Overview

Dataset statistics

Number of variables13
Number of observations1599
Missing cells1289
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.3 KiB
Average record size in memory109.1 B

Variable types

Numeric3
Text6
Categorical3
DateTime1

Dataset

Description충청남도 금산군 태양광 발전소 설치현황(발전소명, 설비용량, 주소, 최초허가일, 사업개시일) 관련하여 자료를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=385&beforeMenuCd=DOM_000000201001001000&publicdatapk=15033866

Alerts

데이터기준일 has constant value ""Constant
사업상태 is highly overall correlated with 공급전압 and 1 other fieldsHigh correlation
주파수 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
공급전압 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
연번 is highly overall correlated with 공급전압 and 1 other fieldsHigh correlation
설비용량 is highly overall correlated with 공급전압 and 1 other fieldsHigh correlation
설치면적 is highly overall correlated with 공급전압 and 1 other fieldsHigh correlation
공급전압 is highly imbalanced (89.5%)Imbalance
주파수 is highly imbalanced (89.5%)Imbalance
사업상태 is highly imbalanced (84.8%)Imbalance
사업개시일 has 1231 (77.0%) missing valuesMissing
설치면적 has 29 (1.8%) missing valuesMissing
지목 has 29 (1.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:11:31.003788
Analysis finished2024-01-09 21:11:32.852950
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1599
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean800
Minimum1
Maximum1599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-01-10T06:11:32.918329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile80.9
Q1400.5
median800
Q31199.5
95-th percentile1519.1
Maximum1599
Range1598
Interquartile range (IQR)799

Descriptive statistics

Standard deviation461.73586
Coefficient of variation (CV)0.57716982
Kurtosis-1.2
Mean800
Median Absolute Deviation (MAD)400
Skewness0
Sum1279200
Variance213200
MonotonicityStrictly increasing
2024-01-10T06:11:33.048836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1064 1
 
0.1%
1074 1
 
0.1%
1073 1
 
0.1%
1072 1
 
0.1%
1071 1
 
0.1%
1070 1
 
0.1%
1069 1
 
0.1%
1068 1
 
0.1%
1067 1
 
0.1%
Other values (1589) 1589
99.4%
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 (%)
1599 1
0.1%
1598 1
0.1%
1597 1
0.1%
1596 1
0.1%
1595 1
0.1%
1594 1
0.1%
1593 1
0.1%
1592 1
0.1%
1591 1
0.1%
1590 1
0.1%

발전소명
Text

Distinct1558
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-01-10T06:11:33.268297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length10.051282
Min length1

Characters and Unicode

Total characters16072
Distinct characters397
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

Unique1519 ?
Unique (%)95.0%

Sample

1st row방우리소수력
2nd row 금성
3rd row 두리
4th row 영솔라
5th row ㈜서울전업공사
ValueCountFrequency (%)
태양광발전소 941
34.3%
태양광 39
 
1.4%
외부리 19
 
0.7%
마장리 16
 
0.6%
1호 14
 
0.5%
2호 13
 
0.5%
금산 12
 
0.4%
3호 11
 
0.4%
진산태양광발전소 10
 
0.4%
제원 8
 
0.3%
Other values (1503) 1663
60.6%
2024-01-10T06:11:33.587383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1893
 
11.8%
태 1283
 
8.0%
양 1278
 
8.0%
광 1263
 
7.9%
소 1223
 
7.6%
전 1214
 
7.6%
발 1203
 
7.5%
호 751
 
4.7%
1 373
 
2.3%
2 265
 
1.6%
Other values (387) 5326
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12630
78.6%
Space Separator 1893
 
11.8%
Decimal Number 1295
 
8.1%
Uppercase Letter 104
 
0.6%
Dash Punctuation 91
 
0.6%
Other Symbol 33
 
0.2%
Open Punctuation 8
 
< 0.1%
Close Punctuation 8
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
태 1283
 
10.2%
양 1278
 
10.1%
광 1263
 
10.0%
소 1223
 
9.7%
전 1214
 
9.6%
발 1203
 
9.5%
호 751
 
5.9%
리 240
 
1.9%
금 183
 
1.4%
에 180
 
1.4%
Other values (343) 3812
30.2%
Uppercase Letter
ValueCountFrequency (%)
S 30
28.8%
J 10
 
