Overview

Dataset statistics

Number of variables15
Number of observations25
Missing cells41
Missing cells (%)10.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory131.3 B

Variable types

Categorical5
Text4
Numeric5
DateTime1

Dataset

Description경상북도 봉화군 폐교매각 현황(매각용도, 매각방법, 매각금액 등)
Author경상북도교육청 경상북도봉화교육지원청
URLhttps://www.data.go.kr/data/15053776/fileData.do

Alerts

교육청 has constant value ""Constant
특약등기여부(○,×) is highly overall correlated with 폐교연도 and 3 other fieldsHigh correlation
특약등기기간 is highly overall correlated with 폐교연도 and 7 other fieldsHigh correlation
매각방법(수의계약,경쟁입찰등) is highly overall correlated with 특약등기기간 and 1 other fieldsHigh correlation
용도 is highly overall correlated with 특약등기기간 and 1 other fieldsHigh correlation
폐교연도 is highly overall correlated with 건물면적(㎡) and 4 other fieldsHigh correlation
토지면적(㎡) is highly overall correlated with 건물면적(㎡) and 3 other fieldsHigh correlation
건물면적(㎡) is highly overall correlated with 폐교연도 and 4 other fieldsHigh correlation
매각금액(단위:천원) is highly overall correlated with 폐교연도 and 4 other fieldsHigh correlation
관리계획 is highly overall correlated with 폐교연도 and 2 other fieldsHigh correlation
토지면적(㎡) has 1 (4.0%) missing valuesMissing
건물면적(㎡) has 1 (4.0%) missing valuesMissing
매각금액(단위:천원) has 1 (4.0%) missing valuesMissing
관리계획 has 18 (72.0%) missing valuesMissing
비고(국유지 및 기타 정보) has 20 (80.0%) missing valuesMissing
폐교명 has unique valuesUnique
소재지 has unique valuesUnique
매각일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:50:00.616358
Analysis finished2023-12-12 00:50:05.539554
Duration4.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
봉화교육지원청
25 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
봉화교육지원청 25
100.0%

Length

2023-12-12T09:50:05.602612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:50:05.690602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
봉화교육지원청 25
100.0%

폐교명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T09:50:05.873801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.56
Min length6

Characters and Unicode

Total characters264
Distinct characters62
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

Unique25 ?
Unique (%)100.0%

Sample

1st row동양초등학교금봉분교장
2nd row문촌초등학교
3rd row다덕초등학교
4th row소천초등학교 고선분교장
5th row소천초등학교 우련전분교장
ValueCountFrequency (%)
소천초등학교 6
 
14.0%
석포초등학교 4
 
9.3%
물야초등학교 2
 
4.7%
신라분교장 1
 
2.3%
애당초등학교 1
 
2.3%
명호초등학교 1
 
2.3%
삼동분교장 1
 
2.3%
동양초등학교 1
 
2.3%
우곡분교장 1
 
2.3%
상운초등학교 1
 
2.3%
Other values (24) 24
55.8%
2023-12-12T09:50:06.228720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 44
16.7%
학 25
 
9.5%
초 24
 
9.1%
등 24
 
9.1%
장 19
 
7.2%
분 19
 
7.2%
18
 
6.8%
소 7
 
2.7%
천 7
 
2.7%
동 4
 
1.5%
Other values (52) 73
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 246
93.2%
Space Separator 18
 
6.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 44
17.9%
학 25
 
10.2%
초 24
 
9.8%
등 24
 
9.8%
장 19
 
7.7%
분 19
 
7.7%
소 7
 
2.8%
천 7
 
2.8%
동 4
 
1.6%
석 4
 
1.6%
Other values (51) 69
28.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 246
93.2%
Common 18
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 44
17.9%
학 25
 
