Overview

Dataset statistics

Number of variables13
Number of observations1491
Missing cells3475
Missing cells (%)17.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory157.4 KiB
Average record size in memory108.1 B

Variable types

Numeric2
DateTime3
Text3
Categorical5

Dataset

Description충청남도 부여군에 위치한 신재생에너지(전기사업) 발전 허가 현황(발전소명, 설비용량, 공급전압, 주파수, 지목, 주소, 허가일 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=385&beforeMenuCd=DOM_000000201001001000&publicdatapk=15033955

Alerts

주파수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
지목 is highly overall correlated with 설치위치 and 1 other fieldsHigh correlation
공급전압 is highly overall correlated with 지목High correlation
설치위치 is highly overall correlated with 지목High correlation
설치위치 is highly imbalanced (67.6%)Imbalance
공급전압 is highly imbalanced (99.2%)Imbalance
지목 is highly imbalanced (50.1%)Imbalance
사업개시일 has 1032 (69.2%) missing valuesMissing
공사준공예정일 has 950 (63.7%) missing valuesMissing
발전소(설치장소) 지번주소 has 21 (1.4%) missing valuesMissing
발전소(설치장소) 도로명주소 has 1472 (98.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:16:09.323798
Analysis finished2024-01-09 20:16:10.776494
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean746
Minimum1
Maximum1491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.2 KiB
2024-01-10T05:16:10.833717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile75.5
Q1373.5
median746
Q31118.5
95-th percentile1416.5
Maximum1491
Range1490
Interquartile range (IQR)745

Descriptive statistics

Standard deviation430.55894
Coefficient of variation (CV)0.57715675
Kurtosis-1.2
Mean746
Median Absolute Deviation (MAD)373
Skewness0
Sum1112286
Variance185381
MonotonicityStrictly increasing
2024-01-10T05:16:10.957180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
993 1
 
0.1%
1002 1
 
0.1%
1001 1
 
0.1%
1000 1
 
0.1%
999 1
 
0.1%
998 1
 
0.1%
997 1
 
0.1%
996 1
 
0.1%
995 1
 
0.1%
Other values (1481) 1481
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1491 1
0.1%
1490 1
0.1%
1489 1
0.1%
1488 1
0.1%
1487 1
0.1%
1486 1
0.1%
1485 1
0.1%
1484 1
0.1%
1483 1
0.1%
1482 1
0.1%

허가일자
Date

Distinct356
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
Minimum2014-01-16 00:00:00
Maximum2020-04-02 00:00:00
2024-01-10T05:16:11.101307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:11.226625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시일
Date

MISSING 

Distinct171
Distinct (%)37.3%
Missing1032
Missing (%)69.2%
Memory size11.8 KiB
Minimum2014-05-12 00:00:00
Maximum2020-02-07 00:00:00
2024-01-10T05:16:11.352690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:11.477604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

공사준공예정일
Date

MISSING 

Distinct201
Distinct (%)37.2%
Missing950
Missing (%)63.7%
Memory size11.8 KiB
Minimum2014-04-03 00:00:00
Maximum2020-04-03 00:00:00
2024-01-10T05:16:11.611066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:11.768291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발전소명(법인명)
Text

Distinct1426
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-01-10T05:16:12.057747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length4.2508384
Min length1

Characters and Unicode

Total characters6338
Distinct characters416
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1376 ?
Unique (%)92.3%

Sample

1st row만수
2nd row대명1호
3rd row대명2호
4th row상황
5th row하늘1호
ValueCountFrequency (%)
발전소 19
 
1.2%
가곡 7
 
0.4%
희망 7
 
0.4%
행복 6
 
0.4%
반학 6
 
0.4%
드림 6
 
0.4%
태양광 6
 
0.4%
세탑 5
 
0.3%
제2 5
 
0.3%
부여 5
 
0.3%
Other values (1419) 1486
95.4%
2024-01-10T05:16:12.482239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 463
 
