Overview

Dataset statistics

Number of variables8
Number of observations117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory70.1 B

Variable types

Numeric4
Categorical2
Text1
Boolean1

Dataset

Description인천광역시 중구 관내에 위치한 쓰레기종량제봉투 단가에 대한 데이터 입니다. 파일명 인천광역시_중구_쓰레기종량제봉투_단가 파일내용 쓰레기종량제봉투시스템 지역코드, 봉투종류, 단가, 사용여부 등
URLhttps://www.data.go.kr/data/15060079/fileData.do

Alerts

지역코드 has constant value ""Constant
사용여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
도매단가 is highly overall correlated with 소매단가High correlation
소매단가 is highly overall correlated with 도매단가High correlation
연번 has unique valuesUnique
도매단가 has 17 (14.5%) zerosZeros
소매단가 has 17 (14.5%) zerosZeros

Reproduction

Analysis started2023-12-12 08:03:51.814339
Analysis finished2023-12-12 08:03:54.731205
Duration2.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:03:54.822255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.8
Q130
median59
Q388
95-th percentile111.2
Maximum117
Range116
Interquartile range (IQR)58

Descriptive statistics

Standard deviation33.919021
Coefficient of variation (CV)0.57489866
Kurtosis-1.2
Mean59
Median Absolute Deviation (MAD)29
Skewness0
Sum6903
Variance1150.5
MonotonicityStrictly increasing
2023-12-12T17:03:55.045069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
75 1
 
0.9%
87 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
117 1
0.9%
116 1
0.9%
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%

지역코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
110301
117 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row110301
2nd row110301
3rd row110301
4th row110301
5th row110301

Common Values

ValueCountFrequency (%)
110301 117
100.0%

Length

2023-12-12T17:03:55.212867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:03:55.317186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
110301 117
100.0%

봉투종류
Text

Distinct70
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T17:03:55.492540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length9.9487179
Min length6

Characters and Unicode

Total characters1164
Distinct characters66
Distinct categories7 ?
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 (%)19.7%

Sample

1st row일반용 5L
2nd row일반용 5L
3rd row일반용 10L
4th row일반용 10L
5th row일반용 20L
ValueCountFrequency (%)
음식물 52
19.5%
일반용 20
 
7.5%
필증 14
 
5.3%
용기 14
 
5.3%
재활용 13
 
4.9%
10l 10
 
3.8%
20l 10
 
3.8%
100l 8
 
3.0%
60l 8
 
3.0%
5l 8
 
3.0%
Other values (46) 109
41.0%
2023-12-12T17:03:55.884315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
12.8%
0 111
 
9.5%
L 109
 
9.4%
용 71
 
6.1%
물 54
 
4.6%
음 52
 
4.5%
식 52
 
4.5%
( 43
 
3.7%
) 43
 
3.7%
1 37
 
3.2%
Other values (56) 443
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 571
49.1%
Decimal Number 234
20.1%
Space Separator 149
 
12.8%
Uppercase Letter 118
 
10.1%
Open Punctuation 43
 
3.7%
Close Punctuation 43
 
3.7%
Other Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 71
 
12.4%
물 54
 
9.5%
음 52
 
9.1%
식 52
 
9.1%
종 25
 
4.4%
영 22
 
3.9%
일 20
 
3.5%
반 20
 
3.5%
재 19
 
3.3%
기 18
 
3.2%
Other values (41) 218
38.2%
Decimal Number
ValueCountFrequency (%)
0 111
47.4%
1 37
 
15.8%
5 34
 
14.5%
2 26
 
11.1%
3 16
 
6.8%
6 8
 
3.4%
7 2
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
L 109
92.4%
T 3
 
2.5%
E 3
 
2.5%
P 3
 
2.5%
Space Separator
ValueCountFrequency (%)
149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 571
49.1%
Common 475
40.8%
Latin 118
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 71
 
12.4%
물 54
 
9.5%
음 52
 
9.1%
식 52
 
9.1%
종 25
 
4.4%
영 22
 
3.9%
일 20
 
3.5%
반 20
 
3.5%
재 19
 
3.3%
기 18
 
3.2%
Other values (41) 218
38.2%
Common
ValueCountFrequency (%)
149
31.4%
0 111
23.4%
( 43
 
