Overview

Dataset statistics

Number of variables20
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory169.3 B

Variable types

Numeric3
Categorical15
Text2

Dataset

Description에너지다소비사업자의 에너지사용량신고에 대한 데이터로 지역(광역시)별, 연도별, 부문별 다소비사업자의 ‘로’설비의 에너지사용량에 대한 데이터 개방
Author한국에너지공단
URLhttps://www.data.go.kr/data/15086731/fileData.do

Alerts

대전 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
전남 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
인천 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
제주 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
경남 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
강원 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
울산 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
광주 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
세종 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
충남 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
전북 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
대구 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
경북 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
충북 is highly overall correlated with 경기 and 14 other fieldsHigh correlation
경기 is highly overall correlated with 총합계 and 15 other fieldsHigh correlation
총합계 is highly overall correlated with 경기 and 15 other fieldsHigh correlation
부문 is highly overall correlated with 경기 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 21:53:05.045112
Analysis finished2023-12-12 21:53:07.985013
Duration2.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T06:53:08.029845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2019
Q32021
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0493902
Coefficient of variation (CV)0.0010150521
Kurtosis-1.2573099
Mean2019
Median Absolute Deviation (MAD)2
Skewness0
Sum42399
Variance4.2
MonotonicityIncreasing
2023-12-13T06:53:08.144212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2016 3
14.3%
2017 3
14.3%
2018 3
14.3%
2019 3
14.3%
2020 3
14.3%
2021 3
14.3%
2022 3
14.3%
ValueCountFrequency (%)
2016 3
14.3%
2017 3
14.3%
2018 3
14.3%
2019 3
14.3%
2020 3
14.3%
2021 3
14.3%
2022 3
14.3%
ValueCountFrequency (%)
2022 3
14.3%
2021 3
14.3%
2020 3
14.3%
2019 3
14.3%
2018 3
14.3%
2017 3
14.3%
2016 3
14.3%

부문
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
산업
7 
건물
7 
수송
7 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산업
2nd row건물
3rd row수송
4th row산업
5th row건물

Common Values

ValueCountFrequency (%)
산업 7
33.3%
건물 7
33.3%
수송 7
33.3%

Length

2023-12-13T06:53:08.272109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:08.726264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산업 7
33.3%
건물 7
33.3%
수송 7
33.3%

강원
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
170332.9196
 
1
171271.612
 
1
183984.1923
 
1
171813.9504
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.2857143
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row170332.9196
2nd row해당없음
3rd row해당없음
4th row171271.612
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
170332.9196 1
 
4.8%
171271.612 1
 
4.8%
183984.1923 1
 
4.8%
171813.9504 1
 
4.8%
149688.3014 1
 
4.8%
157759.5313 1
 
4.8%
164883.0522 1
 
4.8%

Length

2023-12-13T06:53:08.905504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:09.022500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
170332.9196 1
 
4.8%
171271.612 1
 
4.8%
183984.1923 1
 
4.8%
171813.9504 1
 
4.8%
149688.3014 1
 
4.8%
157759.5313 1
 
4.8%
164883.0522 1
 
4.8%

경기
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162763.78
Minimum3.297
Maximum541399.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T06:53:09.124928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.297
5-th percentile3.784
Q13.784
median67.137
Q3443743.77
95-th percentile534998.99
Maximum541399.52
Range541396.22
Interquartile range (IQR)443739.99

Descriptive statistics

Standard deviation237054.79
Coefficient of variation (CV)1.4564345
Kurtosis-1.4569401
Mean162763.78
Median Absolute Deviation (MAD)63.353
Skewness0.79879506
Sum3418039.5
Variance5.6194974 × 1010
MonotonicityNot monotonic
2023-12-13T06:53:09.238602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3.784 5
23.8%
534998.9925 1
 
