Overview

Dataset statistics

Number of variables11
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory98.3 B

Variable types

Categorical2
Text5
Numeric4

Dataset

Description일반농산어촌지역개발 사업정보
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=DEZNU86HQ6W7LNVXKCZV28156697&infSeq=1

Alerts

예산 is highly overall correlated with 준공예정일 and 1 other fieldsHigh correlation
준공예정일 is highly overall correlated with 예산 and 1 other fieldsHigh correlation
Y좌표값 is highly overall correlated with 사업유형High correlation
사업유형 is highly overall correlated with 예산 and 2 other fieldsHigh correlation
사업코드 has unique valuesUnique
사업명 has unique valuesUnique
주요사업내용 has unique valuesUnique
X좌표값 has unique valuesUnique
Y좌표값 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:52:17.127240
Analysis finished2023-12-10 22:52:19.563284
Duration2.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct9
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
여주시
7 
평택시
4 
안성시
2 
양평군
2 
이천시
2 
Other values (4)
4 

Length

Max length4
Median length3
Mean length3.047619
Min length3

Unique

Unique4 ?
Unique (%)19.0%

Sample

1st row가평군
2nd row광주시
3rd row남양주시
4th row안성시
5th row안성시

Common Values

ValueCountFrequency (%)
여주시 7
33.3%
평택시 4
19.0%
안성시 2
 
9.5%
양평군 2
 
9.5%
이천시 2
 
9.5%
가평군 1
 
4.8%
광주시 1
 
4.8%
남양주시 1
 
4.8%
용인시 1
 
4.8%

Length

2023-12-11T07:52:19.635453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:19.798270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여주시 7
33.3%
평택시 4
19.0%
안성시 2
 
9.5%
양평군 2
 
9.5%
이천시 2
 
9.5%
가평군 1
 
4.8%
광주시 1
 
4.8%
남양주시 1
 
4.8%
용인시 1
 
4.8%

사업코드
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:52:20.032967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters525
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row41820INS2017UA24010240192
2nd row41610INS2017UA24010240187
3rd row41360INS2017UA24010240185
4th row41550INS2017UA24010240189
5th row41550INS2017UA24010140351
ValueCountFrequency (%)
41820ins2017ua24010240192 1
 
4.8%
41670ins2017ua23060440018 1
 
4.8%
41220ins2017ua23060440017 1
 
4.8%
41220ins2017ua22020040385 1
 
4.8%
41220ins2017ua23060140156 1
 
4.8%
41500ins2017ua23060140177 1
 
4.8%
41500ins2017ua24010240188 1
 
4.8%
41460ins2017ua24010240184 1
 
4.8%
41670ins2011ua01030040116 1
 
4.8%
41670ins2017ua22020040386 1
 
4.8%
Other values (11) 11
52.4%
2023-12-11T07:52:20.359385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
22.9%
1 82
15.6%
2 64
12.2%
4 59
11.2%
7 31
 
5.9%
I 21
 
4.0%
N 21
 
4.0%
S 21
 
4.0%
U 21
 
4.0%
A 21
 
4.0%
Other values (5) 64
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
80.0%
Uppercase Letter 105
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
28.6%
1 82
19.5%
2 64
15.2%
4 59
14.0%
7 31
 
7.4%
6 18
 
4.3%
3 15
 
3.6%
8 14
 
3.3%
5 13
 
3.1%
9 4
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
I 21
20.0%
N 21
20.0%
S 21
20.0%
U 21
20.0%
A 21
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
80.0%
Latin 105
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
28.6%
1 82
19.5%
2 64
15.2%
4 59
14.0%
7 31
 
7.4%
6 18
 
4.3%
3 15
 
3.6%
8 14
 
3.3%
5 13
 
3.1%
9 4
 
1.0%
Latin
ValueCountFrequency (%)
I 21
20.0%
N 21
20.0%
S 21
20.0%
U 21
20.0%
A 21
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
22.9%
1 82
15.6%
2 64
12.2%
4 59
11.2%
7 31
 
