Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory97.3 B

Variable types

Categorical6
Numeric5

Alerts

배출년도 has constant value ""Constant
배출월 has constant value ""Constant
지자체 시군구명 is highly overall correlated with 일평균배출량(g) and 4 other fieldsHigh correlation
지자체코드 is highly overall correlated with 일평균배출량(g) and 4 other fieldsHigh correlation
지자체 시도명 is highly overall correlated with 지자체코드 and 1 other fieldsHigh correlation
배출요일 is highly overall correlated with 요일갯수High correlation
배출량(g) is highly overall correlated with 일평균배출량(g) and 2 other fieldsHigh correlation
일평균배출량(g) is highly overall correlated with 배출량(g) and 4 other fieldsHigh correlation
배출횟수 is highly overall correlated with 배출량(g) and 4 other fieldsHigh correlation
일평균배출횟수 is highly overall correlated with 배출량(g) and 4 other fieldsHigh correlation
요일갯수 is highly overall correlated with 배출요일High correlation
지자체 시도명 is highly imbalanced (82.7%)Imbalance
배출량(g) has unique valuesUnique
일평균배출량(g) has unique valuesUnique
배출횟수 has unique valuesUnique
일평균배출횟수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:12:16.917092
Analysis finished2023-12-10 13:12:21.913546
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

배출년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2023-12-10T22:12:22.018676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:12:22.183941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

배출월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

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 (%)
1 100
100.0%

Length

2023-12-10T22:12:22.336503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:12:22.494732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
100.0%

배출요일
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.99
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:12:22.634815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.972001
Coefficient of variation (CV)0.49423584
Kurtosis-1.2023594
Mean3.99
Median Absolute Deviation (MAD)2
Skewness-0.018077821
Sum399
Variance3.8887879
MonotonicityNot monotonic
2023-12-10T22:12:22.784864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 16
16.0%
4 15
15.0%
6 14
14.0%
1 14
14.0%
2 14
14.0%
3 14
14.0%
7 13
13.0%
ValueCountFrequency (%)
1 14
14.0%
2 14
14.0%
3 14
14.0%
4 15
15.0%
5 16
16.0%
6 14
14.0%
7 13
13.0%
ValueCountFrequency (%)
7 13
13.0%
6 14
14.0%
5 16
16.0%
4 15
15.0%
3 14
14.0%
2 14
14.0%
1 14
14.0%

요일갯수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
4
58 
5
42 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
4 58
58.0%
5 42
42.0%

Length

2023-12-10T22:12:23.029738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:12:23.170941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 58
58.0%
5 42
42.0%

지자체코드
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
W01
7 
W02
7 
W03
7 
W04
7 
W05
7 
Other values (11)
65 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st rowW3L
2nd rowW3L
3rd rowW01
4th rowW01
5th rowW01

Common Values

ValueCountFrequency (%)
W01 7
 
7.0%
W02 7
 
7.0%
W03 7
 
7.0%
W04 7
 
7.0%
W05 7
 
7.0%
W06 7
 
7.0%
W07 7
 
7.0%
W08 7
 
7.0%
W09 7
 
7.0%
W0A 7
 
7.0%
Other values (6) 30
30.0%

Length

2023-12-10T22:12:23.354211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
w01 7
 
7.0%
w02 7
 
7.0%
w03 7
 
7.0%
w04 7
 
7.0%
w05 7
 
7.0%
w06 7
 
7.0%
w07 7
 
7.0%
w08 7
 
7.0%
w09 7
 
7.0%
w0a 7
 
7.0%
Other values (6) 30
30.0%

지자체 시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
96 
강원도
 
3
경기도
 
1

Length

Max length5
Median length5
Mean length4.92
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row강원도
2nd row강원도
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 96
96.0%
강원도 3
 
3.0%
경기도 1
 
1.0%

Length

2023-12-10T22:12:23.672123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:12:23.842577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 96
96.0%
강원도 3
 
3.0%
경기도 1
 
1.0%

지자체 시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
7 
중구
7 
용산구
7 
성동구
7 
광진구
7 
Other values (11)
65 

Length

Max length4
Median length3
Mean length3.07
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row영월군
2nd row영월군
3rd row종로구
4th row종로구
5th row종로구

Common Values

ValueCountFrequency (%)
종로구 7
 
7.0%
중구 7
 
7.0%
용산구 7
 
7.0%
성동구 7
 
7.0%
광진구 7
 
7.0%
동대문구 7
 
7.0%
중랑구 7
 
7.0%
성북구 7
 
7.0%
강북구 7
 
7.0%
도봉구 7
 
7.0%
Other values (6) 30
30.0%

Length

2023-12-10T22:12:24.034994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로구 7
 
