Overview

Dataset statistics

Number of variables6
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory52.0 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description대구광역시_재생플라스틱 취급업체 현황_20190329
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15035495&dataSetDetailId=150354951fd9061384021&provdMethod=FILE

Alerts

연번 is highly overall correlated with 구군 and 1 other fieldsHigh correlation
구군 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
폐기물재활용업 허가 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
영업대상폐기물 is highly overall correlated with 구군High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:40:16.915131
Analysis finished2023-12-10 17:40:18.280493
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T02:40:18.512661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2023-12-11T02:40:18.844124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

구군
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
달성군
20 
서구
10 
달서구
동구
북구

Length

Max length3
Median length3
Mean length2.5909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달성군 20
45.5%
서구 10
22.7%
달서구 6
 
13.6%
동구 5
 
11.4%
북구 3
 
6.8%

Length

2023-12-11T02:40:19.176373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:40:19.587425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달성군 20
45.5%
서구 10
22.7%
달서구 6
 
13.6%
동구 5
 
11.4%
북구 3
 
6.8%

폐기물재활용업 허가
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
종합
25 
종합재활용
종합재활용업
중간재활용업
 
2
중간재활용
 
1

Length

Max length6
Median length2
Mean length3.4090909
Min length2

Unique

Unique2 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
종합 25
56.8%
종합재활용 9
 
20.5%
종합재활용업 6
 
13.6%
중간재활용업 2
 
4.5%
중간재활용 1
 
2.3%
최종 1
 
2.3%

Length

2023-12-11T02:40:19.930221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:40:20.228316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합 25
56.8%
종합재활용 9
 
20.5%
종합재활용업 6
 
13.6%
중간재활용업 2
 
4.5%
중간재활용 1
 
2.3%
최종 1
 
2.3%
Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-11T02:40:20.676042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.75
Min length4

Characters and Unicode

Total characters253
Distinct characters102
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st row대동수지공업사
2nd row신성상사
3rd row대한민국상이군경회
4th row경북재향군인회각산동지점
5th row㈜유창알앤씨
ValueCountFrequency (%)
㈜유창알앤씨 2
 
4.3%
㈜대한실업 2
 
4.3%
이천플라스틱 1
 
2.1%
창신산업 1
 
2.1%
금이수지 1
 
2.1%
우영수지 1
 
2.1%
동일산업 1
 
2.1%
한국수지 1
 
2.1%
새명주수지 1
 
2.1%
영남수지공업사 1
 
2.1%
Other values (35) 35
74.5%
2023-12-11T02:40:21.369483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
5.9%
14
 
5.5%
13
 
5.1%
12
 
4.7%
9
 
3.6%
9
 
3.6%
6
 
2.4%
6
 
2.4%
6
 
2.4%
5
 
2.0%
Other values (92) 158
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
92.5%
Other Symbol 13
 
5.1%
Space Separator 3
 
1.2%
Decimal Number 1
 
0.4%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
6.4%
14
 
6.0%
12
 
5.1%
9
 
3.8%
9
 
3.8%
6
 
2.6%
6
 
2.6%
6
 
2.6%
5
 
2.1%
5
 
2.1%
Other values (87) 147
62.8%
Other Symbol
ValueCountFrequency (%)
13
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
97.6%
Common 6
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
6.1%
14
 
5.7%
13
 
5.3%
12
 
4.9%
9
 
3.6%
9
 
3.6%
6
 
2.4%
6
 
2.4%
6
 
2.4%
5
 
2.0%
Other values (88) 152
61.5%
Common
ValueCountFrequency (%)
3
50.0%
2 1
 
16.7%
) 1
 
16.7%
( 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
92.5%
None 13
 
5.1%
ASCII 6
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
15
 
6.4%
14
 
6.0%
12
 
5.1%
9
 
3.8%
9
 
3.8%
6
 
2.6%
6
 
2.6%
6
 
2.6%
5
 
2.1%
5
 
2.1%
Other values (87) 147
62.8%
None
ValueCountFrequency (%)
13
100.0%
ASCII
ValueCountFrequency (%)
3
50.0%
2 1
 
16.7%
) 1
 
16.7%
( 1
 
16.7%
Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-11T02:40:21.899456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length16.545455
Min length11

Characters and Unicode

Total characters728
Distinct characters74
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

