Overview

Dataset statistics

Number of variables9
Number of observations51
Missing cells13
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory78.6 B

Variable types

Text4
Categorical2
Numeric3

Dataset

Description경기도 주요관광지 방문객 실태조사 조사지점 목록
Author경기관광공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=SYEU7FRWQTN698YA7IH232217139&infSeq=1

Alerts

정제우편번호 is highly overall correlated with 정제WGS84위도High correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 1 other fieldsHigh correlation
출구개수 is highly overall correlated with 정제WGS84위도High correlation
출구개수 is highly imbalanced (76.1%)Imbalance
정제도로명주소 has 8 (15.7%) missing valuesMissing
정제우편번호 has 1 (2.0%) missing valuesMissing
정제WGS84위도 has 2 (3.9%) missing valuesMissing
정제WGS84경도 has 2 (3.9%) missing valuesMissing
관광지명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:25:58.870467
Analysis finished2023-12-10 21:26:00.182989
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:26:00.327886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.9215686
Min length2

Characters and Unicode

Total characters353
Distinct characters168
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

Unique51 ?
Unique (%)100.0%

Sample

1st row재인폭포
2nd row한탄강관광지오토캠핑장
3rd row안산갈대습지공원
4th row의정부실내빙상장
5th row서울대공원
ValueCountFrequency (%)
재인폭포 1
 
1.9%
행주산성 1
 
1.9%
소요산관광지(자재암 1
 
1.9%
자라섬캠핑장 1
 
1.9%
남한강자전거길(양평구간 1
 
1.9%
에버랜드 1
 
1.9%
서울랜드 1
 
1.9%
캐리비안베이(워터파크 1
 
1.9%
아침고요원예수목원 1
 
1.9%
경기도립물향기수목원 1
 
1.9%
Other values (42) 42
80.8%
2023-12-11T06:26:00.630778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 13
 
3.7%
원 11
 
3.1%
관 9
 
2.5%
장 8
 
2.3%
한 7
 
2.0%
대 7
 
2.0%
지 6
 
1.7%
( 6
 
1.7%
리 6
 
1.7%
) 6
 
1.7%
Other values (158) 274
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
96.3%
Open Punctuation 6
 
1.7%
Close Punctuation 6
 
1.7%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 13
 
3.8%
원 11
 
3.2%
관 9
 
2.6%
장 8
 
2.4%
한 7
 
2.1%
대 7
 
2.1%
지 6
 
1.8%
리 6
 
1.8%
구 6
 
1.8%
수 6
 
1.8%
Other values (155) 261
76.8%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
96.3%
Common 13
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 13
 
3.8%
원 11
 
3.2%
관 9
 
2.6%
장 8
 
2.4%
한 7
 
2.1%
대 7
 
2.1%
지 6
 
1.8%
리 6
 
1.8%
구 6
 
1.8%
수 6
 
1.8%
Other values (155) 261
76.8%
Common
ValueCountFrequency (%)
( 6
46.2%
) 6
46.2%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
96.3%
ASCII 13
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 13
 
3.8%
원 11
 
3.2%
관 9
 
2.6%
장 8
 
2.4%
한 7
 
2.1%
대 7
 
2.1%
지 6
 
1.8%
리 6
 
1.8%
구 6
 
1.8%
수 6
 
1.8%
Other values (155) 261
76.8%
ASCII
ValueCountFrequency (%)
( 6
46.2%
) 6
46.2%
1
 
7.7%

조사위치
Text

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:26:00.780163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.5294118
Min length4

Characters and Unicode

Total characters384
Distinct characters105
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

Unique31 ?
Unique (%)60.8%

Sample

1st row스카이워크 앞 다리
2nd row캠핑장 내
3rd row주차장-환경생태관 사이 탐방로 입구
4th row건물 입구
5th row매표소 및 출입구 앞
ValueCountFrequency (%)
앞 30
24.8%
매표소 15
12.4%
출입구 14
11.6%
입구 8
 
