Overview

Dataset statistics

Number of variables13
Number of observations42
Missing cells5
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory112.1 B

Variable types

Numeric4
Categorical4
Text4
DateTime1

Dataset

Description전라남도 곡성군 소규모 공공하수처리서설의 적정 관리 현황을 제공합니다 (시설명, 처리공법, 위치 , 시설 용량, 처리면적 , 시공업체 등 포함)
URLhttps://www.data.go.kr/data/3074915/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 구분High correlation
시설용량(m3) is highly overall correlated with 처리면적(km2) and 1 other fieldsHigh correlation
처리면적(km2) is highly overall correlated with 시설용량(m3) and 1 other fieldsHigh correlation
처리인구 is highly overall correlated with 시설용량(m3) and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번High correlation
운영년도 is highly imbalanced (79.6%)Imbalance
처리인구 has 2 (4.8%) missing valuesMissing
시공업체 has 3 (7.1%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:35:25.488075
Analysis finished2023-12-12 07:35:28.182809
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.5
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T16:35:28.262495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.05
Q111.25
median21.5
Q331.75
95-th percentile39.95
Maximum42
Range41
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation12.267844
Coefficient of variation (CV)0.5705974
Kurtosis-1.2
Mean21.5
Median Absolute Deviation (MAD)10.5
Skewness0
Sum903
Variance150.5
MonotonicityStrictly increasing
2023-12-12T16:35:28.396680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1 1
 
2.4%
33 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
32 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
42 1
2.4%
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
전라남도
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 42
100.0%

Length

2023-12-12T16:35:28.556218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:35:28.700081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
곡성군
42 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
곡성군 42
100.0%

Length

2023-12-12T16:35:28.814038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:35:28.933364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
곡성군 42
100.0%

구분
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
죽곡면
7 
겸면
5 
곡성읍
4 
목사동면
4 
고달면
4 
Other values (7)
18 

Length

Max length5
Median length4
Mean length3.6428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row곡성읍
2nd row곡성읍
3rd row곡성읍
4th row곡성읍
5th row오곡면

Common Values

ValueCountFrequency (%)
죽곡면 7
16.7%
겸면 5
11.9%
곡성읍 4
9.5%
목사동면 4
9.5%
고달면 4
9.5%
오곡면 3
7.1%
삼기면 3
7.1%
죽곡면 3
7.1%
입면 3
7.1%
석곡면 2
 
4.8%
Other values (2) 4
9.5%

Length

2023-12-12T16:35:29.062093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
죽곡면 10
23.8%
겸면 5
11.9%
곡성읍 4
 
9.5%
목사동면 4
 
9.5%
고달면 4
 
9.5%
오곡면 3
 
7.1%
삼기면 3
 
7.1%
입면 3
 
7.1%
석곡면 2
 
4.8%
옥과면 2
 
4.8%

시설명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T16:35:29.326293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.1666667
Min length2

Characters and Unicode

Total characters91
Distinct characters60
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row구원
2nd row서계
3rd row장선
4th row신기
5th row송정
ValueCountFrequency (%)
구원 1
 
2.4%
합강 1
 
2.4%
평촌 1
 
2.4%
하한1 1
 
2.4%
하한2 1
 
2.4%
강빛 1
 
2.4%
목동 1
 
2.4%
대사 1
 
2.4%
가정1 1
 
2.4%
수리 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T16:35:29.692096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 9
 
9.9%
한 3
 
3.3%
1 3
 
3.3%
2 3
 
3.3%
대 3
 
3.3%
평 3
 
3.3%
동 3
 
3.3%
괴 2
 
2.2%
하 2
 
2.2%
화 2
 
2.2%
Other values (50) 58
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
92.3%
Decimal Number 6
 
6.6%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 9
 
10.7%
한 3
 
3.6%
대 3
 
3.6%
평 3
 
3.6%
동 3
 
3.6%
괴 2
 
2.4%
하 2
 
2.4%
화 2
 
2.4%
연 2
 
2.4%
원 2
 
2.4%
Other values (47) 53
63.1%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
92.3%
Common 7
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 9
 