Unique37 ?
Unique (%)84.1%

Sample

1st row대구광역시 동구 안심로55길 4(동호동)
2nd row대구광역시 동구 안심로65길 14(각산동)
3rd row대구광역시 동구 안심로65길 14(각산동)
4th row대구광역시 동구 안심로65길 14(각산동)
5th row대구광역시 동구 공항로31길 26(불로동)
ValueCountFrequency (%)
하빈면 12
 
9.0%
대구광역시 11
 
8.3%
달서구 6
 
4.5%
동구 5
 
3.8%
하빈남로 5
 
3.8%
옥포읍 4
 
3.0%
논공읍 4
 
3.0%
안심로65길 3
 
2.3%
14(각산동 3
 
2.3%
서변동 2
 
1.5%
Other values (69) 78
58.6%
2023-12-11T02:40:22.733163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
12.2%
40
 
5.5%
2 34
 
4.7%
1 34
 
4.7%
30
 
4.1%
30
 
4.1%
26
 
3.6%
) 24
 
3.3%
( 24
 
3.3%
19
 
2.6%
Other values (64) 378
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 408
56.0%
Decimal Number 173
23.8%
Space Separator 89
 
12.2%
Close Punctuation 24
 
3.3%
Open Punctuation 24
 
3.3%
Dash Punctuation 10
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
40
 
9.8%
30
 
7.4%
30
 
7.4%
26
 
6.4%
19
 
4.7%
17
 
4.2%
17
 
4.2%
15
 
3.7%
14
 
3.4%
13
 
3.2%
Other values (50) 187
45.8%
Decimal Number
ValueCountFrequency (%)
2 34
19.7%
1 34
19.7%
5 17
9.8%
7 15
8.7%
6 14
8.1%
4 14
8.1%
0 14
8.1%
3 13
 
7.5%
8 11
 
6.4%
9 7
 
4.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
56.0%
Common 320
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
40
 
9.8%
30
 
7.4%
30
 
7.4%
26
 
6.4%
19
 
4.7%
17
 
4.2%
17
 
4.2%
15
 
3.7%
14
 
3.4%
13
 
3.2%
Other values (50) 187
45.8%
Common
ValueCountFrequency (%)
89
27.8%
2 34
 
10.6%
1 34
 
10.6%
) 24
 
7.5%
( 24
 
7.5%
5 17
 
5.3%
7 15
 
4.7%
6 14
 
4.4%
4 14
 
4.4%
0 14
 
4.4%
Other values (4) 41
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
56.0%
ASCII 320
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
27.8%
2 34
 
10.6%
1 34
 
10.6%
) 24
 
7.5%
( 24
 
7.5%
5 17
 
5.3%
7 15
 
4.7%
6 14
 
4.4%
4 14
 
4.4%
0 14
 
4.4%
Other values (4) 41
12.8%
Hangul
ValueCountFrequency (%)
40
 
9.8%
30
 
7.4%
30
 
7.4%
26
 
6.4%
19
 
4.7%
17
 
4.2%
17
 
4.2%
15
 
3.7%
14
 
3.4%
13
 
3.2%
Other values (50) 187
45.8%

영업대상폐기물
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
폐합성수지
26 
PE,PP
폐합성수지류
 
2
폐합성수지류(폐전선, 폐통신케이블, 고철)
 
2
폐합성수지류(폐전선, 폐통신케이블, 폐모터, 인쇄회로기관, 고철, 폐합성수지)
 
1
Other values (10)
10 

Length

Max length43
Median length5
Mean length8.3181818
Min length2

Unique

Unique11 ?
Unique (%)25.0%

Sample

1st row폐합성수지류
2nd row폐합성수지류(폐전선, 폐통신케이블, 고철)
3rd row폐합성수지류(폐전선, 폐통신케이블, 폐모터, 인쇄회로기관, 고철, 폐합성수지)
4th row폐합성수지류(폐전선, 폐통신케이블, 고철)
5th row폐합성수지류(폐플라스틱, 폐스티로폼)