7.3%
지 279
 
4.4%
1 269
 
4.2%
2 230
 
3.6%
에 210
 
3.3%
너 181
 
2.9%
171
 
2.7%
산 168
 
2.7%
사 154
 
2.4%
리 138
 
2.2%
Other values (406) 4075
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5019
79.2%
Decimal Number 988
 
15.6%
Space Separator 171
 
2.7%
Uppercase Letter 63
 
1.0%
Connector Punctuation 46
 
0.7%
Lowercase Letter 30
 
0.5%
Other Symbol 8
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 463
 
9.2%
지 279
 
5.6%
에 210
 
4.2%
너 181
 
3.6%
산 168
 
3.3%
사 154
 
3.1%
리 138
 
2.7%
소 76
 
1.5%
수 72
 
1.4%
성 69
 
1.4%
Other values (350) 3209
63.9%
Uppercase Letter
ValueCountFrequency (%)
S 12
19.0%
K 8
12.7%
J 6
 
9.5%
Y 5
 
7.9%
H 4
 
6.3%
M 3
 
4.8%
T 3
 
4.8%
P 2
 
3.2%
V 2
 
3.2%
W 2
 
3.2%
Other values (12) 16
25.4%
Lowercase Letter
ValueCountFrequency (%)
r 3
10.0%
k 3
10.0%
e 3
10.0%
n 3
10.0%
o 2
 
6.7%
i 2
 
6.7%
j 2
 
6.7%
t 2
 
6.7%
s 2
 
6.7%
g 1
 
3.3%
Other values (7) 7
23.3%
Decimal Number
ValueCountFrequency (%)
1 269
27.2%
2 230
23.3%
3 131
13.3%
4 75
 
7.6%
5 61
 
6.2%
6 54
 
5.5%
7 49
 
5.0%
8 44
 
4.5%
0 39
 
3.9%
9 36
 
3.6%
Space Separator
ValueCountFrequency (%)
171
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 46
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5027
79.3%
Common 1218
 
19.2%
Latin 93
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 463
 
9.2%
지 279
 
5.6%
에 210
 
4.2%
너 181
 
3.6%
산 168
 
3.3%
사 154
 
3.1%
리 138
 
2.7%
소 76
 
1.5%
수 72
 
1.4%
성 69
 
1.4%
Other values (351) 3217
64.0%
Latin
ValueCountFrequency (%)
S 12
 
12.9%
K 8
 
8.6%
J 6
 
6.5%
Y 5
 
5.4%
H 4
 
4.3%
r 3
 
3.2%
M 3
 
3.2%
T 3
 
3.2%
k 3
 
3.2%
e 3
 
3.2%
Other values (29) 43
46.2%
Common
ValueCountFrequency (%)
1 269
22.1%
2 230
18.9%
171
14.0%
3 131
10.8%
4 75
 
6.2%
5 61
 
5.0%
6 54
 
4.4%
7 49
 
4.0%
_ 46
 
3.8%
8 44
 
3.6%
Other values (6) 88
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5019
79.2%
ASCII 1311
 
20.7%
None 8
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 463
 
9.2%
지 279
 
5.6%
에 210
 
4.2%
너 181
 
3.6%
산 168
 
3.3%
사 154
 
3.1%
리 138
 
2.7%
소 76
 
1.5%
수 72
 
1.4%
성 69
 
1.4%
Other values (350) 3209
63.9%
ASCII
ValueCountFrequency (%)
1 269
20.5%
2 230
17.5%
171
13.0%
3 131
10.0%
4 75
 
5.7%
5 61
 
4.7%
6 54
 
4.1%
7 49
 
3.7%
_ 46
 
3.5%
8 44
 
3.4%
Other values (45) 181
13.8%
None
ValueCountFrequency (%)
㈜ 8
100.0%

발전소(설치장소) 지번주소
Text

MISSING 

Distinct802
Distinct (%)54.6%
Missing21
Missing (%)1.4%
Memory size11.8 KiB
2024-01-10T05:16:12.783457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length68
Mean length24.77483
Min length18

Characters and Unicode

Total characters36419
Distinct characters141
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique613 ?
Unique (%)41.7%

