Overview

Dataset statistics

Number of variables9
Number of observations102
Missing cells356
Missing cells (%)38.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory79.3 B

Variable types

Categorical4
Numeric5

Dataset

Description유독물질 취급사업장 집계 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=35FIA537O11IRA5589882309238&infSeq=1

Alerts

집계년도 has constant value ""Constant
취급사업장구분명 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 취급사업장구분명High correlation
제조개소수 is highly overall correlated with 사용개소수High correlation
사용개소수 is highly overall correlated with 제조개소수 and 1 other fieldsHigh correlation
보관저장개소수 is highly overall correlated with 사용개소수 and 1 other fieldsHigh correlation
운반개소수 is highly overall correlated with 보관저장개소수High correlation
제조개소수 has 70 (68.6%) missing valuesMissing
사용개소수 has 58 (56.9%) missing valuesMissing
보관저장개소수 has 81 (79.4%) missing valuesMissing
판매개소수 has 61 (59.8%) missing valuesMissing
운반개소수 has 86 (84.3%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:53:41.614588
Analysis finished2023-12-10 21:53:44.915755
Duration3.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2015
102 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2015
5th row2015

Common Values

ValueCountFrequency (%)
2015 102
100.0%

Length

2023-12-11T06:53:44.980360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:45.079566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015 102
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size948.0 B
경기도
9 
가평군
 
3
고양시
 
3
과천시
 
3
광명시
 
3
Other values (27)
81 

Length

Max length4
Median length3
Mean length3.0882353
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 9
 
8.8%
가평군 3
 
2.9%
고양시 3
 
2.9%
과천시 3
 
2.9%
광명시 3
 
2.9%
광주시 3
 
2.9%
구리시 3
 
2.9%
군포시 3
 
2.9%
김포시 3
 
2.9%
남양주시 3
 
2.9%
Other values (22) 66
64.7%

Length

2023-12-11T06:53:45.186270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 9
 
8.8%
가평군 3
 
2.9%
하남시 3
 
2.9%
포천시 3
 
2.9%
평택시 3
 
2.9%
파주시 3
 
2.9%
이천시 3
 
2.9%
의정부시 3
 
2.9%
의왕시 3
 
2.9%
용인시 3
 
2.9%
Other values (22) 66
64.7%

취급사업장구분명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size948.0 B
가평군
 
3
군포시
 
3
수원시
 
3
성남시
 
3
부천시
 
3
Other values (29)
87 

Length

Max length6
Median length3
Mean length3.3529412
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row도공단사업소
5th row도북부환경과

Common Values

ValueCountFrequency (%)
가평군 3
 
2.9%
군포시 3
 
2.9%
수원시 3
 
2.9%
성남시 3
 
2.9%
부천시 3
 
2.9%
동두천시 3
 
2.9%
남양주시 3
 
2.9%
김포시 3
 
2.9%
구리시 3
 
2.9%
용인시 3
 
2.9%
Other values (24) 72
70.6%

Length

2023-12-11T06:53:45.306309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 3
 
2.9%
도공단사업소 3
 
2.9%
하남시 3
 
2.9%
포천시 3
 
2.9%
평택시 3
 
2.9%
파주시 3
 
2.9%
이천시 3
 
2.9%
의정부시 3
 
2.9%
의왕시 3
 
2.9%
군포시 3
 
2.9%
Other values (24) 72
70.6%

취급사업장유형
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
유독물질영업허가
34 
자체방제계획수립대상
34 
다량취급사업장
34 

Length

Max length10
Median length8
Mean length8.3333333
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유독물질영업허가
2nd row자체방제계획수립대상
3rd row다량취급사업장
4th row유독물질영업허가
5th row다량취급사업장

Common Values

ValueCountFrequency (%)
유독물질영업허가 34
33.3%
자체방제계획수립대상 34
33.3%
다량취급사업장 34
33.3%

Length

2023-12-11T06:53:45.421341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:45.527748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유독물질영업허가 34
33.3%
자체방제계획수립대상 34
33.3%
다량취급사업장 34
33.3%

제조개소수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)40.6%
Missing70
Missing (%)68.6%
Infinite0
Infinite (%)0.0%
Mean8.46875
Minimum0
Maximum127
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T06:53:45.623003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q34.25
95-th percentile27.05
Maximum127
Range127
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation22.66016
Coefficient of variation (CV)2.6757385
Kurtosis26.059186
Mean8.46875
Median Absolute Deviation (MAD)1
Skewness4.9508941
Sum271
Variance513.48286
MonotonicityNot monotonic
2023-12-11T06:53:45.741428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 9
 