5.9%
I 21
 
4.0%
N 21
 
4.0%
S 21
 
4.0%
U 21
 
4.0%
A 21
 
4.0%
Other values (5) 64
12.2%

사업명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:52:20.561593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length3
Mean length5.6190476
Min length2

Characters and Unicode

Total characters118
Distinct characters75
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row광주시
3rd row남양주시
4th row안성시
5th row청미천 Eco 나들이
ValueCountFrequency (%)
가평군 1
 
3.8%
광주시 1
 
3.8%
원덕목마을(덕목4리 1
 
3.8%
오성면 1
 
3.8%
대추리 1
 
3.8%
자채방아마을(이천시 1
 
3.8%
이천시 1
 
3.8%
용인시 1
 
3.8%
효지흥천면 1
 
3.8%
점동면 1
 
3.8%
Other values (16) 16
61.5%
2023-12-11T07:52:20.879779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 8
 
6.8%
면 5
 
4.2%
5
 
4.2%
이 4
 
3.4%
천 4
 
3.4%
( 3
 
2.5%
) 3
 
2.5%
주 3
 
2.5%
지 3
 
2.5%
평 3
 
2.5%
Other values (65) 77
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
86.4%
Space Separator 5
 
4.2%
Open Punctuation 3
 
2.5%
Close Punctuation 3
 
2.5%
Decimal Number 2
 
1.7%
Lowercase Letter 2
 
1.7%
Uppercase Letter 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 8
 
7.8%
면 5
 
4.9%
이 4
 
3.9%
천 4
 
3.9%
주 3
 
2.9%
지 3
 
2.9%
평 3
 
2.9%
리 3
 
2.9%
을 2
 
2.0%
효 2
 
2.0%
Other values (57) 65
63.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
86.4%
Common 13
 
11.0%
Latin 3
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 8
 
7.8%
면 5
 
4.9%
이 4
 
3.9%
천 4
 
3.9%
주 3
 
2.9%
지 3
 
2.9%
평 3
 
2.9%
리 3
 
2.9%
을 2
 
2.0%
효 2
 
2.0%
Other values (57) 65
63.7%
Common
ValueCountFrequency (%)
5
38.5%
( 3
23.1%
) 3
23.1%
2 1
 
7.7%
4 1
 
7.7%
Latin
ValueCountFrequency (%)
E 1
33.3%
c 1
33.3%
o 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
86.4%
ASCII 16
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 8
 
7.8%
면 5
 
4.9%
이 4
 
3.9%
천 4
 
3.9%
주 3
 
2.9%
지 3
 
2.9%
평 3
 
2.9%
리 3
 
2.9%
을 2
 
2.0%
효 2
 
2.0%
Other values (57) 65
63.7%
ASCII
ValueCountFrequency (%)
5
31.2%
( 3
18.8%
) 3
18.8%
2 1
 
6.2%
4 1
 
6.2%
E 1
 
6.2%
c 1
 
6.2%
o 1
 
6.2%

사업지역
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:52:21.026788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length8.8571429
Min length3

Characters and Unicode

Total characters186
Distinct characters53
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

Unique19 ?
Unique (%)90.5%

Sample

1st row경기도 가평군
2nd row경기도 광주시
3rd row경기도 남양주시
4th row경기도 안성시
5th row하주천
ValueCountFrequency (%)
경기도 11
33.3%
여주시 2
 
6.1%
양평군 2
 
6.1%
효지1리,효지2리 1
 
3.0%
청안1리,청안2리 1
 
3.0%
덕목4리 1
 
3.0%
숙성1리,숙성5리,죽5리 1
 
3.0%
노와1리,노와2리,노와4리,노와3리 1
 
3.0%
군량1리 1
 
3.0%
이천시 1
 
3.0%
Other values (11) 11
33.3%
2023-12-11T07:52:21.313919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 23
 
12.4%
, 14
 
7.5%
12
 
6.5%
기 11
 
5.9%
경 11
 
5.9%
도 11
 
5.9%
시 8
 
4.3%
1 7
 
3.8%
2 6
 
3.2%
주 5
 
2.7%
Other values (43) 78
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141
75.8%
Decimal Number 19
 