Sample

1st row충청남도 부여군 외산면 만수리 55-7외 6필지
2nd row충청남도 부여군 규암면 노화리 348, 348-1, 349, 349-1, 349-2, 350-8
3rd row충청남도 부여군 규암면 노화리 347-2외 1필지
4th row충청남도 부여군 장암면 상황리 산28
5th row충청남도 부여군 임천면 만사리 651-9
ValueCountFrequency (%)
충청남도 1470
 
18.5%
부여군 1470
 
18.5%
세도면 364
 
4.6%
사산리 195
 
2.4%
임천면 175
 
2.2%
초촌면 140
 
1.8%
석성면 127
 
1.6%
충화면 113
 
1.4%
양화면 74
 
0.9%
봉정리 65
 
0.8%
Other values (1080) 3771
47.4%
2024-01-10T05:16:13.189396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6940
19.1%
도 1856
 
5.1%
충 1584
 
4.3%
1 1507
 
4.1%
청 1504
 
4.1%
부 1502
 
4.1%
여 1496
 
4.1%
남 1489
 
4.1%
리 1482
 
4.1%
군 1473
 
4.0%
Other values (131) 15586
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20006
54.9%
Decimal Number 7232
 
19.9%
Space Separator 6940
 
19.1%
Dash Punctuation 1454
 
4.0%
Other Punctuation 699
 
1.9%
Close Punctuation 44
 
0.1%
Open Punctuation 44
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1856
 
9.3%
충 1584
 
7.9%
청 1504
 
7.5%
부 1502
 
7.5%
여 1496
 
7.5%
남 1489
 
7.4%
리 1482
 
7.4%
군 1473
 
7.4%
면 1445
 
7.2%
산 1297
 
6.5%
Other values (115) 4878
24.4%
Decimal Number
ValueCountFrequency (%)
1 1507
20.8%
3 958
13.2%
4 957
13.2%
2 818
11.3%
5 679
9.4%
6 620
8.6%
8 536
 
7.4%
7 401
 
5.5%
0 396
 
5.5%
9 360
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 698
99.9%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
6940
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1454
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20006
54.9%
Common 16413
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1856
 
9.3%
충 1584
 
7.9%
청 1504
 
7.5%
부 1502
 
7.5%
여 1496
 
7.5%
남 1489
 
7.4%
리 1482
 
7.4%
군 1473
 
7.4%
면 1445
 
7.2%
산 1297
 
6.5%
Other values (115) 4878
24.4%
Common
ValueCountFrequency (%)
6940
42.3%
1 1507
 
9.2%
- 1454
 
8.9%
3 958
 
5.8%
4 957
 
5.8%
2 818
 
5.0%
, 698
 
4.3%
5 679
 
4.1%
6 620
 
3.8%
8 536
 
3.3%
Other values (6) 1246
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20006
54.9%
ASCII 16413
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6940
42.3%
1 1507
 
9.2%
- 1454
 
8.9%
3 958
 
5.8%
4 957
 
5.8%
2 818
 
5.0%
, 698
 
4.3%
5 679
 
4.1%
6 620
 
3.8%
8 536
 
3.3%
Other values (6) 1246
 
7.6%
Hangul
ValueCountFrequency (%)
도 1856
 
9.3%
충 1584
 
7.9%
청 1504
 
7.5%
부 1502
 
7.5%
여 1496
 
7.5%
남 1489
 
7.4%
리 1482
 
7.4%
군 1473
 
7.4%
면 1445
 
7.2%
산 1297
 
6.5%
Other values (115) 4878
24.4%

발전소(설치장소) 도로명주소
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing1472
Missing (%)98.7%
Memory size11.8 KiB
2024-01-10T05:16:13.372782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length20.947368
Min length19

Characters and Unicode

Total characters398
Distinct characters59
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st row충청남도 부여군 규암면 왕흥로 88
2nd row충청남도 부여군 양화면 상시로 51
3rd row충청남도 부여군 규암면 자온로 68
4th row충청남도 부여군 구룡면 흥수로 180
5th row충청남도 부여군 세도면 부흥로543번길 10-26
ValueCountFrequency (%)
충청남도 19
19.8%
부여군 19
19.8%
규암면 4
 
