Overview

Dataset statistics

Number of variables6
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory55.9 B

Variable types

Numeric4
Text2

Dataset

Description화성시 관내 저수지 현황에 대한 데이터로 연번, 지구명, 위치, 면적, 설치연도, 유효저수량에 대한 데이터를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/3047278/fileData.do

Alerts

면적(ha) is highly overall correlated with 유효저수량(천톤)High correlation
유효저수량(천톤) is highly overall correlated with 면적(ha)High correlation
연번 has unique valuesUnique
지구명 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:19:11.975085
Analysis finished2023-12-12 08:19:14.659710
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T17:19:14.758966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q325.75
95-th percentile32.35
Maximum34
Range33
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation9.9582462
Coefficient of variation (CV)0.56904264
Kurtosis-1.2
Mean17.5
Median Absolute Deviation (MAD)8.5
Skewness0
Sum595
Variance99.166667
MonotonicityStrictly increasing
2023-12-12T17:19:14.966882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
27 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
28 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%
25 1
2.9%

지구명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T17:19:15.230847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2941176
Min length2

Characters and Unicode

Total characters78
Distinct characters58
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

Unique34 ?
Unique (%)100.0%

Sample

1st row청운
2nd row송산
3rd row평만
4th row맨드리
5th row기안
ValueCountFrequency (%)
청운 1
 
2.9%
송산 1
 
2.9%
기천3 1
 
2.9%
월문 1
 
2.9%
띠밭 1
 
2.9%
기천1 1
 
2.9%
독골 1
 
2.9%
하저 1
 
2.9%
당너머 1
 
2.9%
뱅치 1
 
2.9%
Other values (24) 24
70.6%
2023-12-12T17:19:15.618966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 4
 
5.1%
하 3
 
3.8%
기 3
 
3.8%
송 3
 
3.8%
산 2
 
2.6%
화 2
 
2.6%
천 2
 
2.6%
월 2
 
2.6%
안 2
 
2.6%
골 2
 
2.6%
Other values (48) 53
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
94.9%
Decimal Number 4
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 4
 
5.4%
하 3
 
4.1%
기 3
 
4.1%
송 3
 
4.1%
산 2
 
2.7%
화 2
 
2.7%
천 2
 
2.7%
월 2
 
2.7%
안 2
 
2.7%
골 2
 
2.7%
Other values (46) 49
66.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
94.9%
Common 4
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 4
 
5.4%
하 3
 
4.1%
기 3
 
4.1%
송 3
 
4.1%
산 2
 
2.7%
화 2
 
2.7%
천 2
 
2.7%
월 2
 
2.7%
안 2
 
2.7%
골 2
 
2.7%
Other values (46) 49
66.2%
Common
ValueCountFrequency (%)
1 2
50.0%
3 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
94.9%
ASCII 4
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 4
 
5.4%
하 3
 
4.1%
기 3
 
4.1%
송 3
 
4.1%
산 2
 
2.7%
화 2
 
2.7%
천 2
 
2.7%
월 2
 
2.7%
안 2
 
2.7%
골 2
 
2.7%
Other values (46) 49
66.2%
ASCII
ValueCountFrequency (%)
1 2
50.0%
3 2
50.0%

위치
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T17:19:15.929123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.882353
Min length16

Characters and Unicode

Total characters642
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row경기도 화성시 황계동 183-2
2nd row경기도 화성시 송산동 131-3
3rd row경기도 화성시 송산동 197-2
4th row경기도 화성시 안녕동 146-137
5th row경기도 화성시 기안동 457-73
ValueCountFrequency (%)
경기도 34
21.5%
화성시 34
21.5%
팔탄면 7
 
4.4%
향남면 6
 
3.8%
송산동 3
 
1.9%
황계동 3
 
1.9%
배양동 3
 
1.9%
서신면 2
 
1.3%
봉담읍 2
 
1.3%
율암리 2
 
1.3%
Other values (57) 62
39.2%
2023-12-12T17:19:16.355016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
19.3%
기 37
 
5.8%
화 35
 
5.5%
성 34
 
5.3%
시 34
 
5.3%
경 34
 
5.3%
도 34
 
5.3%
- 22
 
3.4%
리 22
 
3.4%
1 20
 
3.1%
Other values (53) 246
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
57.8%
Decimal Number 125
 
19.5%
Space Separator 124
 
19.3%
Dash Punctuation 22
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 37
 
