Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory88.3 B

Variable types

Categorical5
Numeric5

Alerts

배출년도 has constant value ""Constant
배출월 has constant value ""Constant
지자체 시도명 has constant value ""Constant
지자체 시군구명 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
지자체코드 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출시 is highly overall correlated with 배출량비율(%) and 1 other fieldsHigh correlation
배출량(g) is highly overall correlated with 배출량비율(%) and 4 other fieldsHigh correlation
배출량비율(%) is highly overall correlated with 배출시 and 3 other fieldsHigh correlation
배출횟수 is highly overall correlated with 배출량(g) and 4 other fieldsHigh correlation
배출횟수비율(%) is highly overall correlated with 배출시 and 3 other fieldsHigh correlation
배출량(g) has unique valuesUnique
배출시 has 5 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-16 22:29:15.458124
Analysis finished2024-04-16 22:29:18.048199
Duration2.59 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
2017
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 100
100.0%

Length

2024-04-17T07:29:18.095697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:18.165892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 100
100.0%

배출월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
11
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 100
100.0%

Length

2024-04-17T07:29:18.244309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:18.314128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 100
100.0%

지자체코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
W01
24 
W02
24 
W03
24 
W04
24 
W05
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
W01 24
24.0%
W02 24
24.0%
W03 24
24.0%
W04 24
24.0%
W05 4
 
4.0%

Length

2024-04-17T07:29:18.389744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:18.469003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
w01 24
24.0%
w02 24
24.0%
w03 24
24.0%
w04 24
24.0%
w05 4
 
4.0%

지자체 시도명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2024-04-17T07:29:18.563748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:18.633550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

지자체 시군구명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
24 
중구
24 
용산구
24 
성동구
24 
광진구
4 

Length

Max length3
Median length3
Mean length2.76
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 24
24.0%
중구 24
24.0%
용산구 24
24.0%
성동구 24
24.0%
광진구 4
 
4.0%

Length

2024-04-17T07:29:18.730769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:18.820253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 24
24.0%
중구 24
24.0%
용산구 24
24.0%
성동구 24
24.0%
광진구 4
 
4.0%

배출시
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.1
Minimum0
Maximum23
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:18.906597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.95
Q15
median11
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.0988689
Coefficient of variation (CV)0.63953774
Kurtosis-1.2463386
Mean11.1
Median Absolute Deviation (MAD)6
Skewness0.053106017
Sum1110
Variance50.393939
MonotonicityNot monotonic
2024-04-17T07:29:18.998010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 5
 
5.0%
3 5
 
5.0%
0 5
 
5.0%
2 5
 
5.0%
15 4
 
4.0%
23 4
 
4.0%
22 4
 
4.0%
21 4
 
4.0%
20 4
 
4.0%
19 4
 
4.0%
Other values (14) 56
56.0%
ValueCountFrequency (%)
0 5
5.0%
1 5
5.0%
2 5
5.0%
3 5
5.0%
4 4
4.0%
5 4
4.0%
6 4
4.0%
7 4
4.0%
8 4
4.0%
9 4
4.0%
ValueCountFrequency (%)
23 4
4.0%
22 4
4.0%
21 4
4.0%
20 4
4.0%
19 4
4.0%
18 4
4.0%
17 4
4.0%
16 4
4.0%
15 4
4.0%
14 4
4.0%

배출량(g)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6126012.5
Minimum5750
Maximum27719900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:19.097057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5750
5-th percentile82760
Q1354387.5
median3958475
Q310043812
95-th percentile21690635
Maximum27719900
Range27714150
Interquartile range (IQR)9689425

Descriptive statistics

Standard deviation7320168.5
Coefficient of variation (CV)1.194932
Kurtosis0.73401904
Mean6126012.5
Median Absolute Deviation (MAD)3640800
Skewness1.3006128
Sum6.1260125 × 108
Variance5.3584866 × 1013
MonotonicityNot monotonic
2024-04-17T07:29:19.211740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
388900 1
 