6.6%
출구 6
 
5.0%
정문 4
 
3.3%
및 3
 
2.5%
주차장 3
 
2.5%
다리 2
 
1.7%
캠핑장 2
 
1.7%
Other values (32) 34
28.1%
2023-12-11T06:26:01.054536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
18.2%
앞 30
 
7.8%
구 29
 
7.6%
입 23
 
6.0%
출 20
 
5.2%
소 18
 
4.7%
매 17
 
4.4%
표 17
 
4.4%
장 8
 
2.1%
문 7
 
1.8%
Other values (95) 145
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
79.7%
Space Separator 70
 
18.2%
Decimal Number 4
 
1.0%
Dash Punctuation 2
 
0.5%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 30
 
9.8%
구 29
 
9.5%
입 23
 
7.5%
출 20
 
6.5%
소 18
 
5.9%
매 17
 
5.6%
표 17
 
5.6%
장 8
 
2.6%
문 7
 
2.3%
터 4
 
1.3%
Other values (88) 133
43.5%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
9 1
25.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
79.7%
Common 78
 
20.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 30
 
9.8%
구 29
 
9.5%
입 23
 
7.5%
출 20
 
6.5%
소 18
 
5.9%
매 17
 
5.6%
표 17
 
5.6%
장 8
 
2.6%
문 7
 
2.3%
터 4
 
1.3%
Other values (88) 133
43.5%
Common
ValueCountFrequency (%)
70
89.7%
- 2
 
2.6%
2 2
 
2.6%
1 1
 
1.3%
( 1
 
1.3%
9 1
 
1.3%
) 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
79.7%
ASCII 78
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
89.7%
- 2
 
2.6%
2 2
 
2.6%
1 1
 
1.3%
( 1
 
1.3%
9 1
 
1.3%
) 1
 
1.3%
Hangul
ValueCountFrequency (%)
앞 30
 
9.8%
구 29
 
9.5%
입 23
 
7.5%
출 20
 
6.5%
소 18
 
5.9%
매 17
 
5.6%
표 17
 
5.6%
장 8
 
2.6%
문 7
 
2.3%
터 4
 
1.3%
Other values (88) 133
43.5%

출구개수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
1
49 
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 49
96.1%
2 2
 
3.9%

Length

2023-12-11T06:26:01.154613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:26:01.223191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
96.1%
2 2
 
3.9%

계수방법
Categorical

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
입장권
33 
계수기
15 
예약
 
3

Length

Max length3
Median length3
Mean length2.9411765
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계수기
2nd row예약
3rd row예약
4th row입장권
5th row입장권

Common Values

ValueCountFrequency (%)
입장권 33
64.7%
계수기 15
29.4%
예약 3
 
5.9%

Length

2023-12-11T06:26:01.299348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:26:01.373241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입장권 33
64.7%
계수기 15
29.4%
예약 3
 
5.9%

정제도로명주소
Text

MISSING 

Distinct42
Distinct (%)97.7%
Missing8
Missing (%)15.7%
Memory size540.0 B
2023-12-11T06:26:01.594413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length19.744186
Min length14

Characters and Unicode

Total characters849
Distinct characters136
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

Unique41 ?
Unique (%)95.3%

Sample

1st row경기도 연천군 전곡읍 선사로 76
2nd row경기도 안산시 상록구 갈대습지로 76
3rd row경기도 의정부시 체육로 136
4th row경기도 과천시 대공원광장로 102
5th row경기도 포천시 신북면 청신로947번길 35
ValueCountFrequency (%)
경기도 43
 
21.0%
파주시 4
 
2.0%
가평군 4
 
2.0%
양평군 4
 
2.0%
용인시 4
 
2.0%
안산시 3
 
1.5%
과천시 3
 
1.5%
양서면 2
 
1.0%
광명로 2
 
1.0%
76 2
 
1.0%
Other values (119) 134
65.4%
2023-12-11T06:26:01.952412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
19.1%
기 46
 