9.6%
N 9
 
8.7%
B 9
 
8.7%
C 8
 
7.7%
P 4
 
3.8%
G 4
 
3.8%
H 3
 
2.9%
E 3
 
2.9%
A 3
 
2.9%
Other values (11) 21
20.2%
Decimal Number
ValueCountFrequency (%)
1 373
28.8%
2 265
20.5%
3 162
12.5%
4 107
 
8.3%
5 93
 
7.2%
0 74
 
5.7%
6 73
 
5.6%
7 57
 
4.4%
8 49
 
3.8%
9 42
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
o 1
25.0%
a 1
25.0%
h 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 1
25.0%
# 1
25.0%
Space Separator
ValueCountFrequency (%)
1893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Math Symbol
ValueCountFrequency (%)
> 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12663
78.8%
Common 3301
 
20.5%
Latin 108
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
태 1283
 
10.1%
양 1278
 
10.1%
광 1263
 
10.0%
소 1223
 
9.7%
전 1214
 
9.6%
발 1203
 
9.5%
호 751
 
5.9%
리 240
 
1.9%
금 183
 
1.4%
에 180
 
1.4%
Other values (344) 3845
30.4%
Latin
ValueCountFrequency (%)
S 30
27.8%
J 10
 
9.3%
N 9
 
8.3%
B 9
 
8.3%
C 8
 
7.4%
P 4
 
3.7%
G 4
 
3.7%
H 3
 
2.8%
E 3
 
2.8%
A 3
 
2.8%
Other values (15) 25
23.1%
Common
ValueCountFrequency (%)
1893
57.3%
1 373
 
11.3%
2 265
 
8.0%
3 162
 
4.9%
4 107
 
3.2%
5 93
 
2.8%
- 91
 
2.8%
0 74
 
2.2%
6 73
 
2.2%
7 57
 
1.7%
Other values (8) 113
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12630
78.6%
ASCII 3409
 
21.2%
None 33
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1893
55.5%
1 373
 
10.9%
2 265
 
7.8%
3 162
 
4.8%
4 107
 
3.1%
5 93
 
2.7%
- 91
 
2.7%
0 74
 
2.2%
6 73
 
2.1%
7 57
 
1.7%
Other values (33) 221
 
6.5%
Hangul
ValueCountFrequency (%)
태 1283
 
10.2%
양 1278
 
10.1%
광 1263
 
10.0%
소 1223
 
9.7%
전 1214
 
9.6%
발 1203
 
9.5%
호 751
 
5.9%
리 240
 
1.9%
금 183
 
1.4%
에 180
 
1.4%
Other values (343) 3812
30.2%
None
ValueCountFrequency (%)
㈜ 33
100.0%

발전소주소
Text

Distinct808
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-01-10T06:11:33.862294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length20.639775
Min length7

Characters and Unicode

Total characters33003
Distinct characters147
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique602 ?
Unique (%)37.6%

Sample

1st row 금산군 부리면 방우리 산3-2
2nd row 금산군 금성면 상가리 산67-1
3rd row 금산군 부리면 창평리 280-1
4th row 금산군 부리면 창평리 280-3
5th row 금산군 추부면 신평리 1000
ValueCountFrequency (%)
금산군 1172
 
17.4%
제원면 267
 
4.0%
부리면 210
 
3.1%
금성면 196
 
2.9%
남이면 180
 
2.7%
진산면 180
 
2.7%
남일면 150
 
2.2%
군북면 140
 
2.1%
복수면 125
 
1.9%
도곡리 111
 
1.6%
Other values (1035) 4011
59.5%
2024-01-10T06:11:34.624820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7927
24.0%
산 2083
 
6.3%
리 1802
 
5.5%
- 1560
 
4.7%
1 1539
 
4.7%
금 1537
 
4.7%
면 1501
 
4.5%
군 1315
 
4.0%
2 1305
 
4.0%
3 1100
 
3.3%
Other values (137) 11334
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13922
42.2%
Decimal Number 8475
25.7%
Space Separator 7927
24.0%
Dash Punctuation 1560
 
