Overview

Dataset statistics

Number of variables19
Number of observations281
Missing cells187
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.9 KiB
Average record size in memory156.5 B

Variable types

Text5
Categorical10
Numeric4

Alerts

데이터기준일자 is highly overall correlated with 위도 and 9 other fieldsHigh correlation
주요포인트 is highly overall correlated with 위도 and 9 other fieldsHigh correlation
편익시설현황 is highly overall correlated with 낚시터유형 and 8 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 위도 and 10 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 9 other fieldsHigh correlation
안전시설현황 is highly overall correlated with 위도 and 7 other fieldsHigh correlation
위도 is highly overall correlated with 주요포인트 and 5 other fieldsHigh correlation
경도 is highly overall correlated with 주요포인트 and 4 other fieldsHigh correlation
낚시터유형 is highly overall correlated with 주요어종 and 5 other fieldsHigh correlation
주요어종 is highly overall correlated with 낚시터유형 and 7 other fieldsHigh correlation
수상시설물유형 is highly overall correlated with 주요포인트 and 3 other fieldsHigh correlation
주변관광지 is highly overall correlated with 위도 and 10 other fieldsHigh correlation
주변관광지 is highly imbalanced (58.6%)Imbalance
소재지도로명주소 has 60 (21.4%) missing valuesMissing
낚시터전화번호 has 127 (45.2%) missing valuesMissing

Reproduction

Analysis started2024-04-20 18:31:35.029635
Analysis finished2024-04-20 18:31:39.361117
Duration4.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

낚시터명
Text

Distinct278
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-21T03:31:39.555213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.1281139
Min length2

Characters and Unicode

Total characters1441
Distinct characters245
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)97.9%

Sample

1st row동교
2nd row밤밭
3rd row용담대물
4th row태산
5th row솟골
ValueCountFrequency (%)
낚시터 19
 
6.2%
초원 2
 
0.7%
문원낚시터 2
 
0.7%
동막낚시터 2
 
0.7%
도심 1
 
0.3%
용주골낚시터 1
 
0.3%
조암낚시터 1
 
0.3%
신촌낚시터 1
 
0.3%
성지골낚시터 1
 
0.3%
어천낚시터 1
 
0.3%
Other values (276) 276
89.9%
2024-04-21T03:31:39.903982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 198
 
13.7%
낚 197
 
13.7%
터 190
 
13.2%
26
 
1.8%
다 24
 
1.7%
바 23
 
1.6%
수 21
 
1.5%
산 21
 
1.5%
원 20
 
1.4%
내 20
 
1.4%
Other values (235) 701
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1391
96.5%
Space Separator 26
 
1.8%
Open Punctuation 8
 
0.6%
Close Punctuation 8
 
0.6%
Decimal Number 5
 
0.3%
Uppercase Letter 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 198
 
14.2%
낚 197
 
14.2%
터 190
 
13.7%
다 24
 
1.7%
바 23
 
1.7%
수 21
 
1.5%
산 21
 
1.5%
원 20
 
1.4%
내 20
 
1.4%
실 19
 
1.4%
Other values (226) 658
47.3%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
2 1
20.0%
1 1
20.0%
9 1
20.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1391
96.5%
Common 48
 
3.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 198
 
14.2%
낚 197
 
14.2%
터 190
 
13.7%
다 24
 
1.7%
바 23
 
1.7%
수 21
 
1.5%
산 21
 
1.5%
원 20
 
1.4%
내 20
 
1.4%
실 19
 
1.4%
Other values (226) 658
47.3%
Common
ValueCountFrequency (%)
26
54.2%
( 8
 
16.7%
) 8
 
16.7%
3 2
 
4.2%
- 1
 
2.1%
2 1
 
2.1%
1 1
 
2.1%
9 1
 
2.1%
Latin
ValueCountFrequency (%)
K 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1391
96.5%
ASCII 50
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 198
 
14.2%
낚 197
 
14.2%
터 190
 
13.7%
다 24
 
1.7%
바 23
 
1.7%
수 21
 
1.5%
산 21
 
1.5%
원 20
 
1.4%
내 20
 
1.4%
실 19
 
1.4%
Other values (226) 658
47.3%
ASCII
ValueCountFrequency (%)
26
52.0%
( 8
 
16.0%
) 8
 
16.0%
3 2
 
4.0%
K 2
 
4.0%
- 1
 
2.0%
2 1
 
2.0%
1 1
 
2.0%
9 1
 
2.0%

낚시터유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
저수지
159 
기타
62 
평지
49 
바다
 
11

Length

Max length3
Median length3
Mean length2.5658363
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
저수지 159
56.6%
기타 62
 
22.1%
평지 49
 
17.4%
바다 11
 
3.9%

Length

2024-04-21T03:31:40.015177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:31:40.101544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저수지 159
56.6%
기타 62
 
22.1%
평지 49
 
17.4%
바다 11
 
3.9%

소재지도로명주소
Text

MISSING 

Distinct215
Distinct (%)97.3%
Missing60
Missing (%)21.4%
Memory size2.3 KiB
2024-04-21T03:31:40.308038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length31
Mean length21.443439
Min length13

Characters and Unicode

Total characters4739
Distinct characters239
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

Unique209 ?
Unique (%)94.6%

Sample

1st row경기도 포천시 동교동 669-1
2nd row경기도 포천시 가산면 마전리 251-1
3rd row경기도 포천시 관인면 숯골길 237-1
4th row경기도 포천시 영북면 호국로3421번길 8
5th row경기도 남양주시 진건읍 사릉로620번길 44-31
ValueCountFrequency (%)
경기도 220
 
20.3%
화성시 34
 
3.1%
포천시 27
 
2.5%
시흥시 18
 
1.7%
파주시 14
 
1.3%
이천시 13
 
1.2%
남양주시 13
 
1.2%
안성시 12
 
1.1%
김포시 12
 
1.1%
양주시 11
 
1.0%
Other values (515) 712
65.6%
2024-04-21T03:31:40.637153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
865
 