10.2%
Other Punctuation 14
 
7.5%
Space Separator 12
 
6.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 23
16.3%
기 11
 
7.8%
경 11
 
7.8%
도 11
 
7.8%
시 8
 
5.7%
주 5
 
3.5%
노 4
 
2.8%
와 4
 
2.8%
군 4
 
2.8%
평 4
 
2.8%
Other values (36) 56
39.7%
Decimal Number
ValueCountFrequency (%)
1 7
36.8%
2 6
31.6%
3 2
 
10.5%
4 2
 
10.5%
5 2
 
10.5%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141
75.8%
Common 45
 
24.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 23
16.3%
기 11
 
7.8%
경 11
 
7.8%
도 11
 
7.8%
시 8
 
5.7%
주 5
 
3.5%
노 4
 
2.8%
와 4
 
2.8%
군 4
 
2.8%
평 4
 
2.8%
Other values (36) 56
39.7%
Common
ValueCountFrequency (%)
, 14
31.1%
12
26.7%
1 7
15.6%
2 6
13.3%
3 2
 
4.4%
4 2
 
4.4%
5 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 141
75.8%
ASCII 45
 
24.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 23
16.3%
기 11
 
7.8%
경 11
 
7.8%
도 11
 
7.8%
시 8
 
5.7%
주 5
 
3.5%
노 4
 
2.8%
와 4
 
2.8%
군 4
 
2.8%
평 4
 
2.8%
Other values (36) 56
39.7%
ASCII
ValueCountFrequency (%)
, 14
31.1%
12
26.7%
1 7
15.6%
2 6
13.3%
3 2
 
4.4%
4 2
 
4.4%
5 2
 
4.4%

사업유형
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
시ㆍ군역량강화
9 
시ㆍ군창의
2 
읍면소재지종합정비
2 
[마을단위]환경(경관ㆍ생태)
2 
농촌 중심지 활성화(일반지구)
2 
Other values (3)
4 

Length

Max length16
Median length15
Mean length8.9047619
Min length5

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row시ㆍ군역량강화
2nd row시ㆍ군역량강화
3rd row시ㆍ군역량강화
4th row시ㆍ군역량강화
5th row시ㆍ군창의

Common Values

ValueCountFrequency (%)
시ㆍ군역량강화 9
42.9%
시ㆍ군창의 2
 
9.5%
읍면소재지종합정비 2
 
9.5%
[마을단위]환경(경관ㆍ생태) 2
 
9.5%
농촌 중심지 활성화(일반지구) 2
 
9.5%
[마을단위]종합개발 2
 
9.5%
창조지역사업 1
 
4.8%
권역단위종합정비 1
 
4.8%

Length

2023-12-11T07:52:21.440776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:21.575554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시ㆍ군역량강화 9
36.0%
시ㆍ군창의 2
 
8.0%
읍면소재지종합정비 2
 
8.0%
마을단위]환경(경관ㆍ생태 2
 
8.0%
농촌 2
 
8.0%
중심지 2
 
8.0%
활성화(일반지구 2
 
8.0%
마을단위]종합개발 2
 
8.0%
창조지역사업 1
 
4.0%
권역단위종합정비 1
 
4.0%

예산
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7705562 × 109
Minimum50000000
Maximum7 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:52:21.761302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50000000
5-th percentile50000000
Q11 × 108
median5 × 108
Q31 × 109
95-th percentile6.99948 × 109
Maximum7 × 109
Range6.95 × 109
Interquartile range (IQR)9 × 108

Descriptive statistics

Standard deviation2.5514247 × 109
Coefficient of variation (CV)1.4410301
Kurtosis0.13387184
Mean1.7705562 × 109
Median Absolute Deviation (MAD)4.5 × 108
Skewness1.3683691
Sum3.718168 × 1010
Variance6.5097681 × 1018
MonotonicityNot monotonic
2023-12-11T07:52:21.865010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
50000000 5
23.8%
1000000000 4
19.0%
200000000 2
 