10.2%
초 24
 
9.8%
등 24
 
9.8%
장 19
 
7.7%
분 19
 
7.7%
소 7
 
2.8%
천 7
 
2.8%
동 4
 
1.6%
석 4
 
1.6%
Other values (51) 69
28.0%
Common
ValueCountFrequency (%)
18
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 246
93.2%
ASCII 18
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 44
17.9%
학 25
 
10.2%
초 24
 
9.8%
등 24
 
9.8%
장 19
 
7.7%
분 19
 
7.7%
소 7
 
2.8%
천 7
 
2.8%
동 4
 
1.6%
석 4
 
1.6%
Other values (51) 69
28.0%
ASCII
ValueCountFrequency (%)
18
100.0%

폐교연도
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1998.48
Minimum1983
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T09:50:06.353615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1983
5-th percentile1988.6
Q11993
median1996
Q32001
95-th percentile2015
Maximum2017
Range34
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.6944427
Coefficient of variation (CV)0.0043505277
Kurtosis0.17934847
Mean1998.48
Median Absolute Deviation (MAD)4
Skewness0.82654433
Sum49962
Variance75.593333
MonotonicityNot monotonic
2023-12-12T09:50:06.495870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1992 3
12.0%
1996 3
12.0%
1999 2
 
8.0%
1993 2
 
8.0%
1995 2
 
8.0%
1997 2
 
8.0%
2015 2
 
8.0%
2011 1
 
4.0%
2017 1
 
4.0%
2009 1
 
4.0%
Other values (6) 6
24.0%
ValueCountFrequency (%)
1983 1
 
4.0%
1988 1
 
4.0%
1991 1
 
4.0%
1992 3
12.0%
1993 2
8.0%
1995 2
8.0%
1996 3
12.0%
1997 2
8.0%
1998 1
 
4.0%
1999 2
8.0%
ValueCountFrequency (%)
2017 1
 
4.0%
2015 2
8.0%
2011 1
 
4.0%
2009 1
 
4.0%
2002 1
 
4.0%
2001 1
 
4.0%
1999 2
8.0%
1998 1
 
4.0%
1997 2
8.0%
1996 3
12.0%

소재지
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T09:50:06.759071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.88
Min length13

Characters and Unicode

Total characters397
Distinct characters64
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

Unique25 ?
Unique (%)100.0%

Sample

1st row봉화군 봉성면 금봉리 769-1
2nd row봉화군 상운면 문촌리 785
3rd row봉화군 법전면 풍정리 751
4th row봉화군 소천면 고선리 501-4
5th row봉화군 재산면 갈산리 57-1
ValueCountFrequency (%)
봉화군 25
25.0%
소천면 5
 
5.0%
재산면 4
 
4.0%
석포면 4
 
4.0%
상운면 3
 
3.0%
물야면 2
 
2.0%
분천리 2
 
2.0%
명호면 2
 
2.0%
갈산리 2
 
2.0%
고선리 2
 
2.0%
Other values (46) 49
49.0%
2023-12-12T09:50:07.131066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
18.9%
봉 28
 
7.1%
면 27
 
6.8%
리 25
 
6.3%
화 25
 
6.3%
군 25
 
6.3%
1 18
 
4.5%
- 12
 
3.0%
5 11
 
2.8%
7 10
 
2.5%
Other values (54) 141
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
57.2%
Decimal Number 83
 
20.9%
Space Separator 75
 
18.9%
Dash Punctuation 12
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 28
12.3%
면 27
11.9%
리 25
 
11.0%
화 25
 
11.0%
군 25
 
11.0%
산 8
 
3.5%
천 7
 
3.1%
포 6
 
2.6%
석 6
 
2.6%
소 5
 
2.2%
Other values (42) 65
28.6%
Decimal Number
ValueCountFrequency (%)
1 18
21.7%
5 11
13.3%
7 10
12.0%
2 9
10.8%
8 8
9.6%
3 8
9.6%
0 5
 