18.3%
경 228
 
4.8%
시 228
 
4.8%
기 227
 
4.8%
도 225
 
4.7%
1 186
 
3.9%
2 135
 
2.8%
길 129
 
2.7%
로 124
 
2.6%
면 102
 
2.2%
Other values (229) 2290
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2839
59.9%
Decimal Number 925
 
19.5%
Space Separator 865
 
18.3%
Dash Punctuation 86
 
1.8%
Open Punctuation 8
 
0.2%
Close Punctuation 8
 
0.2%
Other Punctuation 5
 
0.1%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 228
 
8.0%
시 228
 
8.0%
기 227
 
8.0%
도 225
 
7.9%
길 129
 
4.5%
로 124
 
4.4%
면 102
 
3.6%
성 60
 
2.1%
번 56
 
2.0%
양 54
 
1.9%
Other values (213) 1406
49.5%
Decimal Number
ValueCountFrequency (%)
1 186
20.1%
2 135
14.6%
4 93
10.1%
5 86
9.3%
3 86
9.3%
0 73
 
7.9%
8 71
 
7.7%
7 69
 
7.5%
9 66
 
7.1%
6 60
 
6.5%
Space Separator
ValueCountFrequency (%)
865
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2839
59.9%
Common 1900
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 228
 
8.0%
시 228
 
8.0%
기 227
 
8.0%
도 225
 
7.9%
길 129
 
4.5%
로 124
 
4.4%
면 102
 
3.6%
성 60
 
2.1%
번 56
 
2.0%
양 54
 
1.9%
Other values (213) 1406
49.5%
Common
ValueCountFrequency (%)
865
45.5%
1 186
 
9.8%
2 135
 
7.1%
4 93
 
4.9%
5 86
 
4.5%
- 86
 
4.5%
3 86
 
4.5%
0 73
 
3.8%
8 71
 
3.7%
7 69
 
3.6%
Other values (6) 150
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2839
59.9%
ASCII 1900
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
865
45.5%
1 186
 
9.8%
2 135
 
7.1%
4 93
 
4.9%
5 86
 
4.5%
- 86
 
4.5%
3 86
 
4.5%
0 73
 
3.8%
8 71
 
3.7%
7 69
 
3.6%
Other values (6) 150
 
7.9%
Hangul
ValueCountFrequency (%)
경 228
 
8.0%
시 228
 
8.0%
기 227
 
8.0%
도 225
 
7.9%
길 129
 
4.5%
로 124
 
4.4%
면 102
 
3.6%
성 60
 
2.1%
번 56
 
2.0%
양 54
 
1.9%
Other values (213) 1406
49.5%

소재지지번주소
Text

Distinct275
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-21T03:31:40.913673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length21.466192
Min length14

Characters and Unicode

Total characters6032
Distinct characters210
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

Unique269 ?
Unique (%)95.7%

Sample

1st row경기도 포천시 동교동 669-1
2nd row경기도 포천시 가산면 마전리 251-1
3rd row경기도 포천시 관인면 사정리 380
4th row경기도 포천시 영북면 야미리 462
5th row경기도 남양주시 진건읍 신월리 228번지
ValueCountFrequency (%)
경기도 281
 
19.7%
화성시 34
 
2.4%
안성시 34
 
2.4%
포천시 27
 
1.9%
외 19
 
1.3%
양주시 19
 
1.3%
시흥시 18
 
1.3%
처인구 18
 
1.3%
용인시 18
 
1.3%
남양주시 16
 
1.1%
Other values (625) 940
66.0%
2024-04-21T03:31:41.285540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1143
18.9%
도 292
 
4.8%
기 285
 
4.7%
경 282
 
4.7%
시 278
 
4.6%
1 210
 
3.5%
리 205
 
3.4%
지 187
 
3.1%
- 156
 
2.6%
번 155
 
2.6%
Other values (200) 2839
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3718
61.6%
Space Separator 1143
 
18.9%
Decimal Number 1006
 
16.7%
Dash Punctuation 156
 
2.6%
Other Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 292
 
7.9%
기 285
 
7.7%
경 282
 
7.6%
시 278
 
7.5%
리 205
 
5.5%
지 187
 
5.0%
번 155
 
4.2%
면 145
 
3.9%
동 102
 
2.7%
성 83
 
2.2%
Other values (182) 1704
45.8%
Decimal Number
ValueCountFrequency (%)
1 210
20.9%
2 137
13.6%
3 114
11.3%
4 96
9.5%
5 91
9.0%
7 84
 
8.3%
6 71
 
7.1%
8 69
 
6.9%
9 69
 
6.9%
0 65
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
? 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3718
61.6%
Common 2313
38.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 292
 
7.9%
기 285
 
7.7%
경 282
 
7.6%
시 278
 
7.5%
리 205
 
5.5%
지 187
 
5.0%
번 155
 
4.2%
면 145
 
3.9%
동 102
 
2.7%
성 83
 
2.2%
Other values (182) 1704
45.8%
Common
ValueCountFrequency (%)
1143
49.4%
1 210
 
9.1%
- 156
 
6.7%
2 137
 
5.9%
3 114
 
4.9%
4 96
 
4.2%
5 91
 
3.9%
7 84
 
3.6%
6 71
 
3.1%
8 69
 
3.0%
Other values (7) 142
 
6.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3718
61.6%
ASCII 2314
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1143
49.4%
1 210
 
