Overview

Dataset statistics

Number of variables10
Number of observations43
Missing cells24
Missing cells (%)5.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory89.1 B

Variable types

Text3
Categorical2
Numeric5

Alerts

조성년도 is highly overall correlated with 조성면적(ha) and 2 other fieldsHigh correlation
조성면적(ha) is highly overall correlated with 조성년도High correlation
사업비-합계(백만원) is highly overall correlated with 조성년도 and 2 other fieldsHigh correlation
사업비-국비(백만원) is highly overall correlated with 사업비-합계(백만원) and 1 other fieldsHigh correlation
사업비-시군비(백만원) is highly overall correlated with 사업비-합계(백만원) and 1 other fieldsHigh correlation
소유구분명 is highly overall correlated with 사업비-도비(백만원)High correlation
사업비-도비(백만원) is highly overall correlated with 조성년도 and 3 other fieldsHigh correlation
사업비-국비(백만원) has 24 (55.8%) missing valuesMissing
소재지위치정보 has unique valuesUnique

Reproduction

Analysis started2024-04-14 05:01:12.145463
Analysis finished2024-04-14 05:01:15.693324
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct23
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-04-14T14:01:15.786391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0465116
Min length3

Characters and Unicode

Total characters131
Distinct characters32
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

Unique13 ?
Unique (%)30.2%

Sample

1st row과천시
2nd row광명시
3rd row군포시
4th row김포시
5th row동두천시
ValueCountFrequency (%)
파주시 6
14.0%
의왕시 4
 
9.3%
양주시 4
 
9.3%
여주시 3
 
7.0%
성남시 3
 
7.0%
안양시 2
 
4.7%
안산시 2
 
4.7%
양평군 2
 
4.7%
화성시 2
 
4.7%
시흥시 2
 
4.7%
Other values (13) 13
30.2%
2024-04-14T14:01:16.019708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 43
32.8%
주 13
 
9.9%
양 8
 
6.1%
파 6
 
4.6%
성 6
 
4.6%
의 5
 
3.8%
안 5
 
3.8%
왕 4
 
3.1%
천 4
 
3.1%
평 3
 
2.3%
Other values (22) 34
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 43
32.8%
주 13
 
9.9%
양 8
 
6.1%
파 6
 
4.6%
성 6
 
4.6%
의 5
 
3.8%
안 5
 
3.8%
왕 4
 
3.1%
천 4
 
3.1%
평 3
 
2.3%
Other values (22) 34
26.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 43
32.8%
주 13
 
9.9%
양 8
 
6.1%
파 6
 
4.6%
성 6
 
4.6%
의 5
 
3.8%
안 5
 
3.8%
왕 4
 
3.1%
천 4
 
3.1%
평 3
 
2.3%
Other values (22) 34
26.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 43
32.8%
주 13
 
9.9%
양 8
 
6.1%
파 6
 
4.6%
성 6
 
4.6%
의 5
 
3.8%
안 5
 
3.8%
왕 4
 
3.1%
천 4
 
3.1%
평 3
 
2.3%
Other values (22) 34
26.0%

산림욕장명
Text

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-04-14T14:01:16.172465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9302326
Min length2

Characters and Unicode

Total characters126
Distinct characters68
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

Unique38 ?
Unique (%)88.4%

Sample

1st row청계산
2nd row구름산
3rd row수리산
4th row문수산
5th row소요산
ValueCountFrequency (%)
청계산 3
 
6.8%
수리산 2
 
4.5%
무봉산 1
 
2.3%
오봉산 1
 
2.3%
마감산 1
 
2.3%
자일동 1
 
2.3%
설봉산 1
 
2.3%
황학산 1
 
2.3%
독산성 1
 
2.3%
노고봉 1
 
2.3%
Other values (31) 31
70.5%
2024-04-14T14:01:16.433818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 31
24.6%
봉 8
 
6.3%
수 4
 
3.2%
청 3
 
2.4%
계 3
 
2.4%
성 3
 
2.4%
남 2
 
1.6%
일 2
 
1.6%
고 2
 
1.6%
악 2
 
1.6%
Other values (58) 66
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
99.2%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 31
24.8%
봉 8
 