4.2%
남면 3
 
3.1%
남성로 2
 
2.1%
772 2
 
2.1%
초촌면 2
 
2.1%
옥산면 2
 
2.1%
부여읍 2
 
2.1%
응신길 1
 
1.0%
Other values (40) 40
41.7%
2024-01-10T05:16:13.676041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
19.3%
남 28
 
7.0%
부 22
 
5.5%
여 21
 
5.3%
도 20
 
5.0%
충 19
 
4.8%
청 19
 
4.8%
군 19
 
4.8%
로 18
 
4.5%
면 17
 
4.3%
Other values (49) 138
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
64.1%
Space Separator 77
 
19.3%
Decimal Number 62
 
15.6%
Dash Punctuation 3
 
0.8%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 28
11.0%
부 22
 
8.6%
여 21
 
8.2%
도 20
 
7.8%
충 19
 
7.5%
청 19
 
7.5%
군 19
 
7.5%
로 18
 
7.1%
면 17
 
6.7%
길 6
 
2.4%
Other values (36) 66
25.9%
Decimal Number
ValueCountFrequency (%)
1 11
17.7%
2 8
12.9%
7 7
11.3%
5 7
11.3%
4 6
9.7%
8 6
9.7%
6 5
8.1%
0 5
8.1%
9 4
 
6.5%
3 3
 
4.8%
Space Separator
ValueCountFrequency (%)
77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
64.1%
Common 143
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 28
11.0%
부 22
 
8.6%
여 21
 
8.2%
도 20
 
7.8%
충 19
 
7.5%
청 19
 
7.5%
군 19
 
7.5%
로 18
 
7.1%
면 17
 
6.7%
길 6
 
2.4%
Other values (36) 66
25.9%
Common
ValueCountFrequency (%)
77
53.8%
1 11
 
7.7%
2 8
 
5.6%
7 7
 
4.9%
5 7
 
4.9%
4 6
 
4.2%
8 6
 
4.2%
6 5
 
3.5%
0 5
 
3.5%
9 4
 
2.8%
Other values (3) 7
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
64.1%
ASCII 143
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
53.8%
1 11
 
7.7%
2 8
 
5.6%
7 7
 
4.9%
5 7
 
4.9%
4 6
 
4.2%
8 6
 
4.2%
6 5
 
3.5%
0 5
 
3.5%
9 4
 
2.8%
Other values (3) 7
 
4.9%
Hangul
ValueCountFrequency (%)
남 28
11.0%
부 22
 
8.6%
여 21
 
8.2%
도 20
 
7.8%
충 19
 
7.5%
청 19
 
7.5%
군 19
 
7.5%
로 18
 
7.1%
면 17
 
6.7%
길 6
 
2.4%
Other values (36) 66
25.9%

설치위치
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
토지
1270 
건축물
212 
수상
 
5
토지+건물
 
4

Length

Max length5
Median length2
Mean length2.1502347
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row토지
2nd row토지
3rd row건축물
4th row토지
5th row토지

Common Values

ValueCountFrequency (%)
토지 1270
85.2%
건축물 212
 
14.2%
수상 5
 
0.3%
토지+건물 4
 
0.3%

Length

2024-01-10T05:16:13.831605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:16:13.958254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토지 1270
85.2%
건축물 212
 
14.2%
수상 5
 
0.3%
토지+건물 4
 
0.3%

설비용량(kW)
Real number (ℝ)

Distinct285
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.221
Minimum9.6
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.2 KiB
2024-01-10T05:16:14.078710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.6
5-th percentile53.97
Q198.55
median99
Q399.72
95-th percentile496.8
Maximum500
Range490.4
Interquartile range (IQR)1.17

