Overview

Dataset statistics

Number of variables20
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.4 KiB
Average record size in memory178.3 B

Variable types

Categorical11
Text1
Numeric8

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=aac908b0-50e4-11ec-8ec1-9b2961d225b7

Alerts

조사년도 has constant value ""Constant
시도명 has constant value ""Constant
총계기타 has constant value ""Constant
공공처리기타 has constant value ""Constant
자가처리재활용 has constant value ""Constant
자가처리소각 has constant value ""Constant
자가처리매립 has constant value ""Constant
자가처리기타 has constant value ""Constant
위탁처리소각 has constant value ""Constant
위탁처리기타 has constant value ""Constant
총계재활용 is highly overall correlated with 공공처리재활용High correlation
총계소각 is highly overall correlated with 공공처리소각High correlation
총계매립 is highly overall correlated with 공공처리매립 and 2 other fieldsHigh correlation
공공처리재활용 is highly overall correlated with 총계재활용High correlation
공공처리소각 is highly overall correlated with 총계소각High correlation
공공처리매립 is highly overall correlated with 총계매립 and 1 other fieldsHigh correlation
위탁처리재활용 is highly overall correlated with 총계매립 and 1 other fieldsHigh correlation
위탁처리매립 is highly overall correlated with 총계매립 and 2 other fieldsHigh correlation
총계재활용 has 45 (45.0%) zerosZeros
총계소각 has 56 (56.0%) zerosZeros
총계매립 has 62 (62.0%) zerosZeros
공공처리재활용 has 76 (76.0%) zerosZeros
공공처리소각 has 56 (56.0%) zerosZeros
공공처리매립 has 62 (62.0%) zerosZeros
위탁처리재활용 has 69 (69.0%) zerosZeros
위탁처리매립 has 79 (79.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:55:29.927799
Analysis finished2023-12-10 10:55:44.244852
Duration14.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 100
100.0%

Length

2023-12-10T19:55:44.352367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:44.487320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 100
100.0%

시도명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원 100
100.0%

Length

2023-12-10T19:55:44.652523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:44.804936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원 100
100.0%

시군구명
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
원주시
24 
강릉시
21 
삼척시
12 
동해시
10 
영월군
9 
Other values (4)
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원주시 24
24.0%
강릉시 21
21.0%
삼척시 12
12.0%
동해시 10
10.0%
영월군 9
 
9.0%
속초시 8
 
8.0%
양양군 6
 
6.0%
고성군 5
 
5.0%
양구군 5
 
5.0%

Length

2023-12-10T19:55:44.962452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:45.146969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원주시 24
24.0%
강릉시 21
21.0%
삼척시 12
12.0%
동해시 10
10.0%
영월군 9
 
9.0%
속초시 8
 
8.0%
양양군 6
 
6.0%
고성군 5
 
5.0%
양구군 5
 
5.0%

읍면동명
Text

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:55:45.510385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.06
Min length2

Characters and Unicode

Total characters306
Distinct characters106
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)92.0%

Sample

1st row교1동
2nd row초당동
3rd row경포동
4th row왕산면
5th row성덕동
ValueCountFrequency (%)
남면 2
 
2.0%
송정동 2
 
2.0%
교동 2
 
2.0%
중앙동 2
 
2.0%
현남면 1
 
1.0%
양양읍 1
 
1.0%
영월읍 1
 
1.0%
중동면 1
 
1.0%
김삿갓면 1
 
1.0%
한반도면 1
 
1.0%
Other values (86) 86
86.0%
2023-12-10T19:55:46.450623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 56
 
18.3%
면 40
 
13.1%
읍 10
 
3.3%
남 7
 
2.3%
곡 7
 
2.3%
산 6
 
2.0%
성 6
 
2.0%
양 6
 
2.0%
정 5
 
1.6%
호 5
 
1.6%
Other values (96) 158
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
97.4%
Decimal Number 8
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 56
 
18.8%
면 40
 
13.4%
읍 10
 
3.4%
남 7
 
2.3%
곡 7
 
2.3%
산 6
 
2.0%
성 6
 
2.0%
양 6
 
2.0%
정 5
 
1.7%
호 5
 
1.7%
Other values (94) 150
50.3%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 4
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
97.4%
Common 8
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 56
 
