Overview

Dataset statistics

Number of variables7
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory63.1 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://data.incheon.go.kr/findData/publicDataDetail?dataId=15090804&srcSe=7661IVAWM27C61E190

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 started2024-03-18 04:50:36.061047
Analysis finished2024-03-18 04:50:37.443325
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
110308
42 

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 42
100.0%

Length

2024-03-18T13:50:37.489800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:50:37.563344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
110308 42
100.0%

봉투종류
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-03-18T13:50:37.726835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.2380952
Min length5

Characters and Unicode

Total characters388
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

Unique42 ?
Unique (%)100.0%

Sample

1st row일반용 5L
2nd row일반용 10L
3rd row일반용 20L
4th row일반용 50L
5th row불연성 10L
ValueCountFrequency (%)
음식물 10
 
11.8%
스티커 9
 
10.6%
필증 8
 
9.4%
일반용 7
 
8.2%
불연성 3
 
3.5%
10l 3
 
3.5%
사업계용 3
 
3.5%
재사용 3
 
3.5%
20l 3
 
3.5%
60l 2
 
2.4%
Other values (28) 34
40.0%
2024-03-18T13:50:38.021087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
 
11.3%
43
 
11.1%
L 34
 
8.8%
( 20
 
5.2%
) 20
 
5.2%
용 17
 
4.4%
청 13
 
3.4%
1 13
 
3.4%
2 13
 
3.4%
라 13
 
3.4%
Other values (27) 158
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
46.6%
Decimal Number 90
23.2%
Space Separator 43
 
11.1%
Uppercase Letter 34
 
8.8%
Open Punctuation 20
 
5.2%
Close Punctuation 20
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 17
 
9.4%
청 13
 
7.2%
라 13
 
7.2%
음 10
 
5.5%
식 10
 
5.5%
물 10
 
5.5%
티 9
 
5.0%
스 9
 
5.0%
커 9
 
5.0%
권 8
 
4.4%
Other values (17) 73
40.3%
Decimal Number
ValueCountFrequency (%)
0 44
48.9%
1 13
 
14.4%
2 13
 
14.4%
5 11
 
12.2%
3 7
 
7.8%
6 2
 
2.2%
Space Separator
ValueCountFrequency (%)
43
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181
46.6%
Common 173
44.6%
Latin 34
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 17
 
9.4%
청 13
 
7.2%
라 13
 
7.2%
음 10
 
5.5%
식 10
 
5.5%
물 10
 
5.5%
티 9
 
5.0%
스 9
 
5.0%
커 9
 
5.0%
권 8
 
4.4%
Other values (17) 73
40.3%
Common
ValueCountFrequency (%)
0 44
25.4%
43
24.9%
( 20
11.6%
) 20
11.6%
1 13
 
7.5%
2 13
 
7.5%
5 11
 
6.4%
3 7
 
4.0%
6 2
 
1.2%
Latin
ValueCountFrequency (%)
L 34
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 207
53.4%
Hangul 181
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
21.3%
43
20.8%
L 34
16.4%
( 20
9.7%
) 20
9.7%
1 13
 
6.3%
2 13
 
6.3%
5 11
 
5.3%
3 7
 
3.4%
6 2
 
1.0%
Hangul
ValueCountFrequency (%)
용 17
 
9.4%
청 13
 
7.2%
라 13
 
7.2%
음 10
 
5.5%
식 10
 
5.5%
물 10
 
5.5%
티 9
 
5.0%
스 9
 
5.0%
커 9
 
5.0%
권 8
 
4.4%
Other values (17) 73
40.3%

발주단가
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean376.28571
Minimum18
Maximum4300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-03-18T13:50:38.121792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile22.05
Q132.75
median57
Q3190
95-th percentile3729.3
Maximum4300
Range4282
Interquartile range (IQR)157.25

Descriptive statistics

Standard deviation1039.1738
Coefficient of variation (CV)2.7616617
Kurtosis10.332067
Mean376.28571
Median Absolute Deviation (MAD)34
Skewness3.4197199
Sum15804
Variance1079882.3
MonotonicityNot monotonic
2024-03-18T13:50:38.245031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
190 8
19.0%
23 4
9.5%
57 4
9.5%
38 4
9.5%
31 3
 
7.1%
41 3
 
7.1%
58 2
 
4.8%
22 2
 
4.8%
42 2
 
4.8%
124 2
 
4.8%
Other values (8) 8
19.0%
ValueCountFrequency (%)
18 1
 
2.4%
22 2
4.8%
23 4
9.5%
25 1
 
2.4%
31 3
7.1%
38 4
9.5%
41 3
7.1%
42 2
4.8%
57 4
9.5%
58 2
4.8%
ValueCountFrequency (%)
4300 1
 
2.4%
3980 1
 
2.4%
3900 1
 
2.4%
486 1
 
2.4%
256 1
 
2.4%
190 8
19.0%
139 1
 
2.4%
124 2
 
4.8%
58 2
 
4.8%
57 4
9.5%

도매단가
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1983.8571
Minimum56
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-03-18T13:50:38.362738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile112
Q1279.75
median713.5
Q33201.75
95-th percentile7032.3
Maximum9210
Range9154
Interquartile range (IQR)2922