4.8%
446976.071 1
 
4.8%
3.297 1
 
4.8%
98.19 1
 
4.8%
443743.773 1
 
4.8%
39.241 1
 
4.8%
442407.0004 1
 
4.8%
67.137 1
 
4.8%
57.821 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
3.297 1
 
4.8%
3.784 5
23.8%
3.87 1
 
4.8%
36.221 1
 
4.8%
39.241 1
 
4.8%
57.821 1
 
4.8%
67.137 1
 
4.8%
98.19 1
 
4.8%
136.781 1
 
4.8%
166.331 1
 
4.8%
ValueCountFrequency (%)
541399.5208 1
4.8%
534998.9925 1
4.8%
520640.0738 1
4.8%
487246.2404 1
4.8%
446976.071 1
4.8%
443743.773 1
4.8%
442407.0004 1
4.8%
166.331 1
4.8%
136.781 1
4.8%
98.19 1
4.8%

경남
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
11 
313.845
2 
419545.2892
 
1
297.255
 
1
396155.8895
 
1
Other values (5)
5 

Length

Max length11
Median length4
Mean length6.7619048
Min length4

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st row419545.2892
2nd row297.255
3rd row해당없음
4th row396155.8895
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 11
52.4%
313.845 2
 
9.5%
419545.2892 1
 
4.8%
297.255 1
 
4.8%
396155.8895 1
 
4.8%
388558.2327 1
 
4.8%
351374.9555 1
 
4.8%
342071.9148 1
 
4.8%
353314.7746 1
 
4.8%
381345.6333 1
 
4.8%

Length

2023-12-13T06:53:09.360364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:09.494915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 11
52.4%
313.845 2
 
9.5%
419545.2892 1
 
4.8%
297.255 1
 
4.8%
396155.8895 1
 
4.8%
388558.2327 1
 
4.8%
351374.9555 1
 
4.8%
342071.9148 1
 
4.8%
353314.7746 1
 
4.8%
381345.6333 1
 
4.8%

경북
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
8812699.499
 
1
8554984.733
 
1
8775020.834
 
1
8965757.214
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.3333333
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row8812699.499
2nd row해당없음
3rd row해당없음
4th row8554984.733
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
8812699.499 1
 
4.8%
8554984.733 1
 
4.8%
8775020.834 1
 
4.8%
8965757.214 1
 
4.8%
8656986.808 1
 
4.8%
8134175.061 1
 
4.8%
6286998.216 1
 
4.8%

Length

2023-12-13T06:53:09.655745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:09.793326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
8812699.499 1
 
4.8%
8554984.733 1
 
4.8%
8775020.834 1
 
4.8%
8965757.214 1
 
4.8%
8656986.808 1
 
4.8%
8134175.061 1
 
4.8%
6286998.216 1
 
4.8%

광주
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
8692.047552
 
1
9350.57576
 
1
9926.53924
 
1
7868.6699
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length5.9047619
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row8692.047552
2nd row해당없음
3rd row해당없음
4th row9350.57576
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
8692.047552 1
 
4.8%
9350.57576 1
 
4.8%
9926.53924 1
 
4.8%
7868.6699 1
 
4.8%
9458.38 1
 
4.8%
7930.07704 1
 
4.8%
6473.866297 1
 
4.8%

Length

2023-12-13T06:53:09.937089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:10.095648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
8692.047552 1
 
4.8%
9350.57576 1
 
4.8%
9926.53924 1
 
4.8%
7868.6699 1
 
4.8%
9458.38 1
 
4.8%
7930.07704 1
 
4.8%
6473.866297 1
 
4.8%

대구
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
39220.18452
 
1
37930.01216
 
1
34310.1043
 
1
33652.52747
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.2857143
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row39220.18452
2nd row해당없음
3rd row해당없음
4th row37930.01216
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
39220.18452 1
 
4.8%
37930.01216 1
 
4.8%
34310.1043 1
 
4.8%
33652.52747 1
 
4.8%
32260.66657 1
 
4.8%
32102.94779 1
 
4.8%
31345.54215 1
 
4.8%

Length

2023-12-13T06:53:10.250957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:10.373215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
39220.18452 1
 