18.8%
면 40
 
13.4%
읍 10
 
3.4%
남 7
 
2.3%
곡 7
 
2.3%
산 6
 
2.0%
성 6
 
2.0%
양 6
 
2.0%
정 5
 
1.7%
호 5
 
1.7%
Other values (94) 150
50.3%
Common
ValueCountFrequency (%)
1 4
50.0%
2 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
97.4%
ASCII 8
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 56
 
18.8%
면 40
 
13.4%
읍 10
 
3.4%
남 7
 
2.3%
곡 7
 
2.3%
산 6
 
2.0%
성 6
 
2.0%
양 6
 
2.0%
정 5
 
1.7%
호 5
 
1.7%
Other values (94) 150
50.3%
ASCII
ValueCountFrequency (%)
1 4
50.0%
2 4
50.0%

총계재활용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.395636
Minimum0
Maximum575.48903
Zeros45
Zeros (%)45.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:46.707192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8.004985
Q347.83846
95-th percentile241.49226
Maximum575.48903
Range575.48903
Interquartile range (IQR)47.83846

Descriptive statistics

Standard deviation105.85638
Coefficient of variation (CV)2.1005068
Kurtosis12.660719
Mean50.395636
Median Absolute Deviation (MAD)8.004985
Skewness3.3795524
Sum5039.5636
Variance11205.573
MonotonicityNot monotonic
2023-12-10T19:55:47.005615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 45
45.0%
49.29301637 1
 
1.0%
100.1365921 1
 
1.0%
116.9050585 1
 
1.0%
575.4890254 1
 
1.0%
71.5919992 1
 
1.0%
332.5240897 1
 
1.0%
570.812823 1
 
1.0%
174.4947955 1
 
1.0%
117.4187821 1
 
1.0%
Other values (46) 46
46.0%
ValueCountFrequency (%)
0.0 45
45.0%
3.056568061 1
 
1.0%
6.373628433 1
 
1.0%
6.450464295 1
 
1.0%
6.870250466 1
 
1.0%
7.661097628 1
 
1.0%
8.348872293 1
 
1.0%
8.498795926 1
 
1.0%
9.293391179 1
 
1.0%
9.700059032 1
 
1.0%
ValueCountFrequency (%)
575.4890254 1
1.0%
570.812823 1
1.0%
442.0921209 1
1.0%
332.5240897 1
1.0%
261.3140902 1
1.0%
240.4490071 1
1.0%
212.6420686 1
1.0%
183.8472001 1
1.0%
174.4947955 1
1.0%
132.9798281 1
1.0%

총계소각
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59
Minimum0
Maximum966.52483
Zeros56
Zeros (%)56.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:47.321295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q351.54515
95-th percentile233.55733
Maximum966.52483
Range966.52483
Interquartile range (IQR)51.54515

Descriptive statistics

Standard deviation152.36849
Coefficient of variation (CV)2.5825167
Kurtosis19.404356
Mean59
Median Absolute Deviation (MAD)0
Skewness4.2284707
Sum5900
Variance23216.155
MonotonicityNot monotonic
2023-12-10T19:55:47.605922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 56
56.0%
86.26277865 1
 
1.0%
475.8890572 1
 
1.0%
168.7110263 1
 
1.0%
143.1809845 1
 
1.0%
227.2882889 1
 
1.0%
117.95066 1
 
1.0%
94.82074587 1
 
1.0%
101.4462959 1
 
1.0%
186.6262714 1
 
1.0%
Other values (35) 35
35.0%
ValueCountFrequency (%)
0.0 56
56.0%
5.348994106 1
 
1.0%
11.15384976 1
 
1.0%
11.28831252 1
 
1.0%
12.02293832 1
 
1.0%
13.40692085 1
 
1.0%
14.61052651 1
 
1.0%
14.87289287 1
 
1.0%
16.26343456 1
 
1.0%
16.97510331 1
 
1.0%
ValueCountFrequency (%)
966.5248331 1
1.0%
770.6172206 1
1.0%
686.7740727 1
1.0%
475.8890572 1
1.0%
352.669161 1
1.0%
227.2882889 1
1.0%
186.6262714 1
1.0%
168.7110263 1
1.0%
157.4352579 1
1.0%
143.1809845 1
1.0%

