Overview

Dataset statistics

Number of variables6
Number of observations2920
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory145.6 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Text2
DateTime1

Dataset

Description순환자원정보센터 내 순환장터 물품거래 정보(제품번호, 업체명, 제품명, 제품 가격, 제품 수량, 등록일시 등) 입니다.
URLhttps://www.data.go.kr/data/15070424/fileData.do

Alerts

제품 가격 is highly skewed (γ1 = 53.38673155)Skewed
제품 수량 is highly skewed (γ1 = 46.45702701)Skewed
제품번호 has unique valuesUnique
제품 가격 has 2901 (99.3%) zerosZeros
제품 수량 has 77 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-12 08:27:24.887203
Analysis finished2023-12-12 08:27:26.525942
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제품번호
Real number (ℝ)

UNIQUE 

Distinct2920
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean729778.02
Minimum2695
Maximum946285
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.8 KiB
2023-12-12T17:27:26.611528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2695
5-th percentile645054.95
Q1645638.75
median654794.5
Q3872042.25
95-th percentile945708.75
Maximum946285
Range943590
Interquartile range (IQR)226403.5

Descriptive statistics

Standard deviation116373.32
Coefficient of variation (CV)0.159464
Kurtosis-0.13870548
Mean729778.02
Median Absolute Deviation (MAD)9436
Skewness0.65778799
Sum2.1309518 × 109
Variance1.3542749 × 1010
MonotonicityNot monotonic
2023-12-12T17:27:26.750609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
945581 1
 
< 0.1%
654315 1
 
< 0.1%
654535 1
 
< 0.1%
654536 1
 
< 0.1%
654537 1
 
< 0.1%
654397 1
 
< 0.1%
654384 1
 
< 0.1%
654385 1
 
< 0.1%
654604 1
 
< 0.1%
654605 1
 
< 0.1%
Other values (2910) 2910
99.7%
ValueCountFrequency (%)
2695 1
< 0.1%
2696 1
< 0.1%
544404 1
< 0.1%
573303 1
< 0.1%
575789 1
< 0.1%
575790 1
< 0.1%
644845 1
< 0.1%
644846 1
< 0.1%
644847 1
< 0.1%
644848 1
< 0.1%
ValueCountFrequency (%)
946285 1
< 0.1%
946284 1
< 0.1%
946283 1
< 0.1%
946282 1
< 0.1%
946281 1
< 0.1%
946280 1
< 0.1%
946279 1
< 0.1%
946278 1
< 0.1%
946277 1
< 0.1%
946276 1
< 0.1%

업체명
Text

Distinct63
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
2023-12-12T17:27:26.945264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.5438356
Min length4

Characters and Unicode

Total characters22028
Distinct characters162
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.8%

Sample

1st row놀뫼환경(주)
2nd row부천시하수슬러지처리시설
3rd row(주)그린써비스
4th row녹색자원
5th row지엠비코리아(주)
ValueCountFrequency (%)
놀뫼환경(주 2001
67.9%
대경프라스틱공업(주 339
 
11.5%
주)충남알앤피 257
 
8.7%
주)코레코 163
 
5.5%
주식회사 23
 
0.8%
엘엘케이 13
 
0.4%
삼원리싸이클링(주 12
 
0.4%
한국환경공단 10
 
0.3%
에스아이케미칼(주 9
 
0.3%
주)그린써비스 6
 
0.2%
Other values (57) 114
 
3.9%
2023-12-12T17:27:27.283487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2866
13.0%
( 2838
12.9%
) 2838
12.9%
경 2353
10.7%
환 2014
9.1%
놀 2001
9.1%
뫼 2001
9.1%
스 377
 
1.7%
업 354
 
1.6%
공 353
 
1.6%
Other values (152) 4033
18.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16307
74.0%
Open Punctuation 2838
 
12.9%
Close Punctuation 2838
 
12.9%
Space Separator 27
 
0.1%
Uppercase Letter 12
 
0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2866
17.6%
경 2353
14.4%
환 2014
12.4%
놀 2001
12.3%
뫼 2001
12.3%
스 377
 
2.3%
업 354
 
2.2%
공 353
 
2.2%
대 350
 
2.1%
프 347
 
2.1%
Other values (137) 3291
20.2%
Uppercase Letter
ValueCountFrequency (%)
G 4
33.3%
S 4
33.3%
O 1
 
8.3%
C 1
 
8.3%
I 1
 
8.3%
A 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
r 1
16.7%
m 1
16.7%
y 1
16.7%
p 1
16.7%
i 1
16.7%
a 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 2838
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2838
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16307
74.0%
Common 5703
 
25.9%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2866
17.6%
경 2353
14.4%
환 2014
12.4%
놀 2001
12.3%
뫼 2001
12.3%
스 377
 
2.3%
업 354
 
2.2%
공 353
 
2.2%
대 350
 
2.1%
프 347
 
2.1%
Other values (137) 3291
20.2%
Latin
ValueCountFrequency (%)
G 4
22.2%
S 4
22.2%
r 1
 