9.1%
) 43
 
9.1%
1 37
 
7.8%
5 34
 
7.2%
2 26
 
5.5%
3 16
 
3.4%
6 8
 
1.7%
, 6
 
1.3%
Latin
ValueCountFrequency (%)
L 109
92.4%
T 3
 
2.5%
E 3
 
2.5%
P 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 593
50.9%
Hangul 571
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
25.1%
0 111
18.7%
L 109
18.4%
( 43
 
7.3%
) 43
 
7.3%
1 37
 
6.2%
5 34
 
5.7%
2 26
 
4.4%
3 16
 
2.7%
6 8
 
1.3%
Other values (5) 17
 
2.9%
Hangul
ValueCountFrequency (%)
용 71
 
12.4%
물 54
 
9.5%
음 52
 
9.1%
식 52
 
9.1%
종 25
 
4.4%
영 22
 
3.9%
일 20
 
3.5%
반 20
 
3.5%
재 19
 
3.3%
기 18
 
3.2%
Other values (41) 218
38.2%

발주단가
Real number (ℝ)

Distinct33
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1865.4831
Minimum24.26
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:03:56.040383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.26
5-th percentile29.32
Q134.42
median64.13
Q3218.28
95-th percentile9988
Maximum40000
Range39975.74
Interquartile range (IQR)183.86

Descriptive statistics

Standard deviation6689.6744
Coefficient of variation (CV)3.5860279
Kurtosis21.93396
Mean1865.4831
Median Absolute Deviation (MAD)34.81
Skewness4.6387018
Sum218261.52
Variance44751744
MonotonicityNot monotonic
2023-12-12T17:03:56.199216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
30.0 14
 
12.0%
41.64 10
 
8.5%
62.11 6
 
5.1%
34.42 6
 
5.1%
29.32 6
 
5.1%
24.26 4
 
3.4%
230.0 4
 
3.4%
149.0 4
 
3.4%
95.0 4
 
3.4%
64.13 4
 
3.4%
Other values (23) 55
47.0%
ValueCountFrequency (%)
24.26 4
 
3.4%
29.32 6
5.1%
30.0 14
12.0%
31.42 4
 
3.4%
34.42 6
5.1%
38.0 1
 
0.9%
38.65 2
 
1.7%
41.64 10
8.5%
43.9 2
 
1.7%
62.11 6
5.1%
ValueCountFrequency (%)
40000.0 2
1.7%
30000.0 2
1.7%
12740.0 2
1.7%
9300.0 2
1.7%
4300.0 2
1.7%
3980.0 2
1.7%
3900.0 2
1.7%
450.0 2
1.7%
276.0 2
1.7%
230.0 4
3.4%

도매단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2938.3761
Minimum0
Maximum40000
Zeros17
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:03:56.352778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1165
median570
Q33300
95-th percentile10180
Maximum40000
Range40000
Interquartile range (IQR)3135

Descriptive statistics

Standard deviation6660.7298
Coefficient of variation (CV)2.2668064
Kurtosis19.408905
Mean2938.3761
Median Absolute Deviation (MAD)570
Skewness4.2496833
Sum343790
Variance44365321
MonotonicityNot monotonic
2023-12-12T17:03:56.488044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 17
 
14.5%
165 8
 
6.8%
570 8
 
6.8%
550 8
 
6.8%
275 8
 
6.8%
110 6
 
5.1%
289 6
 
5.1%
4550 4
 
3.4%
910 4
 
3.4%
1100 4
 
3.4%
Other values (20) 44
37.6%
ValueCountFrequency (%)
0 17
14.5%
110 6
 
5.1%
150 4
 
3.4%
165 8
6.8%
275 8
6.8%
289 6
 
5.1%
550 8
6.8%
570 8
6.8%
910 4
 
3.4%
1100 4
 
3.4%
ValueCountFrequency (%)
40000 2
1.7%
30000 2
1.7%
12740 2
1.7%
9540 2
1.7%
9300 2
1.7%
6600 2
1.7%
4850 2
1.7%
4550 4
3.4%
4300 2
1.7%
3980 2
1.7%