6.4%
수 4
 
3.2%
청 3
 
2.4%
계 3
 
2.4%
성 3
 
2.4%
남 2
 
1.6%
일 2
 
1.6%
고 2
 
1.6%
악 2
 
1.6%
Other values (57) 65
52.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 31
24.8%
봉 8
 
6.4%
수 4
 
3.2%
청 3
 
2.4%
계 3
 
2.4%
성 3
 
2.4%
남 2
 
1.6%
일 2
 
1.6%
고 2
 
1.6%
악 2
 
1.6%
Other values (57) 65
52.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
99.2%
ASCII 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 31
24.8%
봉 8
 
6.4%
수 4
 
3.2%
청 3
 
2.4%
계 3
 
2.4%
성 3
 
2.4%
남 2
 
1.6%
일 2
 
1.6%
고 2
 
1.6%
악 2
 
1.6%
Other values (57) 65
52.0%
ASCII
ValueCountFrequency (%)
1
100.0%

소재지위치정보
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-04-14T14:01:16.664522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length21.139535
Min length15

Characters and Unicode

Total characters909
Distinct characters104
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

Unique43 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 문원동 산93 외15
2nd row경기도 광명시 하안동 산141-7 외47
3rd row경기도 군포시 산본동 산18-3 외39
4th row경기도 김포시 월곶면 성동리 산35-1 외1
5th row경기도 동두천시 상봉암동 산23-1 외6
ValueCountFrequency (%)
경기도 43
 
19.3%
파주시 6
 
2.7%
외1 4
 
1.8%
의왕시 4
 
1.8%
양주시 4
 
1.8%
여주시 3
 
1.3%
성남시 3
 
1.3%
시흥시 2
 
0.9%
산120-1 2
 
0.9%
파주읍 2
 
0.9%
Other values (142) 150
67.3%
2024-04-14T14:01:16.994611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
19.8%
1 51
 
5.6%
산 48
 
5.3%
경 43
 
4.7%
도 43
 
4.7%
기 43
 
4.7%
시 43
 
4.7%
동 32
 
3.5%
외 28
 
3.1%
- 25
 
2.8%
Other values (94) 373
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
59.1%
Space Separator 180
 
19.8%
Decimal Number 167
 
18.4%
Dash Punctuation 25
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 48
 
8.9%
경 43
 
8.0%
도 43
 
8.0%
기 43
 
8.0%
시 43
 
8.0%
동 32
 
6.0%
외 28
 
5.2%
리 16
 
3.0%
주 16
 
3.0%
양 14
 
2.6%
Other values (82) 211
39.3%
Decimal Number
ValueCountFrequency (%)
1 51
30.5%
2 22
13.2%
3 18
 
10.8%
4 16
 
9.6%
7 14
 
8.4%
5 12
 
7.2%
6 10
 
6.0%
9 9
 
5.4%
8 8
 
4.8%
0 7
 
4.2%
Space Separator
ValueCountFrequency (%)
180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
59.1%
Common 372
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 48
 
8.9%
경 43
 
8.0%
도 43
 
8.0%
기 43
 
8.0%
시 43
 
8.0%
동 32
 
6.0%
외 28
 
5.2%
리 16
 
3.0%
주 16
 
3.0%
양 14
 
2.6%
Other values (82) 211
39.3%
Common
ValueCountFrequency (%)
180
48.4%
1 51
 
13.7%
- 25
 
6.7%
2 22
 
5.9%
3 18
 
4.8%
4 16
 
4.3%
7 14
 
3.8%
5 12
 
3.2%
6 10
 
2.7%
9 9
 
2.4%
Other values (2) 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
59.1%
ASCII 372
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
48.4%
1 51
 
13.7%
- 25
 
6.7%
2 22
 
5.9%
3 18
 
4.8%
4 16
 
4.3%
7 14
 
3.8%
5 12
 
3.2%
6 10
 
2.7%
9 9
 
2.4%
Other values (2) 15
 
4.0%
Hangul
ValueCountFrequency (%)
산 48
 
8.9%
경 43
 
8.0%
도 43
 
8.0%
기 43
 
8.0%
시 43
 
8.0%
동 32
 
6.0%
외 28
 
5.2%
리 16
 
3.0%
주 16
 
3.0%
양 14
 
2.6%
Other values (82) 211
39.3%

소유구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
사유림
26 
공유림
13 
국유림
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공유림
2nd row사유림
3rd row사유림
4th row공유림
5th row사유림