4.7%
Other Punctuation 910
 
2.8%
Close Punctuation 104
 
0.3%
Open Punctuation 104
 
0.3%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2083
15.0%
리 1802
12.9%
금 1537
 
11.0%
면 1501
 
10.8%
군 1315
 
9.4%
원 407
 
2.9%
남 337
 
2.4%
부 333
 
2.4%
제 314
 
2.3%
곡 300
 
2.2%
Other values (117) 3993
28.7%
Decimal Number
ValueCountFrequency (%)
1 1539
18.2%
2 1305
15.4%
3 1100
13.0%
4 1009
11.9%
6 703
8.3%
5 662
7.8%
9 554
 
6.5%
7 549
 
6.5%
0 546
 
6.4%
8 508
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 884
97.1%
/ 23
 
2.5%
. 3
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 102
98.1%
] 2
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 102
98.1%
[ 2
 
1.9%
Space Separator
ValueCountFrequency (%)
7927
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1560
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19081
57.8%
Hangul 13922
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2083
15.0%
리 1802
12.9%
금 1537
 
11.0%
면 1501
 
10.8%
군 1315
 
9.4%
원 407
 
2.9%
남 337
 
2.4%
부 333
 
2.4%
제 314
 
2.3%
곡 300
 
2.2%
Other values (117) 3993
28.7%
Common
ValueCountFrequency (%)
7927
41.5%
- 1560
 
8.2%
1 1539
 
8.1%
2 1305
 
6.8%
3 1100
 
5.8%
4 1009
 
5.3%
, 884
 
4.6%
6 703
 
3.7%
5 662
 
3.5%
9 554
 
2.9%
Other values (10) 1838
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19081
57.8%
Hangul 13922
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7927
41.5%
- 1560
 
8.2%
1 1539
 
8.1%
2 1305
 
6.8%
3 1100
 
5.8%
4 1009
 
5.3%
, 884
 
4.6%
6 703
 
3.7%
5 662
 
3.5%
9 554
 
2.9%
Other values (10) 1838
 
9.6%
Hangul
ValueCountFrequency (%)
산 2083
15.0%
리 1802
12.9%
금 1537
 
11.0%
면 1501
 
10.8%
군 1315
 
9.4%
원 407
 
2.9%
남 337
 
2.4%
부 333
 
2.4%
제 314
 
2.3%
곡 300
 
2.2%
Other values (117) 3993
28.7%

최초허가일
Text

Distinct374
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-01-10T06:11:34.906246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters15990
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)8.9%

Sample

1st row1986-08-05
2nd row2007-02-02
3rd row2009-08-14
4th row2009-08-14
5th row2009-12-28
ValueCountFrequency (%)
2018-05-15 57
 
3.6%
2016-01-29 48
 
3.0%
2018-09-11 39
 
2.4%
2020-06-30 37
 
2.3%
2018-01-23 35
 
2.2%
2017-09-07 33
 
2.1%
2020-09-29 28
 
1.8%
2018-09-19 28
 
1.8%
2018-06-12 25
 
1.6%
2018-06-28 22
 
1.4%
Other values (364) 1247
78.0%
2024-01-10T06:11:35.301711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3767
23.6%
- 3197
20.0%
2 2817
17.6%
1 2748
17.2%
8 827
 
5.2%
9 698
 
4.4%
7 532
 
3.3%
6 467
 
2.9%
5 345
 
2.2%
3 329
 
2.1%
Other values (2) 263
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12792
80.0%
Dash Punctuation 3197
 
20.0%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3767
29.4%
2 2817
22.0%
1 2748
21.5%
8 827
 
6.5%
9 698
 
5.5%
7 532
 
4.2%
6 467
 
3.7%
5 345
 
2.7%
3 329
 
2.6%
4 262
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 3197
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3767
23.6%
- 3197
20.0%
2 2817
17.6%
1 2748
17.2%
8 827
 