6.0%
9 5
 
6.0%
6 5
 
6.0%
4 4
 
4.8%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
57.2%
Common 170
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 28
12.3%
면 27
11.9%
리 25
 
11.0%
화 25
 
11.0%
군 25
 
11.0%
산 8
 
3.5%
천 7
 
3.1%
포 6
 
2.6%
석 6
 
2.6%
소 5
 
2.2%
Other values (42) 65
28.6%
Common
ValueCountFrequency (%)
75
44.1%
1 18
 
10.6%
- 12
 
7.1%
5 11
 
6.5%
7 10
 
5.9%
2 9
 
5.3%
8 8
 
4.7%
3 8
 
4.7%
0 5
 
2.9%
9 5
 
2.9%
Other values (2) 9
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
57.2%
ASCII 170
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
44.1%
1 18
 
10.6%
- 12
 
7.1%
5 11
 
6.5%
7 10
 
5.9%
2 9
 
5.3%
8 8
 
4.7%
3 8
 
4.7%
0 5
 
2.9%
9 5
 
2.9%
Other values (2) 9
 
5.3%
Hangul
ValueCountFrequency (%)
봉 28
12.3%
면 27
11.9%
리 25
 
11.0%
화 25
 
11.0%
군 25
 
11.0%
산 8
 
3.5%
천 7
 
3.1%
포 6
 
2.6%
석 6
 
2.6%
소 5
 
2.2%
Other values (42) 65
28.6%

토지면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean7076.9167
Minimum3194
Maximum18049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T09:50:07.309439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3194
5-th percentile3428.1
Q14816
median5656.5
Q37681.5
95-th percentile13724.35
Maximum18049
Range14855
Interquartile range (IQR)2865.5

Descriptive statistics

Standard deviation3666.097
Coefficient of variation (CV)0.51803592
Kurtosis2.5420912
Mean7076.9167
Median Absolute Deviation (MAD)1331
Skewness1.634706
Sum169846
Variance13440268
MonotonicityNot monotonic
2023-12-12T09:50:07.453221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3729 1
 
4.0%
6846 1
 
4.0%
13443 1
 
4.0%
18049 1
 
4.0%
5410 1
 
4.0%
3194 1
 
4.0%
9352 1
 
4.0%
5660 1
 
4.0%
5653 1
 
4.0%
7039 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
3194 1
4.0%
3375 1
4.0%
3729 1
4.0%
4195 1
4.0%
4377 1
4.0%
4387 1
4.0%
4959 1
4.0%
5391 1
4.0%
5405 1
4.0%
5410 1
4.0%
ValueCountFrequency (%)
18049 1
4.0%
13774 1
4.0%
13443 1
4.0%
10677 1
4.0%
9352 1
4.0%
8658 1
4.0%
7356 1
4.0%
7039 1
4.0%
6846 1
4.0%
6763 1
4.0%

건물면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean744.33125
Minimum88
Maximum1702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T09:50:07.601766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88
5-th percentile257
Q1414.75
median753.5
Q3977.295
95-th percentile1578.5335
Maximum1702
Range1614
Interquartile range (IQR)562.545

Descriptive statistics

Standard deviation421.61093
Coefficient of variation (CV)0.56642917
Kurtosis0.11599016
Mean744.33125
Median Absolute Deviation (MAD)313
Skewness0.73334463
Sum17863.95
Variance177755.78
MonotonicityNot monotonic
2023-12-12T09:50:07.750611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
88.0 1
 
4.0%
1141.0 1
 
4.0%
975.06 1
 
4.0%
1371.89 1
 
4.0%
476.0 1
 
4.0%
685.0 1
 
4.0%
245.0 1
 
4.0%
1702.0 1
 
4.0%
783.0 1
 
4.0%
335.0 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
88.0 1
4.0%
245.0 1
4.0%
325.0 1
4.0%
335.0 1
4.0%
342.0 1
4.0%
399.0 1
4.0%
420.0 1
4.0%
438.0 1
4.0%
476.0 1
4.0%
520.0 1
4.0%
ValueCountFrequency (%)
1702.0 1
4.0%
1615.0 1
4.0%
1371.89 1
4.0%
1141.0 1
4.0%
1064.0 1
4.0%
984.0 1
4.0%
975.06 1
4.0%
837.0 1
4.0%
836.0 1
4.0%
783.0 1
4.0%