9.5%
500000000 2
 
9.5%
100000000 1
 
4.8%
730200000 1
 
4.8%
4500000000 1
 
4.8%
7000000000 1
 
4.8%
150000000 1
 
4.8%
6000000000 1
 
4.8%
Other values (2) 2
 
9.5%
ValueCountFrequency (%)
50000000 5
23.8%
100000000 1
 
4.8%
150000000 1
 
4.8%
200000000 2
 
9.5%
500000000 2
 
9.5%
730200000 1
 
4.8%
1000000000 4
19.0%
4500000000 1
 
4.8%
6000000000 1
 
4.8%
6052000000 1
 
4.8%
ValueCountFrequency (%)
7000000000 1
 
4.8%
6999480000 1
 
4.8%
6052000000 1
 
4.8%
6000000000 1
 
4.8%
4500000000 1
 
4.8%
1000000000 4
19.0%
730200000 1
 
4.8%
500000000 2
9.5%
200000000 2
9.5%
150000000 1
 
4.8%

준공예정일
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20180293
Minimum20151231
Maximum20211231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:52:21.966358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20151231
5-th percentile20170000
Q120170000
median20171229
Q320190000
95-th percentile20200000
Maximum20211231
Range60000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation14501.395
Coefficient of variation (CV)0.00071859189
Kurtosis-0.3048852
Mean20180293
Median Absolute Deviation (MAD)10002
Skewness0.284469
Sum4.2378615 × 108
Variance2.1029045 × 108
MonotonicityNot monotonic
2023-12-11T07:52:22.066392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20170000 9
42.9%
20190000 5
23.8%
20200000 2
 
9.5%
20191231 1
 
4.8%
20181231 1
 
4.8%
20171229 1
 
4.8%
20211231 1
 
4.8%
20151231 1
 
4.8%
ValueCountFrequency (%)
20151231 1
 
4.8%
20170000 9
42.9%
20171229 1
 
4.8%
20181231 1
 
4.8%
20190000 5
23.8%
20191231 1
 
4.8%
20200000 2
 
9.5%
20211231 1
 
4.8%
ValueCountFrequency (%)
20211231 1
 
4.8%
20200000 2
 
9.5%
20191231 1
 
4.8%
20190000 5
23.8%
20181231 1
 
4.8%
20171229 1
 
4.8%
20170000 9
42.9%
20151231 1
 
4.8%

포함지역
Text

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:52:22.233295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length5.7142857
Min length2

Characters and Unicode

Total characters120
Distinct characters42
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

Unique15 ?
Unique (%)71.4%

Sample

1st row가평군 일원
2nd row광주시 일원
3rd row남양주시 일원
4th row안성시 일원
5th row안성시 일원
ValueCountFrequency (%)
일원 16
42.1%
안성시 2
 
5.3%
양평군 2
 
5.3%
여주시 2
 
5.3%
노와리 1
 
2.6%
가평군 1
 
2.6%
용인시 1
 
2.6%
덕목리 1
 
2.6%
죽리 1
 
2.6%
숙성리 1
 
2.6%
Other values (10) 10
26.3%
2023-12-11T07:52:22.541292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
14.2%
일 16
13.3%
원 16
13.3%
시 9
 
7.5%
리 8
 
6.7%
주 4
 
3.3%
평 4
 
3.3%
군 4
 
3.3%
성 3
 
2.5%
안 3
 
2.5%
Other values (32) 36
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
82.5%
Space Separator 17
 
14.2%
Decimal Number 3
 
2.5%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 16
16.2%
원 16
16.2%
시 9
 
9.1%
리 8
 
8.1%
주 4
 
4.0%
평 4
 
4.0%
군 4
 
4.0%
성 3
 
3.0%
안 3
 
3.0%
양 3
 
3.0%
Other values (27) 29
29.3%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
0 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
82.5%
Common 21
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 16
16.2%
원 16
16.2%
시 9
 