10.7%
한 3
 
3.6%
대 3
 
3.6%
평 3
 
3.6%
동 3
 
3.6%
괴 2
 
2.4%
하 2
 
2.4%
화 2
 
2.4%
연 2
 
2.4%
원 2
 
2.4%
Other values (47) 53
63.1%
Common
ValueCountFrequency (%)
1 3
42.9%
2 3
42.9%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
92.3%
ASCII 7
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 9
 
10.7%
한 3
 
3.6%
대 3
 
3.6%
평 3
 
3.6%
동 3
 
3.6%
괴 2
 
2.4%
하 2
 
2.4%
화 2
 
2.4%
연 2
 
2.4%
원 2
 
2.4%
Other values (47) 53
63.1%
ASCII
ValueCountFrequency (%)
1 3
42.9%
2 3
42.9%
1
 
14.3%

처리공법
Text

Distinct26
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T16:35:29.879061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length5.7380952
Min length3

Characters and Unicode

Total characters241
Distinct characters53
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)40.5%

Sample

1st rowOAM
2nd row자연친화형 무동력 오수처리
3rd rowBSTS-Ⅱ
4th rowAPB-SBR
5th row토양및접촉산화
ValueCountFrequency (%)
khbnr 5
 
11.4%
apb-sbr 4
 
9.1%
fnr공법 4
 
9.1%
oam 3
 
6.8%
abr 3
 
6.8%
고도처리 3
 
6.8%
eco-sbr 2
 
4.5%
오폐수고도처리 2
 
4.5%
l.c정화 2
 
4.5%
hant 1
 
2.3%
Other values (15) 15
34.1%
2023-12-12T16:35:30.236689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 27
 
11.2%
R 23
 
9.5%
S 16
 
6.6%
A 14
 
5.8%
- 11
 
4.6%
N 10
 
4.1%
10
 
4.1%
K 7
 
2.9%
C 7
 
2.9%
처 7
 
2.9%
Other values (43) 109
45.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 138
57.3%
Other Letter 75
31.1%
Space Separator 12
 
5.0%
Dash Punctuation 11
 
4.6%
Other Punctuation 2
 
0.8%
Decimal Number 1
 
0.4%
Connector Punctuation 1
 
0.4%
Letter Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
처 7
 
9.3%
리 7
 
9.3%
법 6
 
8.0%
공 6
 
8.0%
도 6
 
8.0%
고 6
 
8.0%
화 5
 
6.7%
수 3
 
4.0%
정 3
 
4.0%
오 3
 
4.0%
Other values (20) 23
30.7%
Uppercase Letter
ValueCountFrequency (%)
B 27
19.6%
R 23
16.7%
S 16
11.6%
A 14
10.1%
N 10
 
7.2%
K 7
 
5.1%
C 7
 
5.1%
H 6
 
4.3%
F 5
 
3.6%
O 5
 
3.6%
Other values (6) 18
13.0%
Space Separator
ValueCountFrequency (%)
10
83.3%
　 2
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 139
57.7%
Hangul 75
31.1%
Common 27
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
처 7
 
9.3%
리 7
 
9.3%
법 6
 
8.0%
공 6
 
8.0%
도 6
 
8.0%
고 6
 
8.0%
화 5
 
6.7%
수 3
 
4.0%
정 3
 
4.0%
오 3
 
4.0%
Other values (20) 23
30.7%
Latin
ValueCountFrequency (%)
B 27
19.4%
R 23
16.5%
S 16
11.5%
A 14
10.1%
N 10
 
7.2%
K 7
 
5.0%
C 7
 
5.0%
H 6
 
4.3%
F 5
 
3.6%
O 5
 
3.6%
Other values (7) 19
13.7%
Common
ValueCountFrequency (%)
- 11
40.7%
10
37.0%
　 2
 
7.4%
. 2
 
7.4%
2 1
 
3.7%
_ 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
67.6%
Hangul 75
31.1%
None 2
 
0.8%
Number Forms 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 27
16.6%
R 23
14.1%
S 16
9.8%
A 14
8.6%
- 11
 
