Overview

Dataset statistics

Number of variables7
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory62.8 B

Variable types

Categorical2
Text1
Numeric3
Boolean1

Dataset

Description인천광역시 서구 쓰레기종량제봉투 단가에 대한 데이터로 봉투종류, 발주단가, 도매단가, 소매단가 등의 정보가 포함되어 있습니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15090804/fileData.do

Alerts

지역코드 has constant value ""Constant
사용여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
발주단가 is highly overall correlated with 도매단가 and 1 other fieldsHigh correlation
도매단가 is highly overall correlated with 발주단가 and 1 other fieldsHigh correlation
소매단가 is highly overall correlated with 발주단가 and 1 other fieldsHigh correlation
봉투종류 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:40:17.230947
Analysis finished2024-03-14 09:40:20.123062
Duration2.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size488.0 B
110308
45 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row110308
2nd row110308
3rd row110308
4th row110308
5th row110308

Common Values

ValueCountFrequency (%)
110308 45
100.0%

Length

2024-03-14T18:40:20.323103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:40:20.631617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
110308 45
100.0%

봉투종류
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size488.0 B
2024-03-14T18:40:21.358867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length9.2222222
Min length5

Characters and Unicode

Total characters415
Distinct characters37
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

Unique45 ?
Unique (%)100.0%

Sample

1st row일반용 5L
2nd row일반용 10L
3rd row일반용 20L
4th row일반용 50L
5th row불연성 10L
ValueCountFrequency (%)
음식물 10
 
11.0%
스티커 9
 
9.9%
필증 8
 
8.8%
일반용 7
 
7.7%
재사용 6
 
6.6%
불연성 3
 
3.3%
10l(청라 3
 
3.3%
5l(청라 3
 
3.3%
사업계용 3
 
3.3%
5l 3
 
3.3%
Other values (28) 36
39.6%
2024-03-14T18:40:22.556913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
11.1%
0 45
 
10.8%
L 37
 
8.9%
( 22
 
5.3%
) 22
 
5.3%
용 20
 
4.8%
청 15
 
3.6%
라 15
 
3.6%
1 14
 
3.4%
5 13
 
3.1%
Other values (27) 166
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
46.7%
Decimal Number 94
22.7%
Space Separator 46
 
11.1%
Uppercase Letter 37
 
8.9%
Open Punctuation 22
 
5.3%
Close Punctuation 22
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 20
 
10.3%
청 15
 
7.7%
라 15
 
7.7%
물 10
 
5.2%
식 10
 
5.2%
음 10
 
5.2%
사 9
 
4.6%
커 9
 
4.6%
스 9
 
4.6%
티 9
 
4.6%
Other values (17) 78
40.2%
Decimal Number
ValueCountFrequency (%)
0 45
47.9%
1 14
 
14.9%
5 13
 
13.8%
2 13
 
13.8%
3 7
 
7.4%
6 2
 
2.1%
Space Separator
ValueCountFrequency (%)
46
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
46.7%
Common 184
44.3%
Latin 37
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 20
 
10.3%
청 15
 
7.7%
라 15
 
7.7%
물 10
 
5.2%
식 10
 
5.2%
음 10
 
5.2%
사 9
 
4.6%
커 9
 
4.6%
스 9
 
4.6%
티 9
 
4.6%
Other values (17) 78
40.2%
Common
ValueCountFrequency (%)
46
25.0%
0 45
24.5%
( 22
12.0%
) 22
12.0%
1 14
 
7.6%
5 13
 
7.1%
2 13
 
7.1%
3 7
 
3.8%
6 2
 
1.1%
Latin
ValueCountFrequency (%)
L 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221
53.3%
Hangul 194
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
20.8%
0 45
20.4%
L 37
16.7%
( 22
10.0%
) 22
10.0%
1 14
 
6.3%
5 13
 
5.9%
2 13
 
5.9%
3 7
 
3.2%
6 2
 
0.9%
Hangul
ValueCountFrequency (%)
용 20
 
10.3%
청 15
 
7.7%
라 15
 
7.7%
물 10
 
5.2%
식 10
 
5.2%
음 10
 
5.2%
사 9
 
4.6%
커 9
 
4.6%
스 9
 
4.6%
티 9
 
4.6%
Other values (17) 78
40.2%

발주단가
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean353.57778
Minimum18
Maximum4300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size533.0 B
2024-03-14T18:40:22.939530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile22.2
Q133
median42
Q3190
95-th percentile3217.2
Maximum4300
Range4282
Interquartile range (IQR)157

Descriptive statistics

Standard deviation1006.7959
Coefficient of variation (CV)2.8474525
Kurtosis11.3367
Mean353.57778
Median Absolute Deviation (MAD)19
Skewness3.5604009
Sum15911
Variance1013638.1
MonotonicityNot monotonic
2024-03-14T18:40:23.290615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
190 8
17.8%
57 4
 
8.9%
38 4
 
8.9%
41 4
 
8.9%
23 4
 
8.9%
31 3
 
6.7%
42 2
 
4.4%
33 2
 
4.4%
58 2
 
4.4%
22 2
 
4.4%
Other values (9) 10
22.2%
ValueCountFrequency (%)
18 1
 
2.2%
22 2
4.4%
23 4
8.9%
25 1
 
2.2%
31 3
6.7%
33 2
4.4%
38 4
8.9%
41 4
8.9%
42 2
4.4%
57 4
8.9%
ValueCountFrequency (%)
4300 1
 