4.8%
37930.01216 1
 
4.8%
34310.1043 1
 
4.8%
33652.52747 1
 
4.8%
32260.66657 1
 
4.8%
32102.94779 1
 
4.8%
31345.54215 1
 
4.8%

대전
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
11203.34501
 
1
9646.935524
 
1
11692.52741
 
1
11067.7324
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.2857143
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row11203.34501
2nd row해당없음
3rd row해당없음
4th row9646.935524
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
11203.34501 1
 
4.8%
9646.935524 1
 
4.8%
11692.52741 1
 
4.8%
11067.7324 1
 
4.8%
10046.49523 1
 
4.8%
14473.40068 1
 
4.8%
9120.270559 1
 
4.8%

Length

2023-12-13T06:53:10.547037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:10.689887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
11203.34501 1
 
4.8%
9646.935524 1
 
4.8%
11692.52741 1
 
4.8%
11067.7324 1
 
4.8%
10046.49523 1
 
4.8%
14473.40068 1
 
4.8%
9120.270559 1
 
4.8%

부산
Text

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T06:53:10.854633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.952381
Min length4

Characters and Unicode

Total characters146
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)71.4%

Sample

1st row237692.9814
2nd row20.86
3rd row0.095
4th row254109.2293
5th row16.464
ValueCountFrequency (%)
해당없음 6
28.6%
237692.9814 1
 
4.8%
20.86 1
 
4.8%
0.095 1
 
4.8%
254109.2293 1
 
4.8%
16.464 1
 
4.8%
0.215 1
 
4.8%
224743.9914 1
 
4.8%
26.754 1
 
4.8%
246481.8937 1
 
4.8%
Other values (6) 6
28.6%
2023-12-13T06:53:11.167415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19
13.0%
6 15
10.3%
. 15
10.3%
1 15
10.3%
4 12
8.2%
9 11
 
7.5%
3 10
 
6.8%
0 8
 
5.5%
7 7
 
4.8%
해 6
 
4.1%
Other values (5) 28
19.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107
73.3%
Other Letter 24
 
16.4%
Other Punctuation 15
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19
17.8%
6 15
14.0%
1 15
14.0%
4 12
11.2%
9 11
10.3%
3 10
9.3%
0 8
7.5%
7 7
 
6.5%
8 5
 
4.7%
5 5
 
4.7%
Other Letter
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%
Other Punctuation
ValueCountFrequency (%)
. 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122
83.6%
Hangul 24
 
16.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19
15.6%
6 15
12.3%
. 15
12.3%
1 15
12.3%
4 12
9.8%
9 11
9.0%
3 10
8.2%
0 8
6.6%
7 7
 
5.7%
8 5
 
4.1%
Hangul
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
83.6%
Hangul 24
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19
15.6%
6 15
12.3%
. 15
12.3%
1 15
12.3%
4 12
9.8%
9 11
9.0%
3 10
8.2%
0 8
6.6%
7 7
 
5.7%
8 5
 
4.1%
Hangul
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%

서울
Text

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T06:53:11.359866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.952381
Min length4

Characters and Unicode

Total characters146
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)71.4%

Sample

1st row3010.213736
2nd row75.096
3rd row8.79
4th row3737.04868
5th row71.283
ValueCountFrequency (%)
해당없음 6
28.6%
3010.213736 1
 
4.8%
75.096 1
 
4.8%
8.79 1
 
4.8%
3737.04868 1
 
4.8%
71.283 1
 
4.8%
4164.507416 1
 
4.8%
71.678 1
 
4.8%
2977.574088 1
 
4.8%
75.246 1
 
4.8%
Other values (6) 6
28.6%
2023-12-13T06:53:11.680479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 20
13.7%
. 15
10.3%
3 14
9.6%
6 13
8.9%
2 12
 