총계매립
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137
Minimum0
Maximum1632.0499
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:47.886743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q381.162165
95-th percentile873.3314
Maximum1632.0499
Range1632.0499
Interquartile range (IQR)81.162165

Descriptive statistics

Standard deviation310.5936
Coefficient of variation (CV)2.2671065
Kurtosis9.0654992
Mean137
Median Absolute Deviation (MAD)0
Skewness2.9492032
Sum13700
Variance96468.383
MonotonicityNot monotonic
2023-12-10T19:55:48.164271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 62
62.0%
278.8017354 1
 
1.0%
4.39943174 1
 
1.0%
4.387211096 1
 
1.0%
66.55362571 1
 
1.0%
4.130577578 1
 
1.0%
20.58567435 1
 
1.0%
8.291706766 1
 
1.0%
47.90492339 1
 
1.0%
32.44580908 1
 
1.0%
Other values (29) 29
29.0%
ValueCountFrequency (%)
0.0 62
62.0%
4.130577578 1
 
1.0%
4.387211096 1
 
1.0%
4.39943174 1
 
1.0%
8.291706766 1
 
1.0%
11.53017735 1
 
1.0%
20.58567435 1
 
1.0%
32.44580908 1
 
1.0%
47.90492339 1
 
1.0%
51.24726945 1
 
1.0%
ValueCountFrequency (%)
1632.049925 1
1.0%
1478.790491 1
1.0%
1044.761575 1
1.0%
961.8912866 1
1.0%
922.2552262 1
1.0%
870.7564584 1
1.0%
832.2878229 1
1.0%
763.2049925 1
1.0%
601.7372401 1
1.0%
474.0585264 1
1.0%

총계기타
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:48.421287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:48.591619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

공공처리재활용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.395636
Minimum0
Maximum575.48903
Zeros76
Zeros (%)76.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:48.751250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile241.49226
Maximum575.48903
Range575.48903
Interquartile range (IQR)0

Descriptive statistics

Standard deviation107.36361
Coefficient of variation (CV)2.5324213
Kurtosis12.834903
Mean42.395636
Median Absolute Deviation (MAD)0
Skewness3.4396074
Sum4239.5636
Variance11526.945
MonotonicityNot monotonic
2023-12-10T19:55:48.990902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 76
76.0%
116.9050585 1
 
1.0%
37.89699755 1
 
1.0%
48.2505047 1
 
1.0%
118.630643 1
 
1.0%
183.8472001 1
 
1.0%
30.15162579 1
 
1.0%
118.5120914 1
 
1.0%
29.07148891 1
 
1.0%
442.0921209 1
 
1.0%
Other values (15) 15
 
15.0%
ValueCountFrequency (%)
0.0 76
76.0%
29.07148891 1
 
1.0%
30.15162579 1
 
1.0%
37.89699755 1
 
1.0%
48.2505047 1
 
1.0%
50.33174405 1
 
1.0%
67.4558653 1
 
1.0%
71.5919992 1
 
1.0%
96.83031943 1
 
1.0%
100.1365921 1
 
1.0%
ValueCountFrequency (%)
575.4890254 1
1.0%
570.812823 1
1.0%
442.0921209 1
1.0%
332.5240897 1
1.0%
261.3140902 1
1.0%
240.4490071 1
1.0%
212.6420686 1
1.0%
183.8472001 1
1.0%
174.4947955 1
1.0%
130.0115974 1
1.0%

공공처리소각
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59
Minimum0
Maximum966.52483
Zeros56
Zeros (%)56.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:49.242952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q351.54515
95-th percentile233.55733
Maximum966.52483
Range966.52483
Interquartile range (IQR)51.54515

Descriptive statistics

Standard deviation152.36849
Coefficient of variation (CV)2.5825167
Kurtosis19.404356
Mean59
Median Absolute Deviation (MAD)0
Skewness4.2284707
Sum5900
Variance23216.155
MonotonicityNot monotonic
2023-12-10T19:55:49.508929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 56
56.0%
86.26277865 1
 
