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 지자체코드High correlation
지자체코드 is highly overall correlated with 지자체 시군구명High correlation
배출시 is highly overall correlated with 배출량비율(%) and 1 other fieldsHigh correlation
배출량(g) is highly overall correlated with 배출량비율(%) and 2 other fieldsHigh correlation
배출량비율(%) is highly overall correlated with 배출시 and 3 other fieldsHigh correlation
배출횟수 is highly overall correlated with 배출량(g) and 2 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 22:29:31.630536
Analysis finished2024-04-16 22:29:33.951004
Duration2.32 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

2024-04-17T07:29:34.010300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:34.080053image/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
8
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 100
100.0%

Length

2024-04-17T07:29:34.157460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:34.230134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 100
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

2024-04-17T07:29:34.304656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:34.397154image/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

2024-04-17T07:29:34.494882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:34.569126image/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

2024-04-17T07:29:34.648705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:29:34.735085image/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
2024-04-17T07:29:34.821445image/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
2024-04-17T07:29:34.927726image/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%
Mean5599337
Minimum1250
Maximum27489000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:35.028095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1250
5-th percentile95812.5
Q1326775
median3686725
Q38758700
95-th percentile16757322
Maximum27489000
Range27487750
Interquartile range (IQR)8431925

Descriptive statistics

Standard deviation6357572.1
Coefficient of variation (CV)1.1354152
Kurtosis1.2479821
Mean5599337
Median Absolute Deviation (MAD)3397675
Skewness1.2980029
Sum5.599337 × 108
Variance4.0418723 × 1013
MonotonicityNot monotonic
2024-04-17T07:29:35.140678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
383650 1
 
1.0%
300350 1
 
1.0%
567050 1
 
1.0%
800500 1
 
1.0%
2019000 1
 
1.0%
5323650 1
 
1.0%
305750 1
 
1.0%
377600 1
 
1.0%
421850 1
 
1.0%
513250 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1250 1
1.0%
10600 1
1.0%
12800 1
1.0%
29400 1
1.0%
48550 1
1.0%
98300 1
1.0%
144750 1
1.0%
166200 1
1.0%
168350 1
1.0%
174150 1
1.0%
ValueCountFrequency (%)
27489000 1
1.0%
24743250 1
1.0%
24110050 1
1.0%
18251500 1
1.0%
17487350 1
1.0%
16718900 1
1.0%
16245650 1
1.0%
16242800 1
1.0%
16088050 1
1.0%
15125900 1
1.0%

배출량비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0235
Minimum0.02
Maximum9.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:35.269099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.18
Q11.6025
median4.75
Q35.5475
95-th percentile8.1415
Maximum9.1
Range9.08
Interquartile range (IQR)3.945

Descriptive statistics

Standard deviation2.5177629
Coefficient of variation (CV)0.62576436
Kurtosis-0.93095614
Mean4.0235
Median Absolute Deviation (MAD)1.38
Skewness-0.17183534
Sum402.35
Variance6.3391301
MonotonicityNot monotonic
2024-04-17T07:29:35.401453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.18 3
 
3.0%
3.37 2
 
2.0%
5.06 2
 
2.0%
0.28 2
 
2.0%
0.67 2
 
2.0%
5.01 2
 
2.0%
5.38 2
 
2.0%
7.09 2
 
2.0%
4.75 2
 
2.0%
4.62 2
 
2.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
0.02 1
 
1.0%
0.11 1
 
1.0%
0.12 1
 
1.0%
0.18 3
3.0%
0.19 1
 
1.0%
0.2 1
 
1.0%
0.22 1
 
1.0%
0.24 1
 
1.0%
0.26 1
 
1.0%
0.28 2
2.0%
ValueCountFrequency (%)
9.1 1
1.0%
8.94 1
1.0%
8.69 1
1.0%
8.19 1
1.0%
8.17 1
1.0%
8.14 1
1.0%
7.98 1
1.0%
7.58 1
1.0%
7.5 1
1.0%
7.35 1
1.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4454.83
Minimum3
Maximum21931
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:35.526894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile71.7
Q1286
median2591
Q37014.25
95-th percentile14312.15
Maximum21931
Range21928
Interquartile range (IQR)6728.25

Descriptive statistics

Standard deviation5149.4793
Coefficient of variation (CV)1.1559317
Kurtosis1.1632358
Mean4454.83
Median Absolute Deviation (MAD)2378.5
Skewness1.3040635
Sum445483
Variance26517137
MonotonicityNot monotonic
2024-04-17T07:29:35.664623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 2
 