7.0%
중구 7
 
7.0%
용산구 7
 
7.0%
성동구 7
 
7.0%
광진구 7
 
7.0%
동대문구 7
 
7.0%
중랑구 7
 
7.0%
성북구 7
 
7.0%
강북구 7
 
7.0%
도봉구 7
 
7.0%
Other values (6) 30
30.0%

배출량(g)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69210933
Minimum6500
Maximum3.0350655 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:12:24.290264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6500
5-th percentile2096020
Q123205062
median42641960
Q379188125
95-th percentile2.3813822 × 108
Maximum3.0350655 × 108
Range3.0350005 × 108
Interquartile range (IQR)55983062

Descriptive statistics

Standard deviation70805531
Coefficient of variation (CV)1.0230397
Kurtosis1.6462811
Mean69210933
Median Absolute Deviation (MAD)29763195
Skewness1.5561896
Sum6.9210933 × 109
Variance5.0134232 × 1015
MonotonicityNot monotonic
2023-12-10T22:12:24.525700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23150 1
 
1.0%
12774990 1
 
1.0%
206555099 1
 
1.0%
215680550 1
 
1.0%
172290750 1
 
1.0%
237422450 1
 
1.0%
257309550 1
 
1.0%
201328960 1
 
1.0%
237851100 1
 
1.0%
303506550 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
6500 1
1.0%
11550 1
1.0%
23150 1
1.0%
1930050 1
1.0%
2059350 1
1.0%
2097950 1
1.0%
2192600 1
1.0%
2479400 1
1.0%
2485100 1
1.0%
2775950 1
1.0%
ValueCountFrequency (%)
303506550 1
1.0%
257309550 1
1.0%
251131750 1
1.0%
249014099 1
1.0%
243593449 1
1.0%
237851100 1
1.0%
237422450 1
1.0%
215680550 1
1.0%
206555099 1
1.0%
201328960 1
1.0%

일평균배출량(g)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15844489
Minimum1625
Maximum64327388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:12:24.828665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1625
5-th percentile437573.5
Q14674072.5
median10438589
Q319435141
95-th percentile59422898
Maximum64327388
Range64325763
Interquartile range (IQR)14761068

Descriptive statistics

Standard deviation16436761
Coefficient of variation (CV)1.0373804
Kurtosis1.8234582
Mean15844489
Median Absolute Deviation (MAD)7230507.5
Skewness1.6059084
Sum1.5844489 × 109
Variance2.7016712 × 1014
MonotonicityNot monotonic
2023-12-10T22:12:25.047531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5788 1
 
1.0%
3193748 1
 
1.0%
41311020 1
 
1.0%
43136110 1
 
1.0%
43072688 1
 
1.0%
59355613 1
 
1.0%
64327388 1
 
1.0%
50332240 1
 
1.0%
47570220 1
 
1.0%
60701310 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1625 1
1.0%
2888 1
1.0%
5788 1
1.0%
411870 1
1.0%
419590 1
1.0%
438520 1
1.0%
482513 1
1.0%
619850 1
1.0%
621275 1
1.0%
693988 1
1.0%
ValueCountFrequency (%)
64327388 1
1.0%
62782938 1
1.0%
62253525 1
1.0%
60898362 1
1.0%
60701310 1
1.0%
59355613 1
1.0%
50332240 1
1.0%
47570220 1
1.0%
46153788 1
1.0%
43136110 1
1.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40480.53
Minimum3
Maximum175908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:12:25.288233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1526.4
Q114192.5
median27541
Q353307
95-th percentile132684.55
Maximum175908
Range175905
Interquartile range (IQR)39114.5

Descriptive statistics

Standard deviation39113.425
Coefficient of variation (CV)0.96622809
Kurtosis3.2458364
Mean40480.53
Median Absolute Deviation (MAD)18950
Skewness1.758784
Sum4048053
Variance1.52986 × 109
MonotonicityNot monotonic
2023-12-10T22:12:25.583921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 1
 
1.0%
8230 1
 
1.0%
138965 1
 
1.0%
141210 1
 
1.0%
65811 1
 
1.0%
91268 1
 
1.0%
92630 1
 
1.0%
89846 1
 
1.0%
68371 1
 
1.0%
75632 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
3 1
1.0%
8 1
1.0%
18 1
1.0%
1387 1
1.0%
1439 1
1.0%
1531 1
1.0%
1562 1
1.0%
1777 1
1.0%
1833 1
1.0%
1941 1
1.0%
ValueCountFrequency (%)
175908 1
1.0%
175715 1
1.0%
173382 1
1.0%
141210 1
1.0%
138965 1
1.0%
132354 1
1.0%
125180 1
1.0%
92630 1
1.0%
91268 1
1.0%
89846 1
1.0%

일평균배출횟수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9299.17
Minimum1
Maximum43977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:12:25.824551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile311.7
Q13271
median6714.5
Q313108.25
95-th percentile27815.45
Maximum43977
Range43976
Interquartile range (IQR)9837.25

Descriptive statistics

Standard deviation9254.6044
Coefficient of variation (CV)0.99520757
Kurtosis4.333559
Mean9299.17
Median Absolute Deviation (MAD)4657
Skewness1.9371654
Sum929917
Variance85647702
MonotonicityNot monotonic
2023-12-10T22:12:26.045377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
1.0%
2058 1
 