10.0%
화 35
 
9.4%
성 34
 
9.2%
시 34
 
9.2%
경 34
 
9.2%
도 34
 
9.2%
리 22
 
5.9%
면 19
 
5.1%
동 14
 
3.8%
남 8
 
2.2%
Other values (41) 100
27.0%
Decimal Number
ValueCountFrequency (%)
1 20
16.0%
2 18
14.4%
4 15
12.0%
5 15
12.0%
3 14
11.2%
7 14
11.2%
8 8
 
6.4%
9 8
 
6.4%
6 8
 
6.4%
0 5
 
4.0%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
57.8%
Common 271
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 37
 
10.0%
화 35
 
9.4%
성 34
 
9.2%
시 34
 
9.2%
경 34
 
9.2%
도 34
 
9.2%
리 22
 
5.9%
면 19
 
5.1%
동 14
 
3.8%
남 8
 
2.2%
Other values (41) 100
27.0%
Common
ValueCountFrequency (%)
124
45.8%
- 22
 
8.1%
1 20
 
7.4%
2 18
 
6.6%
4 15
 
5.5%
5 15
 
5.5%
3 14
 
5.2%
7 14
 
5.2%
8 8
 
3.0%
9 8
 
3.0%
Other values (2) 13
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
57.8%
ASCII 271
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
45.8%
- 22
 
8.1%
1 20
 
7.4%
2 18
 
6.6%
4 15
 
5.5%
5 15
 
5.5%
3 14
 
5.2%
7 14
 
5.2%
8 8
 
3.0%
9 8
 
3.0%
Other values (2) 13
 
4.8%
Hangul
ValueCountFrequency (%)
기 37
 
10.0%
화 35
 
9.4%
성 34
 
9.2%
시 34
 
9.2%
경 34
 
9.2%
도 34
 
9.2%
리 22
 
5.9%
면 19
 
5.1%
동 14
 
3.8%
남 8
 
2.2%
Other values (41) 100
27.0%

면적(ha)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.511765
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T17:19:16.510242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.065
Q14
median5.3
Q38.425
95-th percentile22.98
Maximum120
Range119
Interquartile range (IQR)4.425

Descriptive statistics

Standard deviation20.242182
Coefficient of variation (CV)1.9256692
Kurtosis27.865323
Mean10.511765
Median Absolute Deviation (MAD)2.3
Skewness5.1011121
Sum357.4
Variance409.74592
MonotonicityNot monotonic
2023-12-12T17:19:16.679115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
4.0 4
 
11.8%
7.6 3
 
8.8%
5.3 2
 
5.9%
3.0 2
 
5.9%
16.7 2
 
5.9%
2.7 1
 
2.9%
5.2 1
 
2.9%
120.0 1
 
2.9%
4.9 1
 
2.9%
10.0 1
 
2.9%
Other values (16) 16
47.1%
ValueCountFrequency (%)
1.0 1
 
2.9%
2.0 1
 
2.9%
2.1 1
 
2.9%
2.5 1
 
2.9%
2.6 1
 
2.9%
2.7 1
 
2.9%
3.0 2
5.9%
4.0 4
11.8%
4.5 1
 
2.9%
4.6 1
 
2.9%
ValueCountFrequency (%)
120.0 1
 
2.9%
30.0 1
 
2.9%
19.2 1
 
2.9%
16.7 2
5.9%
13.0 1
 
2.9%
11.0 1
 
2.9%
10.0 1
 
2.9%
8.7 1
 
2.9%
7.6 3
8.8%
6.9 1
 
2.9%

설치연도
Real number (ℝ)

Distinct9
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1948.7353
Minimum1934
Maximum2003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T17:19:16.826408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1934
5-th percentile1938.95
Q11945
median1945
Q31945
95-th percentile1966.75
Maximum2003
Range69
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.206081
Coefficient of variation (CV)0.0062635911
Kurtosis11.625062
Mean1948.7353
Median Absolute Deviation (MAD)0
Skewness3.068102
Sum66257
Variance148.98841
MonotonicityNot monotonic
2023-12-12T17:19:16.974652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1945 25
73.5%
1963 2
 