5.2%
9 698
 
4.4%
7 532
 
3.3%
6 467
 
2.9%
5 345
 
2.2%
3 329
 
2.1%
Other values (2) 263
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3767
23.6%
- 3197
20.0%
2 2817
17.6%
1 2748
17.2%
8 827
 
5.2%
9 698
 
4.4%
7 532
 
3.3%
6 467
 
2.9%
5 345
 
2.2%
3 329
 
2.1%
Other values (2) 263
 
1.6%

사업개시일
Text

MISSING 

Distinct181
Distinct (%)49.2%
Missing1231
Missing (%)77.0%
Memory size12.6 KiB
2024-01-10T06:11:35.634890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9755435
Min length1

Characters and Unicode

Total characters3671
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)34.2%

Sample

1st row1986-08-05
2nd row2010-01-06
3rd row2010-06-11
4th row2010-06-11
5th row2011-11-25
ValueCountFrequency (%)
2015-03-16 19
 
5.2%
2018-11-28 18
 
4.9%
2018-10-30 16
 
4.4%
2018-05-09 15
 
4.1%
2017-09-21 14
 
3.8%
2018-02-07 9
 
2.5%
2018-11-14 8
 
2.2%
2018-11-02 7
 
1.9%
2018-09-10 7
 
1.9%
2017-03-06 7
 
1.9%
Other values (170) 247
67.3%
2024-01-10T06:11:36.049966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 808
22.0%
- 734
20.0%
1 723
19.7%
2 568
15.5%
8 224
 
6.1%
9 150
 
4.1%
6 115
 
3.1%
3 104
 
2.8%
5 93
 
2.5%
7 93
 
2.5%
Other values (2) 59
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2936
80.0%
Dash Punctuation 734
 
20.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 808
27.5%
1 723
24.6%
2 568
19.3%
8 224
 
7.6%
9 150
 
5.1%
6 115
 
3.9%
3 104
 
3.5%
5 93
 
3.2%
7 93
 
3.2%
4 58
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 734
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 808
22.0%
- 734
20.0%
1 723
19.7%
2 568
15.5%
8 224
 
6.1%
9 150
 
4.1%
6 115
 
3.1%
3 104
 
2.8%
5 93
 
2.5%
7 93
 
2.5%
Other values (2) 59
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 808
22.0%
- 734
20.0%
1 723
19.7%
2 568
15.5%
8 224
 
6.1%
9 150
 
4.1%
6 115
 
3.1%
3 104
 
2.8%
5 93
 
2.5%
7 93
 
2.5%
Other values (2) 59
 
1.6%

설치위치
Text

Distinct820
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-01-10T06:11:36.358937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length17.751094
Min length6

Characters and Unicode

Total characters28384
Distinct characters145
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

Unique615 ?
Unique (%)38.5%

Sample

1st row 금산군 부리면 방우리 산3-2
2nd row 금산군 금성면 상가리 산67-1
3rd row 금산군 부리면 창평리 280-1
4th row 금산군 부리면 창평리 280-3
5th row 금산군 추부면 신평리 1000
ValueCountFrequency (%)
부리면 206
 
3.8%
제원면 187
 
3.4%
금성면 180
 
3.3%
남이면 165
 
3.0%
진산면 154
 
2.8%
남일면 129
 
2.4%
군북면 117
 
2.1%
복수면 116
 
2.1%
도곡리 111
 
2.0%
금산군 94
 
1.7%
Other values (1054) 4028
73.4%
2024-01-10T06:11:36.830539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6963
24.5%
리 1812
 
6.4%
1 1585
 
5.6%
- 1583
 
5.6%
2 1326
 
4.7%
면 1291
 
4.5%
3 1113
 
3.9%
4 1011
 
3.6%
산 987
 
3.5%
, 913
 
3.2%
Other values (135) 9800
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10122
35.7%
Decimal Number 8569
30.2%
Space Separator 6963
24.5%
Dash Punctuation 1583
 
5.6%
Other Punctuation 939
 
3.3%
Open Punctuation 104
 
0.4%
Close Punctuation 104
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1812
17.9%
면 1291
 
