Overview

Dataset statistics

Number of variables7
Number of observations423
Missing cells133
Missing cells (%)4.5%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory24.5 KiB
Average record size in memory59.3 B

Variable types

Text3
Categorical1
Numeric3

Dataset

Description논산시 관내 야외운동기구 설치현황 데이터로 설치기구명, 행정구역, 설치년월, 수량, 제조사 등의 정보를 제공합니다
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=388&beforeMenuCd=DOM_000000201001001000&publicdatapk=15038021

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
경도 is highly overall correlated with 행정구역High correlation
행정구역 is highly overall correlated with 경도High correlation
제조사 has 133 (31.4%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:11:14.763713
Analysis finished2024-01-09 22:11:16.141608
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치기구명
Text

Distinct207
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T07:11:16.280423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length56
Mean length31.399527
Min length3

Characters and Unicode

Total characters13282
Distinct characters221
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)34.3%

Sample

1st rowTM크로스컨트리,TM워밍암,TM트윈트위스트,TM레그프레스,TM롤링웨이스트,TM풀웨이트
2nd row써핑롤링머신,트위스트머신,스윙워커머신,워킹트레이너머신,큰활차머신
3rd row①달리기+좌우파도타기②등허리지압기+허리돌리기③계단밟기+자전거운동④큰활차+역기올리기④좌우파도타기+허리돌리기
4th row①스트라이딩+런닝트레이닝,②레이스라이딩+밸리트레이닝,③웨스트터닝+바디터닝
5th row①L써클드로잉+S써클드로잉,②스트라이딩+런닝트레이닝,③웨스트터닝+바디터닝
ValueCountFrequency (%)
①사이드플라잉+레그푸싱②웨이스트터닝+바디터닝 17
 
4.0%
달리기운동,좌우파도타기,허리돌리기 12
 
2.8%
①마사지롤러+워밍숄더②에어서핑+레그프레스 12
 
2.8%
①좌우파도타기+허리돌리기,②큰활차+역기올리기,③계단밟기+자전거운동 11
 
2.6%
①달리기+좌우파도타기②등허리지압기+허리돌리기③계단밟기+자전거운동 10
 
2.4%
①달리기+좌우파도타기,②큰활차+역기올리기,③등허리지압기+허리돌리 9
 
2.1%
①사이드플라인+레그푸싱,②레이스라이딩+밸리트레이닝,③웨스트터닝+바디터닝 9
 
2.1%
①노르딕머신+에어워킹,②마사지롤러+워밍숄더,③에어서핑+레그프레스 7
 
1.7%
①바디싯업+트위스트,②마사지롤러+워밍숄더③에어서핑+레그프레스 7
 
1.7%
①달리기+좌우파도타기②등허리지압기+허리돌리기③큰활차+역기올리기 7
 
1.7%
Other values (197) 322
76.1%
2024-01-10T07:11:16.657562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1136
 
8.6%
리 866
 
6.5%
+ 771
 
5.8%
, 631
 
4.8%
트 344
 
2.6%
허 331
 
2.5%
스 291
 
2.2%
① 261
 
2.0%
② 259
 
2.0%
이 244
 
1.8%
Other values (211) 8148
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10274
77.4%
Other Punctuation 823
 
6.2%
Math Symbol 771
 
5.8%
Other Number 736
 
5.5%
Uppercase Letter 288
 
2.2%
Decimal Number 257
 
1.9%
Dash Punctuation 51
 
0.4%
Open Punctuation 40
 
0.3%
Close Punctuation 40
 
0.3%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1136
 
11.1%
리 866
 
8.4%
트 344
 
3.3%
허 331
 
3.2%
스 291
 
2.8%
이 244
 
2.4%
레 226
 
2.2%
돌 214
 
2.1%
파 202
 
2.0%
타 197
 
1.9%
Other values (179) 6223
60.6%
Decimal Number
ValueCountFrequency (%)
2 79
30.7%
1 64
24.9%
3 47
18.3%
4 35
13.6%
5 17
 
6.6%
0 9
 
3.5%
6 4
 
1.6%
9 1
 
0.4%
8 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
M 71
24.7%
T 70
24.3%
B 43
14.9%
E 42
14.6%
L 26
 
9.0%
S 25
 
8.7%
R 5
 
1.7%
O 5
 
1.7%
A 1
 
0.3%
Other Number
ValueCountFrequency (%)
① 261
35.5%
② 259
35.2%
③ 186
25.3%
④ 29
 