8.8%
2 8
 
7.8%
3 3
 
2.9%
4 3
 
2.9%
127 1
 
1.0%
23 1
 
1.0%
32 1
 
1.0%
0 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%
Other values (3) 3
 
2.9%
(Missing) 70
68.6%
ValueCountFrequency (%)
0 1
 
1.0%
1 9
8.8%
2 8
7.8%
3 3
 
2.9%
4 3
 
2.9%
5 1
 
1.0%
6 1
 
1.0%
8 1
 
1.0%
11 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
127 1
 
1.0%
32 1
 
1.0%
23 1
 
1.0%
13 1
 
1.0%
11 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%
5 1
 
1.0%
4 3
2.9%
3 3
2.9%

사용개소수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)45.5%
Missing58
Missing (%)56.9%
Infinite0
Infinite (%)0.0%
Mean18.863636
Minimum1
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T06:53:45.855614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3.5
Q314.25
95-th percentile65.3
Maximum328
Range327
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation51.265198
Coefficient of variation (CV)2.7176731
Kurtosis32.240576
Mean18.863636
Median Absolute Deviation (MAD)2.5
Skewness5.3990834
Sum830
Variance2628.1205
MonotonicityNot monotonic
2023-12-11T06:53:45.957092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 15
 
14.7%
3 5
 
4.9%
4 4
 
3.9%
2 2
 
2.0%
7 2
 
2.0%
19 2
 
2.0%
45 1
 
1.0%
28 1
 
1.0%
9 1
 
1.0%
8 1
 
1.0%
Other values (10) 10
 
9.8%
(Missing) 58
56.9%
ValueCountFrequency (%)
1 15
14.7%
2 2
 
2.0%
3 5
 
4.9%
4 4
 
3.9%
5 1
 
1.0%
6 1
 
1.0%
7 2
 
2.0%
8 1
 
1.0%
9 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
328 1
1.0%
83 1
1.0%
68 1
1.0%
50 1
1.0%
47 1
1.0%
45 1
1.0%
28 1
1.0%
20 1
1.0%
19 2
2.0%
18 1
1.0%

보관저장개소수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)38.1%
Missing81
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean3.6190476
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T06:53:46.056666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile9
Maximum17
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.8141341
Coefficient of variation (CV)1.0539055
Kurtosis7.230319
Mean3.6190476
Median Absolute Deviation (MAD)2
Skewness2.499573
Sum76
Variance14.547619
MonotonicityNot monotonic
2023-12-11T06:53:46.160675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 7
 
6.9%
3 5
 
4.9%
2 3
 
2.9%
4 2
 
2.0%
9 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%
17 1
 
1.0%
(Missing) 81
79.4%
ValueCountFrequency (%)
1 7
6.9%
2 3
2.9%
3 5
4.9%
4 2
 
2.0%
6 1
 
1.0%
8 1
 
1.0%
9 1
 
1.0%
17 1
 
1.0%
ValueCountFrequency (%)
17 1
 
1.0%
9 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%
4 2
 
2.0%
3 5
4.9%
2 3
2.9%
1 7
6.9%

판매개소수
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)58.5%
Missing61
Missing (%)59.8%
Infinite0
Infinite (%)0.0%
Mean31.926829
Minimum1
Maximum249
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T06:53:46.303457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median9
Q327
95-th percentile136
Maximum249
Range248
Interquartile range (IQR)25

Descriptive statistics

Standard deviation51.287616
Coefficient of variation (CV)1.6064112
Kurtosis7.520587
Mean31.926829
Median Absolute Deviation (MAD)8
Skewness2.5658252
Sum1309
Variance2630.4195
MonotonicityNot monotonic
2023-12-11T06:53:46.458266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 6
 
5.9%
2 5
 
4.9%
19 4
 
3.9%
3 3
 
2.9%
9 3
 
2.9%
5 2
 
2.0%
44 1
 
1.0%
75 1
 
1.0%
6 1
 
1.0%
27 1
 
1.0%
Other values (14) 14
 
13.7%
(Missing) 61
59.8%
ValueCountFrequency (%)
1 6
5.9%
2 5
4.9%
3 3
2.9%
5 2
 
2.0%
6 1
 
1.0%
8 1
 
1.0%
9 3
2.9%
11 1
 
1.0%
12 1
 
1.0%
16 1
 
1.0%
ValueCountFrequency (%)
249 1
1.0%
140 1
1.0%
136 1
1.0%
113 1
1.0%
93 1
1.0%
92 1
1.0%
75 1
1.0%
54 1
1.0%
48 1
1.0%
44 1
1.0%

운반개소수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)43.8%
Missing86
Missing (%)84.3%
Infinite0
Infinite (%)0.0%
Mean3.125
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T06:53:46.564172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2.5
Q35
95-th percentile6.25
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1563859
Coefficient of variation (CV)0.69004348
Kurtosis-1.3424152
Mean3.125
Median Absolute Deviation (MAD)1.5
Skewness0.45447836
Sum50
Variance4.65
MonotonicityNot monotonic
2023-12-11T06:53:46.653571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
 