9.1%
리 8
 
8.1%
주 4
 
4.0%
평 4
 
4.0%
군 4
 
4.0%
성 3
 
3.0%
안 3
 
3.0%
양 3
 
3.0%
Other values (27) 29
29.3%
Common
ValueCountFrequency (%)
17
81.0%
, 1
 
4.8%
5 1
 
4.8%
0 1
 
4.8%
3 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
82.5%
ASCII 21
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
81.0%
, 1
 
4.8%
5 1
 
4.8%
0 1
 
4.8%
3 1
 
4.8%
Hangul
ValueCountFrequency (%)
일 16
16.2%
원 16
16.2%
시 9
 
9.1%
리 8
 
8.1%
주 4
 
4.0%
평 4
 
4.0%
군 4
 
4.0%
성 3
 
3.0%
안 3
 
3.0%
양 3
 
3.0%
Other values (27) 29
29.3%

주요사업내용
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:52:22.804048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length156
Median length47
Mean length73.857143
Min length24

Characters and Unicode

Total characters1551
Distinct characters206
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row- 지역역량강화 : 사업준비지구 역량강화, 사업완료지구 역량강화
2nd row- 지역역량강화 : 현장포럼, 주민교육, 소액사업
3rd row- 지역역량강화 : 농촌현장포럼, 마을(리더)교육, 공무원 역량강화교육, 소액단위사업
4th row- 지역역량강화 : 사업준비 지구, 사업완료 지구, 기타
5th row- 기초생활기반확충 : 청미천 생태체험학습장, 어린이 자전거 안전운전 인증장, 생태주차장 및 화장실 조성, 농촌체험마을 종합안내소 - 지역역량강화 : 농촌생태체험 스탬프 레이스, 청미천 생태교실 운영, 교육 및 프로그램 지원, 홍보 및 마케팅, 부대비용
ValueCountFrequency (%)
60
 
18.2%
지역역량강화 18
 
5.5%
교육 12
 
3.6%
조성 12
 
3.6%
및 9
 
2.7%
부대비용 7
 
2.1%
기초생활기반확충 6
 
1.8%
컨설팅 6
 
1.8%
지역경관개선 6
 
1.8%
역량강화 6
 
1.8%
Other values (144) 188
57.0%
2023-12-11T07:52:23.258464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
 
19.9%
, 93
 
6.0%
역 55
 
3.5%
지 43
 
2.8%
화 38
 
2.5%
강 32
 
2.1%
- 31
 
2.0%
: 30
 
1.9%
량 30
 
1.9%
비 26
 
1.7%
Other values (196) 864
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1074
69.2%
Space Separator 309
 
19.9%
Other Punctuation 125
 
8.1%
Dash Punctuation 31
 
2.0%
Decimal Number 6
 
0.4%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 55
 
5.1%
지 43
 
4.0%
화 38
 
3.5%
강 32
 
3.0%
량 30
 
2.8%
비 26
 
2.4%
마 22
 
2.0%
성 21
 
2.0%
관 21
 
2.0%
교 21
 
2.0%
Other values (187) 765
71.2%
Other Punctuation
ValueCountFrequency (%)
, 93
74.4%
: 30
 
24.0%
· 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
3 5
83.3%
6 1
 
16.7%
Space Separator
ValueCountFrequency (%)
309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1074
69.2%
Common 477
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 55
 
5.1%
지 43
 
4.0%
화 38
 
3.5%
강 32
 
3.0%
량 30
 
2.8%
비 26
 
2.4%
마 22
 
2.0%
성 21
 
2.0%
관 21
 
2.0%
교 21
 
2.0%
Other values (187) 765
71.2%
Common
ValueCountFrequency (%)
309
64.8%
, 93
 
19.5%
- 31
 
6.5%
: 30
 
6.3%
3 5
 
1.0%
) 3
 
0.6%
( 3
 
0.6%
· 2
 
0.4%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1074
69.2%
ASCII 475
30.6%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
65.1%
, 93
 
