Overview

Dataset statistics

Number of variables6
Number of observations224
Missing cells208
Missing cells (%)15.5%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory10.8 KiB
Average record size in memory49.6 B

Variable types

Text3
Categorical1
Numeric1
DateTime1

Dataset

Description경상북도 김천시에서 제공하는 벤치현황 정보로, 설치위치명, 설치위치구분(공원, 보도, 기타 등), 설치도로명주소 및 설치지번주소, 개수 등의 정보를 포함합니다.
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15099930/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.4%) duplicate rowsDuplicates
설치도로명주소 has 137 (61.2%) missing valuesMissing
설치지번주소 has 71 (31.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:33:18.131794
Analysis finished2023-12-12 18:33:19.460244
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치위치명
Text

Distinct220
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T03:33:19.785217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.9375
Min length3

Characters and Unicode

Total characters2002
Distinct characters281
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)96.4%

Sample

1st row자래봉 공원
2nd row공명선거소공원
3rd row인리쉼터(지동보건소앞)
4th row신촌쉼터(의동보건소앞)
5th row시내이쉼터
ValueCountFrequency (%)
앞 40
 
9.8%
입구 12
 
2.9%
옆 12
 
2.9%
주공해돋이 7
 
1.7%
마을회관 6
 
1.5%
현대아파트 5
 
1.2%
사이 5
 
1.2%
부근 5
 
1.2%
골드클래스 5
 
1.2%
삼도뷰엔빌 4
 
1.0%
Other values (265) 309
75.4%
2023-12-13T03:33:20.625777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
 
9.5%
터 116
 
5.8%
쉼 104
 
5.2%
마 56
 
2.8%
을 50
 
2.5%
) 46
 
2.3%
1 46
 
2.3%
( 46
 
2.3%
앞 44
 
2.2%
동 43
 
2.1%
Other values (271) 1261
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1603
80.1%
Space Separator 190
 
9.5%
Decimal Number 111
 
5.5%
Close Punctuation 46
 
2.3%
Open Punctuation 46
 
2.3%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 116
 
7.2%
쉼 104
 
6.5%
마 56
 
3.5%
을 50
 
3.1%
앞 44
 
2.7%
동 43
 
2.7%
리 42
 
2.6%
공 30
 
1.9%
천 28
 
1.7%
지 27
 
1.7%
Other values (253) 1063
66.3%
Decimal Number
ValueCountFrequency (%)
1 46
41.4%
0 23
20.7%
2 22
19.8%
4 6
 
5.4%
7 5
 
4.5%
3 5
 
4.5%
6 1
 
0.9%
8 1
 
0.9%
5 1
 
0.9%
9 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1603
80.1%
Common 396
 
19.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 116
 
7.2%
쉼 104
 
6.5%
마 56
 
3.5%
을 50
 
3.1%
앞 44
 
2.7%
동 43
 
2.7%
리 42
 
2.6%
공 30
 
1.9%
천 28
 
1.7%
지 27
 
1.7%
Other values (253) 1063
66.3%
Common
ValueCountFrequency (%)
190
48.0%
) 46
 
11.6%
1 46
 
11.6%
( 46
 
11.6%
0 23
 
5.8%
2 22
 
5.6%
4 6
 
1.5%
7 5
 
1.3%
3 5
 
1.3%
6 1
 
0.3%
Other values (6) 6
 
1.5%
Latin
ValueCountFrequency (%)
C 2
66.7%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1603
80.1%
ASCII 399
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
47.6%
) 46
 
11.5%
1 46
 
11.5%
( 46
 
11.5%
0 23
 
5.8%
2 22
 
5.5%
4 6
 
1.5%
7 5
 
1.3%
3 5
 
1.3%
C 2
 
0.5%
Other values (8) 8
 
2.0%
Hangul
ValueCountFrequency (%)
터 116
 
7.2%
쉼 104
 
6.5%
마 56
 
3.5%
을 50
 
3.1%
앞 44
 
2.7%
동 43
 
2.7%
리 42
 
2.6%
공 30
 
1.9%
천 28
 
1.7%
지 27
 
1.7%
Other values (253) 1063
66.3%

설치위치구분
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
공원
115 
기타(아파트단지 등)
93 
보도
16 