5.4%
도 44
 
5.2%
경 43
 
5.1%
로 38
 
4.5%
시 35
 
4.1%
1 32
 
3.8%
2 19
 
2.2%
9 16
 
1.9%
구 15
 
1.8%
Other values (126) 399
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 539
63.5%
Space Separator 162
 
19.1%
Decimal Number 144
 
17.0%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 46
 
8.5%
도 44
 
8.2%
경 43
 
8.0%
로 38
 
7.1%
시 35
 
6.5%
구 15
 
2.8%
면 15
 
2.8%
길 12
 
2.2%
양 12
 
2.2%
평 11
 
2.0%
Other values (114) 268
49.7%
Decimal Number
ValueCountFrequency (%)
1 32
22.2%
2 19
13.2%
9 16
11.1%
0 13
9.0%
3 12
 
8.3%
6 12
 
8.3%
4 12
 
8.3%
8 10
 
6.9%
7 10
 
6.9%
5 8
 
5.6%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 539
63.5%
Common 310
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 46
 
8.5%
도 44
 
8.2%
경 43
 
8.0%
로 38
 
7.1%
시 35
 
6.5%
구 15
 
2.8%
면 15
 
2.8%
길 12
 
2.2%
양 12
 
2.2%
평 11
 
2.0%
Other values (114) 268
49.7%
Common
ValueCountFrequency (%)
162
52.3%
1 32
 
10.3%
2 19
 
6.1%
9 16
 
5.2%
0 13
 
4.2%
3 12
 
3.9%
6 12
 
3.9%
4 12
 
3.9%
8 10
 
3.2%
7 10
 
3.2%
Other values (2) 12
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 539
63.5%
ASCII 310
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
52.3%
1 32
 
10.3%
2 19
 
6.1%
9 16
 
5.2%
0 13
 
4.2%
3 12
 
3.9%
6 12
 
3.9%
4 12
 
3.9%
8 10
 
3.2%
7 10
 
3.2%
Other values (2) 12
 
3.9%
Hangul
ValueCountFrequency (%)
기 46
 
8.5%
도 44
 
8.2%
경 43
 
8.0%
로 38
 
7.1%
시 35
 
6.5%
구 15
 
2.8%
면 15
 
2.8%
길 12
 
2.2%
양 12
 
2.2%
평 11
 
2.0%
Other values (114) 268
49.7%

정제지번주소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:26:02.190629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length21.686275
Min length16

Characters and Unicode

Total characters1106
Distinct characters122
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

Unique49 ?
Unique (%)96.1%

Sample

1st row경기도 연천군 연천읍 고문리 산21
2nd row경기도 연천군 전곡읍 전곡리 696-3번지
3rd row경기도 안산시 상록구 사동 1031-8번지
4th row경기도 의정부시 녹양동 284-4번지 의정부실내빙상장
5th row경기도 과천시 막계동 159-1번지
ValueCountFrequency (%)
경기도 51
 
20.7%
양평군 5
 
2.0%
포천시 4
 
1.6%
가평군 4
 
1.6%
안산시 4
 
1.6%
파주시 4
 
1.6%
용인시 4
 
1.6%
과천시 3
 
1.2%
양서면 3
 
1.2%
막계동 3
 
1.2%
Other values (143) 161
65.4%
2023-12-11T06:26:02.521163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
195
 
17.6%
기 56
 
5.1%
도 52
 
4.7%
경 51
 
4.6%
지 42
 
3.8%
시 41
 
3.7%
번 41
 
3.7%
1 40
 
3.6%
- 33
 
3.0%
동 29
 
2.6%
Other values (112) 526
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 697
63.0%
Space Separator 195
 
17.6%
Decimal Number 181
 
16.4%
Dash Punctuation 33
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 56
 
8.0%
도 52
 
7.5%
경 51
 
7.3%
지 42
 
6.0%
시 41
 
5.9%
번 41
 
5.9%
동 29
 
4.2%
리 26
 
3.7%
산 21
 
3.0%
면 19
 
2.7%
Other values (100) 319
45.8%
Decimal Number
ValueCountFrequency (%)
1 40
22.1%
2 28
15.5%
3 19
10.5%
6 19
10.5%
4 16
 