6.7%
N 10
 
6.1%
10
 
6.1%
K 7
 
4.3%
C 7
 
4.3%
H 6
 
3.7%
Other values (11) 32
19.6%
Hangul
ValueCountFrequency (%)
처 7
 
9.3%
리 7
 
9.3%
법 6
 
8.0%
공 6
 
8.0%
도 6
 
8.0%
고 6
 
8.0%
화 5
 
6.7%
수 3
 
4.0%
정 3
 
4.0%
오 3
 
4.0%
Other values (20) 23
30.7%
None
ValueCountFrequency (%)
　 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

위치
Text

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T16:35:30.558399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.428571
Min length18

Characters and Unicode

Total characters900
Distinct characters77
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

Unique40 ?
Unique (%)95.2%

Sample

1st row전라남도 곡성군 곡성읍 구원리 221-9
2nd row전라남도 곡성군 서계리 188-3
3rd row전라남도 곡성군 곡성읍 장선리 138-4
4th row전라남도 곡성군 곡성읍 신기리 500
5th row전라남도 곡성군 오곡면 송정리 40-1
ValueCountFrequency (%)
전라남도 42
20.2%
곡성군 41
19.7%
죽곡면 10
 
4.8%
겸면 5
 
2.4%
목사동면 4
 
1.9%
삼기면 3
 
1.4%
하한리 3
 
1.4%
고달면 3
 
1.4%
곡성읍 3
 
1.4%
입면 3
 
1.4%
Other values (80) 91
43.8%
2023-12-12T16:35:31.031261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
18.4%
곡 61
 
6.8%
전 45
 
5.0%
성 44
 
4.9%
군 43
 
4.8%
리 42
 
4.7%
남 42
 
4.7%
도 42
 
4.7%
라 42
 
4.7%
면 37
 
4.1%
Other values (67) 336
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 538
59.8%
Space Separator 166
 
18.4%
Decimal Number 161
 
17.9%
Dash Punctuation 35
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
곡 61
11.3%
전 45
 
8.4%
성 44
 
8.2%
군 43
 
8.0%
리 42
 
7.8%
남 42
 
7.8%
도 42
 
7.8%
라 42
 
7.8%
면 37
 
6.9%
죽 11
 
2.0%
Other values (55) 129
24.0%
Decimal Number
ValueCountFrequency (%)
1 34
21.1%
2 22
13.7%
3 17
10.6%
5 16
9.9%
7 15
9.3%
8 14
8.7%
4 12
 
7.5%
9 12
 
7.5%
0 12
 
7.5%
6 7
 
4.3%
Space Separator
ValueCountFrequency (%)
166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 538
59.8%
Common 362
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
곡 61
11.3%
전 45
 
8.4%
성 44
 
8.2%
군 43
 
8.0%
리 42
 
7.8%
남 42
 
7.8%
도 42
 
7.8%
라 42
 
7.8%
면 37
 
6.9%
죽 11
 
2.0%
Other values (55) 129
24.0%
Common
ValueCountFrequency (%)
166
45.9%
- 35
 
9.7%
1 34
 
9.4%
2 22
 
6.1%
3 17
 
4.7%
5 16
 
4.4%
7 15
 
4.1%
8 14
 
3.9%
4 12
 
3.3%
9 12
 
3.3%
Other values (2) 19
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 538
59.8%
ASCII 362
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
45.9%
- 35
 
9.7%
1 34
 
9.4%
2 22
 
6.1%
3 17
 
4.7%
5 16
 
4.4%
7 15
 
4.1%
8 14
 
3.9%
4 12
 
3.3%
9 12
 
3.3%
Other values (2) 19
 
5.2%
Hangul
ValueCountFrequency (%)
곡 61
11.3%
전 45
 
8.4%
성 44
 
8.2%
군 43
 
8.0%
리 42
 
7.8%
남 42
 
7.8%
도 42
 
7.8%
라 42
 
7.8%
면 37
 
6.9%
죽 11
 
2.0%
Other values (55) 129
24.0%

시설용량(m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.785714
Minimum20
Maximum140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T16:35:31.179896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q140
median49
Q355
95-th percentile90
Maximum140
Range120
Interquartile range (IQR)15

Descriptive statistics

Standard deviation22.552417
Coefficient of variation (CV)0.44407009
Kurtosis5.0622299
Mean50.785714
Median Absolute Deviation (MAD)9
Skewness1.7307566
Sum2133
Variance508.6115
MonotonicityNot monotonic
2023-12-12T16:35:31.301364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
50 9
21.4%
45 7
16.7%
40 5
11.9%
30 4
9.5%
20 4
9.5%
60 3
 