1.0%
475.8890572 1
 
1.0%
168.7110263 1
 
1.0%
143.1809845 1
 
1.0%
227.2882889 1
 
1.0%
117.95066 1
 
1.0%
94.82074587 1
 
1.0%
101.4462959 1
 
1.0%
186.6262714 1
 
1.0%
Other values (35) 35
35.0%
ValueCountFrequency (%)
0.0 56
56.0%
5.348994106 1
 
1.0%
11.15384976 1
 
1.0%
11.28831252 1
 
1.0%
12.02293832 1
 
1.0%
13.40692085 1
 
1.0%
14.61052651 1
 
1.0%
14.87289287 1
 
1.0%
16.26343456 1
 
1.0%
16.97510331 1
 
1.0%
ValueCountFrequency (%)
966.5248331 1
1.0%
770.6172206 1
1.0%
686.7740727 1
1.0%
475.8890572 1
1.0%
352.669161 1
1.0%
227.2882889 1
1.0%
186.6262714 1
1.0%
168.7110263 1
1.0%
157.4352579 1
1.0%
143.1809845 1
1.0%

공공처리매립
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135
Minimum0
Maximum1604.8491
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:49.792666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q380.877719
95-th percentile858.77587
Maximum1604.8491
Range1604.8491
Interquartile range (IQR)80.877719

Descriptive statistics

Standard deviation305.7163
Coefficient of variation (CV)2.2645652
Kurtosis9.0290265
Mean135
Median Absolute Deviation (MAD)0
Skewness2.9449436
Sum13500
Variance93462.457
MonotonicityNot monotonic
2023-12-10T19:55:50.082481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 62
62.0%
274.1550398 1
 
1.0%
4.39943174 1
 
1.0%
4.387211096 1
 
1.0%
66.55362571 1
 
1.0%
4.130577578 1
 
1.0%
20.58567435 1
 
1.0%
8.291706766 1
 
1.0%
47.90492339 1
 
1.0%
32.44580908 1
 
1.0%
Other values (29) 29
29.0%
ValueCountFrequency (%)
0.0 62
62.0%
4.130577578 1
 
1.0%
4.387211096 1
 
1.0%
4.39943174 1
 
1.0%
8.291706766 1
 
1.0%
11.53017735 1
 
1.0%
20.58567435 1
 
1.0%
32.44580908 1
 
1.0%
47.90492339 1
 
1.0%
51.24726945 1
 
1.0%
ValueCountFrequency (%)
1604.849092 1
1.0%
1454.143983 1
1.0%
1027.348882 1
1.0%
945.8597652 1
1.0%
906.8843058 1
1.0%
856.2438508 1
1.0%
832.2878229 1
1.0%
750.4849092 1
1.0%
591.7082861 1
1.0%
466.157551 1
1.0%

공공처리기타
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:50.752141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:50.917259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

자가처리재활용
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:51.145326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:51.394798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

자가처리소각
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:51.576422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:51.763482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

자가처리매립
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:51.945791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:52.120579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

자가처리기타
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:52.328609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:52.532983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

위탁처리재활용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8
Minimum0
Maximum132.97983
Zeros69
Zeros (%)69.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:52.733696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38.3863532
95-th percentile35.469172
Maximum132.97983
Range132.97983
Interquartile range (IQR)8.3863532

Descriptive statistics

Standard deviation19.073793
Coefficient of variation (CV)2.3842242
Kurtosis21.361439
Mean8
Median Absolute Deviation (MAD)0
Skewness4.1284309
Sum800
Variance363.80959
MonotonicityNot monotonic
2023-12-10T19:55:52.985934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 69
69.0%
49.29301637 1
 