8.2%
8 9
 
6.2%
4 9
 
6.2%
0 8
 
5.5%
1 8
 
5.5%
5 7
 
4.8%
Other values (5) 31
21.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107
73.3%
Other Letter 24
 
16.4%
Other Punctuation 15
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 20
18.7%
3 14
13.1%
6 13
12.1%
2 12
11.2%
8 9
8.4%
4 9
8.4%
0 8
 
7.5%
1 8
 
7.5%
5 7
 
6.5%
9 7
 
6.5%
Other Letter
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%
Other Punctuation
ValueCountFrequency (%)
. 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122
83.6%
Hangul 24
 
16.4%

Most frequent character per script

Common
ValueCountFrequency (%)
7 20
16.4%
. 15
12.3%
3 14
11.5%
6 13
10.7%
2 12
9.8%
8 9
7.4%
4 9
7.4%
0 8
 
6.6%
1 8
 
6.6%
5 7
 
5.7%
Hangul
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
83.6%
Hangul 24
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 20
16.4%
. 15
12.3%
3 14
11.5%
6 13
10.7%
2 12
9.8%
8 9
7.4%
4 9
7.4%
0 8
 
6.6%
1 8
 
6.6%
5 7
 
5.7%
Hangul
ValueCountFrequency (%)
해 6
25.0%
당 6
25.0%
없 6
25.0%
음 6
25.0%

세종
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
11715.24425
 
1
16361.45494
 
1
21702.28463
 
1
19944.9874
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.1904762
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row11715.24425
2nd row해당없음
3rd row해당없음
4th row16361.45494
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
11715.24425 1
 
4.8%
16361.45494 1
 
4.8%
21702.28463 1
 
4.8%
19944.9874 1
 
4.8%
23572.645 1
 
4.8%
25726.57738 1
 
4.8%
26974.66875 1
 
4.8%

Length

2023-12-13T06:53:11.829935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:11.975444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
11715.24425 1
 
4.8%
16361.45494 1
 
4.8%
21702.28463 1
 
4.8%
19944.9874 1
 
4.8%
23572.645 1
 
4.8%
25726.57738 1
 
4.8%
26974.66875 1
 
4.8%

울산
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
4540501.813
 
1
4775145.367
 
1
4237155.612
 
1
4186922.055
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.3333333
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row4540501.813
2nd row해당없음
3rd row해당없음
4th row4775145.367
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
4540501.813 1
 
4.8%
4775145.367 1
 
4.8%
4237155.612 1
 
4.8%
4186922.055 1
 
4.8%
5062413.945 1
 
4.8%
5007903.067 1
 
4.8%
4816069.135 1
 
4.8%

Length

2023-12-13T06:53:12.125208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:12.247436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
4540501.813 1
 
4.8%
4775145.367 1
 
4.8%
4237155.612 1
 
4.8%
4186922.055 1
 
4.8%
5062413.945 1
 
4.8%
5007903.067 1
 
4.8%
4816069.135 1
 
4.8%

인천
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
13 
1093367.743
 
1
1124311.731
 
1
1085626.731
 
1
1084714.381
 
1
Other values (4)
4 

Length

Max length11
Median length4
Mean length6.4761905
Min length4

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st row1093367.743
2nd row해당없음
3rd row해당없음
4th row1124311.731
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 13
61.9%
1093367.743 1
 
4.8%
1124311.731 1
 
4.8%
1085626.731 1
 
4.8%
1084714.381 1
 
4.8%
1075458.982 1
 
4.8%
1069240.192 1
 
4.8%
902134.9832 1
 
4.8%
892.644 1
 
4.8%

Length

2023-12-13T06:53:12.372654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:12.503869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 13
61.9%
1093367.743 1
 