19.6%
- 31
 
6.5%
: 30
 
6.3%
3 5
 
1.1%
) 3
 
0.6%
( 3
 
0.6%
6 1
 
0.2%
Hangul
ValueCountFrequency (%)
역 55
 
5.1%
지 43
 
4.0%
화 38
 
3.5%
강 32
 
3.0%
량 30
 
2.8%
비 26
 
2.4%
마 22
 
2.0%
성 21
 
2.0%
관 21
 
2.0%
교 21
 
2.0%
Other values (187) 765
71.2%
None
ValueCountFrequency (%)
· 2
100.0%

X좌표값
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean269024.56
Minimum129217.18
Maximum395287.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:52:23.638239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129217.18
5-th percentile139868.6
Q1227373.1
median263146.52
Q3334616.28
95-th percentile367012.24
Maximum395287.23
Range266070.06
Interquartile range (IQR)107243.18

Descriptive statistics

Standard deviation78109.334
Coefficient of variation (CV)0.29034276
Kurtosis-0.80550972
Mean269024.56
Median Absolute Deviation (MAD)57588.794
Skewness-0.2796403
Sum5649515.8
Variance6.101068 × 109
MonotonicityNot monotonic
2023-12-11T07:52:23.762557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
284428.75908118 1
 
4.8%
356498.54290797 1
 
4.8%
344315.6943576 1
 
4.8%
269847.10998694 1
 
4.8%
395287.23296274 1
 
4.8%
139868.59657442 1
 
4.8%
129217.1763954 1
 
4.8%
334616.27733159 1
 
4.8%
150942.81869963 1
 
4.8%
358746.16115454 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
129217.1763954 1
4.8%
139868.59657442 1
4.8%
150942.81869963 1
4.8%
170864.85838365 1
4.8%
220537.51709259 1
4.8%
227373.09616404 1
4.8%
237758.13336949 1
4.8%
248904.25675852 1
4.8%
250510.50561784 1
4.8%
262931.92813447 1
4.8%
ValueCountFrequency (%)
395287.23296274 1
4.8%
367012.23500553 1
4.8%
358746.16115454 1
4.8%
356498.54290797 1
4.8%
344315.6943576 1
4.8%
334616.27733159 1
4.8%
320735.31439249 1
4.8%
315973.10783633 1
4.8%
284428.75908118 1
4.8%
269847.10998694 1
4.8%

Y좌표값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268937.2
Minimum109607.96
Maximum549085.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:52:23.866921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum109607.96
5-th percentile114060.52
Q1184084.34
median238231.61
Q3304940.55
95-th percentile525029.07
Maximum549085.08
Range439477.12
Interquartile range (IQR)120856.22

Descriptive statistics

Standard deviation117278.07
Coefficient of variation (CV)0.43607976
Kurtosis0.9176017
Mean268937.2
Median Absolute Deviation (MAD)60710.404
Skewness1.0055426
Sum5647681.2
Variance1.3754146 × 1010
MonotonicityNot monotonic
2023-12-11T07:52:23.958742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
204900.59291093 1
 
4.8%
151512.51938692 1
 
4.8%
291971.07083118 1
 
4.8%
386927.73388982 1
 
4.8%
287685.63081927 1
 
4.8%
109607.95861603 1
 
4.8%
114060.52206902 1
 
4.8%
292826.39031652 1
 
4.8%
177521.20348884 1
 
4.8%
223732.54948328 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
109607.95861603 1
4.8%
114060.52206902 1
4.8%
151512.51938692 1
4.8%
174316.14028966 1
4.8%
177521.20348884 1
4.8%
184084.33508187 1
4.8%
204900.59291093 1
4.8%
212527.40070823 1
4.8%
221136.50407195 1
4.8%
223732.54948328 1
4.8%
ValueCountFrequency (%)
549085.0765366 1
4.8%
525029.06515563 1
4.8%
386927.73388982 1
4.8%
356185.36241356 1
4.8%
344680.96175174 1
4.8%
304940.55081224 1
4.8%
296717.99703928 1
4.8%
292826.39031652 1
4.8%
291971.07083118 1
4.8%
287685.63081927 1
4.8%