Descriptive statistics

Standard deviation2483.7188
Coefficient of variation (CV)1.2519645
Kurtosis1.9513467
Mean1983.8571
Median Absolute Deviation (MAD)586
Skewness1.6065313
Sum83322
Variance6168859
MonotonicityNot monotonic
2024-03-18T13:50:38.475829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
571 5
 
11.9%
285 4
 
9.5%
148 2
 
4.8%
1417 2
 
4.8%
9210 2
 
4.8%
4605 2
 
4.8%
2763 2
 
4.8%
921 2
 
4.8%
112 2
 
4.8%
168 2
 
4.8%
Other values (16) 17
40.5%
ValueCountFrequency (%)
56 1
 
2.4%
86 1
 
2.4%
112 2
 
4.8%
143 1
 
2.4%
148 2
 
4.8%
168 2
 
4.8%
278 2
 
4.8%
285 4
9.5%
552 1
 
2.4%
571 5
11.9%
ValueCountFrequency (%)
9210 2
4.8%
7050 1
2.4%
6696 1
2.4%
4605 2
4.8%
4600 1
2.4%
4300 1
2.4%
4000 1
2.4%
3420 1
2.4%
3348 1
2.4%
2763 2
4.8%

소매단가
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2155.5476
Minimum60
Maximum10000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-03-18T13:50:38.589751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile120
Q1302.5
median775
Q33450
95-th percentile7637
Maximum10000
Range9940
Interquartile range (IQR)3147.5

Descriptive statistics

Standard deviation2697.8135
Coefficient of variation (CV)1.2515676
Kurtosis1.9282264
Mean2155.5476
Median Absolute Deviation (MAD)637.5
Skewness1.6006108
Sum90533
Variance7278197.7
MonotonicityNot monotonic
2024-03-18T13:50:38.901855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
620 5
 
11.9%
310 4
 
9.5%
160 2
 
4.8%
1540 2
 
4.8%
10000 2
 
4.8%
5000 2
 
4.8%
3000 2
 
4.8%
1000 2
 
4.8%
120 2
 
4.8%
180 2
 
4.8%
Other values (16) 17
40.5%
ValueCountFrequency (%)
60 1
 
2.4%
93 1
 
2.4%
120 2
 
4.8%
155 1
 
2.4%
160 2
 
4.8%
180 2
 
4.8%
300 2
 
4.8%
310 4
9.5%
600 1
 
2.4%
620 5
11.9%
ValueCountFrequency (%)
10000 2
4.8%
7660 1
2.4%
7200 1
2.4%
5060 1
2.4%
5000 2
4.8%
4730 1
2.4%
4400 1
2.4%
3710 1
2.4%
3600 1
2.4%
3000 2
4.8%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size174.0 B
True
42 
ValueCountFrequency (%)
True 42
100.0%
2024-03-18T13:50:38.995178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2022-09-06
42 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-06
2nd row2022-09-06
3rd row2022-09-06
4th row2022-09-06
5th row2022-09-06

Common Values

ValueCountFrequency (%)
2022-09-06 42
100.0%

Length

2024-03-18T13:50:39.072747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:50:39.166644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-06 42
100.0%

Interactions

2024-03-18T13:50:37.016813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.652000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.833613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:37.084098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.710775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.895175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:37.177526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.771344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:36.954830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:50:39.235038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
봉투종류발주단가도매단가소매단가
봉투종류1.0001.0001.0001.000
발주단가1.0001.0000.7420.777
도매단가1.0000.7421.0001.000
소매단가1.0000.7771.0001.000
2024-03-18T13:50:39.335141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주단가도매단가소매단가
발주단가1.0000.8830.885
도매단가0.8831.0001.000
소매단가0.8851.0001.000

Missing values

2024-03-18T13:50:37.310581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:50:37.406702image/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 5L31148160Y2022-09-06
1110308일반용 10L38285310Y2022-09-06
2110308일반용 20L57571620Y2022-09-06
3110308일반용 50L12414171540Y2022-09-06
4110308불연성 10L38285310Y2022-09-06
5110308불연성 20L57571620Y2022-09-06
6110308불연성 50L12414171540Y2022-09-06
7110308일반용 5L(청라)31148160Y2022-09-06
8110308일반용 10L(청라)38285310Y2022-09-06
9110308일반용 20L(청라)57571620Y2022-09-06
지역코드봉투종류발주단가도매단가소매단가사용여부데이터기준일자
32110308스티커 3000원권19027633000Y2022-09-06
33110308스티커 5000원권19046055000Y2022-09-06
34110308스티커 10000원권190921010000Y2022-09-06
35110308스티커 1000원권(청라)1909211000Y2022-09-06
36110308스티커 3000원권(청라)19027633000Y2022-09-06
37110308스티커 5000원권(청라)19046055000Y2022-09-06
38110308스티커 10000원권(청라)190921010000Y2022-09-06
39110308재사용 10L41285310Y2022-09-06
40110308재사용 20L58571620Y2022-09-06
41110308재사용 20L(청라)58571620Y2022-09-06