Length

Max length11
Median length2
Mean length5.7366071
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공원 115
51.3%
기타(아파트단지 등) 93
41.5%
보도 16
 
7.1%

Length

2023-12-13T03:33:20.879645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:33:21.057625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공원 115
36.3%
기타(아파트단지 93
29.3%
등 93
29.3%
보도 16
 
5.0%

설치도로명주소
Text

MISSING 

Distinct65
Distinct (%)74.7%
Missing137
Missing (%)61.2%
Memory size1.9 KiB
2023-12-13T03:33:21.545306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length17.482759
Min length12

Characters and Unicode

Total characters1521
Distinct characters92
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

Unique57 ?
Unique (%)65.5%

Sample

1st row경상북도 김천시 농소면 노곡길 29
2nd row경상북도 김천시 남면 천동안길 48
3rd row경상북도 김천시 남면 천동안길 48
4th row경상북도 김천시 남면 운양길 72
5th row경상북도 김천시 남면 섶밭길 157-10
ValueCountFrequency (%)
경상북도 87
24.3%
김천시 77
21.5%
구성면 11
 
3.1%
김천로 11
 
3.1%
신음새동네길 10
 
2.8%
남면 8
 
2.2%
110 8
 
2.2%
시청로46 7
 
2.0%
혁신2로 5
 
1.4%
76 5
 
1.4%
Other values (107) 129
36.0%
2023-12-13T03:33:22.333411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
273
17.9%
천 96
 
6.3%
상 90
 
5.9%
김 89
 
5.9%
시 88
 
5.8%
도 88
 
5.8%
경 87
 
5.7%
북 87
 
5.7%
1 70
 
4.6%
길 44
 
2.9%
Other values (82) 509
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 968
63.6%
Space Separator 273
 
17.9%
Decimal Number 262
 
17.2%
Dash Punctuation 16
 
1.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 96
9.9%
상 90
 
9.3%
김 89
 
9.2%
시 88
 
9.1%
도 88
 
9.1%
경 87
 
9.0%
북 87
 
9.0%
길 44
 
4.5%
로 41
 
4.2%
면 27
 
2.8%
Other values (69) 231
23.9%
Decimal Number
ValueCountFrequency (%)
1 70
26.7%
2 34
13.0%
6 28
 
10.7%
0 26
 
9.9%
7 25
 
9.5%
3 20
 
7.6%
4 19
 
7.3%
9 15
 
5.7%
5 15
 
5.7%
8 10
 
3.8%
Space Separator
ValueCountFrequency (%)
273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 968
63.6%
Common 553
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 96
9.9%
상 90
 
9.3%
김 89
 
9.2%
시 88
 
9.1%
도 88
 
9.1%
경 87
 
9.0%
북 87
 
9.0%
길 44
 
4.5%
로 41
 
4.2%
면 27
 
2.8%
Other values (69) 231
23.9%
Common
ValueCountFrequency (%)
273
49.4%
1 70
 
12.7%
2 34
 
6.1%
6 28
 
5.1%
0 26
 
4.7%
7 25
 
4.5%
3 20
 
3.6%
4 19
 
3.4%
- 16
 
2.9%
9 15
 
2.7%
Other values (3) 27
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 968
63.6%
ASCII 553
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
273
49.4%
1 70
 
12.7%
2 34
 
6.1%
6 28
 
5.1%
0 26
 
4.7%
7 25
 
4.5%
3 20
 
3.6%
4 19
 
3.4%
- 16
 
2.9%
9 15
 
2.7%
Other values (3) 27
 
4.9%
Hangul
ValueCountFrequency (%)
천 96
9.9%
상 90
 
9.3%
김 89
 
9.2%
시 88
 
9.1%
도 88
 
9.1%
경 87
 
9.0%
북 87
 
9.0%
길 44
 
4.5%
로 41
 
4.2%
면 27
 
2.8%
Other values (69) 231
23.9%

설치지번주소
Text

MISSING 

Distinct145
Distinct (%)94.8%
Missing71
Missing (%)31.7%
Memory size1.9 KiB
2023-12-13T03:33:22.938139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length19.437908
Min length14