4.8%
1124311.731 1
 
4.8%
1085626.731 1
 
4.8%
1084714.381 1
 
4.8%
1075458.982 1
 
4.8%
1069240.192 1
 
4.8%
902134.9832 1
 
4.8%
892.644 1
 
4.8%

전남
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
5198859.851
 
1
5215206.124
 
1
5360256.114
 
1
5331552.13
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.1904762
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row5198859.851
2nd row해당없음
3rd row해당없음
4th row5215206.124
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
5198859.851 1
 
4.8%
5215206.124 1
 
4.8%
5360256.114 1
 
4.8%
5331552.13 1
 
4.8%
5033907.187 1
 
4.8%
5383790.85 1
 
4.8%
7470660.37 1
 
4.8%

Length

2023-12-13T06:53:12.641440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:12.782621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
5198859.851 1
 
4.8%
5215206.124 1
 
4.8%
5360256.114 1
 
4.8%
5331552.13 1
 
4.8%
5033907.187 1
 
4.8%
5383790.85 1
 
4.8%
7470660.37 1
 
4.8%

전북
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
245777.8287
 
1
244377.4671
 
1
223322.0899
 
1
216254.2612
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.3333333
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row245777.8287
2nd row해당없음
3rd row해당없음
4th row244377.4671
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
245777.8287 1
 
4.8%
244377.4671 1
 
4.8%
223322.0899 1
 
4.8%
216254.2612 1
 
4.8%
204852.5071 1
 
4.8%
232667.4953 1
 
4.8%
244139.3073 1
 
4.8%

Length

2023-12-13T06:53:12.942495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:13.077260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
245777.8287 1
 
4.8%
244377.4671 1
 
4.8%
223322.0899 1
 
4.8%
216254.2612 1
 
4.8%
204852.5071 1
 
4.8%
232667.4953 1
 
4.8%
244139.3073 1
 
4.8%

제주
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
19.491
 
1
16.426
 
1
15.309
 
1
35.089
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length5.3809524
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row19.491
2nd row해당없음
3rd row해당없음
4th row16.426
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
19.491 1
 
4.8%
16.426 1
 
4.8%
15.309 1
 
4.8%
35.089 1
 
4.8%
1725.728872 1
 
4.8%
1758.152568 1
 
4.8%
1790.203773 1
 
4.8%

Length

2023-12-13T06:53:13.244097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:13.418651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
19.491 1
 
4.8%
16.426 1
 
4.8%
15.309 1
 
4.8%
35.089 1
 
4.8%
1725.728872 1
 
4.8%
1758.152568 1
 
4.8%
1790.203773 1
 
4.8%

충남
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
4832209.311
 
1
4978157.877
 
1
5181391.668
 
1
4942891.837
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.3333333
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row4832209.311
2nd row해당없음
3rd row해당없음
4th row4978157.877
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
4832209.311 1
 
4.8%
4978157.877 1
 
4.8%
5181391.668 1
 
4.8%
4942891.837 1
 
4.8%
4828519.494 1
 
4.8%
5064783.397 1
 
4.8%
5361303.848 1
 
4.8%

Length

2023-12-13T06:53:13.564795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:13.724154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
4832209.311 1
 
4.8%
4978157.877 1
 
4.8%
5181391.668 1
 
4.8%
4942891.837 1
 
4.8%
4828519.494 1
 
4.8%
5064783.397 1
 
4.8%
5361303.848 1
 
4.8%

충북
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
해당없음
14 
477458.6613
 
1
341476.648
 
1
422963.1611
 
1
378319.6219
 
1
Other values (3)
3 

Length

Max length11
Median length4
Mean length6.2380952
Min length4

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row477458.6613
2nd row해당없음
3rd row해당없음
4th row341476.648
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 14
66.7%
477458.6613 1
 
4.8%
341476.648 1
 
4.8%
422963.1611 1
 
4.8%
378319.6219 1
 
4.8%
393903.3113 1
 
4.8%
491379.4917 1
 
4.8%
394877.628 1
 
4.8%

Length

2023-12-13T06:53:13.895885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:53:14.053241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 14
66.7%
477458.6613 1
 