1.0%
344050 1
 
1.0%
528650 1
 
1.0%
763900 1
 
1.0%
1940700 1
 
1.0%
4949300 1
 
1.0%
280500 1
 
1.0%
327150 1
 
1.0%
449900 1
 
1.0%
420050 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
5750 1
1.0%
9950 1
1.0%
18950 1
1.0%
21450 1
1.0%
31650 1
1.0%
85450 1
1.0%
97850 1
1.0%
133150 1
1.0%
140100 1
1.0%
182450 1
1.0%
ValueCountFrequency (%)
27719900 1
1.0%
26406600 1
1.0%
25509400 1
1.0%
22717550 1
1.0%
22171050 1
1.0%
21665350 1
1.0%
20493300 1
1.0%
20223800 1
1.0%
19657700 1
1.0%
19369950 1
1.0%

배출량비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0215
Minimum0.08
Maximum7.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:19.334219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.08
5-th percentile0.17
Q11.1775
median4.955
Q36.0525
95-th percentile7.5105
Maximum7.95
Range7.87
Interquartile range (IQR)4.875

Descriptive statistics

Standard deviation2.5814965
Coefficient of variation (CV)0.64192378
Kurtosis-1.3940068
Mean4.0215
Median Absolute Deviation (MAD)1.595
Skewness-0.38171451
Sum402.15
Variance6.664124
MonotonicityNot monotonic
2024-04-17T07:29:19.469768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.9 3
 
3.0%
0.47 2
 
2.0%
5.9 2
 
2.0%
0.24 2
 
2.0%
5.61 2
 
2.0%
6.33 2
 
2.0%
5.45 2
 
2.0%
0.17 2
 
2.0%
0.22 2
 
2.0%
7.02 1
 
1.0%
Other values (80) 80
80.0%
ValueCountFrequency (%)
0.08 1
1.0%
0.1 1
1.0%
0.15 1
1.0%
0.16 1
1.0%
0.17 2
2.0%
0.18 1
1.0%
0.22 2
2.0%
0.23 1
1.0%
0.24 2
2.0%
0.27 1
1.0%
ValueCountFrequency (%)
7.95 1
1.0%
7.91 1
1.0%
7.75 1
1.0%
7.53 1
1.0%
7.52 1
1.0%
7.51 1
1.0%
7.31 1
1.0%
7.28 1
1.0%
7.02 1
1.0%
6.93 1
1.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4017.94
Minimum5
Maximum18268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:19.581917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile66.85
Q1264.75
median2365.5
Q36526.5
95-th percentile13828.8
Maximum18268
Range18263
Interquartile range (IQR)6261.75

Descriptive statistics

Standard deviation4837.3692
Coefficient of variation (CV)1.2039426
Kurtosis0.64950505
Mean4017.94
Median Absolute Deviation (MAD)2143
Skewness1.2890994
Sum401794
Variance23400140
MonotonicityNot monotonic
2024-04-17T07:29:19.699960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 2
 
2.0%
202 1
 
1.0%
198 1
 
1.0%
279 1
 
1.0%
450 1
 
1.0%
1091 1
 
1.0%
2845 1
 
1.0%
173 1
 
1.0%
344 1
 
1.0%
300 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
5 1
1.0%
11 1
1.0%
16 1
1.0%
17 1
1.0%
26 1
1.0%
69 1
1.0%
71 1
1.0%
73 1
1.0%
105 1
1.0%
106 1
1.0%
ValueCountFrequency (%)
18268 1
1.0%
17421 1
1.0%
16356 1
1.0%
15092 1
1.0%
14395 1
1.0%
13799 1
1.0%
13610 1
1.0%
13476 1
1.0%
13365 1
1.0%
12660 1
1.0%

배출횟수비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0169
Minimum0.07
Maximum7.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:19.837138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.07
5-th percentile0.14
Q11.1425
median5.155
Q35.975
95-th percentile7.0805
Maximum7.9
Range7.83
Interquartile range (IQR)4.8325