Common Values

ValueCountFrequency (%)
폐합성수지 26
59.1%
PE,PP 3
 
6.8%
폐합성수지류 2
 
4.5%
폐합성수지류(폐전선, 폐통신케이블, 고철) 2
 
4.5%
폐합성수지류(폐전선, 폐통신케이블, 폐모터, 인쇄회로기관, 고철, 폐합성수지) 1
 
2.3%
폐합성수지류(폐플라스틱, 폐스티로폼) 1
 
2.3%
PE,PP,PS 1
 
2.3%
PE 1
 
2.3%
PE,PP,PET,PVC 1
 
2.3%
PE,PP,PET 1
 
2.3%
Other values (5) 5
 
11.4%

Length

2023-12-11T02:40:23.071029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐합성수지 27
45.8%
pe,pp 3
 
5.1%
폐합성수지류(폐전선 3
 
5.1%
폐통신케이블 3
 
5.1%
고철 3
 
5.1%
pp 2
 
3.4%
pe 2
 
3.4%
폐합성수지류 2
 
3.4%
인쇄회로기관 1
 
1.7%
폐합성수지류(폐플라스틱 1
 
1.7%
Other values (12) 12
20.3%

Interactions

2023-12-11T02:40:17.669694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:40:23.285551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군폐기물재활용업 허가업체명소재지영업대상폐기물
연번1.0000.9930.8280.9330.9930.614
구군0.9931.0000.8710.7061.0000.894
폐기물재활용업 허가0.8280.8711.0000.8830.5750.786
업체명0.9330.7060.8831.0000.9830.000
소재지0.9931.0000.5750.9831.0000.866
영업대상폐기물0.6140.8940.7860.0000.8661.000
2023-12-11T02:40:23.559092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업대상폐기물폐기물재활용업 허가구군
영업대상폐기물1.0000.4410.514
폐기물재활용업 허가0.4411.0000.783
구군0.5140.7831.000
2023-12-11T02:40:23.822919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군폐기물재활용업 허가영업대상폐기물
연번1.0000.8180.5930.241
구군0.8181.0000.7830.514
폐기물재활용업 허가0.5930.7831.0000.441
영업대상폐기물0.2410.5140.4411.000

Missing values

2023-12-11T02:40:17.927873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:40:18.188462image/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

연번구군폐기물재활용업 허가업체명소재지영업대상폐기물
01동구종합재활용업대동수지공업사대구광역시 동구 안심로55길 4(동호동)폐합성수지류
12동구종합재활용업신성상사대구광역시 동구 안심로65길 14(각산동)폐합성수지류(폐전선, 폐통신케이블, 고철)
23동구종합재활용업대한민국상이군경회대구광역시 동구 안심로65길 14(각산동)폐합성수지류(폐전선, 폐통신케이블, 폐모터, 인쇄회로기관, 고철, 폐합성수지)
34동구종합재활용업경북재향군인회각산동지점대구광역시 동구 안심로65길 14(각산동)폐합성수지류(폐전선, 폐통신케이블, 고철)
45동구종합재활용업㈜유창알앤씨대구광역시 동구 공항로31길 26(불로동)폐합성수지류(폐플라스틱, 폐스티로폼)
56서구종합재활용상신화학염색공단로 60(비산동)PE,PP,PS
67서구종합재활용한일수지팔달로2길 16(비산동)PE,PP
78서구종합재활용경북산업팔달로2길 18(비산동)PE
89서구종합재활용㈜강철환경염색공단천로16길 19(비산동)PE,PP,PET,PVC
910서구종합재활용서부자원와룡로65길 25(중리동)PE,PP
연번구군폐기물재활용업 허가업체명소재지영업대상폐기물
3435달성군종합이천플라스틱하빈면 달구벌대로8길 193-4폐합성수지
3536달성군종합주식회사 서진화학(제2공장)하빈면 하빈남로 371-45폐합성수지
3637달성군종합태왕샤링하빈면 봉촌리 704-2폐합성수지
3738달성군종합에코그린하빈면 하빈남로 275폐합성수지
3839달성군종합우주산업하빈면 하빈남로 350-8폐합성수지
3940달성군종합건준산업하빈면 하빈남로 409폐합성수지
4041달성군종합신진공업사하빈면 하빈남로 423폐합성수지
4142달성군종합영덕수지하빈면 하산1길 13폐합성수지
4243달성군종합하서종합수지하빈면 하산2길 25폐합성수지
4344달성군종합유니테크무역상사논공읍 논공로87길 117폐합성수지