8.8%
5 14
 
7.7%
9 13
 
7.2%
7 13
 
7.2%
0 11
 
6.1%
8 8
 
4.4%
Space Separator
ValueCountFrequency (%)
195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 697
63.0%
Common 409
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 56
 
8.0%
도 52
 
7.5%
경 51
 
7.3%
지 42
 
6.0%
시 41
 
5.9%
번 41
 
5.9%
동 29
 
4.2%
리 26
 
3.7%
산 21
 
3.0%
면 19
 
2.7%
Other values (100) 319
45.8%
Common
ValueCountFrequency (%)
195
47.7%
1 40
 
9.8%
- 33
 
8.1%
2 28
 
6.8%
3 19
 
4.6%
6 19
 
4.6%
4 16
 
3.9%
5 14
 
3.4%
9 13
 
3.2%
7 13
 
3.2%
Other values (2) 19
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 697
63.0%
ASCII 409
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
195
47.7%
1 40
 
9.8%
- 33
 
8.1%
2 28
 
6.8%
3 19
 
4.6%
6 19
 
4.6%
4 16
 
3.9%
5 14
 
3.4%
9 13
 
3.2%
7 13
 
3.2%
Other values (2) 19
 
4.6%
Hangul
ValueCountFrequency (%)
기 56
 
8.0%
도 52
 
7.5%
경 51
 
7.3%
지 42
 
6.0%
시 41
 
5.9%
번 41
 
5.9%
동 29
 
4.2%
리 26
 
3.7%
산 21
 
3.0%
면 19
 
2.7%
Other values (100) 319
45.8%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)88.0%
Missing1
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean13315.9
Minimum10118
Maximum18345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:26:02.639672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10118
5-th percentile10605.6
Q111181
median12584.5
Q315142.75
95-th percentile17340.65
Maximum18345
Range8227
Interquartile range (IQR)3961.75

Descriptive statistics

Standard deviation2318.7638
Coefficient of variation (CV)0.17413496
Kurtosis-0.72706389
Mean13315.9
Median Absolute Deviation (MAD)1476.5
Skewness0.65349966
Sum665795
Variance5376665.4
MonotonicityNot monotonic
2023-12-11T06:26:02.950537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
13829 3
 
5.9%
11108 2
 
3.9%
12585 2
 
3.9%
17023 2
 
3.9%
12448 2
 
3.9%
17072 1
 
2.0%
10808 1
 
2.0%
12510 1
 
2.0%
11307 1
 
2.0%
12421 1
 
2.0%
Other values (34) 34
66.7%
ValueCountFrequency (%)
10118 1
2.0%
10392 1
2.0%
10440 1
2.0%
10808 1
2.0%
10859 1
2.0%
10862 1
2.0%
10953 1
2.0%
11018 1
2.0%
11027 1
2.0%
11108 2
3.9%
ValueCountFrequency (%)
18345 1
2.0%
18118 1
2.0%
17558 1
2.0%
17075 1
2.0%
17072 1
2.0%
17023 2
3.9%
16255 1
2.0%
16016 1
2.0%
15639 1
2.0%
15637 1
2.0%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct48
Distinct (%)98.0%
Missing2
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean37.549326
Minimum36.992085
Maximum38.079729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:26:03.054010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.992085
5-th percentile37.227516
Q137.364142
median37.516276
Q337.758794
95-th percentile37.991697
Maximum38.079729
Range1.087644
Interquartile range (IQR)0.39465257

Descriptive statistics

Standard deviation0.25872808
Coefficient of variation (CV)0.0068903521
Kurtosis-0.62354079
Mean37.549326
Median Absolute Deviation (MAD)0.21132725
Skewness0.29886388
Sum1839.917
Variance0.066940219
MonotonicityNot monotonic
2023-12-11T06:26:03.175947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
37.2907221232 2
 