3.9%
⑤ 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 631
76.7%
. 191
 
23.2%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
t 1
50.0%
Math Symbol
ValueCountFrequency (%)
+ 771
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10274
77.4%
Common 2718
 
20.5%
Latin 290
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1136
 
11.1%
리 866
 
8.4%
트 344
 
3.3%
허 331
 
3.2%
스 291
 
2.8%
이 244
 
2.4%
레 226
 
2.2%
돌 214
 
2.1%
파 202
 
2.0%
타 197
 
1.9%
Other values (179) 6223
60.6%
Common
ValueCountFrequency (%)
+ 771
28.4%
, 631
23.2%
① 261
 
9.6%
② 259
 
9.5%
. 191
 
7.0%
③ 186
 
6.8%
2 79
 
2.9%
1 64
 
2.4%
- 51
 
1.9%
3 47
 
1.7%
Other values (11) 178
 
6.5%
Latin
ValueCountFrequency (%)
M 71
24.5%
T 70
24.1%
B 43
14.8%
E 42
14.5%
L 26
 
9.0%
S 25
 
8.6%
R 5
 
1.7%
O 5
 
1.7%
A 1
 
0.3%
o 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10274
77.4%
ASCII 2272
 
17.1%
Enclosed Alphanum 736
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1136
 
11.1%
리 866
 
8.4%
트 344
 
3.3%
허 331
 
3.2%
스 291
 
2.8%
이 244
 
2.4%
레 226
 
2.2%
돌 214
 
2.1%
파 202
 
2.0%
타 197
 
1.9%
Other values (179) 6223
60.6%
ASCII
ValueCountFrequency (%)
+ 771
33.9%
, 631
27.8%
. 191
 
8.4%
2 79
 
3.5%
M 71
 
3.1%
T 70
 
3.1%
1 64
 
2.8%
- 51
 
2.2%
3 47
 
2.1%
B 43
 
1.9%
Other values (17) 254
 
11.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 261
35.5%
② 259
35.2%
③ 186
25.3%
④ 29
 
3.9%
⑤ 1
 
0.1%

행정구역
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
연무읍
50 
취암동
48 
연산면
33 
양촌면
33 
부창동
29 
Other values (10)
230 

Length

Max length4
Median length3
Mean length3.0591017
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연무읍 50
11.8%
취암동 48
11.3%
연산면 33
 
7.8%
양촌면 33
 
7.8%
부창동 29
 
6.9%
광석면 28
 
6.6%
성동면 27
 
6.4%
부적면 26
 
6.1%
노성면 25
 
5.9%
가야곡면 25
 
5.9%
Other values (5) 99
23.4%

Length

2024-01-10T07:11:16.763590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연무읍 50
11.8%
취암동 48
11.3%
연산면 33
 
7.8%
양촌면 33
 
7.8%
부창동 29
 
6.9%
광석면 28
 
6.6%
성동면 27
 
6.4%
부적면 26
 
6.1%
노성면 25
 
5.9%
가야곡면 25
 
5.9%
Other values (5) 99
23.4%

설치년월
Text

Distinct68
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T07:11:16.907541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9858156
Min length7

Characters and Unicode

Total characters4224
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)3.8%

Sample

1st row2006-12-01
2nd row2008-11-01
3rd row2012-01-01
4th row2012-08-01
5th row2012-08-01
ValueCountFrequency (%)
2012-08-01 34
 
8.0%
1905-07-01 31
 
7.3%
2012-12-01 28
 
6.6%
2014-03-01 26
 
6.1%
2011-05-01 20
 
4.7%
2011-09-01 18
 
4.3%
2013-04-01 18
 
4.3%
2014-04-01 18
 
4.3%
2013-03-01 14
 
3.3%
2015-06-01 12
 
2.8%
Other values (58) 204
48.2%
2024-01-10T07:11:17.161988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1246
29.5%
1 1000
23.7%
- 844
20.0%
2 536
12.7%
3 123
 
2.9%
4 111
 
2.6%
5 97
 
2.3%
9 92
 
2.2%
7 73
 
1.7%
6 53
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3380
80.0%
Dash Punctuation 844
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1246
36.9%
1 1000
29.6%
2 536
15.9%
3 123
 