5.6%
m 1
 
5.6%
y 1
 
5.6%
p 1
 
5.6%
i 1
 
5.6%
a 1
 
5.6%
O 1
 
5.6%
C 1
 
5.6%
Other values (2) 2
11.1%
Common
ValueCountFrequency (%)
( 2838
49.8%
) 2838
49.8%
27
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16307
74.0%
ASCII 5721
 
26.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2866
17.6%
경 2353
14.4%
환 2014
12.4%
놀 2001
12.3%
뫼 2001
12.3%
스 377
 
2.3%
업 354
 
2.2%
공 353
 
2.2%
대 350
 
2.1%
프 347
 
2.1%
Other values (137) 3291
20.2%
ASCII
ValueCountFrequency (%)
( 2838
49.6%
) 2838
49.6%
27
 
0.5%
G 4
 
0.1%
S 4
 
0.1%
r 1
 
< 0.1%
m 1
 
< 0.1%
y 1
 
< 0.1%
p 1
 
< 0.1%
i 1
 
< 0.1%
Other values (5) 5
 
0.1%

제품명
Text

Distinct190
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
2023-12-12T17:27:27.528505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length42
Mean length4.9030822
Min length2

Characters and Unicode

Total characters14317
Distinct characters306
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)5.2%

Sample

1st row순환잔골재
2nd row소각재
3rd row폐합성수지류
4th row폐지
5th row무기성오니
ValueCountFrequency (%)
순환잔골재 1194
36.5%
순환골재 804
24.6%
요쿠르트 338
 
10.3%
폐토사 160
 
4.9%
pe 56
 
1.7%
pet 52
 
1.6%
pp 38
 
1.2%
구합니다 21
 
0.6%
압축 18
 
0.5%
pe세척품 16
 
0.5%
Other values (295) 577
17.6%
2023-12-12T17:27:28.062988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
재 2040
14.2%
골 2002
14.0%
순 2000
14.0%
환 2000
14.0%
잔 1199
 
8.4%
358
 
2.5%
트 353
 
2.5%
요 344
 
2.4%
쿠 338
 
2.4%
르 338
 
2.4%
Other values (296) 3345
23.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13079
91.4%
Uppercase Letter 607
 
4.2%
Space Separator 358
 
2.5%
Other Punctuation 100
 
0.7%
Lowercase Letter 81
 
0.6%
Close Punctuation 32
 
0.2%
Open Punctuation 32
 
0.2%
Decimal Number 21
 
0.1%
Dash Punctuation 3
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
재 2040
15.6%
골 2002
15.3%
순 2000
15.3%
환 2000
15.3%
잔 1199
9.2%
트 353
 
2.7%
요 344
 
2.6%
쿠 338
 
2.6%
르 338
 
2.6%
폐 255
 
1.9%
Other values (250) 2210
16.9%
Lowercase Letter
ValueCountFrequency (%)
p 39
48.1%
e 13
 
16.0%
r 4
 
4.9%
o 4
 
4.9%
n 3
 
3.7%
i 3
 
3.7%
m 2
 
2.5%
c 2
 
2.5%
u 2
 
2.5%
t 2
 
2.5%
Other values (7) 7
 
8.6%
Uppercase Letter
ValueCountFrequency (%)
P 287
47.3%
E 175
28.8%
T 83
 
13.7%
S 29
 
4.8%
V 10
 
1.6%
C 8
 
1.3%
B 4
 
0.7%
D 3
 
0.5%
A 3
 
0.5%
R 2
 
0.3%
Other values (3) 3
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 9
42.9%
5 4
19.0%
2 3
 
14.3%
1 2
 
9.5%
8 1
 
4.8%
3 1
 
4.8%
7 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 59
59.0%
, 39
39.0%
: 2
 
2.0%
Space Separator
ValueCountFrequency (%)
358
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13079
91.4%
Latin 688
 
4.8%
Common 550
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
재 2040
15.6%
골 2002
15.3%
순 2000
15.3%
환 2000
15.3%
잔 1199
9.2%
트 353
 
2.7%
요 344
 
2.6%
쿠 338
 
2.6%
르 338
 
2.6%
폐 255
 
1.9%
Other values (250) 2210
16.9%
Latin
ValueCountFrequency (%)
P 287
41.7%
E 175
25.4%
T 83
 
12.1%
p 39
 
5.7%
S 29
 
4.2%
e 13
 
1.9%
V 10
 
1.5%
C 8
 
1.2%
r 4
 
0.6%
B 4
 
0.6%
Other values (20) 36
 
5.2%
Common
ValueCountFrequency (%)
358
65.1%
. 59
 
10.7%
, 39
 
7.1%
) 32
 
5.8%
( 32
 
5.8%
0 9
 
1.6%
5 4
 
0.7%
- 3
 
0.5%
2 3
 
0.5%
_ 3
 
0.5%
Other values (6) 8
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13079
91.4%
ASCII 1238
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
재 2040
15.6%
골 2002
15.3%
순 2000
15.3%
환 2000
15.3%
잔 1199
9.2%
트 353
 
