Overview

Dataset statistics

Number of variables4
Number of observations1836
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.1 KiB
Average record size in memory34.1 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description지역별 배전설비계획 지역본부, 사업소, 년도, 지역인구수 정보입니다.
Author한국전력공사
URLhttps://www.data.go.kr/data/3068739/fileData.do

Reproduction

Analysis started2023-12-12 17:16:29.493734
Analysis finished2023-12-12 17:16:30.362032
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역본부
Categorical

Distinct14
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
광주전남지역본부
300 
대구경북지역본부
224 
강원지역본부
214 
경남지역본부
179 
대전충남지역본부
155 
Other values (9)
764 

Length

Max length8
Median length7
Mean length7.0141612
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주전남지역본부 300
16.3%
대구경북지역본부 224
12.2%
강원지역본부 214
11.7%
경남지역본부 179
9.7%
대전충남지역본부 155
8.4%
부산울산지역본부 128
7.0%
충북지역본부 118
 
6.4%
경기지역본부 104
 
5.7%
전북지역본부 103
 
5.6%
경기북부지역본부 97
 
5.3%
Other values (4) 214
11.7%

Length

2023-12-13T02:16:30.447370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광주전남지역본부 300
16.3%
대구경북지역본부 224
12.2%
강원지역본부 214
11.7%
경남지역본부 179
9.7%
대전충남지역본부 155
8.4%
부산울산지역본부 128
7.0%
충북지역본부 118
 
6.4%
경기지역본부 104
 
5.7%
전북지역본부 103
 
5.6%
경기북부지역본부 97
 
5.3%
Other values (4) 214
11.7%

사업소
Text

Distinct188
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2023-12-13T02:16:30.717592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.4907407
Min length4

Characters and Unicode

Total characters8245
Distinct characters123
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row철원지사
2nd row철원지사
3rd row철원지사
4th row철원지사
5th row철원지사
ValueCountFrequency (%)
고성지사 20
 
1.1%
구례지사 12
 
0.7%
진도지사 12
 
0.7%
제주지역본부직할 12
 
0.7%
보성지사 12
 
0.7%
광산지사 12
 
0.7%
목포지사 12
 
0.7%
진천지사 12
 
0.7%
강진지사 12
 
0.7%
영광지사 12
 
0.7%
Other values (178) 1708
93.0%
2023-12-13T02:16:31.253442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 1836
22.3%
사 1706
20.7%
부 253
 
3.1%
산 221
 
2.7%
천 205
 
2.5%
주 166
 
2.0%
양 147
 
1.8%
성 143
 
1.7%
서 142
 
1.7%
역 139
 
1.7%
Other values (113) 3287
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8245
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1836
22.3%
사 1706
20.7%
부 253
 
3.1%
산 221
 
2.7%
천 205
 
2.5%
주 166
 
2.0%
양 147
 
1.8%
성 143
 
1.7%
서 142
 
1.7%
역 139
 
1.7%
Other values (113) 3287
39.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8245
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1836
22.3%
사 1706
20.7%
부 253
 
3.1%
산 221
 
2.7%
천 205
 
2.5%
주 166
 
2.0%
양 147
 
1.8%
성 143
 
1.7%
서 142
 
1.7%
역 139
 
1.7%
Other values (113) 3287
39.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8245
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 1836
22.3%
사 1706
20.7%
부 253
 
3.1%
산 221
 
2.7%
천 205
 
2.5%
주 166
 
2.0%
양 147
 
1.8%
성 143
 
1.7%
서 142
 
1.7%
역 139
 
1.7%
Other values (113) 3287
39.9%

년도
Real number (ℝ)