5.9%
6 2
 
2.0%
5 2
 
2.0%
4 2
 
2.0%
2 2
 
2.0%
3 1
 
1.0%
7 1
 
1.0%
(Missing) 86
84.3%
ValueCountFrequency (%)
1 6
5.9%
2 2
 
2.0%
3 1
 
1.0%
4 2
 
2.0%
5 2
 
2.0%
6 2
 
2.0%
7 1
 
1.0%
ValueCountFrequency (%)
7 1
 
1.0%
6 2
 
2.0%
5 2
 
2.0%
4 2
 
2.0%
3 1
 
1.0%
2 2
 
2.0%
1 6
5.9%

Interactions

2023-12-11T06:53:44.087543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:41.941993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.434325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.176386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.631677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:44.172570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.035815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.774720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.251819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.714682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:44.252544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.112252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.861297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.341669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.819201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:44.359717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.232908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.985293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.437251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.919787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:44.443313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:42.343403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.096602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:43.532400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:53:44.006512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:53:46.735126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명취급사업장구분명취급사업장유형제조개소수사용개소수보관저장개소수판매개소수운반개소수
시군명1.0001.0000.0000.0000.0000.0000.5060.828
취급사업장구분명1.0001.0000.0000.0000.0000.0000.0000.828
취급사업장유형0.0000.0001.0000.0000.0000.0000.0000.000
제조개소수0.0000.0000.0001.0000.9560.6660.6070.487
사용개소수0.0000.0000.0000.9561.0000.7910.6400.783
보관저장개소수0.0000.0000.0000.6660.7911.0000.9220.827
판매개소수0.5060.0000.0000.6070.6400.9221.0000.484
운반개소수0.8280.8280.0000.4870.7830.8270.4841.000
2023-12-11T06:53:46.848527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취급사업장구분명취급사업장유형시군명
취급사업장구분명1.0000.0000.986
취급사업장유형0.0001.0000.000
시군명0.9860.0001.000
2023-12-11T06:53:46.939293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제조개소수사용개소수보관저장개소수판매개소수운반개소수시군명취급사업장구분명취급사업장유형
제조개소수1.0000.6520.4670.1430.0370.0000.0000.000
사용개소수0.6521.0000.6440.0630.1430.0000.0000.000
보관저장개소수0.4670.6441.0000.2810.5000.0000.0000.000
판매개소수0.1430.0630.2811.000-0.0810.0000.0000.000
운반개소수0.0370.1430.500-0.0811.0000.2890.2890.000
시군명0.0000.0000.0000.0000.2891.0000.9860.000
취급사업장구분명0.0000.0000.0000.0000.2890.9861.0000.000
취급사업장유형0.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T06:53:44.552705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:53:44.727198image/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.
2023-12-11T06:53:44.851726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

집계년도시군명취급사업장구분명취급사업장유형제조개소수사용개소수보관저장개소수판매개소수운반개소수
02015가평군가평군유독물질영업허가<NA><NA><NA><NA><NA>
12015가평군가평군자체방제계획수립대상<NA><NA><NA><NA><NA>
22015가평군가평군다량취급사업장<NA><NA><NA><NA><NA>
32015경기도도공단사업소유독물질영업허가12732892491
42015경기도도북부환경과다량취급사업장37<NA>1<NA>
52015경기도도북부환경과자체방제계획수립대상113<NA><NA><NA>
62015경기도도북부환경과유독물질영업허가447<NA>1<NA>
72015경기도도환경안전과다량취급사업장25<NA><NA><NA>
82015경기도도공단사업소자체방제계획수립대상2383312<NA>
92015경기도도공단사업소다량취급사업장325033<NA>
집계년도시군명취급사업장구분명취급사업장유형제조개소수사용개소수보관저장개소수판매개소수운반개소수
922015평택시평택시유독물질영업허가1128827<NA>
932015포천시포천시유독물질영업허가<NA>469<NA>
942015포천시포천시자체방제계획수립대상<NA><NA><NA><NA><NA>
952015포천시포천시다량취급사업장<NA><NA><NA><NA><NA>
962015하남시하남시다량취급사업장<NA><NA><NA><NA><NA>
972015하남시하남시자체방제계획수립대상<NA><NA><NA><NA><NA>
982015하남시하남시유독물질영업허가<NA><NA><NA>6<NA>
992015화성시화성시다량취급사업장21<NA><NA><NA>
1002015화성시화성시자체방제계획수립대상234<NA><NA>
1012015화성시화성시유독물질영업허가134517757