1.0%
27793 1
 
1.0%
28242 1
 
1.0%
16453 1
 
1.0%
22817 1
 
1.0%
23158 1
 
1.0%
22462 1
 
1.0%
13674 1
 
1.0%
15126 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
5 1
1.0%
288 1
1.0%
306 1
1.0%
312 1
1.0%
347 1
1.0%
444 1
1.0%
458 1
1.0%
485 1
1.0%
ValueCountFrequency (%)
43977 1
1.0%
43929 1
1.0%
43346 1
1.0%
31295 1
1.0%
28242 1
1.0%
27793 1
1.0%
26471 1
1.0%
23158 1
1.0%
22817 1
1.0%
22462 1
1.0%

Interactions

2023-12-10T22:12:20.783139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:17.638130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:18.340741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.368056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.059699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.948307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:17.793563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:18.476660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.511158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.198132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:21.089640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:17.934877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:18.615640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.647792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.368929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:21.231313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:18.075344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.095954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.781087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.507322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:21.361689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:18.225662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.243546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:19.923538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:12:20.650894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:12:26.193776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출요일요일갯수지자체코드지자체 시도명지자체 시군구명배출량(g)일평균배출량(g)배출횟수일평균배출횟수
배출요일1.0001.0000.0000.0000.0000.0000.0000.0000.000
요일갯수1.0001.0000.0000.0610.0000.2730.0000.2320.227
지자체코드0.0000.0001.0001.0001.0000.8230.8240.8740.822
지자체 시도명0.0000.0611.0001.0001.0000.0000.0000.0000.000
지자체 시군구명0.0000.0001.0001.0001.0000.8230.8240.8740.822
배출량(g)0.0000.2730.8230.0000.8231.0000.9250.9110.876
일평균배출량(g)0.0000.0000.8240.0000.8240.9251.0000.9610.974
배출횟수0.0000.2320.8740.0000.8740.9110.9611.0000.986
일평균배출횟수0.0000.2270.8220.0000.8220.8760.9740.9861.000
2023-12-10T22:12:26.400603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드지자체 시도명요일갯수
지자체 시군구명1.0001.0000.9310.000
지자체코드1.0001.0000.9310.000
지자체 시도명0.9310.9311.0000.100
요일갯수0.0000.0000.1001.000
2023-12-10T22:12:26.557301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출요일배출량(g)일평균배출량(g)배출횟수일평균배출횟수요일갯수지자체코드지자체 시도명지자체 시군구명
배출요일1.000-0.0580.032-0.0520.0410.9740.0000.0000.000
배출량(g)-0.0581.0000.9930.9930.9850.1980.4890.0000.489
일평균배출량(g)0.0320.9931.0000.9890.9940.0000.5070.0000.507
배출횟수-0.0520.9930.9891.0000.9920.2210.5870.0000.587
일평균배출횟수0.0410.9850.9940.9921.0000.2160.5010.0000.501
요일갯수0.9740.1980.0000.2210.2161.0000.0000.1000.000
지자체코드0.0000.4890.5070.5870.5010.0001.0000.9311.000
지자체 시도명0.0000.0000.0000.0000.0000.1000.9311.0000.931
지자체 시군구명0.0000.4890.5070.5870.5010.0001.0000.9311.000

Missing values

2023-12-10T22:12:21.559844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:12:21.812433image/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

배출년도배출월배출요일요일갯수지자체코드지자체 시도명지자체 시군구명배출량(g)일평균배출량(g)배출횟수일평균배출횟수
02020154W3L강원도영월군231505788185
12020164W3L강원도영월군11550288882
22020115W01서울특별시종로구14549950290999090961819
32020125W01서울특별시종로구15509850310197097601952
42020135W01서울특별시종로구14509450290189093461869
52020144W01서울특별시종로구176610004415250115862897
62020154W01서울특별시종로구172329504308238116502913
72020164W01서울특별시종로구177637504440938117532938
82020174W01서울특별시종로구12772300319307582262057
92020115W02서울특별시중구313168006263360213944279
배출년도배출월배출요일요일갯수지자체코드지자체 시도명지자체 시군구명배출량(g)일평균배출량(g)배출횟수일평균배출횟수
902020144W0D서울특별시서대문구85171900212929755920814802
912020154W0D서울특별시서대문구80797850201994635611914030
922020164W0D서울특별시서대문구77436900193592255372113430
932020174W0D서울특별시서대문구5797350014493375381889547
942020115W0E서울특별시마포구142301150284602307813515627
952020125W0E서울특별시마포구115425350230850707064514129
962020135W0E서울특별시마포구130751150261502306523513047
972020144W0E서울특별시마포구151758999379397508648321621
982020154W0E서울특별시마포구151965799379914508707521769
992020144W3L강원도영월군6500162531