Descriptive statistics

Standard deviation131.77956
Coefficient of variation (CV)0.86571209
Kurtosis2.1631102
Mean152.221
Median Absolute Deviation (MAD)0.645
Skewness1.9314376
Sum226961.51
Variance17365.853
MonotonicityNot monotonic
2024-01-10T05:16:14.196293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 347
23.3%
99.4 97
 
6.5%
97.2 95
 
6.4%
98.55 55
 
3.7%
99.72 45
 
3.0%
99.2 40
 
2.7%
99.36 37
 
2.5%
99.28 36
 
2.4%
97.92 34
 
2.3%
99.84 31
 
2.1%
Other values (275) 674
45.2%
ValueCountFrequency (%)
9.6 1
0.1%
12.0 1
0.1%
12.48 1
0.1%
14.85 1
0.1%
15.21 1
0.1%
17.94 1
0.1%
18.0 2
0.1%
18.225 1
0.1%
18.72 2
0.1%
19.2 2
0.1%
ValueCountFrequency (%)
500.0 2
 
0.1%
499.8 14
0.9%
499.68 2
 
0.1%
499.62 3
 
0.2%
499.5 1
 
0.1%
499.38 2
 
0.1%
499.32 1
 
0.1%
499.2 10
 
0.7%
498.96 27
1.8%
498.6 3
 
0.2%

공급전압
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
380
1490 
220
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row380
2nd row380
3rd row380
4th row380
5th row380

Common Values

ValueCountFrequency (%)
380 1490
99.9%
220 1
 
0.1%

Length

2024-01-10T05:16:14.308728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:16:14.412718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
380 1490
99.9%
220 1
 
0.1%

주파수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
60
1491 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row60
2nd row60
3rd row60
4th row60
5th row60

Common Values

ValueCountFrequency (%)
60 1491
100.0%

Length

2024-01-10T05:16:14.529861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:16:14.629060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 1491
100.0%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct47
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
임야
628 
답
344 
임야, 전
188 
전
80 
임야, 답
 
53
Other values (42)
198 

Length

Max length13
Median length12
Mean length2.5110664
Min length1

Unique

Unique19 ?
Unique (%)1.3%

Sample

1st row임야, 전
2nd row임야, 전
3rd row대지
4th row임야, 전
5th row임야, 전

Common Values

ValueCountFrequency (%)
임야 628
42.1%
답 344
23.1%
임야, 전 188
 
12.6%
전 80
 
5.4%
임야, 답 53
 
3.6%
<NA> 34
 
2.3%
대지 17
 
1.1%
목장용지 14
 
0.9%
전, 임야 14
 
0.9%
공장용지 12
 
0.8%
Other values (37) 107
 
7.2%

Length

2024-01-10T05:16:14.727027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
임야 908
49.6%
답 444
24.2%
전 324
 
17.7%
na 34
 
1.9%
목장용지 21
 
1.1%
대지 19
 
1.0%
대 17
 
0.9%
잡종지 16
 
0.9%
공장용지 12
 
0.7%
창고용지 9
 
0.5%
Other values (16) 27
 
1.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2021-09-24
1491 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-24
2nd row2021-09-24
3rd row2021-09-24
4th row2021-09-24
5th row2021-09-24

Common Values

ValueCountFrequency (%)
2021-09-24 1491
100.0%

Length

2024-01-10T05:16:14.834683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:16:14.928597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-24 1491
100.0%

Interactions

2024-01-10T05:16:10.026505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:09.875651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:10.101507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:16:09.954847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:16:14.988645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발전소(설치장소) 도로명주소설치위치설비용량(kW)공급전압지목
연번1.0001.0000.4190.2920.0040.710
발전소(설치장소) 도로명주소1.0001.0001.0001.000NaN1.000
설치위치0.4191.0001.0000.3800.0680.814
설비용량(kW)0.2921.0000.3801.0000.1020.653
공급전압0.004NaN0.0680.1021.000NaN
지목0.7101.0000.8140.653NaN1.000
2024-01-10T05:16:15.094414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치지목공급전압
설치위치1.0000.5510.045
지목0.5511.0001.000
공급전압0.0451.0001.000
2024-01-10T05:16:15.183084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)설치위치공급전압지목
연번1.0000.1520.2620.0020.327
설비용량(kW)0.1521.0000.2360.0780.283
설치위치0.2620.2361.0000.0450.551
공급전압0.0020.0780.0451.0001.000
지목0.3270.2830.5511.0001.000