3.9%
37.8897176245 1
 
2.0%
37.946522172 1
 
2.0%
37.8209000098 1
 
2.0%
37.5501102802 1
 
2.0%
37.4365017609 1
 
2.0%
37.7439537969 1
 
2.0%
37.1662479454 1
 
2.0%
37.4309778122 1
 
2.0%
37.6638219135 1
 
2.0%
Other values (38) 38
74.5%
(Missing) 2
 
3.9%
ValueCountFrequency (%)
36.9920854519 1
2.0%
37.1662479454 1
2.0%
37.2081438332 1
2.0%
37.2565731109 1
2.0%
37.2667987372 1
2.0%
37.2737293219 1
2.0%
37.2804828957 1
2.0%
37.2825617121 1
2.0%
37.2907221232 2
3.9%
37.3049487881 1
2.0%
ValueCountFrequency (%)
38.0797294619 1
2.0%
38.0703073117 1
2.0%
38.0088794383 1
2.0%
37.9659224212 1
2.0%
37.946522172 1
2.0%
37.9234463151 1
2.0%
37.8897176245 1
2.0%
37.8209000098 1
2.0%
37.7880049977 1
2.0%
37.7730583466 1
2.0%

정제WGS84경도
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)98.0%
Missing2
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean127.07962
Minimum126.54764
Maximum127.62882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:26:03.287039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54764
5-th percentile126.68598
Q1126.92776
median127.06934
Q3127.21682
95-th percentile127.55782
Maximum127.62882
Range1.0811789
Interquartile range (IQR)0.28906654

Descriptive statistics

Standard deviation0.25849622
Coefficient of variation (CV)0.002034128
Kurtosis-0.21259018
Mean127.07962
Median Absolute Deviation (MAD)0.14748039
Skewness0.14905488
Sum6226.9015
Variance0.066820298
MonotonicityNot monotonic
2023-12-11T06:26:03.423395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
127.1967269237 2
 
3.9%
126.7417657057 1
 
2.0%
127.0693437436 1
 
2.0%
127.5210429935 1
 
2.0%
127.3196330231 1
 
2.0%
127.0240724311 1
 
2.0%
127.3525341486 1
 
2.0%
127.0543477507 1
 
2.0%
127.0199705127 1
 
2.0%
126.7556343424 1
 
2.0%
Other values (38) 38
74.5%
(Missing) 2
 
3.9%
ValueCountFrequency (%)
126.547640313 1
2.0%
126.6063858626 1
2.0%
126.6771018353 1
2.0%
126.699308966 1
2.0%
126.7126564851 1
2.0%
126.7417657057 1
2.0%
126.7556343424 1
2.0%
126.7812507272 1
2.0%
126.826474385 1
2.0%
126.8397560994 1
2.0%
ValueCountFrequency (%)
127.6288192417 1
2.0%
127.6113637923 1
2.0%
127.5823452407 1
2.0%
127.5210429935 1
2.0%
127.4902083222 1
2.0%
127.3525341486 1
2.0%
127.3335677739 1
2.0%
127.3239565831 1
2.0%
127.3196330231 1
2.0%
127.3156385962 1
2.0%

Interactions

2023-12-11T06:25:59.712135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.348505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.525755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.779853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.403330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.583291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.848000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.464257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:25:59.647760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:26:03.513320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지명조사위치출구개수계수방법정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
관광지명1.0001.0001.0001.0001.0001.0001.0001.0001.000
조사위치1.0001.0001.0000.9871.0001.0000.6570.8560.922
출구개수1.0001.0001.0000.0001.0001.0000.3280.8870.000
계수방법1.0000.9870.0001.0001.0001.0000.3230.0000.482
정제도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
정제지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
정제우편번호1.0000.6570.3280.3231.0001.0001.0000.8810.877
정제WGS84위도1.0000.8560.8870.0001.0001.0000.8811.0000.000
정제WGS84경도1.0000.9220.0000.4821.0001.0000.8770.0001.000
2023-12-11T06:26:03.602798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구개수계수방법
출구개수1.0000.000
계수방법0.0001.000
2023-12-11T06:26:03.666428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도출구개수계수방법
정제우편번호1.000-0.9060.0400.1890.197
정제WGS84위도-0.9061.0000.1300.6560.000
정제WGS84경도0.0400.1301.0000.0000.299
출구개수0.1890.6560.0001.0000.000
계수방법0.1970.0000.2990.0001.000