9.1%
- 156
 
6.7%
2 137
 
5.9%
3 114
 
4.9%
4 96
 
4.1%
5 91
 
3.9%
7 84
 
3.6%
6 71
 
3.1%
8 69
 
3.0%
Other values (8) 143
 
6.2%
Hangul
ValueCountFrequency (%)
도 292
 
7.9%
기 285
 
7.7%
경 282
 
7.6%
시 278
 
7.5%
리 205
 
5.5%
지 187
 
5.0%
번 155
 
4.2%
면 145
 
3.9%
동 102
 
2.7%
성 83
 
2.2%
Other values (182) 1704
45.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.439979
Minimum36.9542
Maximum38.172559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-21T03:31:41.442437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.9542
5-th percentile37.036038
Q137.15773
median37.367041
Q337.717765
95-th percentile37.974389
Maximum38.172559
Range1.218359
Interquartile range (IQR)0.56003485

Descriptive statistics

Standard deviation0.32176024
Coefficient of variation (CV)0.0085940283
Kurtosis-1.2062752
Mean37.439979
Median Absolute Deviation (MAD)0.272192
Skewness0.37467695
Sum10520.634
Variance0.10352965
MonotonicityNot monotonic
2024-04-21T03:31:41.590524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2315719 2
 
0.7%
37.28422966 2
 
0.7%
37.850261 1
 
0.4%
37.21465039 1
 
0.4%
37.17188889 1
 
0.4%
37.21157743 1
 
0.4%
37.19629691 1
 
0.4%
37.13297478 1
 
0.4%
37.12872541 1
 
0.4%
37.25528976 1
 
0.4%
Other values (269) 269
95.7%
ValueCountFrequency (%)
36.9542 1
0.4%
36.974239 1
0.4%
36.983539 1
0.4%
36.9898764 1
0.4%
36.9919814186 1
0.4%
36.996613 1
0.4%
37.008264 1
0.4%
37.009422 1
0.4%
37.016293 1
0.4%
37.018111 1
0.4%
ValueCountFrequency (%)
38.172559 1
0.4%
38.136567 1
0.4%
38.099837 1
0.4%
38.072347 1
0.4%
38.043659 1
0.4%
38.0431958641 1
0.4%
38.0370457766 1
0.4%
38.032232 1
0.4%
38.019182 1
0.4%
38.0151795909 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07961
Minimum126.53981
Maximum127.7268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-21T03:31:41.724845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53981
5-th percentile126.60557
Q1126.86347
median127.09608
Q3127.27702
95-th percentile127.52432
Maximum127.7268
Range1.1869982
Interquartile range (IQR)0.4135572

Descriptive statistics

Standard deviation0.27531878
Coefficient of variation (CV)0.0021665063
Kurtosis-0.7175
Mean127.07961
Median Absolute Deviation (MAD)0.203445
Skewness0.057765213
Sum35709.371
Variance0.075800431
MonotonicityNot monotonic
2024-04-21T03:31:41.878132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6055749 2
 
0.7%
126.9017887 2
 
0.7%
127.123091 1
 
0.4%
127.0417616 1
 
0.4%
126.8660989 1
 
0.4%
127.0086725 1
 
0.4%
126.9117052 1
 
0.4%
126.9457119 1
 
0.4%
126.8353876 1
 
0.4%
126.9144635 1
 
0.4%
Other values (269) 269
95.7%
ValueCountFrequency (%)
126.5398058 1
0.4%
126.5517462 1
0.4%
126.5530253 1
0.4%
126.5544602 1
0.4%
126.5578227 1
0.4%
126.5593612 1
0.4%
126.5633905 1
0.4%
126.5657961 1
0.4%
126.5714476 1
0.4%
126.5720971 1
0.4%
ValueCountFrequency (%)
127.726804 1
0.4%
127.710493 1
0.4%
127.6867879 1
0.4%
127.6736282 1
0.4%
127.6579298 1
0.4%
127.6511908 1
0.4%
127.6 1
0.4%
127.5955271366 1
0.4%
127.5742395 1
0.4%
127.5667369 1
0.4%

낚시터전화번호
Text

MISSING 

Distinct146
Distinct (%)94.8%
Missing127
Missing (%)45.2%
Memory size2.3 KiB
2024-04-21T03:31:42.101814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.012987
Min length11

Characters and Unicode

Total characters1850
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

Unique140 ?
Unique (%)90.9%

Sample

1st row031-574-6262
2nd row031-577-5327
3rd row031-794-8584
4th row031-426-3690
5th row031-883-9499
ValueCountFrequency (%)
031-000-0000 4
 
2.6%
031-675-0842 2
 
1.3%
031-845-4855 2
 
1.3%
000-0000-0000 2
 
1.3%
031-295-9949 2
 
1.3%
02-502-4269 2
 
1.3%
031-672-3481 1
 
0.6%
031-676-1707 1
 
0.6%
031-358-6346 1
 
0.6%
031-658-5006 1
 
0.6%
Other values (136) 136
88.3%
2024-04-21T03:31:42.591138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 308
16.6%
3 273
14.8%
0 270
14.6%
1 227
12.3%
6 134
7.2%
5 120
 
6.5%
7 119
 
6.4%
2 117
 
6.3%
8 107
 
5.8%
9 94
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1542
83.4%
Dash Punctuation 308
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 273
17.7%
0 270
17.5%
1 227
14.7%
6 134
8.7%
5 120
7.8%
7 119
7.7%
2 117
7.6%
8 107
 
6.9%
9 94
 
6.1%
4 81
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1850
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 308
16.6%
3 273
14.8%
0 270
14.6%
1 227
12.3%
6 134
7.2%
5 120
 
6.5%
7 119
 
6.4%
2 117
 
6.3%
8 107
 
5.8%
9 94
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 308
16.6%
3 273
14.8%
0 270
14.6%
1 227
12.3%
6 134
7.2%
5 120
 
6.5%
7 119
 
6.4%
2 117
 
6.3%
8 107
 
5.8%
9 94
 
5.1%

수면적
Real number (ℝ)

Distinct253
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53269.885
Minimum0.01
Maximum1440000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-21T03:31:42.712346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.9
Q1180
median3134
Q320000
95-th percentile347000
Maximum1440000
Range1440000
Interquartile range (IQR)19820