Characters and Unicode

Total characters2974
Distinct characters106
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)92.2%

Sample

1st row경상북도 김천시 황금동 186
2nd row경상북도 김천시 양천동 1775-1
3rd row경상북도 김천시 아포읍 인4리
4th row경상북도 김천시 아포읍 의1리
5th row경상북도 김천시 아포읍 대신3리 560-1
ValueCountFrequency (%)
경상북도 153
22.0%
김천시 153
22.0%
개령면 15
 
2.2%
감문면 14
 
2.0%
율곡동 12
 
1.7%
감천면 12
 
1.7%
대항면 10
 
1.4%
아포읍 10
 
1.4%
남면 8
 
1.2%
농소면 8
 
1.2%
Other values (225) 300
43.2%
2023-12-13T03:33:23.759808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
564
19.0%
천 179
 
6.0%
상 155
 
5.2%
도 155
 
5.2%
경 153
 
5.1%
북 153
 
5.1%
김 153
 
5.1%
시 153
 
5.1%
1 116
 
3.9%
리 110
 
3.7%
Other values (96) 1083
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1846
62.1%
Space Separator 564
 
19.0%
Decimal Number 493
 
16.6%
Dash Punctuation 69
 
2.3%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 179
 
9.7%
상 155
 
8.4%
도 155
 
8.4%
경 153
 
8.3%
북 153
 
8.3%
김 153
 
8.3%
시 153
 
8.3%
리 110
 
6.0%
면 94
 
5.1%
동 46
 
2.5%
Other values (82) 495
26.8%
Decimal Number
ValueCountFrequency (%)
1 116
23.5%
3 58
11.8%
2 55
11.2%
5 53
10.8%
4 45
 
9.1%
0 35
 
7.1%
9 35
 
7.1%
8 34
 
6.9%
7 33
 
6.7%
6 29
 
5.9%
Space Separator
ValueCountFrequency (%)
564
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1846
62.1%
Common 1128
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 179
 
9.7%
상 155
 
8.4%
도 155
 
8.4%
경 153
 
8.3%
북 153
 
8.3%
김 153
 
8.3%
시 153
 
8.3%
리 110
 
6.0%
면 94
 
5.1%
동 46
 
2.5%
Other values (82) 495
26.8%
Common
ValueCountFrequency (%)
564
50.0%
1 116
 
10.3%
- 69
 
6.1%
3 58
 
5.1%
2 55
 
4.9%
5 53
 
4.7%
4 45
 
4.0%
0 35
 
3.1%
9 35
 
3.1%
8 34
 
3.0%
Other values (4) 64
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1846
62.1%
ASCII 1128
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
564
50.0%
1 116
 
10.3%
- 69
 
6.1%
3 58
 
5.1%
2 55
 
4.9%
5 53
 
4.7%
4 45
 
4.0%
0 35
 
3.1%
9 35
 
3.1%
8 34
 
3.0%
Other values (4) 64
 
5.7%
Hangul
ValueCountFrequency (%)
천 179
 
9.7%
상 155
 
8.4%
도 155
 
8.4%
경 153
 
8.3%
북 153
 
8.3%
김 153
 
8.3%
시 153
 
8.3%
리 110
 
6.0%
면 94
 
5.1%
동 46
 
2.5%
Other values (82) 495
26.8%

개수
Real number (ℝ)

Distinct25
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5803571
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T03:33:24.008700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q36
95-th percentile17
Maximum50
Range49
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.5157692
Coefficient of variation (CV)1.3468258
Kurtosis16.458862
Mean5.5803571
Median Absolute Deviation (MAD)2
Skewness3.7134819
Sum1250
Variance56.486787
MonotonicityNot monotonic
2023-12-13T03:33:24.214082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 50
22.3%
1 43
19.2%
3 25
11.2%
4 22
9.8%
6 18
 