매각용도
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T09:50:07.939062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length4.76
Min length2

Characters and Unicode

Total characters119
Distinct characters58
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

Unique12 ?
Unique (%)48.0%

Sample

1st row농장
2nd row농장
3rd row요양원
4th row연수원
5th row농장
ValueCountFrequency (%)
농장 5
18.5%
소득증대시설 3
 
11.1%
주민복지시설 3
 
11.1%
대안학교 2
 
7.4%
목공예 1
 
3.7%
청소년체험시설 1
 
3.7%
반환 1
 
3.7%
국유지 1
 
3.7%
화실 1
 
3.7%
동식물재배용 1
 
3.7%
Other values (8) 8
29.6%
2023-12-12T09:50:08.378169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7
 
5.9%
설 7
 
5.9%
농 5
 
4.2%
대 5
 
4.2%
장 5
 
4.2%
원 5
 
4.2%
지 5
 
4.2%
주 4
 
3.4%
소 4
 
3.4%
교 4
 
3.4%
Other values (48) 68
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115
96.6%
Space Separator 2
 
1.7%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7
 
6.1%
설 7
 
6.1%
농 5
 
4.3%
대 5
 
4.3%
장 5
 
4.3%
원 5
 
4.3%
지 5
 
4.3%
주 4
 
3.5%
소 4
 
3.5%
교 4
 
3.5%
Other values (45) 64
55.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
96.6%
Common 4
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7
 
6.1%
설 7
 
6.1%
농 5
 
4.3%
대 5
 
4.3%
장 5
 
4.3%
원 5
 
4.3%
지 5
 
4.3%
주 4
 
3.5%
소 4
 
3.5%
교 4
 
3.5%
Other values (45) 64
55.7%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
96.6%
ASCII 4
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7
 
6.1%
설 7
 
6.1%
농 5
 
4.3%
대 5
 
4.3%
장 5
 
4.3%
원 5
 
4.3%
지 5
 
4.3%
주 4
 
3.5%
소 4
 
3.5%
교 4
 
3.5%
Other values (45) 64
55.7%
ASCII
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

특약등기여부(○,×)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
×
21 
○
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row×
2nd row×
3rd row×
4th row×
5th row×

Common Values

ValueCountFrequency (%)
× 21
84.0%
○ 4
 
16.0%

Length

2023-12-12T09:50:08.524406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:50:08.625863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
× 21
84.0%
○ 4
 
16.0%

특약등기기간
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
<NA>
21 
10
4 

Length

Max length4
Median length4
Mean length3.68
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
84.0%
10 4
 
16.0%

Length

2023-12-12T09:50:08.796426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:50:08.934704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
84.0%
10 4
 
16.0%

매각방법(수의계약,경쟁입찰등)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
수의계약
14 
공개입찰
10 
반환
 
1

Length

Max length4
Median length4
Mean length3.92
Min length2

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row수의계약
2nd row수의계약
3rd row수의계약
4th row수의계약
5th row공개입찰

Common Values

ValueCountFrequency (%)
수의계약 14
56.0%
공개입찰 10
40.0%
반환 1
 
4.0%

Length

2023-12-12T09:50:09.052380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:50:09.171073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의계약 14
56.0%
공개입찰 10
40.0%
반환 1
 
4.0%

매각금액(단위:천원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean159258.88
Minimum3330
Maximum736425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T09:50:09.298131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3330
5-th percentile6304
Q157006.75
median110550
Q3151718.25
95-th percentile637494.1
Maximum736425
Range733095
Interquartile range (IQR)94711.5