Descriptive statistics

Standard deviation167128.75
Coefficient of variation (CV)3.1373965
Kurtosis38.187113
Mean53269.885
Median Absolute Deviation (MAD)3131.43
Skewness5.6441991
Sum14968838
Variance2.7932019 × 1010
MonotonicityNot monotonic
2024-04-21T03:31:42.828715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000.0 5
 
1.8%
10000.0 3
 
1.1%
8000.0 3
 
1.1%
0.3 3
 
1.1%
14000.0 2
 
0.7%
2835.0 2
 
0.7%
84.0 2
 
0.7%
0.9 2
 
0.7%
3600.0 2
 
0.7%
0.6 2
 
0.7%
Other values (243) 255
90.7%
ValueCountFrequency (%)
0.01 1
 
0.4%
0.074 1
 
0.4%
0.2 1
 
0.4%
0.29 1
 
0.4%
0.3 3
1.1%
0.34 1
 
0.4%
0.4 2
0.7%
0.5 2
0.7%
0.6 2
0.7%
0.9 2
0.7%
ValueCountFrequency (%)
1440000.0 1
0.4%
1384000.0 1
0.4%
1170000.0 1
0.4%
699173.0 1
0.4%
526600.0 1
0.4%
483714.0 1
0.4%
481000.0 1
0.4%
452000.0 1
0.4%
422154.0 1
0.4%
407736.0 1
0.4%

주요어종
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
붕어+잉어
100 
붕어
58 
붕어,잉어
19 
붕어, 잉어
14 
붕어+잉어 등
14 
Other values (36)
76 

Length

Max length19
Median length14
Mean length5.0177936
Min length2

Unique

Unique25 ?
Unique (%)8.9%

Sample

1st row붕어+잉어
2nd row붕어+잉어
3rd row붕어+잉어
4th row붕어+잉어
5th row붕어, 잉어, 메기, 송어, 향어외

Common Values

ValueCountFrequency (%)
붕어+잉어 100
35.6%
붕어 58
20.6%
붕어,잉어 19
 
6.8%
붕어, 잉어 14
 
5.0%
붕어+잉어 등 14
 
5.0%
붕어+잉어+기타어류 8
 
2.8%
돔류 8
 
2.8%
붕어류 8
 
2.8%
우럭+참돔 7
 
2.5%
붕어+잉어+향어 6
 
2.1%
Other values (31) 39
 
13.9%

Length

2024-04-21T03:31:42.953077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
붕어+잉어 114
34.2%
붕어 79
23.7%
잉어 23
 
6.9%
붕어,잉어 19
 
5.7%
등 14
 
4.2%
붕어+잉어+기타어류 8
 
2.4%
돔류 8
 
2.4%
붕어류 8
 
2.4%
메기 8
 
2.4%
우럭+참돔 7
 
2.1%
Other values (25) 45
 
13.5%

최대수용인원
Real number (ℝ)

Distinct71
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.45196
Minimum10
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-21T03:31:43.061772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile20
Q150
median90
Q3130
95-th percentile640
Maximum2000
Range1990
Interquartile range (IQR)80

Descriptive statistics

Standard deviation249.93179
Coefficient of variation (CV)1.6394134
Kurtosis19.491232
Mean152.45196
Median Absolute Deviation (MAD)40
Skewness4.135397
Sum42839
Variance62465.899
MonotonicityNot monotonic
2024-04-21T03:31:43.181980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 44
15.7%
50 30
 
10.7%
80 22
 
7.8%
30 17
 
6.0%
200 14
 
5.0%
99 12
 
4.3%
150 11
 
3.9%
20 9
 
3.2%
40 8
 
2.8%
120 8
 
2.8%
Other values (61) 106
37.7%
ValueCountFrequency (%)
10 1
 
0.4%
13 1
 
0.4%
15 2
 
0.7%
16 1
 
0.4%
17 1
 
0.4%
18 2
 
0.7%
20 9
3.2%
23 2
 
0.7%
24 2
 
0.7%
26 1
 
0.4%
ValueCountFrequency (%)
2000 1
 
0.4%
1500 2
 
0.7%
1200 1
 
0.4%
1000 7
2.5%
950 1
 
0.4%
900 1
 
0.4%
763 1
 
0.4%
640 1
 
0.4%
600 1
 
0.4%
524 1
 
0.4%

수상시설물유형
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
고정형
118 
부유형
35 
없음
30 
잔교형좌대
18 
지상고정형
12 
Other values (32)
68 

Length

Max length25
Median length3
Mean length4.0604982
Min length2

Unique

Unique24 ?
Unique (%)8.5%

Sample

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

Common Values

ValueCountFrequency (%)
고정형 118
42.0%
부유형 35
 
12.5%
없음 30
 
10.7%
잔교형좌대 18
 
6.4%
지상고정형 12
 
4.3%
고정형+부유형 10
 
3.6%
좌대 8
 
2.8%
해당없음 6
 
2.1%
방갈로+좌대 6
 
2.1%
해가림막+좌대 5
 
1.8%
Other values (27) 33
 
11.7%

Length

2024-04-21T03:31:43.295736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고정형 118
38.3%
부유형 35
 
11.4%
없음 30
 
9.7%
잔교형좌대 20
 
6.5%
좌대 14
 
4.5%
지상고정형 12
 
3.9%
고정형+부유형 10
 
3.2%
방갈로+좌대 6
 
1.9%
수상방갈로 6
 
1.9%
해당없음 6
 
1.9%
Other values (32) 51
16.6%

이용요금
Text

Distinct71
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-21T03:31:43.498721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length50
Mean length8.6512456
Min length4

Characters and Unicode

Total characters2431
Distinct characters61
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