3.6%
4 111
 
3.3%
5 97
 
2.9%
9 92
 
2.7%
7 73
 
2.2%
6 53
 
1.6%
8 49
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 844
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1246
29.5%
1 1000
23.7%
- 844
20.0%
2 536
12.7%
3 123
 
2.9%
4 111
 
2.6%
5 97
 
2.3%
9 92
 
2.2%
7 73
 
1.7%
6 53
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1246
29.5%
1 1000
23.7%
- 844
20.0%
2 536
12.7%
3 123
 
2.9%
4 111
 
2.6%
5 97
 
2.3%
9 92
 
2.2%
7 73
 
1.7%
6 53
 
1.3%

수량
Real number (ℝ)

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1347518
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T07:11:17.257243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q33
95-th percentile5
Maximum12
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2743544
Coefficient of variation (CV)0.40652481
Kurtosis11.371444
Mean3.1347518
Median Absolute Deviation (MAD)0
Skewness2.5481997
Sum1326
Variance1.623979
MonotonicityNot monotonic
2024-01-10T07:11:17.335746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 217
51.3%
2 99
23.4%
4 56
 
13.2%
5 24
 
5.7%
1 11
 
2.6%
6 8
 
1.9%
9 5
 
1.2%
7 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
1 11
 
2.6%
2 99
23.4%
3 217
51.3%
4 56
 
13.2%
5 24
 
5.7%
6 8
 
1.9%
7 1
 
0.2%
9 5
 
1.2%
10 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
10 1
 
0.2%
9 5
 
1.2%
7 1
 
0.2%
6 8
 
1.9%
5 24
 
5.7%
4 56
 
13.2%
3 217
51.3%
2 99
23.4%
1 11
 
2.6%

제조사
Text

MISSING 

Distinct56
Distinct (%)19.3%
Missing133
Missing (%)31.4%
Memory size3.4 KiB
2024-01-10T07:11:17.513057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.1068966
Min length2

Characters and Unicode

Total characters1771
Distinct characters108
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)7.9%

Sample

1st row대산체육산업
2nd rowING
3rd row비이텍
4th row비이텍
5th row그린나래
ValueCountFrequency (%)
ing 45
14.1%
㈜비이텍 42
 
13.2%
유)로드원씨엔씨 31
 
9.7%
아이앤지산업㈜ 19
 
6.0%
ing스포츠산업 18
 
5.6%
스포츠산업 13
 
4.1%
아이세상 12
 
3.8%
호진기계 11
 
3.4%
그린나래 11
 
3.4%
비이텍 10
 
3.1%
Other values (46) 107
33.5%
2024-01-10T07:11:17.818669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 108
 
6.1%
이 102
 
5.8%
산 81
 
4.6%
업 80
 
4.5%
씨 76
 
4.3%
I 65
 
3.7%
G 57
 
3.2%
N 56
 
3.2%
텍 54
 
3.0%
비 54
 
3.0%
Other values (98) 1038
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1252
70.7%
Uppercase Letter 216
 
12.2%
Other Symbol 108
 
6.1%
Lowercase Letter 80
 
4.5%
Open Punctuation 38
 
2.1%
Close Punctuation 38
 
2.1%
Space Separator 30
 
1.7%
Other Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 102
 
8.1%
산 81
 
6.5%
업 80
 
6.4%
씨 76
 
6.1%
텍 54
 
4.3%
비 54
 
4.3%
스 49
 
3.9%
포 45
 
3.6%
아 45
 
3.6%
드 43
 
3.4%
Other values (71) 623
49.8%
Uppercase Letter
ValueCountFrequency (%)
I 65
30.1%
G 57
26.4%
N 56
25.9%
E 10
 
4.6%
T 5
 
2.3%
B 5
 
2.3%
C 4
 
1.9%
J 4
 
1.9%
H 4
 
1.9%
V 1
 
0.5%
Other values (5) 5
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
n 29
36.2%
g 28
35.0%
i 20
25.0%
t 1
 
1.2%
h 1
 
1.2%
e 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 5
55.6%
. 4
44.4%
Other Symbol
ValueCountFrequency (%)
㈜ 108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1360
76.8%
Latin 296
 