Descriptive statistics

Standard deviation189420.28
Coefficient of variation (CV)1.1893861
Kurtosis4.8861744
Mean159258.88
Median Absolute Deviation (MAD)49371.5
Skewness2.2974307
Sum3822213
Variance3.5880044 × 1010
MonotonicityNot monotonic
2023-12-12T09:50:09.481650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3330 1
 
4.0%
88100 1
 
4.0%
678064 1
 
4.0%
736425 1
 
4.0%
114677 1
 
4.0%
96409 1
 
4.0%
407598 1
 
4.0%
111100 1
 
4.0%
60500 1
 
4.0%
129200 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
3330 1
4.0%
4750 1
4.0%
15110 1
4.0%
37100 1
4.0%
37500 1
4.0%
46527 1
4.0%
60500 1
4.0%
63800 1
4.0%
88100 1
4.0%
96409 1
4.0%
ValueCountFrequency (%)
736425 1
4.0%
678064 1
4.0%
407598 1
4.0%
243800 1
4.0%
186000 1
4.0%
159243 1
4.0%
149210 1
4.0%
130000 1
4.0%
129200 1
4.0%
114677 1
4.0%

관리계획
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)85.7%
Missing18
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean2012.8571
Minimum2006
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T09:50:09.610150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2006
Q12009
median2014
Q32016.5
95-th percentile2018.4
Maximum2019
Range13
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation5.1777914
Coefficient of variation (CV)0.0025723591
Kurtosis-1.3484379
Mean2012.8571
Median Absolute Deviation (MAD)3
Skewness-0.52114912
Sum14090
Variance26.809524
MonotonicityIncreasing
2023-12-12T09:50:10.019424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2006 2
 
8.0%
2012 1
 
4.0%
2014 1
 
4.0%
2016 1
 
4.0%
2017 1
 
4.0%
2019 1
 
4.0%
(Missing) 18
72.0%
ValueCountFrequency (%)
2006 2
8.0%
2012 1
4.0%
2014 1
4.0%
2016 1
4.0%
2017 1
4.0%
2019 1
4.0%
ValueCountFrequency (%)
2019 1
4.0%
2017 1
4.0%
2016 1
4.0%
2014 1
4.0%
2012 1
4.0%
2006 2
8.0%

매각일자
Date

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum1983-08-27 00:00:00
Maximum2019-08-22 00:00:00
2023-12-12T09:50:10.174730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:10.317388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

비고(국유지 및 기타 정보)
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing20
Missing (%)80.0%
Memory size332.0 B
2023-12-12T09:50:10.542184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.8
Min length6

Characters and Unicode

Total characters34
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row국유지185㎡
2nd row국유지218㎡
3rd row국유지747㎡
4th row국유지188㎡
5th row국유지 반환
ValueCountFrequency (%)
국유지185㎡ 1
16.7%
국유지218㎡ 1
16.7%
국유지747㎡ 1
16.7%
국유지188㎡ 1
16.7%
국유지 1
16.7%
반환 1
16.7%
2023-12-12T09:50:10.920853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 5
14.7%
유 5
14.7%
지 5
14.7%
8 4
11.8%
㎡ 4
11.8%
1 3
8.8%
7 2
 
5.9%
5 1
 
2.9%
2 1
 
2.9%
4 1
 
2.9%
Other values (3) 3
8.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17
50.0%
Decimal Number 12
35.3%
Other Symbol 4
 
11.8%
Space Separator 1
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 4
33.3%
1 3
25.0%
7 2
16.7%
5 1
 
8.3%
2 1
 
8.3%
4 1
 
8.3%
Other Letter
ValueCountFrequency (%)
국 5
29.4%
유 5
29.4%
지 5
29.4%
반 1
 
5.9%
환 1
 
5.9%
Other Symbol
ValueCountFrequency (%)
㎡ 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17
50.0%
Common 17
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 4
23.5%
㎡ 4
23.5%
1 3
17.6%
7 2
11.8%
5 1
 
