Overview

Dataset statistics

Number of variables4
Number of observations1295
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.4 KiB
Average record size in memory35.1 B

Variable types

Numeric2
Text1
Categorical1

Dataset

Description전기전자제품및자동차의재활용시스템 내 전기전자기타정보를 제공(의무이행 년도, 업체명, 통계 차수, 부과금액)
Author환경부
URLhttps://www.data.go.kr/data/15092479/fileData.do

Alerts

의무이행 년도 is highly overall correlated with 통계 차수High correlation
통계 차수 is highly overall correlated with 의무이행 년도High correlation
부과금액 is highly skewed (γ1 = 28.08708049)Skewed
부과금액 has 42 (3.2%) zerosZeros

Reproduction

Analysis started2024-04-06 08:56:19.140575
Analysis finished2024-04-06 08:56:21.557378
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의무이행 년도
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.5305
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.5 KiB
2024-04-06T17:56:21.738313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12015
median2016
Q32018
95-th percentile2020
Maximum2022
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9059301
Coefficient of variation (CV)0.00094515314
Kurtosis-0.31670752
Mean2016.5305
Median Absolute Deviation (MAD)1
Skewness0.59727967
Sum2611407
Variance3.6325697
MonotonicityIncreasing
2024-04-06T17:56:21.979451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2015 309
23.9%
2017 231
17.8%
2018 199
15.4%
2016 186
14.4%
2014 182
14.1%
2019 87
 
6.7%
2021 58
 
4.5%
2020 39
 
3.0%
2022 4
 
0.3%
ValueCountFrequency (%)
2014 182
14.1%
2015 309
23.9%
2016 186
14.4%
2017 231
17.8%
2018 199
15.4%
2019 87
 
6.7%
2020 39
 
3.0%
2021 58
 
4.5%
2022 4
 
0.3%
ValueCountFrequency (%)
2022 4
 
0.3%
2021 58
 
4.5%
2020 39
 
3.0%
2019 87
 
6.7%
2018 199
15.4%
2017 231
17.8%
2016 186
14.4%
2015 309
23.9%
2014 182
14.1%

업체명
Text

Distinct462
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2024-04-06T17:56:22.397326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length8.5111969
Min length2

Characters and Unicode

Total characters11022
Distinct characters372
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)15.9%

Sample

1st row(주) 셀루온
2nd row(주) 진코퍼레이션
3rd row(주)PN풍년
4th row(주)구츠
5th row(주)귀뚜라미 아산공장
ValueCountFrequency (%)
주식회사 166
 
10.8%
주 19
 
1.2%
코리아 16
 
1.0%
유한회사 14
 
0.9%
청호나이스(주 11
 
0.7%
토마텍주식회사 11
 
0.7%
테크스캔코리아 11
 
0.7%
주)신흥정밀 11
 
0.7%
주)하이필 10
 
0.7%
자이글주식회사 10
 
0.7%
Other values (465) 1255
81.8%
2024-04-06T17:56:23.058316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1080
 
9.8%
( 855
 
7.8%
) 855
 
7.8%
이 553
 
5.0%
스 366
 
3.3%
아 329
 
3.0%
코 297
 
2.7%
사 285
 
2.6%
회 258
 
2.3%
리 250
 
2.3%
Other values (362) 5894
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8917
80.9%
Open Punctuation 855
 
7.8%
Close Punctuation 855
 
7.8%
Space Separator 242
 
2.2%
Lowercase Letter 70
 
0.6%
Uppercase Letter 59
 
0.5%
Other Punctuation 19
 
0.2%
Dash Punctuation 4
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1080
 
12.1%
이 553
 
6.2%
스 366
 
4.1%
아 329
 
3.7%
코 297
 
3.3%
사 285
 
3.2%
회 258
 
2.9%
리 250
 
2.8%
식 237
 
2.7%
에 173
 
1.9%
Other values (329) 5089
57.1%
Lowercase Letter
ValueCountFrequency (%)
e 14
20.0%
n 9
12.9%
c 8
11.4%
a 6
8.6%
r 5
 
7.1%
l 5
 
7.1%
o 5
 
7.1%
v 4
 
5.7%
y 4
 
5.7%
s 3
 
4.3%
Other values (5) 7
10.0%
Uppercase Letter
ValueCountFrequency (%)
P 10
16.9%
O 8
13.6%
B 8
13.6%
E 7
11.9%
I 5
8.5%
K 5
8.5%
G 4
 
6.8%
C 4
 
6.8%
N 4
 
6.8%
H 3
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 11
57.9%
& 8
42.1%
Open Punctuation
ValueCountFrequency (%)
( 855
100.0%
Close Punctuation
ValueCountFrequency (%)
) 855
100.0%
Space Separator
ValueCountFrequency (%)
242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8917
80.9%
Common 1976
 