Unique36 ?
Unique (%)12.8%

Sample

1st row1일 30000원
2nd row1일 30000원
3rd row1일 30000원
4th row1일 30000원
5th row25,000
ValueCountFrequency (%)
1일 91
21.4%
30000원 44
 
10.4%
30000 22
 
5.2%
30,000원 19
 
4.5%
10000원 17
 
4.0%
20,000원 15
 
3.5%
25,000 13
 
3.1%
20000원 13
 
3.1%
60000원 11
 
2.6%
25000원 10
 
2.4%
Other values (72) 170
40.0%
2024-04-21T03:31:43.807393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1141
46.9%
원 197
 
8.1%
1 175
 
7.2%
145
 
6.0%
, 122
 
5.0%
일 112
 
4.6%
3 109
 
4.5%
2 92
 
3.8%
5 79
 
3.2%
) 33
 
1.4%
Other values (51) 226
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1655
68.1%
Other Letter 417
 
17.2%
Space Separator 145
 
6.0%
Other Punctuation 132
 
5.4%
Close Punctuation 33
 
1.4%
Open Punctuation 33
 
1.4%
Math Symbol 16
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 197
47.2%
일 112
26.9%
간 17
 
4.1%
시 17
 
4.1%
휴 9
 
2.2%
평 9
 
2.2%
터 4
 
1.0%
이 3
 
0.7%
인 3
 
0.7%
생 3
 
0.7%
Other values (34) 43
 
10.3%
Decimal Number
ValueCountFrequency (%)
0 1141
68.9%
1 175
 
10.6%
3 109
 
6.6%
2 92
 
5.6%
5 79
 
4.8%
6 24
 
1.5%
4 19
 
1.1%
7 7
 
0.4%
8 6
 
0.4%
9 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 122
92.4%
: 10
 
7.6%
Math Symbol
ValueCountFrequency (%)
+ 9
56.2%
~ 7
43.8%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2014
82.8%
Hangul 417
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 197
47.2%
일 112
26.9%
간 17
 
4.1%
시 17
 
4.1%
휴 9
 
2.2%
평 9
 
2.2%
터 4
 
1.0%
이 3
 
0.7%
인 3
 
0.7%
생 3
 
0.7%
Other values (34) 43
 
10.3%
Common
ValueCountFrequency (%)
0 1141
56.7%
1 175
 
8.7%
145
 
7.2%
, 122
 
6.1%
3 109
 
5.4%
2 92
 
4.6%
5 79
 
3.9%
) 33
 
1.6%
( 33
 
1.6%
6 24
 
1.2%
Other values (7) 61
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2014
82.8%
Hangul 417
 
17.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1141
56.7%
1 175
 
8.7%
145
 
7.2%
, 122
 
6.1%
3 109
 
5.4%
2 92
 
4.6%
5 79
 
3.9%
) 33
 
1.6%
( 33
 
1.6%
6 24
 
1.2%
Other values (7) 61
 
3.0%
Hangul
ValueCountFrequency (%)
원 197
47.2%
일 112
26.9%
간 17
 
4.1%
시 17
 
4.1%
휴 9
 
2.2%
평 9
 
2.2%
터 4
 
1.0%
이 3
 
0.7%
인 3
 
0.7%
생 3
 
0.7%
Other values (34) 43
 
10.3%

주요포인트
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
189 
낚시터 전체
34 
수초지대와 건너편
34 
-
19 
수초지대
 
2
Other values (2)
 
3

Length

Max length9
Median length4
Mean length4.6405694
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 189
67.3%
낚시터 전체 34
 
12.1%
수초지대와 건너편 34
 
12.1%
- 19
 
6.8%
수초지대 2
 
0.7%
해당없음 2
 
0.7%
상류쪽 1
 
0.4%

Length

2024-04-21T03:31:43.928790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:31:44.051455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 189
54.2%
낚시터 34
 
9.7%
전체 34
 
9.7%
수초지대와 34
 
9.7%
건너편 34
 
9.7%
19
 
5.4%
수초지대 2
 
0.6%
해당없음 2
 
0.6%
상류쪽 1
 
0.3%

안전시설현황
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
구명부환+소화기+구급약품+전기설비
54 
구명부환+소화기+구급약품
48 
구명부환+소화기+구급약품 등
34 
구명환, 구명조끼
27 
해당사항 없음
19 
Other values (14)
99 

Length

Max length23
Median length21
Mean length13.807829
Min length7

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row구명환, 구명조끼
2nd row구명환, 구명조끼
3rd row구명환, 구명조끼
4th row구명환, 구명조끼
5th row구명부환+소화기+구급약품

Common Values

ValueCountFrequency (%)
구명부환+소화기+구급약품+전기설비 54
19.2%
구명부환+소화기+구급약품 48
17.1%
구명부환+소화기+구급약품 등 34
12.1%
구명환, 구명조끼 27
9.6%
해당사항 없음 19
 
6.8%
구명부환+구명조끼+소화기 18
 
6.4%
소화기+구명부환 등 14
 
5.0%
구명부환+소화기+구급약품+방송설비 14
 
5.0%
구명부환, 구명조끼, 소화기, 구급약품 12
 
4.3%
소화기, 구명환, 약품 등 12
 
4.3%
Other values (9) 29
10.3%

Length

2024-04-21T03:31:44.192945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구명부환+소화기+구급약품 82
17.9%
등 62
13.5%
구명부환+소화기+구급약품+전기설비 54
11.8%
구명환 39
8.5%
구명조끼 39
8.5%
소화기 28
 
6.1%
없음 19
 
4.1%
해당사항 19
 
4.1%
구명부환+구명조끼+소화기 18
 
3.9%
구명부환 15
 
3.3%
Other values (13) 83
18.1%

편익시설현황
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
화장실+쓰레기통
90 
화장실, 쓰레기통
41 
관리소+화장실+쓰레기통
34 
화장실+분리수거통
27 
해당사항 없음
19 
Other values (8)
70 