7.1%
90 3
 
7.1%
55 2
 
4.8%
75 1
 
2.4%
48 1
 
2.4%
Other values (3) 3
 
7.1%
ValueCountFrequency (%)
20 4
9.5%
30 4
9.5%
40 5
11.9%
45 7
16.7%
48 1
 
2.4%
50 9
21.4%
55 2
 
4.8%
60 3
 
7.1%
65 1
 
2.4%
75 1
 
2.4%
ValueCountFrequency (%)
140 1
 
2.4%
90 3
 
7.1%
80 1
 
2.4%
75 1
 
2.4%
65 1
 
2.4%
60 3
 
7.1%
55 2
 
4.8%
50 9
21.4%
48 1
 
2.4%
45 7
16.7%

처리면적(km2)
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.093452381
Minimum0.01
Maximum0.256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T16:35:31.435002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.0173
Q10.04275
median0.092
Q30.127
95-th percentile0.21995
Maximum0.256
Range0.246
Interquartile range (IQR)0.08425

Descriptive statistics

Standard deviation0.061956004
Coefficient of variation (CV)0.66296871
Kurtosis0.59886222
Mean0.093452381
Median Absolute Deviation (MAD)0.047
Skewness0.89635658
Sum3.925
Variance0.0038385465
MonotonicityNot monotonic
2023-12-12T16:35:31.557658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.045 3
 
7.1%
0.042 2
 
4.8%
0.124 2
 
4.8%
0.092 2
 
4.8%
0.036 2
 
4.8%
0.064 1
 
2.4%
0.138 1
 
2.4%
0.17 1
 
2.4%
0.101 1
 
2.4%
0.025 1
 
2.4%
Other values (26) 26
61.9%
ValueCountFrequency (%)
0.01 1
 
2.4%
0.013 1
 
2.4%
0.017 1
 
2.4%
0.023 1
 
2.4%
0.025 1
 
2.4%
0.028 1
 
2.4%
0.036 2
4.8%
0.037 1
 
2.4%
0.042 2
4.8%
0.045 3
7.1%
ValueCountFrequency (%)
0.256 1
2.4%
0.253 1
2.4%
0.222 1
2.4%
0.181 1
2.4%
0.17 1
2.4%
0.145 1
2.4%
0.141 1
2.4%
0.14 1
2.4%
0.138 1
2.4%
0.129 1
2.4%

처리인구
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)97.5%
Missing2
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean187.425
Minimum43
Maximum484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T16:35:31.690236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile57.65
Q197
median168.5
Q3238
95-th percentile393.25
Maximum484
Range441
Interquartile range (IQR)141

Descriptive statistics

Standard deviation111.1852
Coefficient of variation (CV)0.59322501
Kurtosis0.2074216
Mean187.425
Median Absolute Deviation (MAD)72.5
Skewness0.87638525
Sum7497
Variance12362.148
MonotonicityNot monotonic
2023-12-12T16:35:31.821584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
263 2
 
4.8%
165 1
 
2.4%
66 1
 
2.4%
484 1
 
2.4%
183 1
 
2.4%
69 1
 
2.4%
152 1
 
2.4%
112 1
 
2.4%
60 1
 
2.4%
197 1
 
2.4%
Other values (29) 29
69.0%
(Missing) 2
 
4.8%
ValueCountFrequency (%)
43 1
2.4%
51 1
2.4%
58 1
2.4%
60 1
2.4%
63 1
2.4%
66 1
2.4%
69 1
2.4%
78 1
2.4%
89 1
2.4%
94 1
2.4%
ValueCountFrequency (%)
484 1
2.4%
417 1
2.4%
392 1
2.4%
374 1
2.4%
351 1
2.4%
347 1
2.4%
315 1
2.4%
263 2
4.8%
244 1
2.4%
236 1
2.4%

시공업체
Text

MISSING 

Distinct34
Distinct (%)87.2%
Missing3
Missing (%)7.1%
Memory size468.0 B
2023-12-12T16:35:32.030052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.7435897
Min length2