Missing values

2024-01-10T05:16:10.443555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:16:10.589967image/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.
2024-01-10T05:16:10.711463image/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

연번허가일자사업개시일공사준공예정일발전소명(법인명)발전소(설치장소) 지번주소발전소(설치장소) 도로명주소설치위치설비용량(kW)공급전압주파수지목데이터기준일자
012014-03-15<NA><NA>만수충청남도 부여군 외산면 만수리 55-7외 6필지<NA>토지199.038060임야, 전2021-09-24
122014-03-172014-05-122014-04-11대명1호충청남도 부여군 규암면 노화리 348, 348-1, 349, 349-1, 349-2, 350-8<NA>토지99.038060임야, 전2021-09-24
232014-03-172014-05-132014-04-03대명2호충청남도 부여군 규암면 노화리 347-2외 1필지<NA>건축물50.038060대지2021-09-24
342014-03-17<NA><NA>상황충청남도 부여군 장암면 상황리 산28<NA>토지496.838060임야, 전2021-09-24
452014-03-252014-11-172014-10-14하늘1호충청남도 부여군 임천면 만사리 651-9<NA>토지28.038060임야, 전2021-09-24
562015-07-212014-09-152014-07-09석진솔라충청남도 부여군 임천면 만사리 634-3(주1,주2)<NA>건축물95.038060임야, 전2021-09-24
672015-03-162014-11-102014-10-14가온충청남도 부여군 임천면 만사리 651-8<NA>건축물98.038060임야, 전2021-09-24
782014-04-042014-09-042014-08-13안암컨설팅충청남도 부여군 세도면 귀덕리 633(주1,주2,주4)<NA>건축물97.238060임야, 전2021-09-24
892014-03-262014-08-052014-07-24에덴<NA>충청남도 부여군 규암면 왕흥로 88건축물70.038060임야, 전2021-09-24
9102014-03-27<NA><NA>글로리아충청남도 부여군 임천면 비정리 317-3<NA>건축물99.7538060임야, 전2021-09-24
연번허가일자사업개시일공사준공예정일발전소명(법인명)발전소(설치장소) 지번주소발전소(설치장소) 도로명주소설치위치설비용량(kW)공급전압주파수지목데이터기준일자
148114822020-02-21<NA><NA>김가영3호충청남도 부여군 세도면청송리44-8(제3동)<NA>건축물99.638060답2021-09-24
148214832020-02-21<NA><NA>김가영4호충청남도 부여군 세도면청송리44-8(제4동)<NA>건축물99.638060답2021-09-24
148314842020-03-16<NA><NA>사산라충청남도 부여군 세도면사산리662-9<NA>토지97.238060답2021-09-24
148414852020-03-16<NA><NA>한빛누리1호충청남도 부여군 초촌면세탑리679-9<NA>건축물94.538060답2021-09-24
148514862020-03-16<NA><NA>한빛누리2호충청남도 부여군 초촌면세탑리679-9<NA>건축물94.538060답2021-09-24
148614872020-03-16<NA><NA>한빛누리3호충청남도 부여군 초촌면세탑리679-9<NA>건축물28.12538060답2021-09-24
148714882020-03-23<NA><NA>시경충청남도 부여군 옥산면수암리188-2,188-8<NA>건축물79.038060전2021-09-24
148814892020-03-30<NA><NA>에스엠충청남도 부여군 은산면장벌리532-3<NA>건축물364.538060양어장2021-09-24
148914902020-03-30<NA><NA>금강충청남도 부여군 부여읍염창리511-2<NA>건축물49.9538060잡종지2021-09-24
149014912020-04-02<NA><NA>현내4동충청남도 부여군 석성면현내리233(주24동)<NA>건축물99.938060답2021-09-24