Descriptive statistics

Standard deviation2.5501807
Coefficient of variation (CV)0.63486288
Kurtosis-1.3883651
Mean4.0169
Median Absolute Deviation (MAD)1.44
Skewness-0.42614545
Sum401.69
Variance6.5034216
MonotonicityNot monotonic
2024-04-17T07:29:19.958713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.42 3
 
3.0%
5.88 2
 
2.0%
0.14 2
 
2.0%
0.35 2
 
2.0%
0.24 2
 
2.0%
0.11 2
 
2.0%
6.14 2
 
2.0%
5.63 2
 
2.0%
5.05 2
 
2.0%
5.41 2
 
2.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
0.07 1
1.0%
0.11 2
2.0%
0.12 1
1.0%
0.14 2
2.0%
0.18 1
1.0%
0.19 1
1.0%
0.21 1
1.0%
0.24 2
2.0%
0.26 1
1.0%
0.34 1
1.0%
ValueCountFrequency (%)
7.9 1
1.0%
7.76 1
1.0%
7.55 1
1.0%
7.54 1
1.0%
7.09 1
1.0%
7.08 1
1.0%
7.07 1
1.0%
7.01 1
1.0%
6.89 1
1.0%
6.88 1
1.0%

Interactions

2024-04-17T07:29:17.136949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:15.691763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.028662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.379091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.743753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:17.220556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:15.750068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.090228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.445298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.809861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:17.314902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:15.816887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.156270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.515378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.881783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:17.416091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:15.890347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.232448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.592387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.960648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:17.488578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:15.959335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.305578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:16.666312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:17.045876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T07:29:20.039110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체코드지자체 시군구명배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
지자체코드1.0001.0000.0000.7240.1410.8640.000
지자체 시군구명1.0001.0000.0000.7240.1410.8640.000
배출시0.0000.0001.0000.4990.7850.5950.879
배출량(g)0.7240.7240.4991.0000.8450.9160.528
배출량비율(%)0.1410.1410.7850.8451.0000.6040.880
배출횟수0.8640.8640.5950.9160.6041.0000.863
배출횟수비율(%)0.0000.0000.8790.5280.8800.8631.000
2024-04-17T07:29:20.127504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드
지자체 시군구명1.0001.000
지자체코드1.0001.000
2024-04-17T07:29:20.198141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)지자체코드지자체 시군구명
배출시1.0000.4720.7440.4570.6610.0000.000
배출량(g)0.4721.0000.6130.9900.5920.5180.518
배출량비율(%)0.7440.6131.0000.6130.9480.0740.074
배출횟수0.4570.9900.6131.0000.6260.5180.518
배출횟수비율(%)0.6610.5920.9480.6261.0000.0000.000
지자체코드0.0000.5180.0740.5180.0001.0001.000
지자체 시군구명0.0000.5180.0740.5180.0001.0001.000

Missing values

2024-04-17T07:29:17.591537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T07:29:18.005514image/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

배출년도배출월지자체코드지자체 시도명지자체 시군구명배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
0201711W01서울특별시종로구13889000.472020.4
1201711W01서울특별시종로구21824500.221050.21
2201711W01서울특별시종로구31331500.16690.14
3201711W01서울특별시종로구42241000.271780.35
4201711W01서울특별시종로구53914000.473020.6
5201711W01서울특별시종로구69307501.126951.38
6201711W01서울특별시종로구725554003.0617963.57
7201711W01서울특별시종로구840840504.930846.14
8201711W01서울특별시종로구950553006.0635217.01
9201711W01서울특별시종로구1053100006.3732416.45
배출년도배출월지자체코드지자체 시도명지자체 시군구명배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
90201711W04서울특별시성동구19264066007.53174217.54
91201711W04서울특별시성동구20277199007.91182687.9
92201711W04서울특별시성동구21255094007.28163567.07
93201711W04서울특별시성동구22168624004.81104284.51
94201711W04서울특별시성동구23105159503.063792.76
95201711W05서울특별시광진구025550501.4712441.17
96201711W05서울특별시광진구17147000.413630.34
97201711W05서울특별시광진구23215500.181150.11
98201711W05서울특별시광진구31401000.08730.07
99201711W01서울특별시종로구09766001.175001.0