12.8%
산 987
 
9.8%
금 449
 
4.4%
원 326
 
3.2%
부 317
 
3.1%
곡 300
 
3.0%
남 300
 
3.0%
제 233
 
2.3%
군 214
 
2.1%
Other values (116) 3893
38.5%
Decimal Number
ValueCountFrequency (%)
1 1585
18.5%
2 1326
15.5%
3 1113
13.0%
4 1011
11.8%
6 704
8.2%
5 667
7.8%
9 556
 
6.5%
7 550
 
6.4%
0 546
 
6.4%
8 511
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 913
97.2%
/ 23
 
2.4%
. 3
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 102
98.1%
[ 2
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 102
98.1%
] 2
 
1.9%
Space Separator
ValueCountFrequency (%)
6963
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1583
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18262
64.3%
Hangul 10122
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1812
17.9%
면 1291
 
12.8%
산 987
 
9.8%
금 449
 
4.4%
원 326
 
3.2%
부 317
 
3.1%
곡 300
 
3.0%
남 300
 
3.0%
제 233
 
2.3%
군 214
 
2.1%
Other values (116) 3893
38.5%
Common
ValueCountFrequency (%)
6963
38.1%
1 1585
 
8.7%
- 1583
 
8.7%
2 1326
 
7.3%
3 1113
 
6.1%
4 1011
 
5.5%
, 913
 
5.0%
6 704
 
3.9%
5 667
 
3.7%
9 556
 
3.0%
Other values (9) 1841
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18262
64.3%
Hangul 10122
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6963
38.1%
1 1585
 
8.7%
- 1583
 
8.7%
2 1326
 
7.3%
3 1113
 
6.1%
4 1011
 
5.5%
, 913
 
5.0%
6 704
 
3.9%
5 667
 
3.7%
9 556
 
3.0%
Other values (9) 1841
 
10.1%
Hangul
ValueCountFrequency (%)
리 1812
17.9%
면 1291
 
12.8%
산 987
 
9.8%
금 449
 
4.4%
원 326
 
3.2%
부 317
 
3.1%
곡 300
 
3.0%
남 300
 
3.0%
제 233
 
2.3%
군 214
 
2.1%
Other values (116) 3893
38.5%

설비용량
Real number (ℝ)

HIGH CORRELATION 

Distinct347
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean174.87266
Minimum9
Maximum2994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-01-10T06:11:37.005949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile38.4735
Q197.92
median99
Q399.6
95-th percentile499.384
Maximum2994
Range2985
Interquartile range (IQR)1.68

Descriptive statistics

Standard deviation277.59037
Coefficient of variation (CV)1.5873858
Kurtosis34.590502
Mean174.87266
Median Absolute Deviation (MAD)0.96
Skewness5.2018431
Sum279621.38
Variance77056.416
MonotonicityNot monotonic
2024-01-10T06:11:37.178599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 177
 
11.1%
97.92 133
 
8.3%
98.28 109
 
6.8%
99.2 94
 
5.9%
99.4 79
 
4.9%
97.2 75
 
4.7%
99.75 51
 
3.2%
99.96 34
 
2.1%
98.0 30
 
1.9%
99.18 29
 
1.8%
Other values (337) 788
49.3%
ValueCountFrequency (%)
9.0 1
0.1%
9.92 1
0.1%
11.04 1
0.1%
14.625 1
0.1%
14.74 1
0.1%
14.8 1
0.1%
18.0 1
0.1%
18.36 1
0.1%
18.675 1
0.1%
18.75 1
0.1%
ValueCountFrequency (%)
2994.0 2
0.1%
2800.0 1
 
0.1%
2520.0 1
 
0.1%
2120.0 1
 
0.1%
2034.72 2
0.1%
2000.0 1
 
0.1%
1997.64 4
0.3%
1989.0 1
 
0.1%
1980.0 1
 
0.1%
1756.08 1
 
0.1%

공급전압
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
380
1577 
<NA>
 
22

Length

Max length4
Median length3
Mean length3.0137586
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
380 1577
98.6%
<NA> 22
 
1.4%

Length

2024-01-10T06:11:37.338064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:11:37.432432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
380 1577
98.6%
na 22
 