Interactions

2023-12-11T07:52:18.884349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.669733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.077405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.496085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.979784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.772060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.172889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.626609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:19.071871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.875505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.270254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.709165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:19.174149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.980410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.399513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.796006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:52:24.031982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업코드사업명사업지역사업유형예산준공예정일포함지역주요사업내용X좌표값Y좌표값
시군명1.0001.0001.0001.0000.0000.0000.0001.0001.0000.0000.416
사업코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업지역1.0001.0001.0001.0000.7431.0000.9431.0001.0000.6330.924
사업유형0.0001.0001.0000.7431.0001.0000.8650.0001.0000.5930.719
예산0.0001.0001.0001.0001.0001.0000.9160.4021.0000.7060.499
준공예정일0.0001.0001.0000.9430.8650.9161.0000.9051.0000.4810.000
포함지역1.0001.0001.0001.0000.0000.4020.9051.0001.0000.0000.850
주요사업내용1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
X좌표값0.0001.0001.0000.6330.5930.7060.4810.0001.0001.0000.318
Y좌표값0.4161.0001.0000.9240.7190.4990.0000.8501.0000.3181.000
2023-12-11T07:52:24.139388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업유형
시군명1.0000.000
사업유형0.0001.000
2023-12-11T07:52:24.219275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산준공예정일X좌표값Y좌표값시군명사업유형
예산1.0000.5490.073-0.0650.0000.901
준공예정일0.5491.000-0.269-0.0970.0000.657
X좌표값0.073-0.2691.0000.1870.0000.295
Y좌표값-0.065-0.0970.1871.0000.0000.510
시군명0.0000.0000.0000.0001.0000.000
사업유형0.9010.6570.2950.5100.0001.000

Missing values

2023-12-11T07:52:19.305290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:52:19.488843image/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