17.9%
Latin 129
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1080
 
12.1%
이 553
 
6.2%
스 366
 
4.1%
아 329
 
3.7%
코 297
 
3.3%
사 285
 
3.2%
회 258
 
2.9%
리 250
 
2.8%
식 237
 
2.7%
에 173
 
1.9%
Other values (329) 5089
57.1%
Latin
ValueCountFrequency (%)
e 14
 
10.9%
P 10
 
7.8%
n 9
 
7.0%
c 8
 
6.2%
O 8
 
6.2%
B 8
 
6.2%
E 7
 
5.4%
a 6
 
4.7%
I 5
 
3.9%
K 5
 
3.9%
Other values (16) 49
38.0%
Common
ValueCountFrequency (%)
( 855
43.3%
) 855
43.3%
242
 
12.2%
. 11
 
0.6%
& 8
 
0.4%
- 4
 
0.2%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8917
80.9%
ASCII 2105
 
19.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1080
 
12.1%
이 553
 
6.2%
스 366
 
4.1%
아 329
 
3.7%
코 297
 
3.3%
사 285
 
3.2%
회 258
 
2.9%
리 250
 
2.8%
식 237
 
2.7%
에 173
 
1.9%
Other values (329) 5089
57.1%
ASCII
ValueCountFrequency (%)
( 855
40.6%
) 855
40.6%
242
 
11.5%
e 14
 
0.7%
. 11
 
0.5%
P 10
 
0.5%
n 9
 
0.4%
c 8
 
0.4%
O 8
 
0.4%
& 8
 
0.4%
Other values (23) 85
 
4.0%

통계 차수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
1
708 
2
587 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 708
54.7%
2 587
45.3%

Length

2024-04-06T17:56:23.305220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:56:23.507402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 708
54.7%
2 587
45.3%

부과금액
Real number (ℝ)

SKEWED  ZEROS 

Distinct941
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46666532
Minimum0
Maximum1.5371315 × 1010
Zeros42
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size11.5 KiB
2024-04-06T17:56:23.709893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40261
Q11083100
median4943480
Q315593250
95-th percentile92021910
Maximum1.5371315 × 1010
Range1.5371315 × 1010
Interquartile range (IQR)14510150

Descriptive statistics

Standard deviation4.6824093 × 108
Coefficient of variation (CV)10.033763
Kurtosis894.27812
Mean46666532
Median Absolute Deviation (MAD)4498450
Skewness28.08708
Sum6.0433159 × 1010
Variance2.1924957 × 1017
MonotonicityNot monotonic
2024-04-06T17:56:23.973757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42
 
3.2%
1320170 2
 
0.2%
147770 2
 
0.2%
5073370 2
 
0.2%
6257830 2
 
0.2%
515210 2
 
0.2%
2102260 2
 
0.2%
10460960 2
 
0.2%
9581380 2
 
0.2%
14977080 2
 
0.2%
Other values (931) 1235
95.4%
ValueCountFrequency (%)
0 42
3.2%
490 2
 
0.2%
4050 2
 
0.2%
4630 1
 
0.1%
5490 2
 
0.2%
7620 1
 
0.1%
15440 2
 
0.2%
25930 1
 
0.1%
27750 2
 
0.2%
29130 1
 
0.1%
ValueCountFrequency (%)
15371315190 1
0.1%
4079662110 1
0.1%
2846694900 1
0.1%
2425767780 1
0.1%
2274276910 1
0.1%
1818495960 1
0.1%
1708753060 1
0.1%
933810300 2
0.2%
911368350 1
0.1%
888622360 1
0.1%

Interactions

2024-04-06T17:56:20.295633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:19.706474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:20.600232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:20.014773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:56:24.176242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의무이행 년도통계 차수부과금액
의무이행 년도1.0000.7150.002
통계 차수0.7151.0000.000
부과금액0.0020.0001.000
2024-04-06T17:56:24.442832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의무이행 년도부과금액통계 차수
의무이행 년도1.0000.0650.626
부과금액0.0651.0000.000
통계 차수0.6260.0001.000

Missing values

2024-04-06T17:56:20.899912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:56:21.490255image/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

의무이행 년도업체명통계 차수부과금액
02014(주) 셀루온10
12014(주) 진코퍼레이션11469210
22014(주)PN풍년128932450
32014(주)구츠111985820
42014(주)귀뚜라미 아산공장1197488500
52014(주)귀뚜라미범양냉방아산지점13911200
62014(주)그린쿨텍11954480
72014(주)노루로지넷1161100
82014(주)누리플렉스1274050
92014(주)다빈워텍18047060
의무이행 년도업체명통계 차수부과금액
12852021테크스캔코리아16187920
12862021토마텍주식회사11833930
12872021플랜잇코리아 주식회사137209230
12882021하이네켄코리아112476760
12892021한국애질런트테크놀로지스11049790
12902021현대렌탈케어10
12912022(주)대한과학115409920
12922022(주)케이아이티코리아11414440
12932022청호나이스(주)10
12942022한국타피(주)10