5.9%
1937 1
 
2.9%
1970 1
 
2.9%
1965 1
 
2.9%
2003 1
 
2.9%
1940 1
 
2.9%
1934 1
 
2.9%
1957 1
 
2.9%
ValueCountFrequency (%)
1934 1
 
2.9%
1937 1
 
2.9%
1940 1
 
2.9%
1945 25
73.5%
1957 1
 
2.9%
1963 2
 
5.9%
1965 1
 
2.9%
1970 1
 
2.9%
2003 1
 
2.9%
ValueCountFrequency (%)
2003 1
 
2.9%
1970 1
 
2.9%
1965 1
 
2.9%
1963 2
 
5.9%
1957 1
 
2.9%
1945 25
73.5%
1940 1
 
2.9%
1937 1
 
2.9%
1934 1
 
2.9%

유효저수량(천톤)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.915
Minimum1
Maximum168.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T17:19:17.132636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.325
Q14.125
median7.35
Q311.2
95-th percentile39.1
Maximum168.8
Range167.8
Interquartile range (IQR)7.075

Descriptive statistics

Standard deviation29.227927
Coefficient of variation (CV)1.959633
Kurtosis24.800398
Mean14.915
Median Absolute Deviation (MAD)3.7
Skewness4.7618233
Sum507.11
Variance854.27171
MonotonicityNot monotonic
2023-12-12T17:19:17.293496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
9.2 2
 
5.9%
1.6 2
 
5.9%
1.0 2
 
5.9%
7.1 2
 
5.9%
13.0 1
 
2.9%
168.8 1
 
2.9%
1.5 1
 
2.9%
7.8 1
 
2.9%
7.11 1
 
2.9%
1.9 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
1.0 2
5.9%
1.5 1
2.9%
1.6 2
5.9%
1.9 1
2.9%
2.3 1
2.9%
3.5 1
2.9%
3.8 1
2.9%
5.1 1
2.9%
5.7 1
2.9%
6.4 1
2.9%
ValueCountFrequency (%)
168.8 1
2.9%
56.0 1
2.9%
30.0 1
2.9%
26.1 1
2.9%
22.5 1
2.9%
21.5 1
2.9%
14.8 1
2.9%
13.0 1
2.9%
11.4 1
2.9%
10.6 1
2.9%

Interactions

2023-12-12T17:19:13.921675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:12.236200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.033400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.458283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:14.049165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:12.328193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.139652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.574619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:14.175632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:12.426754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.241161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.669610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:14.318835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:12.884071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.339100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:13.792256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:19:17.419372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지구명위치면적(ha)설치연도유효저수량(천톤)
연번1.0001.0001.0000.0000.4820.174
지구명1.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.000
면적(ha)0.0001.0001.0001.0000.6550.965
설치연도0.4821.0001.0000.6551.0000.485
유효저수량(천톤)0.1741.0001.0000.9650.4851.000
2023-12-12T17:19:17.580569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(ha)설치연도유효저수량(천톤)
연번1.0000.2680.247-0.233
면적(ha)0.2681.000-0.0290.512
설치연도0.247-0.0291.000-0.060
유효저수량(천톤)-0.2330.512-0.0601.000

Missing values

2023-12-12T17:19:14.480186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:19:14.602640image/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

연번지구명위치면적(ha)설치연도유효저수량(천톤)
01청운경기도 화성시 황계동 183-22.719458.7
12송산경기도 화성시 송산동 131-34.019455.7
23평만경기도 화성시 송산동 197-213.0194526.1
34맨드리경기도 화성시 안녕동 146-1376.9194510.6
45기안경기도 화성시 기안동 457-734.0194511.4
56삼화경기도 화성시 황계동 171-964.619457.5
67황계동경기도 화성시 황계동 117-362.519371.6
78먱제경기도 화성시 배양동 19-3295.319456.4
89품목골경기도 화성시 배양동 69-4765.319459.1
910뱅치경기도 화성시 배양동 15-73.0194510.5
연번지구명위치면적(ha)설치연도유효저수량(천톤)
2425모즐경기도 화성시 송산면 칠곡리 4785.6194056.0
2526앞실경기도 화성시 서신면 전곡리 107-25.519341.0
2627당너머경기도 화성시 서신면 백미리 5356.619452.3
2728하저경기도 화성시 팔탄면 하저리 297.619453.5
2829독골경기도 화성시 팔탄면 창곡리 820-22.619631.0
2930기천1경기도 화성시 팔탄면 기천리 5737.619631.9
3031띠밭경기도 화성시 팔탄면 율암리 504-28.719577.11
3132월문경기도 화성시 팔탄면 월문리 5510.019457.8
3233기천3경기도 화성시 팔탄면 기천리 산224.919451.5
3334대성경기도 화성시 팔탄면 율암리 354-1120.01945168.8