4.8%
341476.648 1
 
4.8%
422963.1611 1
 
4.8%
378319.6219 1
 
4.8%
393903.3113 1
 
4.8%
491379.4917 1
 
4.8%
394877.628 1
 
4.8%

총합계
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8873052.1
Minimum3.297
Maximum26742300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T06:53:14.183544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.297
5-th percentile3.784
Q13.999
median448.498
Q326508528
95-th percentile26706233
Maximum26742300
Range26742297
Interquartile range (IQR)26508524

Descriptive statistics

Standard deviation12858090
Coefficient of variation (CV)1.449117
Kurtosis-1.5787044
Mean8873052.1
Median Absolute Deviation (MAD)444.714
Skewness0.76277618
Sum1.863341 × 108
Variance1.6533049 × 1014
MonotonicityNot monotonic
2023-12-13T06:53:14.351281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3.784 4
19.0%
26637305.42 1
 
4.8%
471.075 1
 
4.8%
3.297 1
 
4.8%
1088.585 1
 
4.8%
26742299.91 1
 
4.8%
113.251 1
 
4.8%
26644890.51 1
 
4.8%
142.503 1
 
4.8%
26508528.34 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
3.297 1
 
4.8%
3.784 4
19.0%
3.999 1
 
4.8%
12.755 1
 
4.8%
113.251 1
 
4.8%
142.503 1
 
4.8%
224.528 1
 
4.8%
448.498 1
 
4.8%
471.075 1
 
4.8%
559.542 1
 
4.8%
ValueCountFrequency (%)
26742299.91 1
4.8%
26706233.42 1
4.8%
26652879.2 1
4.8%
26644890.51 1
4.8%
26637305.42 1
4.8%
26508528.34 1
4.8%
26438875.12 1
4.8%
1088.585 1
4.8%
559.542 1
4.8%
471.075 1
4.8%

Interactions

2023-12-13T06:53:07.314273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:06.764676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:07.043764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:07.413296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:06.866762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:07.131713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:07.487544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:06.957863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:07.221625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:53:14.481214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도부문강원경기경남경북광주대구대전부산서울세종울산인천전남전북제주충남충북총합계
연도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.4750.0000.0000.0000.1630.0000.0000.0000.0000.0000.000
부문0.0001.0000.6280.9270.7360.6280.6280.6280.6280.8831.0000.6280.6280.7980.6280.6280.6280.6280.6281.000
강원0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경기0.0000.9271.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경남0.0000.7361.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9691.0001.0001.0001.0001.0001.000
경북0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
광주0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대구0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대전0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
부산0.4750.8831.0001.0001.0001.0001.0001.0001.0001.0000.9971.0001.0001.0001.0001.0001.0001.0001.0001.000
서울0.0001.0001.0001.0001.0001.0001.0001.0001.0000.9971.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
세종0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
울산0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인천0.1630.7981.0001.0000.9691.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전남0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전북0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
제주0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
충남0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
충북0.0000.6281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총합계0.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T06:53:14.668861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대전전남인천제주경남강원울산광주세종충남부문전북대구경북충북
대전1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
전남1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
인천0.9610.9611.0000.9610.8440.9610.9610.9610.9610.9610.3920.9610.9610.9610.961
제주1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
경남0.9200.9200.8440.9201.0000.9200.9200.9200.9200.9200.4550.9200.9200.9200.920
강원1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
울산1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
광주1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
세종1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
충남1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
부문0.4080.4080.3920.4080.4550.4080.4080.4080.4080.4081.0000.4080.4080.4080.408
전북1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
대구1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
경북1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
충북1.0001.0000.9611.0000.9201.0001.0001.0001.0001.0000.4081.0001.0001.0001.000
2023-12-13T06:53:14.842431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도경기총합계부문강원경남경북광주대구대전세종울산인천전남전북제주충남충북
연도1.000-0.210-0.0790.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
경기-0.2101.0000.9400.6670.8500.7820.8500.8500.8500.8500.8500.8500.8160.8500.8500.8500.8500.850
총합계-0.0790.9401.0000.9730.8270.7610.8270.8270.8270.8270.8270.8270.7950.8270.8270.8270.8270.827
부문0.0000.6670.9731.0000.4080.4550.4080.4080.4080.4080.4080.4080.3920.4080.4080.4080.4080.408
강원0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
경남0.0000.7820.7610.4550.9201.0000.9200.9200.9200.9200.9200.9200.8440.9200.9200.9200.9200.920
경북0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
광주0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
대구0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
대전0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
세종0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
울산0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
인천0.0000.8160.7950.3920.9610.8440.9610.9610.9610.9610.9610.9611.0000.9610.9610.9610.9610.961
전남0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
전북0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
제주0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
충남0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000
충북0.0000.8500.8270.4081.0000.9201.0001.0001.0001.0001.0001.0000.9611.0001.0001.0001.0001.000