소매단가
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3203.2479
Minimum0
Maximum43600
Zeros17
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:03:56.630858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1180
median620
Q33600
95-th percentile11096
Maximum43600
Range43600
Interquartile range (IQR)3420

Descriptive statistics

Standard deviation7260.452
Coefficient of variation (CV)2.2665908
Kurtosis19.40449
Mean3203.2479
Median Absolute Deviation (MAD)620
Skewness4.2489438
Sum374780
Variance52714163
MonotonicityNot monotonic
2023-12-12T17:03:56.798260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 17
 
14.5%
180 8
 
6.8%
620 8
 
6.8%
600 8
 
6.8%
300 8
 
6.8%
120 6
 
5.1%
310 6
 
5.1%
5000 4
 
3.4%
1000 4
 
3.4%
1200 4
 
3.4%
Other values (20) 44
37.6%
ValueCountFrequency (%)
0 17
14.5%
120 6
 
5.1%
160 4
 
3.4%
180 8
6.8%
300 8
6.8%
310 6
 
5.1%
600 8
6.8%
620 8
6.8%
1000 4
 
3.4%
1200 4
 
3.4%
ValueCountFrequency (%)
43600 2
1.7%
32700 2
1.7%
13880 2
1.7%
10400 2
1.7%
10130 2
1.7%
7200 2
1.7%
5290 2
1.7%
5000 4
3.4%
4680 2
1.7%
4330 2
1.7%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size249.0 B
True
117 
ValueCountFrequency (%)
True 117
100.0%
2023-12-12T17:03:56.915029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-08-29
117 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-29
2nd row2023-08-29
3rd row2023-08-29
4th row2023-08-29
5th row2023-08-29

Common Values

ValueCountFrequency (%)
2023-08-29 117
100.0%

Length

2023-12-12T17:03:57.033202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:03:57.145134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-29 117
100.0%

Interactions

2023-12-12T17:03:53.981441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.049185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.570890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:53.111346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:54.098453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.176235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.704179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:53.243665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:54.236020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.329400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.824326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:53.725490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:54.347917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.445406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:52.977321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:03:53.859272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:03:57.218806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번봉투종류발주단가도매단가소매단가
연번1.0001.0000.5390.5520.552
봉투종류1.0001.0001.0001.0001.000
발주단가0.5391.0001.0000.9900.990
도매단가0.5521.0000.9901.0001.000
소매단가0.5521.0000.9901.0001.000
2023-12-12T17:03:57.334980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발주단가도매단가소매단가
연번1.0000.215-0.066-0.065
발주단가0.2151.0000.4620.463
도매단가-0.0660.4621.0001.000
소매단가-0.0650.4631.0001.000

Missing values

2023-12-12T17:03:54.492187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:03:54.665038image/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

연번지역코드봉투종류발주단가도매단가소매단가사용여부데이터기준일자
01110301일반용 5L31.42150160Y2023-08-29
12110301일반용 5L31.42150160Y2023-08-29
23110301일반용 10L41.64289310Y2023-08-29
34110301일반용 10L41.64289310Y2023-08-29
45110301일반용 20L62.11570620Y2023-08-29
56110301일반용 20L62.11570620Y2023-08-29
67110301일반용 50L129.7314181540Y2023-08-29
78110301일반용 50L129.7314181540Y2023-08-29
89110301일반용 75L124.9121212300Y2023-08-29
910110301일반용 75L124.9121212300Y2023-08-29
연번지역코드봉투종류발주단가도매단가소매단가사용여부데이터기준일자
107108110301재활용 100L(비닐류)230.000Y2023-08-29
108109110301재활용 30L(투명PET)95.000Y2023-08-29
109110110301재활용 50L(투명PET)149.000Y2023-08-29
110111110301재활용 100L(투명PET)230.000Y2023-08-29
111112110301재활용 30L(종이류)95.000Y2023-08-29
112113110301재활용 50L(종이류)149.000Y2023-08-29
113114110301재활용 100L(종이류)230.000Y2023-08-29
114115110301재활용 30L(캔,유리,플라스틱류)95.000Y2023-08-29
115116110301재활용 50L(캔,유리,플라스틱류)149.000Y2023-08-29
116117110301재활용 100L(캔,유리,플라스틱)230.000Y2023-08-29