16.7%
Common 115
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 108
 
7.9%
이 102
 
7.5%
산 81
 
6.0%
업 80
 
5.9%
씨 76
 
5.6%
텍 54
 
4.0%
비 54
 
4.0%
스 49
 
3.6%
포 45
 
3.3%
아 45
 
3.3%
Other values (72) 666
49.0%
Latin
ValueCountFrequency (%)
I 65
22.0%
G 57
19.3%
N 56
18.9%
n 29
9.8%
g 28
9.5%
i 20
 
6.8%
E 10
 
3.4%
T 5
 
1.7%
B 5
 
1.7%
C 4
 
1.4%
Other values (11) 17
 
5.7%
Common
ValueCountFrequency (%)
( 38
33.0%
) 38
33.0%
30
26.1%
, 5
 
4.3%
. 4
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1252
70.7%
ASCII 411
 
23.2%
None 108
 
6.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 108
100.0%
Hangul
ValueCountFrequency (%)
이 102
 
8.1%
산 81
 
6.5%
업 80
 
6.4%
씨 76
 
6.1%
텍 54
 
4.3%
비 54
 
4.3%
스 49
 
3.9%
포 45
 
3.6%
아 45
 
3.6%
드 43
 
3.4%
Other values (71) 623
49.8%
ASCII
ValueCountFrequency (%)
I 65
15.8%
G 57
13.9%
N 56
13.6%
( 38
9.2%
) 38
9.2%
30
7.3%
n 29
7.1%
g 28
6.8%
i 20
 
4.9%
E 10
 
2.4%
Other values (16) 40
9.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct395
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12054
Minimum126.99578
Maximum127.3158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T07:11:17.937401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.99578
5-th percentile127.01841
Q1127.08465
median127.10416
Q3127.14795
95-th percentile127.24459
Maximum127.3158
Range0.320017
Interquartile range (IQR)0.063302

Descriptive statistics

Standard deviation0.064392402
Coefficient of variation (CV)0.000506546
Kurtosis0.66932647
Mean127.12054
Median Absolute Deviation (MAD)0.028945
Skewness0.81079517
Sum53771.989
Variance0.0041463814
MonotonicityNot monotonic
2024-01-10T07:11:18.047181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.08335 3
 
0.7%
127.146447 3
 
0.7%
127.11472 3
 
0.7%
127.08892 3
 
0.7%
127.08979 3
 
0.7%
127.14731 2
 
0.5%
127.09529 2
 
0.5%
127.20466 2
 
0.5%
127.09977 2
 
0.5%
127.10033 2
 
0.5%
Other values (385) 398
94.1%
ValueCountFrequency (%)
126.99578 1
0.2%
126.996138 1
0.2%
126.99615 1
0.2%
127.002344 1
0.2%
127.00297 1
0.2%
127.00308 1
0.2%
127.00519 1
0.2%
127.0083 1
0.2%
127.01093 1
0.2%
127.01193 1
0.2%
ValueCountFrequency (%)
127.315797 1
0.2%
127.313538 2
0.5%
127.305882 1
0.2%
127.30494 1
0.2%
127.29709 1
0.2%
127.296563 1
0.2%
127.295032 1
0.2%
127.293998 1
0.2%
127.28933 2
0.5%
127.28717 1
0.2%

위도
Real number (ℝ)

Distinct396
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.192102
Minimum36.07604
Maximum36.333053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T07:11:18.154986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.07604
5-th percentile36.113825
Q136.159883
median36.19202
Q336.21589
95-th percentile36.293374
Maximum36.333053
Range0.257013
Interquartile range (IQR)0.056007

Descriptive statistics

Standard deviation0.051291265
Coefficient of variation (CV)0.001417195
Kurtosis0.051244702
Mean36.192102
Median Absolute Deviation (MAD)0.028276
Skewness0.34607258
Sum15309.259
Variance0.0026307939
MonotonicityNot monotonic
2024-01-10T07:11:18.262101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.18851 3
 
0.7%
36.175015 3
 
0.7%
36.151424 3
 
0.7%
36.148273 2
 
0.5%
36.13417 2
 
0.5%
36.13063 2
 
0.5%
36.272347 2
 
0.5%
36.12861 2
 
0.5%
36.20404 2
 
0.5%
36.12541 2
 
0.5%
Other values (386) 400
94.6%
ValueCountFrequency (%)
36.07604 1
0.2%
36.07734 1
0.2%
36.08299 1
0.2%
36.08553 1
0.2%
36.0859 1
0.2%
36.08928 1
0.2%
36.09095 1
0.2%
36.09206 1
0.2%
36.09212 1
0.2%
36.09436 1
0.2%
ValueCountFrequency (%)
36.333053 2
0.5%
36.32133 1
0.2%
36.320389 1
0.2%
36.317373 1
0.2%
36.31649 1
0.2%
36.315513 1
0.2%
36.314038 1
0.2%
36.310819 2
0.5%
36.308866 1
0.2%
36.30811 1
0.2%