8.0%
5 18
 
8.0%
8 11
 
4.9%
10 6
 
2.7%
7 5
 
2.2%
14 4
 
1.8%
Other values (15) 22
9.8%
ValueCountFrequency (%)
1 43
19.2%
2 50
22.3%
3 25
11.2%
4 22
9.8%
5 18
 
8.0%
6 18
 
8.0%
7 5
 
2.2%
8 11
 
4.9%
9 3
 
1.3%
10 6
 
2.7%
ValueCountFrequency (%)
50 2
0.9%
46 1
0.4%
42 1
0.4%
30 1
0.4%
28 1
0.4%
27 1
0.4%
25 1
0.4%
24 1
0.4%
21 1
0.4%
19 1
0.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2022-04-25 00:00:00
Maximum2022-04-25 00:00:00
2023-12-13T03:33:24.393099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:33:24.552871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:33:18.574142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:33:24.659458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치구분설치도로명주소개수
설치위치구분1.0000.9710.218
설치도로명주소0.9711.0000.977
개수0.2180.9771.000
2023-12-13T03:33:24.779036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개수설치위치구분
개수1.0000.139
설치위치구분0.1391.000

Missing values

2023-12-13T03:33:18.871710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:33:19.116123image/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.
2023-12-13T03:33:19.314654image/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

설치위치명설치위치구분설치도로명주소설치지번주소개수데이터기준일자
0자래봉 공원공원<NA>경상북도 김천시 황금동 18622022-04-25
1공명선거소공원공원<NA>경상북도 김천시 양천동 1775-162022-04-25
2인리쉼터(지동보건소앞)공원<NA>경상북도 김천시 아포읍 인4리52022-04-25
3신촌쉼터(의동보건소앞)공원<NA>경상북도 김천시 아포읍 의1리82022-04-25
4시내이쉼터공원<NA>경상북도 김천시 아포읍 대신3리 560-1102022-04-25
5금계쉼터(마을입구)공원<NA>경상북도 김천시 아포읍 송천3리52022-04-25
6국사쉼터(읍청사 뒤)공원<NA>경상북도 김천시 아포읍 국사2리22022-04-25
7연명쉼터공원<NA>경상북도 김천시 농소면 연명리 283-392022-04-25
8선돌쉼터(회관 앞)공원<NA>경상북도 김천시 농소면 입석리 1415-142022-04-25
9용암1리쉼터(마을입구)공원<NA>경상북도 김천시 농소면 용암리 1110-1102022-04-25
설치위치명설치위치구분설치도로명주소설치지번주소개수데이터기준일자
214세븐일레븐 김천평화스타점 앞보도경상북도 김천시 평화길 152-1<NA>22022-04-25
215지지고 김천역점 앞보도경상북도 김천시 김천로 114-1<NA>12022-04-25
216김밥천국 역전점 앞보도경상북도 김천시 김천로 108-2<NA>12022-04-25
217봄봄 김천역점 앞보도경상북도 김천시 김천로 103<NA>22022-04-25
218그린조이 김천점 앞보도경상북도 김천시 김천로 89-2<NA>12022-04-25
219대광빌딩 앞보도경상북도 김천시 김천로 73<NA>22022-04-25
220맘스터치 김천평화점 앞보도경상북도 김천시 김천로 75<NA>12022-04-25
221신한은행~후생당약국보도경상북도 김천시 김천로<NA>282022-04-25
222복전1리 마을회관 앞보도<NA>경상북도 김천시 대항면 복전리 190-2122022-04-25
223덕전2리회관 앞보도<NA>경상북도 김천시 대항면 덕전리 1506-1022022-04-25

Duplicate rows

Most frequently occurring

설치위치명설치위치구분설치도로명주소설치지번주소개수데이터기준일자# duplicates
0문무리쉼터(상여마을 앞)공원<NA>경상북도 김천시 감문면 문무리12022-04-252