Length

Max length17
Median length12
Mean length9.0640569
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row화장실, 쓰레기통
2nd row화장실, 쓰레기통
3rd row화장실, 쓰레기통
4th row화장실, 쓰레기통
5th row화장실+쓰레기통

Common Values

ValueCountFrequency (%)
화장실+쓰레기통 90
32.0%
화장실, 쓰레기통 41
14.6%
관리소+화장실+쓰레기통 34
 
12.1%
화장실+분리수거통 27
 
9.6%
해당사항 없음 19
 
6.8%
화장실+세면소+쓰레기통 14
 
5.0%
화장실+쓰레기통 등 14
 
5.0%
화장실+세면대 등 14
 
5.0%
화장실, 쓰레기통 등 12
 
4.3%
휴게실 9
 
3.2%
Other values (3) 7
 
2.5%

Length

2024-04-21T03:31:44.323234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화장실+쓰레기통 104
26.5%
화장실 55
14.0%
쓰레기통 53
13.5%
등 40
 
10.2%
관리소+화장실+쓰레기통 34
 
8.7%
화장실+분리수거통 27
 
6.9%
해당사항 19
 
4.8%
없음 19
 
4.8%
화장실+세면소+쓰레기통 14
 
3.6%
화장실+세면대 14
 
3.6%
Other values (3) 14
 
3.6%

주변관광지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct35
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
199 
-
 
19
서삼릉+서오릉+종마장+라페스타+원마운트
 
9
봉담호수공원
 
8
남양호(남양황라)
 
4
Other values (30)
42 

Length

Max length21
Median length4
Mean length4.8327402
Min length1

Unique

Unique22 ?
Unique (%)7.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
70.8%
- 19
 
6.8%
서삼릉+서오릉+종마장+라페스타+원마운트 9
 
3.2%
봉담호수공원 8
 
2.8%
남양호(남양황라) 4
 
1.4%
칠보산 제3전망대 4
 
1.4%
제부도 해안산책로 4
 
1.4%
비봉습지공원 2
 
0.7%
우리꽃식물원 2
 
0.7%
용문산 2
 
0.7%
Other values (25) 28
 
10.0%

Length

2024-04-21T03:31:44.428118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 199
67.2%
19
 
6.4%
서삼릉+서오릉+종마장+라페스타+원마운트 9
 
3.0%
봉담호수공원 8
 
2.7%
남양호(남양황라 4
 
1.4%
칠보산 4
 
1.4%
제3전망대 4
 
1.4%
제부도 4
 
1.4%
해안산책로 4
 
1.4%
용문산 3
 
1.0%
Other values (32) 38
 
12.8%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
66 
031-5189-3162
34 
031-678-2593
34 
031-538-3883
20 
031-310-2334
18 
Other values (14)
109 

Length

Max length13
Median length12
Mean length10.302491
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row031-538-3883
2nd row031-860-8932
3rd row031-538-3883
4th row031-538-3883
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 66
23.5%
031-5189-3162 34
12.1%
031-678-2593 34
12.1%
031-538-3883 20
 
7.1%
031-310-2334 18
 
6.4%
031-940-4917 14
 
5.0%
031-644-2339 14
 
5.0%
031-481-3953 14
 
5.0%
031-980-2822 12
 
4.3%
031-770-3639 12
 
4.3%
Other values (9) 43
15.3%

Length

2024-04-21T03:31:44.523288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 66
23.5%
031-5189-3162 34
12.1%
031-678-2593 34
12.1%
031-538-3883 20
 
7.1%
031-310-2334 18
 
6.4%
031-940-4917 14
 
5.0%
031-644-2339 14
 
5.0%
031-481-3953 14
 
5.0%
031-770-3639 12
 
4.3%
031-980-2822 12
 
4.3%
Other values (9) 43
15.3%

관리기관명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
경기도 안성시청
34 
경기도 화성시청
34 
경기도 용인시 처인구청
18 
경기도 시흥시청
18 
포천시
 
14
Other values (25)
163 

Length

Max length12
Median length8
Mean length7.6512456
Min length2

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row포천시
2nd row한국농어촌공사
3rd row포천시
4th row포천시
5th row경기도 남양주시 진건읍

Common Values

ValueCountFrequency (%)
경기도 안성시청 34
 
12.1%
경기도 화성시청 34
 
12.1%
경기도 용인시 처인구청 18
 
6.4%
경기도 시흥시청 18
 
6.4%
포천시 14
 
5.0%
한국농어촌공사 14
 
5.0%
개인 14
 
5.0%
경기도 안산시청 14
 
5.0%
이천시 농업기술센터 14
 
5.0%
경기도 파주시청 14
 
5.0%
Other values (20) 93
33.1%

Length

2024-04-21T03:31:44.613946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 196
36.5%
화성시청 34
 
6.3%
안성시청 34
 
6.3%
용인시 18
 
3.4%
처인구청 18
 
3.4%
시흥시청 18
 
3.4%
남양주시 16
 
3.0%
포천시 14
 
2.6%
한국농어촌공사 14
 
2.6%
개인 14
 
2.6%
Other values (25) 161
30.0%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-15
34 
2024-01-25
34 
2018-08-20
27 
2020-06-15
19 
2023-03-21
18 
Other values (18)
149 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row2018-08-20
2nd row2018-08-20
3rd row2018-08-20
4th row2018-08-20
5th row2020-01-23

Common Values

ValueCountFrequency (%)
2024-04-15 34
12.1%
2024-01-25 34
12.1%
2018-08-20 27
 
9.6%
2020-06-15 19
 
6.8%
2023-03-21 18
 
6.4%
2019-05-23 18
 
6.4%
2020-01-23 16
 
5.7%
2017-04-18 14
 
5.0%
2020-02-12 14
 
5.0%
2023-12-04 14
 
5.0%
Other values (13) 73
26.0%

Length

2024-04-21T03:31:44.703965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-04-15 34
12.1%
2024-01-25 34
12.1%
2018-08-20 27
 