2.0%
241 1
 
1.0%
210 1
 
1.0%
489 1
 
1.0%
1361 1
 
1.0%
3667 1
 
1.0%
255 1
 
1.0%
322 1
 
1.0%
395 1
 
1.0%
450 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
3 1
1.0%
9 1
1.0%
15 1
1.0%
33 1
1.0%
47 1
1.0%
73 1
1.0%
100 2
2.0%
104 1
1.0%
130 1
1.0%
173 1
1.0%
ValueCountFrequency (%)
21931 1
1.0%
19577 1
1.0%
19493 1
1.0%
15413 1
1.0%
14619 1
1.0%
14296 1
1.0%
13625 1
1.0%
12803 1
1.0%
12415 1
1.0%
11790 1
1.0%

배출횟수비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0202
Minimum0.06
Maximum9.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T07:29:35.774977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile0.159
Q11.3475
median4.6
Q35.725
95-th percentile7.8685
Maximum9.04
Range8.98
Interquartile range (IQR)4.3775

Descriptive statistics

Standard deviation2.5421501
Coefficient of variation (CV)0.63234419
Kurtosis-1.0109938
Mean4.0202
Median Absolute Deviation (MAD)1.745
Skewness-0.15434015
Sum402.02
Variance6.4625272
MonotonicityNot monotonic
2024-04-17T07:29:35.883860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.92 3
 
3.0%
0.2 2
 
2.0%
0.17 2
 
2.0%
4.57 2
 
2.0%
4.62 2
 
2.0%
4.86 2
 
2.0%
4.71 2
 
2.0%
5.05 1
 
1.0%
0.14 1
 
1.0%
0.56 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
0.06 1
1.0%
0.09 1
1.0%
0.11 1
1.0%
0.13 1
1.0%
0.14 1
1.0%
0.16 1
1.0%
0.17 2
2.0%
0.2 2
2.0%
0.26 1
1.0%
0.29 1
1.0%
ValueCountFrequency (%)
9.04 1
1.0%
8.67 1
1.0%
8.63 1
1.0%
8.07 1
1.0%
8.03 1
1.0%
7.86 1
1.0%
7.76 1
1.0%
7.64 1
1.0%
7.61 1
1.0%
7.45 1
1.0%

Interactions

2024-04-17T07:29:33.415803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:31.871573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.185374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.497009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.798006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.476494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:31.940545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.249711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.557386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.862129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.541977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.000211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.312083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.620317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.956122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.607770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.058118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.377672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.680593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.022923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.671802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.113494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.438090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:32.739432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:29:33.357973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T07:29:35.963843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체코드지자체 시군구명배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
지자체코드1.0001.0000.0000.7080.0000.8360.000
지자체 시군구명1.0001.0000.0000.7080.0000.8360.000
배출시0.0000.0001.0000.3660.8980.5040.905
배출량(g)0.7080.7080.3661.0000.6210.9400.487
배출량비율(%)0.0000.0000.8980.6211.0000.6960.983
배출횟수0.8360.8360.5040.9400.6961.0000.804
배출횟수비율(%)0.0000.0000.9050.4870.9830.8041.000
2024-04-17T07:29:36.054525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드
지자체 시군구명1.0001.000
지자체코드1.0001.000
2024-04-17T07:29:36.125130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)지자체코드지자체 시군구명
배출시1.0000.4610.7540.4560.6960.0000.000
배출량(g)0.4611.0000.5810.9950.5680.5000.500
배출량비율(%)0.7540.5811.0000.5940.9810.0000.000
배출횟수0.4560.9950.5941.0000.5940.4830.483
배출횟수비율(%)0.6960.5680.9810.5941.0000.0000.000
지자체코드0.0000.5000.0000.4830.0001.0001.000
지자체 시군구명0.0000.5000.0000.4830.0001.0001.000

Missing values

2024-04-17T07:29:33.768385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T07:29:33.890010image/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(%)
020178W01서울특별시종로구13836500.482410.42
120178W01서울특별시종로구21447500.181000.17
220178W01서울특별시종로구3983000.12730.13
320178W01서울특별시종로구42236000.281930.33
420178W01서울특별시종로구55429500.675390.93
520178W01서울특별시종로구615649001.9412562.17
620178W01서울특별시종로구726921003.3422873.96
720178W01서울특별시종로구844306005.4939086.76
820178W01서울특별시종로구947939005.9439506.84
920178W01서울특별시종로구1049998006.236666.34
배출년도배출월지자체코드지자체 시도명지자체 시군구명배출시배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
9020178W04서울특별시성동구19241100507.98195778.07
9120178W04서울특별시성동구20274890009.1219319.04
9220178W04서울특별시성동구21247432508.19194938.03
9320178W04서울특별시성동구22167189005.53128035.28
9420178W04서울특별시성동구23109441003.6279543.28
9520178W05서울특별시광진구021782501.4615441.35
9620178W05서울특별시광진구18891500.65140.45
9720178W05서울특별시광진구23005000.21300.11
9820178W05서울특별시광진구31683500.111000.09
9920178W01서울특별시종로구013329001.657731.34