1.0%
14.70001218 1
 
1.0%
29.02521528 1
 
1.0%
13.62320762 1
 
1.0%
90.2189523 1
 
1.0%
19.22184662 1
 
1.0%
16.98592607 1
 
1.0%
132.9798281 1
 
1.0%
23.79090166 1
 
1.0%
Other values (22) 22
 
22.0%
ValueCountFrequency (%)
0.0 69
69.0%
3.056568061 1
 
1.0%
6.373628433 1
 
1.0%
6.450464295 1
 
1.0%
6.870250466 1
 
1.0%
7.661097628 1
 
1.0%
8.348872293 1
 
1.0%
8.498795926 1
 
1.0%
9.293391179 1
 
1.0%
9.700059032 1
 
1.0%
ValueCountFrequency (%)
132.9798281 1
1.0%
90.2189523 1
1.0%
54.40166415 1
1.0%
49.29301637 1
1.0%
47.70111133 1
1.0%
34.82538582 1
1.0%
32.06304289 1
1.0%
30.74184087 1
1.0%
29.02521528 1
1.0%
25.44016642 1
1.0%

위탁처리소각
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:53.198899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:53.354329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

위탁처리매립
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2
Minimum0
Maximum27.200832
Zeros79
Zeros (%)79.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:55:53.534920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.555523
Maximum27.200832
Range27.200832
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.0830189
Coefficient of variation (CV)2.5415094
Kurtosis10.412949
Mean2
Median Absolute Deviation (MAD)0
Skewness3.1537976
Sum200
Variance25.837081
MonotonicityNot monotonic
2023-12-10T19:55:53.767358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 79
79.0%
24.64650818 1
 
1.0%
3.435125233 1
 
1.0%
14.51260764 1
 
1.0%
4.850029516 1
 
1.0%
3.830548814 1
 
1.0%
7.350006091 1
 
1.0%
17.41269291 1
 
1.0%
16.03152144 1
 
1.0%
4.174436147 1
 
1.0%
Other values (12) 12
 
12.0%
ValueCountFrequency (%)
0.0 79
79.0%
1.52828403 1
 
1.0%
3.186814217 1
 
1.0%
3.225232147 1
 
1.0%
3.435125233 1
 
1.0%
3.830548814 1
 
1.0%
4.174436147 1
 
1.0%
4.249397963 1
 
1.0%
4.646695589 1
 
1.0%
4.850029516 1
 
1.0%
ValueCountFrequency (%)
27.20083208 1
1.0%
24.64650818 1
1.0%
17.41269291 1
1.0%
16.03152144 1
1.0%
15.37092044 1
1.0%
14.51260764 1
1.0%
12.72008321 1
1.0%
10.028954 1
1.0%
7.900975441 1
1.0%
7.492433542 1
1.0%

위탁처리기타
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:55:53.983736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:55:54.144970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

Interactions

2023-12-10T19:55:42.077911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:30.866722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.379921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.765785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:35.593116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.046061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:38.381480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:40.687766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:42.258656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:31.051334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.569366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.946685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:35.793959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.191962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:38.621914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:40.896863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:42.408459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:31.223618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.719668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:34.107965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:35.981632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.346143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:38.853175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.054016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:42.582376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:31.434975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.885752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:34.295170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:36.164692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.498990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:39.135016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.237518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:42.741520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:31.649801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.082074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:34.497102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:36.322467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.674450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:39.431780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.406705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:42.922560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:31.827484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.243301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:34.788567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:36.472516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:37.827037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:40.072244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.556256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:43.151223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.052086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.426285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:35.090719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:36.660272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:38.010900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:40.264965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.735913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:43.334590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:32.211835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:33.601413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:35.367411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:36.836868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:38.186504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:40.451097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:41.901556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:55:54.264013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명읍면동명총계재활용총계소각총계매립공공처리재활용공공처리소각공공처리매립위탁처리재활용위탁처리매립
시군구명1.0000.5670.2770.5770.4440.3300.5770.4440.5010.455
읍면동명0.5671.0001.0000.0000.8651.0000.0000.8651.0000.931
총계재활용0.2771.0001.0000.0000.0001.0000.0000.0000.0000.000
총계소각0.5770.0000.0001.0000.0000.0001.0000.0000.0000.000
총계매립0.4440.8650.0000.0001.0000.0000.0001.0000.7351.000
공공처리재활용0.3301.0001.0000.0000.0001.0000.0000.0000.0000.000
공공처리소각0.5770.0000.0001.0000.0000.0001.0000.0000.0000.000
공공처리매립0.4440.8650.0000.0001.0000.0000.0001.0000.7351.000
위탁처리재활용0.5011.0000.0000.0000.7350.0000.0000.7351.0000.762
위탁처리매립0.4550.9310.0000.0001.0000.0000.0001.0000.7621.000
2023-12-10T19:55:54.475314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계재활용총계소각총계매립공공처리재활용공공처리소각공공처리매립위탁처리재활용위탁처리매립시군구명
총계재활용1.000-0.389-0.0930.757-0.389-0.0940.3270.1930.136
총계소각-0.3891.0000.116-0.4661.0000.1150.1230.3680.347
총계매립-0.0930.1161.000-0.4190.1161.0000.5010.8000.233
공공처리재활용0.757-0.466-0.4191.000-0.466-0.419-0.364-0.2840.165
공공처리소각-0.3891.0000.116-0.4661.0000.1150.1230.3680.347
공공처리매립-0.0940.1151.000-0.4190.1151.0000.5000.7980.233
위탁처리재활용0.3270.1230.501-0.3640.1230.5001.0000.7250.288
위탁처리매립0.1930.3680.800-0.2840.3680.7980.7251.0000.240
시군구명0.1360.3470.2330.1650.3470.2330.2880.2401.000