5.9%
2 1
 
5.9%
4 1
 
5.9%
1
 
5.9%
Hangul
ValueCountFrequency (%)
국 5
29.4%
유 5
29.4%
지 5
29.4%
반 1
 
5.9%
환 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17
50.0%
ASCII 13
38.2%
CJK Compat 4
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 5
29.4%
유 5
29.4%
지 5
29.4%
반 1
 
5.9%
환 1
 
5.9%
ASCII
ValueCountFrequency (%)
8 4
30.8%
1 3
23.1%
7 2
15.4%
5 1
 
7.7%
2 1
 
7.7%
4 1
 
7.7%
1
 
7.7%
CJK Compat
ValueCountFrequency (%)
㎡ 4
100.0%

용도
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
농업
7 
주민복지
5 
수련
2 
교육
2 
문화
2 
Other values (7)
7 

Length

Max length7
Median length2
Mean length2.84
Min length2

Unique

Unique7 ?
Unique (%)28.0%

Sample

1st row농업
2nd row농업
3rd row사회복지
4th row수련
5th row농업

Common Values

ValueCountFrequency (%)
농업 7
28.0%
주민복지 5
20.0%
수련 2
 
8.0%
교육 2
 
8.0%
문화 2
 
8.0%
사회복지 1
 
4.0%
주거 1
 
4.0%
체험 1
 
4.0%
박물 1
 
4.0%
편입 1
 
4.0%
Other values (2) 2
 
8.0%

Length

2023-12-12T09:50:11.111078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농업 7
28.0%
주민복지 5
20.0%
수련 2
 
8.0%
교육 2
 
8.0%
문화 2
 
8.0%
사회복지 1
 
4.0%
주거 1
 
4.0%
체험 1
 
4.0%
박물 1
 
4.0%
편입 1
 
4.0%
Other values (2) 2
 
8.0%

Interactions

2023-12-12T09:50:04.429292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:01.693697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.378158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.016435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.736396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.538562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:01.831137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.517371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.156028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.871993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.665996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:01.979532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.648644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.280939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.016294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.780524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.131897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.772337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.410171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.151312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.928885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.269883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:02.895953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:03.582349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:04.283619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:50:11.261318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐교명폐교연도소재지토지면적(㎡)건물면적(㎡)매각용도특약등기여부(○,×)매각방법(수의계약,경쟁입찰등)매각금액(단위:천원)관리계획매각일자비고(국유지 및 기타 정보)용도
폐교명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
폐교연도1.0001.0001.0000.6150.5450.0001.0000.0000.6631.0001.0001.0000.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
토지면적(㎡)1.0000.6151.0001.0000.8100.7690.6940.0000.9481.0001.0001.0000.710
건물면적(㎡)1.0000.5451.0000.8101.0000.8310.6540.6280.7301.0001.0001.0000.787
매각용도1.0000.0001.0000.7690.8311.0000.8570.8890.8091.0001.0001.0000.999
특약등기여부(○,×)1.0001.0001.0000.6940.6540.8571.0000.1670.8131.0001.000NaN0.444
매각방법(수의계약,경쟁입찰등)1.0000.0001.0000.0000.6280.8890.1671.0000.415NaN1.0001.0000.945
매각금액(단위:천원)1.0000.6631.0000.9480.7300.8090.8130.4151.0001.0001.0001.0000.675
관리계획1.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.000NaN1.000
매각일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
비고(국유지 및 기타 정보)1.0001.0001.0001.0001.0001.000NaN1.0001.000NaN1.0001.0001.000
용도1.0000.0001.0000.7100.7870.9990.4440.9450.6751.0001.0001.0001.000
2023-12-12T09:50:11.457301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특약등기여부(○,×)특약등기기간매각방법(수의계약,경쟁입찰등)용도
특약등기여부(○,×)1.0001.0000.2630.225
특약등기기간1.0001.0001.0001.000
매각방법(수의계약,경쟁입찰등)0.2631.0001.0000.556
용도0.2251.0000.5561.000
2023-12-12T09:50:11.562150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐교연도토지면적(㎡)건물면적(㎡)매각금액(단위:천원)관리계획특약등기여부(○,×)특약등기기간매각방법(수의계약,경쟁입찰등)용도
폐교연도1.0000.4680.5140.6060.9540.8341.0000.0000.000
토지면적(㎡)0.4681.0000.6860.7230.5410.3891.0000.0000.380
건물면적(㎡)0.5140.6861.0000.8030.0180.5381.0000.2690.405
매각금액(단위:천원)0.6060.7230.8031.0000.4140.5621.0000.2890.365
관리계획0.9540.5410.0180.4141.0000.4471.0000.0000.000
특약등기여부(○,×)0.8340.3890.5380.5620.4471.0001.0000.2630.225
특약등기기간1.0001.0001.0001.0001.0001.0001.0001.0001.000
매각방법(수의계약,경쟁입찰등)0.0000.0000.2690.2890.0000.2631.0001.0000.556
용도0.0000.3800.4050.3650.0000.2251.0000.5561.000