9.6%
2020-06-15 19
 
6.8%
2023-03-21 18
 
6.4%
2019-05-23 18
 
6.4%
2020-01-23 16
 
5.7%
2017-04-18 14
 
5.0%
2020-02-12 14
 
5.0%
2023-12-04 14
 
5.0%
Other values (13) 73
26.0%

Interactions

2024-04-21T03:31:38.634034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:37.718007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.055418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.339062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.715173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:37.835526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.125293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.410641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.796321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:37.904535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.191516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.480990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.873093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:37.977740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.265549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:31:38.556844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:31:44.772420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
낚시터유형위도경도수면적주요어종최대수용인원수상시설물유형이용요금주요포인트안전시설현황편익시설현황주변관광지관리기관전화번호관리기관명데이터기준일자
낚시터유형1.0000.5030.6400.1300.9030.2090.5570.9100.6010.7270.7510.8680.8460.8730.851
위도0.5031.0000.6070.0990.8110.3090.8010.8170.8330.8710.7640.9320.9080.9430.910
경도0.6400.6071.0000.0000.8040.2660.7560.8350.8850.7990.7280.9780.8640.9160.880
수면적0.1300.0990.0001.0000.0000.1860.0000.7350.0000.0000.0000.8020.0000.0000.000
주요어종0.9030.8110.8040.0001.0000.0000.9130.9750.9250.9620.9610.9530.9510.9590.958
최대수용인원0.2090.3090.2660.1860.0001.0000.5750.0000.5890.5490.5630.0000.7790.5520.565
수상시설물유형0.5570.8010.7560.0000.9130.5751.0000.4700.8710.9120.9030.9820.9150.8690.915
이용요금0.9100.8170.8350.7350.9750.0000.4701.0000.8930.9430.9480.8790.9600.9630.971
주요포인트0.6010.8330.8850.0000.9250.5890.8710.8931.0001.0001.0001.0000.9950.9431.000
안전시설현황0.7270.8710.7990.0000.9620.5490.9120.9431.0001.0000.9921.0000.9910.9950.996
편익시설현황0.7510.7640.7280.0000.9610.5630.9030.9481.0000.9921.0001.0001.0000.9950.997
주변관광지0.8680.9320.9780.8020.9530.0000.9820.8791.0001.0001.0001.0000.9810.9651.000
관리기관전화번호0.8460.9080.8640.0000.9510.7790.9150.9600.9950.9911.0000.9811.0001.0001.000
관리기관명0.8730.9430.9160.0000.9590.5520.8690.9630.9430.9950.9950.9651.0001.0000.999
데이터기준일자0.8510.9100.8800.0000.9580.5650.9150.9711.0000.9960.9971.0001.0000.9991.000
2024-04-21T03:31:44.901311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자낚시터유형주요포인트주요어종편익시설현황관리기관전화번호관리기관명수상시설물유형주변관광지안전시설현황
데이터기준일자1.0000.6220.9940.5890.9580.9950.9710.4680.8050.950
낚시터유형0.6221.0000.4260.6550.5420.6260.6300.2980.5060.481
주요포인트0.9940.4261.0000.7440.9890.8870.8810.7140.8130.989
주요어종0.5890.6550.7441.0000.6920.6310.5530.3990.5960.634
편익시설현황0.9580.5420.9890.6921.0000.9880.9200.5300.8000.931
관리기관전화번호0.9950.6260.8870.6310.9881.0000.9680.5340.6890.920
관리기관명0.9710.6300.8810.5530.9200.9681.0000.3570.6450.916
수상시설물유형0.4680.2980.7140.3990.5300.5340.3571.0000.6170.485
주변관광지0.8050.5060.8130.5960.8000.6890.6450.6171.0000.800
안전시설현황0.9500.4810.9890.6340.9310.9200.9160.4850.8001.000
2024-04-21T03:31:45.020403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도수면적최대수용인원낚시터유형주요어종수상시설물유형주요포인트안전시설현황편익시설현황주변관광지관리기관전화번호관리기관명데이터기준일자
위도1.000-0.111-0.1850.0160.3210.4110.4080.6790.5550.4460.5690.6410.6220.630
경도-0.1111.0000.119-0.0650.4360.4030.3600.6680.4470.4070.6930.5520.5540.564
수면적-0.1850.1191.0000.1350.0890.0000.0000.0000.0000.0000.3990.0000.0000.000
최대수용인원0.016-0.0650.1351.0000.0940.0000.2490.3990.2610.2930.0000.4220.2410.258
낚시터유형0.3210.4360.0890.0941.0000.6550.2980.4260.4810.5420.5060.6260.6300.622
주요어종0.4110.4030.0000.0000.6551.0000.3990.7440.6340.6920.5960.6310.5530.589
수상시설물유형0.4080.3600.0000.2490.2980.3991.0000.7140.4850.5300.6170.5340.3570.468
주요포인트0.6790.6680.0000.3990.4260.7440.7141.0000.9890.9890.8130.8870.8810.994
안전시설현황0.5550.4470.0000.2610.4810.6340.4850.9891.0000.9310.8000.9200.9160.950
편익시설현황0.4460.4070.0000.2930.5420.6920.5300.9890.9311.0000.8000.9880.9200.958
주변관광지0.5690.6930.3990.0000.5060.5960.6170.8130.8000.8001.0000.6890.6450.805
관리기관전화번호0.6410.5520.0000.4220.6260.6310.5340.8870.9200.9880.6891.0000.9680.995
관리기관명0.6220.5540.0000.2410.6300.5530.3570.8810.9160.9200.6450.9681.0000.971
데이터기준일자0.6300.5640.0000.2580.6220.5890.4680.9940.9500.9580.8050.9950.9711.000