Common Values

ValueCountFrequency (%)
사유림 26
60.5%
공유림 13
30.2%
국유림 4
 
9.3%

Length

2024-04-14T14:01:17.110977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T14:01:17.188218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유림 26
60.5%
공유림 13
30.2%
국유림 4
 
9.3%

조성년도
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.7674
Minimum1990
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-14T14:01:17.263415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1990
5-th percentile1990.1
Q11993
median1998
Q32003.5
95-th percentile2018
Maximum2023
Range33
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation9.8242586
Coefficient of variation (CV)0.0049102452
Kurtosis-0.34168279
Mean2000.7674
Median Absolute Deviation (MAD)5
Skewness0.9679405
Sum86033
Variance96.516058
MonotonicityNot monotonic
2024-04-14T14:01:17.347655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1992 4
 
9.3%
2000 4
 
9.3%
2016 3
 
7.0%
1990 3
 
7.0%
1999 3
 
7.0%
1991 3
 
7.0%
1996 3
 
7.0%
1997 3
 
7.0%
2018 3
 
7.0%
2001 2
 
4.7%
Other values (10) 12
27.9%
ValueCountFrequency (%)
1990 3
7.0%
1991 3
7.0%
1992 4
9.3%
1993 2
4.7%
1994 1
 
2.3%
1995 2
4.7%
1996 3
7.0%
1997 3
7.0%
1998 1
 
2.3%
1999 3
7.0%
ValueCountFrequency (%)
2023 1
 
2.3%
2021 1
 
2.3%
2018 3
7.0%
2016 3
7.0%
2014 1
 
2.3%
2009 1
 
2.3%
2004 1
 
2.3%
2003 1
 
2.3%
2001 2
4.7%
2000 4
9.3%

조성면적(ha)
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.192558
Minimum2.2
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-14T14:01:17.446754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile2.9
Q118.74
median40
Q399
95-th percentile299
Maximum500
Range497.8
Interquartile range (IQR)80.26

Descriptive statistics

Standard deviation105.69009
Coefficient of variation (CV)1.3017214
Kurtosis6.0300612
Mean81.192558
Median Absolute Deviation (MAD)26
Skewness2.3744038
Sum3491.28
Variance11170.395
MonotonicityNot monotonic
2024-04-14T14:01:17.732079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
14.0 3
 
7.0%
21.0 2
 
4.7%
50.0 2
 
4.7%
20.0 2
 
4.7%
37.0 2
 
4.7%
2.9 2
 
4.7%
51.0 1
 
2.3%
110.0 1
 
2.3%
11.0 1
 
2.3%
125.0 1
 
2.3%
Other values (26) 26
60.5%
ValueCountFrequency (%)
2.2 1
 
2.3%
2.5 1
 
2.3%
2.9 2
4.7%
10.3 1
 
2.3%
11.0 1
 
2.3%
14.0 3
7.0%
17.0 1
 
2.3%
17.48 1
 
2.3%
20.0 2
4.7%
21.0 2
4.7%
ValueCountFrequency (%)
500.0 1
2.3%
365.0 1
2.3%
300.0 1
2.3%
290.0 1
2.3%
191.0 1
2.3%
154.0 1
2.3%
149.0 1
2.3%
136.0 1
2.3%
125.0 1
2.3%
110.0 1
2.3%

사업비-합계(백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean394.95349
Minimum15
Maximum1870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-14T14:01:17.815016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile30.1
Q1140
median400
Q3400
95-th percentile992.2
Maximum1870
Range1855
Interquartile range (IQR)260

Descriptive statistics

Standard deviation389.32432
Coefficient of variation (CV)0.98574726
Kurtosis5.9080798
Mean394.95349
Median Absolute Deviation (MAD)200
Skewness2.1798079
Sum16983
Variance151573.43
MonotonicityNot monotonic
2024-04-14T14:01:17.902650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
400 16
37.2%
53 2
 
4.7%
200 2
 
4.7%
922 1
 
2.3%
152 1
 
2.3%
29 1
 
2.3%
716 1
 
2.3%
41 1
 
2.3%
49 1
 
2.3%
44 1
 
2.3%
Other values (16) 16
37.2%
ValueCountFrequency (%)
15 1
2.3%
29 1
2.3%
30 1
2.3%
31 1
2.3%
41 1
2.3%
44 1
2.3%
49 1
2.3%
53 2
4.7%
68 1
2.3%
135 1
2.3%
ValueCountFrequency (%)
1870 1
 
