05-04
5152종합재활용업평동산업자원㈜광주광역시 광산구 평동산단외로 271(지죽동)2017-04-17사업장일반, 생활폐기물 중 폐합성수지류(폐스티로폼)35.140618126.7687112023-05-04
5253종합재활용업㈜와이에이치 인터내셔널광주광역시 광산구 국룡길 202(송학동)2017-10-23사업장일반폐기물 중 비철금속 제련공정 광재(알루미늄)35.118844126.6848492023-05-04
5354종합재활용업대성이엔비(주)광주광역시 광산구 북문대로420번길 1382022-04-04사업장폐기물, 생활폐기물 중 폐발포합성수지(폐스티로폼)35.191798126.8550842023-05-04
5455종합재활용업(유)호진산업광주광역시 광산구 북문대로 363-146(신창동)2022-10-06그 밖의 폐합성고분자화합물(폐전선), 폐목재류35.183625126.8443032023-05-04
5556종합재활용업㈜에스피앤에스광주광역시 광산구 빛중앙12로 22(덕림동)2022-10-17폐합성수지류(ABS)35.181615126.674092023-05-04
5657종합재활용업오션클린폴리머광주광역시 광산구 평동산단외로 111-27(지죽동)2023-03-08폐합성수지류35.136869126.7542742023-05-04