2.2%
3980 1
 
2.2%
3900 1
 
2.2%
486 1
 
2.2%
256 1
 
2.2%
190 8
17.8%
139 1
 
2.2%
124 2
 
4.4%
58 2
 
4.4%
57 4
8.9%

도매단가
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1864.5111
Minimum56
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size533.0 B
2024-03-14T18:40:23.642156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile112
Q1278
median571
Q32763
95-th percentile6979.2
Maximum9210
Range9154
Interquartile range (IQR)2485

Descriptive statistics

Standard deviation2439.7705
Coefficient of variation (CV)1.3085309
Kurtosis2.2911919
Mean1864.5111
Median Absolute Deviation (MAD)428
Skewness1.699516
Sum83903
Variance5952480
MonotonicityNot monotonic
2024-03-14T18:40:24.025477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
571 5
 
11.1%
285 5
 
11.1%
148 4
 
8.9%
1417 2
 
4.4%
9210 2
 
4.4%
4605 2
 
4.4%
2763 2
 
4.4%
921 2
 
4.4%
112 2
 
4.4%
168 2
 
4.4%
Other values (16) 17
37.8%
ValueCountFrequency (%)
56 1
 
2.2%
86 1
 
2.2%
112 2
 
4.4%
143 1
 
2.2%
148 4
8.9%
168 2
 
4.4%
278 2
 
4.4%
285 5
11.1%
552 1
 
2.2%
571 5
11.1%
ValueCountFrequency (%)
9210 2
4.4%
7050 1
2.2%
6696 1
2.2%
4605 2
4.4%
4600 1
2.2%
4300 1
2.2%
4000 1
2.2%
3420 1
2.2%
3348 1
2.2%
2763 2
4.4%

소매단가
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2025.8444
Minimum60
Maximum10000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size533.0 B
2024-03-14T18:40:24.400694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile120
Q1300
median620
Q33000
95-th percentile7568
Maximum10000
Range9940
Interquartile range (IQR)2700

Descriptive statistics

Standard deviation2650.1267
Coefficient of variation (CV)1.308159
Kurtosis2.2668652
Mean2025.8444
Median Absolute Deviation (MAD)465
Skewness1.6936607
Sum91163
Variance7023171.4
MonotonicityNot monotonic
2024-03-14T18:40:24.797042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
620 5
 
11.1%
310 5
 
11.1%
160 4
 
8.9%
1540 2
 
4.4%
10000 2
 
4.4%
5000 2
 
4.4%
3000 2
 
4.4%
1000 2
 
4.4%
120 2
 
4.4%
180 2
 
4.4%
Other values (16) 17
37.8%
ValueCountFrequency (%)
60 1
 
2.2%
93 1
 
2.2%
120 2
 
4.4%
155 1
 
2.2%
160 4
8.9%
180 2
 
4.4%
300 2
 
4.4%
310 5
11.1%
600 1
 
2.2%
620 5
11.1%
ValueCountFrequency (%)
10000 2
4.4%
7660 1
2.2%
7200 1
2.2%
5060 1
2.2%
5000 2
4.4%
4730 1
2.2%
4400 1
2.2%
3710 1
2.2%
3600 1
2.2%
3000 2
4.4%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size173.0 B
True
45 
ValueCountFrequency (%)
True 45
100.0%
2024-03-14T18:40:25.127590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size488.0 B
2023-12-06
45 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-06
2nd row2023-12-06
3rd row2023-12-06
4th row2023-12-06
5th row2023-12-06

Common Values

ValueCountFrequency (%)
2023-12-06 45
100.0%

Length

2024-03-14T18:40:25.454646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:40:25.767001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-06 45
100.0%

Interactions

2024-03-14T18:40:18.750860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:17.406093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:18.054309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:18.981895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:17.626595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:18.284293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:19.213631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:17.820063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:40:18.511862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:40:25.958889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
봉투종류발주단가도매단가소매단가
봉투종류1.0001.0001.0001.000
발주단가1.0001.0000.7460.781
도매단가1.0000.7461.0001.000
소매단가1.0000.7811.0001.000
2024-03-14T18:40:26.208473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주단가도매단가소매단가
발주단가1.0000.8960.898
도매단가0.8961.0001.000
소매단가0.8981.0001.000

Missing values

2024-03-14T18:40:19.549821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:40:19.953970image/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

지역코드봉투종류발주단가도매단가소매단가사용여부데이터기준일자
0110308일반용 5L31148160Y2023-12-06
1110308일반용 10L38285310Y2023-12-06
2110308일반용 20L57571620Y2023-12-06
3110308일반용 50L12414171540Y2023-12-06
4110308불연성 10L38285310Y2023-12-06
5110308불연성 20L57571620Y2023-12-06
6110308불연성 50L12414171540Y2023-12-06
7110308일반용 5L(청라)31148160Y2023-12-06
8110308일반용 10L(청라)38285310Y2023-12-06
9110308일반용 20L(청라)57571620Y2023-12-06
지역코드봉투종류발주단가도매단가소매단가사용여부데이터기준일자
35110308스티커 1000원권(청라)1909211000Y2023-12-06
36110308스티커 3000원권(청라)19027633000Y2023-12-06
37110308스티커 5000원권(청라)19046055000Y2023-12-06
38110308스티커 10000원권(청라)190921010000Y2023-12-06
39110308재사용 10L41285310Y2023-12-06
40110308재사용 20L58571620Y2023-12-06
41110308재사용 20L(청라)58571620Y2023-12-06
42110308재사용 5L33148160Y2023-12-06
43110308재사용 5L(청라)33148160Y2023-12-06
44110308재사용 10L(청라)41285310Y2023-12-06