1.4%

주파수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
60
1577 
<NA>
 
22

Length

Max length4
Median length2
Mean length2.0275172
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 (%)
60 1577
98.6%
<NA> 22
 
1.4%

Length

2024-01-10T06:11:37.556085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:11:37.657583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 1577
98.6%
na 22
 
1.4%

설치면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct859
Distinct (%)54.7%
Missing29
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean2156.4962
Minimum80
Maximum64470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-01-10T06:11:37.803777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile291.45
Q1598
median1200
Q31666.75
95-th percentile9230.55
Maximum64470
Range64390
Interquartile range (IQR)1068.75

Descriptive statistics

Standard deviation3955.2032
Coefficient of variation (CV)1.8340877
Kurtosis58.984882
Mean2156.4962
Median Absolute Deviation (MAD)602
Skewness6.1058378
Sum3385699
Variance15643632
MonotonicityNot monotonic
2024-01-10T06:11:38.000474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
598 64
 
4.0%
560 52
 
3.3%
498 34
 
2.1%
1322 25
 
1.6%
568 23
 
1.4%
605 19
 
1.2%
1320 18
 
1.1%
554 18
 
1.1%
1115 17
 
1.1%
3300 17
 
1.1%
Other values (849) 1283
80.2%
(Missing) 29
 
1.8%
ValueCountFrequency (%)
80 1
 
0.1%
84 1
 
0.1%
89 1
 
0.1%
91 1
 
0.1%
96 3
0.2%
97 1
 
0.1%
99 1
 
0.1%
108 1
 
0.1%
110 1
 
0.1%
113 2
0.1%
ValueCountFrequency (%)
64470 1
0.1%
44382 1
0.1%
29747 1
0.1%
29537 1
0.1%
29227 1
0.1%
28368 1
0.1%
27760 1
0.1%
24420 1
0.1%
23923 1
0.1%
23243 1
0.1%

지목
Text

MISSING 

Distinct115
Distinct (%)7.3%
Missing29
Missing (%)1.8%
Memory size12.6 KiB
2024-01-10T06:11:38.211975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length4.5617834
Min length1

Characters and Unicode

Total characters7162
Distinct characters36
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)3.8%

Sample

1st row 공장용지
2nd row 대
3rd row 잡종지
4th row 임야
5th row 공장용지
ValueCountFrequency (%)
임야 739
46.4%
전 180
 
11.3%
답 166
 
10.4%
공장용지 63
 
4.0%
임 48
 
3.0%
임야/전 42
 
2.6%
잡종지 39
 
2.4%
대 37
 
2.3%
전/임야/전/전/답 18
 
1.1%
창고용지 15
 
0.9%
Other values (86) 245
 
15.4%
2024-01-10T06:11:38.513754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2895
40.4%
임 1002
 
14.0%
야 954
 
13.3%
/ 510
 
7.1%
전 479
 
6.7%
답 266
 
3.7%
지 211
 
2.9%
장 132
 
1.8%
용 111
 
1.5%
공 80
 
1.1%
Other values (26) 522
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3697
51.6%
Space Separator 2895
40.4%
Other Punctuation 539
 
7.5%
Close Punctuation 14
 
0.2%
Open Punctuation 14
 
0.2%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 1002
27.1%
야 954
25.8%
전 479
13.0%
답 266
 
7.2%
지 211
 
5.7%
장 132
 
3.6%
용 111
 
3.0%
공 80
 
2.2%
대 67
 
1.8%
잡 62
 
1.7%
Other values (20) 333
 
9.0%
Other Punctuation
ValueCountFrequency (%)
/ 510
94.6%
, 29
 
5.4%
Space Separator
ValueCountFrequency (%)
2895
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3697
51.6%
Common 3462
48.3%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 1002
27.1%
야 954
25.8%
전 479
13.0%
답 266
 
7.2%
지 211
 
5.7%
장 132
 
3.6%
용 111
 
3.0%
공 80
 
2.2%
대 67
 
1.8%
잡 62
 
1.7%
Other values (20) 333
 
9.0%
Common
ValueCountFrequency (%)
2895
83.6%
/ 510
 
14.7%
, 29
 
0.8%
) 14
 
0.4%
( 14
 
0.4%
Latin
ValueCountFrequency (%)
X 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3697
51.6%
ASCII 3465
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2895
83.5%
/ 510
 
