Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory43.3 B

Variable types

Categorical3
Text1
Numeric1

Alerts

년도 has constant value ""Constant
구분 has constant value ""Constant

Reproduction

Analysis started2023-12-10 11:08:13.078481
Analysis finished2023-12-10 11:08:14.085456
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2018
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 100
100.0%

Length

2023-12-10T20:08:14.182961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:08:14.342823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 100
100.0%

행정구역시도명(시도)
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
32 
경상북도
24 
강원도
19 
경상남도
19 
전라남도
6 

Length

Max length4
Median length3
Mean length3.49
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 32
32.0%
경상북도 24
24.0%
강원도 19
19.0%
경상남도 19
19.0%
전라남도 6
 
6.0%

Length

2023-12-10T20:08:14.502792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:08:14.669586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 32
32.0%
경상북도 24
24.0%
강원도 19
19.0%
경상남도 19
19.0%
전라남도 6
 
6.0%

행정구역시군구명(시군구)
Text

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:08:15.062773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.98
Min length2

Characters and Unicode

Total characters298
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)93.0%

Sample

1st row전체
2nd row강릉시
3rd row고성군
4th row동해시
5th row삼척시
ValueCountFrequency (%)
전체 5
 
5.0%
고성군 2
 
2.0%
울진군 1
 
1.0%
군위군 1
 
1.0%
경주시 1
 
1.0%
경산시 1
 
1.0%
합천군 1
 
1.0%
함양군 1
 
1.0%
함안군 1
 
1.0%
하동군 1
 
1.0%
Other values (85) 85
85.0%
2023-12-10T20:08:15.601063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 55
18.5%
군 43
 
14.4%
천 14
 
4.7%
양 13
 
4.4%
주 11
 
3.7%
성 9
 
3.0%
영 6
 
2.0%
산 5
 
1.7%
체 5
 
1.7%
안 5
 
1.7%
Other values (73) 132
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 55
18.5%
군 43
 
14.4%
천 14
 
4.7%
양 13
 
4.4%
주 11
 
3.7%
성 9
 
3.0%
영 6
 
2.0%
산 5
 
1.7%
체 5
 
1.7%
안 5
 
1.7%
Other values (73) 132
44.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 55
18.5%
군 43
 
14.4%
천 14
 
4.7%
양 13
 
4.4%
주 11
 
3.7%
성 9
 
3.0%
영 6
 
2.0%
산 5
 
1.7%
체 5
 
1.7%
안 5
 
1.7%
Other values (73) 132
44.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 55
18.5%
군 43
 
14.4%
천 14
 
4.7%
양 13
 
4.4%
주 11
 
3.7%
성 9
 
3.0%
영 6
 
2.0%
산 5
 
1.7%
체 5
 
1.7%
안 5
 
1.7%
Other values (73) 132
44.3%

구분
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공당연이용량 100
100.0%

Length

2023-12-10T20:08:15.791152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:08:15.917712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공당연이용량 100
100.0%

공당지하수이용량(㎥/년/공)
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2581.52
Minimum430
Maximum10605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:08:16.075729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum430
5-th percentile952.5
Q11487.5
median1880.5
Q33127
95-th percentile5888.95
Maximum10605
Range10175
Interquartile range (IQR)1639.5

Descriptive statistics

Standard deviation1830.4705
Coefficient of variation (CV)0.70906693
Kurtosis4.2273303
Mean2581.52
Median Absolute Deviation (MAD)615
Skewness1.92964
Sum258152
Variance3350622.1
MonotonicityNot monotonic
2023-12-10T20:08:16.293366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1440 3
 
3.0%
1510 2
 
2.0%
1735 2
 
2.0%
1595 1
 
1.0%
8692 1
 
1.0%
3773 1
 
1.0%
4392 1
 
1.0%
2871 1
 
1.0%
5281 1
 
1.0%
1266 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
430 1
1.0%
625 1
1.0%
639 1
1.0%
748 1
1.0%
772 1
1.0%
962 1
1.0%
1032 1
1.0%
1054 1
1.0%
1067 1
1.0%
1116 1
1.0%
ValueCountFrequency (%)
10605 1
1.0%
8692 1
1.0%
7861 1
1.0%
6594 1
1.0%
6534 1
1.0%
5855 1
1.0%
5854 1
1.0%
5754 1
1.0%
5478 1
1.0%
5382 1
1.0%

Interactions

2023-12-10T20:08:13.321508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:08:16.435628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역시도명(시도)행정구역시군구명(시군구)공당지하수이용량(㎥/년/공)
행정구역시도명(시도)1.0000.0000.389
행정구역시군구명(시군구)0.0001.0000.983
공당지하수이용량(㎥/년/공)0.3890.9831.000
2023-12-10T20:08:16.581392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공당지하수이용량(㎥/년/공)행정구역시도명(시도)
공당지하수이용량(㎥/년/공)1.0000.166
행정구역시도명(시도)0.1661.000

Missing values

2023-12-10T20:08:13.836770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:08:14.016343image/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

년도행정구역시도명(시도)행정구역시군구명(시군구)구분공당지하수이용량(㎥/년/공)
02018강원도전체공당연이용량1595
12018강원도강릉시공당연이용량1229
22018강원도고성군공당연이용량2922
32018강원도동해시공당연이용량5754
42018강원도삼척시공당연이용량7861
52018강원도속초시공당연이용량1929
62018강원도양구군공당연이용량1204
72018강원도양양군공당연이용량1032
82018강원도영월군공당연이용량3175
92018강원도원주시공당연이용량772
년도행정구역시도명(시도)행정구역시군구명(시군구)구분공당지하수이용량(㎥/년/공)
902018경상북도청도군공당연이용량2401
912018경상북도청송군공당연이용량3373
922018경상북도칠곡군공당연이용량2288
932018경상북도포항시공당연이용량5322
942018전라남도전체공당연이용량1498
952018전라남도강진군공당연이용량1440
962018전라남도고흥군공당연이용량962
972018전라남도곡성군공당연이용량1126
982018전라남도광양시공당연이용량1671
992018전라남도구례군공당연이용량1510