시군명사업코드사업명사업지역사업유형예산준공예정일포함지역주요사업내용X좌표값Y좌표값
0가평군41820INS2017UA24010240192가평군경기도 가평군시ㆍ군역량강화5000000020170000가평군 일원- 지역역량강화 : 사업준비지구 역량강화, 사업완료지구 역량강화284428.759081204900.592911
1광주시41610INS2017UA24010240187광주시경기도 광주시시ㆍ군역량강화5000000020170000광주시 일원- 지역역량강화 : 현장포럼, 주민교육, 소액사업356498.542908151512.519387
2남양주시41360INS2017UA24010240185남양주시경기도 남양주시시ㆍ군역량강화5000000020170000남양주시 일원- 지역역량강화 : 농촌현장포럼, 마을(리더)교육, 공무원 역량강화교육, 소액단위사업315973.107836304940.550812
3안성시41550INS2017UA24010240189안성시경기도 안성시시ㆍ군역량강화10000000020170000안성시 일원- 지역역량강화 : 사업준비 지구, 사업완료 지구, 기타250510.505618344680.961752
4안성시41550INS2017UA24010140351청미천 Eco 나들이하주천시ㆍ군창의100000000020190000안성시 일원- 기초생활기반확충 : 청미천 생태체험학습장, 어린이 자전거 안전운전 인증장, 생태주차장 및 화장실 조성, 농촌체험마을 종합안내소 - 지역역량강화 : 농촌생태체험 스탬프 레이스, 청미천 생태교실 운영, 교육 및 프로그램 지원, 홍보 및 마케팅, 부대비용220537.517093525029.065156
5양평군41830INS2017UA24010240191양평군경기도 양평군시ㆍ군역량강화20000000020170000양평군 일원- 지역역량강화 : 사업준비지구 역량강화, 사업완료지구 역량강화, 기타역량 강화170864.858384296717.997039
6양평군41830INS2017UA05020040478지역네트워크를 활용한 헬스투어운영 사업경기도 양평군창조지역사업73020000020191231양평군 일원-양평헬스투어센터 운영사업, 헬스투어 프로그램 개발사업, 주민중심 전문가 인재 양성 및 보수교육, 서비스마인드 교육, 방문객중심 통합홈페이지 구성 및 운영사업, 헬스투어 연계한 6차 상품개발 및 판매사업, 헬스투어 홍보 마케팅, 헬스투어 코스 개발 및 유지관리, 헬스투어 물품구입263146.520643184084.335082
7여주시41670INS2013UA02040040115금당금곡리,금당1리,금당2리,연대리,삼승리,송림리권역단위종합정비450000000020181231일원문화회관리모델링, 다목적회관, 공동생활홈, 다목적운동장, 생태공원, 마을조형물, 지붕정비, 안내간판, 교육 및 선진지견학, 일반컨설팅, 홍보마케팅, 정보화구축, 부대비용, 예비비227373.096164238231.607401
8여주시41670INS2013UA01030040117대신면율촌1리,율촌2리,율촌3리읍면소재지종합정비700000000020171229305번지 일원다목적 복지회관, 상하수도정비, 버스승강장정비, 가로등정비, 주민역량강화367012.235006212527.400708
9여주시41670INS2017UA24010140352세종전통발효단지(능서면)경기도 여주시 능서면시ㆍ군창의100000000020190000여주시 능서면 일원- 기초생활기반확충 : 세종전통발효관 신축 - 지역역량강화 : 효소식품산업 발전 종합계획 수립, 전통발효효소식품 홍보 및 교육320735.314392549085.076537
시군명사업코드사업명사업지역사업유형예산준공예정일포함지역주요사업내용X좌표값Y좌표값
11여주시41670INS2017UA23060440018이포2리이포2리[마을단위]환경(경관ㆍ생태)50000000020190000이포리- 지역경관개선 : 금빛(돌담)길 경관조성, 서원안길 경관조성, 옹기문화길 경관조성 - 지역역량강화 : 교육, 홍보마케팅, 컨설팅, 부대비용248904.256759356185.362414
12여주시41670INS2017UA22020040386점동면청안1리,청안2리농촌 중심지 활성화(일반지구)600000000020211231청안리 일원- 기초생활기반확충 : 3도 문화교류센터 조성, 3도 어울림마당 조성, 3도 학습교류센터 조성 - 지역경관개선 : 중심지 가로경관정비, 중심지 간판정비, 3도 교류 안내판 조성, 3도 화합 소공원 조성 - 지역역량강화 : 교육, 홍보마케팅, 컨설팅, 부대비용237758.133369174316.14029
13여주시41670INS2011UA01030040116효지흥천면효지1리,효지2리읍면소재지종합정비699948000020151231일원흥천문화복지센터, 체육시설보강, 지역역량강화358746.161155223732.549483
14용인시41460INS2017UA24010240184용인시경기도 용인시시ㆍ군역량강화5000000020170000용인시 일원- 지역역량강화 : 농촌 현장포럼, 교육, 소액사업150942.8187177521.203489
15이천시41500INS2017UA24010240188이천시경기도 이천시시ㆍ군역량강화5000000020170000이천시 일원- 지역역량강화 : 사업준비 지구, 사업완료 지구, 기타역량 강화334616.277332292826.390317
16이천시41500INS2017UA23060140177자채방아마을(이천시)군량1리[마을단위]종합개발100000000020190000군량리- 기초생활기반확충 : 도로정비, 갤러리정미소 - 지역경관개선 : 체험관 경관조성, 마을담장 정비 - 지역역량강화 : 교육, 홍보마케팅, 컨설팅, 부대경비129217.176395114060.522069
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19평택시41220INS2017UA23060440017원덕목마을(덕목4리)덕목4리[마을단위]환경(경관ㆍ생태)50000000020190000덕목리- 지역경관개선 : 덕목들판 억새길 복원, 아름다운 마을안길, 운덕목쉼터 조성, 마을회관 환경개선, 안내판·이정표 조성 - 지역역량강화 : 교육, 컨설팅, 홍보마케팅, 부대비용269847.109987386927.73389
20평택시41220INS2017UA24010240186평택시경기도 평택시시ㆍ군역량강화20000000020170000평택시 일원- 지역역량강화 : 농촌현장포럼, 교육, 사업완료지구 역량강화, 기타 역량강화344315.694358291971.070831