14.7%
, 29
 
0.8%
) 14
 
0.4%
( 14
 
0.4%
X 3
 
0.1%
Hangul
ValueCountFrequency (%)
임 1002
27.1%
야 954
25.8%
전 479
13.0%
답 266
 
7.2%
지 211
 
5.7%
장 132
 
3.6%
용 111
 
3.0%
공 80
 
2.2%
대 67
 
1.8%
잡 62
 
1.7%
Other values (20) 333
 
9.0%

사업상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
<NA>
1537 
취소
 
61
 
1

Length

Max length4
Median length4
Mean length3.9218261
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1537
96.1%
취소 61
 
3.8%
1
 
0.1%

Length

2024-01-10T06:11:38.632412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:11:38.734780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1537
96.2%
취소 61
 
3.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
Minimum2021-10-08 00:00:00
Maximum2021-10-08 00:00:00
2024-01-10T06:11:38.809143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:38.897798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:11:32.169802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:31.615123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:31.897655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:32.268916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:31.716440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:31.992270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:32.352516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:31.802356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:11:32.081975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:11:38.994140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량설치면적사업상태
연번1.0000.3210.2050.295
설비용량0.3211.0000.7310.000
설치면적0.2050.7311.0000.000
사업상태0.2950.0000.0001.000
2024-01-10T06:11:39.099550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업상태주파수공급전압
사업상태1.0001.0001.000
주파수1.0001.0001.000
공급전압1.0001.0001.000
2024-01-10T06:11:39.184938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량설치면적공급전압주파수사업상태
연번1.000-0.039-0.3431.0001.0000.300
설비용량-0.0391.0000.4241.0001.0000.000
설치면적-0.3430.4241.0001.0001.0000.000
공급전압1.0001.0001.0001.0001.0001.000
주파수1.0001.0001.0001.0001.0001.000
사업상태0.3000.0000.0001.0001.0001.000

Missing values

2024-01-10T06:11:32.485070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:11:32.649164image/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.
2024-01-10T06:11:32.780351image/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

연번발전소명발전소주소최초허가일사업개시일설치위치설비용량공급전압주파수설치면적지목사업상태데이터기준일
01방우리소수력금산군 부리면 방우리 산3-21986-08-051986-08-05금산군 부리면 방우리 산3-22120.0<NA><NA><NA><NA><NA>2021-10-08
12금성금산군 금성면 상가리 산67-12007-02-022010-01-06금산군 금성면 상가리 산67-11000.0<NA><NA><NA><NA><NA>2021-10-08
23두리금산군 부리면 창평리 280-12009-08-142010-06-11금산군 부리면 창평리 280-199.0<NA><NA><NA><NA><NA>2021-10-08
34영솔라금산군 부리면 창평리 280-32009-08-142010-06-11금산군 부리면 창평리 280-399.0<NA><NA><NA><NA><NA>2021-10-08
45㈜서울전업공사금산군 추부면 신평리 10002009-12-282011-11-25금산군 추부면 신평리 100021.0<NA><NA><NA><NA><NA>2021-10-08
56신정2호금산군 남일면 신정리 418-62010-03-162011-04-07금산군 남일면 신정리 418-619.35<NA><NA><NA><NA><NA>2021-10-08
67문은옥금산군 추부면 대학로 156-14(1필지)2012-03-262012-07-06금산군 추부면 대학로 156-14(1필지)24.0<NA><NA><NA><NA><NA>2021-10-08
78군북금산군 군북면 두두리 380-82012-04-03<NA>금산군 군북면 두두리 380-89.0<NA><NA><NA><NA><NA>2021-10-08
89㈜에버솔라금산군 추부면 신평리 1006-32012-04-092014-01-15금산군 추부면 신평리 1006-3250.0<NA><NA><NA><NA><NA>2021-10-08
910초희금산군 남일면 신정리 4162012-06-042012-12-26금산군 남일면 신정리 41619.74<NA><NA><NA><NA><NA>2021-10-08
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