Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory74.3 B

Variable types

DateTime2
Numeric1
Text1
Categorical5

Alerts

전망주 has constant value ""Constant
수원_취수구분 has constant value ""Constant
전망1주 has constant value ""Constant
전망2주 has constant value ""Constant
전망3주 has constant value ""Constant
전망4주 has constant value ""Constant
등록일자 has constant value ""Constant
행정동코드 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:24:21.027382
Analysis finished2023-12-10 13:24:22.076052
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전망주
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2021-05-05 00:00:00
Maximum2021-05-05 00:00:00
2023-12-10T22:24:22.178013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:24:22.347641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

행정동코드
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0087196 × 109
Minimum1.1110515 × 109
Maximum4.136056 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:24:22.584634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110515 × 109
5-th percentile4.1250579 × 109
Q14.1273548 × 109
median4.1281665 × 109
Q34.1290542 × 109
95-th percentile4.136051 × 109
Maximum4.136056 × 109
Range3.0250045 × 109
Interquartile range (IQR)1699500

Descriptive statistics

Standard deviation5.9447105 × 108
Coefficient of variation (CV)0.14829449
Kurtosis21.142319
Mean4.0087196 × 109
Median Absolute Deviation (MAD)815000
Skewness-4.7664559
Sum4.0087196 × 1011
Variance3.5339582 × 1017
MonotonicityNot monotonic
2023-12-10T22:24:22.830573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4125058000 1
 
1.0%
4128758000 1
 
1.0%
4131053000 1
 
1.0%
4131052000 1
 
1.0%
4131051000 1
 
1.0%
4129056000 1
 
1.0%
4129055000 1
 
1.0%
4129054000 1
 
1.0%
4129053000 1
 
1.0%
4129052000 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1111051500 1
1.0%
1111053000 1
1.0%
1111054000 1
1.0%
1111055000 1
1.0%
4125056600 1
1.0%
4125058000 1
1.0%
4125060000 1
1.0%
4127151000 1
1.0%
4127151500 1
1.0%
4127152000 1
1.0%
ValueCountFrequency (%)
4136056000 1
1.0%
4136055000 1
1.0%
4136054000 1
1.0%
4136053000 1
1.0%
4136052000 1
1.0%
4136051000 1
1.0%
4136037000 1
1.0%
4136036000 1
1.0%
4136034000 1
1.0%
4136031000 1
1.0%

주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:24:23.218030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12.5
Mean length11.73
Min length9

Characters and Unicode

Total characters1173
Distinct characters104
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 row경기도동두천시소요동
2nd row경기도동두천시상패동
3rd row경기도안산시상록구일동
4th row경기도안산시상록구이동
5th row경기도안산시상록구사1동
ValueCountFrequency (%)
경기도동두천시소요동 1
 
1.0%
경기도고양시일산서구주엽2동 1
 
1.0%
경기도구리시동구동 1
 
1.0%
경기도구리시갈매동 1
 
1.0%
경기도과천시문원동 1
 
1.0%
경기도과천시과천동 1
 
1.0%
경기도과천시부림동 1
 
1.0%
경기도과천시별양동 1
 
1.0%
경기도과천시갈현동 1
 
1.0%
경기도과천시중앙동 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:24:23.854985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 107
 
9.1%
도 100
 
8.5%
시 100
 
8.5%
경 96
 
8.2%
기 96
 
8.2%
구 77
 
6.6%
양 76
 
6.5%
산 54
 
4.6%
고 43
 
3.7%
안 27
 
2.3%
Other values (94) 397
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1137
96.9%
Decimal Number 36
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 107
 
9.4%
도 100
 
8.8%
시 100
 
8.8%
경 96
 
8.4%
기 96
 
8.4%
구 77
 
6.8%
양 76
 
6.7%
산 54
 
4.7%
고 43
 
3.8%
안 27
 
2.4%
Other values (91) 361
31.8%
Decimal Number
ValueCountFrequency (%)
1 15
41.7%
2 15
41.7%
3 6
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1137
96.9%
Common 36
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 107
 
9.4%
도 100
 
8.8%
시 100
 
8.8%
경 96
 
8.4%
기 96
 
8.4%
구 77
 
6.8%
양 76
 
6.7%
산 54
 
4.7%
고 43
 
3.8%
안 27
 
2.4%
Other values (91) 361
31.8%
Common
ValueCountFrequency (%)
1 15
41.7%
2 15
41.7%
3 6
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1137
96.9%
ASCII 36
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 107
 
9.4%
도 100
 
8.8%
시 100
 
8.8%
경 96
 
8.4%
기 96
 
8.4%
구 77
 
6.8%
양 76
 
6.7%
산 54
 
4.7%
고 43
 
3.8%
안 27
 
2.4%
Other values (91) 361
31.8%
ASCII
ValueCountFrequency (%)
1 15
41.7%
2 15
41.7%
3 6
 
16.7%

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

2023-12-10T22:24:24.186459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:24.424575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원 100
100.0%

전망1주
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

2023-12-10T22:24:24.605074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:24.749317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

전망2주
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

2023-12-10T22:24:24.890052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:25.025415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

전망3주
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

2023-12-10T22:24:25.178651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:25.331149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

전망4주
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

2023-12-10T22:24:25.484691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:25.641316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 100
100.0%

등록일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2021-05-05 00:00:00
Maximum2021-05-05 00:00:00
2023-12-10T22:24:25.839642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:24:26.032383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-10T22:24:21.439426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:24:26.138708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드주소
행정동코드1.0001.000
주소1.0001.000

Missing values

2023-12-10T22:24:21.734516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:24:22.000782image/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

전망주행정동코드주소수원_취수구분전망1주전망2주전망3주전망4주등록일자
02021-05-054125058000경기도동두천시소요동수원정상정상정상정상2021-05-05
12021-05-054125060000경기도동두천시상패동수원정상정상정상정상2021-05-05
22021-05-054127151000경기도안산시상록구일동수원정상정상정상정상2021-05-05
32021-05-054127151500경기도안산시상록구이동수원정상정상정상정상2021-05-05
42021-05-054127152000경기도안산시상록구사1동수원정상정상정상정상2021-05-05
52021-05-054127153000경기도안산시상록구사2동수원정상정상정상정상2021-05-05
62021-05-054127153500경기도안산시상록구사3동수원정상정상정상정상2021-05-05
72021-05-054127154000경기도안산시상록구본오1동수원정상정상정상정상2021-05-05
82021-05-054127155000경기도안산시상록구본오2동수원정상정상정상정상2021-05-05
92021-05-054127156000경기도안산시상록구본오3동수원정상정상정상정상2021-05-05
전망주행정동코드주소수원_취수구분전망1주전망2주전망3주전망4주등록일자
902021-05-054136052000경기도남양주시평내동수원정상정상정상정상2021-05-05
912021-05-054136053000경기도남양주시금곡동수원정상정상정상정상2021-05-05
922021-05-054136054000경기도남양주시양정동수원정상정상정상정상2021-05-05
932021-05-054136055000경기도남양주시지금동수원정상정상정상정상2021-05-05
942021-05-054136056000경기도남양주시도농동수원정상정상정상정상2021-05-05
952021-05-051111051500서울특별시종로구청운효자동수원정상정상정상정상2021-05-05
962021-05-051111053000서울특별시종로구사직동수원정상정상정상정상2021-05-05
972021-05-051111054000서울특별시종로구삼청동수원정상정상정상정상2021-05-05
982021-05-051111055000서울특별시종로구부암동수원정상정상정상정상2021-05-05
992021-05-054125056600경기도동두천시송내동수원정상정상정상정상2021-05-05