Interactions

2024-01-10T07:11:15.805437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.396569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.600349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.868183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.462692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.669301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.939548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.533895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:11:15.738301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:11:18.350510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역설치년월수량제조사경도위도
행정구역1.0000.7520.2890.9450.8620.838
설치년월0.7521.0000.8210.9710.5020.178
수량0.2890.8211.0000.9190.0000.000
제조사0.9450.9710.9191.0000.7200.587
경도0.8620.5020.0000.7201.0000.581
위도0.8380.1780.0000.5870.5811.000
2024-01-10T07:11:18.453034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량경도위도행정구역
수량1.000-0.022-0.0320.120
경도-0.0221.0000.0460.537
위도-0.0320.0461.0000.499
행정구역0.1200.5370.4991.000

Missing values

2024-01-10T07:11:16.023110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:11:16.107164image/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

설치기구명행정구역설치년월수량제조사경도위도
0TM크로스컨트리,TM워밍암,TM트윈트위스트,TM레그프레스,TM롤링웨이스트,TM풀웨이트강경읍2006-12-016<NA>127.0160636.15104
1써핑롤링머신,트위스트머신,스윙워커머신,워킹트레이너머신,큰활차머신강경읍2008-11-015<NA>127.0119336.16453
2①달리기+좌우파도타기②등허리지압기+허리돌리기③계단밟기+자전거운동④큰활차+역기올리기④좌우파도타기+허리돌리기강경읍2012-01-015<NA>127.008336.1483
3①스트라이딩+런닝트레이닝,②레이스라이딩+밸리트레이닝,③웨스트터닝+바디터닝강경읍2012-08-013<NA>127.0128636.15949
4①L써클드로잉+S써클드로잉,②스트라이딩+런닝트레이닝,③웨스트터닝+바디터닝강경읍2012-08-013<NA>127.016636.16615
5①달리기+좌우파도타기,②등허리지압기+허리돌리기,③큰활차+역기올리기강경읍2012-08-013<NA>127.0194736.16387
6달리기+좌우파도타기,큰활차+역기올리기,등허리지압기+허리돌리기강경읍2013-04-013<NA>127.0183336.16489
7달리기+좌우파도타기,거꾸로매달리기,다리뻗치기강경읍2013-04-013<NA>127.0232536.1627
8거꾸로매달리기,큰활차+역기올리기강경읍2013-04-012<NA>127.0143336.16127
9달리기+좌우파도타기,큰활차+역기올리기,등허리지압기+허리돌리기강경읍2013-04-013<NA>127.0204636.16161
설치기구명행정구역설치년월수량제조사경도위도
413①큰활차+역기올리기②등허리지압기+허리돌리기부창동2014-12-012<NA>127.089136.19312
414①달리기운동,②두팔노젖기,③큰활차머신부창동2015-02-013ING127.0833536.2074
415①허리돌리(2015병촌품),자전거타기(2015병촌품)부창동2012-08-012ING127.0789436.19662
416자전거타기싱글부창동2015-12-011그린나래127.0894436.19202
417바디싯업+트위스트부창동2017-06-011비이텍127.0897936.19243
418파워사이클+트위스트,사이드스윙+사이드스윙부창동2017-03-012그린나래127.0889236.18851
419바디싯업+트위스트부창동2017-06-011비이텍127.0897936.19243
420파워싸이클+트위스트부창동2017-04-013그린나래127.0889236.18851
421싸이클링+오금펴기어꺠근육풀기+상체근육풀기부창동2018-06-012아이세상127.0805136.20714
422허리돌리기,옆파도타기,윗몸일으키기+오금펴기부창동2019-06-013아이세상127.0915936.21091

Duplicate rows

Most frequently occurring

설치기구명행정구역설치년월수량제조사경도위도# duplicates
0바디싯업+트위스트부창동2017-06-011비이텍127.0897936.192432