Missing values

2023-12-11T06:25:59.935759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:26:00.038971image/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.
2023-12-11T06:26:00.125658image/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

관광지명조사위치출구개수계수방법정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0재인폭포스카이워크 앞 다리1계수기<NA>경기도 연천군 연천읍 고문리 산211101838.070307127.128637
1한탄강관광지오토캠핑장캠핑장 내1예약경기도 연천군 전곡읍 선사로 76경기도 연천군 전곡읍 전곡리 696-3번지1102738.008879127.058864
2안산갈대습지공원주차장-환경생태관 사이 탐방로 입구1예약경기도 안산시 상록구 갈대습지로 76경기도 안산시 상록구 사동 1031-8번지1563537.273729126.839756
3의정부실내빙상장건물 입구1입장권경기도 의정부시 체육로 136경기도 의정부시 녹양동 284-4번지 의정부실내빙상장1160637.758794127.023843
4서울대공원매표소 및 출입구 앞1입장권경기도 과천시 대공원광장로 102경기도 과천시 막계동 159-1번지1382937.436443127.014103
5허브아일랜드매표소 앞1입장권경기도 포천시 신북면 청신로947번길 35경기도 포천시 신북면 삼정리 517-2번지1113737.965922127.131709
6한국민속촌매표소 출입구 앞1입장권경기도 용인시 기흥구 민속촌로 90경기도 용인시 기흥구 보라동 35번지1707537.256573127.117508
7안성팜랜드정문 메인매표소 앞2입장권경기도 안성시 공도읍 대신두길 28경기도 안성시 공도읍 신두리 451번지1755836.992085127.194422
8고성청소년수련원(쁘띠프랑스)후문 출구 앞1입장권경기도 가평군 청평면 호반로 1063경기도 가평군 청평면 고성리 616-2번지1245637.715194127.490208
9광명동굴광명동굴 입구1입장권경기도 광명시 가학로85번길 142경기도 광명시 가학동 27번지1434137.424668126.863444
관광지명조사위치출구개수계수방법정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
41헤이리예술마을화이트아트센터블럭 인근1입장권경기도 파주시 탄현면 헤이리마을길 70-21경기도 파주시 탄현면 법흥리 1652-239번지1085937.788005126.699309
42융건릉매표소 근처1입장권경기도 화성시 효행로481번길 21경기도 화성시 안녕동 187-1번지1834537.208144126.989222
43장릉매표소 앞1입장권경기도 김포시 장릉로 79경기도 김포시 풍무동 666-3번지1011837.610752126.712656
44통일전망대출입구 앞1입장권경기도 파주시 탄현면 필승로 369경기도 파주시 탄현면 성동리 659번지1086237.773026126.677102
45세미원매표소 출입구 앞1입장권경기도 양평군 양서면 양수로 93경기도 양평군 양서면 용담리 428-8번지1258437.540941127.323957
46수리산입구등산객 출입구 앞1계수기<NA>경기도 안산시 상록구 수암동 277-21520037.364142126.883157
47관악산자연학습장학습장 입구1계수기<NA>경기도 안양시 동안구 비산동 산42-11391537.414443126.958094
48잣향기푸른숲정문 매표소1입장권경기도 가평군 상면 축령로 289-146경기도 가평군 상면 행현리 산92-1번지1244837.769148127.333568
49두물머리두물머리나루터1계수기<NA>경기도 양평군 양서면 양수리 711-11258537.532735127.315639
50포천한탄강하늘다리다리 입구1계수기<NA>경기도 포천시 영북면 비둘기낭길 20711108<NA><NA>