2.3%
1650 1
 
2.3%
1000 1
 
2.3%
922 1
 
2.3%
740 1
 
2.3%
734 1
 
2.3%
716 1
 
2.3%
568 1
 
2.3%
447 1
 
2.3%
400 16
37.2%

사업비-국비(백만원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)31.6%
Missing24
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean275.05263
Minimum100
Maximum1095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-14T14:01:17.985343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1200
median200
Q3200
95-th percentile829.5
Maximum1095
Range995
Interquartile range (IQR)0

Descriptive statistics

Standard deviation248.99631
Coefficient of variation (CV)0.90526788
Kurtosis7.1525195
Mean275.05263
Median Absolute Deviation (MAD)0
Skewness2.7170594
Sum5226
Variance61999.164
MonotonicityNot monotonic
2024-04-14T14:01:18.056592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
200 12
27.9%
100 3
 
7.0%
1095 1
 
2.3%
367 1
 
2.3%
800 1
 
2.3%
264 1
 
2.3%
(Missing) 24
55.8%
ValueCountFrequency (%)
100 3
 
7.0%
200 12
27.9%
264 1
 
2.3%
367 1
 
2.3%
800 1
 
2.3%
1095 1
 
2.3%
ValueCountFrequency (%)
1095 1
 
2.3%
800 1
 
2.3%
367 1
 
2.3%
264 1
 
2.3%
200 12
27.9%
100 3
 
7.0%

사업비-도비(백만원)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
26 
100
10 
200
5 
40
 
1
300
 
1

Length

Max length4
Median length4
Mean length3.5813953
Min length2

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st row200
2nd row<NA>
3rd row<NA>
4th row100
5th row100

Common Values

ValueCountFrequency (%)
<NA> 26
60.5%
100 10
 
23.3%
200 5
 
11.6%
40 1
 
2.3%
300 1
 
2.3%

Length

2024-04-14T14:01:18.146855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T14:01:18.234830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
60.5%
100 10
 
23.3%
200 5
 
11.6%
40 1
 
2.3%
300 1
 
2.3%

사업비-시군비(백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219
Minimum15
Maximum1650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-14T14:01:18.316099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile30.1
Q198
median135
Q3208
95-th percentile728.2
Maximum1650
Range1635
Interquartile range (IQR)110

Descriptive statistics

Standard deviation283.2459
Coefficient of variation (CV)1.2933603
Kurtosis15.571035
Mean219
Median Absolute Deviation (MAD)65
Skewness3.5686322
Sum9417
Variance80228.238
MonotonicityNot monotonic
2024-04-14T14:01:18.407759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
100 10
23.3%
200 8
18.6%
53 2
 
4.7%
68 1
 
2.3%
29 1
 
2.3%
216 1
 
2.3%
41 1
 
2.3%
49 1
 
2.3%
44 1
 
2.3%
1650 1
 
2.3%
Other values (16) 16
37.2%
ValueCountFrequency (%)
15 1
2.3%
29 1
2.3%
30 1
2.3%
31 1
2.3%
41 1
2.3%
44 1
2.3%
49 1
2.3%
53 2
4.7%
68 1
2.3%
96 1
2.3%
ValueCountFrequency (%)
1650 1
2.3%
775 1
2.3%
740 1
2.3%
622 1
2.3%
447 1
2.3%
367 1
2.3%
300 1
2.3%
264 1
2.3%
257 1
2.3%
238 1
2.3%