Characters and Unicode

Total characters263
Distinct characters62
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)76.9%

Sample

1st row(유)대신건설
2nd row(주)성암토건
3rd row화신건설(주)
4th row성현개발(주)
5th row토우건설(주)
ValueCountFrequency (%)
원진 3
 
7.7%
화성건설(주 2
 
5.1%
주)청호환경개발 2
 
5.1%
세일종합건설 2
 
5.1%
유)대신건설 1
 
2.6%
주)세진종합건설 1
 
2.6%
주)동남기업 1
 
2.6%
j.a건설(주 1
 
2.6%
주)유성기업 1
 
2.6%
죽암건설(주 1
 
2.6%
Other values (24) 24
61.5%
2023-12-12T16:35:32.425722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 28
 
10.6%
) 28
 
10.6%
주 27
 
10.3%
건 24
 
9.1%
설 23
 
8.7%
성 9
 
3.4%
종 7
 
2.7%
합 7
 
2.7%
㈜ 6
 
2.3%
진 5
 
1.9%
Other values (52) 99
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
74.9%
Open Punctuation 28
 
10.6%
Close Punctuation 28
 
10.6%
Other Symbol 6
 
2.3%
Uppercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 27
 
13.7%
건 24
 
12.2%
설 23
 
11.7%
성 9
 
4.6%
종 7
 
3.6%
합 7
 
3.6%
진 5
 
2.5%
원 4
 
2.0%
화 4
 
2.0%
우 4
 
2.0%
Other values (45) 83
42.1%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
A 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
　 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
77.2%
Common 58
 
22.1%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 27
 
13.3%
건 24
 
11.8%
설 23
 
11.3%
성 9
 
4.4%
종 7
 
3.4%
합 7
 
3.4%
㈜ 6
 
3.0%
진 5
 
2.5%
원 4
 
2.0%
화 4
 
2.0%
Other values (46) 87
42.9%
Common
ValueCountFrequency (%)
( 28
48.3%
) 28
48.3%
. 1
 
1.7%
　 1
 
1.7%
Latin
ValueCountFrequency (%)
J 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
74.9%
ASCII 59
 
22.4%
None 7
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 28
47.5%
) 28
47.5%
J 1
 
1.7%
. 1
 
1.7%
A 1
 
1.7%
Hangul
ValueCountFrequency (%)
주 27
 
13.7%
건 24
 
12.2%
설 23
 
11.7%
성 9
 
4.6%
종 7
 
3.6%
합 7
 
3.6%
진 5
 
2.5%
원 4
 
2.0%
화 4
 
2.0%
우 4
 
2.0%
Other values (45) 83
42.1%
None
ValueCountFrequency (%)
㈜ 6
85.7%
　 1
 
14.3%

운영년도
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
2016
40 
1998
 
1
1999
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)4.8%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 40
95.2%
1998 1
 
2.4%
1999 1
 
2.4%

Length

2023-12-12T16:35:32.580246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:35:32.676813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 40
95.2%
1998 1
 
2.4%
1999 1
 
2.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2023-03-08 00:00:00
Maximum2023-03-08 00:00:00
2023-12-12T16:35:32.778277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:32.884268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T16:35:27.509856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.051751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.748558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.156968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.582843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.137727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.872597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.257233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.672355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.219107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.975898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.353003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.749910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:26.654229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.062864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:27.433777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:35:32.968630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시설명처리공법위치시설용량(m3)처리면적(km2)처리인구시공업체운영년도
연번1.0000.9131.0000.6791.0000.0000.6290.2760.8260.239
구분0.9131.0001.0000.0001.0000.0000.5010.4970.5980.468
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
처리공법0.6790.0001.0001.0000.9920.6490.3740.0000.9890.000
위치1.0001.0001.0000.9921.0000.9211.0001.0000.9871.000
시설용량(m3)0.0000.0001.0000.6490.9211.0000.4690.6400.0000.000
처리면적(km2)0.6290.5011.0000.3741.0000.4691.0000.8140.9100.000
처리인구0.2760.4971.0000.0001.0000.6400.8141.0000.0000.000
시공업체0.8260.5981.0000.9890.9870.0000.9100.0001.0000.000
운영년도0.2390.4681.0000.0001.0000.0000.0000.0000.0001.000
2023-12-12T16:35:33.094738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영년도구분
운영년도1.0000.195
구분0.1951.000
2023-12-12T16:35:33.209555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설용량(m3)처리면적(km2)처리인구구분운영년도
연번1.0000.0850.1340.0530.6800.111
시설용량(m3)0.0851.0000.5890.6420.0000.000
처리면적(km2)0.1340.5891.0000.7000.2110.000
처리인구0.0530.6420.7001.0000.2060.000
구분0.6800.0000.2110.2061.0000.195
운영년도0.1110.0000.0000.0000.1951.000

