Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory66.3 B

Variable types

Categorical6
Numeric1
Text1

Alerts

전망월 has constant value ""Constant
수원_취수구분 has constant value ""Constant
전망1월 has constant value ""Constant
전망2월 has constant value ""Constant
전망3월 has constant value ""Constant
등록일자 has constant value ""Constant
행정동코드 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:34:35.972147
Analysis finished2023-12-10 10:34:37.364525
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전망월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2021-01
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01
2nd row2021-01
3rd row2021-01
4th row2021-01
5th row2021-01

Common Values

ValueCountFrequency (%)
2021-01 100
100.0%

Length

2023-12-10T19:34:37.594254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:37.794019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01 100
100.0%

행정동코드
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6247677 × 109
Minimum4.61108 × 109
Maximum4.672033 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:34:37.995757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.61108 × 109
5-th percentile4.613033 × 109
Q14.6130798 × 109
median4.6150628 × 109
Q34.6230322 × 109
95-th percentile4.67104 × 109
Maximum4.672033 × 109
Range60953000
Interquartile range (IQR)9952500

Descriptive statistics

Standard deviation20630422
Coefficient of variation (CV)0.0044608559
Kurtosis1.3981823
Mean4.6247677 × 109
Median Absolute Deviation (MAD)1992000
Skewness1.7977527
Sum4.6247677 × 1011
Variance4.2561431 × 1014
MonotonicityNot monotonic
2023-12-10T19:34:38.334784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4611081000 1
 
1.0%
4617043000 1
 
1.0%
4623033000 1
 
1.0%
4623032000 1
 
1.0%
4623031000 1
 
1.0%
4623025000 1
 
1.0%
4617060000 1
 
1.0%
4617058000 1
 
1.0%
4617055000 1
 
1.0%
4617054000 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
4611080000 1
1.0%
4611081000 1
1.0%
4613025000 1
1.0%
4613031000 1
1.0%
4613032000 1
1.0%
4613033000 1
1.0%
4613034000 1
1.0%
4613035000 1
1.0%
4613036000 1
1.0%
4613051500 1
1.0%
ValueCountFrequency (%)
4672033000 1
1.0%
4672032000 1
1.0%
4672031000 1
1.0%
4672025000 1
1.0%
4671041000 1
1.0%
4671040000 1
1.0%
4671039000 1
1.0%
4671038000 1
1.0%
4671037000 1
1.0%
4671036000 1
1.0%

주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:34:38.941495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.96
Min length9

Characters and Unicode

Total characters996
Distinct characters105
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

Unique100 ?
Unique (%)100.0%

Sample

1st row전라남도목포시부주동
2nd row전라남도여수시돌산읍
3rd row전라남도여수시소라면
4th row전라남도여수시율촌면
5th row전라남도여수시화양면
ValueCountFrequency (%)
전라남도목포시부주동 1
 
1.0%
전라남도나주시산포면 1
 
1.0%
전라남도광양시옥룡면 1
 
1.0%
전라남도광양시봉강면 1
 
1.0%
전라남도광양시광양읍 1
 
1.0%
전라남도나주시이창동 1
 
1.0%
전라남도나주시영산동 1
 
1.0%
전라남도나주시성북동 1
 
1.0%
전라남도나주시금남동 1
 
1.0%
전라남도나주시영강동 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:34:39.759823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
남 106
 
10.6%
전 104
 
10.4%
도 103
 
10.3%
라 101
 
10.1%
시 86
 
8.6%
동 48
 
4.8%
면 48
 
4.8%
여 29
 
2.9%
수 29
 
2.9%
천 27
 
2.7%
Other values (95) 315
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 994
99.8%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 106
 
10.7%
전 104
 
10.5%
도 103
 
10.4%
라 101
 
10.2%
시 86
 
8.7%
동 48
 
4.8%
면 48
 
4.8%
여 29
 
2.9%
수 29
 
2.9%
천 27
 
2.7%
Other values (93) 313
31.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 994
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 106
 
10.7%
전 104
 
10.5%
도 103
 
10.4%
라 101
 
10.2%
시 86
 
8.7%
동 48
 
4.8%
면 48
 
4.8%
여 29
 
2.9%
수 29
 
2.9%
천 27
 
2.7%
Other values (93) 313
31.5%
Common
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 994
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
남 106
 
10.7%
전 104
 
10.5%
도 103
 
10.4%
라 101
 
10.2%
시 86
 
8.7%
동 48
 
4.8%
면 48
 
4.8%
여 29
 
2.9%
수 29
 
2.9%
천 27
 
2.7%
Other values (93) 313
31.5%
ASCII
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

수원_취수구분
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원 100
100.0%

Length

2023-12-10T19:34:40.090503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:40.307515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원 100
100.0%

전망1월
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 100
100.0%

Length

2023-12-10T19:34:40.524654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:40.711170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

전망2월
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 100
100.0%

Length

2023-12-10T19:34:40.933212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:41.084136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

전망3월
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 100
100.0%

Length

2023-12-10T19:34:41.275164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:41.511765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2021-01-14
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-14
2nd row2021-01-14
3rd row2021-01-14
4th row2021-01-14
5th row2021-01-14

Common Values

ValueCountFrequency (%)
2021-01-14 100
100.0%

Length

2023-12-10T19:34:41.676387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:34:41.835224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-14 100
100.0%

Interactions

2023-12-10T19:34:36.542714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:34:41.938358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드주소
행정동코드1.0001.000
주소1.0001.000

Missing values

2023-12-10T19:34:36.879579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:34:37.219078image/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

전망월행정동코드주소수원_취수구분전망1월전망2월전망3월등록일자
02021-014611081000전라남도목포시부주동수원정상정상정상2021-01-14
12021-014613025000전라남도여수시돌산읍수원정상정상정상2021-01-14
22021-014613031000전라남도여수시소라면수원정상정상정상2021-01-14
32021-014613032000전라남도여수시율촌면수원정상정상정상2021-01-14
42021-014613033000전라남도여수시화양면수원정상정상정상2021-01-14
52021-014613034000전라남도여수시남면수원정상정상정상2021-01-14
62021-014613035000전라남도여수시화정면수원정상정상정상2021-01-14
72021-014613036000전라남도여수시삼산면수원정상정상정상2021-01-14
82021-014613051500전라남도여수시동문동수원정상정상정상2021-01-14
92021-014613053500전라남도여수시한려동수원정상정상정상2021-01-14
전망월행정동코드주소수원_취수구분전망1월전망2월전망3월등록일자
902021-014671037000전라남도담양군금성면수원정상정상정상2021-01-14
912021-014671038000전라남도담양군용면수원정상정상정상2021-01-14
922021-014671039000전라남도담양군월산면수원정상정상정상2021-01-14
932021-014671040000전라남도담양군수북면수원정상정상정상2021-01-14
942021-014671041000전라남도담양군대전면수원정상정상정상2021-01-14
952021-014672025000전라남도곡성군곡성읍수원정상정상정상2021-01-14
962021-014672031000전라남도곡성군오곡면수원정상정상정상2021-01-14
972021-014672032000전라남도곡성군삼기면수원정상정상정상2021-01-14
982021-014672033000전라남도곡성군석곡면수원정상정상정상2021-01-14
992021-014611080000전라남도목포시부흥동수원정상정상정상2021-01-14