Missing values

2024-04-21T03:31:38.991887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:31:39.177503image/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.
2024-04-21T03:31:39.300566image/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

낚시터명낚시터유형소재지도로명주소소재지지번주소위도경도낚시터전화번호수면적주요어종최대수용인원수상시설물유형이용요금주요포인트안전시설현황편익시설현황주변관광지관리기관전화번호관리기관명데이터기준일자
0동교저수지경기도 포천시 동교동 669-1경기도 포천시 동교동 669-137.850261127.123091<NA>34000.0붕어+잉어100고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-538-3883포천시2018-08-20
1밤밭저수지경기도 포천시 가산면 마전리 251-1경기도 포천시 가산면 마전리 251-137.842701127.213272<NA>58000.0붕어+잉어100고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-860-8932한국농어촌공사2018-08-20
2용담대물저수지경기도 포천시 관인면 숯골길 237-1경기도 포천시 관인면 사정리 38038.136567127.260385<NA>20000.0붕어+잉어50고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-538-3883포천시2018-08-20
3태산저수지경기도 포천시 영북면 호국로3421번길 8경기도 포천시 영북면 야미리 46238.043659127.265118<NA>4400.0붕어+잉어30고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-538-3883포천시2018-08-20
4솟골저수지경기도 남양주시 진건읍 사릉로620번길 44-31경기도 남양주시 진건읍 신월리 228번지37.670972127.169896031-574-62627921.0붕어, 잉어, 메기, 송어, 향어외200고정형25,000<NA>구명부환+소화기+구급약품화장실+쓰레기통<NA><NA>경기도 남양주시 진건읍2020-01-23
5새말저수지경기도 남양주시 진건읍 사릉로 554-47경기도 남양주시 진건읍 신월리 44번지37.666461127.171404<NA>4925.0잉어, 붕어, 향어, 메기200고정형30,000<NA>구명부환+소화기+구급약품화장실+쓰레기통<NA><NA>경기도 남양주시 진건읍2020-01-23
6월문평지경기도 남양주시 와부읍 수레로661번안길 95경기도 남양주시 와부읍 월문리 96번지37.624745127.275995031-577-5327649.0붕어, 잉어100고정형20,000<NA>구명부환+소화기+구급약품화장실+쓰레기통<NA><NA>경기도 남양주시 와부읍2020-01-23
7무네미저수지경기도 포천시 군내면 유교로88번길 43경기도 포천시 군내면 유교리 75137.866909127.194815<NA>8000.0붕어+잉어50고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-538-3883포천시2018-08-20
8수목원기타경기도 포천시 소흘읍 직동리 80-4경기도 포천시 소흘읍 직동리 80-437.766181127.169065<NA>900.0붕어+잉어40고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-538-3883개인2018-08-20
9금주저수지경기도 포천시 영중면 금주리 231-3경기도 포천시 영중면 금주리 231-337.974389127.269187<NA>159000.0붕어+잉어100고정형1일 30000원<NA>구명환, 구명조끼화장실, 쓰레기통<NA>031-860-8932한국농어촌공사2018-08-20
낚시터명낚시터유형소재지도로명주소소재지지번주소위도경도낚시터전화번호수면적주요어종최대수용인원수상시설물유형이용요금주요포인트안전시설현황편익시설현황주변관광지관리기관전화번호관리기관명데이터기준일자
271동산저수지경기도 양주시 남면 감악산로514번길 54-20경기도 양주시 남면 신암리 99-4번지37.908294126.9654031-863-00020.2붕어,잉어300잔교형좌대10,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
272연곡낚시터저수지경기도 양주시 백석읍 연곡로182번길 100경기도 양주시 백석읍 연곡리 69-1번지37.817004126.959573031-879-53112.1붕어,잉어1000잔교형좌대,연안방갈로60,000-해당사항 없음해당사항 없음-031-8082-6132시유지2020-06-15
273은현피싱타운평지경기도 양주시 은현면 그루고개로490번길 49-27경기도 양주시 은현면 도하리 120-4번지37.851463127.015794031-863-89350.6붕어,잉어600잔교형좌대25,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
274삼하평지<NA>경기도 양주시 장흥면 삼하리 198-1,3,437.673308126.908806031-871-00470.5붕어,잉어300잔교형좌대20,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
275일영평지<NA>경기도 양주시 장흥면 일영리 572-437.70597126.931596031-855-55200.5붕어,잉어500잔교형좌대30,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
276광사평지경기도 양주시 부흥로 1864-40경기도 양주시 광사동 373-10번지37.788552127.07095031-847-05200.3붕어,잉어300잔교형좌대25,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
277장자원평지경기도 양주시 장흥면 일영로502번길 2-105경기도 양주시 장흥면 삼상리 455-1번지37.685744126.928522031-855-72440.4붕어,잉어900잔교형좌대15,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
278송추평지경기도 양주시 장흥면 호국로 586-24경기도 양주시 장흥면 울대리 426-1번지37.717765126.979217031-826-05290.3붕어,잉어500잔교형좌대10,000-해당사항 없음해당사항 없음-<NA>개인2020-06-15
279샘골 낚시터평지경기도 시흥시 신흥마을5길 32-21경기도 시흥시 신천동 617번지37.439688126.771803<NA>1792.0붕어+잉어100지상고정형1일 15000원<NA>구명부환+소화기+구급약품화장실+쓰레기통<NA>031-310-2334경기도 시흥시청2019-05-23
280도심 바다 낚시터기타경기도 시흥시 옥구상가2길 4경기도 시흥시 정왕동 1861-4번지 로얄타운 B02호37.353941126.723974<NA>60.72민어+가재23지상고정형1시간 (남)20000원+(여, 아동)15000원<NA>구명부환+소화기+구급약품화장실+쓰레기통<NA>031-310-2334경기도 시흥시청2019-05-23