Missing values

2023-12-12T16:35:27.858465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:35:28.033438image/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.
2023-12-12T16:35:28.137333image/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

연번시도명시군구명구분시설명처리공법위치시설용량(m3)처리면적(km2)처리인구시공업체운영년도데이터기준일자
01전라남도곡성군곡성읍구원OAM전라남도 곡성군 곡성읍 구원리 221-9550.253392(유)대신건설20162023-03-08
12전라남도곡성군곡성읍서계자연친화형 무동력 오수처리전라남도 곡성군 서계리 188-3300.037107(주)성암토건20162023-03-08
23전라남도곡성군곡성읍장선BSTS-Ⅱ전라남도 곡성군 곡성읍 장선리 138-4600.084236화신건설(주)20162023-03-08
34전라남도곡성군곡성읍신기APB-SBR전라남도 곡성군 곡성읍 신기리 500450.102166성현개발(주)20162023-03-08
45전라남도곡성군오곡면송정토양및접촉산화전라남도 곡성군 오곡면 송정리 40-1500.0158토우건설(주)20162023-03-08
56전라남도곡성군오곡면압록오폐수고도처리전라남도 곡성군 오곡면 압록리 57-2900.092263화성건설(주)20162023-03-08
67전라남도곡성군오곡면이정OAM전라남도 곡성군 오곡면 압록리 산8-3200.03689장호이엔지(주)20162023-03-08
78전라남도곡성군삼기면원등KHBNR전라남도 곡성군 삼기면 원등리 675900.129417원진20162023-03-08
89전라남도곡성군삼기면괴소KHBNR전라남도 곡성군 삼기면 의암리 37-12500.113157도원환경기계㈜20162023-03-08
910전라남도곡성군삼기면근촌ABR전라남도 곡성군 삼기면 근촌리 197-10450.093216(주)진광건설20162023-03-08
연번시도명시군구명구분시설명처리공법위치시설용량(m3)처리면적(km2)처리인구시공업체운영년도데이터기준일자
3233전라남도곡성군입면종방KHBNR전라남도 곡성군 입면 송전리 1-284500.222165(주)후소엔지니어링20162023-03-08
3334전라남도곡성군겸면현정HANT전라남도 곡성군 겸면 현정리 692400.064197원진20162023-03-08
3435전라남도곡성군겸면가정2BCS-공법전라남도 곡성군 겸면 가정리 841-5500.081244유성환경건설㈜20162023-03-08
3536전라남도곡성군겸면괴정고도처리전라남도 곡성군 겸면 송강리 726-9500.128315대야종합건설㈜20162023-03-08
3637전라남도곡성군겸면운교KSMBR전라남도 곡성군 겸면 운교리 435-25550.085263학성건설(주)20162023-03-08
3738전라남도곡성군오산면봉동인고도처리전라남도 곡성군 오산면 봉동리 393-8800.256347서화종합건설㈜20162023-03-08
3839전라남도곡성군오산면연화2FNR공법전라남도 곡성군 오산면 연화리 372-7600.181351성흥건설(주)20162023-03-08
3940전라남도곡성군고달면고달ECO-SBR전라남도 곡성군 고달면 고달리 785-49400.049124세일종합건설20162023-03-08
4041전라남도곡성군입면평촌ECO-SBR전라남도 곡성군 입면 제월리 711-13450.124189세일종합건설20162023-03-08
4142전라남도곡성군겸면남양APB-SBR전라남도 곡성군 겸면 칠봉리 33-2600.117171㈜풍산건설20162023-03-08