Missing values

2023-12-13T06:53:07.627463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:53:07.899965image/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

연도부문강원경기경남경북광주대구대전부산서울세종울산인천전남전북제주충남충북총합계
02016산업170332.9196534998.9925419545.28928812699.4998692.04755239220.1845211203.34501237692.98143010.21373611715.244254540501.8131093367.7435198859.851245777.828719.4914832209.311477458.661326637305.42
12016건물해당없음166.331297.255해당없음해당없음해당없음해당없음20.8675.096해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음559.542
22016수송해당없음3.87해당없음해당없음해당없음해당없음해당없음0.0958.79해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음12.755
32017산업171271.612520640.0738396155.88958554984.7339350.5757637930.012169646.935524254109.22933737.0486816361.454944775145.3671124311.7315215206.124244377.467116.4264978157.877341476.64826652879.2
42017건물해당없음136.781해당없음해당없음해당없음해당없음해당없음16.46471.283해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음224.528
52017수송해당없음3.784해당없음해당없음해당없음해당없음해당없음0.215해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.999
62018산업183984.1923541399.5208388558.23278775020.8349926.5392434310.104311692.52741224743.99144164.50741621702.284634237155.6121085626.7315360256.114223322.089915.3095181391.668422963.161126706233.42
72018건물해당없음36.221313.845해당없음해당없음해당없음해당없음26.75471.678해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음448.498
82018수송해당없음3.784해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.784
92019산업171813.9504487246.2404351374.95558965757.2147868.669933652.5274711067.7324246481.89372977.57408819944.98744186922.0551084714.3815331552.13216254.261235.0894942891.837378319.621926438875.12
연도부문강원경기경남경북광주대구대전부산서울세종울산인천전남전북제주충남충북총합계
112019수송해당없음3.784해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.784
122020산업149688.3014446976.071342071.91488656986.8089458.3832260.6665710046.49523233362.06563323.83322423572.6455062413.9451075458.9825033907.187204852.50711725.7288724828519.494393903.311326508528.34
132020건물해당없음67.137해당없음해당없음해당없음해당없음해당없음해당없음75.366해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음142.503
142020수송해당없음3.784해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.784
152021산업157759.5313442407.0004353314.77468134175.0617930.0770432102.9477914473.40068222731.60162746.89699225726.577385007903.0671069240.1925383790.85232667.49531758.1525685064783.397491379.491726644890.51
162021건물해당없음39.241해당없음해당없음해당없음해당없음해당없음10.96163.049해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음113.251
172021수송해당없음3.784해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.784
182022산업164883.0522443743.773381345.63336286998.2166473.86629731345.542159120.270559197921.71362517.70322726974.668754816069.135902134.98327470660.37244139.30731790.2037735361303.848394877.62826742299.91
192022건물해당없음98.19해당없음해당없음해당없음해당없음해당없음26.18471.567해당없음해당없음892.644해당없음해당없음해당없음해당없음해당없음1088.585
202022수송해당없음3.297해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음해당없음3.297