2.7%
요 344
 
2.6%
쿠 338
 
2.6%
르 338
 
2.6%
폐 255
 
1.9%
Other values (250) 2210
16.9%
ASCII
ValueCountFrequency (%)
358
28.9%
P 287
23.2%
E 175
14.1%
T 83
 
6.7%
. 59
 
4.8%
, 39
 
3.2%
p 39
 
3.2%
) 32
 
2.6%
( 32
 
2.6%
S 29
 
2.3%
Other values (36) 105
 
8.5%

제품 가격
Real number (ℝ)

SKEWED  ZEROS 

Distinct17
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324241.93
Minimum0
Maximum8.206 × 108
Zeros2901
Zeros (%)99.3%
Negative0
Negative (%)0.0%
Memory size25.8 KiB
2023-12-12T17:27:28.226127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8.206 × 108
Range8.206 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15249978
Coefficient of variation (CV)47.032715
Kurtosis2870.7341
Mean324241.93
Median Absolute Deviation (MAD)0
Skewness53.386732
Sum9.4678643 × 108
Variance2.3256183 × 1014
MonotonicityNot monotonic
2023-12-12T17:27:28.351098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 2901
99.3%
5000 2
 
0.1%
10000 2
 
0.1%
5000000 2
 
0.1%
590 1
 
< 0.1%
700 1
 
< 0.1%
720 1
 
< 0.1%
920 1
 
< 0.1%
100000 1
 
< 0.1%
820600000 1
 
< 0.1%
Other values (7) 7
 
0.2%
ValueCountFrequency (%)
0 2901
99.3%
590 1
 
< 0.1%
700 1
 
< 0.1%
720 1
 
< 0.1%
920 1
 
< 0.1%
3500 1
 
< 0.1%
5000 2
 
0.1%
10000 2
 
0.1%
100000 1
 
< 0.1%
2500000 1
 
< 0.1%
ValueCountFrequency (%)
820600000 1
< 0.1%
72300000 1
< 0.1%
15000000 1
< 0.1%
12000000 1
< 0.1%
10000000 1
< 0.1%
5000000 2
0.1%
4250000 1
< 0.1%
2500000 1
< 0.1%
100000 1
< 0.1%
10000 2
0.1%

제품 수량
Real number (ℝ)

SKEWED  ZEROS 

Distinct255
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18290.442
Minimum0
Maximum32000000
Zeros77
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size25.8 KiB
2023-12-12T17:27:28.511291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112
median16
Q3100
95-th percentile8000
Maximum32000000
Range32000000
Interquartile range (IQR)88

Descriptive statistics

Standard deviation630218.78
Coefficient of variation (CV)34.45618
Kurtosis2298.0552
Mean18290.442
Median Absolute Deviation (MAD)9
Skewness46.457027
Sum53408092
Variance3.9717571 × 1011
MonotonicityNot monotonic
2023-12-12T17:27:29.049339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 1199
41.1%
1 562
19.2%
7500 175
 
6.0%
8000 169
 
5.8%
25 165
 
5.7%
0 77
 
2.6%
12 47
 
1.6%
1000 40
 
1.4%
17000 40
 
1.4%
10 37
 
1.3%
Other values (245) 409
 
14.0%
ValueCountFrequency (%)
0 77
 
2.6%
1 562
19.2%
2 6
 
0.2%
3 2
 
0.1%
4 2
 
0.1%
5 6
 
0.2%
6 1
 
< 0.1%
8 5
 
0.2%
10 37
 
1.3%
12 47
 
1.6%
ValueCountFrequency (%)
32000000 1
 
< 0.1%
10000000 1
 
< 0.1%
6000000 1
 
< 0.1%
450000 1
 
< 0.1%
270000 1
 
< 0.1%
75000 1
 
< 0.1%
30000 1
 
< 0.1%
24000 6
 
0.2%
20000 22
0.8%
18558 1
 
< 0.1%

등록일
Date

Distinct315
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
Minimum2013-02-14 10:16:00
Maximum2023-02-17 14:15:00
2023-12-12T17:27:29.200755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:29.355344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T17:27:25.970828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.372137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.687138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:26.063773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.468665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.774676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:26.166093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.570632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:27:25.861905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:27:29.475683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제품번호업체명제품 가격제품 수량
제품번호1.0000.7250.0000.000
업체명0.7251.0000.4660.000
제품 가격0.0000.4661.0000.000
제품 수량0.0000.0000.0001.000
2023-12-12T17:27:29.584802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제품번호제품 가격제품 수량
제품번호1.0000.1200.261
제품 가격0.1201.000-0.013
제품 수량0.261-0.0131.000

Missing values

2023-12-12T17:27:26.332317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:27:26.472403image/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

제품번호업체명제품명제품 가격제품 수량등록일
0945581놀뫼환경(주)순환잔골재060000002017-09-06 11:29
1945580부천시하수슬러지처리시설소각재062862017-09-06 10:12
2945677(주)그린써비스폐합성수지류723000007232017-09-21 11:14
3945686녹색자원폐지02700002017-09-21 16:38
4945953지엠비코리아(주)무기성오니0102019-07-25 14:09
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