Distinct13
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.744
Minimum2000
Maximum2012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2023-12-13T02:16:31.424895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001
Q12003
median2006
Q32008
95-th percentile2011
Maximum2012
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0385071
Coefficient of variation (CV)0.0015149027
Kurtosis-0.90460614
Mean2005.744
Median Absolute Deviation (MAD)2
Skewness0.0043478104
Sum3682546
Variance9.2325254
MonotonicityNot monotonic
2023-12-13T02:16:31.589067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2004 189
10.3%
2005 189
10.3%
2006 189
10.3%
2007 189
10.3%
2003 186
10.1%
2008 186
10.1%
2009 186
10.1%
2002 141
7.7%
2010 110
6.0%
2001 101
5.5%
Other values (3) 170
9.3%
ValueCountFrequency (%)
2000 65
 
3.5%
2001 101
5.5%
2002 141
7.7%
2003 186
10.1%
2004 189
10.3%
2005 189
10.3%
2006 189
10.3%
2007 189
10.3%
2008 186
10.1%
2009 186
10.1%
ValueCountFrequency (%)
2012 30
 
1.6%
2011 75
 
4.1%
2010 110
6.0%
2009 186
10.1%
2008 186
10.1%
2007 189
10.3%
2006 189
10.3%
2005 189
10.3%
2004 189
10.3%
2003 186
10.1%

지역인구수
Real number (ℝ)

Distinct1827
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295216.74
Minimum3513
Maximum3472431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2023-12-13T02:16:31.781635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3513
5-th percentile27236.5
Q150483.75
median111698
Q3347186.75
95-th percentile1027514.5
Maximum3472431
Range3468918
Interquartile range (IQR)296703

Descriptive statistics

Standard deviation418412.72
Coefficient of variation (CV)1.4173069
Kurtosis14.142133
Mean295216.74
Median Absolute Deviation (MAD)77324
Skewness3.1232873
Sum5.4201794 × 108
Variance1.7506921 × 1011
MonotonicityNot monotonic
2023-12-13T02:16:32.008697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45599 2
 
0.1%
36047 2
 
0.1%
41155 2
 
0.1%
45973 2
 
0.1%
169819 2
 
0.1%
32681 2
 
0.1%
109432 2
 
0.1%
31524 2
 
0.1%
26785 2
 
0.1%
92487 1
 
0.1%
Other values (1817) 1817
99.0%
ValueCountFrequency (%)
3513 1
0.1%
3530 1
0.1%
3568 1
0.1%
3705 1
0.1%
3929 1
0.1%
4178 1
0.1%
4300 1
0.1%
4372 1
0.1%
4582 1
0.1%
9201 1
0.1%
ValueCountFrequency (%)
3472431 1
0.1%
3445707 1
0.1%
3391773 1
0.1%
3337146 1
0.1%
3319983 1
0.1%
3293235 1
0.1%
3275835 1
0.1%
2301106 1
0.1%
2265784 1
0.1%
2205074 1
0.1%

Interactions

2023-12-13T02:16:29.936088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:16:29.705383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:16:30.067235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:16:29.809307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:16:32.139789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역본부년도지역인구수
지역본부1.0000.2890.703
년도0.2891.0000.000
지역인구수0.7030.0001.000
2023-12-13T02:16:32.230892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도지역인구수지역본부
년도1.000-0.0000.133
지역인구수-0.0001.0000.403
지역본부0.1330.4031.000

Missing values

2023-12-13T02:16:30.203968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:16:30.317016image/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

지역본부사업소년도지역인구수
0강원지역본부철원지사200053329
1강원지역본부철원지사200152224
2강원지역본부철원지사200250682
3강원지역본부철원지사200350450
4강원지역본부철원지사200449908
5강원지역본부철원지사200549167
6강원지역본부철원지사200648260
7강원지역본부철원지사200747719
8강원지역본부철원지사200848066
9강원지역본부철원지사200948054
지역본부사업소년도지역인구수
1826충북지역본부옥천지사201048705
1827충북지역본부영동지사200255967
1828충북지역본부영동지사200354284
1829충북지역본부영동지사200452905
1830충북지역본부영동지사200552188
1831충북지역본부영동지사200651226
1832충북지역본부영동지사200750568
1833충북지역본부영동지사200850756
1834충북지역본부영동지사200950918
1835충북지역본부영동지사201050985