Interactions

2024-04-14T14:01:15.091972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:13.697444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.155632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.481506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.803585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:15.181200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:13.847961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.218931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.550170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.861777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:15.270028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:13.926785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.278539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.611546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.917537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:15.368821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.013238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.354222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.676028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.975424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:15.433288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.082364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.412135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:14.734212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T14:01:15.031602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T14:01:18.489998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명산림욕장명소재지위치정보소유구분명조성년도조성면적(ha)사업비-합계(백만원)사업비-국비(백만원)사업비-도비(백만원)사업비-시군비(백만원)
시군명1.0000.8321.0000.7080.6430.6680.8670.0960.6930.868
산림욕장명0.8321.0001.0000.0000.7630.0000.9401.0001.0000.765
소재지위치정보1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소유구분명0.7080.0001.0001.0000.6510.3900.2060.0000.6840.271
조성년도0.6430.7631.0000.6511.0000.0000.6250.0000.8420.409
조성면적(ha)0.6680.0001.0000.3900.0001.0000.0000.0000.0000.000
사업비-합계(백만원)0.8670.9401.0000.2060.6250.0001.0000.8930.8280.896
사업비-국비(백만원)0.0961.0001.0000.0000.0000.0000.8931.000NaN0.933
사업비-도비(백만원)0.6931.0001.0000.6840.8420.0000.828NaN1.0000.610
사업비-시군비(백만원)0.8680.7651.0000.2710.4090.0000.8960.9330.6101.000
2024-04-14T14:01:18.599613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업비-도비(백만원)소유구분명
사업비-도비(백만원)1.0000.687
소유구분명0.6871.000
2024-04-14T14:01:18.684740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조성년도조성면적(ha)사업비-합계(백만원)사업비-국비(백만원)사업비-시군비(백만원)소유구분명사업비-도비(백만원)
조성년도1.000-0.5190.5630.2320.3730.3710.660
조성면적(ha)-0.5191.000-0.149-0.1120.0440.2650.000
사업비-합계(백만원)0.563-0.1491.0000.8300.8370.1070.463
사업비-국비(백만원)0.232-0.1120.8301.0000.4620.0001.000
사업비-시군비(백만원)0.3730.0440.8370.4621.0000.0980.598
소유구분명0.3710.2650.1070.0000.0981.0000.687
사업비-도비(백만원)0.6600.0000.4631.0000.5980.6871.000

Missing values

2024-04-14T14:01:15.536841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T14:01:15.644682image/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

시군명산림욕장명소재지위치정보소유구분명조성년도조성면적(ha)사업비-합계(백만원)사업비-국비(백만원)사업비-도비(백만원)사업비-시군비(백만원)
0과천시청계산경기도 과천시 문원동 산93 외15공유림200151.0400<NA>200200
1광명시구름산경기도 광명시 하안동 산141-7 외47사유림1996300.0400100<NA>300
2군포시수리산경기도 군포시 산본동 산18-3 외39사유림1993154.0257<NA><NA>257
3김포시문수산경기도 김포시 월곶면 성동리 산35-1 외1공유림199570.0922200100622
4동두천시소요산경기도 동두천시 상봉암동 산23-1 외6사유림200017.0400200100100
5부천시원미산경기도 부천시 원미구 원미동 산20-10 외15사유림199150.053<NA><NA>53
6성남시청계산경기도 성남시 수정구 상적동 산73-2국유림2021500.0400200<NA>200
7성남시불국산경기도 성남시 분당구 수내동 산66사유림1997100.0152<NA><NA>152
8성남시남한산성경기도 성남시 중원구 상대원동 산193-7국유림199740.0135<NA><NA>135
9수원시광교산경기도 수원시 장안구 조원동 산32사유림199145.0238<NA><NA>238
시군명산림욕장명소재지위치정보소유구분명조성년도조성면적(ha)사업비-합계(백만원)사업비-국비(백만원)사업비-도비(백만원)사업비-시군비(백만원)
33이천시설봉산경기도 이천시 관고동 산63-1 외 3사유림199998.0400<NA>200200
34파주시안산경기도 파주시 조리읍 봉일천리 79사유림199550.044<NA><NA>44
35파주시봉서산경기도 파주시 파주읍 파주리 산54 외158사유림199728.049<NA><NA>49
36파주시박달산경기도 파주시 광탄면 마장리 산62 외 7사유림200014.0400200100100
37파주시감악산경기도 파주시 적성면 설마리 산21-1 외1국유림1996149.041<NA><NA>41
38파주시삼봉산경기도 파주시 법원읍 법원리 산24-1일원사유림200420.0716200300216
39파주시통일공원경기도 파주시 파주읍 봉서리 산42 외14사유림199614.029<NA><NA>29
40평택시무봉산경기도 평택시 진위면 동천리 산209 외127사유림1992290.053<NA><NA>53
41화성시초록산경기도 화성시 양감면 사창리 산159-1 외47사유림199497.0400200100100
42화성시서봉산경기도 화성시 정남면 문학리 산120-1사유림1998365.0400200100100