Missing values

2023-12-10T19:55:43.616702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:55:44.077559image/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

조사년도시도명시군구명읍면동명총계재활용총계소각총계매립총계기타공공처리재활용공공처리소각공공처리매립공공처리기타자가처리재활용자가처리소각자가처리매립자가처리기타위탁처리재활용위탁처리소각위탁처리매립위탁처리기타
02019강원강릉시교1동49.29301686.2627791478.79049100.086.2627791454.1439830000049.293016024.6465080
12019강원강릉시초당동9.29339116.263435278.80173500.016.263435274.15504000009.29339104.6466960
22019강원강릉시경포동15.80195127.653414474.05852600.027.653414466.1575510000015.80195107.9009750
32019강원강릉시왕산면3.0565685.34899491.69704200.05.34899490.168758000003.05656801.5282840
42019강원강릉시성덕동54.40166495.2029121632.04992500.095.2029121604.8490920000054.401664027.2008320
52019강원강릉시연곡면12.41180321.720655372.35408200.021.720655366.1481810000012.41180306.2059010
62019강원강릉시교2동14.98486726.223517449.54601300.026.223517442.0535790000014.98486707.4924340
72019강원강릉시주문진읍30.74184153.798222922.25522600.053.798222906.8843060000030.741841015.370920
82019강원강릉시포남1동20.05790835.101339601.7372400.035.101339591.7082860000020.057908010.0289540
92019강원강릉시포남2동25.44016644.520291763.20499300.044.520291750.4849090000025.440166012.7200830
조사년도시도명시군구명읍면동명총계재활용총계소각총계매립총계기타공공처리재활용공공처리소각공공처리매립공공처리기타자가처리재활용자가처리소각자가처리매립자가처리기타위탁처리재활용위탁처리소각위탁처리매립위탁처리기타
902019강원원주시태장1동130.0115970.00.00130.0115970.00.0000000.000.00
912019강원원주시무실동442.0921210.00.00442.0921210.00.0000000.000.00
922019강원원주시귀래면29.0714890.00.0029.0714890.00.0000000.000.00
932019강원원주시흥업면118.5120910.00.00118.5120910.00.0000000.000.00
942019강원원주시부론면30.1516260.00.0030.1516260.00.0000000.000.00
952019강원원주시우산동183.84720.00.00183.84720.00.0000000.000.00
962019강원원주시명륜1동118.6306430.00.00118.6306430.00.0000000.000.00
972019강원원주시신림면48.2505050.00.0048.2505050.00.0000000.000.00
982019강원원주시중앙동37.8969980.00.0037.8969980.00.0000000.000.00
992019강원강릉시홍제동29.02521550.794127870.75645800.050.794127856.2438510000029.025215014.5126080