Missing values

2023-12-12T09:50:05.082600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:50:05.299488image/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.
2023-12-12T09:50:05.456228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

교육청폐교명폐교연도소재지토지면적(㎡)건물면적(㎡)매각용도특약등기여부(○,×)특약등기기간매각방법(수의계약,경쟁입찰등)매각금액(단위:천원)관리계획매각일자비고(국유지 및 기타 정보)용도
0봉화교육지원청동양초등학교금봉분교장1983봉화군 봉성면 금봉리 769-1372988.0농장×<NA>수의계약3330<NA>1983-08-27<NA>농업
1봉화교육지원청문촌초등학교1988봉화군 상운면 문촌리 7855470748.0농장×<NA>수의계약4750<NA>1990-05-04<NA>농업
2봉화교육지원청다덕초등학교1992봉화군 법전면 풍정리 7517356759.0요양원×<NA>수의계약159243<NA>1997-07-16<NA>사회복지
3봉화교육지원청소천초등학교 고선분교장1992봉화군 소천면 고선리 501-44195420.0연수원×<NA>수의계약37500<NA>1994-09-09<NA>수련
4봉화교육지원청소천초등학교 우련전분교장1992봉화군 재산면 갈산리 57-14959342.0농장×<NA>공개입찰46527<NA>1999-12-01<NA>농업
5봉화교육지원청고계초등학교1993봉화군 명호면 고계리 6136763775.0농장×<NA>공개입찰111650<NA>2000-08-16<NA>농업
6봉화교육지원청석포초등학교 승부분교장1993봉화군 석포면 승부리 4375391<NA>수련원×<NA>수의계약15110<NA>1999-12-04<NA>수련
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8봉화교육지원청소천중학교 옥방분교장1995봉화군 소천면 분천리 93375984.0친환경(녹색환경 체험교실)×<NA>공개입찰13000020062009-04-30<NA>체험
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15봉화교육지원청애당초등학교1999봉화군 춘양면 애당리 185137741615.0목공예×<NA>수의계약243800<NA>2001-08-03국유지747㎡문화
16봉화교육지원청명호초등학교 삼동분교장1999봉화군 명호면 삼동리 6397039837.0동식물재배용×<NA>공개입찰129200<NA>2001-11-22국유지188㎡농업
17봉화교육지원청동양초등학교 우곡분교장2001봉화군 봉성면 우곡리 272-15653335.0주민복지시설×<NA>수의계약60500<NA>2001-12-27<NA>주민복지
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